Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

Science.gov (United States)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng

2016-05-10

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Partial wave analysis using graphics processing units

Energy Technology Data Exchange (ETDEWEB)

Berger, Niklaus; Liu Beijiang; Wang Jike, E-mail: nberger@ihep.ac.c [Institute of High Energy Physics, Chinese Academy of Sciences, 19B Yuquan Lu, Shijingshan, 100049 Beijing (China)

2010-04-01

Partial wave analysis is an important tool for determining resonance properties in hadron spectroscopy. For large data samples however, the un-binned likelihood fits employed are computationally very expensive. At the Beijing Spectrometer (BES) III experiment, an increase in statistics compared to earlier experiments of up to two orders of magnitude is expected. In order to allow for a timely analysis of these datasets, additional computing power with short turnover times has to be made available. It turns out that graphics processing units (GPUs) originally developed for 3D computer games have an architecture of massively parallel single instruction multiple data floating point units that is almost ideally suited for the algorithms employed in partial wave analysis. We have implemented a framework for tensor manipulation and partial wave fits called GPUPWA. The user writes a program in pure C++ whilst the GPUPWA classes handle computations on the GPU, memory transfers, caching and other technical details. In conjunction with a recent graphics processor, the framework provides a speed-up of the partial wave fit by more than two orders of magnitude compared to legacy FORTRAN code.

Sequential combination of k-t principle component analysis (PCA) and partial parallel imaging: k-t PCA GROWL.

Science.gov (United States)

Qi, Haikun; Huang, Feng; Zhou, Hongmei; Chen, Huijun

2017-03-01

k-t principle component analysis (k-t PCA) is a distinguished method for high spatiotemporal resolution dynamic MRI. To further improve the accuracy of k-t PCA, a combination with partial parallel imaging (PPI), k-t PCA/SENSE, has been tested. However, k-t PCA/SENSE suffers from long reconstruction time and limited improvement. This study aims to improve the combination of k-t PCA and PPI on both reconstruction speed and accuracy. A sequential combination scheme called k-t PCA GROWL (GRAPPA operator for wider readout line) was proposed. The GRAPPA operator was performed before k-t PCA to extend each readout line into a wider band, which improved the condition of the encoding matrix in the following k-t PCA reconstruction. k-t PCA GROWL was tested and compared with k-t PCA and k-t PCA/SENSE on cardiac imaging. k-t PCA GROWL consistently resulted in better image quality compared with k-t PCA/SENSE at high acceleration factors for both retrospectively and prospectively undersampled cardiac imaging, with a much lower computation cost. The improvement in image quality became greater with the increase of acceleration factor. By sequentially combining the GRAPPA operator and k-t PCA, the proposed k-t PCA GROWL method outperformed k-t PCA/SENSE in both reconstruction speed and accuracy, suggesting that k-t PCA GROWL is a better combination scheme than k-t PCA/SENSE. Magn Reson Med 77:1058-1067, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Improving the robustness of a partial least squares (PLS) model based on pure component selectivity analysis and range optimization: Case study for the analysis of an etching solution containing hydrogen peroxide

Energy Technology Data Exchange (ETDEWEB)

Lee, Youngbok [Department of Chemistry, College of Natural Sciences, Hanyang University Haengdang-Dong, Seoul 133-791 (Korea, Republic of); Chung, Hoeil [Department of Chemistry, College of Natural Sciences, Hanyang University Haengdang-Dong, Seoul 133-791 (Korea, Republic of)]. E-mail: hoeil@hanyang.ac.kr; Arnold, Mark A. [Optical Science and Technology Center and Department of Chemistry, University of Iowa, Iowa City, IA 52242 (United States)

2006-07-14

Pure component selectivity analysis (PCSA) was successfully utilized to enhance the robustness of a partial least squares (PLS) model by examining the selectivity of a given component to other components. The samples used in this study were composed of NH{sub 4}OH, H{sub 2}O{sub 2} and H{sub 2}O, a popular etchant solution in the electronic industry. Corresponding near-infrared (NIR) spectra (9000-7500 cm{sup -1}) were used to build PLS models. The selective determination of H{sub 2}O{sub 2} without influences from NH{sub 4}OH and H{sub 2}O was a key issue since its molecular structure is similar to that of H{sub 2}O and NH{sub 4}OH also has a hydroxyl functional group. The best spectral ranges for the determination of NH{sub 4}OH and H{sub 2}O{sub 2} were found with the use of moving window PLS (MW-PLS) and corresponding selectivity was examined by pure component selectivity analysis. The PLS calibration for NH{sub 4}OH was free from interferences from the other components due to the presence of its unique NH absorption bands. Since the spectral variation from H{sub 2}O{sub 2} was broadly overlapping and much less distinct than that from NH{sub 4}OH, the selectivity and prediction performance for the H{sub 2}O{sub 2} calibration were sensitively varied depending on the spectral ranges and number of factors used. PCSA, based on the comparison between regression vectors from PLS and the net analyte signal (NAS), was an effective method to prevent over-fitting of the H{sub 2}O{sub 2} calibration. A robust H{sub 2}O{sub 2} calibration model with minimal interferences from other components was developed. PCSA should be included as a standard method in PLS calibrations where prediction error only is the usual measure of performance.

Partial wave analysis of ι/η(1430) from DM2

International Nuclear Information System (INIS)

Augustin, J.E.; Cosme, G.; Couchot, F.; Fulda, F.; Grosdidier, G.; Jean-Marie, B.; Lepeltier, V.; Mane, M.; Szklarz, G.; Jousset, J.; Ajaltouni, Z.; Falvard, A.; Michel, B.; Montret, J.C.

1989-12-01

A Partial Wave Analysis of the ι/η (1430) region from the study of the radiative decays J/Ψ → γ K S 0 K ± π -+ and J/Ψ → γ K ± K -+ π 0 is presented. Pseudoscalar dominance appears clearly with two dynamical components. The main one which proceeds via δ/a 0 (980) π is centered at 1460 MeV/c 2 , while the second one with K*(892) K dynamics is peaked at a lower mass (1420 MeV/c 2 ) close to its kinematical threshold. In addition, the higher part of the mass spectrum contains a significant contribution from the 1 ++ K*(892)K wave

Load transfer characteristics of unilateral distal extension removable partial dentures with polyacetal resin supporting components.

Science.gov (United States)

Jiao, T; Chang, T; Caputo, A A

2009-03-01

To photoelastically examine load transfer by unilateral distal extension removable partial dentures with supporting and retentive components made of the lower stiffness polyacetal resins. A mandibular photoelastic model, with edentulous space distal to the right second premolar and missing the left first molar, was constructed to determine the load transmission characteristics of a unilateral distal extension base removable partial denture. Individual simulants were used for tooth structure, periodontal ligament, and alveolar bone. Three designs were fabricated: a major connector and clasps made from polyacetal resin, a metal framework as the major connector with polyacetal resin clasp and denture base, and a traditional metal framework I-bar removable partial denture. Simulated posterior bilateral and unilateral occlusal loads were applied to the removable partial dentures. Under bilateral and left side unilateral loading, the highest stress was observed adjacent to the left side posterior teeth with the polyacetal removable partial denture. The lowest stress was seen with the traditional metal framework. Unilateral loads on the right edentulous region produced similar distributed stress under the denture base with all three designs but a somewhat higher intensity with the polyacetal framework. The polyacetal resin removable partial denture concentrated the highest stresses to the abutment and the bone. The traditional metal framework I-bar removable partial denture most equitably distributed force. The hybrid design that combined a metal framework and polyacetal clasp and denture base may be a viable alternative when aesthetics are of primary concern.

On the structure of dynamic principal component analysis used in statistical process monitoring

DEFF Research Database (Denmark)

Vanhatalo, Erik; Kulahci, Murat; Bergquist, Bjarne

2017-01-01

When principal component analysis (PCA) is used for statistical process monitoring it relies on the assumption that data are time independent. However, industrial data will often exhibit serial correlation. Dynamic PCA (DPCA) has been suggested as a remedy for high-dimensional and time...... for determining the number of principal components to retain. The number of retained principal components is determined by visual inspection of the serial correlation in the squared prediction error statistic, Q (SPE), together with the cumulative explained variance of the model. The methods are illustrated using...... driven method to determine the maximum number of lags in DPCA with a foundation in multivariate time series analysis. The method is based on the behavior of the eigenvalues of the lagged autocorrelation and partial autocorrelation matrices. Given a specific lag structure we also propose a method...

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer

International Nuclear Information System (INIS)

Gu Haiwei; Pan Zhengzheng; Xi Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-01-01

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, 1 H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

Science.gov (United States)

Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-02-07

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

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

Clinical evaluation of failures in removable partial dentures.

Science.gov (United States)

Jorge, Janaina H; Quishida, Cristiane C C; Vergani, Carlos E; Machado, Ana L; Pavarina, Ana C; Giampaolo, Eunice T

2012-01-01

The aim of this clinical study was to evaluate the effects of removable partial dentures on the support tissues and changes occurring in lower tooth-supported and bilateral distal-extension dentures, 5 years after placement. The study involved analysis of a total of 53 patients who received prosthetic treatment for removable partial dentures. The patients were divided into two groups. In group 1, the patients had a completely edentulous maxilla and an edentulous area with natural teeth remaining in both the anterior and posterior regions. In group 2, the patients had a completely edentulous maxilla and partially edentulous mandible with preserved anterior teeth. Tooth mobility, prevalence of caries, fracture of the abutment teeth, fracture and/or deformation of the removable partial denture components and stability of the denture base were evaluated. The use of a removable partial denture increased tooth mobility, reduced the prevalence of caries, and did not cause loss or fracture of the abutments or damage to their components, when compared with the baseline. It was concluded that there was no difference between the groups as evaluated in terms of tooth mobility, prevalence of caries, loss and fracture of the abutments or damage to the components of the removable partial denture.

[Main Components of Xinjiang Lavender Essential Oil Determined by Partial Least Squares and Near Infrared Spectroscopy].

Science.gov (United States)

Liao, Xiang; Wang, Qing; Fu, Ji-hong; Tang, Jun

2015-09-01

This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum (NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100~4500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction (RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares (PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two

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...

The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

Science.gov (United States)

Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

2018-03-01

Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

ANOVA-principal component analysis and ANOVA-simultaneous component analysis: a comparison.

NARCIS (Netherlands)

Zwanenburg, G.; Hoefsloot, H.C.J.; Westerhuis, J.A.; Jansen, J.J.; Smilde, A.K.

2011-01-01

ANOVA-simultaneous component analysis (ASCA) is a recently developed tool to analyze multivariate data. In this paper, we enhance the explorative capability of ASCA by introducing a projection of the observations on the principal component subspace to visualize the variation among the measurements.

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...

Group-wise partial least square regression

NARCIS (Netherlands)

Camacho, José; Saccenti, Edoardo

2018-01-01

This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are

Theory and Design of Tunable and Reconfigurable Microwave Passive Components on Partially Magnetized Ferrite Substrate

KAUST Repository

Ghaffar, Farhan A.

2016-11-01

Typical microwave components such as antennas are large in size and occupy considerable space. Since multiple standards are utilized in modern day systems and thus multiple antennas are required, it is best if a single component can be reconfigured or tuned to various bands. Similarly phase shifters to provide beam scanning and polarization reconfigurable antennas are important for modern day congested wireless systems. Tunability of antennas or phase shifting between antenna elements has been demonstrated using various techniques which include magnetically tunable components on ferrite based substrates. Although this method has shown promising results it also has several issues due to the use of large external electromagnets and operation in the magnetically saturated state. These issues include the device being bulky, inefficient, non-integrable and expensive. In this thesis, we have tried to resolve the above mentioned issues of large size and large power requirement by replacing the large electromagnets with embedded bias windings and also by operating the ferrites in the partially magnetized state. New theoretical models and simulation methodology have been used to evaluate the performance of the microwave passive components in the partially magnetized state. A multilayer ferrite Low Temperature Cofired Ceramic (LTCC) tape system has been used to verify the performance experimentally. There exists a good agreement between the theoretical, simulation and measurement results. Tunable antennas with tuning range of almost 10 % and phase shifter with an FoM of 83.2/dB have been demonstrated in this work, however the major contribution is that this has been achieved with bias fields that are 90 % less than the typically reported values in the literature. Finally, polarization reconfigurability has also been demonstrated for a circular patch antenna using a low cost additive manufacturing technique. The results are promising and indicate that highly integrated

The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

Directory of Open Access Journals (Sweden)

Ying Peng

2018-03-01

Full Text Available Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

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...

Principal component regression analysis with SPSS.

Science.gov (United States)

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Reliability Analysis of Fatigue Failure of Cast Components for Wind Turbines

Directory of Open Access Journals (Sweden)

Hesam Mirzaei Rafsanjani

2015-04-01

Full Text Available Fatigue failure is one of the main failure modes for wind turbine drivetrain components made of cast iron. The wind turbine drivetrain consists of a variety of heavily loaded components, like the main shaft, the main bearings, the gearbox and the generator. The failure of each component will lead to substantial economic losses such as cost of lost energy production and cost of repairs. During the design lifetime, the drivetrain components are exposed to variable loads from winds and waves and other sources of loads that are uncertain and have to be modeled as stochastic variables. The types of loads are different for offshore and onshore wind turbines. Moreover, uncertainties about the fatigue strength play an important role in modeling and assessment of the reliability of the components. In this paper, a generic stochastic model for fatigue failure of cast iron components based on fatigue test data and a limit state equation for fatigue failure based on the SN-curve approach and Miner’s rule is presented. The statistical analysis of the fatigue data is performed using the Maximum Likelihood Method which also gives an estimate of the statistical uncertainties. Finally, illustrative examples are presented with reliability analyses depending on various stochastic models and partial safety factors.

Multiscale principal component analysis

International Nuclear Information System (INIS)

Akinduko, A A; Gorban, A N

2014-01-01

Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis

COMPARISON OF PARTIAL LEAST SQUARES REGRESSION METHOD ALGORITHMS: NIPALS AND PLS-KERNEL AND AN APPLICATION

Directory of Open Access Journals (Sweden)

ELİF BULUT

2013-06-01

Full Text Available Partial Least Squares Regression (PLSR is a multivariate statistical method that consists of partial least squares and multiple linear regression analysis. Explanatory variables, X, having multicollinearity are reduced to components which explain the great amount of covariance between explanatory and response variable. These components are few in number and they don’t have multicollinearity problem. Then multiple linear regression analysis is applied to those components to model the response variable Y. There are various PLSR algorithms. In this study NIPALS and PLS-Kernel algorithms will be studied and illustrated on a real data set.

Assessment of drinking water quality using principal component ...

African Journals Online (AJOL)

Assessment of drinking water quality using principal component analysis and partial least square discriminant analysis: a case study at water treatment plants, ... water and to detect the source of pollution for the most revealing parameters.

Influence of Growth Stage and Leaf Age on Expression of the Components of Partial Resistance of Faba Bean to Botrytis fabae Sard.

Directory of Open Access Journals (Sweden)

A. Bouhassan

2004-12-01

Full Text Available In detached leaf tests on faba bean (Vicia faba L., genotypes partially resistant and susceptible to Botrytis fabae were examined. Expression of four components of partial resistance to a virulent isolate of B. fabae differed depending on the plant age and the leaf age of the genotypes. The incubation period of resistant genotypes at the podding stage was longer than that of susceptible genotypes at the same stage. The area under disease progress curve (AUDPC of the lesion size increased from the seedling to the flowering stage but declined at the podding stage in all genotypes. Differences between resistant and susceptible genotypes for lesion size were significant except on old leaves from plants at the podding stage. The latent period decreased, and spore production increased with increasing growth and leaf age but there was significant interaction with the genotype. These last two components of partial resistance were more clearly expressed at all growth stages on FRY167 (highly resistant but were expressed only at the seedling and podding stages on FRY7 (resistant. The resistant line BPL710 was not significantly different from the susceptible genotypes for the latent period at any growth stage, and for spore production at the seedling and flowering stages. Leaf age affected all genotypes, but with a significant interaction between leaf age and growth stage. Components of partial resistance were more strongly expressed on young leaves from plants at the seedling or flowering stage.

Development of partial safety factors for the design of partially prestressed rectangular sections in biaxial flexure

International Nuclear Information System (INIS)

Chatterjee, Aritra; Bhattacharya, Baidurya; Agrawal, Gunjan; Mondal, Apurba

2011-01-01

Partial safety factors (PSFs) used in reliability-based design are intended to account for uncertainties in load, material and mathematical modeling while ensuring that the target reliability is satisfied for the relevant class of structural components in the given load combination and limit state. This paper describes the methodology in detail for developing a set of optimal reliability-based PSFs for the design of rectangular partially prestressed concrete sections subjected to biaxial flexure. The mechanical formulation of the flexural limit state is based on the principle behind prestressed concrete design recommended by IS 1343 and SP16 and failure is defined as tensile cracking of concrete extending beyond the depth of cover. The applied moments are combined according to Wood's criteria. The optimization of the PSFs is based on reliability indices obtained from first order reliability analysis of the structural components; Monte Carlo simulations are performed in each run to determine the capacity statistics and dependence between capacity and applied loads (effected through the axial loads influencing moment capacity corresponding to cracking). Numerical examples involving flexural design of partially prestressed concrete shell elements in nuclear power plant containments under accidental pressure load combination are provided. (author)

SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test.

Science.gov (United States)

O'Connor, B P

2000-08-01

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

Multiview Bayesian Correlated Component Analysis

DEFF Research Database (Denmark)

Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai

2015-01-01

are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....

SLAC three-body partial wave analysis system

International Nuclear Information System (INIS)

Aston, D.; Lasinski, T.A.; Sinervo, P.K.

1985-10-01

We present a heuristic description of the SLAC-LBL three-meson partial wave model, and describe how we have implemented it at SLAC. The discussion details the assumptions of the model and the analysis, and emphasizes the methods we have used to prepare and fit the data. 28 refs., 12 figs., 1 tab

Implications of the effective one-component analysis of pair correlations in colloidal fluids with polydispersity

Science.gov (United States)

Pond, Mark J.; Errington, Jeffrey R.; Truskett, Thomas M.

2011-09-01

Partial pair-correlation functions of colloidal suspensions with continuous polydispersity can be challenging to characterize from optical microscopy or computer simulation data due to inadequate sampling. As a result, it is common to adopt an effective one-component description of the structure that ignores the differences between particle types. Unfortunately, whether this kind of simplified description preserves or averages out information important for understanding the behavior of the fluid depends on the degree of polydispersity and can be difficult to assess, especially when the corresponding multicomponent description of the pair correlations is unavailable for comparison. Here, we present a computer simulation study that examines the implications of adopting an effective one-component structural description of a polydisperse fluid. The square-well model that we investigate mimics key aspects of the experimental behavior of suspended colloids with short-range, polymer-mediated attractions. To characterize the partial pair-correlation functions and thermodynamic excess entropy of this system, we introduce a Monte Carlo sampling strategy appropriate for fluids with a large number of pseudo-components. The data from our simulations at high particle concentrations, as well as exact theoretical results for dilute systems, show how qualitatively different trends between structural order and particle attractions emerge from the multicomponent and effective one-component treatments, even with systems characterized by moderate polydispersity. We examine consequences of these differences for excess-entropy based scalings of shear viscosity, and we discuss how use of the multicomponent treatment reveals similarities between the corresponding dynamic scaling behaviors of attractive colloids and liquid water that the effective one-component analysis does not capture.

Recommended practice for process sampling for partial pressure analysis

International Nuclear Information System (INIS)

Blessing, James E.; Ellefson, Robert E.; Raby, Bruce A.; Brucker, Gerardo A.; Waits, Robert K.

2007-01-01

This Recommended Practice describes and recommends various procedures and types of apparatus for obtaining representative samples of process gases from >10 -2 Pa (10 -4 Torr) for partial pressure analysis using a mass spectrometer. The document was prepared by a subcommittee of the Recommended Practices Committee of the American Vacuum Society. The subcommittee was comprised of vacuum users and manufacturers of mass spectrometer partial pressure analyzers who have practical experience in the sampling of process gas atmospheres

Three-dimensional finite element analysis of implant-assisted removable partial dentures.

Science.gov (United States)

Eom, Ju-Won; Lim, Young-Jun; Kim, Myung-Joo; Kwon, Ho-Beom

2017-06-01

Whether the implant abutment in implant-assisted removable partial dentures (IARPDs) functions as a natural removable partial denture (RPD) tooth abutment is unknown. The purpose of this 3-dimensional finite element study was to analyze the biomechanical behavior of implant crown, bone, RPD, and IARPD. Finite element models of the partial maxilla, teeth, and prostheses were generated on the basis of a patient's computed tomographic data. The teeth, surveyed crowns, and RPDs were created in the model. With the generated components, four 3-dimensional finite element models of the partial maxilla were constructed: tooth-supported RPD (TB), implant-supported RPD (IB), tooth-tissue-supported RPD (TT), and implant-tissue-supported RPD (IT) models. Oblique loading of 300 N was applied on the crowns and denture teeth. The von Mises stress and displacement of the denture abutment tooth and implant system were identified. The highest von Mises stress values of both IARPDs occurred on the implants, while those of both natural tooth RPDs occurred on the frameworks of the RPDs. The highest von Mises stress of model IT was about twice that of model IB, while the value of model TT was similar to that of model TB. The maximum displacement was greater in models TB and TT than in models IB and IT. Among the 4 models, the highest maximum displacement value was observed in the model TT and the lowest value was in the model IB. Finite element analysis revealed that the stress distribution pattern of the IARPDs was different from that of the natural tooth RPDs and the stress distribution of implant-supported RPD was different from that of implant-tissue-supported RPD. When implants are used for RPD abutments, more consideration concerning the RPD design and the number or location of the implant is necessary. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Nonlinear analysis of shear deformable beam-columns partially ...

African Journals Online (AJOL)

In this paper, a boundary element method is developed for the nonlinear analysis of shear deformable beam-columns of arbitrary doubly symmetric simply or multiply connected constant cross section, partially supported on tensionless Winkler foundation, undergoing moderate large deflections under general boundary ...

Partial wave analysis of DM2 data in the η(1430) energy range

International Nuclear Information System (INIS)

Augustin, J.E.; Cosme, G.; Couchot, F.; Fulda, F.; Grosdidier, G.; Jean-Marie, B.; Lepeltier, V.; Szklarz, G.; Bisello, D.; Busetto, G.; Castro, A.; Pescara, L.; Sartori, P.; Stanco, L.; Ajaltouni, Z.; Falvard, A.; Jousset, J.; Michel, B.; Montret, J.C.

1990-10-01

Partial Wave Analysis of the J/ψ → γK S 0 K ± π -+ , γK ± K -+ π 0 decays in the ι/η(1430) mass range shows a clear pseudoscalar dominance, with two dynamical components. The main one, centered at ∼ 1460 MeV/c 2 , proceeds via a 0 (980)π dynamics, while the second one with K*(892)K dynamics is peaked at ∼ 1420 MeV/c 2 , close to its threshold. In addition, the higher part of the mass spectrum contains a significant contribution from the 1 ++ K*(892)K wave. In the PWA of the J/ψ → γηπ + π - channel a resonant a 0 π production is observed slightly below 1400 MeV/c 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

Model reduction by weighted Component Cost Analysis

Science.gov (United States)

Kim, Jae H.; Skelton, Robert E.

1990-01-01

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Ultrasonic partial discharge monitoring method on instrument transformers

Directory of Open Access Journals (Sweden)

Kartalović Nenad

2012-01-01

Full Text Available Sonic and ultrasonic partial discharge monitoring have been applied since the early days of these phenomena monitoring. Modern measurement and partial discharge acoustic (ultrasonic and sonic monitoring method has been rapidly evolving as a result of new electronic component design, information technology and updated software solutions as well as the development of knowledge in the partial discharge diagnosis. Electrical discharges in the insulation system generate voltage-current pulses in the network and ultrasonic waves that propagate through the insulation system and structure. Amplitude-phase-frequency analysis of these signals reveals information about the intensity, type and location of partial discharges. The paper discusses the possibility of ultrasonic method selectivity improvement and the increase of diagnosis reliability in the field. Measurements were performed in the laboratory and in the field while a number of transformers were analysed for dissolved gases in the oil. A comparative review of methods for the partial discharge detection is also presented in this paper.

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

COPD phenotype description using principal components analysis

DEFF Research Database (Denmark)

Roy, Kay; Smith, Jacky; Kolsum, Umme

2009-01-01

BACKGROUND: Airway inflammation in COPD can be measured using biomarkers such as induced sputum and Fe(NO). This study set out to explore the heterogeneity of COPD using biomarkers of airway and systemic inflammation and pulmonary function by principal components analysis (PCA). SUBJECTS...... AND METHODS: In 127 COPD patients (mean FEV1 61%), pulmonary function, Fe(NO), plasma CRP and TNF-alpha, sputum differential cell counts and sputum IL8 (pg/ml) were measured. Principal components analysis as well as multivariate analysis was performed. RESULTS: PCA identified four main components (% variance...... associations between the variables within components 1 and 2. CONCLUSION: COPD is a multi dimensional disease. Unrelated components of disease were identified, including neutrophilic airway inflammation which was associated with systemic inflammation, and sputum eosinophils which were related to increased Fe...

Component evaluation testing and analysis algorithms.

Energy Technology Data Exchange (ETDEWEB)

Hart, Darren M.; Merchant, Bion John

2011-10-01

The Ground-Based Monitoring R&E Component Evaluation project performs testing on the hardware components that make up Seismic and Infrasound monitoring systems. The majority of the testing is focused on the Digital Waveform Recorder (DWR), Seismic Sensor, and Infrasound Sensor. In order to guarantee consistency, traceability, and visibility into the results of the testing process, it is necessary to document the test and analysis procedures that are in place. Other reports document the testing procedures that are in place (Kromer, 2007). This document serves to provide a comprehensive overview of the analysis and the algorithms that are applied to the Component Evaluation testing. A brief summary of each test is included to provide the context for the analysis that is to be performed.

Does friendship give us non-derivative partial reasons ?

Directory of Open Access Journals (Sweden)

Andrew Reisner

2008-02-01

Full Text Available One way to approach the question of whether there are non-derivative partial reasons of any kind is to give an account of what partial reasons are, and then to consider whether there are such reasons. If there are, then it is at least possible that there are partial reasons of friendship. It is this approach that will be taken here, and it produces several interesting results. The first is a point about the structure of partial reasons. It is at least a necessary condition of a reason’s being partial that it has an explicit relational component. This component, technically, is a relatum in the reason relation that itself is a relation between the person to whom the reason applies and the person whom the action for which there is a reason concerns. The second conclusion of the paper is that this relational component is also required for a number of types of putatively impartial reasons. In order to avoid trivialising the distinction between partial and impartial reasons, some further sufficient condition must be applied. Finally, there is some prospect for a way of distinguishing between impartial reasons that contain a relational component and partial reasons, but that this approach suggests that the question of whether ethics is partial or impartial will be settled at the level of normative ethical discourse, or at least not at the level of discourse about the nature of reasons for action.

Radiation inactivation analysis of assimilatory NADH:nitrate reductase. Apparent functional sizes of partial activities associated with intact and proteolytically modified enzyme

International Nuclear Information System (INIS)

Solomonson, L.P.; McCreery, M.J.; Kay, C.J.; Barber, M.J.

1987-01-01

Recently we demonstrated that target sizes for the partial activities of nitrate reductase were considerably smaller than the 100-kDa subunit which corresponded to the target size of the full (physiologic) activity NADH:nitrate reductase. These results suggested that the partial activities resided on functionally independent domains and that radiation inactivation may be due to localized rather than extensive damage to protein structure. The present study extends these observations and addresses several associated questions. Monophasic plots were observed over a wide range of radiation doses, suggesting a single activity component in each case. No apparent differences were observed over a 10-fold range of concentration for each substrate, suggesting that the observed slopes were not due to marked changes in Km values. Apparent target sizes estimated for partial activities associated with native enzyme and with limited proteolysis products of native enzyme suggested that the functional size obtained by radiation inactivation analysis is independent of the size of the polypeptide chain. The presence of free radical scavengers during irradiation reduced the apparent target size of both the physiologic and partial activities by an amount ranging from 24 to 43%, suggesting that a free radical mechanism is at least partially responsible for the inactivation. Immunoblot analysis of nitrate reductase irradiated in the presence of free radical scavengers revealed formation of distinct bands at 90, 75, and 40 kDa with increasing doses of irradiation rather than complete destruction of the polypeptide chain

Exploiting partial knowledge for efficient model analysis

OpenAIRE

Macedo, Nuno; Cunha, Alcino; Pessoa, Eduardo José Dias

2017-01-01

The advancement of constraint solvers and model checkers has enabled the effective analysis of high-level formal specification languages. However, these typically handle a specification in an opaque manner, amalgamating all its constraints in a single monolithic verification task, which often proves to be a performance bottleneck. This paper addresses this issue by proposing a solving strategy that exploits user-provided partial knowledge, namely by assigning symbolic bounds to the problem’s ...

Improvement of Binary Analysis Components in Automated Malware Analysis Framework

Science.gov (United States)

2017-02-21

AFRL-AFOSR-JP-TR-2017-0018 Improvement of Binary Analysis Components in Automated Malware Analysis Framework Keiji Takeda KEIO UNIVERSITY Final...TYPE Final 3. DATES COVERED (From - To) 26 May 2015 to 25 Nov 2016 4. TITLE AND SUBTITLE Improvement of Binary Analysis Components in Automated Malware ...analyze malicious software ( malware ) with minimum human interaction. The system autonomously analyze malware samples by analyzing malware binary program

Boundary layer noise subtraction in hydrodynamic tunnel using robust principal component analysis.

Science.gov (United States)

Amailland, Sylvain; Thomas, Jean-Hugh; Pézerat, Charles; Boucheron, Romuald

2018-04-01

The acoustic study of propellers in a hydrodynamic tunnel is of paramount importance during the design process, but can involve significant difficulties due to the boundary layer noise (BLN). Indeed, advanced denoising methods are needed to recover the acoustic signal in case of poor signal-to-noise ratio. The technique proposed in this paper is based on the decomposition of the wall-pressure cross-spectral matrix (CSM) by taking advantage of both the low-rank property of the acoustic CSM and the sparse property of the BLN CSM. Thus, the algorithm belongs to the class of robust principal component analysis (RPCA), which derives from the widely used principal component analysis. If the BLN is spatially decorrelated, the proposed RPCA algorithm can blindly recover the acoustical signals even for negative signal-to-noise ratio. Unfortunately, in a realistic case, acoustic signals recorded in a hydrodynamic tunnel show that the noise may be partially correlated. A prewhitening strategy is then considered in order to take into account the spatially coherent background noise. Numerical simulations and experimental results show an improvement in terms of BLN reduction in the large hydrodynamic tunnel. The effectiveness of the denoising method is also investigated in the context of acoustic source localization.

Comparative study of various normal mode analysis techniques based on partial Hessians.

Science.gov (United States)

Ghysels, An; Van Speybroeck, Veronique; Pauwels, Ewald; Catak, Saron; Brooks, Bernard R; Van Neck, Dimitri; Waroquier, Michel

2010-04-15

Standard normal mode analysis becomes problematic for complex molecular systems, as a result of both the high computational cost and the excessive amount of information when the full Hessian matrix is used. Several partial Hessian methods have been proposed in the literature, yielding approximate normal modes. These methods aim at reducing the computational load and/or calculating only the relevant normal modes of interest in a specific application. Each method has its own (dis)advantages and application field but guidelines for the most suitable choice are lacking. We have investigated several partial Hessian methods, including the Partial Hessian Vibrational Analysis (PHVA), the Mobile Block Hessian (MBH), and the Vibrational Subsystem Analysis (VSA). In this article, we focus on the benefits and drawbacks of these methods, in terms of the reproduction of localized modes, collective modes, and the performance in partially optimized structures. We find that the PHVA is suitable for describing localized modes, that the MBH not only reproduces localized and global modes but also serves as an analysis tool of the spectrum, and that the VSA is mostly useful for the reproduction of the low frequency spectrum. These guidelines are illustrated with the reproduction of the localized amine-stretch, the spectrum of quinine and a bis-cinchona derivative, and the low frequency modes of the LAO binding protein. 2009 Wiley Periodicals, Inc.

SYSTEMATIZATION AND ANALYSIS OF PARTIALLY AND FULLY HOMOMORPHIC CRYPTOSYSTEM

Directory of Open Access Journals (Sweden)

A. V. Epishkina

2016-12-01

Full Text Available In this article provides an overview of the known partially and fully homomorphic cryptosystem, such as: RSA, ElGamal, Paillier, Gentry and Halevi. Justified the homomorphic properties of the considered cryptosystems. The comparative analysis of the homomorphic encryption algorithms has been committed

Outcomes in patients with esotropic duane retraction syndrome and a partially accommodative component

Directory of Open Access Journals (Sweden)

Ramesh Kekunnaya

2013-01-01

Full Text Available Background: The management of Duane retraction syndrome (DRS is challenging and may become more difficult if an associated accommodative component due to high hyperopia is present. The purpose of this study is to review clinical features and outcomes in patients with partially accommodative esotropia and DRS. Setting and Design: Retrospective, non-comparative case series. Materials and Methods: Six cases of DRS with high hyperopia were reviewed. Results: Of the patients studied, the mean age of presentation was 1.3 years (range: 0.5-2.5 years. The mean amount of hyperopia was + 5D (range: 3.50-8.50 in both eyes. The mean follow up period was 7 years (range: 4 months-12 years. Five cases were unilateral while one was bilateral. Four cases underwent vertical rectus muscle transposition (VRT and one had medial rectus recession prior to presentation; all were given optical correction. Two (50% of the four patients who underwent vertical rectus transposition cases developed consecutive exotropia, one of whom did not have spectacles prescribed pre-operatively. All other cases (four had minimal residual esotropia and face turn at the last follow-up with spectacle correction. Conclusion: Patients with Duane syndrome can have an accommodative component to their esotropia, which is crucial to detect and correct prior to surgery to decrease the risk of long-term over-correction. Occasionally, torticollis in Duane syndrome can be satisfactorily corrected with spectacles alone.

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...

Analysis of water hammer in two-component two-phase flows

International Nuclear Information System (INIS)

Warde, H.; Marzouk, E.; Ibrahim, S.

1989-01-01

The water hammer phenomena caused by a sudden valve closure in air-water two-phase flows must be clarified for the safety analysis of LOCA in reactors and further for the safety of boilers, chemical plants, pipe transport of fluids such as petroleum and natural gas. In the present work water hammer phenomena caused by sudden valve closure in two-component two-phase flows are investigated theoretically and experimentally. The phenomena are more complicated than in single phase-flows due to the fact of the presence of compressible component. Basic partial differential equations based on a one-dimensional homogeneous flow model are solved by the method of characteristic. The analysis is extended to include friction in a two-phase mixture depending on the local flow pattern. The profiles of the pressure transients, the propagation velocity of pressure waves and the effect of valve closure on the transient pressure are found. Different two-phase flow pattern and frictional pressure drop correlations were used including Baker, Chesholm and Beggs and Bril correlations. The effect of the flow pattern on the characteristic of wave propagation is discussed primarily to indicate the effect of void fraction on the velocity of wave propagation and on the attenuation of pressure waves. Transient pressure in the mixture were recorded at different air void fractions, rates of uniform valve closure and liquid flow velocities with the aid of pressure transducers, transient wave form recorders interfaced with an on-line pc computer. The results are compared with computation, and good agreement was obtained within experimental accuracy

Key components of financial-analysis education for clinical nurses.

Science.gov (United States)

Lim, Ji Young; Noh, Wonjung

2015-09-01

In this study, we identified key components of financial-analysis education for clinical nurses. We used a literature review, focus group discussions, and a content validity index survey to develop key components of financial-analysis education. First, a wide range of references were reviewed, and 55 financial-analysis education components were gathered. Second, two focus group discussions were performed; the participants were 11 nurses who had worked for more than 3 years in a hospital, and nine components were agreed upon. Third, 12 professionals, including professors, nurse executive, nurse managers, and an accountant, participated in the content validity index. Finally, six key components of financial-analysis education were selected. These key components were as follows: understanding the need for financial analysis, introduction to financial analysis, reading and implementing balance sheets, reading and implementing income statements, understanding the concepts of financial ratios, and interpretation and practice of financial ratio analysis. The results of this study will be used to develop an education program to increase financial-management competency among clinical nurses. © 2015 Wiley Publishing Asia Pty Ltd.

Euler principal component analysis

NARCIS (Netherlands)

Liwicki, Stephan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

Principal Component Analysis (PCA) is perhaps the most prominent learning tool for dimensionality reduction in pattern recognition and computer vision. However, the ℓ 2-norm employed by standard PCA is not robust to outliers. In this paper, we propose a kernel PCA method for fast and robust PCA,

Identifying the Component Structure of Satisfaction Scales by Nonlinear Principal Components Analysis

NARCIS (Netherlands)

Manisera, M.; Kooij, A.J. van der; Dusseldorp, E.

2010-01-01

The component structure of 14 Likert-type items measuring different aspects of job satisfaction was investigated using nonlinear Principal Components Analysis (NLPCA). NLPCA allows for analyzing these items at an ordinal or interval level. The participants were 2066 workers from five types of social

Constrained principal component analysis and related techniques

CERN Document Server

Takane, Yoshio

2013-01-01

In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? What kind of benefits are we getting from them? Addressing these questions, Constrained Principal Component Analysis and Related Techniques shows how constrained PCA (CPCA) offers a unified framework for these approaches.The book begins with four concre

Nutritional and amino acid analysis of raw, partially fermented and ...

African Journals Online (AJOL)

African Journal of Food, Agriculture, Nutrition and Development ... The nutritional and amino acid analysis of raw and fermented seeds of Parkia ... between 4.27 and 8.33 % for the fully fermented and the partially fermented seeds, respectively.

Analysis Method for Integrating Components of Product

Energy Technology Data Exchange (ETDEWEB)

Choi, Jun Ho [Inzest Co. Ltd, Seoul (Korea, Republic of); Lee, Kun Sang [Kookmin Univ., Seoul (Korea, Republic of)

2017-04-15

This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

Analysis Method for Integrating Components of Product

International Nuclear Information System (INIS)

Choi, Jun Ho; Lee, Kun Sang

2017-01-01

This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

Physicochemical properties of different corn varieties by principal components analysis and cluster analysis

International Nuclear Information System (INIS)

Zeng, J.; Li, G.; Sun, J.

2013-01-01

Principal components analysis and cluster analysis were used to investigate the properties of different corn varieties. The chemical compositions and some properties of corn flour which processed by drying milling were determined. The results showed that the chemical compositions and physicochemical properties were significantly different among twenty six corn varieties. The quality of corn flour was concerned with five principal components from principal component analysis and the contribution rate of starch pasting properties was important, which could account for 48.90%. Twenty six corn varieties could be classified into four groups by cluster analysis. The consistency between principal components analysis and cluster analysis indicated that multivariate analyses were feasible in the study of corn variety properties. (author)

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.

Function spaces and partial differential equations volume 2 : contemporary analysis

CERN Document Server

Taheri, Ali

2015-01-01

This is a book written primarily for graduate students and early researchers in the fields of Analysis and Partial Differential Equations (PDEs). Coverage of the material is essentially self-contained, extensive and novel with great attention to details and rigour.

Comparative analysis of unilateral removable partial denture and classical removable partial denture by using finite element method

Directory of Open Access Journals (Sweden)

Radović Katarina

2010-01-01

Full Text Available Introduction. Various mobile devices are used in the therapy of unilateral free-end saddle. Unilateral dentures with precise connectivity elements are not used frequently. In this paper the problem of applying and functionality of unilateral freeend saddle denture without major connector was taken into consideration. Objective. The aim was to analyze and compare a unilateral RPD (removable partial denture and a classical RPD by calculating and analyzing stresses under different loads. Methods. 3D models of unilateral removable partial denture and classical removable partial denture with casted clasps were made by using computer program CATIA V5 (abutment teeth, canine and first premolar, with crowns and abutment tissues were also made. The models were built in full-scale. Stress analyses for both models were performed by applying a force of 300 N on the second premolar, a force of 500 N on the first molar and a force of 700 N on the second molar. Results. The Fault Model Extractor (FME analysis and calculation showed the complete behavior of unilateral removable partial denture and abutments (canine and first premolar, as well as the behavior of RPD under identical loading conditions. Applied forces with extreme values caused high stress levels on both models and their abutments within physiological limits. Conclusion. Having analyzed stresses under same conditions, we concluded that the unilateral RPD and classical RPD have similar physiological values.

Partial differential equations with variable exponents variational methods and qualitative analysis

CERN Document Server

Radulescu, Vicentiu D

2015-01-01

Partial Differential Equations with Variable Exponents: Variational Methods and Qualitative Analysis provides researchers and graduate students with a thorough introduction to the theory of nonlinear partial differential equations (PDEs) with a variable exponent, particularly those of elliptic type. The book presents the most important variational methods for elliptic PDEs described by nonhomogeneous differential operators and containing one or more power-type nonlinearities with a variable exponent. The authors give a systematic treatment of the basic mathematical theory and constructive meth

Partial Automated Alignment and Integration System

Science.gov (United States)

Kelley, Gary Wayne (Inventor)

2014-01-01

The present invention is a Partial Automated Alignment and Integration System (PAAIS) used to automate the alignment and integration of space vehicle components. A PAAIS includes ground support apparatuses, a track assembly with a plurality of energy-emitting components and an energy-receiving component containing a plurality of energy-receiving surfaces. Communication components and processors allow communication and feedback through PAAIS.

Incremental Tensor Principal Component Analysis for Handwritten Digit Recognition

Directory of Open Access Journals (Sweden)

Chang Liu

2014-01-01

Full Text Available To overcome the shortcomings of traditional dimensionality reduction algorithms, incremental tensor principal component analysis (ITPCA based on updated-SVD technique algorithm is proposed in this paper. This paper proves the relationship between PCA, 2DPCA, MPCA, and the graph embedding framework theoretically and derives the incremental learning procedure to add single sample and multiple samples in detail. The experiments on handwritten digit recognition have demonstrated that ITPCA has achieved better recognition performance than that of vector-based principal component analysis (PCA, incremental principal component analysis (IPCA, and multilinear principal component analysis (MPCA algorithms. At the same time, ITPCA also has lower time and space complexity.

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

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

Science.gov (United States)

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

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...

A comparative study of volatile components in Dianhong teas from fresh leaves of four tea cultivars by using chromatography-mass spectrometry, multivariate data analysis, and descriptive sensory analysis.

Science.gov (United States)

Wang, Chao; Zhang, Chenxia; Kong, Yawen; Peng, Xiaopei; Li, Changwen; Liu, Shunhang; Du, Liping; Xiao, Dongguang; Xu, Yongquan

2017-10-01

Dianhong teas produced from fresh leaves of different tea cultivars (YK is Yunkang No. 10, XY is Xueya 100, CY is Changyebaihao, SS is Shishengmiao), were compared in terms of volatile compounds and descriptive sensory analysis. A total of 73 volatile compounds in 16 tea samples were tentatively identified. YK, XY, CY, and SS contained 55, 53, 49, and 51 volatile compounds, respectively. Partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to classify the samples, and 40 key components were selected based on variable importance in the projection. Moreover, 11 flavor attributes, namely, floral, fruity, grass/green, woody, sweet, roasty, caramel, mellow and thick, bitter, astringent, and sweet aftertaste were identified through descriptive sensory analysis (DSA). In generally, innate differences among the tea varieties significantly affected the intensities of most of the key sensory attributes of Dianhong teas possibly because of the different amounts of aroma-active and taste components in Dianhong teas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Meta-analysis of adjunctive levetiracetam in refractory partial sei

Directory of Open Access Journals (Sweden)

ZHANG Ying

2012-10-01

Full Text Available Objective To evaluate the effects and tolerability of adjunctive levetiracetam (LEV in refractory partial seizures. Methods Relevant research articles about randomized controlled trials of adjunctive LEV in refractory partial seizures from January 1998 to December 2010 were retrieved from Cochrane Library, MEDLINE, EMbase, Social Sciences Citation Index (SSCI, VIP, Chinese National Knowledge Infrastructure (CNKI database, China Biology Medicine (CBM. Two reviewers independently evaluated the quality of the included articles and abstracted the data. A Meta-analysis was conducted by using RevMan 5.0 software. Results According to the enrollment criteria, eleven prospective, randomized controlled clinical trials with a total of 1192 in LEV group and 789 in placebo group were finally selected. The reduction in three endpoints (a 50% or greater reduction of partial seizure frequency per week, a 75% or greater reduction of partial seizure frequency per week and seizure free was significant in LEV group than placebo group. There was no significance between LEV group and placebo group in the withdrawl rate (1000 mg/d: OR = 1.180, 95%CI: 0.690-2.010, P = 0.540; 2000 mg/d: OR = 1.530, 95%CI: 0.770-3.030, P = 0.230; 3000 mg/d: OR = 1.000, 95% CI: 0.620-1.600, P = 1.000. The following adverse events were associated with LEV: somnolence (OR = 1.720, 95%CI: 1.280-2.310, P = 0.000, dizziness (OR = 1.490, 95%CI: 1.000-2.220, P = 0.050, asthenia (OR = 1.670, 95%CI: 1.140-2.240, P = 0.008, nasopharyngitis (OR = 1.120, 95% CI: 0.710-1.760, P = 0.630, psychiatric and behavioral abnormalities (OR = 2.120, 95% CI: 1.370-3.280, P = 0.000. Conclusion LEV is effective and well tolerated when added to existing therapy in patients with refractory partial seizures compared with control drugs. Further studies are needed to identify the effects of monotherapy of LEV in partial seizures.

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....

An analysis of the nucleon spectrum from lattice partially-quenched QCD

Energy Technology Data Exchange (ETDEWEB)

Armour, W. [Swansea University, Swansea, SA2 8PP, Wales, U.K.; Allton, C. R. [Swansea University, Swansea, SA2 8PP, Wales, U.K.; Leinweber, Derek B. [Univ. of Adelaide, SA (Australia); Thomas, Anthony W. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); College of William and Mary, Williamsburg, VA (United States); Young, Ross D. [Argonne National Lab. (ANL), Argonne, IL (United States)

2010-09-01

The chiral extrapolation of the nucleon mass, Mn, is investigated using data coming from 2-flavour partially-quenched lattice simulations. The leading one-loop corrections to the nucleon mass are derived for partially-quenched QCD. A large sample of lattice results from the CP-PACS Collaboration is analysed, with explicit corrections for finite lattice spacing artifacts. The extrapolation is studied using finite range regularised chiral perturbation theory. The analysis also provides a quantitative estimate of the leading finite volume corrections. It is found that the discretisation, finite-volume and partial quenching effects can all be very well described in this framework, producing an extrapolated value of Mn in agreement with experiment. This procedure is also compared with extrapolations based on polynomial forms, where the results are less encouraging.

Towards a simple method of analysis for partially prestressed concrete

NARCIS (Netherlands)

Bruggeling, A.S.G.

1983-01-01

This report examines the question whether, and to what extent, it is possible to leave the time-dependent effects out of account in the analysis of partially prestressed concrete, at least in so far as they relate to the redistribution of the stresses over the cross-section.

Multilevel sparse functional principal component analysis.

Science.gov (United States)

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

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

Full and part load exergetic analysis of a hybrid micro gas turbine fuel cell system based on existing components

International Nuclear Information System (INIS)

Bakalis, Diamantis P.; Stamatis, Anastassios G.

2012-01-01

Highlights: ► Hybrid SOFC/GT system based on existing components. ► Exergy analysis using AspenPlus™ software. ► Greenhouse gases emission is significantly affected by SOFC stack temperature. ► Comparison with a conventional GT of similar power. ► SOFC/GT is almost twice efficient in terms of second low efficiency and CO 2 emission. - Abstract: The paper deals with the examination of a hybrid system consisting of a pre-commercially available high temperature solid oxide fuel cell and an existing recuperated microturbine. The irreversibilities and thermodynamic inefficiencies of the system are evaluated after examining the full and partial load exergetic performance and estimating the amount of exergy destruction and the efficiency of each hybrid system component. At full load operation the system achieves an exergetic efficiency of 59.8%, which increases during the partial load operation, as a variable speed control method is utilized. Furthermore, the effects of the various performance parameters such as fuel cell stack temperature and fuel utilization factor are assessed. The results showed that the components in which chemical reactions occur have the higher exergy destruction rates. The exergetic performance of the system is affected significantly by the stack temperature. Based on the exergetic analysis, suggestions are given for reducing the overall system irreversibility. Finally, the environmental impact of the operation of the hybrid system is evaluated and compared with a similarly rated conventional gas turbine plant. From the comparison it is apparent that the hybrid system obtains nearly double exergetic efficiency and about half the amount of greenhouse gas emissions compared with the conventional plant.

EXAFS and principal component analysis : a new shell game

International Nuclear Information System (INIS)

Wasserman, S.

1998-01-01

The use of principal component (factor) analysis in the analysis EXAFS spectra is described. The components derived from EXAFS spectra share mathematical properties with the original spectra. As a result, the abstract components can be analyzed using standard EXAFS methodology to yield the bond distances and other coordination parameters. The number of components that must be analyzed is usually less than the number of original spectra. The method is demonstrated using a series of spectra from aqueous solutions of uranyl ions

Reliability Analysis and Calibration of Partial Safety Factors for Redundant Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1998-01-01

Redundancy is important to include in the design and analysis of structural systems. In most codes of practice redundancy is not directly taken into account. In the paper various definitions of a deterministic and reliability based redundancy measure are reviewed. It is described how reundancy can...... be included in the safety system and how partial safety factors can be calibrated. An example is presented illustrating how redundancy is taken into account in the safety system in e.g. the Danish codes. The example shows how partial safety factors can be calibrated to comply with the safety level...

Problems of stress analysis of fuelling machine head components

International Nuclear Information System (INIS)

Mathur, D.D.

1975-01-01

The problem of stress analysis of fuelling machine head components are discussed. To fulfil the functional requirements, the components are required to have certain shapes where stress problems cannot be matched to a catalogue of pre-determined solutions. The areas where complex systems of loading due to hydrostatic pressure, weight, moments and temperature gradients coupled with the intricate shapes of the components make it difficult to arrive at satisfactory solutions. Particularly, the analysis requirements of the magazine housing, end cover, gravloc clamps and centre support are highlighted. An experimental stress analysis programme together with a theoretical finite element analysis is perhaps the answer. (author)

Partial wave analysis of the Q region in the reactions K-p→K-π+π-p and K-p→antikaon neutral π-π0p at 14.3GeV/c

International Nuclear Information System (INIS)

Tovey, S.N.; Hansen, J.D.; Paler, K.; Shah, T.P.; Borg, A.; Denegri, D.; Pons, Y.; Spiro, M.

1975-01-01

The reactions K - p→K - π + π - and K - p→ antikaon-neutral π - π 0 p at 14.3GeV/c has been studied using respectively 15992 and 3723 events. Partial wave analysis of the region 1.0 + but that the partial wave substrates have very different branching ratios into (rho) and K*π, the K*π component of the 1 + state being similar to the 1 + state of the 3π system produced in the reaction πp→(3π)p [fr

Seismic Response Analysis of Continuous Multispan Bridges with Partial Isolation

Directory of Open Access Journals (Sweden)

E. Tubaldi

2015-01-01

Full Text Available Partially isolated bridges are a particular class of bridges in which isolation bearings are placed only between the piers top and the deck whereas seismic stoppers restrain the transverse motion of the deck at the abutments. This paper proposes an analytical formulation for the seismic analysis of these bridges, modelled as beams with intermediate viscoelastic restraints whose properties describe the pier-isolator behaviour. Different techniques are developed for solving the seismic problem. The first technique employs the complex mode superposition method and provides an exact benchmark solution to the problem at hand. The two other simplified techniques are based on an approximation of the displacement field and are useful for preliminary assessment and design purposes. A realistic bridge is considered as case study and its seismic response under a set of ground motion records is analyzed. First, the complex mode superposition method is applied to study the characteristic features of the dynamic and seismic response of the system. A parametric analysis is carried out to evaluate the influence of support stiffness and damping on the seismic performance. Then, a comparison is made between the exact solution and the approximate solutions in order to evaluate the accuracy and suitability of the simplified analysis techniques for evaluating the seismic response of partially isolated bridges.

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.

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...

Abstract interfaces for data analysis - component architecture for data analysis tools

International Nuclear Information System (INIS)

Barrand, G.; Binko, P.; Doenszelmann, M.; Pfeiffer, A.; Johnson, A.

2001-01-01

The fast turnover of software technologies, in particular in the domain of interactivity (covering user interface and visualisation), makes it difficult for a small group of people to produce complete and polished software-tools before the underlying technologies make them obsolete. At the HepVis'99 workshop, a working group has been formed to improve the production of software tools for data analysis in HENP. Beside promoting a distributed development organisation, one goal of the group is to systematically design a set of abstract interfaces based on using modern OO analysis and OO design techniques. An initial domain analysis has come up with several categories (components) found in typical data analysis tools: Histograms, Ntuples, Functions, Vectors, Fitter, Plotter, analyzer and Controller. Special emphasis was put on reducing the couplings between the categories to a minimum, thus optimising re-use and maintainability of any component individually. The interfaces have been defined in Java and C++ and implementations exist in the form of libraries and tools using C++ (Anaphe/Lizard, OpenScientist) and Java (Java Analysis Studio). A special implementation aims at accessing the Java libraries (through their Abstract Interfaces) from C++. The authors give an overview of the architecture and design of the various components for data analysis as discussed in AIDA

Component reliability analysis for development of component reliability DB of Korean standard NPPs

International Nuclear Information System (INIS)

Choi, S. Y.; Han, S. H.; Kim, S. H.

2002-01-01

The reliability data of Korean NPP that reflects the plant specific characteristics is necessary for PSA and Risk Informed Application. We have performed a project to develop the component reliability DB and calculate the component reliability such as failure rate and unavailability. We have collected the component operation data and failure/repair data of Korean standard NPPs. We have analyzed failure data by developing a data analysis method which incorporates the domestic data situation. And then we have compared the reliability results with the generic data for the foreign NPPs

Sparse Principal Component Analysis in Medical Shape Modeling

DEFF Research Database (Denmark)

Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus

2006-01-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...

Nucleon-nucleon partial-wave analysis to 1100 MeV

International Nuclear Information System (INIS)

Arndt, R.A.; Hyslop, J.S. III; Roper, L.D.

1987-01-01

Comprehensive analyses of nucleon-nucleon elastic-scattering data below 1100 MeV laboratory kinetic energy are presented. The data base from which an energy-dependent solution and 22 single-energy solutions are obtained consists of 7223 pp and 5474 np data. A resonancelike structure is found to occur in the 1 D 2 , 3 F 3 , 3 P 2 - 3 F 2 , and 3 F 4 - 3 H 4 partial waves; this behavior is associated with poles in the complex energy plane. The pole positions and residues are obtained by analytic continuation of the ''production'' piece of the T matrix obtained in the energy-dependent solution. The new phases differ somewhat from previously published VPIandSU solutions, especially in I = 0 waves above 500 MeV, where np data are very sparse. The partial waves are, however, based upon a significantly larger data base and reflect correspondingly smaller errors. The full data base and solution files can be obtained through a computer scattering analysis interactive dial-in (SAID) system at VPIandSU, which also exists at many institutions around the world and which can be transferred to any site with a suitable computer system. The SAID system can be used to modify solutions, plan experiments, and obtain any of the multitude of predictions which derive from partial-wave analyses of the world data base

Partial wave analysis of anti pp → anti ΛΛ

International Nuclear Information System (INIS)

Bugg, D.V.

2004-01-01

A partial wave analysis of PS185 data for anti pp → anti ΛΛ is presented. A 3 S 1 cusp is identified in the inverse process anti ΛΛ→ anti p p at threshold, using detailed balance to deduce cross sections from anti pp → anti ΛΛ. Partial wave amplitudes for anti pp 3 P 0 , 3 F 3 , 3 D 3 and 3 G 3 exhibit a behaviour very similar to resonances observed in Crystal Barrel data. With this identification, the anti pp → anti ΛΛ data then provide evidence for a new I=0, J PC =1 - resonance with mass M = 2290 ±20 MeV, Γ= 275 ±35 MeV, coupling to both 3 S 1 and 3 D 1 . (orig.)

Discriminatory components retracing strategy for monitoring the preparation procedure of Chinese patent medicines by fingerprint and chemometric analysis.

Directory of Open Access Journals (Sweden)

Shuai Yao

Full Text Available Chinese patent medicines (CPM, generally prepared from several traditional Chinese medicines (TCMs in accordance with specific process, are the typical delivery form of TCMs in Asia. To date, quality control of CPMs has typically focused on the evaluation of the final products using fingerprint technique and multi-components quantification, but rarely on monitoring the whole preparation process, which was considered to be more important to ensure the quality of CPMs. In this study, a novel and effective strategy labeling "retracing" way based on HPLC fingerprint and chemometric analysis was proposed with Shenkang injection (SKI serving as an example to achieve the quality control of the whole preparation process. The chemical fingerprints were established initially and then analyzed by similarity, principal component analysis (PCA and partial least squares-discriminant analysis (PLS-DA to evaluate the quality and to explore discriminatory components. As a result, the holistic inconsistencies of ninety-three batches of SKIs were identified and five discriminatory components including emodic acid, gallic acid, caffeic acid, chrysophanol-O-glucoside, and p-coumaroyl-O-galloyl-glucose were labeled as the representative targets to explain the retracing strategy. Through analysis of the targets variation in the corresponding semi-products (ninety-three batches, intermediates (thirty-three batches, and the raw materials, successively, the origins of the discriminatory components were determined and some crucial influencing factors were proposed including the raw materials, the coextraction temperature, the sterilizing conditions, and so on. Meanwhile, a reference fingerprint was established and subsequently applied to the guidance of manufacturing. It was suggested that the production process should be standardized by taking the concentration of the discriminatory components as the diagnostic marker to ensure the stable and consistent quality for multi

Dynamic Modal Analysis of Vertical Machining Centre Components

OpenAIRE

Anayet U. Patwari; Waleed F. Faris; A. K. M. Nurul Amin; S. K. Loh

2009-01-01

The paper presents a systematic procedure and details of the use of experimental and analytical modal analysis technique for structural dynamic evaluation processes of a vertical machining centre. The main results deal with assessment of the mode shape of the different components of the vertical machining centre. The simplified experimental modal analysis of different components of milling machine was carried out. This model of the different machine tool's structure is made by design software...

Mirroring behavior of partial photodetachment and photoionization cross sections in the neighborhood of a resonance

International Nuclear Information System (INIS)

Liu, C.; Starace, A.F.

1999-01-01

Partial photodetachment and photoionization cross sections corresponding to highly excited residual atoms or ions are shown analytically to mirror one another in the neighborhood of a resonance. More precisely, any two groupings of partial cross sections are shown here to have components whose variations with energy near a resonance are equal in magnitude and opposite in direction. This work extends an analysis of Starace [Phys. Rev. A 16, 231 (1977)] for the behavior of partial cross sections near a resonance to the case when the ρ 2 parameter of Fano and Cooper [Phys. Rev. 137, A1364 (1965)] tends to zero. copyright 1999 The American Physical Society

Functional Principal Components Analysis of Shanghai Stock Exchange 50 Index

Directory of Open Access Journals (Sweden)

Zhiliang Wang

2014-01-01

Full Text Available The main purpose of this paper is to explore the principle components of Shanghai stock exchange 50 index by means of functional principal component analysis (FPCA. Functional data analysis (FDA deals with random variables (or process with realizations in the smooth functional space. One of the most popular FDA techniques is functional principal component analysis, which was introduced for the statistical analysis of a set of financial time series from an explorative point of view. FPCA is the functional analogue of the well-known dimension reduction technique in the multivariate statistical analysis, searching for linear transformations of the random vector with the maximal variance. In this paper, we studied the monthly return volatility of Shanghai stock exchange 50 index (SSE50. Using FPCA to reduce dimension to a finite level, we extracted the most significant components of the data and some relevant statistical features of such related datasets. The calculated results show that regarding the samples as random functions is rational. Compared with the ordinary principle component analysis, FPCA can solve the problem of different dimensions in the samples. And FPCA is a convenient approach to extract the main variance factors.

Surgical treatment of gastroesophageal reflux disease: total or partial fundoplication? Systematic review and meta-analysis

Directory of Open Access Journals (Sweden)

Rodrigo F Ramos

2011-12-01

Full Text Available CONTEXT: Although the high incidence of gastroesophageal reflux disease (GERD in the population, there is much controversy in this topic, especially in the surgical treatment. The decision to use of a total or partial fundoplication in the treatment of GERD is still a challenge to many surgeons because the few evidence found in the literature. OBJECTIVE: To bring more clear evidence in the comparison between total and partial fundoplication. DATA SOURCES: A systematic review of the literature and metaanalysis with randomized controlled trials accessed from MEDLINE, LILACS, Cochrane Controlled Trials Database was done. The outcomes remarked were: dysphagia, inability to belch, bloating, recurrence of acid reflux, heartburn and esophagitis. For data analysis the odds ratio was used with corresponding 95% confidence interval. Statistical heterogeneity in the results of the metaanalysis was assessed by calculating a test of heterogeneity. The software Review Manager 5 (Cochrane Collaboration was utilized for the data gathered and the statistical analysis. Sensitive analysis was applied using only trials that included follow-up over 2 years. RESULTS: Ten trials were included with 1003 patients: 502 to total fundoplication group and 501 to partial fundoplication group. The outcomes dysphagia and inability to belch had statistical significant difference (P = 0.00001 in favor of partial fundoplication. There was not statistical difference in outcomes related with treatment failure. There were no heterogeneity in the outcomes dysphagia and recurrence of the acid reflux. CONCLUSION: The partial fundoplication has lower incidence of obstructive side effects.

Calculation of partial derivatives of thermophysical properties of sodium for safety analysis

International Nuclear Information System (INIS)

Shan Jianqiang; Qiu Suizhang; Zhu Jizhou; Zhang Guiqin

1997-01-01

According to the characters of safety analysis of LMFBR, the partial derivatives formula of some special thermophysical properties of sodium, including single-and two-phase properties, are calculated based on the basic Maxwell equations, and on the formulae of basic thermophysical properties of sodium which were verified abroad. The present study can provide theoretical base for safety analysis of LMFBR

Artificial neural network combined with principal component analysis for resolution of complex pharmaceutical formulations.

Science.gov (United States)

Ioele, Giuseppina; De Luca, Michele; Dinç, Erdal; Oliverio, Filomena; Ragno, Gaetano

2011-01-01

A chemometric approach based on the combined use of the principal component analysis (PCA) and artificial neural network (ANN) was developed for the multicomponent determination of caffeine (CAF), mepyramine (MEP), phenylpropanolamine (PPA) and pheniramine (PNA) in their pharmaceutical preparations without any chemical separation. The predictive ability of the ANN method was compared with the classical linear regression method Partial Least Squares 2 (PLS2). The UV spectral data between 220 and 300 nm of a training set of sixteen quaternary mixtures were processed by PCA to reduce the dimensions of input data and eliminate the noise coming from instrumentation. Several spectral ranges and different numbers of principal components (PCs) were tested to find the PCA-ANN and PLS2 models reaching the best determination results. A two layer ANN, using the first four PCs, was used with log-sigmoid transfer function in first hidden layer and linear transfer function in output layer. Standard error of prediction (SEP) was adopted to assess the predictive accuracy of the models when subjected to external validation. PCA-ANN showed better prediction ability in the determination of PPA and PNA in synthetic samples with added excipients and pharmaceutical formulations. Since both components are characterized by low absorptivity, the better performance of PCA-ANN was ascribed to the ability in considering all non-linear information from noise or interfering excipients.

Probabilistic Principal Component Analysis for Metabolomic Data.

LENUS (Irish Health Repository)

Nyamundanda, Gift

2010-11-23

Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.jp; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo, Kyoto 606-8507 (Japan)

2016-09-15

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

International Nuclear Information System (INIS)

Matsuo, Yukinori; Nakamura, Mitsuhiro; Mizowaki, Takashi; Hiraoka, Masahiro

2016-01-01

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

Partial scram incident in FBTR

International Nuclear Information System (INIS)

Usha, S.; Pillai, C.P.; Muralikrishna, G.

1989-01-01

Evaluation of a partial scram incident occurred at the Fast Breeder Test Reactor at Kalpakkam was carried out. Based on the observations of the experiments it was ascertained that the nonpersistant order was due to superimposed noise component on the channel that was close to the threshold and had resulted in intermittent supply to electro-magnetic (EM) coils. Owing to a larger discharge time and a smaller charge time, the EM coils got progressively discharged. It was confirmed that during the incident, partial scram took place since the charging and discharging patterns of the EM coils are dissimilar and EM coils of rods A, E and F had discharged faster than others for noise component of a particular duty cycle. However, nonlatching of scram order was because of the fact that noise pulse duration was less than latching time. (author)

Clinical usefulness of physiological components obtained by factor analysis

International Nuclear Information System (INIS)

Ohtake, Eiji; Murata, Hajime; Matsuda, Hirofumi; Yokoyama, Masao; Toyama, Hinako; Satoh, Tomohiko.

1989-01-01

The clinical usefulness of physiological components obtained by factor analysis was assessed in 99m Tc-DTPA renography. Using definite physiological components, another dynamic data could be analyzed. In this paper, the dynamic renal function after ESWL (Extracorporeal Shock Wave Lithotripsy) treatment was examined using physiological components in the kidney before ESWL and/or a normal kidney. We could easily evaluate the change of renal functions by this method. The usefulness of a new analysis using physiological components was summarized as follows: 1) The change of a dynamic function could be assessed in quantity as that of the contribution ratio. 2) The change of a sick condition could be morphologically evaluated as that of the functional image. (author)

Multi-component separation and analysis of bat echolocation calls.

Science.gov (United States)

DiCecco, John; Gaudette, Jason E; Simmons, James A

2013-01-01

The vast majority of animal vocalizations contain multiple frequency modulated (FM) components with varying amounts of non-linear modulation and harmonic instability. This is especially true of biosonar sounds where precise time-frequency templates are essential for neural information processing of echoes. Understanding the dynamic waveform design by bats and other echolocating animals may help to improve the efficacy of man-made sonar through biomimetic design. Bats are known to adapt their call structure based on the echolocation task, proximity to nearby objects, and density of acoustic clutter. To interpret the significance of these changes, a method was developed for component separation and analysis of biosonar waveforms. Techniques for imaging in the time-frequency plane are typically limited due to the uncertainty principle and interference cross terms. This problem is addressed by extending the use of the fractional Fourier transform to isolate each non-linear component for separate analysis. Once separated, empirical mode decomposition can be used to further examine each component. The Hilbert transform may then successfully extract detailed time-frequency information from each isolated component. This multi-component analysis method is applied to the sonar signals of four species of bats recorded in-flight by radiotelemetry along with a comparison of other common time-frequency representations.

Analysis methods for structure reliability of piping components

International Nuclear Information System (INIS)

Schimpfke, T.; Grebner, H.; Sievers, J.

2004-01-01

In the frame of the German reactor safety research program of the Federal Ministry of Economics and Labour (BMWA) GRS has started to develop an analysis code named PROST (PRObabilistic STructure analysis) for estimating the leak and break probabilities of piping systems in nuclear power plants. The long-term objective of this development is to provide failure probabilities of passive components for probabilistic safety analysis of nuclear power plants. Up to now the code can be used for calculating fatigue problems. The paper mentions the main capabilities and theoretical background of the present PROST development and presents some of the results of a benchmark analysis in the frame of the European project NURBIM (Nuclear Risk Based Inspection Methodologies for Passive Components). (orig.)

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.

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.

Comparative videostroboscopic analysis after different external partial laryngectomies

Directory of Open Access Journals (Sweden)

Mumović Gordana M.

2014-01-01

Full Text Available Background/Aim. After external partial laryngectomias, videostroborscopy is very usefull in evaluation of postoperative phonatory mehanisms showing the “slow motion” of the vibrations of the remaining laryngeal structures. The aim of this paper was to compare the videostroboscopic characteristics of the vibration and to establish the differences in the phonation mechanisms depending on the type of external partial laryngectomy performed. Methods. This prospective study was conducted during the period 2003-2009 at the Ear, Nose and Throat Clinic, Clinical Center of Vojvodina, Novi Sad, including 99 patients with laryngeal carcinoma, treated with open surgical approach using different types of vertical and horizontal partial laryngectomy. Videostroboscopy was used to analyse vibrations of the remaining laryngeal structures. Results. The dominant vibration structure after partial horizontal laryngectomy, chordectomy, frontolateral laryngectomy and three quarter laryngectomy was the remaining vocal fold, after hemilaryngectomy it was the false vocal fold and after subtotal and near total laryngectomy it was the arythenoid. In patients with supracricoid hemilaryngopharyngectomy performed, many different structures were involved in the vibration. After most of the partial laryngectomies, vibrations can be found in the reconstructed part of the defect. In both horizontal and vertical partial laryngectomies movements of the larynx during phonation were mostly medial, while in cricohyoidoglottopexies they were anterior-posterior. Most of the operated patients (72.7% had insufficient occlusion of the neoglottis during the phonation. Conclusion. Videostroboscopy is a useful method in examining the phonation mechanisms of reconstructed laryngeal structures after partial laryngectomy as well as in planning postoperative voice therapy.

System diagnostics using qualitative analysis and component functional classification

International Nuclear Information System (INIS)

Reifman, J.; Wei, T.Y.C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures

Partially wrong? Partial equilibrium and the economic analysis of public health emergencies of international concern.

Science.gov (United States)

Beutels, P; Edmunds, W J; Smith, R D

2008-11-01

We argue that traditional health economic analysis is ill-equipped to estimate the cost effectiveness and cost benefit of interventions that aim at controlling and/or preventing public health emergencies of international concern (such as pandemic influenza or severe acute respiratory syndrome). The implicit assumption of partial equilibrium within both the health sector itself and--if a wider perspective is adopted--the economy as a whole would be violated by such emergencies. We propose an alternative, with the specific aim of accounting for the behavioural changes and capacity problems that are expected to occur when such an outbreak strikes. Copyright (c) 2008 John Wiley & Sons, Ltd.

Na+/K+-ATPase inhibition partially mimics the ethanol-induced increase of the Golgi cell-dependent component of the tonic GABAergic current in rat cerebellar granule cells.

Directory of Open Access Journals (Sweden)

Marvin R Diaz

Full Text Available Cerebellar granule cells (CGNs are one of many neurons that express phasic and tonic GABAergic conductances. Although it is well established that Golgi cells (GoCs mediate phasic GABAergic currents in CGNs, their role in mediating tonic currents in CGNs (CGN-I(tonic is controversial. Earlier studies suggested that GoCs mediate a component of CGN-I(tonic that is present only in preparations from immature rodents. However, more recent studies have detected a GoC-dependent component of CGN-I(tonic in preparations of mature rodents. In addition, acute exposure to ethanol was shown to potentiate the GoC component of CGN-I(tonic and to induce a parallel increase in spontaneous inhibitory postsynaptic current frequency at CGNs. Here, we tested the hypothesis that these effects of ethanol on GABAergic transmission in CGNs are mediated by inhibition of the Na(+/K(+-ATPase. We used whole-cell patch-clamp electrophysiology techniques in cerebellar slices of male rats (postnatal day 23-30. Under these conditions, we reliably detected a GoC-dependent component of CGN-I(tonic that could be blocked with tetrodotoxin. Further analysis revealed a positive correlation between basal sIPSC frequency and the magnitude of the GoC-dependent component of CGN-I(tonic. Inhibition of the Na(+/K(+-ATPase with a submaximal concentration of ouabain partially mimicked the ethanol-induced potentiation of both phasic and tonic GABAergic currents in CGNs. Modeling studies suggest that selective inhibition of the Na(+/K(+-ATPase in GoCs can, in part, explain these effects of ethanol. These findings establish a novel mechanism of action of ethanol on GABAergic transmission in the central nervous system.

Physics of partially ionized plasmas

CERN Document Server

Krishan, Vinod

2016-01-01

Plasma is one of the four fundamental states of matter; the other three being solid, liquid and gas. Several components, such as molecular clouds, diffuse interstellar gas, the solar atmosphere, the Earth's ionosphere and laboratory plasmas, including fusion plasmas, constitute the partially ionized plasmas. This book discusses different aspects of partially ionized plasmas including multi-fluid description, equilibrium and types of waves. The discussion goes on to cover the reionization phase of the universe, along with a brief description of high discharge plasmas, tokomak plasmas and laser plasmas. Various elastic and inelastic collisions amongst the three particle species are also presented. In addition, the author demonstrates the novelty of partially ionized plasmas using many examples; for instance, in partially ionized plasma the magnetic induction is subjected to the ambipolar diffusion and the Hall effect, as well as the usual resistive dissipation. Also included is an observation of kinematic dynam...

Principal Component Analysis of Body Measurements In Three ...

African Journals Online (AJOL)

This study was conducted to explore the relationship among body measurements in 3 strains of broilers chicken (Arbor Acre, Marshal and Ross) using principal component analysis with the view of identifying those components that define body conformation in broilers. A total of 180 birds were used, 60 per strain.

Through-flow analysis of steam turbines operating under partial admission

International Nuclear Information System (INIS)

Delabriere, H.; Werthe, J.M.

1993-05-01

In order to produce electric energy with improved efficiency, Electricite de France has to check the performances of equipment proposed by manufacturers. In the specific field of steam turbines, one of the main tools of analysis is the quasi 3D through flow computer code CAPTUR, which enables the calculation of all the aerothermodynamic parameters in a steam turbine. The last development that has been performed on CAPTUR is the extension to a calculation of a flow within a turbine operating under partial admission. For such turbines, it is now possible to calculate an internal flow field, and determine the efficiency, in a much more accurate way than with previous methods, which consist in an arbitrary efficiency correction on an averaged 1D flow calculation. From the aerodynamic point of view, partial admission involves specific losses in the first stage, then expansion and turbulent mixing just downstream of the first stage. Losses in the first stage are of very different types: windage, pumping and expansion at the ends of an admission sector. Their values have been estimated, with help of experimental results, and then expressed as a slow down coefficient applied to the relative velocity at the blade outlet. As for the flow downstream the first stage, a computational analysis has been made with specific 2D and 3D codes. It has led to define the numerical treatment established in the CAPTUR code. Some problems had to be solved to make compatible a quasi 3D formulation, making an average in the azimutal direction and using a streamline curvature method, with an absolute 3D phenomenon. Certain limitations of the working conditions were first adopted, but a generalization is on hand. The calculation of a nuclear HP steam turbine operating under partial admission has been performed. Calculation results are in good accordance with tests results, especially as regards the expansion line along the stages. The code CAPTUR will be particularly useful for the calculation

Fault tree analysis with multistate components

International Nuclear Information System (INIS)

Caldarola, L.

1979-02-01

A general analytical theory has been developed which allows one to calculate the occurence probability of the top event of a fault tree with multistate (more than states) components. It is shown that, in order to correctly describe a system with multistate components, a special type of Boolean algebra is required. This is called 'Boolean algebra with restrictions on varibales' and its basic rules are the same as those of the traditional Boolean algebra with some additional restrictions on the variables. These restrictions are extensively discussed in the paper. Important features of the method are the identification of the complete base and of the smallest irredundant base of a Boolean function which does not necessarily need to be coherent. It is shown that the identification of the complete base of a Boolean function requires the application of some algorithms which are not used in today's computer programmes for fault tree analysis. The problem of statistical dependence among primary components is discussed. The paper includes a small demonstrative example to illustrate the method. The example includes also statistical dependent components. (orig.) [de

Mirroring behavior of partial photodetachment and photoionization cross sections in the neighborhood of a resonance

Energy Technology Data Exchange (ETDEWEB)

Liu, C.; Starace, A.F. [Department of Physics and Astronomy, The University of Nebraska, Lincoln, Nebraska 68588-0111 (United States)

1999-03-01

Partial photodetachment and photoionization cross sections corresponding to highly excited residual atoms or ions are shown analytically to mirror one another in the neighborhood of a resonance. More precisely, any two groupings of partial cross sections are shown here to have components whose variations with energy near a resonance are equal in magnitude and opposite in direction. This work extends an analysis of Starace [Phys. Rev. A {bold 16}, 231 (1977)] for the behavior of partial cross sections near a resonance to the case when the {rho}{sup 2} parameter of Fano and Cooper [Phys. Rev. {bold 137}, A1364 (1965)] tends to zero. {copyright} {ital 1999} {ital The American Physical Society}

Multistage principal component analysis based method for abdominal ECG decomposition

International Nuclear Information System (INIS)

Petrolis, Robertas; Krisciukaitis, Algimantas; Gintautas, Vladas

2015-01-01

Reflection of fetal heart electrical activity is present in registered abdominal ECG signals. However this signal component has noticeably less energy than concurrent signals, especially maternal ECG. Therefore traditionally recommended independent component analysis, fails to separate these two ECG signals. Multistage principal component analysis (PCA) is proposed for step-by-step extraction of abdominal ECG signal components. Truncated representation and subsequent subtraction of cardio cycles of maternal ECG are the first steps. The energy of fetal ECG component then becomes comparable or even exceeds energy of other components in the remaining signal. Second stage PCA concentrates energy of the sought signal in one principal component assuring its maximal amplitude regardless to the orientation of the fetus in multilead recordings. Third stage PCA is performed on signal excerpts representing detected fetal heart beats in aim to perform their truncated representation reconstructing their shape for further analysis. The algorithm was tested with PhysioNet Challenge 2013 signals and signals recorded in the Department of Obstetrics and Gynecology, Lithuanian University of Health Sciences. Results of our method in PhysioNet Challenge 2013 on open data set were: average score: 341.503 bpm 2 and 32.81 ms. (paper)

Determining the number of components in principal components analysis: A comparison of statistical, crossvalidation and approximated methods

NARCIS (Netherlands)

Saccenti, E.; Camacho, J.

2015-01-01

Principal component analysis is one of the most commonly used multivariate tools to describe and summarize data. Determining the optimal number of components in a principal component model is a fundamental problem in many fields of application. In this paper we compare the performance of several

Importance Analysis of In-Service Testing Components for Ulchin Unit 3

International Nuclear Information System (INIS)

Dae-Il Kan; Kil-Yoo Kim; Jae-Joo Ha

2002-01-01

We performed an importance analysis of In-Service Testing (IST) components for Ulchin Unit 3 using the integrated evaluation method for categorizing component safety significance developed in this study. The importance analysis using the developed method is initiated by ranking the component importance using quantitative PSA information. The importance analysis of the IST components not modeled in the PSA is performed through the engineering judgment, based on the expertise of PSA, and the quantitative and qualitative information for the IST components. The PSA scope for importance analysis includes not only Level 1 and 2 internal PSA but also Level 1 external and shutdown/low power operation PSA. The importance analysis results of valves show that 167 (26.55%) of the 629 IST valves are HSSCs and 462 (73.45%) are LSSCs. Those of pumps also show that 28 (70%) of the 40 IST pumps are HSSCs and 12 (30%) are LSSCs. (authors)

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...

Functional analytic methods in complex analysis and applications to partial differential equations

International Nuclear Information System (INIS)

Mshimba, A.S.A.; Tutschke, W.

1990-01-01

The volume contains 24 lectures given at the Workshop on Functional Analytic Methods in Complex Analysis and Applications to Partial Differential Equations held in Trieste, Italy, between 8-19 February 1988, at the ICTP. A separate abstract was prepared for each of these lectures. Refs and figs

Group-wise Principal Component Analysis for Exploratory Data Analysis

NARCIS (Netherlands)

Camacho, J.; Rodriquez-Gomez, Rafael A.; Saccenti, E.

2017-01-01

In this paper, we propose a new framework for matrix factorization based on Principal Component Analysis (PCA) where sparsity is imposed. The structure to impose sparsity is defined in terms of groups of correlated variables found in correlation matrices or maps. The framework is based on three new

Proportion of various dendromass components of spruce (Picea abies), and partial models for modification of wind speed and radiation by pure spruce stands

International Nuclear Information System (INIS)

Wollmerstädt, J.; Sharma, S.C.; Marsch, M.

1992-01-01

Means for quantifying dendromass components of spruce stands have been discussed, and partial models for modification of radiation and wind by the pure spruce stand were developed. By means of a sampling procedure, the components needle dry mass and branchwood dry mass without needles of individual trees are recorded. Using the relationship between branch basal diameter and needle respectively branchwood dry mass, the total needle and branchwood dry mass of trees is estimated. Based on that, stand or regional parameters for the allometric function between diameter breast height and needle respectively branchwood dry mass can be determined for defined H/D-clusters. Published data from various sources were used in this paper. The lowest coefficients of determination were found in H/D-cluster 120 (H/D-values over 114). Therefore, further differentiation within this range seems to be necessary. For assimilation models, there should be quantification of needle dry mass separately for needle age classes and morphological characteristics of needles. Basis for the estimate of tree-bole volume is the relationship between H/D-value and oven-dry weight. There are problems as far as methods for quantifying the subterranean dendromass (e.g. dynamics of fine roots) are concerned; this is requiring considerable efforts, too. Spatial structure was also described by allometric functions (crown length and crown cover in relation to diameter breast height). For the partial model to express wind modification by the stand, standardized wind profiles as related to crown canopy density were used. The modification of radiation by the stand is closely related with the vertical needle mass distribution (sum curves). These two partial models have to be considered as an approach for the description of the modifying effect by the stocking [de

Partial discharge transients and the influence of dielectric polarization

DEFF Research Database (Denmark)

Pedersen, A.; Crichton, George C; McAllister, Iain Wilson

1996-01-01

Based on a field-theoretical approach, a physically valid theory of partial discharge transients has been developed. The theory is based upon the concept of the charge induced upon the detecting electrode by the partial discharge. This induced charge is shown to be composed of a component...

Real Time Engineering Analysis Based on a Generative Component Implementation

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Klitgaard, Jens

2007-01-01

The present paper outlines the idea of a conceptual design tool with real time engineering analysis which can be used in the early conceptual design phase. The tool is based on a parametric approach using Generative Components with embedded structural analysis. Each of these components uses the g...

An evaluation of directional analysis techniques for multidirectional, partially reflected waves .1. numerical investigations

DEFF Research Database (Denmark)

Ilic, C; Chadwick, A; Helm-Petersen, Jacob

2000-01-01

, non-phased locked methods are more appropriate. In this paper, the accuracy of two non-phased locked methods of directional analysis, the maximum likelihood method (MLM) and the Bayesian directional method (BDM) have been quantitatively evaluated using numerical simulations for the case...... of multidirectional waves with partial reflections. It is shown that the results are influenced by the ratio of distance from the reflector (L) to the length of the time series (S) used in the spectral analysis. Both methods are found to be capable of determining the incident and reflective wave fields when US > 0......Recent studies of advanced directional analysis techniques have mainly centred on incident wave fields. In the study of coastal structures, however, partially reflective wave fields are commonly present. In the near structure field, phase locked methods can be successfully applied. In the far field...

Abstract Interfaces for Data Analysis Component Architecture for Data Analysis Tools

CERN Document Server

Barrand, G; Dönszelmann, M; Johnson, A; Pfeiffer, A

2001-01-01

The fast turnover of software technologies, in particular in the domain of interactivity (covering user interface and visualisation), makes it difficult for a small group of people to produce complete and polished software-tools before the underlying technologies make them obsolete. At the HepVis '99 workshop, a working group has been formed to improve the production of software tools for data analysis in HENP. Beside promoting a distributed development organisation, one goal of the group is to systematically design a set of abstract interfaces based on using modern OO analysis and OO design techniques. An initial domain analysis has come up with several categories (components) found in typical data analysis tools: Histograms, Ntuples, Functions, Vectors, Fitter, Plotter, Analyzer and Controller. Special emphasis was put on reducing the couplings between the categories to a minimum, thus optimising re-use and maintainability of any component individually. The interfaces have been defined in Java and C++ and i...

Component Analysis of Long-Lag, Wide-Pulse Gamma-Ray Burst ...

Indian Academy of Sciences (India)

Principal Component Analysis of Long-Lag, Wide-Pulse Gamma-Ray. Burst Data. Zhao-Yang Peng. ∗. & Wen-Shuai Liu. Department of Physics, Yunnan Normal University, Kunming 650500, China. ∗ e-mail: pzy@ynao.ac.cn. Abstract. We have carried out a Principal Component Analysis (PCA) of the temporal and spectral ...

Logical Specification and Analysis of Fault Tolerant Systems through Partial Model Checking

NARCIS (Netherlands)

Gnesi, S.; Etalle, Sandro; Mukhopadhyay, S.; Lenzini, Gabriele; Lenzini, G.; Martinelli, F.; Roychoudhury, A.

2003-01-01

This paper presents a framework for a logical characterisation of fault tolerance and its formal analysis based on partial model checking techniques. The framework requires a fault tolerant system to be modelled using a formal calculus, here the CCS process algebra. To this aim we propose a uniform

Modular Accident Analysis Program (MAAP) - MELCOR Crosswalk: Phase II Analyzing a Partially Recovered Accident Scenario

Energy Technology Data Exchange (ETDEWEB)

Andrews, Nathan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Faucett, Christopher [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Haskin, Troy Christopher [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Luxat, Dave [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Geiger, Garrett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Codella, Brittany [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-10-01

Following the conclusion of the first phase of the crosswalk analysis, one of the key unanswered questions was whether or not the deviations found would persist during a partially recovered accident scenario, similar to the one that occurred in TMI - 2. In particular this analysis aims to compare the impact of core degradation morphology on quenching models inherent within the two codes and the coolability of debris during partially recovered accidents. A primary motivation for this study is the development of insights into how uncertainties in core damage progression models impact the ability to assess the potential for recovery of a degraded core. These quench and core recovery models are of the most interest when there is a significant amount of core damage, but intact and degraded fuel still remain in the cor e region or the lower plenum. Accordingly this analysis presents a spectrum of partially recovered accident scenarios by varying both water injection timing and rate to highlight the impact of core degradation phenomena on recovered accident scenarios. This analysis uses the newly released MELCOR 2.2 rev. 966 5 and MAAP5, Version 5.04. These code versions, which incorporate a significant number of modifications that have been driven by analyses and forensic evidence obtained from the Fukushima - Daiichi reactor site.

Patterns of Failure After MammoSite Brachytherapy Partial Breast Irradiation: A Detailed Analysis

International Nuclear Information System (INIS)

Chen, Sea; Dickler, Adam; Kirk, Michael; Shah, Anand; Jokich, Peter; Solmos, Gene; Strauss, Jonathan; Dowlatshahi, Kambiz; Nguyen, Cam; Griem, Katherine

2007-01-01

Purpose: To report the results of a detailed analysis of treatment failures after MammoSite breast brachytherapy for partial breast irradiation from our single-institution experience. Methods and Materials: Between October 14, 2002 and October 23, 2006, 78 patients with early-stage breast cancer were treated with breast-conserving surgery and accelerated partial breast irradiation using the MammoSite brachytherapy applicator. We identified five treatment failures in the 70 patients with >6 months' follow-up. Pathologic data, breast imaging, and radiation treatment plans were reviewed. For in-breast failures more than 2 cm away from the original surgical bed, the doses delivered to the areas of recurrence by partial breast irradiation were calculated. Results: At a median follow-up time of 26.1 months, five treatment failures were identified. There were three in-breast failures more than 2 cm away from the original surgical bed, one failure directly adjacent to the original surgical bed, and one failure in the axilla with synchronous distant metastases. The crude failure rate was 7.1% (5 of 70), and the crude local failure rate was 5.7% (4 of 70). Estimated progression-free survival at 48 months was 89.8% (standard error 4.5%). Conclusions: Our case series of 70 patients with >6 months' follow-up and a median follow-up of 26 months is the largest single-institution report to date with detailed failure analysis associated with MammoSite brachytherapy. Our failure data emphasize the importance of patient selection when offering partial breast irradiation

Use of Sparse Principal Component Analysis (SPCA) for Fault Detection

DEFF Research Database (Denmark)

Gajjar, Shriram; Kulahci, Murat; Palazoglu, Ahmet

2016-01-01

Principal component analysis (PCA) has been widely used for data dimension reduction and process fault detection. However, interpreting the principal components and the outcomes of PCA-based monitoring techniques is a challenging task since each principal component is a linear combination of the ...

Integrating Data Transformation in Principal Components Analysis

KAUST Repository

Maadooliat, Mehdi; Huang, Jianhua Z.; Hu, Jianhua

2015-01-01

Principal component analysis (PCA) is a popular dimension reduction method to reduce the complexity and obtain the informative aspects of high-dimensional datasets. When the data distribution is skewed, data transformation is commonly used prior

NEPR Principle Component Analysis - NOAA TIFF Image

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a representation of seafloor topography in Northeast Puerto Rico derived from a bathymetry model with a principle component analysis (PCA). The area...

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.

PCA: Principal Component Analysis for spectra modeling

Science.gov (United States)

Hurley, Peter D.; Oliver, Seb; Farrah, Duncan; Wang, Lingyu; Efstathiou, Andreas

2012-07-01

The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components. This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.

BUSINESS PROCESS MANAGEMENT SYSTEMS TECHNOLOGY COMPONENTS ANALYSIS

Directory of Open Access Journals (Sweden)

Andrea Giovanni Spelta

2007-05-01

Full Text Available The information technology that supports the implementation of the business process management appproach is called Business Process Management System (BPMS. The main components of the BPMS solution framework are process definition repository, process instances repository, transaction manager, conectors framework, process engine and middleware. In this paper we define and characterize the role and importance of the components of BPMS's framework. The research method adopted was the case study, through the analysis of the implementation of the BPMS solution in an insurance company called Chubb do Brasil. In the case study, the process "Manage Coinsured Events"" is described and characterized, as well as the components of the BPMS solution adopted and implemented by Chubb do Brasil for managing this process.

Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin

Science.gov (United States)

zhangli, Sun; xiufang, Zhu; yaozhong, Pan

2016-04-01

Accurate estimation of flood frequency is key to effective, nationwide flood damage abatement programs. The partial duration series (PDS) method is widely used in hydrologic studies because it considers all events above a certain threshold level as compared to the annual maximum series (AMS) method, which considers only the annual maximum value. However, the PDS has a drawback in that it is difficult to define the thresholds and maintain an independent and identical distribution of the partial duration time series; this drawback is discussed in this paper. The Ganjiang River is the seventh largest tributary of the Yangtze River, the longest river in China. The Ganjiang River covers a drainage area of 81,258 km2 at the Wanzhou hydrologic station as the basin outlet. In this work, 56 years of daily flow data (1954-2009) from the Wanzhou station were used to analyze flood frequency, and the Pearson-III model was employed as the hydrologic probability distribution. Generally, three tasks were accomplished: (1) the threshold of PDS by percentile rank of daily runoff was obtained; (2) trend analysis of the flow series was conducted using PDS; and (3) flood frequency analysis was conducted for partial duration flow series. The results showed a slight upward trend of the annual runoff in the Ganjiang River basin. The maximum flow with a 0.01 exceedance probability (corresponding to a 100-year flood peak under stationary conditions) was 20,000 m3/s, while that with a 0.1 exceedance probability was 15,000 m3/s. These results will serve as a guide to hydrological engineering planning, design, and management for policymakers and decision makers associated with hydrology.

Economical analysis of the second partial reload for Angra 1 with partial low-leakage

International Nuclear Information System (INIS)

Mascarenhas, H.A.; Teixeira, M.C.C.; Dias, A.M.

1990-01-01

Preliminary results for the Angra 1 second reload design with partial low-leakage were assessed with NUCOST 1.0, code for nuclear power costs calculation. In the proposed scheme, some partially burned fuel assemblies (FAs) are located at the core boundary, while new FAs occupy more internal positions. The nuclear design - utilizing the code system SAV (from Siemens/KWU Group, F.R. Germany) - has been performed with detail for the 3rd cycle while simpler approach has been utilized for subsequent reloads. Results of NUCOST 1.0 show that the partial low-leakage reload in the 3rd cycle of Angra 1 offers fuel costs 1% lower when compared to the Plant's actual reload scheme, what corresponds to an savings of about US$190.000. When operation and maintenance and capital costs are also considered, economies in the order of US$2.6 million are obrained. (author) [pt

Differential equation analysis in biomedical science and engineering partial differential equation applications with R

CERN Document Server

Schiesser, William E

2014-01-01

Features a solid foundation of mathematical and computational tools to formulate and solve real-world PDE problems across various fields With a step-by-step approach to solving partial differential equations (PDEs), Differential Equation Analysis in Biomedical Science and Engineering: Partial Differential Equation Applications with R successfully applies computational techniques for solving real-world PDE problems that are found in a variety of fields, including chemistry, physics, biology, and physiology. The book provides readers with the necessary knowledge to reproduce and extend the com

Efficacy of the Principal Components Analysis Techniques Using ...

African Journals Online (AJOL)

Second, the paper reports results of principal components analysis after the artificial data were submitted to three commonly used procedures; scree plot, Kaiser rule, and modified Horn's parallel analysis, and demonstrate the pedagogical utility of using artificial data in teaching advanced quantitative concepts. The results ...

Functional Generalized Structured Component Analysis.

Science.gov (United States)

Suk, Hye Won; Hwang, Heungsun

2016-12-01

An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA wastewater data

Directory of Open Access Journals (Sweden)

Stefania Salvatore

2016-07-01

Full Text Available Abstract Background Wastewater-based epidemiology (WBE is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA and to wavelet principal component analysis (WPCA which is more flexible temporally. Methods We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. Results The first three principal components (PCs, functional principal components (FPCs and wavelet principal components (WPCs explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. Conclusion FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

Study of NΣ cusp in p+p → p+K{sup +}+Λ with partial wave analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, S.; Muenzer, R.; Epple, E.; Fabbietti, L. [Excellenz Cluster Universe, Technische Universitaet Muenchen (Germany); Ritman, J.; Roderburg, E.; Hauenstein, F. [FZ Juelich (Germany); Collaboration: Hades and FOPI Collaboration

2016-07-01

In the last years, an analysis of exclusive reaction of p+p → p+K{sup +}+Λ has been carried out using Bonn-Gatchina Partial Wave Analysis. In a combined analysis of data from Hades, Fopi, Disto and Cosy-TOF, an energy dependent production process is determined. This analysis has shown that a sufficient description of the p+p → p+K{sup +}+Λ is quite challenging due to the presence of resonances N* and interference, which requires Partial Wave Analysis. A pronounced narrow structure is observed in its projection on the pΛ-invariant mass. This peak structure, which appears around the NΣ threshold, has a strongly asymmetric structure and is interpreted a NΣ cusp effect. In this talk, the results from a combined analysis will be shown, with a special focus on the NΣ cusp structure and a description using Flatte parametrization.

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.

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

Microstrip natural wave spectrum mathematical model using partial inversion method

International Nuclear Information System (INIS)

Pogarsky, S.A.; Litvinenko, L.N.; Prosvirnin, S.L.

1995-01-01

It is generally agreed that both microstrip lines itself and different discontinuities based on microstrips are the most difficult problem for accurate electrodynamic analysis. Over the last years much has been published about principles and accurate (or full wave) methods of microstrip lines investigations. The growing interest for this problem may be explained by the microstrip application in the millimeter-wave range for purpose of realizing interconnects and a variety of passive components. At these higher operating rating frequencies accurate component modeling becomes more critical. A creation, examination and experimental verification of the accurate method for planar electrodynamical structures natural wave spectrum investigations are the objects of this manuscript. The moment method with partial inversion operator method using may be considered as a basical way for solving this problem. This method is outlook for accurate analysis of different planar discontinuities in microstrip: such as step discontinuities, microstrip turns, Y- and X-junctions and etc., substrate space steps dielectric constants and other anisotropy types

3-D fracture analysis using a partial-reduced integration scheme

International Nuclear Information System (INIS)

Leitch, B.W.

1987-01-01

This paper presents details of 3-D elastic-plastic analyses of axially orientated external surface flaw in an internally pressurized thin-walled cylinder and discusses the variation of the J-integral values around the crack tip. A partial-reduced-integration-penalty method is introduced to minimize this variation of the J-integral near the crack tip. Utilizing 3-D symmetry, an eighth segment of a tube containing an elliptically shaped external surface flaw is modelled using 20-noded isoparametric elements. The crack-tip elements are collapsed to form a 1/r stress singularity about the curved crack front. The finite element model is subjected to internal pressure and axial pressure-generated loads. The virtual crack extension method is used to determine linear elastic stress intensity factors from the J-integral results at various points around the crack front. Despite the different material constants and the thinner wall thickness in this analysis, the elastic results compare favourably with those obtained by other researchers. The nonlinear stress-strain behaviour of the tube material is modelled using an incremental theory of plasticity. Variations of the J-integral values around the curved crack front of the 3-D flaw were seen. These variations could not be resolved by neglecting the immediate crack-tip elements J-integral results in favour of the more remote contour paths or else smoothed out when all the path results are averaged. Numerical incompatabilities in the 20-noded 3-D finite elements used to model the surface flaw were found. A partial-reduced integration scheme, using a combination of full and reduced integration elements, is proposed to determine J-integral results for 3-D fracture analyses. This procedure is applied to the analysis of an external semicircular surface flaw projecting halfway into the tube wall thickness. Examples of the J-integral values, before and after the partial-reduced integration method is employed, are given around the

Fault Localization for Synchrophasor Data using Kernel Principal Component Analysis

Directory of Open Access Journals (Sweden)

CHEN, R.

2017-11-01

Full Text Available In this paper, based on Kernel Principal Component Analysis (KPCA of Phasor Measurement Units (PMU data, a nonlinear method is proposed for fault location in complex power systems. Resorting to the scaling factor, the derivative for a polynomial kernel is obtained. Then, the contribution of each variable to the T2 statistic is derived to determine whether a bus is the fault component. Compared to the previous Principal Component Analysis (PCA based methods, the novel version can combat the characteristic of strong nonlinearity, and provide the precise identification of fault location. Computer simulations are conducted to demonstrate the improved performance in recognizing the fault component and evaluating its propagation across the system based on the proposed method.

An analysis of the nucleon spectrum from lattice partially-quenched QCD.

Energy Technology Data Exchange (ETDEWEB)

Armour, W.; Allton, C. R.; Leinweber, D. B.; Thomas, A. W.; Young, R. D.; Physics; Swansea Univ.; Univ. of Adelaide; Coll. of William and Mary

2010-09-01

The chiral extrapolation of the nucleon mass, M{sub n}, is investigated using data coming from 2-flavour partially-quenched lattice simulations. A large sample of lattice results from the CP-PACS Collaboration is analysed using the leading one-loop corrections, with explicit corrections for finite lattice spacing artifacts. The extrapolation is studied using finite-range regularised chiral perturbation theory. The analysis also provides a quantitative estimate of the leading finite volume corrections. It is found that the discretisation, finite volume and partial quenching effects can all be very well described in this framework, producing an extrapolated value of Mn in agreement with experiment. Furthermore, determinations of the low energy constants of the nucleon mass's chiral expansion are in agreement with previous methods, but with significantly reduced errors. This procedure is also compared with extrapolations based on polynomial forms, where the results are less encouraging.

An analysis of the nucleon spectrum from lattice partially-quenched QCD

Energy Technology Data Exchange (ETDEWEB)

Armour, W. [Department of Physics, Swansea University, Swansea SA2 8PP, Wales (United Kingdom); Allton, C.R., E-mail: c.allton@swan.ac.u [Department of Physics, Swansea University, Swansea SA2 8PP, Wales (United Kingdom); Leinweber, D.B. [Special Research Centre for the Subatomic Structure of Matter (CSSM), School of Chemistry and Physics, University of Adelaide, 5005 (Australia); Thomas, A.W. [Jefferson Lab, 12000 Jefferson Ave., Newport News, VA 23606 (United States); College of William and Mary, Williamsburg, VA 23187 (United States); Young, R.D. [Physics Division, Argonne National Laboratory, Argonne, IL 60439 (United States)

2010-09-01

The chiral extrapolation of the nucleon mass, M{sub n}, is investigated using data coming from 2-flavour partially-quenched lattice simulations. A large sample of lattice results from the CP-PACS Collaboration is analysed using the leading one-loop corrections, with explicit corrections for finite lattice spacing artifacts. The extrapolation is studied using finite-range regularised chiral perturbation theory. The analysis also provides a quantitative estimate of the leading finite volume corrections. It is found that the discretisation, finite volume and partial quenching effects can all be very well described in this framework, producing an extrapolated value of M{sub n} in agreement with experiment. Furthermore, determinations of the low energy constants of the nucleon mass's chiral expansion are in agreement with previous methods, but with significantly reduced errors. This procedure is also compared with extrapolations based on polynomial forms, where the results are less encouraging.

Advanced BWR core component designs and the implications for SFD analysis

International Nuclear Information System (INIS)

Ott, L.J.

1997-01-01

Prior to the DF-4 boiling water reactor (BWR) severe fuel damage (SFD) experiment conducted at the Sandia National Laboratories in 1986, no experimental data base existed for guidance in modeling core component behavior under postulated severe accident conditions in commercial BWRs. This paper will present the lessons learned from the DF-4 experiment (and subsequent German CORA BWR SFD tests) and the impact on core models in the current generation of SFD codes. The DF-4 and CORA BWR test assemblies were modeled on the core component designs circa 1985; that is, the 8 x 8 fuel assembly with two water rods and a cruciform control blade constructed of B 4 C-filled tubelets. Within the past ten years, the state-of-the-art with respect to BWR core component development has out-distanced the current SFD experimental data base and SFD code capabilities. For example, modern BWR control blade design includes hafnium at the tips and top of each control blade wing for longer blade operating lifetimes; also water rods have been replaced by larger water channels for better neutronics economy; and fuel assemblies now contain partial-length fuel rods, again for better neutronics economy. This paper will also discuss the implications of these advanced fuel assembly and core component designs on severe accident progression and on the current SFD code capabilities

Component effects in mixture experiments

International Nuclear Information System (INIS)

Piepel, G.F.

1980-01-01

In a mixture experiment, the response to a mixture of q components is a function of the proportions x 1 , x 2 , ..., x/sub q/ of components in the mixture. Experimental regions for mixture experiments are often defined by constraints on the proportions of the components forming the mixture. The usual (orthogonal direction) definition of a factor effect does not apply because of the dependence imposed by the mixture restriction, /sup q/Σ/sub i=1/ x/sub i/ = 1. A direction within the experimental region in which to compute a mixture component effect is presented and compared to previously suggested directions. This new direction has none of the inadequacies or errors of previous suggestions while having a more meaningful interpretation. The distinction between partial and total effects is made. The uses of partial and total effects (computed using the new direction) in modification and interpretation of mixture response prediction equations are considered. The suggestions of the paper are illustrated in an example from a glass development study in a waste vitrification program. 5 figures, 3 tables

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.

Partial volume effect in MRI

International Nuclear Information System (INIS)

Maeda, Munehiro; Yoshiya, Kazuhiko; Suzuki, Eiji

1989-01-01

According to the direction and the thickness of the imaging slice in tomography, the border between the tissues becomes unclear (partial volume effect). In the present MRI experiment, we examined border area between fat and water components using phantom in order to investigate the partial volume effect in MRI. In spin echo sequences, the intensity of the border area showed a linear relationship with composition of fat and water. Whereas, in inversion recovery and field echo sequences, we found the parameters to produce an extremely low intensity area at the border region between fat and water. This low intensity area was explained by cancellation of NMR signals from fat and water due to the difference in the direction of magnetic vectors. Clinically, partial volume effect can cause of mis-evaluation of walls, small nodules, tumor capsules and the tumor invasion in the use of inversion recovery and field echo sequences. (author)

Experimental modal analysis of components of the LHC experiments

CERN Document Server

Guinchard, M; Catinaccio, A; Kershaw, K; Onnela, A

2007-01-01

Experimental modal analysis of components of the LHC experiments is performed with the purpose of determining their fundamental frequencies, their damping and the mode shapes of light and fragile detector components. This process permits to confirm or replace Finite Element analysis in the case of complex structures (with cables and substructure coupling). It helps solving structural mechanical problems to improve the operational stability and determine the acceleration specifications for transport operations. This paper describes the hardware and software equipment used to perform a modal analysis on particular structures such as a particle detector and the method of curve fitting to extract the results of the measurements. This paper exposes also the main results obtained for the LHC Experiments.

PEMBUATAN PERANGKAT LUNAK PENGENALAN WAJAH MENGGUNAKAN PRINCIPAL COMPONENTS ANALYSIS

Directory of Open Access Journals (Sweden)

Kartika Gunadi

2001-01-01

Full Text Available Face recognition is one of many important researches, and today, many applications have implemented it. Through development of techniques like Principal Components Analysis (PCA, computers can now outperform human in many face recognition tasks, particularly those in which large database of faces must be searched. Principal Components Analysis was used to reduce facial image dimension into fewer variables, which are easier to observe and handle. Those variables then fed into artificial neural networks using backpropagation method to recognise the given facial image. The test results show that PCA can provide high face recognition accuracy. For the training faces, a correct identification of 100% could be obtained. From some of network combinations that have been tested, a best average correct identification of 91,11% could be obtained for the test faces while the worst average result is 46,67 % correct identification Abstract in Bahasa Indonesia : Pengenalan wajah manusia merupakan salah satu bidang penelitian yang penting, dan dewasa ini banyak aplikasi yang dapat menerapkannya. Melalui pengembangan suatu teknik seperti Principal Components Analysis (PCA, komputer sekarang dapat melebihi kemampuan otak manusia dalam berbagai tugas pengenalan wajah, terutama tugas-tugas yang membutuhkan pencarian pada database wajah yang besar. Principal Components Analysis digunakan untuk mereduksi dimensi gambar wajah sehingga menghasilkan variabel yang lebih sedikit yang lebih mudah untuk diobsevasi dan ditangani. Hasil yang diperoleh kemudian akan dimasukkan ke suatu jaringan saraf tiruan dengan metode Backpropagation untuk mengenali gambar wajah yang telah diinputkan ke dalam sistem. Hasil pengujian sistem menunjukkan bahwa penggunaan PCA untuk pengenalan wajah dapat memberikan tingkat akurasi yang cukup tinggi. Untuk gambar wajah yang diikutsertakankan dalam latihan, dapat diperoleh 100% identifikasi yang benar. Dari beberapa kombinasi jaringan yang

Oil classification using X-ray scattering and principal component analysis

Energy Technology Data Exchange (ETDEWEB)

Almeida, Danielle S.; Souza, Amanda S.; Lopes, Ricardo T., E-mail: dani.almeida84@gmail.com, E-mail: ricardo@lin.ufrj.br, E-mail: amandass@bioqmed.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil); Oliveira, Davi F.; Anjos, Marcelino J., E-mail: davi.oliveira@uerj.br, E-mail: marcelin@uerj.br [Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ (Brazil). Inst. de Fisica Armando Dias Tavares

2015-07-01

X-ray scattering techniques have been considered promising for the classification and characterization of many types of samples. This study employed this technique combined with chemical analysis and multivariate analysis to characterize 54 vegetable oil samples (being 25 olive oils)with different properties obtained in commercial establishments in Rio de Janeiro city. The samples were chemically analyzed using the following indexes: iodine, acidity, saponification and peroxide. In order to obtain the X-ray scattering spectrum, an X-ray tube with a silver anode operating at 40kV and 50 μA was used. The results showed that oils cab ne divided in tow large groups: olive oils and non-olive oils. Additionally, in a multivariate analysis (Principal Component Analysis - PCA), two components were obtained and accounted for more than 80% of the variance. One component was associated with chemical parameters and the other with scattering profiles of each sample. Results showed that use of X-ray scattering spectra combined with chemical analysis and PCA can be a fast, cheap and efficient method for vegetable oil characterization. (author)

Oil classification using X-ray scattering and principal component analysis

International Nuclear Information System (INIS)

Almeida, Danielle S.; Souza, Amanda S.; Lopes, Ricardo T.; Oliveira, Davi F.; Anjos, Marcelino J.

2015-01-01

X-ray scattering techniques have been considered promising for the classification and characterization of many types of samples. This study employed this technique combined with chemical analysis and multivariate analysis to characterize 54 vegetable oil samples (being 25 olive oils)with different properties obtained in commercial establishments in Rio de Janeiro city. The samples were chemically analyzed using the following indexes: iodine, acidity, saponification and peroxide. In order to obtain the X-ray scattering spectrum, an X-ray tube with a silver anode operating at 40kV and 50 μA was used. The results showed that oils cab ne divided in tow large groups: olive oils and non-olive oils. Additionally, in a multivariate analysis (Principal Component Analysis - PCA), two components were obtained and accounted for more than 80% of the variance. One component was associated with chemical parameters and the other with scattering profiles of each sample. Results showed that use of X-ray scattering spectra combined with chemical analysis and PCA can be a fast, cheap and efficient method for vegetable oil characterization. (author)

Prestudy - Development of trend analysis of component failure

International Nuclear Information System (INIS)

Poern, K.

1995-04-01

The Bayesian trend analysis model that has been used for the computation of initiating event intensities (I-book) is based on the number of events that have occurred during consecutive time intervals. The model itself is a Poisson process with time-dependent intensity. For the analysis of aging it is often more relevant to use times between failures for a given component as input, where by 'time' is meant a quantity that best characterizes the age of the component (calendar time, operating time, number of activations etc). Therefore, it has been considered necessary to extend the model and the computer code to allow trend analysis of times between events, and also of several sequences of times between events. This report describes this model extension as well as an application on an introductory ageing analysis of centrifugal pumps defined in Table 5 of the T-book. The application in turn directs the attention to the need for further development of both the trend model and the data base. Figs

On continuous ambiguities in model-independent partial wave analysis - 1

International Nuclear Information System (INIS)

Nikitin, I.N.

1995-01-01

A problem of amplitude reconstruction in terms of the given angular distribution is considered. Solution of this problem is not unique. A class of amplitudes, correspondent to one and the same angular distribution, forms a region in projection onto a finite set of spherical harmonics. An explicit parametrization of a boundary of the region is obtained. A shape of the region of ambiguities is studied in particular example. A scheme of partial-wave analysis, which describes all solutions in the limits of the region, is proposed. 5 refs., 5 figs

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...

Experimental and principal component analysis of waste ...

African Journals Online (AJOL)

The present study is aimed at determining through principal component analysis the most important variables affecting bacterial degradation in ponds. Data were collected from literature. In addition, samples were also collected from the waste stabilization ponds at the University of Nigeria, Nsukka and analyzed to ...

Fatigue Reliability Analysis of Wind Turbine Cast Components

DEFF Research Database (Denmark)

Rafsanjani, Hesam Mirzaei; Sørensen, John Dalsgaard; Fæster, Søren

2017-01-01

.) and to quantify the relevant uncertainties using available fatigue tests. Illustrative results are presented as obtained by statistical analysis of a large set of fatigue data for casted test components typically used for wind turbines. Furthermore, the SN curves (fatigue life curves based on applied stress......The fatigue life of wind turbine cast components, such as the main shaft in a drivetrain, is generally determined by defects from the casting process. These defects may reduce the fatigue life and they are generally distributed randomly in components. The foundries, cutting facilities and test...... facilities can affect the verification of properties by testing. Hence, it is important to have a tool to identify which foundry, cutting and/or test facility produces components which, based on the relevant uncertainties, have the largest expected fatigue life or, alternatively, have the largest reliability...

Topics in numerical partial differential equations and scientific computing

CERN Document Server

2016-01-01

Numerical partial differential equations (PDEs) are an important part of numerical simulation, the third component of the modern methodology for science and engineering, besides the traditional theory and experiment. This volume contains papers that originated with the collaborative research of the teams that participated in the IMA Workshop for Women in Applied Mathematics: Numerical Partial Differential Equations and Scientific Computing in August 2014.

OUTLIER DETECTION IN PARTIAL ERRORS-IN-VARIABLES MODEL

Directory of Open Access Journals (Sweden)

JUN ZHAO

Full Text Available The weighed total least square (WTLS estimate is very sensitive to the outliers in the partial EIV model. A new procedure for detecting outliers based on the data-snooping is presented in this paper. Firstly, a two-step iterated method of computing the WTLS estimates for the partial EIV model based on the standard LS theory is proposed. Secondly, the corresponding w-test statistics are constructed to detect outliers while the observations and coefficient matrix are contaminated with outliers, and a specific algorithm for detecting outliers is suggested. When the variance factor is unknown, it may be estimated by the least median squares (LMS method. At last, the simulated data and real data about two-dimensional affine transformation are analyzed. The numerical results show that the new test procedure is able to judge that the outliers locate in x component, y component or both components in coordinates while the observations and coefficient matrix are contaminated with outliers

Root cause analysis in support of reliability enhancement of engineering components

International Nuclear Information System (INIS)

Kumar, Sachin; Mishra, Vivek; Joshi, N.S.; Varde, P.V.

2014-01-01

Reliability based methods have been widely used for the safety assessment of plant system, structures and components. These methods provide a quantitative estimation of system reliability but do not give insight into the failure mechanism. Understanding the failure mechanism is a must to avoid the recurrence of the events and enhancement of the system reliability. Root cause analysis provides a tool for gaining detailed insights into the causes of failure of component with particular attention to the identification of fault in component design, operation, surveillance, maintenance, training, procedures and policies which must be improved to prevent repetition of incidents. Root cause analysis also helps in developing Probabilistic Safety Analysis models. A probabilistic precursor study provides a complement to the root cause analysis approach in event analysis by focusing on how an event might have developed adversely. This paper discusses the root cause analysis methodologies and their application in the specific case studies for enhancement of system reliability. (author)

Clustering stocks using partial correlation coefficients

Science.gov (United States)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

A Partially Saturated Constitutive Theory for Compacted Fills

National Research Council Canada - National Science Library

Berney, Ernest

2004-01-01

... variables present within the soil. From a thermodynamic viewpoint, a partially saturated soil can be best described by the free energy associated with each component of the soil and water mixture...

Thermodynamic analysis of a coal-based polygeneration system with partial gasification

International Nuclear Information System (INIS)

Li, Yuanyuan; Zhang, Guoqiang; Yang, Yongping; Zhai, Dailong; Zhang, Kai; Xu, Gang

2014-01-01

This study proposed a polygeneration system based on coal partial gasification, in which methanol and power were generated. This proposed system, comprising chemical and power islands, was designed and its characteristics are analyzed. The commercial software Aspen Plus was used to perform the system analysis. In the case study, the energy and exergy efficiency values of the proposed polygeneration system were 51.16% and 50.58%, which are 2.34% and 2.10%, respectively, higher than that of the reference system. Energy-Utilization Diagram analysis showed that removing composition adjustment and recycling 72.7% of the unreacted gas could reduce the exergy destruction during methanol synthesis by 46.85% and that the char utilized to preheat the compressed air could reduce the exergy destruction during combustion by 10.28%. Sensitivity analysis was also performed. At the same capacity ratio, the energy and exergy efficiency values of the proposed system were 1.30%–2.48% and 1.21%–2.30% higher than that of the reference system, respectively. The range of chemical-to-power capacity ratio in the proposed system was 0.41–1.40, which was narrower than that in the reference system. But the range of 1.04–1.4 was not recommended for the disappearance of energy saving potential in methanol synthesis. - Highlights: • A novel polygeneration system based on coal partial gasification is proposed. • The efficient conversion method for methanol and power is explored. • The exergy destruction in chemical energy conversion processes is decreased. • Thermodynamic performance and system characteristics are analyzed

Measurement of activated rCBF by the 133Xe inhalation technique: a comparison of total versus partial curve analysis

International Nuclear Information System (INIS)

Leli, D.A.; Katholi, C.R.; Hazelrig, J.B.; Falgout, J.C.; Hannay, H.J.; Wilson, E.M.; Wills, E.L.; Halsey, J.H. Jr.

1985-01-01

An initial assessment of the differential sensitivity of total versus partial curve analysis in estimating task related focal changes in cortical blood flow measured by the 133 Xe inhalation technique was accomplished by comparing the patterns during the performance of two sensorimotor tasks by normal subjects. The validity of these patterns was evaluated by comparing them to the activation patterns expected from activation studies with the intra-arterial technique and the patterns expected from neuropsychological research literature. Subjects were 10 young adult nonsmoking healthy male volunteers. They were administered two tasks having identical sensory and cognitive components but different response requirements (oral versus manual). The regional activation patterns produced by the tasks varied with the method of curve analysis. The activation produced by the two tasks was very similar to that predicted from the research literature only for total curve analysis. To the extent that the predictions are correct, these data suggest that the 133 Xe inhalation technique is more sensitive to regional flow changes when flow parameters are estimated from the total head curve. The utility of the total head curve analysis will be strengthened if similar sensitivity is demonstrated in future studies assessing normal subjects and patients with neurological and psychiatric disorders

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)

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

Analysis of pumping tests: Significance of well diameter, partial penetration, and noise

Science.gov (United States)

Heidari, M.; Ghiassi, K.; Mehnert, E.

1999-01-01

The nonlinear least squares (NLS) method was applied to pumping and recovery aquifer test data in confined and unconfined aquifers with finite diameter and partially penetrating pumping wells, and with partially penetrating piezometers or observation wells. It was demonstrated that noiseless and moderately noisy drawdown data from observation points located less than two saturated thicknesses of the aquifer from the pumping well produced an exact or acceptable set of parameters when the diameter of the pumping well was included in the analysis. The accuracy of the estimated parameters, particularly that of specific storage, decreased with increases in the noise level in the observed drawdown data. With consideration of the well radii, the noiseless drawdown data from the pumping well in an unconfined aquifer produced good estimates of horizontal and vertical hydraulic conductivities and specific yield, but the estimated specific storage was unacceptable. When noisy data from the pumping well were used, an acceptable set of parameters was not obtained. Further experiments with noisy drawdown data in an unconfined aquifer revealed that when the well diameter was included in the analysis, hydraulic conductivity, specific yield and vertical hydraulic conductivity may be estimated rather effectively from piezometers located over a range of distances from the pumping well. Estimation of specific storage became less reliable for piezemeters located at distances greater than the initial saturated thickness of the aquifer. Application of the NLS to field pumping and recovery data from a confined aquifer showed that the estimated parameters from the two tests were in good agreement only when the well diameter was included in the analysis. Without consideration of well radii, the estimated values of hydraulic conductivity from the pumping and recovery tests were off by a factor of four.The nonlinear least squares method was applied to pumping and recovery aquifer test data in

Hospitalization for partial nephrectomy was not associated with intrathecal opioid analgesia: Retrospective analysis.

Science.gov (United States)

Weingarten, Toby N; Del Mundo, Serena B; Yeoh, Tze Yeng; Scavonetto, Federica; Leibovich, Bradley C; Sprung, Juraj

2014-10-01

The aim of this retrospective study is to test the hypothesis that the use of spinal analgesia shortens the length of hospital stay after partial nephrectomy. We reviewed all patients undergoing partial nephrectomy for malignancy through flank incision between January 1, 2008, and June 30, 2011. We excluded patients who underwent tumor thrombectomy, used sustained-release opioids, or had general anesthesia supplemented by epidural analgesia. Patients were grouped into "spinal" (intrathecal opioid injection for postoperative analgesia) versus "general anesthetic" group, and "early" discharge group (within 3 postoperative days) versus "late" group. Association between demographics, patient physical status, anesthetic techniques, and surgical complexity and hospital stay were analyzed using multivariable logistic regression analysis. Of 380 patients, 158 (41.6%) were discharged "early" and 151 (39.7%) were "spinal" cases. Both spinal and early discharge groups had better postoperative pain control and used less postoperative systemic opioids. Spinal analgesia was associated with early hospital discharge, odds ratio 1.52, (95% confidence interval 1.00-2.30), P = 0.05, but in adjusted analysis was no longer associated with early discharge, 1.16 (0.73-1.86), P = 0.52. Early discharge was associated with calendar year, with more recent years being associated with early discharge. Spinal analgesia combined with general anesthesia was associated with improved postoperative pain control during the 1(st) postoperative day, but not with shorter hospital stay following partial nephrectomy. Therefore, unaccounted practice changes that occurred during more recent times affected hospital stay.

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.

Relationship between partial and average atomic volumes of components in Au-Ni alloys%Au-Ni合金中组元的平均原子体积和偏摩尔体积的关系

Institute of Scientific and Technical Information of China (English)

谢佑卿

2011-01-01

在系统合金科学框架中建立有关无序合金的平均摩尔性质(体积和势能)的函数.通过对这些函数进行推导,可以得到平均摩尔体积函数、偏摩尔体积函数及派生出与成分相关的函数.在组元的偏摩尔性质和平均摩尔性质之间的普适方程、差分方程、在偏摩尔性质和平均摩尔性质之间不同参数的约束方程和普适的Gibbs-Duhem公式.可以证明从合金平均摩尔性质的不同函数计算的偏摩尔性质是相等的,但总体来说偏摩尔性质不等于给定组元的平均摩尔性质,即偏摩尔性质不能代表相应组元的摩尔性质.通过计算Au-Ni系中组元的偏摩尔体积和平均原子体积以及合金的平均原子体积,证明所建立的公式和函数的正确性.%In the framework of systematic science of alloys,the average molar property (volume and potential energy) functions of disordered alloys were established.From these functions,the average molar property functions,partial molar property functions,derivative functions with respect to composition,general equation of relationship between partial and average molar properties of components,difference equation and constraining equation of different values between partial and average molar properties,as well as general Gibbs-Duhem formula were derived.It was proved that the partial molar properties calculated from various combinative functions of average molar properties of alloys are equal,but in general,the partial molar properties are not equal to the average molar properties of a given component.This means that the partial molar properties cannot represent the corresponding properties of the component.All the equations and functions established in this work were proved to be correct by calculating the results of partial and average atomic volumes of components as well as average atomic volumes of alloys in the Au-Ni system.

Vibration analysis of partially cracked plate submerged in fluid

Science.gov (United States)

Soni, Shashank; Jain, N. K.; Joshi, P. V.

2018-01-01

The present work proposes an analytical model for vibration analysis of partially cracked rectangular plates coupled with fluid medium. The governing equation of motion for the isotropic plate based on the classical plate theory is modified to accommodate a part through continuous line crack according to simplified line spring model. The influence of surrounding fluid medium is incorporated in the governing equation in the form of inertia effects based on velocity potential function and Bernoulli's equations. Both partially and totally submerged plate configurations are considered. The governing equation also considers the in-plane stretching due to lateral deflection in the form of in-plane forces which introduces geometric non-linearity into the system. The fundamental frequencies are evaluated by expressing the lateral deflection in terms of modal functions. The assessment of the present results is carried out for intact submerged plate as to the best of the author's knowledge the literature lacks in analytical results for submerged cracked plates. New results for fundamental frequencies are presented as affected by crack length, fluid level, fluid density and immersed depth of plate. By employing the method of multiple scales, the frequency response and peak amplitude of the cracked structure is analyzed. The non-linear frequency response curves show the phenomenon of bending hardening or softening and the effect of fluid dynamic pressure on the response of the cracked plate.

Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market.

Science.gov (United States)

Kenett, Dror Y; Tumminello, Michele; Madi, Asaf; Gur-Gershgoren, Gitit; Mantegna, Rosario N; Ben-Jacob, Eshel

2010-12-20

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question--the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001-2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.

Partial wave analysis of KKPI system in D and E/IOTA region

International Nuclear Information System (INIS)

Chung, S.U.; Fernow, R.; Kirk, H.

1985-01-01

A partial wave analysis and a Dalitz plot analysis of high-statistics data from reaction π - p → K + K/sub S/π - n at 8.0 GeV/c show that the D(1285) is a J/sup PG/ = 1 ++ state and the E(1420) a J/sup PG/ = 0 -+ state both with a substantial deltaπ decay mode. The 1 ++ K*anti K wave exhibits a rapid rise near threshold but no evidence of a resonance in the E region. The assignment of J/sup PG/ = O -+ to the E is confirmed from a Dalitz-plot analysis of the reaction pp → K + K/sub S/π - X 0 . 11 refs., 5 figs

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 ...

UPLC-MS/MS analysis for antioxidant components of Lycii Fructus based on spectrum-effect relationship.

Science.gov (United States)

Zhang, Xian-Fei; Chen, Juan; Yang, Jun-Li; Shi, Yan-Ping

2018-04-01

Lycii Fructus is widely cultivated in the Northwest China. It is well-known for its antiaging effect in traditional Chinese medicines (TCMs), but the effective components are not clear. In this work, the ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was used to study the antioxidant components of Lycii Fructus through analyzing the spectrum-effect relationship, and the positive correlation components with antioxidant activity were partially identified. The extractums of Lycii Fructus were adsorbed with macroporous resin, and then eluted with water and 30%, 60%, 90% ethanol in turn. The extract fraction eluted with 60% ethanol was determined as the best, and was taken for subsequent experiments. With the above separation method, UPLC fingerprints of thirty batches of Lycii Fructus (from different areas) were obtained, and thirty common peaks were selected through similarity analysis (SA). Combined with the data of the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) assays, the spectrum-effect relationship was studied. The results showed that the main peaks with antioxidant activity were P14, P26, P8, and P21 for DPPH, and P26, P14, P21, and P19 for ABTS. Using the UPLC-MS/MS data, peaks P14, P19, P21, and P30 were respectively identified as chlorogenic acid, quercetin, kaempferol, and isorhamnetin, and then the results were confirmed through comparison with the standards and other references. Finally, their strong antioxidant activities were validated experimentally. Copyright © 2017 Elsevier B.V. All rights reserved.

Sparse logistic principal components analysis for binary data

KAUST Repository

Lee, Seokho

2010-09-01

We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of the success probabilities of the binary observations. Sparsity is introduced to the principal component (PC) loading vectors for enhanced interpretability and more stable extraction of the principal components. Our sparse PCA is formulated as solving an optimization problem with a criterion function motivated from a penalized Bernoulli likelihood. A Majorization-Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated by application to a single nucleotide polymorphism data set and a simulation study. © Institute ol Mathematical Statistics, 2010.

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

Science.gov (United States)

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides

Evaluation of metal-polymeric fixed partial prosthesis using optical coherence tomography

Science.gov (United States)

Sinescu, C.; Negrutiu, M. L.; Duma, V. F.; Marcauteanu, C.; Topala, F. I.; Rominu, M.; Bradu, A.; Podoleanu, A. Gh.

2013-11-01

Metal-Polymeric fixed partial prosthesis is the usual prosthetic treatment for many dental patients. However, during the mastication the polymeric component of the prosthesis is fractured and will be lost. This fracture is caused by the material defects or by the fracture lines trapped inside the esthetic components of the prosthesis. This will finally lead to the failure of the prosthetic treatment. Nowadays, there is no method of identification and forecast for the materials defects of the polymeric materials. The aim of this paper is to demonstrate the capability of Optical Coherence Tomography (OCT) as a non-invasive clinical method that can be used for the evaluation of metal-polymeric fixed partial prostheses. Twenty metal-polymeric fixed partial prostheses were used for this study. The esthetic component of the prostheses has been Adoro (Ivoclar). Optical investigations of the metal prostheses have revealed no material defects or fracture lines. All the prostheses were temporary cemented in the oral cavities of the patients for six month. The non-invasive method used for the investigations was OCT working in Time Domain mode at 1300 nm. The evaluations of the prostheses were performed before and after their cementation in the patient mouths. All the imagistic results were performed in 2D and than in 3D, after the reconstruction. The results obtained after the OCT evaluation allowed for the identification of 4 metal-polymeric fixed partial prostheses with material defects immediately after finishing the technological procedures. After 6 month in the oral environment other 3 fixed partial prostheses revealed fracture lines. In conclusion, OCT proved to be a valuable tool for the noninvasive evaluation of the metal-polymeric fixed partial prostheses.

Interpretable functional principal component analysis.

Science.gov (United States)

Lin, Zhenhua; Wang, Liangliang; Cao, Jiguo

2016-09-01

Functional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). The intervals where the values of FPCs are significant are interpreted as where sample curves have major variations. However, these intervals are often hard for naïve users to identify, because of the vague definition of "significant values". In this article, we develop a novel penalty-based method to derive FPCs that are only nonzero precisely in the intervals where the values of FPCs are significant, whence the derived FPCs possess better interpretability than the FPCs derived from existing methods. To compute the proposed FPCs, we devise an efficient algorithm based on projection deflation techniques. We show that the proposed interpretable FPCs are strongly consistent and asymptotically normal under mild conditions. Simulation studies confirm that with a competitive performance in explaining variations of sample curves, the proposed FPCs are more interpretable than the traditional counterparts. This advantage is demonstrated by analyzing two real datasets, namely, electroencephalography data and Canadian weather data. © 2015, The International Biometric Society.

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

Science.gov (United States)

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

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

Barrelet zeros and elastic π+p partial waves

International Nuclear Information System (INIS)

Chew, D.M.; Urban, M.

1976-06-01

A procedure is proposed for constructing low-order partial-wave amplitudes from a knowledge of Barrelet zeros near the physical region. The method is applied to the zeros already obtained for elastic π + p scattering data between 1.2 and 2.2 GeV cm energies. The partial waves emerge with errors that are straight-forwardly related to the accuracy of the data and satisfy unitarity without any constraint being imposed. There are significant differences from the partial waves obtained by other methods; this can be partially explained by the fact that no previous partial-wave analysis has been able to solve the discrete ambiguity. The cost of the analysis is much less

Development of computational methods of design by analysis for pressure vessel components

International Nuclear Information System (INIS)

Bao Shiyi; Zhou Yu; He Shuyan; Wu Honglin

2005-01-01

Stress classification is not only one of key steps when pressure vessel component is designed by analysis, but also a difficulty which puzzles engineers and designers at all times. At present, for calculating and categorizing the stress field of pressure vessel components, there are several computation methods of design by analysis such as Stress Equivalent Linearization, Two-Step Approach, Primary Structure method, Elastic Compensation method, GLOSS R-Node method and so on, that are developed and applied. Moreover, ASME code also gives an inelastic method of design by analysis for limiting gross plastic deformation only. When pressure vessel components design by analysis, sometimes there are huge differences between the calculating results for using different calculating and analysis methods mentioned above. As consequence, this is the main reason that affects wide application of design by analysis approach. Recently, a new approach, presented in the new proposal of a European Standard, CEN's unfired pressure vessel standard EN 13445-3, tries to avoid problems of stress classification by analyzing pressure vessel structure's various failure mechanisms directly based on elastic-plastic theory. In this paper, some stress classification methods mentioned above, are described briefly. And the computational methods cited in the European pressure vessel standard, such as Deviatoric Map, and nonlinear analysis methods (plastic analysis and limit analysis), are depicted compendiously. Furthermore, the characteristics of computational methods of design by analysis are summarized for selecting the proper computational method when design pressure vessel component by analysis. (authors)

Analysis of diffusivity of the oscillating reaction components in a microreactor system

Directory of Open Access Journals (Sweden)

Martina Šafranko

2017-01-01

Full Text Available When performing oscillating reactions, periodical changes in the concentrations of reactants, intermediaries, and products take place. Due to the mentioned periodical changes of the concentrations, the information about the diffusivity of the components included into oscillating reactions is very important for the control of the oscillating reactions. Non-linear dynamics makes oscillating reactions very interesting for analysis in different reactor systems. In this paper, the analysis of diffusivity of the oscillating reaction components was performed in a microreactor, with the aim of identifying the limiting component. The geometry of the microreactor microchannel and a well defined flow profile ensure optimal conditions for the diffusion phenomena analysis, because diffusion profiles in a microreactor depend only on the residence time. In this paper, the analysis of diffusivity of the oscillating reaction components was performed in a microreactor equipped with 2 Y-shape inlets and 2 Y-shape outlets, with active volume of V = 4 μL at different residence times.

Aerothermal optimization of partially shrouded axial turbines[Dissertation 17138

Energy Technology Data Exchange (ETDEWEB)

Porreca, L.

2007-07-01

measurements show that a highly three-dimensional interaction occurs in the partial shroud cases between the passage vortex and a vortex caused by the recessed shroud platform design. This results in an aerodynamic penalty of the partial shrouded test case (CPS) to 1% with respect to the full shroud test case (RRD). However in the modified partial shroud case (EPS) with a shroud platform that covers the blade throat, the aerodynamic performance has improved of about 0.6% due to the enhanced flow control and lower interaction between main-stream and tip leakage. Measurements and computations clearly show that this modification is effective and the flow field is significantly modified towards the design intent of an axisymmetric full shroud. Moreover, the modified shroud geometry keeps almost unchanged the overall weight of this component compared with the CPS case. The influence of the shroud geometry on the heat load and mechanical stresses has been then evaluated by means of a computational analysis. The turbine flow field has been numerically simulated in a engine representative conditions (high inlet temperature). To evaluate the heat load and the temperature distribution on the blades, a conjugate heat transfer analysis has been performed taking into account an internal cooling strategy and a shroud external cooling arrangement. The combination of aerodynamic and centrifugal load together with the thermal load has been applied on the blade solid model in order to assess the effect of the shroud geometry on the mechanical stresses by means of a finite element analysis (FEM). A life prediction has been performed based on the Low-Cycle Fatigue and creep analysis. The FEM analysis shows that the full shroud test case has a higher stresses on the blade root but less stress concentrations on the blade/shroud components. On the other hand, the CPS case has the lowest blade root stresses but the highest stress concentration in the shroud/blade junction due to a low stiffness that

Thermodynamic Equilibria and Extrema Analysis of Attainability Regions and Partial Equilibria

CERN Document Server

Gorban, Alexander N; Kaganovich, Boris M; Keiko, Alexandre V; Shamansky, Vitaly A; Shirkalin, Igor A

2006-01-01

This book discusses mathematical models that are based on the concepts of classical equilibrium thermodynamics. They are intended for the analysis of possible results of diverse natural and production processes. Unlike the traditional models, these allow one to view the achievable set of partial equilibria with regards to constraints on kinetics, energy and mass exchange and to determine states of the studied systems of interest for the researcher. Application of the suggested models in chemical technology, energy and ecology is illustrated in the examples.

Principal Component Analysis: Most Favourite Tool in Chemometrics

Indian Academy of Sciences (India)

Abstract. Principal component analysis (PCA) is the most commonlyused chemometric technique. It is an unsupervised patternrecognition technique. PCA has found applications in chemistry,biology, medicine and economics. The present work attemptsto understand how PCA work and how can we interpretits results.

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

Science.gov (United States)

Zhang, Ying-Zhi; Liu, Jin-Tong; Shen, Gui-Xiang; Long, Zhe; Sun, Shu-Guang

2017-07-01

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

Process management using component thermal-hydraulic function classes

Science.gov (United States)

Morman, J.A.; Wei, T.Y.C.; Reifman, J.

1999-07-27

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced. 5 figs.

Process management using component thermal-hydraulic function classes

Science.gov (United States)

Morman, James A.; Wei, Thomas Y. C.; Reifman, Jaques

1999-01-01

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced.

Principal Component Analysis - A Powerful Tool in Computing Marketing Information

Directory of Open Access Journals (Sweden)

Constantin C.

2014-12-01

Full Text Available This paper is about an instrumental research regarding a powerful multivariate data analysis method which can be used by the researchers in order to obtain valuable information for decision makers that need to solve the marketing problem a company face with. The literature stresses the need to avoid the multicollinearity phenomenon in multivariate analysis and the features of Principal Component Analysis (PCA in reducing the number of variables that could be correlated with each other to a small number of principal components that are uncorrelated. In this respect, the paper presents step-by-step the process of applying the PCA in marketing research when we use a large number of variables that naturally are collinear.

Barrelet zeros in partial wave analysis

International Nuclear Information System (INIS)

Baker, R.D.

1976-01-01

The formalism of Barrelet zeros is discussed. Spinless scattering is described to introduce the idea, then the more usual case of 0 - 1/2 + → 0 - 1/2 + scattering. The zeros are regarded here only as a means to an end, viz the partial waves. The extraction of these is given in detail, and ambiguities are discussed at length. (author)

A Note on McDonald's Generalization of Principal Components Analysis

Science.gov (United States)

Shine, Lester C., II

1972-01-01

It is shown that McDonald's generalization of Classical Principal Components Analysis to groups of variables maximally channels the totalvariance of the original variables through the groups of variables acting as groups. An equation is obtained for determining the vectors of correlations of the L2 components with the original variables.…

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

Science.gov (United States)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Structural studies of formic acid using partial form-factor analysis

International Nuclear Information System (INIS)

Swan, G.; Dore, J.C.; Bellissent-Funel, M.C.

1993-01-01

Neutron diffraction measurements have been made of liquid formic acid using H/D isotopic substitution. Data are recorded for samples of DCOOD, HCOOD and a (H/D)COOD mixture (α D =0.36). A first-order difference method is used to determine the intra-molecular contribution through the introduction of a partial form-factor analysis technique incorporating a hydrogen-bond term. The method improves the sensitivity of the parameters defining the molecular geometry and avoids some of the ambiguities arising from terms involving spatial overlap of inter- and intra-molecular features. The possible application to other systems is briefly reviewed. (authors). 8 figs., 2 tabs., 8 refs

Functional principal component analysis of glomerular filtration rate curves after kidney transplant.

Science.gov (United States)

Dong, Jianghu J; Wang, Liangliang; Gill, Jagbir; Cao, Jiguo

2017-01-01

This article is motivated by some longitudinal clinical data of kidney transplant recipients, where kidney function progression is recorded as the estimated glomerular filtration rates at multiple time points post kidney transplantation. We propose to use the functional principal component analysis method to explore the major source of variations of glomerular filtration rate curves. We find that the estimated functional principal component scores can be used to cluster glomerular filtration rate curves. Ordering functional principal component scores can detect abnormal glomerular filtration rate curves. Finally, functional principal component analysis can effectively estimate missing glomerular filtration rate values and predict future glomerular filtration rate values.

Computer compensation for NMR quantitative analysis of trace components

International Nuclear Information System (INIS)

Nakayama, T.; Fujiwara, Y.

1981-01-01

A computer program has been written that determines trace components and separates overlapping components in multicomponent NMR spectra. This program uses the Lorentzian curve as a theoretical curve of NMR spectra. The coefficients of the Lorentzian are determined by the method of least squares. Systematic errors such as baseline/phase distortion are compensated and random errors are smoothed by taking moving averages, so that there processes contribute substantially to decreasing the accumulation time of spectral data. The accuracy of quantitative analysis of trace components has been improved by two significant figures. This program was applied to determining the abundance of 13C and the saponification degree of PVA

An elementary components of variance analysis for multi-center quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1977-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality control (QC) studies. Statistical analysis methods for such studies using an 'analysis of variance with components of variance estimation' are discussed. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Components of variance analysis also provides an intelligent way to combine the results of several QC samples run at different evels, from which we may decide if any component varies systematically with dose level; if not, pooling of estimates becomes possible. We consider several possible relationships of standard deviation to the laboratory mean. Each relationship corresponds to an underlying statistical model, and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine if an appropriate model has been chosen, although the exact functional relationship of standard deviation to lab mean may be difficult to establish. Appropriate graphical display of the data aids in visual understanding of the data. A plot of the ranked standard deviation vs. ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean. (orig.) [de

Reactor modeling and process analysis for partial oxidation of natural gas

NARCIS (Netherlands)

Albrecht, B.A.

2004-01-01

This thesis analyses a novel process of partial oxidation of natural gas and develops a numerical tool for the partial oxidation reactor modeling. The proposed process generates syngas in an integrated plant of a partial oxidation reactor, a syngas turbine and an air separation unit. This is called

Time-domain ultra-wideband radar, sensor and components theory, analysis and design

CERN Document Server

Nguyen, Cam

2014-01-01

This book presents the theory, analysis, and design of ultra-wideband (UWB) radar and sensor systems (in short, UWB systems) and their components. UWB systems find numerous applications in the military, security, civilian, commercial and medicine fields. This book addresses five main topics of UWB systems: System Analysis, Transmitter Design, Receiver Design, Antenna Design and System Integration and Test. The developments of a practical UWB system and its components using microwave integrated circuits, as well as various measurements, are included in detail to demonstrate the theory, analysis and design technique. Essentially, this book will enable the reader to design their own UWB systems and components. In the System Analysis chapter, the UWB principle of operation as well as the power budget analysis and range resolution analysis are presented. In the UWB Transmitter Design chapter, the design, fabrication and measurement of impulse and monocycle pulse generators are covered. The UWB Receiver Design cha...

Study on determination of durability analysis process and fatigue damage parameter for rubber component

International Nuclear Information System (INIS)

Moon, Seong In; Cho, Il Je; Woo, Chang Su; Kim, Wan Doo

2011-01-01

Rubber components, which have been widely used in the automotive industry as anti-vibration components for many years, are subjected to fluctuating loads, often failing due to the nucleation and growth of defects or cracks. To prevent such failures, it is necessary to understand the fatigue failure mechanism for rubber materials and to evaluate the fatigue life for rubber components. The objective of this study is to develop a durability analysis process for vulcanized rubber components, that can predict fatigue life at the initial product design step. The determination method of nonlinear material constants for FE analysis was proposed. Also, to investigate the applicability of the commonly used damage parameters, fatigue tests and corresponding finite element analyses were carried out and normal and shear strain was proposed as the fatigue damage parameter for rubber components. Fatigue analysis for automotive rubber components was performed and the durability analysis process was reviewed

Flexible removable partial dentures: a basic overview.

Science.gov (United States)

Hill, Edward E; Rubel, Barry; Smith, John B

2014-01-01

For many years, flexible resin materials have been available for fabricating removable partial denture (RPD) prostheses. Using a nonrigid material for the major connector or other components of an RPD may be a consideration for certain patients. Except for the promotional literature that has been written for flexible resin dentures, there is very little information available in the dental literature concerning nonrigid RPDs. As a result, the decision to use this treatment option depends on the judgment and experience of the dentist and fabricating laboratory. This article summarizes clinically pertinent information about flexible, nonrigid partial dentures.

A component analysis of positive behaviour support plans.

Science.gov (United States)

McClean, Brian; Grey, Ian

2012-09-01

Positive behaviour support (PBS) emphasises multi-component interventions by natural intervention agents to help people overcome challenging behaviours. This paper investigates which components are most effective and which factors might mediate effectiveness. Sixty-one staff working with individuals with intellectual disability and challenging behaviours completed longitudinal competency-based training in PBS. Each staff participant conducted a functional assessment and developed and implemented a PBS plan for one prioritised individual. A total of 1,272 interventions were available for analysis. Measures of challenging behaviour were taken at baseline, after 6 months, and at an average of 26 months follow-up. There was a significant reduction in the frequency, management difficulty, and episodic severity of challenging behaviour over the duration of the study. Escape was identified by staff as the most common function, accounting for 77% of challenging behaviours. The most commonly implemented components of intervention were setting event changes and quality-of-life-based interventions. Only treatment acceptability was found to be related to decreases in behavioural frequency. No single intervention component was found to have a greater association with reductions in challenging behaviour.

Principal Component Analysis of Working Memory Variables during Child and Adolescent Development.

Science.gov (United States)

Barriga-Paulino, Catarina I; Rodríguez-Martínez, Elena I; Rojas-Benjumea, María Ángeles; Gómez, Carlos M

2016-10-03

Correlation and Principal Component Analysis (PCA) of behavioral measures from two experimental tasks (Delayed Match-to-Sample and Oddball), and standard scores from a neuropsychological test battery (Working Memory Test Battery for Children) was performed on data from participants between 6-18 years old. The correlation analysis (p 1), the scores of the first extracted component were significantly correlated (p < .05) to most behavioral measures, suggesting some commonalities of the processes of age-related changes in the measured variables. The results suggest that this first component would be related to age but also to individual differences during the cognitive maturation process across childhood and adolescence stages. The fourth component would represent the speed-accuracy trade-off phenomenon as it presents loading components with different signs for reaction times and errors.

Comparative Study of Various Normal Mode Analysis Techniques Based on Partial Hessians

OpenAIRE

GHYSELS, AN; VAN SPEYBROECK, VERONIQUE; PAUWELS, EWALD; CATAK, SARON; BROOKS, BERNARD R.; VAN NECK, DIMITRI; WAROQUIER, MICHEL

2010-01-01

Standard normal mode analysis becomes problematic for complex molecular systems, as a result of both the high computational cost and the excessive amount of information when the full Hessian matrix is used. Several partial Hessian methods have been proposed in the literature, yielding approximate normal modes. These methods aim at reducing the computational load and/or calculating only the relevant normal modes of interest in a specific application. Each method has its own (dis)advantages and...

PyPWA: A partial-wave/amplitude analysis software framework

Science.gov (United States)

Salgado, Carlos

2016-05-01

The PyPWA project aims to develop a software framework for Partial Wave and Amplitude Analysis of data; providing the user with software tools to identify resonances from multi-particle final states in photoproduction. Most of the code is written in Python. The software is divided into two main branches: one general-shell where amplitude's parameters (or any parametric model) are to be estimated from the data. This branch also includes software to produce simulated data-sets using the fitted amplitudes. A second branch contains a specific realization of the isobar model (with room to include Deck-type and other isobar model extensions) to perform PWA with an interface into the computer resources at Jefferson Lab. We are currently implementing parallelism and vectorization using the Intel's Xeon Phi family of coprocessors.

Poles of the Zagreb analysis partial-wave T matrices

Science.gov (United States)

Batinić, M.; Ceci, S.; Švarc, A.; Zauner, B.

2010-09-01

The Zagreb analysis partial-wave T matrices included in the Review of Particle Physics [by the Particle Data Group (PDG)] contain Breit-Wigner parameters only. As the advantages of pole over Breit-Wigner parameters in quantifying scattering matrix resonant states are becoming indisputable, we supplement the original solution with the pole parameters. Because of an already reported numeric error in the S11 analytic continuation [Batinić , Phys. Rev. CPRVCAN0556-281310.1103/PhysRevC.57.1004 57, 1004(E) (1997); arXiv:nucl-th/9703023], we declare the old BATINIC 95 solution, presently included by the PDG, invalid. Instead, we offer two new solutions: (A) corrected BATINIC 95 and (B) a new solution with an improved S11 πN elastic input. We endorse solution (B).

Scalable Robust Principal Component Analysis Using Grassmann Averages

DEFF Research Database (Denmark)

Hauberg, Søren; Feragen, Aasa; Enficiaud, Raffi

2016-01-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortu...

Effect of partially purified components of zoospores and mycelia of phytophthora infestans on uptake of 3H-leucine by potato tuber disks

International Nuclear Information System (INIS)

Nishimura, Norio; Tomiyama, Kohei; Doke, Noriyuki

1980-01-01

The zoosporial component of Phytophthora infestans, which was previously reported to cause reduction of 3 H-leucine uptake by potato tuber disks, was partially purified. Precipitate (A-fraction) was obtained by homogenizing zoospores with acetate buffer at pH 4.5 and centrifuging at 20,000 x g, and the A-fraction was suspended in borate buffer at pH 8.8, boiled for 1 hr and then centrifuged at 20,000 x g, giving the precipitate (B-fraction) and supernatant (C-fraction). Ten ml of 10 mM tris-HCl buffer containing 1 mM CaCl 2 at pH 7.4 was used to suspend A and B-fraction. The buffer was used as a control. A, B and C fractions obtained from 5 - 6 x 10 6 zoosprores reducted uptake of 3 H-leucine by the tuber disks of potato cv. Rishiri, but the inhibition rates caused by these fractions differed markedly. However, very high correlation was found between inhibition rates of 3 H-leucine uptake and sugar contents of these fractions. There was no difference in the inhibition rates between the zoosporial components of incompatible and compatible races, when the activities were expressed in terms of the sugar contents. The mycelial components of P. infestans extracted by the modified method of Lisker and Kuc which was used to extract phytoalexin elicitor from that of P. infestans, also had the same effect as the zoosporial components (A, B, and C-fraction) on 3 H-leucine uptake by the disks. C-fraction containing 15 μg of sugar per ml sufficed to inhibit 3 H-leucine uptake at the maximum rate, and the maximum rate of inhibition was attained within 2 hr after the zoosporial component (C-fraction containing 30 μg sugar/ml) was administered to the disks. (author)

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

Energy Technology Data Exchange (ETDEWEB)

Kang, Ho Yang [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of); Kim, Ki Bok [Chungnam National University, Daejeon (Korea, Republic of)

2003-06-15

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

International Nuclear Information System (INIS)

Kang, Ho Yang; Kim, Ki Bok

2003-01-01

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

Nonparametric inference in nonlinear principal components analysis : exploration and beyond

NARCIS (Netherlands)

Linting, Mariëlle

2007-01-01

In the social and behavioral sciences, data sets often do not meet the assumptions of traditional analysis methods. Therefore, nonlinear alternatives to traditional methods have been developed. This thesis starts with a didactic discussion of nonlinear principal components analysis (NLPCA),

Quantitative analysis of CT brain images: a statistical model incorporating partial volume and beam hardening effects

International Nuclear Information System (INIS)

McLoughlin, R.F.; Ryan, M.V.; Heuston, P.M.; McCoy, C.T.; Masterson, J.B.

1992-01-01

The purpose of this study was to construct and evaluate a statistical model for the quantitative analysis of computed tomographic brain images. Data were derived from standard sections in 34 normal studies. A model representing the intercranial pure tissue and partial volume areas, with allowance for beam hardening, was developed. The average percentage error in estimation of areas, derived from phantom tests using the model, was 28.47%. We conclude that our model is not sufficiently accurate to be of clinical use, even though allowance was made for partial volume and beam hardening effects. (author)

Regional frequency analysis of extreme rainfalls using partial L moments method

Science.gov (United States)

Zakaria, Zahrahtul Amani; Shabri, Ani

2013-07-01

An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events.

The analysis of linear partial differential operators I distribution theory and Fourier analysis

CERN Document Server

Hörmander, Lars

2003-01-01

The main change in this edition is the inclusion of exercises with answers and hints. This is meant to emphasize that this volume has been written as a general course in modern analysis on a graduate student level and not only as the beginning of a specialized course in partial differen­ tial equations. In particular, it could also serve as an introduction to harmonic analysis. Exercises are given primarily to the sections of gen­ eral interest; there are none to the last two chapters. Most of the exercises are just routine problems meant to give some familiarity with standard use of the tools introduced in the text. Others are extensions of the theory presented there. As a rule rather complete though brief solutions are then given in the answers and hints. To a large extent the exercises have been taken over from courses or examinations given by Anders Melin or myself at the University of Lund. I am grateful to Anders Melin for letting me use the problems originating from him and for numerous valuable comm...

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...

Probabilistic structural analysis methods for select space propulsion system components

Science.gov (United States)

Millwater, H. R.; Cruse, T. A.

1989-01-01

The Probabilistic Structural Analysis Methods (PSAM) project developed at the Southwest Research Institute integrates state-of-the-art structural analysis techniques with probability theory for the design and analysis of complex large-scale engineering structures. An advanced efficient software system (NESSUS) capable of performing complex probabilistic analysis has been developed. NESSUS contains a number of software components to perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown. An expert system is included to capture and utilize PSAM knowledge and experience. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator (FPI). The expert system menu structure is summarized. The NESSUS system contains a state-of-the-art nonlinear probabilistic finite element code, NESSUS/FEM, to determine the structural response and sensitivities. A broad range of analysis capabilities and an extensive element library is present.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy

International Nuclear Information System (INIS)

Jesse, Stephen; Kalinin, Sergei V

2009-01-01

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Probabilistic Structural Analysis Methods for select space propulsion system components (PSAM). Volume 2: Literature surveys of critical Space Shuttle main engine components

Science.gov (United States)

Rajagopal, K. R.

1992-01-01

The technical effort and computer code development is summarized. Several formulations for Probabilistic Finite Element Analysis (PFEA) are described with emphasis on the selected formulation. The strategies being implemented in the first-version computer code to perform linear, elastic PFEA is described. The results of a series of select Space Shuttle Main Engine (SSME) component surveys are presented. These results identify the critical components and provide the information necessary for probabilistic structural analysis. Volume 2 is a summary of critical SSME components.

The role of damage analysis in the assessment of service-exposed components

International Nuclear Information System (INIS)

Bendick, W.; Muesch, H.; Weber, H.

1987-01-01

Components in power stations are subjected to service conditions under which creep processes take place limiting the component's lifetime by material exhaustion. To ensure a safe and economic plant operation it is necessary to get information about the exhaustion grade of single components as well as of the whole plant. A comprehensive lifetime assessment requests the complete knowledge of the service parameters, the component's deformtion behavior, and the change in material properties caused by longtime exposure to high service temperatures. A basis of evaluation is given by: 1) determination of material exhaustion by calculation, 2) investigation of the material properties, and 3) damage analysis. The purpose of this report is to show the role which damage analysis can play in the assessment of service-exposed components. As an example the test results of a damaged pipe bend will be discussed. (orig./MM)

Prospective study of robotic partial nephrectomy for renal cancer in Japan: Comparison with a historical control undergoing laparoscopic partial nephrectomy.

Science.gov (United States)

Tanaka, Kazushi; Teishima, Jun; Takenaka, Atsushi; Shiroki, Ryoichi; Kobayashi, Yasuyuki; Hattori, Kazunori; Kanayama, Hiro-Omi; Horie, Shigeo; Yoshino, Yasushi; Fujisawa, Masato

2018-05-01

To evaluate the outcomes of robotic partial nephrectomy compared with those of laparoscopic partial nephrectomy for T1 renal tumors in Japanese centers. Patients with a T1 renal tumor who underwent robotic partial nephrectomy were eligible for inclusion in the present study. The primary end-point consisted of three components: a negative surgical margin, no conversion to open or laparoscopic surgery and a warm ischemia time ≤25 min. We compared data from these patients with the data from a retrospective study of laparoscopic partial nephrectomy carried out in Japan. A total of 108 patients were registered in the present study; 105 underwent robotic partial nephrectomy. The proportion of patients who met the primary end-point was 91.3% (95% confidence interval 84.1-95.9%), which was significantly higher than 23.3% in the historical data. Major complications were seen in 19 patients (18.1%). The mean change in the estimated glomerular filtration rate in the operated kidney, 180 days postoperatively, was -10.8 mL/min/1.73 m 2 (95% confidence interval -12.3-9.4%). Robotic partial nephrectomy for patients with a T1 renal tumor is a safe, feasible and more effective operative method compared with laparoscopic partial nephrectomy. It can be anticipated that robotic partial nephrectomy will become more widely used in Japan in the future. © 2018 The Japanese Urological Association.

Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis.

Science.gov (United States)

Yang, Yan-Qin; Yin, Hong-Xu; Yuan, Hai-Bo; Jiang, Yong-Wen; Dong, Chun-Wang; Deng, Yu-Liang

2018-01-01

In the present work, a novel infrared-assisted extraction coupled to headspace solid-phase microextraction (IRAE-HS-SPME) followed by gas chromatography-mass spectrometry (GC-MS) was developed for rapid determination of the volatile components in green tea. The extraction parameters such as fiber type, sample amount, infrared power, extraction time, and infrared lamp distance were optimized by orthogonal experimental design. Under optimum conditions, a total of 82 volatile compounds in 21 green tea samples from different geographical origins were identified. Compared with classical water-bath heating, the proposed technique has remarkable advantages of considerably reducing the analytical time and high efficiency. In addition, an effective classification of green teas based on their volatile profiles was achieved by partial least square-discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). Furthermore, the application of a dual criterion based on the variable importance in the projection (VIP) values of the PLS-DA models and on the category from one-way univariate analysis (ANOVA) allowed the identification of 12 potential volatile markers, which were considered to make the most important contribution to the discrimination of the samples. The results suggest that IRAE-HS-SPME/GC-MS technique combined with multivariate analysis offers a valuable tool to assess geographical traceability of different tea varieties.

Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis.

Directory of Open Access Journals (Sweden)

Yan-Qin Yang

Full Text Available In the present work, a novel infrared-assisted extraction coupled to headspace solid-phase microextraction (IRAE-HS-SPME followed by gas chromatography-mass spectrometry (GC-MS was developed for rapid determination of the volatile components in green tea. The extraction parameters such as fiber type, sample amount, infrared power, extraction time, and infrared lamp distance were optimized by orthogonal experimental design. Under optimum conditions, a total of 82 volatile compounds in 21 green tea samples from different geographical origins were identified. Compared with classical water-bath heating, the proposed technique has remarkable advantages of considerably reducing the analytical time and high efficiency. In addition, an effective classification of green teas based on their volatile profiles was achieved by partial least square-discriminant analysis (PLS-DA and hierarchical clustering analysis (HCA. Furthermore, the application of a dual criterion based on the variable importance in the projection (VIP values of the PLS-DA models and on the category from one-way univariate analysis (ANOVA allowed the identification of 12 potential volatile markers, which were considered to make the most important contribution to the discrimination of the samples. The results suggest that IRAE-HS-SPME/GC-MS technique combined with multivariate analysis offers a valuable tool to assess geographical traceability of different tea varieties.

Partial wave analysis of the 18O(p,α0)15N reaction

International Nuclear Information System (INIS)

Wild, L.W.J.; Spicer, B.M.

1979-01-01

A partial wave analysis of the differential cross sections for the 18 O(p,α 0 ) 15 N reaction has been carried out applying the formalism of Blatt and Biedenharn (1952), made specific for this reaction. The differential cross sections, measured at 200 keV intervals from 6.6 to 10.4 MeV bombarding energy, were subjected to least-squares fitting to this specific analytic expression. Two resonances were given by the analysis, the 19 F states being at 14.71+-0.07 MeV (1/2 - ) and 14.80 + 0.07 MeV (1/2) +

Robust LOD scores for variance component-based linkage analysis.

Science.gov (United States)

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

Analysis of spiral components in 16 galaxies

International Nuclear Information System (INIS)

Considere, S.; Athanassoula, E.

1988-01-01

A Fourier analysis of the intensity distributions in the plane of 16 spiral galaxies of morphological types from 1 to 7 is performed. The galaxies processed are NGC 300,598,628,2403,2841,3031,3198,3344,5033,5055,5194,5247,6946,7096,7217, and 7331. The method, mathematically based upon a decomposition of a distribution into a superposition of individual logarithmic spiral components, is first used to determine for each galaxy the position angle PA and the inclination ω of the galaxy plane onto the sky plane. Our results, in good agreement with those issued from different usual methods in the literature, are discussed. The decomposition of the deprojected galaxies into individual spiral components reveals that the two-armed component is everywhere dominant. Our pitch angles are then compared to the previously published ones and their quality is checked by drawing each individual logarithmic spiral on the actual deprojected galaxy images. Finally, the surface intensities for angular periodicities of interest are calculated. A choice of a few of the most important ones is used to elaborate a composite image well representing the main spiral features observed in the deprojected galaxies

On Bayesian Principal Component Analysis

Czech Academy of Sciences Publication Activity Database

Šmídl, Václav; Quinn, A.

2007-01-01

Roč. 51, č. 9 (2007), s. 4101-4123 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Principal component analysis ( PCA ) * Variational bayes (VB) * von-Mises–Fisher distribution Subject RIV: BC - Control Systems Theory Impact factor: 1.029, year: 2007 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4MYD60N-6&_user=10&_coverDate=05%2F15%2F2007&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=b8ea629d48df926fe18f9e5724c9003a

Structural analysis of nuclear components

International Nuclear Information System (INIS)

Ikonen, K.; Hyppoenen, P.; Mikkola, T.; Noro, H.; Raiko, H.; Salminen, P.; Talja, H.

1983-05-01

THe report describes the activities accomplished in the project 'Structural Analysis Project of Nuclear Power Plant Components' during the years 1974-1982 in the Nuclear Engineering Laboratory at the Technical Research Centre of Finland. The objective of the project has been to develop Finnish expertise in structural mechanics related to nuclear engineering. The report describes the starting point of the research work, the organization of the project and the research activities on various subareas. Further the work done with computer codes is described and also the problems which the developed expertise has been applied to. Finally, the diploma works, publications and work reports, which are mainly in Finnish, are listed to give a view of the content of the project. (author)

Dynamic analysis of the radiolysis of binary component system

International Nuclear Information System (INIS)

Katayama, M.; Trumbore, C.N.

1975-01-01

Dynamic analysis was performed on a variety of combinations of components in the radiolysis of binary system, taking the hydrogen-producing reaction with hydrocarbon RH 2 as an example. A definite rule was able to be established from this analysis, which is useful for revealing the reaction mechanism. The combinations were as follows: 1) both components A and B do not interact but serve only as diluents, 2) A is a diluent, and B is a radical captor, 3) both A and B are radical captors, 4-1) A is a diluent, and B decomposes after the reception of the exciting energy of A, 4-2) A is a diluent, and B does not participate in decomposition after the reception of the exciting energy of A, 5-1) A is a radical captor, and B decomposes after the reception of the exciting energy of A, 5-2) A is a radical captor, and B does not participate in decomposition after the reception of the exciting energy of A, 6-1) both A and B decompose after the reception of the exciting energy of the partner component; and 6-2) both A and B do not decompose after the reception of the exciting energy of the partner component. According to the dynamical analysis of the above nine combinations, it can be pointed out that if excitation transfer participates, the similar phenomena to radical capture are presented apparently. It is desirable to measure the yield of radicals experimentally with the system which need not much consideration to the excitation transfer. Isotope substitution mixture system is conceived as one of such system. This analytical method was applied to the system containing cyclopentanone, such as cyclopentanone-cyclohexane system. (Iwakiri, K.)

APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

International Nuclear Information System (INIS)

STOYANOVA, R.S.; OCHS, M.F.; BROWN, T.R.; ROONEY, W.D.; LI, X.; LEE, J.H.; SPRINGER, C.S.

1999-01-01

Standard analysis methods for processing inversion recovery MR images traditionally have used single pixel techniques. In these techniques each pixel is independently fit to an exponential recovery, and spatial correlations in the data set are ignored. By analyzing the image as a complete dataset, improved error analysis and automatic segmentation can be achieved. Here, the authors apply principal component analysis (PCA) to a series of relaxographic images. This procedure decomposes the 3-dimensional data set into three separate images and corresponding recovery times. They attribute the 3 images to be spatial representations of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) content

Value Added Tax and price stability in Nigeria: A partial equilibrium analysis

Directory of Open Access Journals (Sweden)

Marius Ikpe

2013-12-01

Full Text Available The economic impact of Value Added Tax (VAT that was implemented in Nigeria in 1994 has generated much debate in recent times, especially with respect to its effect on the level of aggregate prices. This study empirically examines the influence of VAT on price stability in Nigeria using partial equilibrium analysis. We introduced the VAT variable in the framework of a combination of structuralist, monetarist and fiscalist approaches to inflation modelling. The analysis was carried out by applying multiple regression analysis in static form to data for the 1994-2010 period. The results reveal that VAT exerts a strong upward pressure on price levels, most likely due to the burden of VAT on intermediate outputs. The study rules out the option of VAT exemptions for intermediate outputs as a solution, due to the difficulty in distinguishing between intermediate and final outputs. Instead, it recommends a detailed post-VAT cost-benefit analysis to assess the social desirability of VAT policy in Nigeria.

TG-MS analysis and kinetic study for thermal decomposition of six representative components of municipal solid waste under steam atmosphere.

Science.gov (United States)

Zhang, Jinzhi; Chen, Tianju; Wu, Jingli; Wu, Jinhu

2015-09-01

Thermal decomposition of six representative components of municipal solid waste (MSW, including lignin, printing paper, cotton, rubber, polyvinyl chloride (PVC) and cabbage) was investigated by thermogravimetric-mass spectroscopy (TG-MS) under steam atmosphere. Compared with TG and derivative thermogravimetric (DTG) curves under N2 atmosphere, thermal decomposition of MSW components under steam atmosphere was divided into pyrolysis and gasification stages. In the pyrolysis stage, the shapes of TG and DTG curves under steam atmosphere were almost the same with those under N2 atmosphere. In the gasification stage, the presence of steam led to a greater mass loss because of the steam partial oxidation of char residue. The evolution profiles of H2, CH4, CO and CO2 were well consistent with DTG curves in terms of appearance of peaks and relevant stages in the whole temperature range, and the steam partial oxidation of char residue promoted the generation of more gas products in high temperature range. The multi-Gaussian distributed activation energy model (DAEM) was proved plausible to describe thermal decomposition behaviours of MSW components under steam atmosphere. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Sample preparation methods for chromatographic analysis of organic components in atmospheric particulate matter].

Science.gov (United States)

Hao, Liang; Wu, Dapeng; Guan, Yafeng

2014-09-01

The determination of organic composition in atmospheric particulate matter (PM) is of great importance in understanding how PM affects human health, environment, climate, and ecosystem. Organic components are also the scientific basis for emission source tracking, PM regulation and risk management. Therefore, the molecular characterization of the organic fraction of PM has become one of the priority research issues in the field of environmental analysis. Due to the extreme complexity of PM samples, chromatographic methods have been the chief selection. The common procedure for the analysis of organic components in PM includes several steps: sample collection on the fiber filters, sample preparation (transform the sample into a form suitable for chromatographic analysis), analysis by chromatographic methods. Among these steps, the sample preparation methods will largely determine the throughput and the data quality. Solvent extraction methods followed by sample pretreatment (e. g. pre-separation, derivatization, pre-concentration) have long been used for PM sample analysis, and thermal desorption methods have also mainly focused on the non-polar organic component analysis in PM. In this paper, the sample preparation methods prior to chromatographic analysis of organic components in PM are reviewed comprehensively, and the corresponding merits and limitations of each method are also briefly discussed.

Numerical analysis of magnetoelastic coupled buckling of fusion reactor components

International Nuclear Information System (INIS)

Demachi, K.; Yoshida, Y.; Miya, K.

1994-01-01

For a tokamak fusion reactor, it is one of the most important subjects to establish the structural design in which its components can stand for strong magnetic force induced by plasma disruption. A number of magnetostructural analysis of the fusion reactor components were done recently. However, in these researches the structural behavior was calculated based on the small deformation theory where the nonlinearity was neglected. But it is known that some kinds of structures easily exceed the geometrical nonlinearity. In this paper, the deflection and the magnetoelastic buckling load of fusion reactor components during plasma disruption were calculated

A further component analysis for illicit drugs mixtures with THz-TDS

Science.gov (United States)

Xiong, Wei; Shen, Jingling; He, Ting; Pan, Rui

2009-07-01

A new method for quantitative analysis of mixtures of illicit drugs with THz time domain spectroscopy was proposed and verified experimentally. In traditional method we need fingerprints of all the pure chemical components. In practical as only the objective components in a mixture and their absorption features are known, it is necessary and important to present a more practical technique for the detection and identification. Our new method of quantitatively inspect of the mixtures of illicit drugs is developed by using derivative spectrum. In this method, the ratio of objective components in a mixture can be obtained on the assumption that all objective components in the mixture and their absorption features are known but the unknown components are not needed. Then methamphetamine and flour, a illicit drug and a common adulterant, were selected for our experiment. The experimental result verified the effectiveness of the method, which suggested that it could be an effective method for quantitative identification of illicit drugs. This THz spectroscopy technique is great significant in the real-world applications of illicit drugs quantitative analysis. It could be an effective method in the field of security and pharmaceuticals inspection.

Protein structure similarity from principle component correlation analysis

Directory of Open Access Journals (Sweden)

Chou James

2006-01-01

Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

Partial versus complete fundoplication for the correction of pediatric GERD: a systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Peter Glen

Full Text Available There is no consensus as to what extent of "wrap" is required in a fundoplication for correction of gastroesophageal reflux disease (GERD.To evaluate if a complete (360 degree or partial fundoplication gives better control of GERD.A systematic search of MEDLINE and Scopus identified interventional and observational studies of fundoplication in children. Screening identified those comparing techniques. The primary outcome was recurrence of GERD following surgery. Dysphagia and complications were secondary outcomes of interest. Meta-analysis was performed when appropriate. Study quality was assessed using the Cochrane Risk of Bias Tool.2289 abstracts were screened, yielding 2 randomized controlled trials (RCTs and 12 retrospective cohort studies. The RCTs were pooled. There was no difference in surgical success between partial and complete fundoplication, OR 1.33 [0.67,2.66]. In the 12 cohort studies, 3 (25% used an objective assessment of the surgery, one of which showed improved outcomes with complete fundoplication. Twenty-five different complications were reported; common were dysphagia and gas-bloat syndrome. Overall study quality was poor.The comparison of partial fundoplication with complete fundoplication warrants further study. The evidence does not demonstrate superiority of one technique. The lack of high quality RCTs and the methodological heterogeneity of observational studies limits a powerful meta-analysis.

Global sensitivity analysis of bogie dynamics with respect to suspension components

Energy Technology Data Exchange (ETDEWEB)

Mousavi Bideleh, Seyed Milad, E-mail: milad.mousavi@chalmers.se; Berbyuk, Viktor, E-mail: viktor.berbyuk@chalmers.se [Chalmers University of Technology, Department of Applied Mechanics (Sweden)

2016-06-15

The effects of bogie primary and secondary suspension stiffness and damping components on the dynamics behavior of a high speed train are scrutinized based on the multiplicative dimensional reduction method (M-DRM). A one-car railway vehicle model is chosen for the analysis at two levels of the bogie suspension system: symmetric and asymmetric configurations. Several operational scenarios including straight and circular curved tracks are considered, and measurement data are used as the track irregularities in different directions. Ride comfort, safety, and wear objective functions are specified to evaluate the vehicle’s dynamics performance on the prescribed operational scenarios. In order to have an appropriate cut center for the sensitivity analysis, the genetic algorithm optimization routine is employed to optimize the primary and secondary suspension components in terms of wear and comfort, respectively. The global sensitivity indices are introduced and the Gaussian quadrature integrals are employed to evaluate the simplified sensitivity indices correlated to the objective functions. In each scenario, the most influential suspension components on bogie dynamics are recognized and a thorough analysis of the results is given. The outcomes of the current research provide informative data that can be beneficial in design and optimization of passive and active suspension components for high speed train bogies.

Global sensitivity analysis of bogie dynamics with respect to suspension components

International Nuclear Information System (INIS)

Mousavi Bideleh, Seyed Milad; Berbyuk, Viktor

2016-01-01

The effects of bogie primary and secondary suspension stiffness and damping components on the dynamics behavior of a high speed train are scrutinized based on the multiplicative dimensional reduction method (M-DRM). A one-car railway vehicle model is chosen for the analysis at two levels of the bogie suspension system: symmetric and asymmetric configurations. Several operational scenarios including straight and circular curved tracks are considered, and measurement data are used as the track irregularities in different directions. Ride comfort, safety, and wear objective functions are specified to evaluate the vehicle’s dynamics performance on the prescribed operational scenarios. In order to have an appropriate cut center for the sensitivity analysis, the genetic algorithm optimization routine is employed to optimize the primary and secondary suspension components in terms of wear and comfort, respectively. The global sensitivity indices are introduced and the Gaussian quadrature integrals are employed to evaluate the simplified sensitivity indices correlated to the objective functions. In each scenario, the most influential suspension components on bogie dynamics are recognized and a thorough analysis of the results is given. The outcomes of the current research provide informative data that can be beneficial in design and optimization of passive and active suspension components for high speed train bogies.

Creative design-by-analysis solutions applied to high-temperature components

International Nuclear Information System (INIS)

Dhalla, A.K.

1993-01-01

Elevated temperature design has evolved over the last two decades from design-by-formula philosophy of the ASME Boiler and Pressure Vessel Code, Sections I and VIII (Division 1), to the design-by-analysis philosophy of Section III, Code Case N-47. The benefits of design-by-analysis procedures, which were developed under a US-DOE-sponsored high-temperature structural design (HTSD) program, are illustrated in the paper through five design examples taken from two U.S. liquid metal reactor (LMR) plants. Emphasis in the paper is placed upon the use of a detailed, nonlinear finite element analysis method to understand the structural response and to suggest design optimization so as to comply with Code Case N-47 criteria. A detailed analysis is cost-effective, if selectively used, to qualify an LMR component for service when long-lead-time structural forgings, procured based upon simplified preliminary analysis, do not meet the design criteria, or the operational loads are increased after the components have been fabricated. In the future, the overall costs of a detailed analysis will be reduced even further with the availability of finite element software used on workstations or PCs

Priority of VHS Development Based in Potential Area using Principal Component Analysis

Science.gov (United States)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

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...

Using partially labeled data for normal mixture identification with application to class definition

Science.gov (United States)

Shahshahani, Behzad M.; Landgrebe, David A.

1992-01-01

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

Summary of component reliability data for probabilistic safety analysis of Korean standard nuclear power plant

International Nuclear Information System (INIS)

Choi, S. Y.; Han, S. H.

2004-01-01

The reliability data of Korean NPP that reflects the plant specific characteristics is necessary for PSA of Korean nuclear power plants. We have performed a study to develop the component reliability DB and S/W for component reliability analysis. Based on the system, we had have collected the component operation data and failure/repair data during plant operation data to 1998/2000 for YGN 3,4/UCN 3,4 respectively. Recently, we have upgraded the database by collecting additional data by 2002 for Korean standard nuclear power plants and performed component reliability analysis and Bayesian analysis again. In this paper, we supply the summary of component reliability data for probabilistic safety analysis of Korean standard nuclear power plant and describe the plant specific characteristics compared to the generic data

Thermodynamically consistent modeling and simulation of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng

2017-12-09

A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is an attractive alternative recently over the NPT-based framework to model the realistic fluids. The proposed model uses the Helmholtz free energy rather than Gibbs free energy in the NPT-based framework. Different from the classical routines, we combine the first law of thermodynamics and related thermodynamical relations to derive the entropy balance equation, and then we derive a transport equation of the Helmholtz free energy density. Furthermore, by using the second law of thermodynamics, we derive a set of unified equations for both interfaces and bulk phases that can describe the partial miscibility of multiple fluids. A relation between the pressure gradient and chemical potential gradients is established, and this relation leads to a new formulation of the momentum balance equation, which demonstrates that chemical potential gradients become the primary driving force of fluid motion. Moreover, we prove that the proposed model satisfies the total (free) energy dissipation with time. For numerical simulation of the proposed model, the key difficulties result from the strong nonlinearity of Helmholtz free energy density and tight coupling relations between molar densities and velocity. To resolve these problems, we propose a novel convex-concave splitting of Helmholtz free energy density and deal well with the coupling relations between molar densities and velocity through very careful physical observations with a mathematical rigor. We prove that the proposed numerical scheme can preserve the discrete (free) energy dissipation. Numerical tests are carried out to verify the effectiveness of the proposed method.

Effects of asynchrony and ear of presentation on the pitch of mistuned partials in harmonic and frequency-shifted complex tones.

Science.gov (United States)

Brunstrom, J M; Roberts, B

2001-07-01

When a partial of a periodic complex is mistuned, its change in pitch is greater than expected. Two experiments examined whether these partial-pitch shifts are related to the computation of global pitch. In experiment 1, stimuli were either harmonic or frequency-shifted (25% of F0) complexes. One partial was mistuned by +/- 4% and played with leading and lagging portions of 500 ms each, relative to the other components (1 s), in both monaural and dichotic contexts. Subjects indicated whether the mistuned partial was higher or lower in pitch when concurrent with the other components. Responses were positively correlated with the direction of mistuning in all conditions. In experiment 2, stimuli from each condition were compared with synchronous equivalents. Subjects matched a pure tone to the pitch of the mistuned partial (component 4). The results showed that partial-pitch shifts are not reduced in size by asynchrony. Similar asynchronies are known to produce a near-exclusion of a mistuned partial from the global-pitch computation. This mismatch indicates that global and partial pitch are derived from different processes. The similarity of the partial-pitch shifts observed for harmonic and frequency-shifted stimuli suggests that they arise from a grouping mechanism that is sensitive to spectral regularity.

Multigroup Moderation Test in Generalized Structured Component Analysis

Directory of Open Access Journals (Sweden)

Angga Dwi Mulyanto

2016-05-01

Full Text Available Generalized Structured Component Analysis (GSCA is an alternative method in structural modeling using alternating least squares. GSCA can be used for the complex analysis including multigroup. GSCA can be run with a free software called GeSCA, but in GeSCA there is no multigroup moderation test to compare the effect between groups. In this research we propose to use the T test in PLS for testing moderation Multigroup on GSCA. T test only requires sample size, estimate path coefficient, and standard error of each group that are already available on the output of GeSCA and the formula is simple so the user does not need a long time for analysis.

Radionuclide X-ray fluorescence analysis of components of the environment

International Nuclear Information System (INIS)

Toelgyessy, J.; Havranek, E.; Dejmkova, E.

1983-12-01

The physical foundations and methodology are described of radionuclide X-ray fluorescence analysis. The sources are listed of air, water and soil pollution, and the transfer of impurities into biological materials is described. A detailed description is presented of the sampling of air, soil and biological materials and their preparation for analysis. Greatest attention is devoted to radionuclide X-ray fluorescence analysis of the components of the environment. (ES)

Sparse principal component analysis in medical shape modeling

Science.gov (United States)

Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus

2006-03-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

Science.gov (United States)

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Radiation effects on eye components

Science.gov (United States)

Durchschlag, H.; Fochler, C.; Abraham, K.; Kulawik, B.

1999-08-01

The most important water-soluble components of the vertebrate eye (lens proteins, aqueous humor, vitreous, hyaluronic acid, ascorbic acid) have been investigated in aqueous solution, after preceding X- or UV-irradiation. Spectroscopic, chromatographic, electrophoretic, hydrodynamic and analytic techniques have been applied, to monitor several radiation damages such as destruction of aromatic and sulfur-containing amino acids, aggregation, crosslinking, dissociation, fragmentation, and partial unfolding. Various substances were found which were able to protect eye components effectively against radiation, some of them being also of medical relevance.

Fast principal component analysis for stacking seismic data

Science.gov (United States)

Wu, Juan; Bai, Min

2018-04-01

Stacking seismic data plays an indispensable role in many steps of the seismic data processing and imaging workflow. Optimal stacking of seismic data can help mitigate seismic noise and enhance the principal components to a great extent. Traditional average-based seismic stacking methods cannot obtain optimal performance when the ambient noise is extremely strong. We propose a principal component analysis (PCA) algorithm for stacking seismic data without being sensitive to noise level. Considering the computational bottleneck of the classic PCA algorithm in processing massive seismic data, we propose an efficient PCA algorithm to make the proposed method readily applicable for industrial applications. Two numerically designed examples and one real seismic data are used to demonstrate the performance of the presented method.

Path and correlation analysis of perennial ryegrass (Lolium perenne L.) seed yield components

DEFF Research Database (Denmark)

Abel, Simon; Gislum, René; Boelt, Birte

2017-01-01

Maximum perennial ryegrass seed production potential is substantially greater than harvested yields with harvested yields representing only 20% of calculated potential. Similar to wheat, maize and other agriculturally important crops, seed yield is highly dependent on a number of interacting seed...... yield components. This research was performed to apply and describe path analysis of perennial ryegrass seed yield components in relation to harvested seed yields. Utilising extensive yield components which included subdividing reproductive inflorescences into five size categories, path analysis...... was undertaken assuming a unidirectional causal-admissible relationship between seed yield components and harvested seed yield in six commercial seed production fields. Both spikelets per inflorescence and florets per spikelet had a significant (p seed yield; however, total...

Pregabalin versus gabapentin in partial epilepsy: a meta-analysis of dose-response relationships

Directory of Open Access Journals (Sweden)

Thompson Sally

2010-11-01

Full Text Available Abstract Background To compare the efficacy of pregabalin and gabapentin at comparable effective dose levels in patients with refractory partial epilepsy. Methods Eight randomized placebo controlled trials investigating the efficacy of pregabalin (4 studies and gabapentin (4 studies over 12 weeks were identified with a systematic literature search. The endpoints of interest were "responder rate" (where response was defined as at least a 50% reduction from baseline in the number of seizures and "change from baseline in seizure-free days over the last 28 days (SFD". Results of all trials were analyzed using an indirect comparison approach with placebo as the common comparator. The base-case analysis used the intention-to-treat last observation carried forward method. Two sensitivity analyses were conducted among completer and responder populations. Results The base-case analysis revealed statistically significant differences in response rate in favor of pregabalin 300 mg versus gabapentin 1200 mg (odds ratio, 1.82; 95% confidence interval, 1.02, 3.25 and pregabalin 600 mg versus gabapentin 1800 mg (odds ratio, 2.52; 95% confidence interval, 1.21, 5.27. Both sensitivity analyses supported the findings of the base-case analysis, although statistical significance was not demonstrated. All dose levels of pregabalin (150 mg to 600 mg were more efficacious than corresponding dosages of gabapentin (900 mg to 2400 mg in terms of SFD over the last 28 days. Conclusion In patients with refractory partial epilepsy, pregabalin is likely to be more effective than gabapentin at comparable effective doses, based on clinical response and the number of SFD.

Failure trend analysis for safety related components of Korean standard NPPs

International Nuclear Information System (INIS)

Choi, Sun Yeong; Han, Sang Hoon

2005-01-01

The component reliability data of Korean NPP that reflects the plant specific characteristics is required necessarily for PSA of Korean nuclear power plants. We have performed a project to develop the component reliability database (KIND, Korea Integrated Nuclear Reliability Database) and S/W for database management and component reliability analysis. Based on the system, we have collected the component operation data and failure/repair data during from plant operation date to 2002 for YGN 3, 4 and UCN 3, 4 plants. Recently, we provided the component failure rate data for UCN 3, 4 standard PSA model from the KIND. We evaluated the components that have high-ranking failure rates with the component reliability data from plant operation date to 1998 and 2000 for YGN 3,4 and UCN 3, 4 respectively. We also identified their failure mode that occurred frequently. In this study, we analyze the component failure trend and perform site comparison based on the generic data by using the component reliability data which is extended to 2002 for UCN 3, 4 and YGN 3, 4 respectively. We focus on the major safety related rotating components such as pump, EDG etc

Repair process and a repaired component

Energy Technology Data Exchange (ETDEWEB)

Roberts, III, Herbert Chidsey; Simpson, Stanley F.

2018-02-20

Matrix composite component repair processes are disclosed. The matrix composite repair process includes applying a repair material to a matrix composite component, securing the repair material to the matrix composite component with an external securing mechanism and curing the repair material to bond the repair material to the matrix composite component during the securing by the external securing mechanism. The matrix composite component is selected from the group consisting of a ceramic matrix composite, a polymer matrix composite, and a metal matrix composite. In another embodiment, the repair process includes applying a partially-cured repair material to a matrix composite component, and curing the repair material to bond the repair material to the matrix composite component, an external securing mechanism securing the repair material throughout a curing period, In another embodiment, the external securing mechanism is consumed or decomposed during the repair process.

A Genealogical Interpretation of Principal Components Analysis

Science.gov (United States)

McVean, Gil

2009-01-01

Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to inform about historical demographic processes, little is known about the relationship between fundamental demographic parameters and the projection of samples onto the primary axes. Here I show that for SNP data the projection of samples onto the principal components can be obtained directly from considering the average coalescent times between pairs of haploid genomes. The result provides a framework for interpreting PCA projections in terms of underlying processes, including migration, geographical isolation, and admixture. I also demonstrate a link between PCA and Wright's fst and show that SNP ascertainment has a largely simple and predictable effect on the projection of samples. Using examples from human genetics, I discuss the application of these results to empirical data and the implications for inference. PMID:19834557

Mathematical Methods for Engineers and Scientists 3 Fourier Analysis, Partial Differential Equations and Variational Methods

CERN Document Server

Tang, Kwong-Tin

2007-01-01

Pedagogical insights gained through 30 years of teaching applied mathematics led the author to write this set of student oriented books. Topics such as complex analysis, matrix theory, vector and tensor analysis, Fourier analysis, integral transforms, ordinary and partial differential equations are presented in a discursive style that is readable and easy to follow. Numerous clearly stated, completely worked out examples together with carefully selected problem sets with answers are used to enhance students' understanding and manipulative skill. The goal is to make students comfortable and confident in using advanced mathematical tools in junior, senior, and beginning graduate courses.

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.

Sensitivity analysis on the component cooling system of the Angra 1 NPP

International Nuclear Information System (INIS)

Castro Silva, Luiz Euripedes Massiere de

1995-01-01

The component cooling system has been studied within the scope of the Probabilistic Safety Analysis of the Angra I NPP in order to assure that the proposed modelling suits as close as possible the functioning system and its availability aspects. In such a way a sensitivity analysis was performed on the equivalence between the operating modes of the component cooling system and its results show the fitness of the model. (author). 4 refs, 3 figs, 3 tabs

Efectivity of Additive Spline for Partial Least Square Method in Regression Model Estimation

Directory of Open Access Journals (Sweden)

Ahmad Bilfarsah

2005-04-01

Full Text Available Additive Spline of Partial Least Square method (ASPL as one generalization of Partial Least Square (PLS method. ASPLS method can be acommodation to non linear and multicollinearity case of predictor variables. As a principle, The ASPLS method approach is cahracterized by two idea. The first is to used parametric transformations of predictors by spline function; the second is to make ASPLS components mutually uncorrelated, to preserve properties of the linear PLS components. The performance of ASPLS compared with other PLS method is illustrated with the fisher economic application especially the tuna fish production.

Reliability Analysis of 6-Component Star Markov Repairable System with Spatial Dependence

Directory of Open Access Journals (Sweden)

Liying Wang

2017-01-01

Full Text Available Star repairable systems with spatial dependence consist of a center component and several peripheral components. The peripheral components are arranged around the center component, and the performance of each component depends on its spatial “neighbors.” Vector-Markov process is adapted to describe the performance of the system. The state space and transition rate matrix corresponding to the 6-component star Markov repairable system with spatial dependence are presented via probability analysis method. Several reliability indices, such as the availability, the probabilities of visiting the safety, the degradation, the alert, and the failed state sets, are obtained by Laplace transform method and a numerical example is provided to illustrate the results.

Optimization benefits analysis in production process of fabrication components

Science.gov (United States)

Prasetyani, R.; Rafsanjani, A. Y.; Rimantho, D.

2017-12-01

The determination of an optimal number of product combinations is important. The main problem at part and service department in PT. United Tractors Pandu Engineering (shortened to PT.UTPE) Is the optimization of the combination of fabrication component products (known as Liner Plate) which influence to the profit that will be obtained by the company. Liner Plate is a fabrication component that serves as a protector of core structure for heavy duty attachment, such as HD Vessel, HD Bucket, HD Shovel, and HD Blade. The graph of liner plate sales from January to December 2016 has fluctuated and there is no direct conclusion about the optimization of production of such fabrication components. The optimal product combination can be achieved by calculating and plotting the amount of production output and input appropriately. The method that used in this study is linear programming methods with primal, dual, and sensitivity analysis using QM software for Windows to obtain optimal fabrication components. In the optimal combination of components, PT. UTPE provide the profit increase of Rp. 105,285,000.00 for a total of Rp. 3,046,525,000.00 per month and the production of a total combination of 71 units per unit variance per month.

[Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

Science.gov (United States)

Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

2011-11-01

The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

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.

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.

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

Sensitivity Analysis on Elbow Piping Components in Seismically Isolated NPP under Seismic Loading

Energy Technology Data Exchange (ETDEWEB)

Ju, Hee Kun; Hahm, Dae Gi; Kim, Min Kyu [KAERI, Daejeon (Korea, Republic of); Jeon, Bub Gyu; Kim, Nam Sik [Pusan National University, Busan (Korea, Republic of)

2016-05-15

In this study, the FE model is verified using specimen test results and simulation with parameter variations are conducted. Effective parameters will randomly sampled and used as input values for simulations to be applied to the fragility analysis. pipelines are representative of them because they could undergo larger displacements when they are supported on both isolated and non-isolated structures simultaneously. Especially elbows are critical components of pipes under severed loading conditions such as earthquake action because strain is accumulated on them during the repeated bending of the pipe. Therefore, seismic performance of pipe elbow components should be examined thoroughly based on the fragility analysis. Fragility assessment of interface pipe should take different sources of uncertainty into account. However, selection of important sources and repeated tests with many random input values are very time consuming and expensive, so numerical analysis is commonly used. In the present study, finite element (FE) model of elbow component will be validated using the dynamic test results of elbow components. Using the verified model, sensitivity analysis will be implemented as a preliminary process of seismic fragility of piping system. Several important input parameters are selected and how the uncertainty of them are apportioned to the uncertainty of the elbow response is to be studied. Piping elbows are critical components under cyclic loading conditions as they are subjected large displacement. In a seismically isolated NPP, seismic capacity of piping system should be evaluated with caution. Seismic fragility assessment preliminarily needs parameter sensitivity analysis about the output of interest with different input parameter values.

Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis

Directory of Open Access Journals (Sweden)

Xiaoming Xu

2017-01-01

Full Text Available In traditional principle component analysis (PCA, because of the neglect of the dimensions influence between different variables in the system, the selected principal components (PCs often fail to be representative. While the relative transformation PCA is able to solve the above problem, it is not easy to calculate the weight for each characteristic variable. In order to solve it, this paper proposes a kind of fault diagnosis method based on information entropy and Relative Principle Component Analysis. Firstly, the algorithm calculates the information entropy for each characteristic variable in the original dataset based on the information gain algorithm. Secondly, it standardizes every variable’s dimension in the dataset. And, then, according to the information entropy, it allocates the weight for each standardized characteristic variable. Finally, it utilizes the relative-principal-components model established for fault diagnosis. Furthermore, the simulation experiments based on Tennessee Eastman process and Wine datasets demonstrate the feasibility and effectiveness of the new method.

Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components

Energy Technology Data Exchange (ETDEWEB)

Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc

2017-06-27

The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.

Numerical Analysis for Stochastic Partial Differential Delay Equations with Jumps

OpenAIRE

Li, Yan; Hu, Junhao

2013-01-01

We investigate the convergence rate of Euler-Maruyama method for a class of stochastic partial differential delay equations driven by both Brownian motion and Poisson point processes. We discretize in space by a Galerkin method and in time by using a stochastic exponential integrator. We generalize some results of Bao et al. (2011) and Jacob et al. (2009) in finite dimensions to a class of stochastic partial differential delay equations with jumps in infinite dimensions.

MULTI-COMPONENT ANALYSIS OF POSITION-VELOCITY CUBES OF THE HH 34 JET

International Nuclear Information System (INIS)

Rodríguez-González, A.; Esquivel, A.; Raga, A. C.; Cantó, J.; Curiel, S.; Riera, A.; Beck, T. L.

2012-01-01

We present an analysis of Hα spectra of the HH 34 jet with two-dimensional spectral resolution. We carry out multi-Gaussian fits to the spatially resolved line profiles and derive maps of the intensity, radial velocity, and velocity width of each of the components. We find that close to the outflow source we have three components: a high (negative) radial velocity component with a well-collimated, jet-like morphology; an intermediate velocity component with a broader morphology; and a positive radial velocity component with a non-collimated morphology and large linewidth. We suggest that this positive velocity component is associated with jet emission scattered in stationary dust present in the circumstellar environment. Farther away from the outflow source, we find only two components (a high, negative radial velocity component, which has a narrower spatial distribution than an intermediate velocity component). The fitting procedure was carried out with the new AGA-V1 code, which is available online and is described in detail in this paper.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

Science.gov (United States)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Dual stacked partial least squares for analysis of near-infrared spectra

Energy Technology Data Exchange (ETDEWEB)

Bi, Yiming [Institute of Automation, Chinese Academy of Sciences, 100190 Beijing (China); Xie, Qiong, E-mail: yimbi@163.com [Institute of Automation, Chinese Academy of Sciences, 100190 Beijing (China); Peng, Silong; Tang, Liang; Hu, Yong; Tan, Jie [Institute of Automation, Chinese Academy of Sciences, 100190 Beijing (China); Zhao, Yuhui [School of Economics and Business, Northeastern University at Qinhuangdao, 066000 Qinhuangdao City (China); Li, Changwen [Food Research Institute of Tianjin Tasly Group, 300410 Tianjin (China)

2013-08-20

Graphical abstract: -- Highlights: •Dual stacking steps are used for multivariate calibration of near-infrared spectra. •A selective weighting strategy is introduced that only a subset of all available sub-models is used for model fusion. •Using two public near-infrared datasets, the proposed method achieved competitive results. •The method can be widely applied in many fields, such as Mid-infrared spectra data and Raman spectra data. -- Abstract: A new ensemble learning algorithm is presented for quantitative analysis of near-infrared spectra. The algorithm contains two steps of stacked regression and Partial Least Squares (PLS), termed Dual Stacked Partial Least Squares (DSPLS) algorithm. First, several sub-models were generated from the whole calibration set. The inner-stack step was implemented on sub-intervals of the spectrum. Then the outer-stack step was used to combine these sub-models. Several combination rules of the outer-stack step were analyzed for the proposed DSPLS algorithm. In addition, a novel selective weighting rule was also involved to select a subset of all available sub-models. Experiments on two public near-infrared datasets demonstrate that the proposed DSPLS with selective weighting rule provided superior prediction performance and outperformed the conventional PLS algorithm. Compared with the single model, the new ensemble model can provide more robust prediction result and can be considered an alternative choice for quantitative analytical applications.

Dual stacked partial least squares for analysis of near-infrared spectra

International Nuclear Information System (INIS)

Bi, Yiming; Xie, Qiong; Peng, Silong; Tang, Liang; Hu, Yong; Tan, Jie; Zhao, Yuhui; Li, Changwen

2013-01-01

Graphical abstract: -- Highlights: •Dual stacking steps are used for multivariate calibration of near-infrared spectra. •A selective weighting strategy is introduced that only a subset of all available sub-models is used for model fusion. •Using two public near-infrared datasets, the proposed method achieved competitive results. •The method can be widely applied in many fields, such as Mid-infrared spectra data and Raman spectra data. -- Abstract: A new ensemble learning algorithm is presented for quantitative analysis of near-infrared spectra. The algorithm contains two steps of stacked regression and Partial Least Squares (PLS), termed Dual Stacked Partial Least Squares (DSPLS) algorithm. First, several sub-models were generated from the whole calibration set. The inner-stack step was implemented on sub-intervals of the spectrum. Then the outer-stack step was used to combine these sub-models. Several combination rules of the outer-stack step were analyzed for the proposed DSPLS algorithm. In addition, a novel selective weighting rule was also involved to select a subset of all available sub-models. Experiments on two public near-infrared datasets demonstrate that the proposed DSPLS with selective weighting rule provided superior prediction performance and outperformed the conventional PLS algorithm. Compared with the single model, the new ensemble model can provide more robust prediction result and can be considered an alternative choice for quantitative analytical applications

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.

Enantiomer-specific analysis of multi-component mixtures by correlated electron imaging-ion mass spectrometry

NARCIS (Netherlands)

Rafiee Fanood, M.M.; Ram, N.B.; Lehmann, C.S.; Powis, I.; Janssen, M.H.M.

2015-01-01

Simultaneous, enantiomer-specific identification of chiral molecules in multi-component mixtures is extremely challenging. Many established techniques for single-component analysis fail to provide selectivity in multi-component mixtures and lack sensitivity for dilute samples. Here we show how

Identification of components of fibroadenoma in cytology preparations using texture analysis: a morphometric study.

Science.gov (United States)

Singh, S; Gupta, R

2012-06-01

To evaluate the utility of image analysis using textural parameters obtained from a co-occurrence matrix in differentiating the three components of fibroadenoma of the breast, in fine needle aspirate smears. Sixty cases of histologically proven fibroadenoma were included in this study. Of these, 40 cases were used as a training set and 20 cases were taken as a test set for the discriminant analysis. Digital images were acquired from cytological preparations of all the cases and three components of fibroadenoma (namely, monolayered cell clusters, stromal fragments and background with bare nuclei) were selected for image analysis. A co-occurrence matrix was generated and a texture parameter vector (sum mean, energy, entropy, contrast, cluster tendency and homogeneity) was calculated for each pixel. The percentage of pixels correctly classified to a component of fibroadenoma on discriminant analysis was noted. The textural parameters, when considered in isolation, showed considerable overlap in their values of the three cytological components of fibroadenoma. However, the stepwise discriminant analysis revealed that all six textural parameters contributed significantly to the discriminant functions. Discriminant analysis using all the six parameters showed that the numbers of pixels correctly classified in training and tests sets were 96.7% and 93.0%, respectively. Textural analysis using a co-occurrence matrix appears to be useful in differentiating the three cytological components of fibroadenoma. These results could further be utilized in developing algorithms for image segmentation and automated diagnosis, but need to be confirmed in further studies. © 2011 Blackwell Publishing Ltd.

On the Partial-Wave Analysis of Mesonic Resonances Decaying to Multiparticle Final States Produced by Polarized Photons

Energy Technology Data Exchange (ETDEWEB)

Salgado, Carlos W. [Norfolk State University, Norfolk, VA (United States) and Thomas Jefferson National Accelerator Facility, Newport News, VA (United States); Weygand, Dennis P. [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States)

2014-04-01

Meson spectroscopy is going through a revival with the advent of high statistics experiments and new advances in the theoretical predictions. The Constituent Quark Model (CQM) is finally being expanded considering more basic principles of field theory and using discrete calculations of Quantum Chromodynamics (lattice QCD). These new calculations are approaching predictive power for the spectrum of hadronic resonances and decay modes. It will be the task of the new experiments to extract the meson spectrum from the data and compare with those predictions. The goal of this report is to describe one particular technique for extracting resonance information from multiparticle final states. The technique described here, partial wave analysis based on the helicity formalism, has been used at Brookhaven National Laboratory (BNL) using pion beams, and Jefferson Laboratory (Jlab) using photon beams. In particular this report broaden this technique to include production experiments using linearly polarized real photons or quasi-real photons. This article is of a didactical nature. We describe the process of analysis, detailing assumptions and formalisms, and is directed towards people interested in starting partial wave analysis.

Confirmation of a novel siadenovirus species detected in raptors: partial sequence and phylogenetic analysis.

Science.gov (United States)

Kovács, Endre R; Benko, Mária

2009-03-01

Partial genome characterisation of a novel adenovirus, found recently in organ samples of multiple species of dead birds of prey, was carried out by sequence analysis of PCR-amplified DNA fragments. The virus, named as raptor adenovirus 1 (RAdV-1), has originally been detected by a nested PCR method with consensus primers targeting the adenoviral DNA polymerase gene. Phylogenetic analysis with the deduced amino acid sequence of the small PCR product has implied a new siadenovirus type present in the samples. Since virus isolation attempts remained unsuccessful, further characterisation of this putative novel siadenovirus was carried out with the use of PCR on the infected organ samples. The DNA sequence of the central genome part of RAdV-1, encompassing nine full (pTP, 52K, pIIIa, III, pVII, pX, pVI, hexon, protease) and two partial (DNA polymerase and DBP) genes and exceeding 12 kb pairs in size, was determined. Phylogenetic tree reconstructions, based on several genes, unambiguously confirmed the preliminary classification of RAdV-1 as a new species within the genus Siadenovirus. Further study of RAdV-1 is of interest since it represents a rare adenovirus genus of yet undetermined host origin.

Facilitating preemptive hardware system design using partial reconfiguration techniques.

Science.gov (United States)

Dondo Gazzano, Julio; Rincon, Fernando; Vaderrama, Carlos; Villanueva, Felix; Caba, Julian; Lopez, Juan Carlos

2014-01-01

In FPGA-based control system design, partial reconfiguration is especially well suited to implement preemptive systems. In real-time systems, the deadline for critical task can compel the preemption of noncritical one. Besides, an asynchronous event can demand immediate attention and, then, force launching a reconfiguration process for high-priority task implementation. If the asynchronous event is previously scheduled, an explicit activation of the reconfiguration process is performed. If the event cannot be previously programmed, such as in dynamically scheduled systems, an implicit activation to the reconfiguration process is demanded. This paper provides a hardware-based approach to explicit and implicit activation of the partial reconfiguration process in dynamically reconfigurable SoCs and includes all the necessary tasks to cope with this issue. Furthermore, the reconfiguration service introduced in this work allows remote invocation of the reconfiguration process and then the remote integration of off-chip components. A model that offers component location transparency is also presented to enhance and facilitate system integration.

$L^2$ estimates for the $\\bar \\partial$ operator

OpenAIRE

McNeal, Jeffery D.; Varolin, Dror

2015-01-01

This is a survey article about $L^2$ estimates for the $\\bar \\partial$ operator. After a review of the basic approach that has come to be called the "Bochner-Kodaira Technique", the focus is on twisted techniques and their applications to estimates for $\\bar \\partial$, to $L^2$ extension theorems, and to other problems in complex analysis and geometry, including invariant metric estimates and the $\\bar \\partial$-Neumann Problem.

Component analysis and initial validity of the exercise fear avoidance scale.

Science.gov (United States)

Wingo, Brooks C; Baskin, Monica; Ard, Jamy D; Evans, Retta; Roy, Jane; Vogtle, Laura; Grimley, Diane; Snyder, Scott

2013-01-01

To develop the Exercise Fear Avoidance Scale (EFAS) to measure fear of exercise-induced discomfort. We conducted principal component analysis to determine component structure and Cronbach's alpha to assess internal consistency of the EFAS. Relationships between EFAS scores, BMI, physical activity, and pain were analyzed using multivariate regression. The best fit was a 3-component structure: weight-specific fears, cardiorespiratory fears, and musculoskeletal fears. Cronbach's alpha for the EFAS was α=.86. EFAS scores significantly predicted BMI, physical activity, and PDI scores. Psychometric properties of this scale suggest it may be useful for tailoring exercise prescriptions to address fear of exercise-related discomfort.

Fusion-component lifetime analysis

International Nuclear Information System (INIS)

Mattas, R.F.

1982-09-01

A one-dimensional computer code has been developed to examine the lifetime of first-wall and impurity-control components. The code incorporates the operating and design parameters, the material characteristics, and the appropriate failure criteria for the individual components. The major emphasis of the modeling effort has been to calculate the temperature-stress-strain-radiation effects history of a component so that the synergystic effects between sputtering erosion, swelling, creep, fatigue, and crack growth can be examined. The general forms of the property equations are the same for all materials in order to provide the greatest flexibility for materials selection in the code. The individual coefficients within the equations are different for each material. The code is capable of determining the behavior of a plate, composed of either a single or dual material structure, that is either totally constrained or constrained from bending but not from expansion. The code has been utilized to analyze the first walls for FED/INTOR and DEMO and to analyze the limiter for FED/INTOR

Methylation analysis of polysaccharides: Technical advice.

Science.gov (United States)

Sims, Ian M; Carnachan, Susan M; Bell, Tracey J; Hinkley, Simon F R

2018-05-15

Glycosyl linkage (methylation) analysis is used widely for the structural determination of oligo- and poly-saccharides. The procedure involves derivatisation of the individual component sugars of a polysaccharide to partially methylated alditol acetates which are analysed and quantified by gas chromatography-mass spectrometry. The linkage positions for each component sugar can be determined by correctly identifying the partially methylated alditol acetates. Although the methods are well established, there are many technical aspects to this procedure and both careful attention to detail and considerable experience are required to achieve a successful methylation analysis and to correctly interpret the data generated. The aim of this article is to provide the technical details and critical procedural steps necessary for a successful methylation analysis and to assist researchers (a) with interpreting data correctly and (b) in providing the comprehensive data required for reviewers to fully assess the work. Copyright © 2018 Elsevier Ltd. All rights reserved.

A multi-dimensional functional principal components analysis of EEG data.

Science.gov (United States)

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-09-01

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.

Aeromagnetic Compensation Algorithm Based on Principal Component Analysis

Directory of Open Access Journals (Sweden)

Peilin Wu

2018-01-01

Full Text Available Aeromagnetic exploration is an important exploration method in geophysics. The data is typically measured by optically pumped magnetometer mounted on an aircraft. But any aircraft produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is important in aeromagnetic exploration. However, multicollinearity of the aeromagnetic compensation model degrades the performance of the compensation. To address this issue, a novel aeromagnetic compensation method based on principal component analysis is proposed. Using the algorithm, the correlation in the feature matrix is eliminated and the principal components are using to construct the hyperplane to compensate the platform-generated magnetic fields. The algorithm was tested using a helicopter, and the obtained improvement ratio is 9.86. The compensated quality is almost the same or slightly better than the ridge regression. The validity of the proposed method was experimentally demonstrated.

Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis

Directory of Open Access Journals (Sweden)

A. Ahmad

2012-06-01

Full Text Available Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA of Moderate Resolution Imaging Spectroradiometer (MODIS data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4, three thermal bands (29, 31 and 32, the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect clouds. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.

Component identification of electron transport chains in curdlan-producing Agrobacterium sp. ATCC 31749 and its genome-specific prediction using comparative genome and phylogenetic trees analysis.

Science.gov (United States)

Zhang, Hongtao; Setubal, Joao Carlos; Zhan, Xiaobei; Zheng, Zhiyong; Yu, Lijun; Wu, Jianrong; Chen, Dingqiang

2011-06-01

Agrobacterium sp. ATCC 31749 (formerly named Alcaligenes faecalis var. myxogenes) is a non-pathogenic aerobic soil bacterium used in large scale biotechnological production of curdlan. However, little is known about its genomic information. DNA partial sequence of electron transport chains (ETCs) protein genes were obtained in order to understand the components of ETC and genomic-specificity in Agrobacterium sp. ATCC 31749. Degenerate primers were designed according to ETC conserved sequences in other reported species. DNA partial sequences of ETC genes in Agrobacterium sp. ATCC 31749 were cloned by the PCR method using degenerate primers. Based on comparative genomic analysis, nine electron transport elements were ascertained, including NADH ubiquinone oxidoreductase, succinate dehydrogenase complex II, complex III, cytochrome c, ubiquinone biosynthesis protein ubiB, cytochrome d terminal oxidase, cytochrome bo terminal oxidase, cytochrome cbb (3)-type terminal oxidase and cytochrome caa (3)-type terminal oxidase. Similarity and phylogenetic analyses of these genes revealed that among fully sequenced Agrobacterium species, Agrobacterium sp. ATCC 31749 is closest to Agrobacterium tumefaciens C58. Based on these results a comprehensive ETC model for Agrobacterium sp. ATCC 31749 is proposed.

Structural analysis of NPP components and structures

International Nuclear Information System (INIS)

Saarenheimo, A.; Keinaenen, H.; Talja, H.

1998-01-01

Capabilities for effective structural integrity assessment have been created and extended in several important cases. In the paper presented applications deal with pressurised thermal shock loading, PTS, and severe dynamic loading cases of containment, reinforced concrete structures and piping components. Hydrogen combustion within the containment is considered in some severe accident scenarios. Can a steel containment withstand the postulated hydrogen detonation loads and still maintain its integrity? This is the topic of Chapter 2. The following Chapter 3 deals with a reinforced concrete floor subjected to jet impingement caused by a postulated rupture of a near-by high-energy pipe and Chapter 4 deals with dynamic loading resistance of the pipe lines under postulated pressure transients due to water hammer. The reliability of the structural integrity analysing methods and capabilities which have been developed for application in NPP component assessment, shall be evaluated and verified. The resources available within the RATU2 programme alone cannot allow performing of the large scale experiments needed for that purpose. Thus, the verification of the PTS analysis capabilities has been conducted by participation in international co-operative programmes. Participation to the European Network for Evaluating Steel Components (NESC) is the topic of a parallel paper in this symposium. The results obtained in two other international programmes are summarised in Chapters 5 and 6 of this paper, where PTS tests with a model vessel and benchmark assessment of a RPV nozzle integrity are described. (author)

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

Science.gov (United States)

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

Principal component analysis of FDG PET in amnestic MCI

International Nuclear Information System (INIS)

Nobili, Flavio; Girtler, Nicola; Brugnolo, Andrea; Dessi, Barbara; Rodriguez, Guido; Salmaso, Dario; Morbelli, Silvia; Piccardo, Arnoldo; Larsson, Stig A.; Pagani, Marco

2008-01-01

The purpose of the study is to evaluate the combined accuracy of episodic memory performance and 18 F-FDG PET in identifying patients with amnestic mild cognitive impairment (aMCI) converting to Alzheimer's disease (AD), aMCI non-converters, and controls. Thirty-three patients with aMCI and 15 controls (CTR) were followed up for a mean of 21 months. Eleven patients developed AD (MCI/AD) and 22 remained with aMCI (MCI/MCI). 18 F-FDG PET volumetric regions of interest underwent principal component analysis (PCA) that identified 12 principal components (PC), expressed by coarse component scores (CCS). Discriminant analysis was performed using the significant PCs and episodic memory scores. PCA highlighted relative hypometabolism in PC5, including bilateral posterior cingulate and left temporal pole, and in PC7, including the bilateral orbitofrontal cortex, both in MCI/MCI and MCI/AD vs CTR. PC5 itself plus PC12, including the left lateral frontal cortex (LFC: BAs 44, 45, 46, 47), were significantly different between MCI/AD and MCI/MCI. By a three-group discriminant analysis, CTR were more accurately identified by PET-CCS + delayed recall score (100%), MCI/MCI by PET-CCS + either immediate or delayed recall scores (91%), while MCI/AD was identified by PET-CCS alone (82%). PET increased by 25% the correct allocations achieved by memory scores, while memory scores increased by 15% the correct allocations achieved by PET. Combining memory performance and 18 F-FDG PET yielded a higher accuracy than each single tool in identifying CTR and MCI/MCI. The PC containing bilateral posterior cingulate and left temporal pole was the hallmark of MCI/MCI patients, while the PC including the left LFC was the hallmark of conversion to AD. (orig.)

Principal component analysis of FDG PET in amnestic MCI

Energy Technology Data Exchange (ETDEWEB)

Nobili, Flavio; Girtler, Nicola; Brugnolo, Andrea; Dessi, Barbara; Rodriguez, Guido [University of Genoa, Clinical Neurophysiology, Department of Endocrinological and Medical Sciences, Genoa (Italy); S. Martino Hospital, Alzheimer Evaluation Unit, Genoa (Italy); S. Martino Hospital, Head-Neck Department, Genoa (Italy); Salmaso, Dario [CNR, Institute of Cognitive Sciences and Technologies, Rome (Italy); CNR, Institute of Cognitive Sciences and Technologies, Padua (Italy); Morbelli, Silvia [University of Genoa, Nuclear Medicine Unit, Department of Internal Medicine, Genoa (Italy); Piccardo, Arnoldo [Galliera Hospital, Nuclear Medicine Unit, Department of Imaging Diagnostics, Genoa (Italy); Larsson, Stig A. [Karolinska Hospital, Department of Nuclear Medicine, Stockholm (Sweden); Pagani, Marco [CNR, Institute of Cognitive Sciences and Technologies, Rome (Italy); CNR, Institute of Cognitive Sciences and Technologies, Padua (Italy); Karolinska Hospital, Department of Nuclear Medicine, Stockholm (Sweden)

2008-12-15

The purpose of the study is to evaluate the combined accuracy of episodic memory performance and {sup 18}F-FDG PET in identifying patients with amnestic mild cognitive impairment (aMCI) converting to Alzheimer's disease (AD), aMCI non-converters, and controls. Thirty-three patients with aMCI and 15 controls (CTR) were followed up for a mean of 21 months. Eleven patients developed AD (MCI/AD) and 22 remained with aMCI (MCI/MCI). {sup 18}F-FDG PET volumetric regions of interest underwent principal component analysis (PCA) that identified 12 principal components (PC), expressed by coarse component scores (CCS). Discriminant analysis was performed using the significant PCs and episodic memory scores. PCA highlighted relative hypometabolism in PC5, including bilateral posterior cingulate and left temporal pole, and in PC7, including the bilateral orbitofrontal cortex, both in MCI/MCI and MCI/AD vs CTR. PC5 itself plus PC12, including the left lateral frontal cortex (LFC: BAs 44, 45, 46, 47), were significantly different between MCI/AD and MCI/MCI. By a three-group discriminant analysis, CTR were more accurately identified by PET-CCS + delayed recall score (100%), MCI/MCI by PET-CCS + either immediate or delayed recall scores (91%), while MCI/AD was identified by PET-CCS alone (82%). PET increased by 25% the correct allocations achieved by memory scores, while memory scores increased by 15% the correct allocations achieved by PET. Combining memory performance and {sup 18}F-FDG PET yielded a higher accuracy than each single tool in identifying CTR and MCI/MCI. The PC containing bilateral posterior cingulate and left temporal pole was the hallmark of MCI/MCI patients, while the PC including the left LFC was the hallmark of conversion to AD. (orig.)

Fluorescence lifetime selectivity in excitation-emission matrices for qualitative analysis of a two-component system

International Nuclear Information System (INIS)

Millican, D.W.; McGown, L.B.

1989-01-01

Steady-state fluorescence excitation-emission matrices (EEMs), and phase-resolved EEMs (PREEMs) collected at modulation frequencies of 6, 18, and 30 MHz, were used for qualitative analysis of mixtures of benzo[k]fluoranthene (τ = 8 ns) and benzo[b]fluoranthene (τ = 29 ns) in ethanol. The EEMs of the individual components were extracted from mixture EEMs by means of wavelength component vector-gram (WCV) analysis. Phase resolution was found to be superior to steady-state measurements for extraction of the component spectra, for mixtures in which the intensity contributions from the two components are unequal

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.

The analysis of multivariate group differences using common principal components

NARCIS (Netherlands)

Bechger, T.M.; Blanca, M.J.; Maris, G.

2014-01-01

Although it is simple to determine whether multivariate group differences are statistically significant or not, such differences are often difficult to interpret. This article is about common principal components analysis as a tool for the exploratory investigation of multivariate group differences

Source Signals Separation and Reconstruction Following Principal Component Analysis

Directory of Open Access Journals (Sweden)

WANG Cheng

2014-02-01

Full Text Available For separation and reconstruction of source signals from observed signals problem, the physical significance of blind source separation modal and independent component analysis is not very clear, and its solution is not unique. Aiming at these disadvantages, a new linear and instantaneous mixing model and a novel source signals separation reconstruction solving method from observed signals based on principal component analysis (PCA are put forward. Assumption of this new model is statistically unrelated rather than independent of source signals, which is different from the traditional blind source separation model. A one-to-one relationship between linear and instantaneous mixing matrix of new model and linear compound matrix of PCA, and a one-to-one relationship between unrelated source signals and principal components are demonstrated using the concept of linear separation matrix and unrelated of source signals. Based on this theoretical link, source signals separation and reconstruction problem is changed into PCA of observed signals then. The theoretical derivation and numerical simulation results show that, in despite of Gauss measurement noise, wave form and amplitude information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal and normalized; only wave form information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal but not normalized, unrelated source signal cannot be separated and reconstructed by PCA when mixing matrix is not column orthogonal or linear.

Partial-wave analysis of π-π0π0 events at 18 GeV/c

International Nuclear Information System (INIS)

Brown, D.S.

1998-01-01

A partial-wave analysis has been performed on 170 K π - π 0 π 0 events produced in the reaction π - p→pπ - π 0 π 0 , and the results of the mass-independent fits are presented. The objective was to confirm the existence of the π(1800) and the exotic J PC =1 -+ object, reported by VES. copyright 1998 American Institute of Physics

Thermodynamically consistent modeling and simulation of multi-component two-phase flow model with partial miscibility

KAUST Repository

Kou, Jisheng

2016-11-25

A general diffuse interface model with a realistic equation of state (e.g. Peng-Robinson equation of state) is proposed to describe the multi-component two-phase fluid flow based on the principles of the NVT-based framework which is a latest alternative over the NPT-based framework to model the realistic fluids. The proposed model uses the Helmholtz free energy rather than Gibbs free energy in the NPT-based framework. Different from the classical routines, we combine the first law of thermodynamics and related thermodynamical relations to derive the entropy balance equation, and then we derive a transport equation of the Helmholtz free energy density. Furthermore, by using the second law of thermodynamics, we derive a set of unified equations for both interfaces and bulk phases that can describe the partial miscibility of two fluids. A relation between the pressure gradient and chemical potential gradients is established, and this relation leads to a new formulation of the momentum balance equation, which demonstrates that chemical potential gradients become the primary driving force of fluid motion. Moreover, we prove that the proposed model satisfies the total (free) energy dissipation with time. For numerical simulation of the proposed model, the key difficulties result from the strong nonlinearity of Helmholtz free energy density and tight coupling relations between molar densities and velocity. To resolve these problems, we propose a novel convex-concave splitting of Helmholtz free energy density and deal well with the coupling relations between molar densities and velocity through very careful physical observations with a mathematical rigor. We prove that the proposed numerical scheme can preserve the discrete (free) energy dissipation. Numerical tests are carried out to verify the effectiveness of the proposed method.

Spectral Mixture Analysis: Linear and Semi-parametric Full and Iterated Partial Unmixing in Multi- and Hyperspectral Image Data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2001-01-01

) and non-negative least squares (NNLS), and the partial unmixing methods orthogonal subspace projection (OSP), constrained energy minimization (CEM) and an eigenvalue formulation alternative are dealt with. The solution to the eigenvalue formulation alternative proves to be identical to the CEM solution....... The matrix inversion involved in CEM can be avoided by working on (a subset of) orthogonally transformed data such as signal maximum autocorrelation factors, MAFs, or signal minimum noise fractions, MNFs. This will also cause the partial unmixing result to be independent of the noise isolated in the MAF....../MNFs not included in the analysis. CEM and the eigenvalue formulation alternative enable us to perform partial unmixing when we know one desired end-member spectrum only and not the full set of end-member spectra. This is an advantage over full unmixing and OSP. The eigenvalue formulation of CEM inspires us...

Genetic analysis of partial resistance to basal stem rot (Sclerotinia sclerotiorum in sunflower

Directory of Open Access Journals (Sweden)

Amouzadeh Masoumeh

2013-01-01

Full Text Available Basal stem rot, caused by Sclerotinia sclerotiorum (Lib. de Bary, is one of the major diseases of sunflower (Helianthus annuus L. in the world. Quantitative trait loci (QTLs implicated in partial resistance to basal stem rot disease were identified using 99 recombinant inbred lines (RILs from the cross between sunflower parental lines PAC2 and RHA266. The study was undertaken in a completely randomized design with three replications under controlled conditions. The RILs and their parental lines were inoculated with a moderately aggressive isolate of S. sclerotiorum (SSKH41. Resistance to disease was evaluated by measuring the percentage of necrosis area three days after inoculation. QTLs were mapped using an updated high-density SSR and SNP linkage map. ANOVA showed significant differences among sunflower lines for resistance to basal stem rot (P≤0.05. The frequency distribution of lines for susceptibility to disease showed a continuous pattern. Composite interval mapping analysis revealed 5 QTLs for percentage of necrotic area, localized on linkage groups 1, 3, 8, 10 and 17. The sign of additive effect was positive in 5 QTLs, suggesting that the additive allele for partial resistance to basal stem rot came from the paternal line (RHA266. The phenotypic variance explained by QTLs (R2 ranged from 0.5 to 3.16%. Identified genes (HUCL02246_1, GST and POD, and SSR markers (ORS338, and SSL3 encompassing the QTLs for partial resistance to basal stem rot could be good candidates for marker assisted selection.

Single and multi-component adsorption of salicylic acid, clofibric acid, carbamazepine and caffeine from water onto transition metal modified and partially calcined inorganic-organic pillared clay fixed beds.

Science.gov (United States)

Cabrera-Lafaurie, Wilman A; Román, Félix R; Hernández-Maldonado, Arturo J

2015-01-23

Fixed-beds of transition metal (Co(2+), Ni(2+) or Cu(2+)) inorganic-organic pillared clays (IOCs) were prepared to study single- and multi-component non-equilibrium adsorption of a set of pharmaceutical and personal care products (PPCPs: salicylic acid, clofibric acid, carbamazepine and caffeine) from water. Adsorption capacities for single components revealed that the copper(II) IOCs have better affinity toward salicylic and clofibric acid. However, multi-component adsorption tests showed a considerable decrease in adsorption capacity for the acids and an unusual selectivity toward carbamazepine depending on the transition metal. This was attributed to a combination of competition between PPCPs for adsorption sites, adsorbate-adsorbate interactions, and plausible pore blocking caused by carbamazepine. The cobalt(II) IOC bed that was partially calcined to fractionate the surfactant moiety showcased the best selectivity toward caffeine, even during multi-component adsorption. This was due to a combination of a mildly hydrophobic surface and interaction between the PPCP and cobalt(II). In general, the tests suggest that these IOCs may be a potential solution for the removal of PPCPs if employed in a layered-bed configuration, to take care of families of adsorbates in a sequence that would produce sharpened concentration wavefronts. Copyright © 2014 Elsevier B.V. All rights reserved.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

Science.gov (United States)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

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...

Supermembrane in D=5: component action

International Nuclear Information System (INIS)

Bellucci, S.; Kozyrev, N.; Krivonos, S.; Yeranyan, A.

2014-01-01

Based on the connection between partial breaking of global supersymmetry, coset approach, which realized the given pattern of supersymmetry breaking, and the Nambu-Goto actions for the extended objects, we have constructed on-shell component action for N=1,D=5 supermembrane and its dual cousins. We demonstrate that the proper choice of the components and the use of the covariant (with respect to broken supersymmetry) derivatives drastically simplify the action: it can be represented as a sum of four terms each having an explicit geometric meaning

The derivative assay--an analysis of two fast components of DNA rejoining kinetics

International Nuclear Information System (INIS)

Sandstroem, B.E.

1989-01-01

The DNA rejoining kinetics of human U-118 MG cells were studied after gamma-irradiation with 4 Gy. The analysis of the sealing rate of the induced DNA strand breaks was made with a modification of the DNA unwinding technique. The modification meant that rather than just monitoring the number of existing breaks at each time of analysis, the velocity, at which the rejoining process proceeded, was determined. Two apparent first-order components of single-strand break repair could be identified during the 25 min of analysis. The half-times for the two components were 1.9 and 16 min, respectively

A Generalized Partial Credit Model: Application of an EM Algorithm.

Science.gov (United States)

Muraki, Eiji

1992-01-01

The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)

Radar fall detection using principal component analysis

Science.gov (United States)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Predicting Insolvency : A comparison between discriminant analysis and logistic regression using principal components

OpenAIRE

Geroukis, Asterios; Brorson, Erik

2014-01-01

In this study, we compare the two statistical techniques logistic regression and discriminant analysis to see how well they classify companies based on clusters – made from the solvency ratio ­– using principal components as independent variables. The principal components are made with different financial ratios. We use cluster analysis to find groups with low, medium and high solvency ratio of 1200 different companies found on the NASDAQ stock market and use this as an apriori definition of ...

Group-wise ANOVA simultaneous component analysis for designed omics experiments

NARCIS (Netherlands)

Saccenti, Edoardo; Smilde, Age K.; Camacho, José

2018-01-01

Introduction: Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis

Probabilistic methods in nuclear power plant component ageing analysis

International Nuclear Information System (INIS)

Simola, K.

1992-03-01

The nuclear power plant ageing research is aimed to ensure that the plant safety and reliability are maintained at a desired level through the designed, and possibly extended lifetime. In ageing studies, the reliability of components, systems and structures is evaluated taking into account the possible time- dependent decrease in reliability. The results of analyses can be used in the evaluation of the remaining lifetime of components and in the development of preventive maintenance, testing and replacement programmes. The report discusses the use of probabilistic models in the evaluations of the ageing of nuclear power plant components. The principles of nuclear power plant ageing studies are described and examples of ageing management programmes in foreign countries are given. The use of time-dependent probabilistic models to evaluate the ageing of various components and structures is described and the application of models is demonstrated with two case studies. In the case study of motor- operated closing valves the analysis are based on failure data obtained from a power plant. In the second example, the environmentally assisted crack growth is modelled with a computer code developed in United States, and the applicability of the model is evaluated on the basis of operating experience

Development of component failure data for seismic risk analysis

International Nuclear Information System (INIS)

Fray, R.R.; Moulia, T.A.

1981-01-01

This paper describes the quantification and utilization of seismic failure data used in the Diablo Canyon Seismic Risk Study. A single variable representation of earthquake severity that uses peak horizontal ground acceleration to characterize earthquake severity was employed. The use of a multiple variable representation would allow direct consideration of vertical accelerations and the spectral nature of earthquakes but would have added such complexity that the study would not have been feasible. Vertical accelerations and spectral nature were indirectly considered because component failure data were derived from design analyses, qualification tests and engineering judgment that did include such considerations. Two types of functions were used to describe component failure probabilities. Ramp functions were used for components, such as piping and structures, qualified by stress analysis. 'Anchor points' for ramp functions were selected by assuming a zero probability of failure at code allowable stress levels and unity probability of failure at ultimate stress levels. The accelerations corresponding to allowable and ultimate stress levels were determined by conservatively assuming a linear relationship between seismic stress and ground acceleration. Step functions were used for components, such as mechanical and electrical equipment, qualified by testing. Anchor points for step functions were selected by assuming a unity probability of failure above the qualification acceleration. (orig./HP)

Partial Safety Factors for Rubble Mound Breakwaters

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Burcharth, H. F.; Christiani, E.

1995-01-01

On the basis of the failure modes formulated in the various subtasks calibration of partial safety factors are described in this paper. The partial safety factors can be used to design breakwaters under quite different design conditions, namely probabilities of failure from 0.01 to 0.4, design...... lifetimes from 20 to 100 years and different qualities of wave data. A code of practice where safety is taken into account using partial safety factors is called a level I code. The partial safety factors are calibrated using First Order Reliability Methods (FORM, see Madsen et al. [1]) where...... in section 3. First Order Reliability Methods are described in section 4, and in section 5 it is shown how partial safety factors can be introduced and calibrated. The format of a code for design and analysis of rubble mound breakwaters is discussed in section 6. The mathematical formulation of the limit...

Partial Least Square Discriminant Analysis Discovered a Dietary Pattern Inversely Associated with Nasopharyngeal Carcinoma Risk.

Science.gov (United States)

Lo, Yen-Li; Pan, Wen-Harn; Hsu, Wan-Lun; Chien, Yin-Chu; Chen, Jen-Yang; Hsu, Mow-Ming; Lou, Pei-Jen; Chen, I-How; Hildesheim, Allan; Chen, Chien-Jen

2016-01-01

Evidence on the association between dietary component, dietary pattern and nasopharyngeal carcinoma (NPC) is scarce. A major challenge is the high degree of correlation among dietary constituents. We aimed to identify dietary pattern associated with NPC and to illustrate the dose-response relationship between the identified dietary pattern scores and the risk of NPC. Taking advantage of a matched NPC case-control study, data from a total of 319 incident cases and 319 matched controls were analyzed. Dietary pattern was derived employing partial least square discriminant analysis (PLS-DA) performed on energy-adjusted food frequencies derived from a 66-item food-frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated with multiple conditional logistic regression models, linking pattern scores and NPC risk. A high score of the PLS-DA derived pattern was characterized by high intakes of fruits, milk, fresh fish, vegetables, tea, and eggs ordered by loading values. We observed that one unit increase in the scores was associated with a significantly lower risk of NPC (ORadj = 0.73, 95% CI = 0.60-0.88) after controlling for potential confounders. Similar results were observed among Epstein-Barr virus seropositive subjects. An NPC protective diet is indicated with more phytonutrient-rich plant foods (fruits, vegetables), milk, other protein-rich foods (in particular fresh fish and eggs), and tea. This information may be used to design potential dietary regimen for NPC prevention.

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....

Robust-BD Estimation and Inference for General Partially Linear Models

Directory of Open Access Journals (Sweden)

Chunming Zhang

2017-11-01

Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.

Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

Directory of Open Access Journals (Sweden)

Hesse Morten

2005-05-01

Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

Reformulating Component Identification as Document Analysis Problem

NARCIS (Netherlands)

Gross, H.G.; Lormans, M.; Zhou, J.

2007-01-01

One of the first steps of component procurement is the identification of required component features in large repositories of existing components. On the highest level of abstraction, component requirements as well as component descriptions are usually written in natural language. Therefore, we can

Thermogravimetric analysis of combustible waste components

DEFF Research Database (Denmark)

Munther, Anette; Wu, Hao; Glarborg, Peter

In order to gain fundamental knowledge about the co-combustion of coal and waste derived fuels, the pyrolytic behaviors of coal, four typical waste components and their mixtures have been studied by a simultaneous thermal analyzer (STA). The investigated waste components were wood, paper, polypro......In order to gain fundamental knowledge about the co-combustion of coal and waste derived fuels, the pyrolytic behaviors of coal, four typical waste components and their mixtures have been studied by a simultaneous thermal analyzer (STA). The investigated waste components were wood, paper...

Reliability Analysis of Fatigue Fracture of Wind Turbine Drivetrain Components

DEFF Research Database (Denmark)

Berzonskis, Arvydas; Sørensen, John Dalsgaard

2016-01-01

in the volume of the casted ductile iron main shaft, on the reliability of the component. The probabilistic reliability analysis conducted is based on fracture mechanics models. Additionally, the utilization of the probabilistic reliability for operation and maintenance planning and quality control is discussed....

Identifying effective components of child maltreatment interventions: A meta-analysis

NARCIS (Netherlands)

van der Put, C.E.; Assink, M.; Gubbels, J.; Boekhout van Solinge, N.F.

There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining

Principal component analysis of image gradient orientations for face recognition

NARCIS (Netherlands)

Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data

Reliability analysis of nuclear component cooling water system using semi-Markov process model

International Nuclear Information System (INIS)

Veeramany, Arun; Pandey, Mahesh D.

2011-01-01

Research highlights: → Semi-Markov process (SMP) model is used to evaluate system failure probability of the nuclear component cooling water (NCCW) system. → SMP is used because it can solve reliability block diagram with a mixture of redundant repairable and non-repairable components. → The primary objective is to demonstrate that SMP can consider Weibull failure time distribution for components while a Markov model cannot → Result: the variability in component failure time is directly proportional to the NCCW system failure probability. → The result can be utilized as an initiating event probability in probabilistic safety assessment projects. - Abstract: A reliability analysis of nuclear component cooling water (NCCW) system is carried out. Semi-Markov process model is used in the analysis because it has potential to solve a reliability block diagram with a mixture of repairable and non-repairable components. With Markov models it is only possible to assume an exponential profile for component failure times. An advantage of the proposed model is the ability to assume Weibull distribution for the failure time of components. In an attempt to reduce the number of states in the model, it is shown that usage of poly-Weibull distribution arises. The objective of the paper is to determine system failure probability under these assumptions. Monte Carlo simulation is used to validate the model result. This result can be utilized as an initiating event probability in probabilistic safety assessment projects.

Introduction to partial differential equations

CERN Document Server

Borthwick, David

2016-01-01

This modern take on partial differential equations does not require knowledge beyond vector calculus and linear algebra. The author focuses on the most important classical partial differential equations, including conservation equations and their characteristics, the wave equation, the heat equation, function spaces, and Fourier series, drawing on tools from analysis only as they arise.Within each section the author creates a narrative that answers the five questions: (1) What is the scientific problem we are trying to understand? (2) How do we model that with PDE? (3) What techniques can we use to analyze the PDE? (4) How do those techniques apply to this equation? (5) What information or insight did we obtain by developing and analyzing the PDE? The text stresses the interplay between modeling and mathematical analysis, providing a thorough source of problems and an inspiration for the development of methods.

Modified cleaning method for biomineralized components

Science.gov (United States)

Tsutsui, Hideto; Jordan, Richard W.

2018-02-01

The extraction and concentration of biomineralized components from sediment or living materials is time consuming and laborious and often involves steps that remove either the calcareous or siliceous part, in addition to organic matter. However, a relatively quick and easy method using a commercial cleaning fluid for kitchen drains, sometimes combined with a kerosene soaking step, can produce remarkable results. In this study, the method is applied to sediments and living materials bearing calcareous (e.g., coccoliths, foraminiferal tests, holothurian ossicles, ichthyoliths, and fish otoliths) and siliceous (e.g., diatom valves, silicoflagellate skeletons, and sponge spicules) components. The method preserves both components in the same sample, without etching or partial dissolution, but is not applicable to unmineralized components such as dinoflagellate thecae, tintinnid loricae, pollen, or plant fragments.

Principal component analysis of tomato genotypes based on some morphological and biochemical quality indicators

Directory of Open Access Journals (Sweden)

Glogovac Svetlana

2012-01-01

Full Text Available This study investigates variability of tomato genotypes based on morphological and biochemical fruit traits. Experimental material is a part of tomato genetic collection from Institute of Filed and Vegetable Crops in Novi Sad, Serbia. Genotypes were analyzed for fruit mass, locule number, index of fruit shape, fruit colour, dry matter content, total sugars, total acidity, lycopene and vitamin C. Minimum, maximum and average values and main indicators of variability (CV and σ were calculated. Principal component analysis was performed to determinate variability source structure. Four principal components, which contribute 93.75% of the total variability, were selected for analysis. The first principal component is defined by vitamin C, locule number and index of fruit shape. The second component is determined by dry matter content, and total acidity, the third by lycopene, fruit mass and fruit colour. Total sugars had the greatest part in the fourth component.

Cast Partial Denture versus Acrylic Partial Denture for Replacement of Missing Teeth in Partially Edentulous Patients

Directory of Open Access Journals (Sweden)

Pramita Suwal

2017-03-01

Full Text Available Aim: To compare the effects of cast partial denture with conventional all acrylic denture in respect to retention, stability, masticatory efficiency, comfort and periodontal health of abutments. Methods: 50 adult partially edentulous patient seeking for replacement of missing teeth having Kennedy class I and II arches with or without modification areas were selected for the study. Group-A was treated with cast partial denture and Group-B with acrylic partial denture. Data collected during follow-up visit of 3 months, 6 months, and 1 year by evaluating retention, stability, masticatory efficiency, comfort, periodontal health of abutment. Results: Chi-square test was applied to find out differences between the groups at 95% confidence interval where p = 0.05. One year comparison shows that cast partial denture maintained retention and stability better than acrylic partial denture (p< 0.05. The masticatory efficiency was significantly compromising from 3rd month to 1 year in all acrylic partial denture groups (p< 0.05. The comfort of patient with cast partial denture was maintained better during the observation period (p< 0.05. Periodontal health of abutment was gradually deteriorated in all acrylic denture group (p

DNA damage focus analysis in blood samples of minipigs reveals acute partial body irradiation.

Directory of Open Access Journals (Sweden)

Andreas Lamkowski

Full Text Available Radiation accidents frequently involve acute high dose partial body irradiation leading to victims with radiation sickness and cutaneous radiation syndrome that implements radiation-induced cell death. Cells that are not lethally hit seek to repair ionizing radiation (IR induced damage, albeit at the expense of an increased risk of mutation and tumor formation due to misrepair of IR-induced DNA double strand breaks (DSBs. The response to DNA damage includes phosphorylation of histone H2AX in the vicinity of DSBs, creating foci in the nucleus whose enumeration can serve as a radiation biodosimeter. Here, we investigated γH2AX and DNA repair foci in peripheral blood lymphocytes of Göttingen minipigs that experienced acute partial body irradiation (PBI with 49 Gy (± 6% Co-60 γ-rays of the upper lumbar region. Blood samples taken 4, 24 and 168 hours post PBI were subjected to γ-H2AX, 53BP1 and MRE11 focus enumeration. Peripheral blood lymphocytes (PBL of 49 Gy partial body irradiated minipigs were found to display 1-8 DNA damage foci/cell. These PBL values significantly deceed the high foci numbers observed in keratinocyte nuclei of the directly γ-irradiated minipig skin regions, indicating a limited resident time of PBL in the exposed tissue volume. Nonetheless, PBL samples obtained 4 h post IR in average contained 2.2% of cells displaying a pan-γH2AX signal, suggesting that these received a higher IR dose. Moreover, dispersion analysis indicated partial body irradiation for all 13 minipigs at 4 h post IR. While dose reconstruction using γH2AX DNA repair foci in lymphocytes after in vivo PBI represents a challenge, the DNA damage focus assay may serve as a rapid, first line indicator of radiation exposure. The occurrence of PBLs with pan-γH2AX staining and of cells with relatively high foci numbers that skew a Poisson distribution may be taken as indicator of acute high dose partial body irradiation, particularly when samples are available

Statistical Analysis of Partial Discharge Characteristics in Transformer Oil at the “Point-Plane” Electrode at Alternating Voltage

Directory of Open Access Journals (Sweden)

Korobeynikov S.M.

2017-08-01

Full Text Available In this paper, we consider the problems related to measuring and analyzing the characteristics of partial discharges which are the main instrument for oil-filled high-voltage electrical equipment diagnosing. The experiments on recording of partial discharges in transformer oil have been carried out in the “point-plane” electrode system at alternating current. The instantaneous voltage and the apparent charge have been measured depending on the root-mean-square voltage and the phase angle of partial discharges. This paper aimes at carrying out a statistical analysis of the obtained experimental results, in particular, the construction of a parametric probabilistic model of the dependence of the partial discharge inception voltage distribution on the value of the root-mean-square voltage. It differs from usual discharges which occur in liquid dielectric materials in case of sharp inhomogeneous electrode system. It has been suggested that discharges of a different type are the discharges in gas bubbles that occur when partial discharges in a liquid emerge. This assumption is confirmed by the fact that the number of such discharges increases with increasing the root-mean-square voltage value. It is the main novelty of this paper. This corresponds to the nature of the occurrence of such discharges. After rejecting the observations corresponding to discharges in gas bubbles, a parametric probabilistic model has been constructed. The model obtained makes it possible to determine the probability of partial discharge occurrence in a liquid at a given value of the instantaneous voltage depending on the root-mean-square voltage.

Using MDA for integration of heterogeneous components in software supply chains

NARCIS (Netherlands)

Hartmann, Johan Herman; Keren, Mila; Matsinger, Aart; Rubin, Julia; Trew, Tim; Yatzkar-Haham, Tali

2013-01-01

Software product lines are increasingly built using components from specialized suppliers. A company that is in the middle of a supply chain has to integrate components from its suppliers and offer (partially configured) products to its customers. To satisfy both the variability required by each

Buckling analysis of partially corroded steel plates with irregular ...

Indian Academy of Sciences (India)

Department of Ocean Engineering, AmirKabir University of Technology, ... could yield some acceptance criteria to assist surveyors or designers in repair and .... Finite element model of a partially both-sided corroded plate (shell elements).

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

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

Exploring Omics data from designed experiments using analysis of variance multiblock Orthogonal Partial Least Squares

International Nuclear Information System (INIS)

Boccard, Julien; Rudaz, Serge

2016-01-01

Many experimental factors may have an impact on chemical or biological systems. A thorough investigation of the potential effects and interactions between the factors is made possible by rationally planning the trials using systematic procedures, i.e. design of experiments. However, assessing factors' influences remains often a challenging task when dealing with hundreds to thousands of correlated variables, whereas only a limited number of samples is available. In that context, most of the existing strategies involve the ANOVA-based partitioning of sources of variation and the separate analysis of ANOVA submatrices using multivariate methods, to account for both the intrinsic characteristics of the data and the study design. However, these approaches lack the ability to summarise the data using a single model and remain somewhat limited for detecting and interpreting subtle perturbations hidden in complex Omics datasets. In the present work, a supervised multiblock algorithm based on the Orthogonal Partial Least Squares (OPLS) framework, is proposed for the joint analysis of ANOVA submatrices. This strategy has several advantages: (i) the evaluation of a unique multiblock model accounting for all sources of variation; (ii) the computation of a robust estimator (goodness of fit) for assessing the ANOVA decomposition reliability; (iii) the investigation of an effect-to-residuals ratio to quickly evaluate the relative importance of each effect and (iv) an easy interpretation of the model with appropriate outputs. Case studies from metabolomics and transcriptomics, highlighting the ability of the method to handle Omics data obtained from fixed-effects full factorial designs, are proposed for illustration purposes. Signal variations are easily related to main effects or interaction terms, while relevant biochemical information can be derived from the models. - Highlights: • A new method is proposed for the analysis of Omics data generated using design of experiments

Exploring Omics data from designed experiments using analysis of variance multiblock Orthogonal Partial Least Squares

Energy Technology Data Exchange (ETDEWEB)

Boccard, Julien, E-mail: julien.boccard@unige.ch; Rudaz, Serge

2016-05-12

Many experimental factors may have an impact on chemical or biological systems. A thorough investigation of the potential effects and interactions between the factors is made possible by rationally planning the trials using systematic procedures, i.e. design of experiments. However, assessing factors' influences remains often a challenging task when dealing with hundreds to thousands of correlated variables, whereas only a limited number of samples is available. In that context, most of the existing strategies involve the ANOVA-based partitioning of sources of variation and the separate analysis of ANOVA submatrices using multivariate methods, to account for both the intrinsic characteristics of the data and the study design. However, these approaches lack the ability to summarise the data using a single model and remain somewhat limited for detecting and interpreting subtle perturbations hidden in complex Omics datasets. In the present work, a supervised multiblock algorithm based on the Orthogonal Partial Least Squares (OPLS) framework, is proposed for the joint analysis of ANOVA submatrices. This strategy has several advantages: (i) the evaluation of a unique multiblock model accounting for all sources of variation; (ii) the computation of a robust estimator (goodness of fit) for assessing the ANOVA decomposition reliability; (iii) the investigation of an effect-to-residuals ratio to quickly evaluate the relative importance of each effect and (iv) an easy interpretation of the model with appropriate outputs. Case studies from metabolomics and transcriptomics, highlighting the ability of the method to handle Omics data obtained from fixed-effects full factorial designs, are proposed for illustration purposes. Signal variations are easily related to main effects or interaction terms, while relevant biochemical information can be derived from the models. - Highlights: • A new method is proposed for the analysis of Omics data generated using design of

Demixed principal component analysis of neural population data.

Science.gov (United States)

Kobak, Dmitry; Brendel, Wieland; Constantinidis, Christos; Feierstein, Claudia E; Kepecs, Adam; Mainen, Zachary F; Qi, Xue-Lian; Romo, Ranulfo; Uchida, Naoshige; Machens, Christian K

2016-04-12

Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure.

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.

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.

Applications of the TVO piping and component analysis and monitoring system (PAMS)

Energy Technology Data Exchange (ETDEWEB)

Smeekes, P. (Teollisuuden Voima Oy, Olkiluoto (Finland)); Kuuluvainen, O. (Rostedt Oy, Luvia (Finland)); Torkkeli, E. (FEMdata Oy, Haukilahti (Finland))

2010-05-15

To make fitness, safety and lifetime related assessments for piping and components, the amount of data to be managed is getting larger and larger. At the same time it is essential that the data is reliable, up-to-date, well traceable and easy and fast to obtain. At present the main focus of PAMS is still on piping, but in the future the component related databases and applications will be more and more developed. This paper presents a piping and component database system, consisting of separate geometrical, material, loading, result and document databases as well as current and future applications of the system. By means of a user configurable interface program the user can generate indata files, run application programs and define what data to write back into the result database. The data in the result database can subsequently be used in new input files to perform postprocessing on previous results, for instance fatigue analysis. crack growth analysis or RI-ISI. The system is intended to facilitate the analyses of piping and components and generate well-documented appendices comprising significant parts of the input and output and the associated source references. (orig.)

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

Science.gov (United States)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

Real time analysis under EDS

International Nuclear Information System (INIS)

Schneberk, D.

1985-07-01

This paper describes the analysis component of the Enrichment Diagnostic System (EDS) developed for the Atomic Vapor Laser Isotope Separation Program (AVLIS) at Lawrence Livermore National Laboratory (LLNL). Four different types of analysis are performed on data acquired through EDS: (1) absorption spectroscopy on laser-generated spectral lines, (2) mass spectrometer analysis, (3) general purpose waveform analysis, and (4) separation performance calculations. The information produced from this data includes: measures of particle density and velocity, partial pressures of residual gases, and overall measures of isotope enrichment. The analysis component supports a variety of real-time modeling tasks, a means for broadcasting data to other nodes, and a great degree of flexibility for tailoring computations to the exact needs of the process. A particular data base structure and program flow is common to all types of analysis. Key elements of the analysis component are: (1) a fast access data base which can configure all types of analysis, (2) a selected set of analysis routines, (3) a general purpose data manipulation and graphics package for the results of real time analysis. Each of these components are described with an emphasis upon how each contributes to overall system capability. 3 figs

Nonlinear principal component analysis and its applications

CERN Document Server

Mori, Yuichi; Makino, Naomichi

2016-01-01

This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed...

Partially Adaptive STAP Algorithm Approaches to functional MRI

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Huang, Lejian; Thompson, Elizabeth A.; Schmithorst, Vincent; Holland, Scott K.; Talavage, Thomas M.

2010-01-01

In this work, the architectures of three partially adaptive STAP algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in construction of brain activation maps in fMRI. Computer simulations incorporating actual MRI noise and human data analysis indicate that element space partially adaptive STAP can attain close to the performance of fully adaptive STAP while significantly decreasing processing time and maximum memory requirements, and thus demonstrates potential in fMRI analysis. PMID:19272913

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

Science.gov (United States)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Robust estimation for partially linear models with large-dimensional covariates.

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Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

A review of the reliability analysis of LPRS including the components repairs

International Nuclear Information System (INIS)

Oliveira, L.F.S. de; Fleming, P.V.; Frutuoso e Melo, P.F.F.; Tayt-Sohn, L.C.

1983-01-01

The reliability analysis of low pressure recirculation system in its long-term recicurlation phase before 24hs is presented. The possibility of repairing the components out of the containment is included. A general revision of analysis of the short-term recirculation phase is done. (author) [pt

Assessing and grouping chemicals applying partial ordering Alkyl anilines as an illustrative example.

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Carlsen, Lars; Bruggemann, Rainer

2018-06-03

In chemistry there is a long tradition in classification. Usually methods are adopted from the wide field of cluster analysis. Here, based on the example of 21 alkyl anilines we show that also concepts taken out from the mathematical discipline of partially ordered sets may also be applied. The chemical compounds are described by a multi-indicator system. For the present study four indicators, mainly taken from the field of environmental chemistry were applied and a Hasse diagram was constructed. A Hasse diagram is an acyclic, transitively reduced, triangle free graph that may have several components. The crucial question is, whether or not the Hasse diagram can be interpreted from a structural chemical point of view. This is indeed the case, but it must be clearly stated that a guarantee for meaningful results in general cannot be given. For that further theoretical work is needed. Two cluster analysis methods are applied (K-means and a hierarchical cluster method). In both cases the partitioning of the set of 21 compounds by the component structure of the Hasse diagram appears to be better interpretable. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Partial synchronization and spontaneous spatial ordering in coupled chaotic systems

International Nuclear Information System (INIS)

Ying Zhang; Gang Hu; Cerdeira, Hilda A.; Shigang Chen; Braun, Thomas; Yugui Yao

2000-11-01

A model of many symmetrically and locally coupled chaotic oscillators is studied. Partial chaotic synchronizations associated with spontaneous spatial ordering are demonstrated. Very rich patterns of the system are revealed, based on partial synchronization analysis. The stabilities of different partially synchronous spatiotemporal structures and some novel dynamical behaviors of these states are discussed both numerically and analytically. (author)

Generalized modeling of multi-component vaporization/condensation phenomena for multi-phase-flow analysis

International Nuclear Information System (INIS)

Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.

2003-01-01

A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)

Reliability analysis of component-level redundant topologies for solid-state fault current limiter

Science.gov (United States)

Farhadi, Masoud; Abapour, Mehdi; Mohammadi-Ivatloo, Behnam

2018-04-01

Experience shows that semiconductor switches in power electronics systems are the most vulnerable components. One of the most common ways to solve this reliability challenge is component-level redundant design. There are four possible configurations for the redundant design in component level. This article presents a comparative reliability analysis between different component-level redundant designs for solid-state fault current limiter. The aim of the proposed analysis is to determine the more reliable component-level redundant configuration. The mean time to failure (MTTF) is used as the reliability parameter. Considering both fault types (open circuit and short circuit), the MTTFs of different configurations are calculated. It is demonstrated that more reliable configuration depends on the junction temperature of the semiconductor switches in the steady state. That junction temperature is a function of (i) ambient temperature, (ii) power loss of the semiconductor switch and (iii) thermal resistance of heat sink. Also, results' sensitivity to each parameter is investigated. The results show that in different conditions, various configurations have higher reliability. The experimental results are presented to clarify the theory and feasibility of the proposed approaches. At last, levelised costs of different configurations are analysed for a fair comparison.

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).

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

Science.gov (United States)

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Partial resistance of carrot to Alternaria dauci correlates with in vitro cultured carrot cell resistance to fungal exudates.

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Mickaël Lecomte

Full Text Available Although different mechanisms have been proposed in the recent years, plant pathogen partial resistance is still poorly understood. Components of the chemical warfare, including the production of plant defense compounds and plant resistance to pathogen-produced toxins, are likely to play a role. Toxins are indeed recognized as important determinants of pathogenicity in necrotrophic fungi. Partial resistance based on quantitative resistance loci and linked to a pathogen-produced toxin has never been fully described. We tested this hypothesis using the Alternaria dauci-carrot pathosystem. Alternaria dauci, causing carrot leaf blight, is a necrotrophic fungus known to produce zinniol, a compound described as a non-host selective toxin. Embryogenic cellular cultures from carrot genotypes varying in resistance against A. dauci were confronted with zinniol at different concentrations or to fungal exudates (raw, organic or aqueous extracts. The plant response was analyzed through the measurement of cytoplasmic esterase activity, as a marker of cell viability, and the differentiation of somatic embryos in cellular cultures. A differential response to toxicity was demonstrated between susceptible and partially resistant genotypes, with a good correlation noted between the resistance to the fungus at the whole plant level and resistance at the cellular level to fungal exudates from raw and organic extracts. No toxic reaction of embryogenic cultures was observed after treatment with the aqueous extract or zinniol used at physiological concentration. Moreover, we did not detect zinniol in toxic fungal extracts by UHPLC analysis. These results suggest that strong phytotoxic compounds are present in the organic extract and remain to be characterized. Our results clearly show that carrot tolerance to A. dauci toxins is one component of its partial resistance.

Disturbance Elimination for Partial Discharge Detection in the Spacer of Gas-Insulated Switchgears

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Guoming Wang

2017-11-01

Full Text Available With the increasing demand for precise condition monitoring and diagnosis of gas-insulated switchgears (GISs, it has become a challenge to improve the detection sensitivity of partial discharge (PD induced in the GIS spacer. This paper deals with the elimination of the capacitive component from the phase-resolved partial discharge (PRPD signal generated in GIS spacers based on discrete wavelet transform (WT. Three types of typical insulation defects were simulated using PD cells. The single PD pulses were detected and were further used to determine the optimal mother wavelet. As a result, the bior6.8 was selected to decompose the PD signal into 8 levels and the signal energy at each level was calculated. The decomposed components related with capacitive disturbance were discarded, whereas those associated with PD were de-noised by a threshold and a thresholding function. Finally, the PRPD signals were reconstructed using the de-noised components.

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

Science.gov (United States)

Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

2010-09-01

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

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.

Solving of some Problems with On-Line Mode Measurement of Partial Discharges

Directory of Open Access Journals (Sweden)

Karel Zalis

2004-01-01

Full Text Available This paper deals with the problems discussing the transition from off-line diagnostic methods to on-line ones. Based on the experience with commercial partial discharge measuring equipment a new digital system for the evaluation of partial discharge measurement including software and hardware facilities has been developed at the Czech Technical University in Prague. Two expert systems work in this complex evaluating system: a rule-based expert system performing an amplitude analysis of partial discharge impulses for determining the damage of the insulation system, and a neural network which is used for a phase analysis of partial discharge impulses to determine the kind of partial discharge activity. Problem of the elimination of disturbances is also discussed.

Machine learning of frustrated classical spin models. I. Principal component analysis

Science.gov (United States)

Wang, Ce; Zhai, Hui

2017-10-01

This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.

Reliability analysis and component functional allocations for the ESF multi-loop controller design

International Nuclear Information System (INIS)

Hur, Seop; Kim, D.H.; Choi, J.K.; Park, J.C.; Seong, S.H.; Lee, D.Y.

2006-01-01

This paper deals with the reliability analysis and component functional allocations to ensure the enhanced system reliability and availability. In the Engineered Safety Features, functionally dependent components are controlled by a multi-loop controller. The system reliability of the Engineered Safety Features-Component Control System, especially, the multi-loop controller which is changed comparing to the conventional controllers is an important factor for the Probability Safety Assessment in the nuclear field. To evaluate the multi-loop controller's failure rate of the k-out-of-m redundant system, the binomial process is used. In addition, the component functional allocation is performed to tolerate a single multi-loop controller failure without the loss of vital operation within the constraints of the piping and component configuration, and ensure that mechanically redundant components remain functional. (author)

Robustness analysis of bogie suspension components Pareto optimised values

Science.gov (United States)

Mousavi Bideleh, Seyed Milad

2017-08-01

Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway operations from different perspectives. Uncertainties in the design parameters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto optimised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1.

Analysis of Partial Discharge Activity for Evaluation of the State of High Power Electric Generators Stator Windings

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Dumitrescu Sorin

2016-08-01

Full Text Available The paper shows the importance of trending of partial discharge activity in assessing the insulation condition. It is presented the principle of the measurement method and the quantities that characterize partial discharges and also the criteria utilized for the assessement of the insulation condition of the hydrogenerators. Results of the measurements made on several hydrogenerators are presented, like the variation with time of the two main quantities that characterize the partial discharges, maximum magnitude, Qm and the normalized quantity, NQN over a period of about 10 years. Further, a classification of the insulation condition by 3 main and 2 intermediary categories and the definition of these categories are given. The criteria used for the assessment of the insulation condition are presented in the form of a table: quantitative criteria by the ± NQN and ± Qm values and qualitative criteria for the analysis of the 2D and 3D diagrams. At the end of each set of measurements, an analyze of the insulation condition annual evaluation is made, also a verdict is put, and of course, the recommendations made relating to the maintenance and the decisions that have been taken. The paper ends with several considerations on the method of on-line partial discharges and especially, on the conditions for valid trending activity in time.

Chiral and continuum extrapolation of partially quenched lattice results

Energy Technology Data Exchange (ETDEWEB)

C.R. Allton; W. Armour; D.B. Leinweber; A.W. Thomas; R.D. Young

2005-04-01

The vector meson mass is extracted from a large sample of partially quenched, two-flavor lattice QCD simulations. For the first time, discretization, finite-volume and partial quenching artifacts are treated in a unified chiral effective field theory analysis of the lattice simulation results.

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

Science.gov (United States)

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

Science.gov (United States)

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Task-related component analysis for functional neuroimaging and application to near-infrared spectroscopy data.

Science.gov (United States)

Tanaka, Hirokazu; Katura, Takusige; Sato, Hiroki

2013-01-01

Reproducibility of experimental results lies at the heart of scientific disciplines. Here we propose a signal processing method that extracts task-related components by maximizing the reproducibility during task periods from neuroimaging data. Unlike hypothesis-driven methods such as general linear models, no specific time courses are presumed, and unlike data-driven approaches such as independent component analysis, no arbitrary interpretation of components is needed. Task-related components are constructed by a linear, weighted sum of multiple time courses, and its weights are optimized so as to maximize inter-block correlations (CorrMax) or covariances (CovMax). Our analysis method is referred to as task-related component analysis (TRCA). The covariance maximization is formulated as a Rayleigh-Ritz eigenvalue problem, and corresponding eigenvectors give candidates of task-related components. In addition, a systematic statistical test based on eigenvalues is proposed, so task-related and -unrelated components are classified objectively and automatically. The proposed test of statistical significance is found to be independent of the degree of autocorrelation in data if the task duration is sufficiently longer than the temporal scale of autocorrelation, so TRCA can be applied to data with autocorrelation without any modification. We demonstrate that simple extensions of TRCA can provide most distinctive signals for two tasks and can integrate multiple modalities of information to remove task-unrelated artifacts. TRCA was successfully applied to synthetic data as well as near-infrared spectroscopy (NIRS) data of finger tapping. There were two statistically significant task-related components; one was a hemodynamic response, and another was a piece-wise linear time course. In summary, we conclude that TRCA has a wide range of applications in multi-channel biophysical and behavioral measurements. Copyright © 2012 Elsevier Inc. All rights reserved.

Integrative sparse principal component analysis of gene expression data.

Science.gov (United States)

Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Competition analysis on the operating system market using principal component analysis

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Brătucu, G.

2011-01-01

Full Text Available Operating system market has evolved greatly. The largest software producer in the world, Microsoft, dominates the operating systems segment. With three operating systems: Windows XP, Windows Vista and Windows 7 the company held a market share of 87.54% in January 2011. Over time, open source operating systems have begun to penetrate the market very strongly affecting other manufacturers. Companies such as Apple Inc. and Google Inc. penetrated the operating system market. This paper aims to compare the best-selling operating systems on the market in terms of defining characteristics. To this purpose the principal components analysis method was used.

Analysis of failed nuclear plant components

International Nuclear Information System (INIS)

Diercks, D.R.

1993-01-01

Argonne National Laboratory has conducted analyses of failed components from nuclear power-generating stations since 1974. The considerations involved in working with an analyzing radioactive components are reviewed here, and the decontamination of these components is discussed. Analyses of four failed components from nuclear plants are then described to illustrate the kinds of failures seen in service. The failures discussed are (1) intergranular stress-corrosion cracking of core spray injection piping in a boiling water reactor, (2) failure of canopy seal welds in adapter tube assemblies in the control rod drive head of a pressurized water reactor, (3) thermal fatigue of a recirculation pump shaft in a boiling water reactor, and (4) failure of pump seal wear rings by nickel leaching in a boiling water reactor

Analysis of failed nuclear plant components

International Nuclear Information System (INIS)

Diercks, D.R.

1992-07-01

Argonne National Laboratory has conducted analyses of failed components from nuclear power generating stations since 1974. The considerations involved in working with and analyzing radioactive components are reviewed here, and the decontamination of these components is discussed. Analyses of four failed components from nuclear plants are then described to illustrate the kinds of failures seen in service. The failures discussed are (a) intergranular stress corrosion cracking of core spray injection piping in a boiling water reactor, (b) failure of canopy seal welds in adapter tube assemblies in the control rod drive head of a pressure water reactor, (c) thermal fatigue of a recirculation pump shaft in a boiling water reactor, and (d) failure of pump seal wear rings by nickel leaching in a boiling water reactor

Growth modeling of Cryptomeria japonica by partial trunk analysis

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Vinícius Morais Coutinho

2017-06-01

Full Text Available This study aimed to evaluate the growth pattern of Cryptomeria japonica increment (L. F. D. Don. and to describe the probability distribution in stands stablished at the municipality of Rio Negro, Paraná State. Twenty trees were sampled in a 34 years-old stand, with 3 m x 2 m spacing. Wood disks were taken from each tree at 1.3 m above the ground (DBH to perform partial stem analysis. Diameter growth series without bark were used to generate the average cumulative growth curves for DBH (cm, mean annual increment (MAI and current annual increment (CAI. From the increment data, the frequency distribution was evaluated by means of probability density functions (pdfs. The mean annual increment for DBH was 0.78 cm year-1 and the age of intersection of CAI and MAI curves was between the 7th and 8th years. It was found that near 43% of the species increments are concentrated bellow 0.5 cm. The results are useful to define appropriate management strategies for the species for sites similar to the studying regions, defining for example ages of silvicultural intervention, such as thinning.

Component fragilities - data collection, analysis and interpretation

International Nuclear Information System (INIS)

Bandyopadhyay, K.K.; Hofmayer, C.H.

1986-01-01

As part of the component fragility research program sponsored by the US Nuclear Regulatory Commission, BNL is involved in establishing seismic fragility levels for various nuclear power plant equipment with emphasis on electrical equipment, by identifying, collecting and analyzing existing test data from various sources. BNL has reviewed approximately seventy test reports to collect fragility or high level test data for switchgears, motor control centers and similar electrical cabinets, valve actuators and numerous electrical and control devices of various manufacturers and models. Through a cooperative agreement, BNL has also obtained test data from EPRI/ANCO. An analysis of the collected data reveals that fragility levels can best be described by a group of curves corresponding to various failure modes. The lower bound curve indicates the initiation of malfunctioning or structural damage, whereas the upper bound curve corresponds to overall failure of the equipment based on known failure modes occurring separately or interactively. For some components, the upper and lower bound fragility levels are observed to vary appreciably depending upon the manufacturers and models. An extensive amount of additional fragility or high level test data exists. If completely collected and properly analyzed, the entire data bank is expected to greatly reduce the need for additional testing to establish fragility levels for most equipment

Component fragilities. Data collection, analysis and interpretation

International Nuclear Information System (INIS)

Bandyopadhyay, K.K.; Hofmayer, C.H.

1985-01-01

As part of the component fragility research program sponsored by the US NRC, BNL is involved in establishing seismic fragility levels for various nuclear power plant equipment with emphasis on electrical equipment. To date, BNL has reviewed approximately seventy test reports to collect fragility or high level test data for switchgears, motor control centers and similar electrical cabinets, valve actuators and numerous electrical and control devices, e.g., switches, transmitters, potentiometers, indicators, relays, etc., of various manufacturers and models. BNL has also obtained test data from EPRI/ANCO. Analysis of the collected data reveals that fragility levels can best be described by a group of curves corresponding to various failure modes. The lower bound curve indicates the initiation of malfunctioning or structural damage, whereas the upper bound curve corresponds to overall failure of the equipment based on known failure modes occurring separately or interactively. For some components, the upper and lower bound fragility levels are observed to vary appreciably depending upon the manufacturers and models. For some devices, testing even at the shake table vibration limit does not exhibit any failure. Failure of a relay is observed to be a frequent cause of failure of an electrical panel or a system. An extensive amount of additional fregility or high level test data exists

Components of Program for Analysis of Spectra and Their Testing

Directory of Open Access Journals (Sweden)

Ivan Taufer

2013-11-01

Full Text Available The spectral analysis of aqueous solutions of multi-component mixtures is used for identification and distinguishing of individual componentsin the mixture and subsequent determination of protonation constants and absorptivities of differently protonated particles in the solution in steadystate (Meloun and Havel 1985, (Leggett 1985. Apart from that also determined are the distribution diagrams, i.e. concentration proportions ofthe individual components at different pH values. The spectra are measured with various concentrations of the basic components (one or severalpolyvalent weak acids or bases and various pH values within the chosen range of wavelengths. The obtained absorbance response area has to beanalyzed by non-linear regression using specialized algorithms. These algorithms have to meet certain requirements concerning the possibility ofcalculations and the level of outputs. A typical example is the SQUAD(84 program, which was gradually modified and extended, see, e.g., (Melounet al. 1986, (Meloun et al. 2012.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

Science.gov (United States)

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

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

Analysis of boundary layer flow over a porous nonlinearly stretching sheet with partial slip at

Directory of Open Access Journals (Sweden)

Swati Mukhopadhyay

2013-12-01

Full Text Available The boundary layer flow of a viscous incompressible fluid toward a porous nonlinearly stretching sheet is considered in this analysis. Velocity slip is considered instead of no-slip condition at the boundary. Similarity transformations are used to convert the partial differential equation corresponding to the momentum equation into nonlinear ordinary differential equation. Numerical solution of this equation is obtained by shooting method. It is found that the horizontal velocity decreases with increasing slip parameter.

Fluorescence excitation-emission matrix (EEM) spectroscopy for rapid identification and quality evaluation of cell culture media components.

Science.gov (United States)

Li, Boyan; Ryan, Paul W; Shanahan, Michael; Leister, Kirk J; Ryder, Alan G

2011-11-01

The application of fluorescence excitation-emission matrix (EEM) spectroscopy to the quantitative analysis of complex, aqueous solutions of cell culture media components was investigated. These components, yeastolate, phytone, recombinant human insulin, eRDF basal medium, and four different chemically defined (CD) media, are used for the formulation of basal and feed media employed in the production of recombinant proteins using a Chinese Hamster Ovary (CHO) cell based process. The comprehensive analysis (either identification or quality assessment) of these materials using chromatographic methods is time consuming and expensive and is not suitable for high-throughput quality control. The use of EEM in conjunction with multiway chemometric methods provided a rapid, nondestructive analytical method suitable for the screening of large numbers of samples. Here we used multiway robust principal component analysis (MROBPCA) in conjunction with n-way partial least squares discriminant analysis (NPLS-DA) to develop a robust routine for both the identification and quality evaluation of these important cell culture materials. These methods are applicable to a wide range of complex mixtures because they do not rely on any predetermined compositional or property information, thus making them potentially very useful for sample handling, tracking, and quality assessment in biopharmaceutical industries.

An Analysis of Testing Requirements for Fluoride Salt Cooled High Temperature Reactor Components

Energy Technology Data Exchange (ETDEWEB)

Holcomb, David Eugene [ORNL; Cetiner, Sacit M [ORNL; Flanagan, George F [ORNL; Peretz, Fred J [ORNL; Yoder Jr, Graydon L [ORNL

2009-11-01

This report provides guidance on the component testing necessary during the next phase of fluoride salt-cooled high temperature reactor (FHR) development. In particular, the report identifies and describes the reactor component performance and reliability requirements, provides an overview of what information is necessary to provide assurance that components will adequately achieve the requirements, and then provides guidance on how the required performance information can efficiently be obtained. The report includes a system description of a representative test scale FHR reactor. The reactor parameters presented in this report should only be considered as placeholder values until an FHR test scale reactor design is completed. The report focus is bounded at the interface between and the reactor primary coolant salt and the fuel and the gas supply and return to the Brayton cycle power conversion system. The analysis is limited to component level testing and does not address system level testing issues. Further, the report is oriented as a bottom-up testing requirements analysis as opposed to a having a top-down facility description focus.

Determination of amplitudes in neutral pion photoproduction and comparison with partial waves analysis in the energy range of 1.3 to 2.1 GeV

International Nuclear Information System (INIS)

Forozani, G.

2004-01-01

The magnitude of four independent amplitudes are obtained pion photoproduction in the energy range of 1300 to 2100 MeV incident photon. Different cross section and three polarization parameters are required for such amplitudes reconstruction at different pion scattering angles. Results of the direct amplitudes reconstruction have been compared with the solution of partial wave analysis SM95 and SM00K at all energies. This analysis indicates that we have a fair agreement between the present work and the results of partial wave analysis at many angles

Determination of amplitudes in neutral pion photoproduction and comparison with partial waves analysis in the energy range of 1.3 to 2.1 GeV

International Nuclear Information System (INIS)

Forozani, G.

2004-01-01

The magnitude of four independent amplitudes are obtained in neutral pion photoproduction in the energy range of 1300 to 2100 MeV incident photon. Differential gross section and three polarization parameters are required for such amplitudes reconstruction at different pion scattering angles. Results of the direct amplitudes reconstruction have been compared with the solution of partial wave analysis SM95 and SM00K at all energies. This analysis indicates that we have a fair agreement between the present work and the results of partial wave analysis at meny angles (Author)

Integrating Data Transformation in Principal Components Analysis

KAUST Repository

Maadooliat, Mehdi

2015-01-02

Principal component analysis (PCA) is a popular dimension reduction method to reduce the complexity and obtain the informative aspects of high-dimensional datasets. When the data distribution is skewed, data transformation is commonly used prior to applying PCA. Such transformation is usually obtained from previous studies, prior knowledge, or trial-and-error. In this work, we develop a model-based method that integrates data transformation in PCA and finds an appropriate data transformation using the maximum profile likelihood. Extensions of the method to handle functional data and missing values are also developed. Several numerical algorithms are provided for efficient computation. The proposed method is illustrated using simulated and real-world data examples.

Analysis of failed nuclear plant components

Science.gov (United States)

Diercks, D. R.

1993-12-01

Argonne National Laboratory has conducted analyses of failed components from nuclear power- gener-ating stations since 1974. The considerations involved in working with and analyzing radioactive compo-nents are reviewed here, and the decontamination of these components is discussed. Analyses of four failed components from nuclear plants are then described to illustrate the kinds of failures seen in serv-ice. The failures discussed are (1) intergranular stress- corrosion cracking of core spray injection piping in a boiling water reactor, (2) failure of canopy seal welds in adapter tube assemblies in the control rod drive head of a pressurized water reactor, (3) thermal fatigue of a recirculation pump shaft in a boiling water reactor, and (4) failure of pump seal wear rings by nickel leaching in a boiling water reactor.

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

Impact of Renal Hilar Control on Outcomes of Robotic Partial Nephrectomy: Systematic Review and Cumulative Meta-analysis.

Science.gov (United States)

Cacciamani, Giovanni E; Medina, Luis G; Gill, Tania S; Mendelsohn, Alec; Husain, Fatima; Bhardwaj, Lokesh; Artibani, Walter; Sotelo, Renè; Gill, Inderbir S

2018-02-05

During robotic partial nephrectomy (RPN), various techniques of hilar control have been described, including on-clamp, early unclamping, selective/super-selective clamping, and completely-unclamped RPN. To evaluate the impact of various hilar control techniques on perioperative, functional, and oncological outcomes of RPN for tumors. We conducted a systematic literature review and meta-analysis of all comparative studies on various hilar control techniques during RPN using PubMed, Scopus, and Web of Science according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement, and Methods and Guide for Effectiveness and Comparative Effectiveness Review of the Agency for Healthcare Research and Quality. Cumulative meta-analysis of comparative studies was conducted using Review Manager 5.3. Of 987 RPN publications in the literature, 19 qualified for this analysis. Comparison of off-clamp versus on-clamp RPN (n=9), selective clamping versus on-clamp RPN (n=3), super selective clamping versus on-clamp RPN (n=5), and early unclamped versus on-clamp (n=3) were reported. Patients undergoing RPN using off-clamp, selective/super selective, or early unclamp techniques had higher estimated blood loss compared with on-clamp RPN (weight mean difference [WMD]: 47.83, p=0.000, WMD: 41.06, p=0.02, and WMD: 37.50, p=0.47); however, this did not seem clinically relevant, since transfusion rates were similar (odds ratio [OR]: 0.98, p=0.95, OR: 0.72, p=0.7, and OR: 1.36, p=0.33, respectively). All groups appeared similar with regards to hospital stay, transfusions, overall and major complications, and positive cancer margin rates. Short- and long-term renal functional outcomes appeared superior in the off-clamp and super selective clamp groups compared with the on-clamp RPN cohort. Off-clamp, selective/super selective clamp, and early unclamp hilar control techniques are safe and feasible approaches for RPN surgery, with similar perioperative and oncological

Plasma-assisted partial oxidation of methane at low temperatures: numerical analysis of gas-phase chemical mechanism

Energy Technology Data Exchange (ETDEWEB)

Goujard, Valentin; Nozaki, Tomohiro; Yuzawa, Shuhei; Okazaki, Ken [Department of Mechanical and Control Engineering, Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro, 1528552, Tokyo (Japan); Agiral, Anil, E-mail: tnozaki@mech.titech.ac.jp [Mesoscale Chemical Systems, MESA Institute for Nanotechnology, Faculty of Science and Technology, University of Twente, PO Box 217, 7500 AE, Enschede (Netherlands)

2011-07-13

Methane partial oxidation was investigated using a plasma microreactor. The experiments were performed at 5 and 300 deg. C. Microreactor configuration allows an efficient evacuation of the heat generated by methane partial oxidation and dielectric barrier discharges, allowing at the same time a better temperature control. At 5 deg. C, liquid condensation of low vapour pressure compounds, such as formaldehyde and methanol, occurs. {sup 1}H-NMR analysis allowed us to demonstrate significant CH{sub 3}OOH formation during plasma-assisted partial oxidation of methane. Conversion and product selectivity were discussed for both temperatures. In the second part of this work, a numerical simulation was performed and a gas-phase chemical mechanism was proposed and discussed. From the comparison between the experimental results and the simulation it was found that CH{sub 3}OO{center_dot} formation has a determinant role in oxygenated compound production, since its fast formation disfavoured radical recombination. At 5 deg. C the oxidation leads mainly towards oxygenated compound formation, and plasma dissociation was the major phenomenon responsible for CH{sub 4} conversion. At 300 deg. C, higher CH{sub 4} conversion resulted from oxidative reactions induced by {center_dot}OH radicals with a chemistry predominantly oxidative, producing CO, H{sub 2}, CO{sub 2} and H{sub 2}O.

Process parameter optimization based on principal components analysis during machining of hardened steel

Directory of Open Access Journals (Sweden)

Suryakant B. Chandgude

2015-09-01

Full Text Available The optimum selection of process parameters has played an important role for improving the surface finish, minimizing tool wear, increasing material removal rate and reducing machining time of any machining process. In this paper, optimum parameters while machining AISI D2 hardened steel using solid carbide TiAlN coated end mill has been investigated. For optimization of process parameters along with multiple quality characteristics, principal components analysis method has been adopted in this work. The confirmation experiments have revealed that to improve performance of cutting; principal components analysis method would be a useful tool.

Risk-informed importance analysis of in-service testing components for Ulchin units 3 and 4

International Nuclear Information System (INIS)

Kang, D. I.; Kim, K. Y.; Ha, J. J.

2001-01-01

In this paper, we perform risk-informed importance analysis of in-service tesing (IST) components for Ulchin Units 3 and 4. The importance analysis using PSA is performed through Level 1 internal and external, shutdown/low power operation, and Level 2 internal PSA. The sensitivity analysis is also performed. For the components not modeled in PSA logic, we develop and apply a new integrated importance analysis method. The importance analysis results for IST valves show that 167 (26.55%) of 629 IST valves are HSSCs and 462 (73.45%) are LSSCs. The importance analysis results for IST pumps show that 28 (70%) of 40 IST pumps are HSSCs and 12 (30%) are KSSCs

Advances in the Partial Oxidation of Methane to Synthesis Gas

Institute of Scientific and Technical Information of China (English)

Quanli Zhu; Xutao Zhao; Youquan Deng

2004-01-01

The conversion and utilization of natural gas is of significant meaning to the national economy,even to the everyday life of people. However, it has not become a popular industrial process as expected due to the technical obstacles. In the past decades, much investigation into the conversion of methane,predominant component of natural gas, has been carried out. Among the possible routes of methane conversion, the partial oxidation of methane to synthesis gas is considered as an effective and economically feasible one. In this article, a brief review of recent studies on the mechanism of the partial oxidation of methane to synthesis gas together with catalyst development is wherein presented.

Fluoride in the Serra Geral Aquifer System: Source Evaluation Using Stable Isotopes and Principal Component Analysis

OpenAIRE

Nanni, Arthur Schmidt; Roisenberg, Ari; de Hollanda, Maria Helena Bezerra Maia; Marimon, Maria Paula Casagrande; Viero, Antonio Pedro; Scheibe, Luiz Fernando

2013-01-01

Groundwater with anomalous fluoride content and water mixture patterns were studied in the fractured Serra Geral Aquifer System, a basaltic to rhyolitic geological unit, using a principal component analysis interpretation of groundwater chemical data from 309 deep wells distributed in the Rio Grande do Sul State, Southern Brazil. A four-component model that explains 81% of the total variance in the Principal Component Analysis is suggested. Six hydrochemical groups were identified. δ18O and δ...

Cloning and sequence analysis of a partial CDS of leptospiral ligA gene in pET-32a - Escherichia coli DH5α system

Directory of Open Access Journals (Sweden)

Manju Soman

2018-04-01

Full Text Available Aim: This study aims at cloning, sequencing, and phylogenetic analysis of a partial CDS of ligA gene in pET-32a - Escherichia coli DH5α system, with the objective of identifying the conserved nature of the ligA gene in the genus Leptospira. Materials and Methods: A partial CDS (nucleotide 1873 to nucleotide 3363 of the ligA gene was amplified from genomic DNA of Leptospira interrogans serovar Canicola by polymerase chain reaction (PCR. The PCR-amplified DNA was cloned into pET-32a vector and transformed into competent E. coli DH5α bacterial cells. The partial ligA gene insert was sequenced and the nucleotide sequences obtained were aligned with the published ligA gene sequences of other Leptospira serovars, using nucleotide BLAST, NCBI. Phylogenetic analysis of the gene sequence was done by maximum likelihood method using Mega 6.06 software. Results: The PCR could amplify the 1491 nucleotide sequence spanning from nucleotide 1873 to nucleotide 3363 of the ligA gene and the partial ligA gene could be successfully cloned in E. coli DH5α cells. The nucleotide sequence when analyzed for homology with the reported gene sequences of other Leptospira serovars was found to have 100% homology to the 1910 bp to 3320 bp sequence of ligA gene of L. interrogans strain Kito serogroup Canicola. The predicted protein consisted of 470 aminoacids. Phylogenetic analysis revealed that the ligA gene was conserved in L. interrogans species. Conclusion: The partial ligA gene could be successfully cloned and sequenced from E. coli DH5α cells. The sequence showed 100% homology to the published ligA gene sequences. The phylogenetic analysis revealed the conserved nature of the ligA gene. Further studies on the expression and immunogenicity of the partial LigA protein need to be carried out to determine its competence as a subunit vaccine candidate.

Computer-aided stress analysis system for nuclear plant primary components

International Nuclear Information System (INIS)

Murai, Tsutomu; Tokumaru, Yoshio; Yamazaki, Junko.

1980-06-01

Generally it needs a vast quantity of calculation to make the stress analysis reports of nuclear plant primary components. In Japan, especially, stress analysis reports are under obligation to make for each plant. In Mitsubishi Heavy Industries, Ltd., We have been making great efforts to rationalize the process of analysis for about these ten years. As the result of rationalization up to now, a computer-aided stress analysis system using graphic display, graphic tablet, data file, etc. was accomplished and it needs us only the least hand work. In addition we developed a fracture safety analysis system. And we are going to develop the input generator system for 3-dimensional FEM analysis by graphics terminals in the near future. We expect that when the above-mentioned input generator system is accomplished, it will be possible for us to solve instantly any case of problem. (author)

Harmonic Stability Analysis of Offshore Wind Farm with Component Connection Method

DEFF Research Database (Denmark)

Hou, Peng; Ebrahimzadeh, Esmaeil; Wang, Xiongfei

2017-01-01

In this paper, an eigenvalue-based harmonic stability analysis method for offshore wind farm is proposed. Considering the internal cable connection layout, a component connection method (CCM) is adopted to divide the system into individual blocks as current controller of converters, LCL filters...

Nonlinear seismic analysis of a reactor structure with impact between core components

International Nuclear Information System (INIS)

Hill, R.G.

1975-01-01

The seismic analysis of the FFTF-PIOTA (Fast Flux Test Facility-Postirradiation Open Test Assembly), subjected to a horizontal DBE (Design Base Earthquake) is presented. The PIOTA is the first in a set of open test assemblies to be designed for the FFTF. Employing the direct method of transient analysis, the governing differential equations describing the motion of the system are set up directly and are implicitly integrated numerically in time. A simple lumped-mass beam model of the FFTF which includes small clearances between core components is used as a ''driver'' for a fine mesh model of the PIOTA. The nonlinear forces due to the impact of the core components and their effect on the PIOTA are computed. 6 references

F4E studies for the electromagnetic analysis of ITER components

Energy Technology Data Exchange (ETDEWEB)

Testoni, P., E-mail: pietro.testoni@f4e.europa.eu [Fusion for Energy, Torres Diagonal Litoral B3, c/ Josep Plá n.2, Barcelona (Spain); Cau, F.; Portone, A. [Fusion for Energy, Torres Diagonal Litoral B3, c/ Josep Plá n.2, Barcelona (Spain); Albanese, R. [Associazione EURATOM/ENEA/CREATE, DIETI, Università Federico II di Napoli, Napoli (Italy); Juirao, J. [Numerical Analysis TEChnologies S.L. (NATEC), c/ Marqués de San Esteban, 52 Entlo D Gijón (Spain)

2014-10-15

Highlights: • Several ITER components have been analyzed from the electromagnetic point of view. • Categorization of DINA load cases is described. • VDEs, MDs and MFD have been studied. • Integral values of forces and moments components versus time have been computed for all the ITER components under study. - Abstract: Fusion for Energy (F4E) is involved in a relevant number of activities in the area of electromagnetic analysis in support of ITER general design and EU in-kind procurement. In particular several ITER components (vacuum vessel, blanket shield modules and first wall panels, test blanket modules, ICRH antenna) are being analyzed from the electromagnetic point of view. In this paper we give an updated description of our main activities, highlighting the main assumptions, objectives, results and conclusions. The plasma instabilities we consider, typically disruptions and VDEs, can be both toroidally symmetric and asymmetric. This implies that, depending on the specific component and loading conditions, FE models we use span from a sector of 10 up to 360° of the ITER machine. The techniques for simulating the electromagnetic phenomena involved in a disruption and the postprocessing of the results to obtain the loads acting on the structures are described. Finally we summarize the typical loads applied to different components and give a critical view of the results.

Experimental and simulation analysis of hydrogen production by partial oxidation of methanol

Energy Technology Data Exchange (ETDEWEB)

Sikander, U. [National Univ. of Science and Technology, Islamabad (Pakistan)

2014-10-15

Partial oxidation of methanol is the only self-sustaining process for onboard production of hydrogen. For this a fixed bed catalytic reactor is designed, based on heterogeneous catalytic reaction. To develop an optimized process, simulation is carried out using ASPEN HYSYS v 7.1. Reaction kinetics is developed on the basis of Langmuir Hinshel wood model. 45:55:5 of CuO: ZnO: Al/sub 2/O/sub 3/ is used as a catalyst. Simulation results are studied in detail to understand the phenomenon of partial oxidation of methanol inside the reactor. An experimental rig is developed for hydrogen production through partial oxidation of methanol. Results obtained from process simulation and experimental work; are compared with each other. (author)

Quality analysis of commercial samples of Ziziphi spinosae semen (suanzaoren by means of chromatographic fingerprinting assisted by principal component analysis

Directory of Open Access Journals (Sweden)

Shuai Sun

2014-06-01

Full Text Available Due to the scarcity of resources of Ziziphi spinosae semen (ZSS, many inferior goods and even adulterants are generally found in medicine markets. To strengthen the quality control, HPLC fingerprint common pattern established in this paper showed three main bioactive compounds in one chromatogram simultaneously. Principal component analysis based on DAD signals could discriminate adulterants and inferiorities. Principal component analysis indicated that all samples could be mainly regrouped into two main clusters according to the first principal component (PC1, redefined as Vicenin II and the second principal component (PC2, redefined as zizyphusine. PC1 and PC2 could explain 91.42% of the variance. Content of zizyphusine fluctuated more greatly than that of spinosin, and this result was also confirmed by the HPTLC result. Samples with low content of jujubosides and two common adulterants could not be used equivalently with authenticated ones in clinic, while one reference standard extract could substitute the crude drug in pharmaceutical production. Giving special consideration to the well-known bioactive saponins but with low response by end absorption, a fast and cheap HPTLC method for quality control of ZSS was developed and the result obtained was commensurate well with that of HPLC analysis. Samples having similar fingerprints to HPTLC common pattern targeting at saponins could be regarded as authenticated ones. This work provided a faster and cheaper way for quality control of ZSS and laid foundation for establishing a more effective quality control method for ZSS. Keywords: Adulterant, Common pattern, Principal component analysis, Quality control, Ziziphi spinosae semen

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

Recurrent Partial Words

Directory of Open Access Journals (Sweden)

Francine Blanchet-Sadri

2011-08-01

Full Text Available Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words. Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.

Influence of Barley Sourdough and Vacuum Cooling on Shelf Life Quality of Partially Baked Bread

Science.gov (United States)

2017-01-01

Summary Driven by the bakery industry urge to satisfy consumer demand for fresh, diverse and high quality bakery products, we investigated the influence of barley sourdough and vacuum cooling on shelf life quality of partially baked bread stored in modified atmosphere packaging at ambient conditions. Barley sourdough was fermented with Lactobacillus reuteri (DSM 20016, F275). Partially baked bread with sourdough was microbiologically acceptable during 30 days of storage, while bread without sourdough had detectable mould on the 30th day. Stored bread samples were rebaked after 1, 8, 15, 22 and 30 days to determine moisture content, physical and sensorial properties. Moisture loss (5%) was detected on the 15th day, after which it remained stable until the end of investigated storage period. Nevertheless, textural quality of stored bread continuously declined due to crumb firming. Bread flavour did not change during mould-free storage time. The principal component analysis identified major differences in the flavour of sour and control bread, also in crumb firmness and moisture content of samples. This study indicates the positive role of barley sourdough fermented with L. reuteri in improving crumb texture for at least 15 days, and ensuring mould- and bacteria-free partially baked bread for 30 days. Vacuum cooling combined with sourdough improved bread shape, porosity, and reduced sour taste, crust colouring and crumbliness. Hence, it can successfully extend shelf life quality of partially baked bread in modified atmosphere packaging. PMID:29540981

Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis

NARCIS (Netherlands)

Lopes da Silva, F.H.; Vos, J.E.; Mooibroek, J.; Rotterdam, A. van

1980-01-01

The thalamo-cortical relationships of alpha rhythms have been analysed in dogs using partial coherence function analysis. The objective was to clarify how far the large intracortical coherence commonly recorded between different cortical sites could depend on a common thalamic site. It was found

Study of displacement cascades in metals by means of component analysis

International Nuclear Information System (INIS)

Hou, M.

1981-01-01

Component analysis is used to study the spatial distributions of point defects resulting from collision cascades in solids. The components are the three (orthogonal) eigenvectors of the covariance matrix of the spatial distribution. Those corresponding to the extreme eigenvalues determine the directions maximizing and minimizing the variance of the spatial distribution. The intermediate one is the direction maximizing the variance of the distribution projected on a plane perpendicular to the principal component. The standard deviations of the distribution projected on the three components give a measure of its size. This measure is only dependent on the cascade structure. Vacancy and interstitial distributions generated in metals by the computer code MARLOWE based on the binary collision approximation are analysed and compared in this picture. The simulation of hundreds of cascades generated by projectiles in the keV energy range incident on polycrystalline gold makes it possible to collect information on their average spatial anisotropy, energy density and on the casade development. The dependence of characteristics on the energy and the masses involved is discussed. (orig.)

New applications of partial residual methodology

International Nuclear Information System (INIS)

Uslu, V.R.

1999-12-01

The formulation of a problem of interest in the framework of a statistical analysis starts with collecting the data, choosing a model, making certain assumptions as described in the basic paradigm by Box (1980). This stage is is called model building. Then the estimation stage is in order by pretending as if the formulation of the problem was true to obtain estimates, to make tests and inferences. In the final stage, called diagnostic checking, checking of whether there are some disagreements between the data and the model fitted is done by using diagnostic measures and diagnostic plots. It is well known that statistical methods perform best under the condition that all assumptions related to the methods are satisfied. However it is true that having the ideal case in practice is very difficult. Diagnostics are therefore becoming important so are diagnostic plots because they provide a immediate assessment. Partial residual plots that are the main interest of the present study are playing the major role among the diagnostic plots in multiple regression analysis. In statistical literature it is admitted that partial residual plots are more useful than ordinary residual plots in detecting outliers, nonconstant variance, and especially discovering curvatures. In this study we consider the partial residual methodology in statistical methods rather than multiple regression. We have shown that for the same purpose as in the multiple regression the use of partial residual plots is possible particularly in autoregressive time series models, transfer function models, linear mixed models and ridge regression. (author)

Visualizing solvent mediated phase transformation behavior of carbamazepine polymorphs by principal component analysis

DEFF Research Database (Denmark)

Tian, Fang; Rades, Thomas; Sandler, Niklas

2008-01-01

The purpose of this research is to gain a greater insight into the hydrate formation processes of different carbamazepine (CBZ) anhydrate forms in aqueous suspension, where principal component analysis (PCA) was applied for data analysis. The capability of PCA to visualize and to reveal simplified...

Principal Component Analysis Based Measure of Structural Holes

Science.gov (United States)

Deng, Shiguo; Zhang, Wenqing; Yang, Huijie

2013-02-01

Based upon principal component analysis, a new measure called compressibility coefficient is proposed to evaluate structural holes in networks. This measure incorporates a new effect from identical patterns in networks. It is found that compressibility coefficient for Watts-Strogatz small-world networks increases monotonically with the rewiring probability and saturates to that for the corresponding shuffled networks. While compressibility coefficient for extended Barabasi-Albert scale-free networks decreases monotonically with the preferential effect and is significantly large compared with that for corresponding shuffled networks. This measure is helpful in diverse research fields to evaluate global efficiency of networks.

Nonlinear Principal Component Analysis Using Strong Tracking Filter

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive leastsquares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

Science.gov (United States)

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

Response spectrum analysis of coupled structural response to a three component seismic disturbance

International Nuclear Information System (INIS)

Boulet, J.A.M.; Carley, T.G.

1977-01-01

The work discussed herein is a comparison and evaluation of several response spectrum analysis (RSA) techniques as applied to the same structural model with seismic excitation having three spatial components. Lagrange's equations of motion for the system were written in matrix form and uncoupled with the modal matrix. Numerical integration (fourth order Runge-Kutta) of the resulting model equations produced time histories of system displacements in response to simultaneous application of three orthogonal components of ground motion, and displacement response spectra for each modal coordinate in response to each of the three ground motion components. Five different RSA techniques were used to combine the spectral displacements and the modal matrix to give approximations of maximum system displacements. These approximations were then compared with the maximum system displacements taken from the time histories. The RSA techniques used are the method of absolute sums, the square root of the sum of the squares, the double sum approach, the method of closely spaced modes, and Lin's method. The vectors of maximum system displacements as computed by the time history analysis and the five response spectrum analysis methods are presented. (Auth.)

Nonlinear analysis of LWR components: areas of investigation/benefits/recommendations

Energy Technology Data Exchange (ETDEWEB)

Brown, S. J. [ed.

1980-04-01

The purpose of this study is to identify specific topics of investigation into design procedures, design concepts, methods of analysis, testing practices, and standards which are characterized by nonlinear behavior (both geometric and material) and which are considered to offer some economic and/or technical benefits to the LWR industry (excluding piping). In this study these topics were collected, compiled, and subjectively evaluated as to their potential benefit. The topics considered to have the greatest benefit/impact potential are discussed. The topics of investigation were found to fall basically into three areas: component, code interpretation, and load/failure mechanism. The topics are arbitrarily reorganized into six areas of investigation: Fracture, Fatigue, Vibration/Dynamic/Seismic, Plasticity, Component/Computational Considerations, and Code Interpretation.

Building Block Approach' for Structural Analysis of Thermoplastic Composite Components for Automotive Applications

Science.gov (United States)

Carello, M.; Amirth, N.; Airale, A. G.; Monti, M.; Romeo, A.

2017-12-01

Advanced thermoplastic prepreg composite materials stand out with regard to their ability to allow complex designs with high specific strength and stiffness. This makes them an excellent choice for lightweight automotive components to reduce mass and increase fuel efficiency, while maintaining the functionality of traditional thermosetting prepreg (and mechanical characteristics) and with a production cycle time and recyclability suited to mass production manufacturing. Currently, the aerospace and automotive sectors struggle to carry out accurate Finite Elements (FE) component analyses and in some cases are unable to validate the obtained results. In this study, structural Finite Elements Analysis (FEA) has been done on a thermoplastic fiber reinforced component designed and manufactured through an integrated injection molding process, which consists in thermoforming the prepreg laminate and overmolding the other parts. This process is usually referred to as hybrid molding, and has the provision to reinforce the zones subjected to additional stresses with thermoformed themoplastic prepreg as required and overmolded with a shortfiber thermoplastic resin in single process. This paper aims to establish an accurate predictive model on a rational basis and an innovative methodology for the structural analysis of thermoplastic composite components by comparison with the experimental tests results.

Other components

International Nuclear Information System (INIS)

Anon.

1993-01-01

This chapter includes descriptions of electronic and mechanical components which do not merit a chapter to themselves. Other hardware requires mention because of particularly high tolerance or intolerance of exposure to radiation. A more systematic analysis of radiation responses of structures which are definable by material was given in section 3.8. The components discussed here are field effect transistors, transducers, temperature sensors, magnetic components, superconductors, mechanical sensors, and miscellaneous electronic components