Constrained principal component analysis and related techniques
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
Nuclear analysis techniques as a component of thermoluminescence dating
Energy Technology Data Exchange (ETDEWEB)
Prescott, J.R.; Hutton, J.T.; Habermehl, M.A. [Adelaide Univ., SA (Australia); Van Moort, J. [Tasmania Univ., Sandy Bay, TAS (Australia)
1996-12-31
In luminescence dating, an age is found by first measuring dose accumulated since the event being dated, then dividing by the annual dose rate. Analyses of minor and trace elements performed by nuclear techniques have long formed an essential component of dating. Results from some Australian sites are reported to illustrate the application of nuclear techniques of analysis in this context. In particular, a variety of methods for finding dose rates are compared, an example of a site where radioactive disequilibrium is significant and a brief summary is given of a problem which was not resolved by nuclear techniques. 5 refs., 2 tabs.
Nuclear analysis techniques as a component of thermoluminescence dating
Energy Technology Data Exchange (ETDEWEB)
Prescott, J R; Hutton, J T; Habermehl, M A [Adelaide Univ., SA (Australia); Van Moort, J [Tasmania Univ., Sandy Bay, TAS (Australia)
1997-12-31
In luminescence dating, an age is found by first measuring dose accumulated since the event being dated, then dividing by the annual dose rate. Analyses of minor and trace elements performed by nuclear techniques have long formed an essential component of dating. Results from some Australian sites are reported to illustrate the application of nuclear techniques of analysis in this context. In particular, a variety of methods for finding dose rates are compared, an example of a site where radioactive disequilibrium is significant and a brief summary is given of a problem which was not resolved by nuclear techniques. 5 refs., 2 tabs.
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 ...
Energy Technology Data Exchange (ETDEWEB)
Clegg, Samuel M [Los Alamos National Laboratory; Barefield, James E [Los Alamos National Laboratory; Wiens, Roger C [Los Alamos National Laboratory; Sklute, Elizabeth [MT HOLYOKE COLLEGE; Dyare, Melinda D [MT HOLYOKE COLLEGE
2008-01-01
Quantitative analysis with LIBS traditionally employs calibration curves that are complicated by the chemical matrix effects. These chemical matrix effects influence the LIBS plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, LIBS calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis (MV A) techniques are employed to analyze the LIBS spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares (PLS) analysis is used to generate a calibration model from which unknown samples can be analyzed. Principal Components Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) are employed to generate a model and predict the rock type of the samples. These MV A techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.
Directory of Open Access Journals (Sweden)
Gheorghe Gîlcă
2015-06-01
Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.
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
The application of principal component analysis to quantify technique in sports.
Federolf, P; Reid, R; Gilgien, M; Haugen, P; Smith, G
2014-06-01
Analyzing an athlete's "technique," sport scientists often focus on preselected variables that quantify important aspects of movement. In contrast, coaches and practitioners typically describe movements in terms of basic postures and movement components using subjective and qualitative features. A challenge for sport scientists is finding an appropriate quantitative methodology that incorporates the holistic perspective of human observers. Using alpine ski racing as an example, this study explores principal component analysis (PCA) as a mathematical method to decompose a complex movement pattern into its main movement components. Ski racing movements were recorded by determining the three-dimensional coordinates of 26 points on each skier which were subsequently interpreted as a 78-dimensional posture vector at each time point. PCA was then used to determine the mean posture and principal movements (PMk ) carried out by the athletes. The first four PMk contained 95.5 ± 0.5% of the variance in the posture vectors which quantified changes in body inclination, vertical or fore-aft movement of the trunk, and distance between skis. In summary, calculating PMk offered a data-driven, quantitative, and objective method of analyzing human movement that is similar to how human observers such as coaches or ski instructors would describe the movement. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
International Nuclear Information System (INIS)
Choi, Moon Kyoung; Seong, Poong Hyun; Son, Han Seong
2017-01-01
The digitalization of infrastructure makes systems vulnerable to cyber threats and hybrid attacks. According to ICS-CERT report, as time goes by, the number of vulnerabilities in ICS industries increases rapidly. Digital I and C systems have been developed and installed in nuclear power plants, and due to installation of the digital I and C systems, cyber security concerns are increasing in nuclear industry. However, there are too many critical digital assets to be inspected in digitalized NPPs. In order to reduce the inefficiency of regulation in nuclear facilities, the critical components that are directly related to an accident are elicited by using the reliability analysis techniques. Target initial events are selected, and their headings are analyzed through event tree analysis about whether the headings can be affected by cyber-attacks or not. Among the headings, the headings that can be proceeded directly to the core damage by the cyber-attack when they are fail are finally selected as the target of deriving the minimum cut-sets. We analyze the fault trees and derive the minimum set-cuts. In terms of original PSA, the value of probability for the cut-sets is important but the probability is not important in terms of cyber security of NPPs. The important factors is the number of basic events consisting of the minimal cut-sets that is proportional to vulnerability.
A comparative study of different techniques in the stress analysis of a nuclear component
International Nuclear Information System (INIS)
Dickenson, P.W.; Floyd, C.G.
1985-01-01
The inner surface stresses around the corner between the cylindrical wall and end plate of a flat ended pressure vessel have been determined using finite element, boundary element and photoelastic techniques. The results demonstrate severe deficiencies under certain conditions in the performance of the quadrilateral axisymmetric finite element which is commonly used in this type of analysis. The boundary element method is shown to provide an alternative analysis route giving more accurate results. The hybrid formulation finite element is also found to give reasonable results for the analysis of stresses in regions of rapidly varying stress. (orig.)
International Nuclear Information System (INIS)
Yu, P.
2008-01-01
More recently, advanced synchrotron radiation-based bioanalytical technique (SRFTIRM) has been applied as a novel non-invasive analysis tool to study molecular, functional group and biopolymer chemistry, nutrient make-up and structural conformation in biomaterials. This novel synchrotron technique, taking advantage of bright synchrotron light (which is million times brighter than sunlight), is capable of exploring the biomaterials at molecular and cellular levels. However, with the synchrotron RFTIRM technique, a large number of molecular spectral data are usually collected. The objective of this article was to illustrate how to use two multivariate statistical techniques: (1) agglomerative hierarchical cluster analysis (AHCA) and (2) principal component analysis (PCA) and two advanced multicomponent modeling methods: (1) Gaussian and (2) Lorentzian multi-component peak modeling for molecular spectrum analysis of bio-tissues. The studies indicated that the two multivariate analyses (AHCA, PCA) are able to create molecular spectral corrections by including not just one intensity or frequency point of a molecular spectrum, but by utilizing the entire spectral information. Gaussian and Lorentzian modeling techniques are able to quantify spectral omponent peaks of molecular structure, functional group and biopolymer. By application of these four statistical methods of the multivariate techniques and Gaussian and Lorentzian modeling, inherent molecular structures, functional group and biopolymer onformation between and among biological samples can be quantified, discriminated and classified with great efficiency.
Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li
2009-02-01
Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.
Energy Technology Data Exchange (ETDEWEB)
Sabharwall, Piyush [Idaho National Laboratory (INL), Idaho Falls, ID (United States); O' Brien, James E. [Idaho National Laboratory (INL), Idaho Falls, ID (United States); McKellar, Michael G. [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Housley, Gregory K. [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Bragg-Sitton, Shannon M. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)
2015-03-01
Hybrid energy system research has the potential to expand the application for nuclear reactor technology beyond electricity. The purpose of this research is to reduce both technical and economic risks associated with energy systems of the future. Nuclear hybrid energy systems (NHES) mitigate the variability of renewable energy sources, provide opportunities to produce revenue from different product streams, and avoid capital inefficiencies by matching electrical output to demand by using excess generation capacity for other purposes when it is available. An essential step in the commercialization and deployment of this advanced technology is scaled testing to demonstrate integrated dynamic performance of advanced systems and components when risks cannot be mitigated adequately by analysis or simulation. Further testing in a prototypical environment is needed for validation and higher confidence. This research supports the development of advanced nuclear reactor technology and NHES, and their adaptation to commercial industrial applications that will potentially advance U.S. energy security, economy, and reliability and further reduce carbon emissions. Experimental infrastructure development for testing and feasibility studies of coupled systems can similarly support other projects having similar developmental needs and can generate data required for validation of models in thermal energy storage and transport, energy, and conversion process development. Experiments performed in the Systems Integration Laboratory will acquire performance data, identify scalability issues, and quantify technology gaps and needs for various hybrid or other energy systems. This report discusses detailed scaling (component and integrated system) and heat transfer figures of merit that will establish the experimental infrastructure for component, subsystem, and integrated system testing to advance the technology readiness of components and systems to the level required for commercial
International Nuclear Information System (INIS)
Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.
1981-01-01
A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From this analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained
Hearty, Aine P; Gibney, Michael J
2009-02-01
The aims of the present study were to examine and compare dietary patterns in adults using cluster and factor analyses and to examine the format of the dietary variables on the pattern solutions (i.e. expressed as grams/day (g/d) of each food group or as the percentage contribution to total energy intake). Food intake data were derived from the North/South Ireland Food Consumption Survey 1997-9, which was a randomised cross-sectional study of 7 d recorded food and nutrient intakes of a representative sample of 1379 Irish adults aged 18-64 years. Cluster analysis was performed using the k-means algorithm and principal component analysis (PCA) was used to extract dietary factors. Food data were reduced to thirty-three food groups. For cluster analysis, the most suitable format of the food-group variable was found to be the percentage contribution to energy intake, which produced six clusters: 'Traditional Irish'; 'Continental'; 'Unhealthy foods'; 'Light-meal foods & low-fat milk'; 'Healthy foods'; 'Wholemeal bread & desserts'. For PCA, food groups in the format of g/d were found to be the most suitable format, and this revealed four dietary patterns: 'Unhealthy foods & high alcohol'; 'Traditional Irish'; 'Healthy foods'; 'Sweet convenience foods & low alcohol'. In summary, cluster and PCA identified similar dietary patterns when presented with the same dataset. However, the two dietary pattern methods required a different format of the food-group variable, and the most appropriate format of the input variable should be considered in future studies.
Nika, Varvara; Babyn, Paul; Zhu, Hongmei
2014-07-01
Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.
Forootan, Ehsan; Kusche, Jürgen
2016-04-01
Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i
Conte, Esterina
2017-01-01
Portulaca oleracea is a wild plant pest of orchards and gardens, but is also an edible vegetable rich in beneficial nutrients. It possesses many antioxidant properties due to the high content of vitamins, minerals, omega-3 essential fatty acids and other healthful compounds; therefore, the intake of purslane and/or its bioactive compounds could help to improve the health and function of the whole human organism. Accordingly, in this work it was analyzed and compared to the extractive capacity of the antioxidant component of purslane leaves obtained by solid-liquid extraction techniques such as: hot-maceration, maceration with ultrasound, rapid solid-liquid dynamic extraction using the Naviglio extractor, and a combination of two techniques (mix extraction). The chromatographic analysis by High Performance Liquid Chromatography (HPLC) of the methanolic extract of dried purslane leaves allowed the identification of various polyphenolic compounds for comparison with the standards. In addition, the properties of the different extracts were calculated on dry matter and the antioxidant properties of the total polyphenol components analyzed by the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay. The results showed that mix extraction was the most efficient compared to other techniques. In fact, it obtained a quantity of polyphenols amounting to 237.8 mg Gallic Acid Equivalents (GAE)/100 g of fresh weight, while in other techniques, the range varied from 60–160 mg GAE/100 g fresh weight. In addition, a qualitative analysis by Liquid Chromatography-Tandem Mass Spectrometry (LC/MS/MS) of the phenolic compounds present in the purslane leaves examined was carried out. The compounds were identified by comparison of their molecular weight, fragmentation pattern and retention time with those of standards, using the “Multiple Reaction Monitoring” mode (MRM). Therefore, this study allowed the re-evaluation of a little-known plant that possesses as its beneficial properties, a
Analysis of potential component cleaning techniques. Final report, July 6, 1992 - July 5, 1995
International Nuclear Information System (INIS)
Hess, D.W.
1997-01-01
Elevated temperature, elevated pressure water, supercritical carbon dioxide and helical resonator plasmas were investigated for potential use in surface cleaning. A surface analysis system consisting of X-ray Photoelectron Spectroscopy and Auger Electron Spectroscopy was used to evaluate surfaces exposed to water and supercritical carbon dioxide. Langmuir probe and silicon oxidation studies were used to evaluate the effect of oxygen plasmas on silicon surfaces. Silicon oxides were removed from silicon surfaces by water at temperatures above 260 degrees C and pressures above 2000 psi; silicon oxidation and simultaneous dissolution of the oxide grown occurred under these conditions. A new approach for in-situ monitoring of subcritical and supercritical fluid density was devised
Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi
2018-04-01
Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.
Young, Cole; Reinkensmeyer, David J
2014-08-01
Athletes rely on subjective assessment of complex movements from coaches and judges to improve their motor skills. In some sports, such as diving, snowboard half pipe, gymnastics, and figure skating, subjective scoring forms the basis for competition. It is currently unclear whether this scoring process can be mathematically modeled; doing so could provide insight into what motor skill is. Principal components analysis has been proposed as a motion analysis method for identifying fundamental units of coordination. We used PCA to analyze movement quality of dives taken from USA Diving's 2009 World Team Selection Camp, first identifying eigenpostures associated with dives, and then using the eigenpostures and their temporal weighting coefficients, as well as elements commonly assumed to affect scoring - gross body path, splash area, and board tip motion - to identify eigendives. Within this eigendive space we predicted actual judges' scores using linear regression. This technique rated dives with accuracy comparable to the human judges. The temporal weighting of the eigenpostures, body center path, splash area, and board tip motion affected the score, but not the eigenpostures themselves. These results illustrate that (1) subjective scoring in a competitive diving event can be mathematically modeled; (2) the elements commonly assumed to affect dive scoring actually do affect scoring (3) skill in elite diving is more associated with the gross body path and the effect of the movement on the board and water than the units of coordination that PCA extracts, which might reflect the high level of technique these divers had achieved. We also illustrate how eigendives can be used to produce dive animations that an observer can distort continuously from poor to excellent, which is a novel approach to performance visualization. Copyright © 2014 Elsevier B.V. All rights reserved.
Osis, Sean T; Hettinga, Blayne A; Leitch, Jessica; Ferber, Reed
2014-08-22
As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89-94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.
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...
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
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...
Euler principal component analysis
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,
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...
International Nuclear Information System (INIS)
Bach, F.W.; Steiner, H.; Schreck, G.
1993-01-01
The present joint study performed by the Commissariat a l'energie atomique and the Universitaet Hannover and coordinated by the Commission of the European Communities was intended to analyse the results generated in a number of research contracts concerned with cutting tests in air and underwater, with consideration of the prevailing working conditions. The analysis has led to a large database, giving broadly-assessed information for the dismantling of radioactive components. The range of study was enlarged, where possible, to include recently obtained results outside the present research programme, consideration also being given to supplementary cutting tools and filtration systems not covered by the present programme. Data was concentrated in structured information packages on practical experience available for a series of cutting tools and filters. These were introduced into a computerized user-friendly databank, to be considered as a first-stage development, which should be continuously updated and possibly oriented in the future to an expert system
Energy Technology Data Exchange (ETDEWEB)
Gautam, R.S.; Singh, D.; Mittal, A. [Indian Institute of Technology Roorkee, Roorkee (India)
2007-07-01
Present paper proposes an algorithm for hotspot (sub-surface fire) detection in NOAA/AVHRR images in Jharia region of India by employing Principal Component Analysis (PCA) and fusion technique. Proposed technique is very simple to implement and is more adaptive in comparison to thresholding, multi-thresholding and contextual algorithms. The algorithm takes into account the information of AVHRR channels 1, 2, 3, 4 and vegetation indices NDVI and MSAVI for the required purpose. Proposed technique consists of three steps: (1) detection and removal of cloud and water pixels from preprocessed AVHRR image and screening out the noise of channel 3, (2) application of PCA on multi-channel information along with vegetation index information of NOAA/AVHRR image to obtain principal components, and (3) fusion of information obtained from principal component 1 and 2 to classify image pixels as hotspots. Image processing techniques are applied to fuse information in first two principal component images and no absolute threshold is incorporated to specify whether particular pixel belongs to hotspot class or not, hence, proposed method is adaptive in nature and works successfully for most of the AVHRR images with average 87.27% detection accuracy and 0.201% false alarm rate while comparing with ground truth points in Jharia region of India.
International Nuclear Information System (INIS)
Kim, Jae Joon
2004-01-01
Neural network-based signal classification systems are increasingly used in the analysis of large volumes of data obtained in NDE applications. Ultrasonic inspection methods on the other hand are commonly used in the nondestructive evaluation of welds to detect flaws. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a peculiar signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information tying in the neighboring signals. The approach is based on a 2-dimensional Fourier transform and the principal component analysis to generate a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of actual steel welds are presented
Shi, L.; Wang, Y.; Liu, X.; Mao, J.
2018-03-01
Raman spectroscopy, ultraviolet, visible, and near infrared (UV-Vis-NIR) reflectance spectroscopy, and X-ray fluorescence (XRF) spectroscopy were used to characterize black Tahitian cultured pearls and imitations of these saltwater cultured pearls produced by γ-irradiation, and by coloring of cultured pearls with silver nitrate or organic dyes. Raman spectra indicated that aragonite was the major constituent of these four types of pearl. Using Raman spectroscopy at an excitation wavelength of 514 nm, black Tahitian cultured pearls exhibited characteristic 1100-1700 cm-1 bands. These bands were attributed to various organic components, including conchiolin and other black biological pigments. The peaks shown by saltwater cultured pearls colored with organic dyes varied with the type of dye used. Tahitian cultured and organic-dye-treated saltwater cultured pearls were easily identified by Raman spectroscopy. UV-Vis-NIR reflectance spectra showed bands at 408, 497, and 700 nm derived from porphyrin pigment and other black pigments. The spectra of dye-treated black saltwater pearls showed absorption peaks at 216, 261, 300, and 578 nm. The 261-nm absorption band disappeared from the spectra of γ-irradiated saltwater cultured pearls. This suggests the degradation of conchiolin in the γ-irradiated saltwater cultured pearls. XRF analysis revealed the presence of Ag on the surface of silver nitrate-dyed saltwater cultured pearls.
Shabri, Ani; Samsudin, Ruhaidah
2014-01-01
Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666
Directory of Open Access Journals (Sweden)
Ani Shabri
2014-01-01
Full Text Available Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI, has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.
Shabri, Ani; Samsudin, Ruhaidah
2014-01-01
Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.
International Nuclear Information System (INIS)
Pirkle, F.L.
1981-04-01
STAARS is a new series which is being published to disseminate information concerning statistical procedures for interpreting aerial radiometric data. The application of a particular data interpretation technique to geologic understanding for delineating regions favorable to uranium deposition is the primary concern of STAARS. Statements concerning the utility of a technique on aerial reconnaissance data as well as detailed aerial survey data will be included
Principal Components as a Data Reduction and Noise Reduction Technique
Imhoff, M. L.; Campbell, W. J.
1982-01-01
The potential of principal components as a pipeline data reduction technique for thematic mapper data was assessed and principal components analysis and its transformation as a noise reduction technique was examined. Two primary factors were considered: (1) how might data reduction and noise reduction using the principal components transformation affect the extraction of accurate spectral classifications; and (2) what are the real savings in terms of computer processing and storage costs of using reduced data over the full 7-band TM complement. An area in central Pennsylvania was chosen for a study area. The image data for the project were collected using the Earth Resources Laboratory's thematic mapper simulator (TMS) instrument.
International Nuclear Information System (INIS)
Nair, Suma; Bhati, Sharda
2010-01-01
The concentration of some radiologically and nutritionally important trace elements: Th, Cs, Sr, I, Co, Fe, Zn, Ca and K were determined in major food components such as cereals, pulses, vegetables, fruits, milk etc. The trace elements in food samples were determined using neutron activation analysis technique which involves instrumental and radiochemical neutron activation analysis. Whereas, the trace elements Th, Cs, K and Sr, are important in radiation protection; Fe and Zn are of importance in nutrition studies and Ca and I have dual importance, both in nutrition and radiation protection. The results of analysis show that among the food materials, higher concentrations of Th, Cs, Sr, K, Fe, Zn and Co were found in cereals and pulses. In case of Ca, the milk appears to be the main contributor towards its dietary intake. The estimated concentrations of the trace elements in food components can be employed in determining the daily dietary intake of these elements which in turn can be used for their biokinetic studies. (author)
INTERNAL ENVIRONMENT ANALYSIS TECHNIQUES
Directory of Open Access Journals (Sweden)
Caescu Stefan Claudiu
2011-12-01
Full Text Available Theme The situation analysis, as a separate component of the strategic planning, involves collecting and analysing relevant types of information on the components of the marketing environment and their evolution on the one hand and also on the organization’s resources and capabilities on the other. Objectives of the Research The main purpose of the study of the analysis techniques of the internal environment is to provide insight on those aspects that are of strategic importance to the organization. Literature Review The marketing environment consists of two distinct components, the internal environment that is made from specific variables within the organization and the external environment that is made from variables external to the organization. Although analysing the external environment is essential for corporate success, it is not enough unless it is backed by a detailed analysis of the internal environment of the organization. The internal environment includes all elements that are endogenous to the organization, which are influenced to a great extent and totally controlled by it. The study of the internal environment must answer all resource related questions, solve all resource management issues and represents the first step in drawing up the marketing strategy. Research Methodology The present paper accomplished a documentary study of the main techniques used for the analysis of the internal environment. Results The special literature emphasizes that the differences in performance from one organization to another is primarily dependant not on the differences between the fields of activity, but especially on the differences between the resources and capabilities and the ways these are capitalized on. The main methods of analysing the internal environment addressed in this paper are: the analysis of the organizational resources, the performance analysis, the value chain analysis and the functional analysis. Implications Basically such
Sierra-Pérez, Julián; Torres-Arredondo, M.-A.; Alvarez-Montoya, Joham
2018-01-01
Structural health monitoring consists of using sensors integrated within structures together with algorithms to perform load monitoring, damage detection, damage location, damage size and severity, and prognosis. One possibility is to use strain sensors to infer structural integrity by comparing patterns in the strain field between the pristine and damaged conditions. In previous works, the authors have demonstrated that it is possible to detect small defects based on strain field pattern recognition by using robust machine learning techniques. They have focused on methodologies based on principal component analysis (PCA) and on the development of several unfolding and standardization techniques, which allow dealing with multiple load conditions. However, before a real implementation of this approach in engineering structures, changes in the strain field due to conditions different from damage occurrence need to be isolated. Since load conditions may vary in most engineering structures and promote significant changes in the strain field, it is necessary to implement novel techniques for uncoupling such changes from those produced by damage occurrence. A damage detection methodology based on optimal baseline selection (OBS) by means of clustering techniques is presented. The methodology includes the use of hierarchical nonlinear PCA as a nonlinear modeling technique in conjunction with Q and nonlinear-T 2 damage indices. The methodology is experimentally validated using strain measurements obtained by 32 fiber Bragg grating sensors bonded to an aluminum beam under dynamic bending loads and simultaneously submitted to variations in its pitch angle. The results demonstrated the capability of the methodology for clustering data according to 13 different load conditions (pitch angles), performing the OBS and detecting six different damages induced in a cumulative way. The proposed methodology showed a true positive rate of 100% and a false positive rate of 1.28% for a
Independent component analysis: recent advances
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...
Shifted Independent Component Analysis
DEFF Research Database (Denmark)
Mørup, Morten; Madsen, Kristoffer Hougaard; Hansen, Lars Kai
2007-01-01
Delayed mixing is a problem of theoretical interest and practical importance, e.g., in speech processing, bio-medical signal analysis and financial data modelling. Most previous analyses have been based on models with integer shifts, i.e., shifts by a number of samples, and have often been carried...
Interpretable functional principal component analysis.
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.
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....
Handbook of microwave component measurements with advanced VNA techniques
Dunsmore, Joel P
2012-01-01
This book provides state-of-the-art coverage for making measurements on RF and Microwave Components, both active and passive. A perfect reference for R&D and Test Engineers, with topics ranging from the best practices for basic measurements, to an in-depth analysis of errors, correction methods, and uncertainty analysis, this book provides everything you need to understand microwave measurements. With primary focus on active and passive measurements using a Vector Network Analyzer, these techniques and analysis are equally applicable to measurements made with Spectrum Analyzers or Noise Figure
International Nuclear Information System (INIS)
Dillinger, K.H.
2000-03-01
Tilsit cheese is made by the influence of lab ferment and starter cultures on milk. The ripening is done by repeated inoculation of the surface of the Tilsit cheese with yeasts and read smear cultures. This surface flora forms the typical aroma of the Tilsit cheese during the ripening process. The aim of the work was to receive general knowledge about the kind and amount of the neutral volatile aroma components of Tilsit cheese. Beyond this the ability of forming aroma components by read smear cultures and the dispersion of these components in cheese was to be examined. The results were intended to evaluate the formation of aroma components in Tilsit cheese. The semi-quantitative analyses of the aroma components of all samples were done by combining dynamic headspace extraction, gas chromatography and mass spectrometry. In this process the neutral volatile aroma components were extracted by dynamic headspace technique, adsorbed on a trap, thermally desorbed, separated by gas chromatography, detected and identified by mass spectrometry. 63 components belonging to the chemical classes of esters, ketones, aldehydes, alcohols and sulfur containing substances as well as aromatic hydrocarbons, chlorinated hydrocarbons and hydrocarbons were found in the analysed cheese samples of different Austrian Tilsit manufacturing plants. All cheese samples showed a qualitative equal but quantitative varied spectrum of aroma components. The cultivation of pure cultures on a cheese agar medium showed all analysed aroma components to be involved in the biochemical metabolism of these cultures. The ability to produce aroma components greatly differed between the strains and it was not possible to correlate this ability with the taxonomic classification of the strains. The majority of the components had a non-homogeneous concentration profile in the cheese body. This was explained by effects of diffusion and temporal and spatial different forming of components by the metabolism of the
International Nuclear Information System (INIS)
Shimada, Yoshio; Miyazaki, Takamasa
2006-01-01
In order to analyze large amounts of trouble information of overseas nuclear power plants, it is necessary to select information that is significant in terms of both safety and reliability. In this research, a method of efficiently and simply classifying degrees of importance of components in terms of safety and reliability while paying attention to root-cause components appearing in the information was developed. Regarding safety, the reactor core damage frequency (CDF), which is used in the probabilistic analysis of a reactor, was used. Regarding reliability, the automatic plant trip probability (APTP), which is used in the probabilistic analysis of automatic reactor trips, was used. These two aspects were reflected in the development of criteria for classifying degrees of importance of components. By applying these criteria, a method of quantitatively and simply judging the significance of trouble information of overseas nuclear power plants was developed. (author)
Reliability analysis techniques in power plant design
International Nuclear Information System (INIS)
Chang, N.E.
1981-01-01
An overview of reliability analysis techniques is presented as applied to power plant design. The key terms, power plant performance, reliability, availability and maintainability are defined. Reliability modeling, methods of analysis and component reliability data are briefly reviewed. Application of reliability analysis techniques from a design engineering approach to improving power plant productivity is discussed. (author)
Analysis and analytical techniques
Energy Technology Data Exchange (ETDEWEB)
Batuecas Rodriguez, T [Department of Chemistry and Isotopes, Junta de Energia Nuclear, Madrid (Spain)
1967-01-01
The technology associated with the use of organic coolants in nuclear reactors depends to a large extent on the determination and control of their physical and chemical properties, and particularly on the viability, speed, sensitivity, precision and accuracy (depending on the intended usage) of the methods employed in detection and analytical determination. This has led to the study and development of numerous techniques, some specially designed for the extreme conditions involved in working with the types of product in question and others adapted from existing techniques. In the specific case of polyphenyl and hydropolyphenyl mixtures, which have been the principal subjects of study to date and offer greatest promise, the analytical problems are broadly as follows: Composition of initial product or virgin coolant composition of macro components and amounts of organic and inorganic impurities; Coolant during and after operation. Determination of gases and organic compounds produced by pyrolysis and radiolysis (degradation and polymerization products); Control of systems for purifying and regenerating the coolant after use. Dissolved pressurization gases; Detection of intermediate products during decomposition; these are generally very unstable (free radicals); Degree of fouling and film formation. Tests to determine potential formation of films; Corrosion of structural elements and canning materials; Health and safety. Toxicity, inflammability and impurities that can be activated. Although some of the above problems are closely interrelated and entail similar techniques, they vary as to degree of difficulty. Another question is the difficulty of distinguishing clearly between techniques for determining physical and physico-chemical properties, on one hand, and analytical techniques on the other. Any classification is therefore somewhat arbitrary (for example, in the case of dosimetry and techniques for determining mean molecular weights or electrical conductivity
Directory of Open Access Journals (Sweden)
Mihail Lucian Birsa
2011-10-01
Full Text Available In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen, or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry and GC-MS (gas chromatography-mass spectrometry spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA. The scores of the forensic compounds on the main principal components (PCs were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%, as well as a good selectivity (a rate of true negatives TN
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.
Radar fall detection using principal component analysis
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.
International Nuclear Information System (INIS)
Othman, I.; Bakir, M. A.; Yassine, T.; Sarhel, A.
2001-12-01
The purpose of this study was to investigate the relationship between selenium (Se) concentration in blood components and tumour tissues of breast and GI tract cancers using neutron activation analysis. red blood cell (RBC) and serum Se concentrations were determined in 50 healthy volunteers aged 25-84 years, 70 breast cancer patients aged 25-70 years and 34 GI tract cancer patients aged 31-85 years, Se levels were also determined in malignant and adjacent normal tissues from breast cancer and GI tract cancer patients. The results showed that Se concentrations in serum and RBC were significantly lower among breast and GI cancer compared to healthy volunteers. The results also showed that Se concentrations were significantly higher in the cancer tissues compared to adjacent normal tissues. These data have shown a relationship between selenium status in blood components and both cancer. selenium is enriched in cancer tissue, possibly in an effort of the body to inhibit the growth of tumours. (author)
Techniques for preventing damage to high power laser components
International Nuclear Information System (INIS)
Stowers, I.F.; Patton, H.G.; Jones, W.A.; Wentworth, D.E.
1977-09-01
Techniques for preventing damage to components of the LASL Shiva high power laser system were briefly presented. Optical element damage in the disk amplifier from the combined fluence of the primary laser beam and the Xenon flash lamps that pump the cavity was discussed. Assembly and cleaning techniques were described which have improved optical element life by minimizing particulate and optically absorbing film contamination on assembled amplifier structures. A Class-100 vertical flaw clean room used for assembly and inspection of laser components was also described. The life of a disk amplifier was extended from less than 50 shots to 500 shots through application of these assembly and cleaning techniques
Passive RF component technology materials, techniques, and applications
Wang, Guoan
2012-01-01
Focusing on novel materials and techniques, this pioneering volume provides you with a solid understanding of the design and fabrication of smart RF passive components. You find comprehensive details on LCP, metal materials, ferrite materials, nano materials, high aspect ratio enabled materials, green materials for RFID, and silicon micromachining techniques. Moreover, this practical book offers expert guidance on how to apply these materials and techniques to design a wide range of cutting-edge RF passive components, from MEMS switch based tunable passives and 3D passives, to metamaterial-bas
Functional Generalized Structured Component Analysis.
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.
PCA: Principal Component Analysis for spectra modeling
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.
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)
Directory of Open Access Journals (Sweden)
Hammad Dabo Baba
2014-01-01
Full Text Available One of the most significant step in building structure maintenance decision is the physical inspection of the facility to be maintained. The physical inspection involved cursory assessment of the structure and ratings of the identified defects based on expert evaluation. The objective of this paper is to describe present a novel approach to prioritizing the criticality of physical defects in a residential building system using multi criteria decision analysis approach. A residential building constructed in 1985 was considered in this study. Four criteria which includes; Physical Condition of the building system (PC, Effect on Asset (EA, effect on Occupants (EO and Maintenance Cost (MC are considered in the inspection. The building was divided in to nine systems regarded as alternatives. Expert's choice software was used in comparing the importance of the criteria against the main objective, whereas structured Proforma was used in quantifying the defects observed on all building systems against each criteria. The defects severity score of each building system was identified and later multiplied by the weight of the criteria and final hierarchy was derived. The final ranking indicates that, electrical system was considered the most critical system with a risk value of 0.134 while ceiling system scored the lowest risk value of 0.066. The technique is often used in prioritizing mechanical equipment for maintenance planning. However, result of this study indicates that the technique could be used in prioritizing building systems for maintenance planning
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 ...
Advanced inspection and repair techniques for primary side components
International Nuclear Information System (INIS)
Elm, Ralph
1998-01-01
The availability of nuclear power plant mainly depends on the components of the Nuclear Steam Supply System (NSSS) such as reactor pressure vessel, core internals and steam generators. The last decade has been characterized by intensive inspection and repair work on PWR steam generators. In the future, it can be expected, that the inspection of the reactor pressure vessel and the inspection and repair of its internals, in both PWR and BWR will be one of the challenges for the nuclear community. Due to this challenge, new, advanced inspection and repair techniques for the vital primary side components have been developed and applied, taking into account such issues as: use of reliable and fast inspection methods, repair of affected components instead of costly replacement, reduction of outage time compared to conventional methods, minimized radiation exposure, acceptable costs. This paper reflects on advanced inspection and repair techniques such as: Baffle Former Bolt inspection and replacement, Barrel Former Bolt inspection and replacement, Mechanized UT and visual inspection of reactor pressure vessels, Steam Generator repair by advanced sleeving technology. The techniques described have been successfully applied in nuclear power plants and improved the operation performance of the components and the NPP. (author). 6 figs
Uncertainty analysis techniques
International Nuclear Information System (INIS)
Marivoet, J.; Saltelli, A.; Cadelli, N.
1987-01-01
The origin of the uncertainty affecting Performance Assessments, as well as their propagation to dose and risk results is discussed. The analysis is focused essentially on the uncertainties introduced by the input parameters, the values of which may range over some orders of magnitude and may be given as probability distribution function. The paper briefly reviews the existing sampling techniques used for Monte Carlo simulations and the methods for characterizing the output curves, determining their convergence and confidence limits. Annual doses, expectation values of the doses and risks are computed for a particular case of a possible repository in clay, in order to illustrate the significance of such output characteristics as the mean, the logarithmic mean and the median as well as their ratios. The report concludes that provisionally, due to its better robustness, such estimation as the 90th percentile may be substituted to the arithmetic mean for comparison of the estimated doses with acceptance criteria. In any case, the results obtained through Uncertainty Analyses must be interpreted with caution as long as input data distribution functions are not derived from experiments reasonably reproducing the situation in a well characterized repository and site
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.
Principal component regression analysis with SPSS.
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.
Nonlinear principal component analysis and its applications
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...
Model reduction by weighted Component Cost Analysis
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.
Boat sampling technique for assessment of ageing of components
International Nuclear Information System (INIS)
Kumar, Kundan; Shyam, T.V.; Kayal, J.N.; Rupani, B.B.
2006-01-01
Boat sampling technique (BST) is a surface sampling technique, which has been developed for obtaining, in-situ, metal samples from the surface of an operating component without affecting its operating service life. The BST is non-destructive in nature and the sample is obtained without plastic deformation or without thermal degradation of the parent material. The shape and size of the sample depends upon the shape of the cutter and the surface geometry of the parent material. Miniature test specimens are generated from the sample and the specimens are subjected to various tests, viz. Metallurgical Evaluation, Metallographic Evaluation, Micro-hardness Evaluation, sensitisation test, small punch test etc. to confirm the integrity and assessment of safe operating life of the component. This paper highlights design objective of boat sampling technique, description of sampling module, sampling cutter and its performance evaluation, cutting process, boat samples, operational sequence of sampling module, qualification of sampling module, qualification of sampling technique, qualification of scooped region of the parent material, sample retrieval system, inspection, testing and examination to be carried out on the boat samples and scooped region. (author)
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
Component of the risk analysis
International Nuclear Information System (INIS)
Martinez, I.; Campon, G.
2013-01-01
The power point presentation reviews issues like analysis of risk (Codex), management risk, preliminary activities manager, relationship between government and industries, microbiological danger and communication of risk
Probabilistic techniques using Monte Carlo sampling for multi- component system diagnostics
International Nuclear Information System (INIS)
Aumeier, S.E.; Lee, J.C.; Akcasu, A.Z.
1995-01-01
We outline the structure of a new approach at multi-component system fault diagnostics which utilizes detailed system simulation models, uncertain system observation data, statistical knowledge of system parameters, expert opinion, and component reliability data in an effort to identify incipient component performance degradations of arbitrary number and magnitude. The technique involves the use of multiple adaptive Kalman filters for fault estimation, the results of which are screened using standard hypothesis testing procedures to define a set of component events that could have transpired. Latin Hypercube sample each of these feasible component events in terms of uncertain component reliability data and filter estimates. The capabilities of the procedure are demonstrated through the analysis of a simulated small magnitude binary component fault in a boiling water reactor balance of plant. The results show that the procedure has the potential to be a very effective tool for incipient component fault diagnosis
Tomato sorting using independent component analysis on spectral images
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
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.
Multivariate analysis techniques
Energy Technology Data Exchange (ETDEWEB)
Bendavid, Josh [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Fisher, Wade C. [Michigan State Univ., East Lansing, MI (United States); Junk, Thomas R. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
2016-01-01
The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually both be improved by separating signal events from background events with higher efficiency and purity.
Dynamic Modal Analysis of Vertical Machining Centre Components
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...
International Nuclear Information System (INIS)
Escourbiac, F.; Constans, S.; Courtois, X.; Durocher, A.
2007-01-01
A non destructive testing technique - so called modulated photothermal thermography or lock-in thermography - has been set-up for plasma facing components examination. Reliable measurements of phase contrast were obtained on 8 mm carbon fiber composite (CFC) armoured W7-X divertor component with calibrated flaws. A 3D finite element analysis allowed the correlation of the measured phase contrast and showed that a 4 mm strip flaw can be detected at the CFC/copper interface
Aging techniques and qualified life for safety system components
International Nuclear Information System (INIS)
Weaver, W.W.
1980-01-01
Presently, the qualified life objective for Class IE safety system components in nuclear power plants is somewhat of a subjective engineering judgment. When the desired qualified life is ascertained, there are other choices that must be made (which may be influenced by the desired qualified life) such as selecting the aging procedure to use in the qualification process. Adding complexity to the situation is the fact that there are some limitations in aging techniques at the present time. This article presents (1) a discussion of the limitations in aging procedures, (2) the general philosophy of qualification, and (3) a proposed method for specifying a desired qualified life, which uses a probabilistic approach. The probabilistic approach proposed in item 3 can be applied to natural aging programs and eventually to accelerated aging once the present technical difficulties are overcome
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...
A numerical technique for reactor subchannel analysis
International Nuclear Information System (INIS)
Fath, Hassan E.S.
1983-01-01
A numerical technique is developed for the solution of the transient boundary layer equations with a moving liquid-vapour interface boundary. The technique uses the finite difference method with the velocity components defined over an Eulerian mesh. A system of interface massless markers is defined where the markers move with the flow field according to a simple kinematic relation between the interface geometry and the fluid velocity. Different applications of nuclear engineering interest are reported with some available results. The present technique is capable of predicting the interface profile near the wall which is important in the reactor subchannel analysis
Soil analysis. Modern instrumental technique
International Nuclear Information System (INIS)
Smith, K.A.
1993-01-01
This book covers traditional methods of analysis and specialist monographs on individual instrumental techniques, which are usually not written with soil or plant analysis specifically in mind. The principles of the techniques are combined with discussions of sample preparation and matrix problems, and critical reviews of applications in soil science and related disciplines. Individual chapters are processed separately for inclusion in the appropriate data bases
Surface analysis the principal techniques
Vickerman, John C
2009-01-01
This completely updated and revised second edition of Surface Analysis: The Principal Techniques, deals with the characterisation and understanding of the outer layers of substrates, how they react, look and function which are all of interest to surface scientists. Within this comprehensive text, experts in each analysis area introduce the theory and practice of the principal techniques that have shown themselves to be effective in both basic research and in applied surface analysis. Examples of analysis are provided to facilitate the understanding of this topic and to show readers how they c
Integrating Data Transformation in Principal Components Analysis
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
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...
Structured Performance Analysis for Component Based Systems
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...
Evaluation of flow-induced vibration prediction techniques for in-reactor components
International Nuclear Information System (INIS)
Mulcahy, T.M.; Turula, P.
1975-05-01
Selected in-reactor components of a hydraulic and structural dynamic scale model of the U. S. Energy Research and Development Administration experimental Fast Test Reactor have been studied in an effort to develop and evaluate techniques for predicting vibration behavior of elastic structures exposed to a moving fluid. Existing analysis methods are used to compute the natural frequencies and modal shapes of submerged beam and shell type components. Component response is calculated, assuming as fluid forcing mechanisms both vortex shedding and random excitations characterized by the available hydraulic data. The free and force vibration response predictions are compared with extensive model flow and shaker test data. (U.S.)
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.
Statistical techniques for the identification of reactor component structural vibrations
International Nuclear Information System (INIS)
Kemeny, L.G.
1975-01-01
The identification, on-line and in near real-time, of the vibration frequencies, modes and amplitudes of selected key reactor structural components and the visual monitoring of these phenomena by nuclear power plant operating staff will serve to further the safety and control philosophy of nuclear systems and lead to design optimisation. The School of Nuclear Engineering has developed a data acquisition system for vibration detection and identification. The system is interfaced with the HIFAR research reactor of the Australian Atomic Energy Commission. The reactor serves to simulate noise and vibrational phenomena which might be pertinent in power reactor situations. The data acquisition system consists of a small computer interfaced with a digital correlator and a Fourier transform unit. An incremental tape recorder is utilised as a backing store and as a means of communication with other computers. A small analogue computer and an analogue statistical analyzer can be used in the pre and post computational analysis of signals which are received from neutron and gamma detectors, thermocouples, accelerometers, hydrophones and strain gauges. Investigations carried out to date include a study of the role of local and global pressure fields due to turbulence in coolant flow and pump impeller induced perturbations on (a) control absorbers, (B) fuel element and (c) coolant external circuit and core tank structure component vibrations. (Auth.)
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.
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.
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
Principal components analysis in clinical studies.
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.
Bulk analysis using nuclear techniques
International Nuclear Information System (INIS)
Borsaru, M.; Holmes, R.J.; Mathew, P.J.
1983-01-01
Bulk analysis techniques developed for the mining industry are reviewed. Using penetrating neutron and #betta#-radiations, measurements are obtained directly from a large volume of sample (3-30 kg) #betta#-techniques were used to determine the grade of iron ore and to detect shale on conveyor belts. Thermal neutron irradiation was developed for the simultaneous determination of iron and aluminium in iron ore on a conveyor belt. Thermal-neutron activation analysis includes the determination of alumina in bauxite, and manganese and alumina in manganese ore. Fast neutron activation analysis is used to determine silicon in iron ores, and alumina and silica in bauxite. Fast and thermal neutron activation has been used to determine the soil in shredded sugar cane. (U.K.)
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 ...
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 ...
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...
Applications Of Binary Image Analysis Techniques
Tropf, H.; Enderle, E.; Kammerer, H. P.
1983-10-01
After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.
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.
Independent component analysis for automatic note extraction from musical trills
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.
Optimal Component Lumping: problem formulation and solution techniques
DEFF Research Database (Denmark)
Lin, Bao; Leibovici, Claude F.; Jørgensen, Sten Bay
2008-01-01
This paper presents a systematic method for optimal lumping of a large number of components in order to minimize the loss of information. In principle, a rigorous composition-based model is preferable to describe a system accurately. However, computational intensity and numerical issues restrict ...
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.
ANOVA-principal component analysis and ANOVA-simultaneous component analysis: a comparison.
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.
Advanced Techniques of Stress Analysis
Directory of Open Access Journals (Sweden)
Simion TATARU
2013-12-01
Full Text Available This article aims to check the stress analysis technique based on 3D models also making a comparison with the traditional technique which utilizes a model built directly into the stress analysis program. This comparison of the two methods will be made with reference to the rear fuselage of IAR-99 aircraft, structure with a high degree of complexity which allows a meaningful evaluation of both approaches. Three updated databases are envisaged: the database having the idealized model obtained using ANSYS and working directly on documentation, without automatic generation of nodes and elements (with few exceptions, the rear fuselage database (performed at this stage obtained with Pro/ ENGINEER and the one obtained by using ANSYS with the second database. Then, each of the three databases will be used according to arising necessities.The main objective is to develop the parameterized model of the rear fuselage using the computer aided design software Pro/ ENGINEER. A review of research regarding the use of virtual reality with the interactive analysis performed by the finite element method is made to show the state- of- the-art achieved in this field.
Improvement of Binary Analysis Components in Automated Malware Analysis Framework
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
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
Techniques for Automated Performance Analysis
Energy Technology Data Exchange (ETDEWEB)
Marcus, Ryan C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-09-02
The performance of a particular HPC code depends on a multitude of variables, including compiler selection, optimization flags, OpenMP pool size, file system load, memory usage, MPI configuration, etc. As a result of this complexity, current predictive models have limited applicability, especially at scale. We present a formulation of scientific codes, nodes, and clusters that reduces complex performance analysis to well-known mathematical techniques. Building accurate predictive models and enhancing our understanding of scientific codes at scale is an important step towards exascale computing.
Integrative sparse principal component analysis of gene expression data.
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.
Multi-component separation and analysis of bat echolocation calls.
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.
Multilevel sparse functional principal component analysis.
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.
Blind source separation dependent component analysis
Xiang, Yong; Yang, Zuyuan
2015-01-01
This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sources are presented. The book further focuses on the non-negativity based methods, the time-frequency analysis based methods, and the pre-coding based methods, respectively.
Reliability of surface inspection techniques for pressurized components
International Nuclear Information System (INIS)
Kauppinen, P.; Sillanpaeae, J.
1991-01-01
In the Nordtest NDT-programme (1984 - 1988) the detection of flaws by surface inspection methods has been studied. In the round-robin exercise, 133 test pieces have been inspected by 32 inspectors in Denmark, Finland, Norway and Sweden. From the results, the detectability of defects by magnetic particle and liquid-penetrant testing and the influence of materials and techniques used are evaluated. (author)
A Genealogical Interpretation of Principal Components Analysis
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
Nano powders, components and coatings by plasma technique
McKechnie, Timothy N. (Inventor); Antony, Leo V. M. (Inventor); O'Dell, Scott (Inventor); Power, Chris (Inventor); Tabor, Terry (Inventor)
2009-01-01
Ultra fine and nanometer powders and a method of producing same are provided, preferably refractory metal and ceramic nanopowders. When certain precursors are injected into the plasma flame in a reactor chamber, the materials are heated, melted and vaporized and the chemical reaction is induced in the vapor phase. The vapor phase is quenched rapidly to solid phase to yield the ultra pure, ultra fine and nano product. With this technique, powders have been made 20 nanometers in size in a system capable of a bulk production rate of more than 10 lbs/hr. The process is particularly applicable to tungsten, molybdenum, rhenium, tungsten carbide, molybdenum carbide and other related materials.
Nano powders, components and coatings by plasma technique
McKechnie, Timothy N [Brownsboro, AL; Antony, Leo V. M. [Huntsville, AL; O'Dell, Scott [Arab, AL; Power, Chris [Guntersville, AL; Tabor, Terry [Huntsville, AL
2009-11-10
Ultra fine and nanometer powders and a method of producing same are provided, preferably refractory metal and ceramic nanopowders. When certain precursors are injected into the plasma flame in a reactor chamber, the materials are heated, melted and vaporized and the chemical reaction is induced in the vapor phase. The vapor phase is quenched rapidly to solid phase to yield the ultra pure, ultra fine and nano product. With this technique, powders have been made 20 nanometers in size in a system capable of a bulk production rate of more than 10 lbs/hr. The process is particularly applicable to tungsten, molybdenum, rhenium, tungsten carbide, molybdenum carbide and other related materials.
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...
Light scattering techniques for the characterization of optical components
Hauptvogel, M.; Schröder, S.; Herffurth, T.; Trost, M.; von Finck, A.; Duparré, A.; Weigel, T.
2017-11-01
The rapid developments in optical technologies generate increasingly higher and sometimes completely new demands on the quality of materials, surfaces, components, and systems. Examples for such driving applications are the steadily shrinking feature sizes in semiconductor lithography, nanostructured functional surfaces for consumer optics, and advanced optical systems for astronomy and space applications. The reduction of surface defects as well as the minimization of roughness and other scatter-relevant irregularities are essential factors in all these areas of application. Quality-monitoring for analysing and improving those properties must ensure that even minimal defects and roughness values can be detected reliably. Light scattering methods have a high potential for a non-contact, rapid, efficient, and sensitive determination of roughness, surface structures, and defects.
Small specimen technique for assessing mechanical properties of metallic components
Energy Technology Data Exchange (ETDEWEB)
Lobo, Raquel M.; Andrade, Arnaldo H.P.; Morcelli, Aparecido E., E-mail: rmlobo@ipen.br, E-mail: morcelliae@gmail.com [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2017-11-01
Small Punch Test (SPT) is one of the most promising techniques of small specimen test, which was originally applied in testing of irradiated materials in nuclear engineering. Then it was introduced to other fields as an almost nondestructive method to measure the local mechanical properties that are difficult to be obtained using conventional mechanical tests. Most studies to date are focused on metallic materials, although SPT applications are recently spreading to other materials. The small punch test (SPT) employs small-sized specimens (for example, samples measuring 8 mm in diameter and 0.5 mm thick). The specimen is firmly clamped between two circular dies and is bi-axially strained until failure into a circular hole using a hemispherical punch. The 'load-punch displacement' record can be used to estimate the yield strength, the ultimate tensile strength, the tensile elongation, and the temperature of the ductile-to-brittle transition. Recently, some researchers are working on the use of miniature notched or pre-cracked specimens (denoted as p-SPT) to validate its geometry and dimensions for obtaining the fracture properties of metallic materials. In a first approach, the technique makes it possible to convert primary experimental data into conventional mechanical properties of a massive specimen. In this paper a comprehensive review of the different STP applications is presented with the aim of clarifying its usefulness. (author)
Small specimen technique for assessing mechanical properties of metallic components
International Nuclear Information System (INIS)
Lobo, Raquel M.; Andrade, Arnaldo H.P.; Morcelli, Aparecido E.
2017-01-01
Small Punch Test (SPT) is one of the most promising techniques of small specimen test, which was originally applied in testing of irradiated materials in nuclear engineering. Then it was introduced to other fields as an almost nondestructive method to measure the local mechanical properties that are difficult to be obtained using conventional mechanical tests. Most studies to date are focused on metallic materials, although SPT applications are recently spreading to other materials. The small punch test (SPT) employs small-sized specimens (for example, samples measuring 8 mm in diameter and 0.5 mm thick). The specimen is firmly clamped between two circular dies and is bi-axially strained until failure into a circular hole using a hemispherical punch. The 'load-punch displacement' record can be used to estimate the yield strength, the ultimate tensile strength, the tensile elongation, and the temperature of the ductile-to-brittle transition. Recently, some researchers are working on the use of miniature notched or pre-cracked specimens (denoted as p-SPT) to validate its geometry and dimensions for obtaining the fracture properties of metallic materials. In a first approach, the technique makes it possible to convert primary experimental data into conventional mechanical properties of a massive specimen. In this paper a comprehensive review of the different STP applications is presented with the aim of clarifying its usefulness. (author)
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
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)
Reformulating Component Identification as Document Analysis Problem
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
International Nuclear Information System (INIS)
Kim, Bo Gyung; Kang, Hyun Gook; Kim, Hee Eun; Lee, Seung Jun; Seong, Poong Hyun
2013-01-01
Highlights: • Integrated fault coverage is introduced for reflecting characteristics of fault-tolerant techniques in the reliability model of digital protection system in NPPs. • The integrated fault coverage considers the process of fault-tolerant techniques from detection to fail-safe generation process. • With integrated fault coverage, the unavailability of repairable component of DPS can be estimated. • The new developed reliability model can reveal the effects of fault-tolerant techniques explicitly for risk analysis. • The reliability model makes it possible to confirm changes of unavailability according to variation of diverse factors. - Abstract: With the improvement of digital technologies, digital protection system (DPS) has more multiple sophisticated fault-tolerant techniques (FTTs), in order to increase fault detection and to help the system safely perform the required functions in spite of the possible presence of faults. Fault detection coverage is vital factor of FTT in reliability. However, the fault detection coverage is insufficient to reflect the effects of various FTTs in reliability model. To reflect characteristics of FTTs in the reliability model, integrated fault coverage is introduced. The integrated fault coverage considers the process of FTT from detection to fail-safe generation process. A model has been developed to estimate the unavailability of repairable component of DPS using the integrated fault coverage. The new developed model can quantify unavailability according to a diversity of conditions. Sensitivity studies are performed to ascertain important variables which affect the integrated fault coverage and unavailability
Preliminary detection of explosive standard components with Laser Raman Technique
International Nuclear Information System (INIS)
Botti, S.; Ciardi, R.
2008-01-01
Presently, our section is leader of the ISOTREX project (Integrated System for On-line TRace EXplosives detection in solid, liquid and vapour state), funded in the frame of the PASR 2006 action (Preparatory Action on the enhancement of the European industrial potential in the field of Security Research Preparatory Action) of the 6. EC framework. ISOTREX project will exploit the capabilities of different laser techniques as LIBS (Laser Induced Breakdown Spectroscopy), LPA (Laser Photo Acustic) and CRDS (Cavity Ring Down Spectroscopy) to monitor explosive traces. In this frame, we extended our investigation also to the laser induced Raman effect spectroscopy, in order to investigate its capabilities and possible future integration. We analysed explosive samples in bulk solid phase, diluted liquid phase and as evaporated films over suitable substrate. In the following, we present the main results obtained, outlining preliminary conclusions [it
Wear studies of engine components using neutron activation techniques
International Nuclear Information System (INIS)
Banados Perez, H.E.; Carvalho, G.; Daltro, T.F.L.
1984-01-01
The results obtained in a series of tests for determining the wearing rate of some diesel engine components are reported. The pieces investigated were the needles of fuel injection nozzles, that were previously irradiated with a 10 13 nv in the IEA-R1 nuclear reactor, and the wearing rate was established for different types of fuels. Total wear was calculated by measuring the specific activity of 51 Cr present in the fuel and originated by metal particles worn from the needle. Wear were performed using a device that simulated the actual working conditions of the injection nozzles. The system was run during 350 hours and, along that period, 36 fuel samples of 10 ml each, were collected and analysed for cumulative wear calculation. A metal concentration as low as 10- 6 g in 10 ml of fuel sample could be measured by this method. At present time this procedure is being applied for measuring the wear-rate of other nozzle parts, using localized neutron activation techiques. (Author) [pt
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.
Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox
DEFF Research Database (Denmark)
Nonejad, Nima
This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast...... and efficient framework for estimation. These advantages are used to for instance estimate stochastic volatility models with leverage effect or with Student-t distributed errors. We also model changing time series characteristics of the US inflation rate by considering a heteroskedastic ARFIMA model where...
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
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
Integrating Data Transformation in Principal Components Analysis
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.
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.
CATEGORICAL IMAGE COMPONENTS IN THE FORMING SYSTEM OF A MARKETING TECHNIQUES MANAGER’S IMAGE CULTURE
Directory of Open Access Journals (Sweden)
Anna Borisovna Cherednyakova
2015-08-01
Full Text Available Based on the understanding of the image culture formation of managers of marketing techniques, as a representative of the social and communication interaction of public structures, categorical apparatus of image culture with an emphasis on the etymology of the image, as an integral component of image culture was analyzed. Categorical components of the image are presented from the standpoint of image culture, as personal new formation, an integral part of the professional activity of the marketing techniques manager: object-communicative categorical component, subject-activity categorical component of image, personality-oriented categorical component, value-acmeological categorical component of image.The aim is to identify and justify the image categorical components as a component of image culture of the marketing techniques manager.Method and methodology of work – a general scientific research approach reflecting scientific apparatus of research.Results. Categorical components of the image, as an image culture component of manager of marketing techniques were defined.Practical implication of the results. The theoretical part of «Imageology» course, special course «Image culture of manager of marketing techniques», the theoretical and methodological study and the formation of image culture.
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
ASSESSMENT OF DYNAMIC PRA TECHNIQUES WITH INDUSTRY AVERAGE COMPONENT PERFORMANCE DATA
Energy Technology Data Exchange (ETDEWEB)
Yadav, Vaibhav; Agarwal, Vivek; Gribok, Andrei V.; Smith, Curtis L.
2017-06-01
In the nuclear industry, risk monitors are intended to provide a point-in-time estimate of the system risk given the current plant configuration. Current risk monitors are limited in that they do not properly take into account the deteriorating states of plant equipment, which are unit-specific. Current approaches to computing risk monitors use probabilistic risk assessment (PRA) techniques, but the assessment is typically a snapshot in time. Living PRA models attempt to address limitations of traditional PRA models in a limited sense by including temporary changes in plant and system configurations. However, information on plant component health are not considered. This often leaves risk monitors using living PRA models incapable of conducting evaluations with dynamic degradation scenarios evolving over time. There is a need to develop enabling approaches to solidify risk monitors to provide time and condition-dependent risk by integrating traditional PRA models with condition monitoring and prognostic techniques. This paper presents estimation of system risk evolution over time by integrating plant risk monitoring data with dynamic PRA methods incorporating aging and degradation. Several online, non-destructive approaches have been developed for diagnosing plant component conditions in nuclear industry, i.e., condition indication index, using vibration analysis, current signatures, and operational history [1]. In this work the component performance measures at U.S. commercial nuclear power plants (NPP) [2] are incorporated within the various dynamic PRA methodologies [3] to provide better estimates of probability of failures. Aging and degradation is modeled within the Level-1 PRA framework and is applied to several failure modes of pumps and can be extended to a range of components, viz. valves, generators, batteries, and pipes.
PRINCIPAL COMPONENT ANALYSIS (PCA DAN APLIKASINYA DENGAN SPSS
Directory of Open Access Journals (Sweden)
Hermita Bus Umar
2009-03-01
Full Text Available PCA (Principal Component Analysis are statistical techniques applied to a single set of variables when the researcher is interested in discovering which variables in the setform coherent subset that are relativity independent of one another.Variables that are correlated with one another but largely independent of other subset of variables are combined into factors. The Coals of PCA to which each variables is explained by each dimension. Step in PCA include selecting and mean measuring a set of variables, preparing the correlation matrix, extracting a set offactors from the correlation matrixs. Rotating the factor to increase interpretabilitv and interpreting the result.
Structure analysis of active components of traditional Chinese medicines
DEFF Research Database (Denmark)
Zhang, Wei; Sun, Qinglei; Liu, Jianhua
2013-01-01
Traditional Chinese Medicines (TCMs) have been widely used for healing of different health problems for thousands of years. They have been used as therapeutic, complementary and alternative medicines. TCMs usually consist of dozens to hundreds of various compounds, which are extracted from raw...... herbal sources by aqueous or alcoholic solvents. Therefore, it is difficult to correlate the pharmaceutical effect to a specific lead compound in the TCMs. A detailed analysis of various components in TCMs has been a great challenge for modern analytical techniques in recent decades. In this chapter...
Group-wise Principal Component Analysis for Exploratory Data Analysis
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
Gene set analysis using variance component tests.
Huang, Yen-Tsung; Lin, Xihong
2013-06-28
Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.
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...
Probabilistic structural analysis methods for select space propulsion system components
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.
Demixed principal component analysis of neural population data.
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.
Running Technique is an Important Component of Running Economy and Performance
FOLLAND, JONATHAN P.; ALLEN, SAM J.; BLACK, MATTHEW I.; HANDSAKER, JOSEPH C.; FORRESTER, STEPHANIE E.
2017-01-01
ABSTRACT Despite an intuitive relationship between technique and both running economy (RE) and performance, and the diverse techniques used by runners to achieve forward locomotion, the objective importance of overall technique and the key components therein remain to be elucidated. Purpose This study aimed to determine the relationship between individual and combined kinematic measures of technique with both RE and performance. Methods Ninety-seven endurance runners (47 females) of diverse competitive standards performed a discontinuous protocol of incremental treadmill running (4-min stages, 1-km·h−1 increments). Measurements included three-dimensional full-body kinematics, respiratory gases to determine energy cost, and velocity of lactate turn point. Five categories of kinematic measures (vertical oscillation, braking, posture, stride parameters, and lower limb angles) and locomotory energy cost (LEc) were averaged across 10–12 km·h−1 (the highest common velocity < velocity of lactate turn point). Performance was measured as season's best (SB) time converted to a sex-specific z-score. Results Numerous kinematic variables were correlated with RE and performance (LEc, 19 variables; SB time, 11 variables). Regression analysis found three variables (pelvis vertical oscillation during ground contact normalized to height, minimum knee joint angle during ground contact, and minimum horizontal pelvis velocity) explained 39% of LEc variability. In addition, four variables (minimum horizontal pelvis velocity, shank touchdown angle, duty factor, and trunk forward lean) combined to explain 31% of the variability in performance (SB time). Conclusions This study provides novel and robust evidence that technique explains a substantial proportion of the variance in RE and performance. We recommend that runners and coaches are attentive to specific aspects of stride parameters and lower limb angles in part to optimize pelvis movement, and ultimately enhance performance
Analysis of failed nuclear plant components
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 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
A radiographic analysis of implant component misfit.
LENUS (Irish Health Repository)
Sharkey, Seamus
2011-07-01
Radiographs are commonly used to assess the fit of implant components, but there is no clear agreement on the amount of misfit that can be detected by this method. This study investigated the effect of gap size and the relative angle at which a radiograph was taken on the detection of component misfit. Different types of implant connections (internal or external) and radiographic modalities (film or digital) were assessed.
Colwell, R. N.
1973-01-01
Since May 1970, personnel on several campuses of the University of California have been conducting investigations which seek to determine the usefulness of modern remote sensing techniques for studying various components of California's earth resources complex. Emphasis has been given to California's water resources as exemplified by the Feather River project and other aspects of the California Water Plan. This study is designed to consider in detail the supply, demand, and impact relationships. The specific geographic areas studied are the Feather River drainage in northern California, the Chino-Riverside Basin and Imperial Valley areas in southern California, and selected portions of the west side of San Joaquin Valley in central California. An analysis is also given on how an effective benefit-cost study of remote sensing in relation to California's water resources might best be made.
Lifetime analysis of fusion-reactor components
International Nuclear Information System (INIS)
Mattas, R.F.
1983-01-01
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 modelling 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 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
Mapping ash properties using principal components analysis
Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Ubeda, Xavier; Novara, Agata; Francos, Marcos; Rodrigo-Comino, Jesus; Bogunovic, Igor; Khaledian, Yones
2017-04-01
In post-fire environments ash has important benefits for soils, such as protection and source of nutrients, crucial for vegetation recuperation (Jordan et al., 2016; Pereira et al., 2015a; 2016a,b). The thickness and distribution of ash are fundamental aspects for soil protection (Cerdà and Doerr, 2008; Pereira et al., 2015b) and the severity at which was produced is important for the type and amount of elements that is released in soil solution (Bodi et al., 2014). Ash is very mobile material, and it is important were it will be deposited. Until the first rainfalls are is very mobile. After it, bind in the soil surface and is harder to erode. Mapping ash properties in the immediate period after fire is complex, since it is constantly moving (Pereira et al., 2015b). However, is an important task, since according the amount and type of ash produced we can identify the degree of soil protection and the nutrients that will be dissolved. The objective of this work is to apply to map ash properties (CaCO3, pH, and select extractable elements) using a principal component analysis (PCA) in the immediate period after the fire. Four days after the fire we established a grid in a 9x27 m area and took ash samples every 3 meters for a total of 40 sampling points (Pereira et al., 2017). The PCA identified 5 different factors. Factor 1 identified high loadings in electrical conductivity, calcium, and magnesium and negative with aluminum and iron, while Factor 3 had high positive loadings in total phosphorous and silica. Factor 3 showed high positive loadings in sodium and potassium, factor 4 high negative loadings in CaCO3 and pH, and factor 5 high loadings in sodium and potassium. The experimental variograms of the extracted factors showed that the Gaussian model was the most precise to model factor 1, the linear to model factor 2 and the wave hole effect to model factor 3, 4 and 5. The maps produced confirm the patternd observed in the experimental variograms. Factor 1 and 2
Generalized structured component analysis a component-based approach to structural equation modeling
Hwang, Heungsun
2014-01-01
Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...
Principal component analysis of psoriasis lesions images
DEFF Research Database (Denmark)
Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær
2003-01-01
A set of RGB images of psoriasis lesions is used. By visual examination of these images, there seem to be no common pattern that could be used to find and align the lesions within and between sessions. It is expected that the principal components of the original images could be useful during future...
Independent component analysis classification of laser induced breakdown spectroscopy spectra
International Nuclear Information System (INIS)
Forni, Olivier; Maurice, Sylvestre; Gasnault, Olivier; Wiens, Roger C.; Cousin, Agnès; Clegg, Samuel M.; Sirven, Jean-Baptiste; Lasue, Jérémie
2013-01-01
The ChemCam instrument on board Mars Science Laboratory (MSL) rover uses the laser-induced breakdown spectroscopy (LIBS) technique to remotely analyze Martian rocks. It retrieves spectra up to a distance of seven meters to quantify and to quantitatively analyze the sampled rocks. Like any field application, on-site measurements by LIBS are altered by diverse matrix effects which induce signal variations that are specific to the nature of the sample. Qualitative aspects remain to be studied, particularly LIBS sample identification to determine which samples are of interest for further analysis by ChemCam and other rover instruments. This can be performed with the help of different chemometric methods that model the spectra variance in order to identify a the rock from its spectrum. In this paper we test independent components analysis (ICA) rock classification by remote LIBS. We show that using measures of distance in ICA space, namely the Manhattan and the Mahalanobis distance, we can efficiently classify spectra of an unknown rock. The Mahalanobis distance gives overall better performances and is easier to manage than the Manhattan distance for which the determination of the cut-off distance is not easy. However these two techniques are complementary and their analytical performances will improve with time during MSL operations as the quantity of available Martian spectra will grow. The analysis accuracy and performances will benefit from a combination of the two approaches. - Highlights: • We use a novel independent component analysis method to classify LIBS spectra. • We demonstrate the usefulness of ICA. • We report the performances of the ICA classification. • We compare it to other classical classification schemes
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
Nuclear analysis techniques and environmental sciences
International Nuclear Information System (INIS)
1997-10-01
31 theses are collected in this book. It introduced molecular activation analysis micro-PIXE and micro-probe analysis, x-ray fluorescence analysis and accelerator mass spectrometry. The applications about these nuclear analysis techniques are presented and reviewed for environmental sciences
Analysis of archaeological pieces with nuclear techniques
International Nuclear Information System (INIS)
Tenorio, D.
2002-01-01
In this work nuclear techniques such as Neutron Activation Analysis, PIXE, X-ray fluorescence analysis, Metallography, Uranium series, Rutherford Backscattering for using in analysis of archaeological specimens and materials are described. Also some published works and thesis about analysis of different Mexican and Meso american archaeological sites are referred. (Author)
Chemical analysis by nuclear techniques
International Nuclear Information System (INIS)
Sohn, S. C.; Kim, W. H.; Park, Y. J.; Park, Y. J.; Song, B. C.; Jeon, Y. S.; Jee, K. Y.; Pyo, H. Y.
2002-01-01
This state art report consists of four parts, production of micro-particles, analysis of boron, alpha tracking method and development of neutron induced prompt gamma ray spectroscopy (NIPS) system. The various methods for the production of micro-paticles such as mechanical method, electrolysis method, chemical method, spray method were described in the first part. The second part contains sample treatment, separation and concentration, analytical method, and application of boron analysis. The third part contains characteristics of alpha track, track dectectors, pretreatment of sample, neutron irradiation, etching conditions for various detectors, observation of track on the detector, etc. The last part contains basic theory, neutron source, collimator, neutron shields, calibration of NIPS, and application of NIPS system
Chemical analysis by nuclear techniques
Energy Technology Data Exchange (ETDEWEB)
Sohn, S. C.; Kim, W. H.; Park, Y. J.; Song, B. C.; Jeon, Y. S.; Jee, K. Y.; Pyo, H. Y
2002-01-01
This state art report consists of four parts, production of micro-particles, analysis of boron, alpha tracking method and development of neutron induced prompt gamma ray spectroscopy (NIPS) system. The various methods for the production of micro-paticles such as mechanical method, electrolysis method, chemical method, spray method were described in the first part. The second part contains sample treatment, separation and concentration, analytical method, and application of boron analysis. The third part contains characteristics of alpha track, track dectectors, pretreatment of sample, neutron irradiation, etching conditions for various detectors, observation of track on the detector, etc. The last part contains basic theory, neutron source, collimator, neutron shields, calibration of NIPS, and application of NIPS system.
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
CATEGORICAL IMAGE COMPONENTS IN THE FORMING SYSTEM OF A MARKETING TECHNIQUES MANAGER’S IMAGE CULTURE
Anna Borisovna Cherednyakova
2015-01-01
Based on the understanding of the image culture formation of managers of marketing techniques, as a representative of the social and communication interaction of public structures, categorical apparatus of image culture with an emphasis on the etymology of the image, as an integral component of image culture was analyzed. Categorical components of the image are presented from the standpoint of image culture, as personal new formation, an integral part of the professional activity of the marke...
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
Olsztyńska-Janus, Sylwia; Szymborska-Małek, Katarzyna; Gąsior-Głogowska, Marlena; Walski, Tomasz; Komorowska, Małgorzata; Witkiewicz, Wojciech; Pezowicz, Celina; Kobielarz, Magdalena; Szotek, Sylwia
2012-01-01
Among the currently used methods of monitoring human tissues and their components many types of research are distinguished. These include spectroscopic techniques. The advantage of these techniques is the small amount of sample required, the rapid process of recording the spectra, and most importantly in the case of biological samples - preparation of tissues is not required. In this work, vibrational spectroscopy: ATR-FTIR and Raman spectroscopy will be used. Studies are carried out on tissues: tendons, blood vessels, skin, red blood cells and biological components: amino acids, proteins, DNA, plasma, and deposits.
Columbia River Component Data Gap Analysis
Energy Technology Data Exchange (ETDEWEB)
L. C. Hulstrom
2007-10-23
This Data Gap Analysis report documents the results of a study conducted by Washington Closure Hanford (WCH) to compile and reivew the currently available surface water and sediment data for the Columbia River near and downstream of the Hanford Site. This Data Gap Analysis study was conducted to review the adequacy of the existing surface water and sediment data set from the Columbia River, with specific reference to the use of the data in future site characterization and screening level risk assessments.
Event tree analysis using artificial intelligence techniques
International Nuclear Information System (INIS)
Dixon, B.W.; Hinton, M.F.
1985-01-01
Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs
Energy Technology Data Exchange (ETDEWEB)
NONE
2013-09-15
direction of research, development and demonstration in this area. The technologies discussed in this project are intended to establish the state of the art in surveillance, diagnostics and prognostics (SDP) technologies for equipment and process health monitoring in nuclear facilities. It is also intended to identify technology gaps and research needs of the nuclear industry in the area of SDP. The report draws on the conventional SDP technologies, as well as the latest tools, algorithms and techniques that have emerged over the last few years, especially in enabling technologies including fast data acquisition, data storage, data qualification and data analysis algorithms, such as empirical and physical modelling techniques. These new tools have made it possible to identify problems earlier and with better resolution. The significance of the material presented in this report is that it contributes not only to the current needs of the nuclear industry but also to the design improvements of the next generation of reactors. For example, the nuclear industry is currently striving to operate the plants for up to 80 years or more, as the value of nuclear assets has risen in recent years, resulting partly from environmental concerns with fossil energy production, as well as increased future demand for base load electricity. This long term operation (LTO) or life extension goal of the nuclear industry has stimulated renewed interest in more frequent monitoring of equipment to guard against ageing effects, not to mention the economic benefits that SDP implementation can produce, and contributions to radiation exposure that is as low as reasonably achievable, reduction of human errors, and optimized maintenance. Together with capabilities that enhance situational awareness, the technologies described in this report will enable more holistic management of plant structures, systems and components (SSCs), maintain high capacity factor in LTO and enable higher levels of safe operation
International Nuclear Information System (INIS)
2013-01-01
direction of research, development and demonstration in this area. The technologies discussed in this project are intended to establish the state of the art in surveillance, diagnostics and prognostics (SDP) technologies for equipment and process health monitoring in nuclear facilities. It is also intended to identify technology gaps and research needs of the nuclear industry in the area of SDP. The report draws on the conventional SDP technologies, as well as the latest tools, algorithms and techniques that have emerged over the last few years, especially in enabling technologies including fast data acquisition, data storage, data qualification and data analysis algorithms, such as empirical and physical modelling techniques. These new tools have made it possible to identify problems earlier and with better resolution. The significance of the material presented in this report is that it contributes not only to the current needs of the nuclear industry but also to the design improvements of the next generation of reactors. For example, the nuclear industry is currently striving to operate the plants for up to 80 years or more, as the value of nuclear assets has risen in recent years, resulting partly from environmental concerns with fossil energy production, as well as increased future demand for base load electricity. This long term operation (LTO) or life extension goal of the nuclear industry has stimulated renewed interest in more frequent monitoring of equipment to guard against ageing effects, not to mention the economic benefits that SDP implementation can produce, and contributions to radiation exposure that is as low as reasonably achievable, reduction of human errors, and optimized maintenance. Together with capabilities that enhance situational awareness, the technologies described in this report will enable more holistic management of plant structures, systems and components (SSCs), maintain high capacity factor in LTO and enable higher levels of safe operation
Projection and analysis of nuclear components
International Nuclear Information System (INIS)
Heeschen, U.
1980-01-01
The classification and the types of analysis carried out in pipings for quality control and safety of nuclear power plants, are presented. The operation and emergency conditions with emphasis of possible simplifications of calculations are described. (author/M.C.K.) [pt
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....
TV content analysis techniques and applications
Kompatsiaris, Yiannis
2012-01-01
The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers. Leaving no stone unturned, TV Content Analysis: Techniques and Applications provides a detailed exploration of TV program analysis techniques. Leading researchers and academics from around the world supply scientifically sound treatment of recent developments across the related subject areas--including systems, architectures, algorithms,
Statistical evaluation of vibration analysis techniques
Milner, G. Martin; Miller, Patrice S.
1987-01-01
An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.
Determination of the optimal number of components in independent components analysis.
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.
Nonparametric inference in nonlinear principal components analysis : exploration and beyond
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),
Principal component analysis networks and algorithms
Kong, Xiangyu; Duan, Zhansheng
2017-01-01
This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
International Nuclear Information System (INIS)
Lilen, H.
1976-01-01
Neutron and electron bombardment techniques for materials doping, newly introduced in the fabrication of power semiconductor components: diodes, transistors, thyristors, and triacs are briefly outlined. A neutron bombardment of high purity silicon results in a short-lived 31 Si isotope (from 30 Si) decaying into 31 P. The phosphorus with its five peripheral electrons induces a negative doping (N), and the neutron technique gives a homogeneous doping. Furthermore, silicon bombardment with 1 to 2MeV electrons induces micro-ruptures in the lattice, that act as recombination traps reducing carrier lifetimes. Consequently, gold diffusion techniques can be replaced by electron bombardment with a gain in controlling carrier lifetimes [fr
Kernel principal component analysis for change detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Morton, J.C.
2008-01-01
region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....
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...
How Many Separable Sources? Model Selection In Independent Components Analysis
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
Abstract Interfaces for Data Analysis Component Architecture for Data Analysis Tools
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...
International Nuclear Information System (INIS)
Chatterjee, S.; Madhusoodanan, K.; Panwar, Sanjay; Rupani, B.B.
2007-01-01
Material properties of components change during service due to environmental conditions. Measurement of mechanical properties of the components is important for assessing their fitness for service. In many instances, it is not possible to remove sizable samples from the component for doing the measurement in laboratory. In-situ technique for measurement of mechanical properties has great significance in such cases. One of the nondestructive methods that can be adopted for in-situ application is based on cyclic ball indentation technique. It involves multiple indentation cycles (at the same penetration location) on a metallic surface by a spherical indenter. Each cycle consists of indentation, partial unload and reload sequences. Presently, commercial systems are available for doing indentation test on structural component for limited applications. But, there is a genuine need of remotely operable compact in-situ property measurement system. Considering the importance of such applications Reactor Engineering Division of BARC has developed an In-situ Property Measurement System (IProMS), which can be used for in-situ measurement of mechanical properties of a flat or tubular component. This paper highlights the basic theory of measurement, qualification tests on IProMS and results from tests done on flat specimens and tubular component. (author)
Using Machine Learning Techniques in the Analysis of Oceanographic Data
Falcinelli, K. E.; Abuomar, S.
2017-12-01
Acoustic Doppler Current Profilers (ADCPs) are oceanographic tools capable of collecting large amounts of current profile data. Using unsupervised machine learning techniques such as principal component analysis, fuzzy c-means clustering, and self-organizing maps, patterns and trends in an ADCP dataset are found. Cluster validity algorithms such as visual assessment of cluster tendency and clustering index are used to determine the optimal number of clusters in the ADCP dataset. These techniques prove to be useful in analysis of ADCP data and demonstrate potential for future use in other oceanographic applications.
Techniques and Applications of Urban Data Analysis
AlHalawani, Sawsan N.
2016-05-26
Digitization and characterization of urban spaces are essential components as we move to an ever-growing ’always connected’ world. Accurate analysis of such digital urban spaces has become more important as we continue to get spatial and social context-aware feedback and recommendations in our daily activities. Modeling and reconstruction of urban environments have thus gained unprecedented importance in the last few years. Such analysis typically spans multiple disciplines, such as computer graphics, and computer vision as well as architecture, geoscience, and remote sensing. Reconstructing an urban environment usually requires an entire pipeline consisting of different tasks. In such a pipeline, data analysis plays a strong role in acquiring meaningful insights from the raw data. This dissertation primarily focuses on the analysis of various forms of urban data and proposes a set of techniques to extract useful information, which is then used for different applications. The first part of this dissertation presents a semi-automatic framework to analyze facade images to recover individual windows along with their functional configurations such as open or (partially) closed states. The main advantage of recovering both the repetition patterns of windows and their individual deformation parameters is to produce a factored facade representation. Such a factored representation enables a range of applications including interactive facade images, improved multi-view stereo reconstruction, facade-level change detection, and novel image editing possibilities. The second part of this dissertation demonstrates the importance of a layout configuration on its performance. As a specific application scenario, I investigate the interior layout of warehouses wherein the goal is to assign items to their storage locations while reducing flow congestion and enhancing the speed of order picking processes. The third part of the dissertation proposes a method to classify cities
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)
Elemental analysis techniques using proton microbeam
International Nuclear Information System (INIS)
Sakai, Takuro; Oikawa, Masakazu; Sato, Takahiro
2005-01-01
Proton microbeam is a powerful tool for two-dimensional elemental analysis. The analysis is based on Particle Induced X-ray Emission (PIXE) and Particle Induced Gamma-ray Emission (PIGE) techniques. The paper outlines the principles and instruments, and describes the dental application has been done in JAERI Takasaki. (author)
Ultrasonic techniques for quality assessment of ITER Divertor plasma facing component
International Nuclear Information System (INIS)
Martinez-Ona, Rafael; Garcia, Monica; Medrano, Mercedes
2009-01-01
The divertor is one of the most challenging components of ITER machine. Its plasma facing components contain thousands of joints that should be assessed to demonstrate their integrity during the required lifetime. Ultrasonic (US) techniques have been developed to study the capability of defect detection and to control the quality and degradation of these interfaces after the manufacturing process. Three types of joints made of carbon fibre composite to copper alloy, tungsten to copper alloy, and copper-to-copper alloy with two types of configurations have been studied. More than 100 samples representing these configurations and containing implanted flaws of different sizes have been examined. US techniques developed are detailed and results of validation samples examination before and after high heat flux (HHF) tests are presented. The results show that for W monoblocks the US technique is able to detect, locate and size the degradations in the two sample joints; for CFC monoblocks, the US technique is also able to detect, locate and size the calibrated defects in the two joints before the HHF, however after the HHF test the technique is not able to reliably detect defects in the CFC/Cu joint; finally, for the W flat tiles the US technique is able to detect, locate and size the calibrated defects in the two joints before HHF test, nevertheless defect location and sizing are more difficult after the HHF test.
Techniques for sensitivity analysis of SYVAC results
International Nuclear Information System (INIS)
Prust, J.O.
1985-05-01
Sensitivity analysis techniques may be required to examine the sensitivity of SYVAC model predictions to the input parameter values, the subjective probability distributions assigned to the input parameters and to the relationship between dose and the probability of fatal cancers plus serious hereditary disease in the first two generations of offspring of a member of the critical group. This report mainly considers techniques for determining the sensitivity of dose and risk to the variable input parameters. The performance of a sensitivity analysis technique may be improved by decomposing the model and data into subsets for analysis, making use of existing information on sensitivity and concentrating sampling in regions the parameter space that generates high doses or risks. A number of sensitivity analysis techniques are reviewed for their application to the SYVAC model including four techniques tested in an earlier study by CAP Scientific for the SYVAC project. This report recommends the development now of a method for evaluating the derivative of dose and parameter value and extending the Kruskal-Wallis technique to test for interactions between parameters. It is also recommended that the sensitivity of the output of each sub-model of SYVAC to input parameter values should be examined. (author)
Tripathy, Manoj
2012-01-01
This paper describes a new approach for power transformer differential protection which is based on the wave-shape recognition technique. An algorithm based on neural network principal component analysis (NNPCA) with back-propagation learning is proposed for digital differential protection of power transformer. The principal component analysis is used to preprocess the data from power system in order to eliminate redundant information and enhance hidden pattern of differential current to disc...
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 ...
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
Flow analysis techniques for phosphorus: an overview.
Estela, José Manuel; Cerdà, Víctor
2005-04-15
A bibliographical review on the implementation and the results obtained in the use of different flow analytical techniques for the determination of phosphorus is carried out. The sources, occurrence and importance of phosphorus together with several aspects regarding the analysis and terminology used in the determination of this element are briefly described. A classification as well as a brief description of the basis, advantages and disadvantages of the different existing flow techniques, namely; segmented flow analysis (SFA), flow injection analysis (FIA), sequential injection analysis (SIA), all injection analysis (AIA), batch injection analysis (BIA), multicommutated FIA (MCFIA), multisyringe FIA (MSFIA) and multipumped FIA (MPFIA) is also carried out. The most relevant manuscripts regarding the analysis of phosphorus by means of flow techniques are herein classified according to the detection instrumental technique used with the aim to facilitate their study and obtain an overall scope. Finally, the analytical characteristics of numerous flow-methods reported in the literature are provided in the form of a table and their applicability to samples with different matrixes, namely water samples (marine, river, estuarine, waste, industrial, drinking, etc.), soils leachates, plant leaves, toothpaste, detergents, foodstuffs (wine, orange juice, milk), biological samples, sugars, fertilizer, hydroponic solutions, soils extracts and cyanobacterial biofilms are tabulated.
Quality assurance techniques for activation analysis
International Nuclear Information System (INIS)
Becker, D.A.
1984-01-01
The principles and techniques of quality assurance are applied to the measurement method of activation analysis. Quality assurance is defined to include quality control and quality assessment. Plans for quality assurance include consideration of: personnel; facilities; analytical design; sampling and sample preparation; the measurement process; standards; and documentation. Activation analysis concerns include: irradiation; chemical separation; counting/detection; data collection, and analysis; and calibration. Types of standards discussed include calibration materials and quality assessment materials
International Nuclear Information System (INIS)
Oras, J.J.; Kasza, K.E.
1988-01-01
A novel laser flow visualization technique is presented together with examples of its use in visualizing complex flow patterns and plans for its further development. This technique has been successfully used to study (1) the flow in a horizontal pipe subject to temperature transients, to view the formation and breakup of thermally stratified flow and to determine instantaneous velocity distributions in the same flow at various axial locations; (2) the discharge of a stratified pipe flow into a plenum exhibiting a periodic vortex pattern; and (3) the thermal-buoyancy-induced flow channeling on the shell side of a heat exchanger with glass tubes and shell. This application of the technique to heat exchangers is unique. The flow patterns deep within a large tube bundle can be studied under steady or transient conditions. This laser flow visualization technique constitutes a very powerful tool for studying single or multiphase flows in complex thermal system components
Variational Bayesian Learning for Wavelet Independent Component Analysis
Roussos, E.; Roberts, S.; Daubechies, I.
2005-11-01
In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.
International Nuclear Information System (INIS)
Bonnet, Nogl; Nuzillard, Danielle
2005-01-01
A complementary approach is proposed for analysing series of electron energy-loss spectra that can be recorded with the spectrum-line technique, across an interface for instance. This approach, called blind source separation (BSS) or independent component analysis (ICA), complements two existing methods: the spatial difference approach and multivariate statistical analysis. The principle of the technique is presented and illustrations are given through one simulated example and one real example
Techniques and Applications of Urban Data Analysis
AlHalawani, Sawsan
2016-01-01
Digitization and characterization of urban spaces are essential components as we move to an ever-growing ’always connected’ world. Accurate analysis of such digital urban spaces has become more important as we continue to get spatial and social
International Nuclear Information System (INIS)
Giniyatulin, R.N.; Komarov, V.L.; Kuzmin, E.G.; Makhankov, A.N.; Mazul, I.V.; Yablokov, N.A.; Zhuk, A.N.
2002-01-01
Joining of tungsten with copper-based cooling structure and armour geometry optimization are the major aspects in development of the tungsten-armoured plasma facing components (PFC). Fabrication techniques and high heat flux (HHF) tests of tungsten-armoured components have to reflect different PFC designs and acceptable manufacturing cost. The authors present the recent results of tungsten-armoured mock-ups development based on manufacturing and HHF tests. Two aspects were investigated--selection of armour geometry and examination of tungsten-copper bonding techniques. Brazing and casting tungsten-copper bonding techniques were used in small mock-ups. The mock-ups with armour tiles (20x5x10, 10x10x10, 20x20x10, 27x27x10) mm 3 in dimensions were tested by cyclic heat fluxes in the range of (5-20) MW/m 2 , the number of thermal cycles varied from hundreds to several thousands for each mock-up. The results of the tests show the applicability of different geometry and different bonding technique to corresponding heat loading. A medium-scale mock-up 0.6-m in length was manufactured and tested. HHF tests of the medium-scale mock-up have demonstrated the applicability of the applied bonding techniques and armour geometry for full-scale PFC's manufacturing
Analysis of contaminants on electronic components by reflectance FTIR spectroscopy
International Nuclear Information System (INIS)
Griffith, G.W.
1982-09-01
The analysis of electronic component contaminants by infrared spectroscopy is often a difficult process. Most of the contaminants are very small, which necessitates the use of microsampling techniques. Beam condensers will provide the required sensitivity but most require that the sample be removed from the substrate before analysis. Since it can be difficult and time consuming, it is usually an undesirable approach. Micro ATR work can also be exasperating, due to the difficulty of positioning the sample at the correct place under the ATR plate in order to record a spectrum. This paper describes a modified reflection beam condensor which has been adapted to a Nicolet 7199 FTIR. The sample beam is directed onto the sample surface and reflected from the substrate back to the detector. A micropositioning XYZ stage and a close-focusing telescope are used to position the contaminant directly under the infrared beam. It is possible to analyze contaminants on 1 mm wide leads surrounded by an epoxy matrix using this device. Typical spectra of contaminants found on small circuit boards are included
A survival analysis on critical components of nuclear power plants
International Nuclear Information System (INIS)
Durbec, V.; Pitner, P.; Riffard, T.
1995-06-01
Some tubes of heat exchangers of nuclear power plants may be affected by Primary Water Stress Corrosion Cracking (PWSCC) in highly stressed areas. These defects can shorten the lifetime of the component and lead to its replacement. In order to reduce the risk of cracking, a preventive remedial operation called shot peening was applied on the French reactors between 1985 and 1988. To assess and investigate the effects of shot peening, a statistical analysis was carried on the tube degradation results obtained from in service inspection that are regularly conducted using non destructive tests. The statistical method used is based on the Cox proportional hazards model, a powerful tool in the analysis of survival data, implemented in PROC PHRED recently available in SAS/STAT. This technique has a number of major advantages including the ability to deal with censored failure times data and with the complication of time-dependant co-variables. The paper focus on the modelling and a presentation of the results given by SAS. They provide estimate of how the relative risk of degradation changes after peening and indicate for which values of the prognostic factors analyzed the treatment is likely to be most beneficial. (authors). 2 refs., 3 figs., 6 tabs
Infrared and millimeter waves v.14 millimeter components and techniques, pt.V
Button, Kenneth J
1985-01-01
Infrared and Millimeter Waves, Volume 14: Millimeter Components and Techniques, Part V is concerned with millimeter-wave guided propagation and integrated circuits. In addition to millimeter-wave planar integrated circuits and subsystems, this book covers transducer configurations and integrated-circuit techniques, antenna arrays, optoelectronic devices, and tunable gyrotrons. Millimeter-wave gallium arsenide (GaAs) IMPATT diodes are also discussed. This monograph is comprised of six chapters and begins with a description of millimeter-wave integrated-circuit transducers, focusing on vario
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.
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
Technique for ultrasonic testing of austenitic steel weldments of NPP components
International Nuclear Information System (INIS)
Lantukh, V.M.; Grebennik, V.S.; Kordinov, E.V.; Kesler, N.A.; Shchedrin, I.F.
1987-01-01
Special literature on ultrasonic testing of weldments of austenitic steel is analysed. Technique for ultrasonic testing of the ring and longitudinal butt welded joints of NPP components without reinforcing bead removal is described. Special converter design and fabrication practice are described. Results of experimental check of the developed testing technology and its application during NNPs' mounting and operation are presented. Results of ultrasonic and X-ray testing are compared
International Nuclear Information System (INIS)
Hino, Takehisa; Tamura, Masataka; Tanaka, Yoshimi; Kouno, Wataru; Makino, Yoshinobu; Kawano, Shohei; Matsunaga, Keiji
2009-01-01
Stress corrosion cracking (SCC) has been reported at the aged components in many nuclear power plants. Toshiba has been developing the underwater laser welding. This welding technique can be conducted without draining the water in the reactor vessel. It is beneficial for workers not to exposure the radiation. The welding speed can be attaining twice as fast as that of Gas Tungsten Arc Welding (GTAW). The susceptibility of SCC can also be lower than the Alloy 600 base metal. (author)
X-ray fluorescence beamline at LNLS: components and some associated techniques
International Nuclear Information System (INIS)
Perez, CArlos A.; Radtke, Martin; Perez, Carlos; Tolentino, Helio; Vicentin, Flavio; Sanchez, Hector Jorge; Perez, Roberto D.
1997-01-01
Full text. In this work a general description of the Total Reflection X-Ray Fluorescence (TXRF) and the X-Ray Fluorescence Microprobe (XRFM) is presented. Components, equipment and experimental stations for the x-ray fluorescence beamline are described, regarding to the techniques mentioned above. Results from the simulations of a pair bended mirrors in a Kirkpatrick-Baez configuration, are shown. The simulations were performed with Shadow program. (author)
International Nuclear Information System (INIS)
Nelson, G.C.
1984-01-01
Linear least-squares methods have been used to quantitatively decompose experimental data obtained from surface analytical techniques into its separate components. The mathematical procedure for accomplishing this is described and examples are given of the use of this method with data obtained from Auger electron spectroscopy [both N(E) and derivative], x-ray photoelectron spectroscopy, and low energy ion scattering spectroscopy. The requirements on the quality of the data are discussed
Key components of financial-analysis education for clinical nurses.
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.
A technique of including the effect of aging of passive components in probabilistic risk assessments
International Nuclear Information System (INIS)
Phillips, J.H.; Weidenhamer, G.H.
1992-01-01
The probabilistic risk assessments (PRAS) being developed at most nuclear power plants to calculate the risk of core damage generally focus on the possible failure of active components. The possible failure of passive components is given little consideration. We are developing methods for selecting risk-significant passive components and including them in PRAS. These methods provide effective ways to prioritize passive components for inspection, and where inspection reveals aging damage, mitigation or repair can be employed to reduce the likelihood of component failure. We demonstrated a method by selecting a weld in the auxiliary feedwater (AFW) system, basing our selection on expert judgement of the likelihood of failure and on an estimate of the consequence of component failure to plant safety. We then modified and used the Piping Reliability Analysis Including Seismic Events (PRAISE) computer code to perform a probabilistic structural analysis to calculate the probability that crack growth due to aging would cause the weld to fail. The PRAISE code was modified to include the effects of changing design material properties with age and changing stress cycles. The calculation included the effects of mechanical loads and thermal transients typical of the service loads for this piping design and the effects of thermal cycling caused by a leaking check valve. However, this particular calculation showed little change in low component failure probability and plant risk for 48 years of service. However, sensitivity studies showed that if the probability of component failure is high, the effect on plant risk is significant. The success of this demonstration shows that this method could be applied to nuclear power plants. The demonstration showed the method is too involved (PRAISE takes a long time to perform the calculation and the input information is extensive) for handling a large number of passive components and therefore simpler methods are needed
Techniques to extract physical modes in model-independent analysis of rings
International Nuclear Information System (INIS)
Wang, C.-X.
2004-01-01
A basic goal of Model-Independent Analysis is to extract the physical modes underlying the beam histories collected at a large number of beam position monitors so that beam dynamics and machine properties can be deduced independent of specific machine models. Here we discuss techniques to achieve this goal, especially the Principal Component Analysis and the Independent Component Analysis.
Gold analysis by the gamma absorption technique
International Nuclear Information System (INIS)
Kurtoglu, Arzu; Tugrul, A.B.
2003-01-01
Gold (Au) analyses are generally performed using destructive techniques. In this study, the Gamma Absorption Technique has been employed for gold analysis. A series of different gold alloys of known gold content were analysed and a calibration curve was obtained. This curve was then used for the analysis of unknown samples. Gold analyses can be made non-destructively, easily and quickly by the gamma absorption technique. The mass attenuation coefficients of the alloys were measured around the K-shell absorption edge of Au. Theoretical mass attenuation coefficient values were obtained using the WinXCom program and comparison of the experimental results with the theoretical values showed generally good and acceptable agreement
Sensitivity analysis of hybrid thermoelastic techniques
W.A. Samad; J.M. Considine
2017-01-01
Stress functions have been used as a complementary tool to support experimental techniques, such as thermoelastic stress analysis (TSA) and digital image correlation (DIC), in an effort to evaluate the complete and separate full-field stresses of loaded structures. The need for such coupling between experimental data and stress functions is due to the fact that...
Energy Technology Data Exchange (ETDEWEB)
Schneider, E.; Kern, R.; Theiner, W.A. [Fraunhofer Inst. fuer Zerstoerungsfreie Pruefverfahren, IZFP, Saarbruecken (Germany)
1999-08-01
The electromagnetic and ultrasonic techniques are comparably recent NDT methods for determination of stress states of components. They are simple in application, but require pre-measurement preparation: Electromagnetic techniques need calibration, and quantitative stress analysis by ultrasonic techniques needs reference values, i.e. verified materials-specific quantities to be obtained with representative specimens. Electromagnetic and ultrasonic techniques have been developed for specific tests at defined components, and the corresponding instruments and sensors have been used in practice for several years now. The paper summarizes fundamental aspects and explains the state of the art by means of several examples. (orig./CB) [Deutsch] Elektromagnetische und Ultraschallverfahren sind vergleichsweise neue zerstoerungsfreie Verfahren zur Bestimmung von Eigenspannungen in Bauteilen. Ihre Anwendung ist einfach, setzt aber Vorarbeiten voraus: Elektromagnetische Verfahren muessen kalibriert und zur quantitativen Spannungsanalyse mittels Ultraschallverfahren muessen materialspezifische Kenngroessen an repraesentativen Materialproben ermittelt werden. Elektromagnetische und Ultraschallverfahren sind fuer konkrete Anwendungen an Bauteilen entwickelt, angepasste Geraete und Sensoren seit Jahren in der Nutzung. Der Beitrag fasst die Grundlagen zusammen und stellt den Stand der Technik anhand ausgewaehlter Anwendungen dar. (orig.)
Microextraction sample preparation techniques in biomedical analysis.
Szultka, Malgorzata; Pomastowski, Pawel; Railean-Plugaru, Viorica; Buszewski, Boguslaw
2014-11-01
Biologically active compounds are found in biological samples at relatively low concentration levels. The sample preparation of target compounds from biological, pharmaceutical, environmental, and food matrices is one of the most time-consuming steps in the analytical procedure. The microextraction techniques are dominant. Metabolomic studies also require application of proper analytical technique for the determination of endogenic metabolites present in biological matrix on trace concentration levels. Due to the reproducibility of data, precision, relatively low cost of the appropriate analysis, simplicity of the determination, and the possibility of direct combination of those techniques with other methods (combination types on-line and off-line), they have become the most widespread in routine determinations. Additionally, sample pretreatment procedures have to be more selective, cheap, quick, and environmentally friendly. This review summarizes the current achievements and applications of microextraction techniques. The main aim is to deal with the utilization of different types of sorbents for microextraction and emphasize the use of new synthesized sorbents as well as to bring together studies concerning the systematic approach to method development. This review is dedicated to the description of microextraction techniques and their application in biomedical analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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
CRDM motion analysis using machine learning technique
International Nuclear Information System (INIS)
Nishimura, Takuya; Nakayama, Hiroyuki; Saitoh, Mayumi; Yaguchi, Seiji
2017-01-01
Magnetic jack type Control Rod Drive Mechanism (CRDM) for pressurized water reactor (PWR) plant operates control rods in response to electrical signals from a reactor control system. CRDM operability is evaluated by quantifying armature's response of closed/opened time which means interval time between coil energizing/de-energizing points and armature closed/opened points. MHI has already developed an automatic CRDM motion analysis and applied it to actual plants so far. However, CRDM operational data has wide variation depending on their characteristics such as plant condition, plant, etc. In the existing motion analysis, there is an issue of analysis accuracy for applying a single analysis technique to all plant conditions, plants, etc. In this study, MHI investigated motion analysis using machine learning (Random Forests) which is flexibly accommodated to CRDM operational data with wide variation, and is improved analysis accuracy. (author)
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
PHOTOGRAMMETRIC TECHNIQUES FOR ROAD SURFACE ANALYSIS
Directory of Open Access Journals (Sweden)
V. A. Knyaz
2016-06-01
Full Text Available The quality and condition of a road surface is of great importance for convenience and safety of driving. So the investigations of the behaviour of road materials in laboratory conditions and monitoring of existing roads are widely fulfilled for controlling a geometric parameters and detecting defects in the road surface. Photogrammetry as accurate non-contact measuring method provides powerful means for solving different tasks in road surface reconstruction and analysis. The range of dimensions concerned in road surface analysis can have great variation from tenths of millimetre to hundreds meters and more. So a set of techniques is needed to meet all requirements of road parameters estimation. Two photogrammetric techniques for road surface analysis are presented: for accurate measuring of road pavement and for road surface reconstruction based on imagery obtained from unmanned aerial vehicle. The first technique uses photogrammetric system based on structured light for fast and accurate surface 3D reconstruction and it allows analysing the characteristics of road texture and monitoring the pavement behaviour. The second technique provides dense 3D model road suitable for road macro parameters estimation.
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)
Detection of cow's milk proteins and minor components in human milk using proteomics techniques.
Coscia, A; Orrù, S; Di Nicola, P; Giuliani, F; Varalda, A; Peila, C; Fabris, C; Conti, A; Bertino, E
2012-10-01
Cow's milk proteins (CMPs) are the best characterized food allergens. The aim of this study was to investigate cow's milk allergens in human colostrum of term and preterm newborns' mothers, and other minor protein components by proteomics techniques, more sensitive than other techniques used in the past. Sixty-two term and 11 preterm colostrum samples were collected, subjected to a treatment able to increase the concentration of the most diluted proteins and simultaneously to reduce the concentration of the proteins present at high concentration (Proteominer Treatment), and subsequently subjected to the steps of proteomic techniques. The most relevant finding in this study was the detection of the intact bovine alpha-S1-casein in human colostrum, then bovine alpha-1-casein could be considered the cow's milk allergen that is readily secreted in human milk and could be a cause of sensitization to cow's milk in exclusively breastfed predisposed infants. Another interesting result was the detection, at very low concentrations, of proteins previously not described in human milk (galectin-7, the different isoforms of the 14-3-3 protein and the serum amyloid P-component), probably involved in the regulation of the normal cell growth, in the pro-apoptotic function and in the regulation of tissue homeostasis. Further investigations are needed to understand if these families of proteins have specific biological activity in human milk.
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...
Principal Component Clustering Approach to Teaching Quality Discriminant Analysis
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…
Diffraction analysis of customized illumination technique
Lim, Chang-Moon; Kim, Seo-Min; Eom, Tae-Seung; Moon, Seung Chan; Shin, Ki S.
2004-05-01
Various enhancement techniques such as alternating PSM, chrome-less phase lithography, double exposure, etc. have been considered as driving forces to lead the production k1 factor towards below 0.35. Among them, a layer specific optimization of illumination mode, so-called customized illumination technique receives deep attentions from lithographers recently. A new approach for illumination customization based on diffraction spectrum analysis is suggested in this paper. Illumination pupil is divided into various diffraction domains by comparing the similarity of the confined diffraction spectrum. Singular imaging property of individual diffraction domain makes it easier to build and understand the customized illumination shape. By comparing the goodness of image in each domain, it was possible to achieve the customized shape of illumination. With the help from this technique, it was found that the layout change would not gives the change in the shape of customized illumination mode.
Eliminating the Influence of Harmonic Components in Operational Modal Analysis
DEFF Research Database (Denmark)
Jacobsen, Niels-Jørgen; Andersen, Palle; Brincker, Rune
2007-01-01
structures, in contrast, are subject inherently to deterministic forces due to the rotating parts in the machinery. These forces are seen as harmonic components in the responses, and their influence should be eliminated before extracting the modes in their vicinity. This paper describes a new method based...... on the well-known Enhanced Frequency Domain Decomposition (EFDD) technique for eliminating these harmonic components in the modal parameter extraction process. For assessing the quality of the method, various experiments were carried out where the results were compared with those obtained with pure stochastic...
Time-domain ultra-wideband radar, sensor and components theory, analysis and design
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...
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.
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)
Fault tree analysis: concepts and techniques
International Nuclear Information System (INIS)
Fussell, J.B.
1976-01-01
Concepts and techniques of fault tree analysis have been developed over the past decade and now predictions from this type analysis are important considerations in the design of many systems such as aircraft, ships and their electronic systems, missiles, and nuclear reactor systems. Routine, hardware-oriented fault tree construction can be automated; however, considerable effort is needed in this area to get the methodology into production status. When this status is achieved, the entire analysis of hardware systems will be automated except for the system definition step. Automated analysis is not undesirable; to the contrary, when verified on adequately complex systems, automated analysis could well become a routine analysis. It could also provide an excellent start for a more in-depth fault tree analysis that includes environmental effects, common mode failure, and human errors. The automated analysis is extremely fast and frees the analyst from the routine hardware-oriented fault tree construction, as well as eliminates logic errors and errors of oversight in this part of the analysis. Automated analysis then affords the analyst a powerful tool to allow his prime efforts to be devoted to unearthing more subtle aspects of the modes of failure of the system
Wieczorek, Piotr; Ligor, Magdalena; Buszewski, Bogusław
Electromigration techniques, including capillary electrophoresis (CE), are widely used for separation and identification of compounds present in food products. These techniques may also be considered as alternate and complementary with respect to commonly used analytical techniques, such as high-performance liquid chromatography (HPLC), or gas chromatography (GC). Applications of CE concern the determination of high-molecular compounds, like polyphenols, including flavonoids, pigments, vitamins, food additives (preservatives, antioxidants, sweeteners, artificial pigments) are presented. Also, the method developed for the determination of proteins and peptides composed of amino acids, which are basic components of food products, are studied. Other substances such as carbohydrates, nucleic acids, biogenic amines, natural toxins, and other contaminations including pesticides and antibiotics are discussed. The possibility of CE application in food control laboratories, where analysis of the composition of food and food products are conducted, is of great importance. CE technique may be used during the control of technological processes in the food industry and for the identification of numerous compounds present in food. Due to the numerous advantages of the CE technique it is successfully used in routine food analysis.
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
Applications of neutron activation analysis technique
International Nuclear Information System (INIS)
Jonah, S. A.
2000-07-01
The technique was developed as far back as 1936 by G. Hevesy and H. Levy for the analysis of Dy using an isotopic source. Approximately 40 elements can be analyzed by instrumental neutron activation analysis (INNA) technique with neutrons from a nuclear reactor. By applying radiochemical separation, the number of elements that can be analysed may be increased to almost 70. Compared with other analytical methods used in environmental and industrial research, NAA has some unique features. These are multi-element capability, rapidity, reproducibility of results, complementarity to other methods, freedom from analytical blank and independency of chemical state of elements. There are several types of neutron sources namely: nuclear reactors, accelerator-based and radioisotope-based sources, but nuclear reactors with high fluxes of neutrons from the fission of 235 U give the most intense irradiation, and hence the highest available sensitivities for NAA. In this paper, the applications of NAA of socio-economic importance are discussed. The benefits of using NAA and related nuclear techniques for on-line applications in industrial process control are highlighted. A brief description of the NAA set-ups at CERT is enumerated. Finally, NAA is compared with other leading analytical techniques
Oluwasuji Dada, Joshua
2014-01-01
The purpose of this paper is to examine the intrinsic relationships among sets of quantity surveyors’ skill and competence variables with a view to reducing them into principal components. The research adopts a data reduction technique using factor analysis statistical technique. A structured questionnaire was administered among major stakeholders in the Nigerian construction industry. The respondents were asked to give rating, on a 5 point Likert scale, on skills and competencies re...
Li, Xiang; Luo, Ming; Qiu, Ying; Alphones, Arokiaswami; Zhong, Wen-De; Yu, Changyuan; Yang, Qi
2018-02-01
In this paper, channel equalization techniques for coherent optical fiber transmission systems based on independent component analysis (ICA) are reviewed. The principle of ICA for blind source separation is introduced. The ICA based channel equalization after both single-mode fiber and few-mode fiber transmission for single-carrier and orthogonal frequency division multiplexing (OFDM) modulation formats are investigated, respectively. The performance comparisons with conventional channel equalization techniques are discussed.
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
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
Chromatographic Techniques for Rare Earth Elements Analysis
Chen, Beibei; He, Man; Zhang, Huashan; Jiang, Zucheng; Hu, Bin
2017-04-01
The present capability of rare earth element (REE) analysis has been achieved by the development of two instrumental techniques. The efficiency of spectroscopic methods was extraordinarily improved for the detection and determination of REE traces in various materials. On the other hand, the determination of REEs very often depends on the preconcentration and separation of REEs, and chromatographic techniques are very powerful tools for the separation of REEs. By coupling with sensitive detectors, many ambitious analytical tasks can be fulfilled. Liquid chromatography is the most widely used technique. Different combinations of stationary phases and mobile phases could be used in ion exchange chromatography, ion chromatography, ion-pair reverse-phase chromatography and some other techniques. The application of gas chromatography is limited because only volatile compounds of REEs can be separated. Thin-layer and paper chromatography are techniques that cannot be directly coupled with suitable detectors, which limit their applications. For special demands, separations can be performed by capillary electrophoresis, which has very high separation efficiency.
Infrared and millimeter waves v.15 millimeter components and techniques, pt.VI
Button, Kenneth J
1986-01-01
Infrared and Millimeter Waves, Volume 15: Millimeter Components and Techniques, Part VI is concerned with millimeter-wave guided propagation and integrated circuits. This book covers low-noise receiver technology for near-millimeter wavelengths; dielectric image-line antennas; EHF satellite communications (SATCOM) terminal antennas; and semiconductor antennas for millimeter-wave integrated circuits. A scanning airborne radiometer for 30 and 90 GHz and a self-oscillating mixer are also described. This monograph is comprised of six chapters and begins with a discussion on the design of low-n
Artificial Intelligence techniques for big data analysis
Aditya Khatri
2017-01-01
During my stay in Salamanca (Spain), I was fortunate enough to participate in the BISITE Research Group of the University of Salamanca. The University of Salamanca is the oldest university in Spain and in 2018 it celebrates its 8th centenary. As a computer science researcher, I participated in one of the many international projects that the research group has active, especially in big data analysis using Artificial Intelligence (AI) techniques. AI is one of BISITE's main lines of rese...
Dong, Wenjiang; Hu, Rongsuo; Chu, Zhong; Zhao, Jianping; Tan, Lehe
2017-11-01
This study investigated the effect of different drying techniques, namely, room-temperature drying (RTD), solar drying (SD), heat-pump drying (HPD), hot-air drying (HAD), and freeze drying (FD), on bioactive components, fatty acid composition, and the volatile compound profile of robusta coffee beans. The data showed that FD was an effective method to preserve fat, organic acids, and monounsaturated fatty acids. In contrast, HAD was ideal for retaining polyunsaturated fatty acids and amino acids. Sixty-two volatile compounds were identified in the differently dried coffee beans, representing 90% of the volatile compounds. HPD of the coffee beans produced the largest number of volatiles, whereas FD resulted in the highest volatile content. A principal component analysis demonstrated a close relationship between the HPD, SD, and RTD methods whereas the FD and HAD methods were significantly different. Overall, the results provide a basis for potential application to other similar thermal sensitive materials. Copyright © 2017 Elsevier Ltd. All rights reserved.
Analysis of Thermo-Mechanical Distortions in Sliding Components : An ALE Approach
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
An RFI Detection Algorithm for Microwave Radiometers Using Sparse Component Analysis
Mohammed-Tano, Priscilla N.; Korde-Patel, Asmita; Gholian, Armen; Piepmeier, Jeffrey R.; Schoenwald, Adam; Bradley, Damon
2017-01-01
Radio Frequency Interference (RFI) is a threat to passive microwave measurements and if undetected, can corrupt science retrievals. The sparse component analysis (SCA) for blind source separation has been investigated to detect RFI in microwave radiometer data. Various techniques using SCA have been simulated to determine detection performance with continuous wave (CW) RFI.
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
Infusing Reliability Techniques into Software Safety Analysis
Shi, Ying
2015-01-01
Software safety analysis for a large software intensive system is always a challenge. Software safety practitioners need to ensure that software related hazards are completely identified, controlled, and tracked. This paper discusses in detail how to incorporate the traditional reliability techniques into the entire software safety analysis process. In addition, this paper addresses how information can be effectively shared between the various practitioners involved in the software safety analyses. The author has successfully applied the approach to several aerospace applications. Examples are provided to illustrate the key steps of the proposed approach.
The development of human behavior analysis techniques
International Nuclear Information System (INIS)
Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang.
1997-07-01
In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator's physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs
The development of human behavior analysis techniques
Energy Technology Data Exchange (ETDEWEB)
Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang
1997-07-01
In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator`s physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs.
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...
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
Characterization of decommissioned reactor internals: Monte Carlo analysis technique
International Nuclear Information System (INIS)
Reid, B.D.; Love, E.F.; Luksic, A.T.
1993-03-01
This study discusses computer analysis techniques for determining activation levels of irradiated reactor component hardware to yield data for the Department of Energy's Greater-Than-Class C Low-Level Radioactive Waste Program. The study recommends the Monte Carlo Neutron/Photon (MCNP) computer code as the best analysis tool for this application and compares the technique to direct sampling methodology. To implement the MCNP analysis, a computer model would be developed to reflect the geometry, material composition, and power history of an existing shutdown reactor. MCNP analysis would then be performed using the computer model, and the results would be validated by comparison to laboratory analysis results from samples taken from the shutdown reactor. The report estimates uncertainties for each step of the computational and laboratory analyses; the overall uncertainty of the MCNP results is projected to be ±35%. The primary source of uncertainty is identified as the material composition of the components, and research is suggested to address that uncertainty
Nucelar reactor seismic safety analysis techniques
International Nuclear Information System (INIS)
Cummings, G.E.; Wells, J.E.; Lewis, L.C.
1979-04-01
In order to provide insights into the seismic safety requirements for nuclear power plants, a probabilistic based systems model and computational procedure have been developed. This model and computational procedure will be used to identify where data and modeling uncertainties need to be decreased by studying the effect of these uncertainties on the probability of radioactive release and the probability of failure of various structures, systems, and components. From the estimates of failure and release probabilities and their uncertainties the most sensitive steps in the seismic methodologies can be identified. In addition, the procedure will measure the uncertainty due to random occurrences, e.g. seismic event probabilities, material property variability, etc. The paper discusses the elements of this systems model and computational procedure, the event-tree/fault-tree development, and the statistical techniques to be employed
Automatic ECG analysis using principal component analysis and wavelet transformation
Khawaja, Antoun
2007-01-01
The main objective of this book is to analyse and detect small changes in ECG waves and complexes that indicate cardiac diseases and disorders. Detecting predisposition to Torsade de Points (TDP) by analysing the beat-to-beat variability in T wave morphology is the main core of this work. The second main topic is detecting small changes in QRS complex and predicting future QRS complexes of patients. Moreover, the last main topic is clustering similar ECG components in different groups.
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
Non-destructive test of lock actuator component using neutron radiography technique
International Nuclear Information System (INIS)
Juliyanti; Setiawan; Sutiarso
2012-01-01
Non-destructive test of lock actuator using neutron radiography technique has been done. The lock actuator is a mechanical system which is controlled by central lock module consisting of electronic circuit which drives the lock actuator works accordingly to open and lock the vehicle door. The non-destructive test using neutron radiography is carried out to identify the type of defect is presence by comparing between the broken and the brand new one. The method used to test the lock actuator component is film method (direct method). The result show that the radiography procedure has complied with the ASTM standard for neutron radiography with background density of 2.2, 7 lines and 3 holes was seen in the sensitivity indicator (SI) and the quite good image quality was obtained. In the brand new actuator is seen that isolator part which separated the coils has melted. By this non-destructive test using neutron radiography technique is able to detect in early stage the type of component's defect inside the lock actuator without to dismantle it. (author)
A new analysis technique for microsamples
International Nuclear Information System (INIS)
Boyer, R.; Journoux, J.P.; Duval, C.
1989-01-01
For many decades, isotopic analysis of Uranium or Plutonium has been performed by mass spectrometry. The most recent analytical techniques, using the counting method or a plasma torch combined with a mass spectrometer (ICP.MS) have not yet to reach a greater degree of precision than the older methods in this field. The two means of ionization for isotopic analysis - by electronic bombardment of atoms or molecules (source of gas ions) and - by thermal effect (thermoionic source) are compared revealing some inconsistency between the quantity of sample necessary for analysis and the luminosity. In fact, the quantity of sample necessary for the gas source mass spectrometer is 10 to 20 times greater than that for the thermoionization spectrometer, while the sample consumption is between 10 5 to 10 6 times greater. This proves that almost the entire sample is not necessary for the measurement; it is only required because of the system of introduction for the gas spectrometer. The new analysis technique referred to as ''Microfluorination'' corrects this anomaly and exploits the advantages of the electron bombardment method of ionization
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...
Flash Infrared Thermography Contrast Data Analysis Technique
Koshti, Ajay
2014-01-01
This paper provides information on an IR Contrast technique that involves extracting normalized contrast versus time evolutions from the flash thermography inspection infrared video data. The analysis calculates thermal measurement features from the contrast evolution. In addition, simulation of the contrast evolution is achieved through calibration on measured contrast evolutions from many flat-bottom holes in the subject material. The measurement features and the contrast simulation are used to evaluate flash thermography data in order to characterize delamination-like anomalies. The thermal measurement features relate to the anomaly characteristics. The contrast evolution simulation is matched to the measured contrast evolution over an anomaly to provide an assessment of the anomaly depth and width which correspond to the depth and diameter of the equivalent flat-bottom hole (EFBH) similar to that used as input to the simulation. A similar analysis, in terms of diameter and depth of an equivalent uniform gap (EUG) providing a best match with the measured contrast evolution, is also provided. An edge detection technique called the half-max is used to measure width and length of the anomaly. Results of the half-max width and the EFBH/EUG diameter are compared to evaluate the anomaly. The information provided here is geared towards explaining the IR Contrast technique. Results from a limited amount of validation data on reinforced carbon-carbon (RCC) hardware are included in this paper.
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...
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.)
Eddy current technique for detecting and sizing surface cracks in steel components
International Nuclear Information System (INIS)
Cecco, V.S.; Carter, J.R.; Sullivan, S.P.
1995-01-01
Cracking has occurred in pressure vessel nozzles and girth welds due to thermal fatigue. Pipe welds, welds in support structures, and welds in reactor vault liner panels in nuclear facilities have failed because of cracks. Cracking can also occur in turbine rotor bore surfaces due to high cycle fatigue. Dye penetrant, magnetic particle and other surface NDT methods are used to detect cracks but cannot be used for depth sizing. Crack depth can be measured with various NDT methods such as ultrasonic time-of-flight diffraction (TOFD), potential drop, and eddy current. The TOFD technique can be difficult to implement on nozzle welds and is best suited for sizing deep cracks (>5 mm). The conventional eddy current method is easy to implement, but crack sizing is normally limited to shallow cracks ( 2 mm) cracks. Eddy current testing (ET) techniques are readily amenable to remote/automatic inspections. These new probes could augment present magnetic particle (MT) and dye penetrant (PT) testing through provision of reliable defect depth information. Reliable crack sizing permits identification of critical cracks for plant life extension and licensing purposes. In addition, performing PT and MT generates low level radioactive waste in some inspection applications in nuclear facilities. Replacing these techniques with ET for some components will eliminate some of this radioactive waste. (author)
Design and Fabrication Technique of the Key Components for Very High Temperature Reactor
Energy Technology Data Exchange (ETDEWEB)
Lee, Ho Jin; Song, Ki Nam; Kim, Yong Wan
2006-12-15
The gas outlet temperature of Very High Temperature Reactor (VHTR) may be beyond the capability of conventional metallic materials. The requirement of the gas outlet temperature of 950 .deg. C will result in operating temperatures for metallic core components that will approach very high temperature on some cases. The materials that are capable of withstanding this temperature should be prepared, or nonmetallic materials will be required for limited components. The Ni-base alloys such as Alloy 617, Hastelloy X, XR, Incoloy 800H, and Haynes 230 are being investigated to apply them on components operated in high temperature. Currently available national and international codes and procedures are needed reviewed to design the components for HTGR/VHTR. Seven codes and procedures, including five ASME Codes and Code cases, one French code (RCC-MR), and on British Procedure (R5) were reviewed. The scope of the code and code cases needs to be expanded to include the materials with allowable temperatures of 950 .deg. C and higher. The selection of compact heat exchangers technology depends on the operating conditions such as pressure, flow rates, temperature, but also on other parameters such as fouling, corrosion, compactness, weight, maintenance and reliability. Welding, brazing, and diffusion bonding are considered proper joining processes for the heat exchanger operating in the high temperature and high pressure conditions without leakage. Because VHTRs require high temperature operations, various controlled materials, thick vessels, dissimilar metal joints, and precise controls of microstructure in weldment, the more advanced joining processes are needed than PWRs. The improved solid joining techniques are considered for the IHX fabrication. The weldability for Alloy 617 and Haynes 230 using GTAW and SMAW processes was investigated by CEA.
Design and Fabrication Technique of the Key Components for Very High Temperature Reactor
International Nuclear Information System (INIS)
Lee, Ho Jin; Song, Ki Nam; Kim, Yong Wan
2006-12-01
The gas outlet temperature of Very High Temperature Reactor (VHTR) may be beyond the capability of conventional metallic materials. The requirement of the gas outlet temperature of 950 .deg. C will result in operating temperatures for metallic core components that will approach very high temperature on some cases. The materials that are capable of withstanding this temperature should be prepared, or nonmetallic materials will be required for limited components. The Ni-base alloys such as Alloy 617, Hastelloy X, XR, Incoloy 800H, and Haynes 230 are being investigated to apply them on components operated in high temperature. Currently available national and international codes and procedures are needed reviewed to design the components for HTGR/VHTR. Seven codes and procedures, including five ASME Codes and Code cases, one French code (RCC-MR), and on British Procedure (R5) were reviewed. The scope of the code and code cases needs to be expanded to include the materials with allowable temperatures of 950 .deg. C and higher. The selection of compact heat exchangers technology depends on the operating conditions such as pressure, flow rates, temperature, but also on other parameters such as fouling, corrosion, compactness, weight, maintenance and reliability. Welding, brazing, and diffusion bonding are considered proper joining processes for the heat exchanger operating in the high temperature and high pressure conditions without leakage. Because VHTRs require high temperature operations, various controlled materials, thick vessels, dissimilar metal joints, and precise controls of microstructure in weldment, the more advanced joining processes are needed than PWRs. The improved solid joining techniques are considered for the IHX fabrication. The weldability for Alloy 617 and Haynes 230 using GTAW and SMAW processes was investigated by CEA
Reliability analysis techniques for the design engineer
International Nuclear Information System (INIS)
Corran, E.R.; Witt, H.H.
1980-01-01
A fault tree analysis package is described that eliminates most of the housekeeping tasks involved in proceeding from the initial construction of a fault tree to the final stage of presenting a reliability analysis in a safety report. It is suitable for designers with relatively little training in reliability analysis and computer operation. Users can rapidly investigate the reliability implications of various options at the design stage, and evolve a system which meets specified reliability objectives. Later independent review is thus unlikely to reveal major shortcomings necessitating modification and projects delays. The package operates interactively allowing the user to concentrate on the creative task of developing the system fault tree, which may be modified and displayed graphically. For preliminary analysis system data can be derived automatically from a generic data bank. As the analysis procedes improved estimates of critical failure rates and test and maintenance schedules can be inserted. The computations are standard, - identification of minimal cut-sets, estimation of reliability parameters, and ranking of the effect of the individual component failure modes and system failure modes on these parameters. The user can vary the fault trees and data on-line, and print selected data for preferred systems in a form suitable for inclusion in safety reports. A case history is given - that of HIFAR containment isolation system. (author)
Reliability analysis techniques for the design engineer
International Nuclear Information System (INIS)
Corran, E.R.; Witt, H.H.
1982-01-01
This paper describes a fault tree analysis package that eliminates most of the housekeeping tasks involved in proceeding from the initial construction of a fault tree to the final stage of presenting a reliability analysis in a safety report. It is suitable for designers with relatively little training in reliability analysis and computer operation. Users can rapidly investigate the reliability implications of various options at the design stage and evolve a system which meets specified reliability objectives. Later independent review is thus unlikely to reveal major shortcomings necessitating modification and project delays. The package operates interactively, allowing the user to concentrate on the creative task of developing the system fault tree, which may be modified and displayed graphically. For preliminary analysis, system data can be derived automatically from a generic data bank. As the analysis proceeds, improved estimates of critical failure rates and test and maintenance schedules can be inserted. The technique is applied to the reliability analysis of the recently upgraded HIFAR Containment Isolation System. (author)
The analysis of multivariate group differences using common principal components
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
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...
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....
Principal component analysis of image gradient orientations for face recognition
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
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....
Principal component analysis of NEXAFS spectra for molybdenum speciation in hydrotreating catalysts
International Nuclear Information System (INIS)
Faro Junior, Arnaldo da C.; Rodrigues, Victor de O.; Eon, Jean-G.; Rocha, Angela S.
2010-01-01
Bulk and supported molybdenum based catalysts, modified by nickel, phosphorous or tungsten were studied by NEXAFS spectroscopy at the Mo L III and L II edges. The techniques of principal component analysis (PCA) together with a linear combination analysis (LCA) allowed the detection and quantification of molybdenum atoms in two different coordination states in the oxide form of the catalysts, namely tetrahedral and octahedral coordination. (author)
Interferogram analysis using the Abel inversion technique
International Nuclear Information System (INIS)
Yusof Munajat; Mohamad Kadim Suaidi
2000-01-01
High speed and high resolution optical detection system were used to capture the image of acoustic waves propagation. The freeze image in the form of interferogram was analysed to calculate the transient pressure profile of the acoustic waves. The interferogram analysis was based on the fringe shift and the application of the Abel inversion technique. An easier approach was made by mean of using MathCAD program as a tool in the programming; yet powerful enough to make such calculation, plotting and transfer of file. (Author)
Directory of Open Access Journals (Sweden)
Khuat Thanh Tung
2016-11-01
Full Text Available Optical Character Recognition plays an important role in data storage and data mining when the number of documents stored as images is increasing. It is expected to find the ways to convert images of typewritten or printed text into machine-encoded text effectively in order to support for the process of information handling effectively. In this paper, therefore, the techniques which are being used to convert image into editable text in the computer such as principal component analysis, multilayer perceptron network, self-organizing maps, and improved multilayer neural network using principal component analysis are experimented. The obtained results indicated the effectiveness and feasibility of the proposed methods.
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.
Experimental modal analysis of components of the LHC experiments
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.
Low energy analysis techniques for CUORE
Energy Technology Data Exchange (ETDEWEB)
Alduino, C.; Avignone, F.T.; Chott, N.; Creswick, R.J.; Rosenfeld, C.; Wilson, J. [University of South Carolina, Department of Physics and Astronomy, Columbia, SC (United States); Alfonso, K.; Huang, H.Z.; Sakai, M.; Schmidt, J. [University of California, Department of Physics and Astronomy, Los Angeles, CA (United States); Artusa, D.R.; Rusconi, C. [University of South Carolina, Department of Physics and Astronomy, Columbia, SC (United States); INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); Azzolini, O.; Camacho, A.; Keppel, G.; Palmieri, V.; Pira, C. [INFN-Laboratori Nazionali di Legnaro, Padua (Italy); Bari, G.; Deninno, M.M. [INFN-Sezione di Bologna, Bologna (Italy); Beeman, J.W. [Lawrence Berkeley National Laboratory, Materials Science Division, Berkeley, CA (United States); Bellini, F.; Cosmelli, C.; Ferroni, F.; Piperno, G. [Sapienza Universita di Roma, Dipartimento di Fisica, Rome (Italy); INFN-Sezione di Roma, Rome (Italy); Benato, G.; Singh, V. [University of California, Department of Physics, Berkeley, CA (United States); Bersani, A.; Caminata, A. [INFN-Sezione di Genova, Genoa (Italy); Biassoni, M.; Brofferio, C.; Capelli, S.; Carniti, P.; Cassina, L.; Chiesa, D.; Clemenza, M.; Faverzani, M.; Fiorini, E.; Gironi, L.; Gotti, C.; Maino, M.; Nastasi, M.; Nucciotti, A.; Pavan, M.; Pozzi, S.; Sisti, M.; Terranova, F.; Zanotti, L. [Universita di Milano-Bicocca, Dipartimento di Fisica, Milan (Italy); INFN-Sezione di Milano Bicocca, Milan (Italy); Branca, A.; Taffarello, L. [INFN-Sezione di Padova, Padua (Italy); Bucci, C.; Cappelli, L.; D' Addabbo, A.; Gorla, P.; Pattavina, L.; Pirro, S. [INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); Canonica, L. [INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); Massachusetts Institute of Technology, Cambridge, MA (United States); Cao, X.G.; Fang, D.Q.; Ma, Y.G.; Wang, H.W.; Zhang, G.Q. [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai (China); Cardani, L.; Casali, N.; Dafinei, I.; Morganti, S.; Mosteiro, P.J.; Tomei, C.; Vignati, M. [INFN-Sezione di Roma, Rome (Italy); Copello, S.; Di Domizio, S.; Marini, L.; Pallavicini, M. [INFN-Sezione di Genova, Genoa (Italy); Universita di Genova, Dipartimento di Fisica, Genoa (Italy); Cremonesi, O.; Ferri, E.; Giachero, A.; Pessina, G.; Previtali, E. [INFN-Sezione di Milano Bicocca, Milan (Italy); Cushman, J.S.; Davis, C.J.; Heeger, K.M.; Lim, K.E.; Maruyama, R.H. [Yale University, Department of Physics, New Haven, CT (United States); D' Aguanno, D.; Pagliarone, C.E. [INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); Universita degli Studi di Cassino e del Lazio Meridionale, Dipartimento di Ingegneria Civile e Meccanica, Cassino (Italy); Dell' Oro, S. [INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); INFN-Gran Sasso Science Institute, L' Aquila (Italy); Di Vacri, M.L.; Santone, D. [INFN-Laboratori Nazionali del Gran Sasso, L' Aquila (Italy); Universita dell' Aquila, Dipartimento di Scienze Fisiche e Chimiche, L' Aquila (Italy); Drobizhev, A.; Hennings-Yeomans, R.; Kolomensky, Yu.G.; Wagaarachchi, S.L. [University of California, Department of Physics, Berkeley, CA (United States); Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, CA (United States); Franceschi, M.A.; Ligi, C.; Napolitano, T. [INFN-Laboratori Nazionali di Frascati, Rome (Italy); Freedman, S.J. [University of California, Department of Physics, Berkeley, CA (United States); Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, CA (United States); Fujikawa, B.K.; Mei, Y.; Schmidt, B.; Smith, A.R.; Welliver, B. [Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, CA (United States); Giuliani, A.; Novati, V. [Universite Paris-Saclay, CSNSM, Univ. Paris-Sud, CNRS/IN2P3, Orsay (France); Gladstone, L.; Leder, A.; Ouellet, J.L.; Winslow, L.A. [Massachusetts Institute of Technology, Cambridge, MA (United States); Gutierrez, T.D. [California Polytechnic State University, Physics Department, San Luis Obispo, CA (United States); Haller, E.E. [Lawrence Berkeley National Laboratory, Materials Science Division, Berkeley, CA (United States); University of California, Department of Materials Science and Engineering, Berkeley, CA (United States); Han, K. [Shanghai Jiao Tong University, Department of Physics and Astronomy, Shanghai (China); Hansen, E. [University of California, Department of Physics and Astronomy, Los Angeles, CA (United States); Massachusetts Institute of Technology, Cambridge, MA (United States); Kadel, R. [Lawrence Berkeley National Laboratory, Physics Division, Berkeley, CA (United States); Martinez, M. [Sapienza Universita di Roma, Dipartimento di Fisica, Rome (Italy); INFN-Sezione di Roma, Rome (Italy); Universidad de Zaragoza, Laboratorio de Fisica Nuclear y Astroparticulas, Saragossa (Spain); Moggi, N.; Zucchelli, S. [INFN-Sezione di Bologna, Bologna (Italy); Universita di Bologna - Alma Mater Studiorum, Dipartimento di Fisica e Astronomia, Bologna (IT); Nones, C. [CEA/Saclay, Service de Physique des Particules, Gif-sur-Yvette (FR); Norman, E.B.; Wang, B.S. [Lawrence Livermore National Laboratory, Livermore, CA (US); University of California, Department of Nuclear Engineering, Berkeley, CA (US); O' Donnell, T. [Virginia Polytechnic Institute and State University, Center for Neutrino Physics, Blacksburg, VA (US); Sangiorgio, S.; Scielzo, N.D. [Lawrence Livermore National Laboratory, Livermore, CA (US); Wise, T. [Yale University, Department of Physics, New Haven, CT (US); University of Wisconsin, Department of Physics, Madison, WI (US); Woodcraft, A. [University of Edinburgh, SUPA, Institute for Astronomy, Edinburgh (GB); Zimmermann, S. [Lawrence Berkeley National Laboratory, Engineering Division, Berkeley, CA (US)
2017-12-15
CUORE is a tonne-scale cryogenic detector operating at the Laboratori Nazionali del Gran Sasso (LNGS) that uses tellurium dioxide bolometers to search for neutrinoless double-beta decay of {sup 130}Te. CUORE is also suitable to search for low energy rare events such as solar axions or WIMP scattering, thanks to its ultra-low background and large target mass. However, to conduct such sensitive searches requires improving the energy threshold to 10 keV. In this paper, we describe the analysis techniques developed for the low energy analysis of CUORE-like detectors, using the data acquired from November 2013 to March 2015 by CUORE-0, a single-tower prototype designed to validate the assembly procedure and new cleaning techniques of CUORE. We explain the energy threshold optimization, continuous monitoring of the trigger efficiency, data and event selection, and energy calibration at low energies in detail. We also present the low energy background spectrum of CUORE-0 below 60 keV. Finally, we report the sensitivity of CUORE to WIMP annual modulation using the CUORE-0 energy threshold and background, as well as an estimate of the uncertainty on the nuclear quenching factor from nuclear recoils in CUORE-0. (orig.)
Machine monitoring via current signature analysis techniques
International Nuclear Information System (INIS)
Smith, S.F.; Castleberry, K.N.; Nowlin, C.H.
1992-01-01
A significant need in the effort to provide increased production quality is to provide improved plant equipment monitoring capabilities. Unfortunately, in today's tight economy, even such monitoring instrumentation must be implemented in a recognizably cost effective manner. By analyzing the electric current drawn by motors, actuator, and other line-powered industrial equipment, significant insights into the operations of the movers, driven equipment, and even the power source can be obtained. The generic term 'current signature analysis' (CSA) has been coined to describe several techniques for extracting useful equipment or process monitoring information from the electrical power feed system. A patented method developed at Oak Ridge National Laboratory is described which recognizes the presence of line-current modulation produced by motors and actuators driving varying loads. The in-situ application of applicable linear demodulation techniques to the analysis of numerous motor-driven systems is also discussed. The use of high-quality amplitude and angle-demodulation circuitry has permitted remote status monitoring of several types of medium and high-power gas compressors in (US DOE facilities) driven by 3-phase induction motors rated from 100 to 3,500 hp, both with and without intervening speed increasers. Flow characteristics of the compressors, including various forms of abnormal behavior such as surging and rotating stall, produce at the output of the specialized detectors specific time and frequency signatures which can be easily identified for monitoring, control, and fault-prevention purposes. The resultant data are similar in form to information obtained via standard vibration-sensing techniques and can be analyzed using essentially identical methods. In addition, other machinery such as refrigeration compressors, brine pumps, vacuum pumps, fans, and electric motors have been characterized
International Nuclear Information System (INIS)
Souza, V.E.S.; Masieiro, F.R.S.; Lourenco, J.M.; Felipe, R.C.T.S.
2009-01-01
Full text: The powder metallurgy process consists to produce metallic or ceramic components through pressure in a powder mass. These components will be submitted to a sintering temperature in order to consolidate them and then improve their mechanical proprieties. The industry is responsible for the swarf generation from different manufacture process. This paper has main goal the reutilization of aluminum and steel swarf using the powder metallurgy as technique. The methodology used in this work consists to compact Al 6060 plus steel SAE 1045 as reinforce material at 250MPa, 400MPa and 600MPa. The composition about these compacted will be 30%, 40%, 50% of steel into aluminum matrix. In this way will be analyze the hardness as function of the compressibility and quantity of steel. The samples will be processed at 500°C during 45 minutes using a resistive furnace in a hydrogen atmosphere. Micrographs of the sintered samples will be obtained by using a Scanning Electron Microscope and Optic Microscope. X-rays diffraction will be also used to characterize the phases found to due diffusivity between the steel and aluminum. (author)
Integrity evaluation of power plant components by fracture mechanics and related techniques
International Nuclear Information System (INIS)
Mukherjee, B.; Vanderglas, M.L.; Davies, P.H.
1982-01-01
Power plant components can be subject to unexpected failures with serious consequences, unless careful attention is paid to minute crack defects and their possible growth. The Linear Elastic Fracture Mechanics approach to structural integrity evaluation, as it appears in the ASME Code, is discussed. Projects related to material data generation and the development of structural analysis methods to make the above method usable are described. Several integrity-related questions outside the scope of the Code guidelines are documented, concluding with comments on possible future developments
Energy Technology Data Exchange (ETDEWEB)
Kim, Youngmoo [Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Agency for Defense Development, Yuseong, P.O. Box 35, Yuseong-gu, Daejeon 34186, Republic of Korea. (Korea, Republic of); Lee, Dongju [Korea Atomic Energy Research Institute, 111 Daedeok-daero, Yuseong-gu, Daejeon 34057 (Korea, Republic of); Hwang, Jaewon [Samsung Electronics, 129 Samsung-ro, Youngtong-gu, Suwon 16677 (Korea, Republic of); Ryu, Ho Jin, E-mail: hojinryu@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Hong, Soon Hyung, E-mail: shhong@kaist.ac.kr [Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141 (Korea, Republic of)
2016-04-15
The present study has investigated the consolidation behaviors of tantalum powders during compaction and sintering, and the characteristics of sintered components. For die compaction, the densification behaviors of the powders are simulated by finite element analyses based on the yield function proposed by Shima and Oyane. Accordingly, the green density distribution for coarser particles is predicted to be more uniform because they exhibits higher initial relative tap density owing to lower interparticle friction. It is also found that cold isostatic pressing is capable of producing higher dense compacts compared to the die pressing. However, unlike the compaction behavior, the sintered density of smaller particles is found to be higher than those of coarser ones owing to their higher specific surface area. The maximum sintered density was found to be 0.96 of theoretical density where smaller particles were pressed isostatically at 400 MPa followed by sintering at 2000 °C. Moreover, the effects of processing conditions on grain size and texture were also investigated. The average grain size of the sintered specimen is 30.29 μm and its texture is less than 2 times random intensity. Consequently, it is concluded that the higher pressure compaction technique is beneficial to produce high dense and texture-free tantalum components compared to hot pressing and spark plasma sintering. - Highlights: • Higher Ta density is obtained from higher pressure and sintering temperature. • High compaction method enables P/M Ta to achieve the density of 16.00 g·cm{sup −3}. • A P/M Ta component with fine microstructure and random orientation is developed.
Nonlinear Ultrasonic Techniques to Monitor Radiation Damage in RPV and Internal Components
Energy Technology Data Exchange (ETDEWEB)
Jacobs, Laurence [Georgia Inst. of Technology, Atlanta, GA (United States); Kim, Jin-Yeon [Georgia Inst. of Technology, Atlanta, GA (United States); Qu, Jisnmin [Northwestern Univ., Evanston, IL (United States); Ramuhalli, Pradeep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wall, Joe [Electric Power Research Inst. (EPRI), Knoxville, TN (United States)
2015-11-02
The objective of this research is to demonstrate that nonlinear ultrasonics (NLU) can be used to directly and quantitatively measure the remaining life in radiation damaged reactor pressure vessel (RPV) and internal components. Specific damage types to be monitored are irradiation embrittlement and irradiation assisted stress corrosion cracking (IASCC). Our vision is to develop a technique that allows operators to assess damage by making a limited number of NLU measurements in strategically selected critical reactor components during regularly scheduled outages. This measured data can then be used to determine the current condition of these key components, from which remaining useful life can be predicted. Methods to unambiguously characterize radiation related damage in reactor internals and RPVs remain elusive. NLU technology has demonstrated great potential to be used as a material sensor – a sensor that can continuously monitor a material’s damage state. The physical effect being monitored by NLU is the generation of higher harmonic frequencies in an initially monochromatic ultrasonic wave. The degree of nonlinearity is quantified with the acoustic nonlinearity parameter, β, which is an absolute, measurable material constant. Recent research has demonstrated that nonlinear ultrasound can be used to characterize material state and changes in microscale characteristics such as internal stress states, precipitate formation and dislocation densities. Radiation damage reduces the fracture toughness of RPV steels and internals, and can leave them susceptible to IASCC, which may in turn limit the lifetimes of some operating reactors. The ability to characterize radiation damage in the RPV and internals will enable nuclear operators to set operation time thresholds for vessels and prescribe and schedule replacement activities for core internals. Such a capability will allow a more clear definition of reactor safety margins. The research consists of three tasks: (1
Nonlinear Ultrasonic Techniques to Monitor Radiation Damage in RPV and Internal Components
International Nuclear Information System (INIS)
Jacobs, Laurence; Kim, Jin-Yeon; Qu, Jisnmin; Ramuhalli, Pradeep; Wall, Joe
2015-01-01
The objective of this research is to demonstrate that nonlinear ultrasonics (NLU) can be used to directly and quantitatively measure the remaining life in radiation damaged reactor pressure vessel (RPV) and internal components. Specific damage types to be monitored are irradiation embrittlement and irradiation assisted stress corrosion cracking (IASCC). Our vision is to develop a technique that allows operators to assess damage by making a limited number of NLU measurements in strategically selected critical reactor components during regularly scheduled outages. This measured data can then be used to determine the current condition of these key components, from which remaining useful life can be predicted. Methods to unambiguously characterize radiation related damage in reactor internals and RPVs remain elusive. NLU technology has demonstrated great potential to be used as a material sensor - a sensor that can continuously monitor a material's damage state. The physical effect being monitored by NLU is the generation of higher harmonic frequencies in an initially monochromatic ultrasonic wave. The degree of nonlinearity is quantified with the acoustic nonlinearity parameter, β, which is an absolute, measurable material constant. Recent research has demonstrated that nonlinear ultrasound can be used to characterize material state and changes in microscale characteristics such as internal stress states, precipitate formation and dislocation densities. Radiation damage reduces the fracture toughness of RPV steels and internals, and can leave them susceptible to IASCC, which may in turn limit the lifetimes of some operating reactors. The ability to characterize radiation damage in the RPV and internals will enable nuclear operators to set operation time thresholds for vessels and prescribe and schedule replacement activities for core internals. Such a capability will allow a more clear definition of reactor safety margins. The research consists of three tasks
Sparse logistic principal components analysis for binary data
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.
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.
International Nuclear Information System (INIS)
Waheed, S.; Rahman, S.; Siddique, N.
2013-01-01
Different types of Ca supplements are available in the local markets of Pakistan. It is sometimes difficult to classify these with respect to their composition. In the present work principal component analysis (PCA) technique was applied to classify different Ca supplements on the basis of their elemental data obtained using instrumental neutron activation analysis (INAA) and atomic absorption spectrometry (AAS) techniques. The graphical representation of principal component analysis (PCA) scores utilizing intricate analytical data successfully generated four different types of Ca supplements with compatible samples grouped together. These included Ca supplements with CaCO/sub 3/as Ca source along with vitamin C, the supplements with CaCO/sub 3/ as Ca source along with vitamin D, Supplements with Ca from bone meal and supplements with chelated calcium. (author)
Directory of Open Access Journals (Sweden)
Enrico Mick
2015-07-01
Full Text Available Both titanium and ceramic materials provide specific advantages in dental implant technology. However, some problems, like hypersensitivity reactions, corrosion and mechanical failure, have been reported. Therefore, the combining of both materials to take advantage of their pros, while eliminating their respective cons, would be desirable. Hence, we introduced a new technique to bond titanium and ceramic materials by means of a silica-based glass ceramic solder. Cylindrical compound samples (Ø10 mm × 56 mm made of alumina toughened zirconia (ATZ, as well as titanium grade 5, were bonded by glass solder on their end faces. As a control, a two-component adhesive glue was utilized. The samples were investigated without further treatment, after 30 and 90 days of storage in distilled water at room temperature, and after aging. All samples were subjected to quasi-static four-point-bending tests. We found that the glass solder bonding provided significantly higher bending strength than adhesive glue bonding. In contrast to the glued samples, the bending strength of the soldered samples remained unaltered by the storage and aging treatments. Scanning electron microscopy (SEM and energy-dispersive X-ray (EDX analyses confirmed the presence of a stable solder-ceramic interface. Therefore, the glass solder technique represents a promising method for optimizing dental and orthopedic implant bondings.
Hiramatsu, Yoichi; Ishii, Jun; Funato, Kazuhiro
A significant number of hydraulic turbines operated in Japan were installed in the first half of the 20th century. Today, aging degradation and flaws are observed in these turbine equipments. So far, Japanese engineers have applied NDI technology of Ultrasonic Testing (UT) to detect the flaws, and after empirical evaluation of the remaining life they decided an adequate moment to replace the equipments. Since the replacement requires a large-scale field site works and high-cost, one of the solutions for life-extension of the equipments is introduction of repair services. We have been working in order to enhance the accuracy of results during the detection of flaws and flaws dimensioning, in particular focusing on the techniques of Tip-echo, TOFD and Phased-Array UT, accompanied by the conventional UT. These NDI methods made possible to recognize the entire image of surface and embedded flaws with complicated geometry. Then, we have developed an evaluation system of these flaws based on the theory of crack propagation, of the logic of crack growth driven by the stress-intensity factor of the crack tip front. The sophisticated evaluation system is constituted by a hand-made software and database of stress-intensity factor. Based on these elemental technologies, we propose a technique of repair welding to provide a life-extension of hydraulic turbine components.
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.
Sánchez-Sánchez, M Luz; Belda-Lois, Juan-Manuel; Mena-Del Horno, Silvia; Viosca-Herrero, Enrique; Igual-Camacho, Celedonia; Gisbert-Morant, Beatriz
2018-05-05
A major goal in stroke rehabilitation is the establishment of more effective physical therapy techniques to recover postural stability. Functional Principal Component Analysis provides greater insight into recovery trends. However, when missing values exist, obtaining functional data presents some difficulties. The purpose of this study was to reveal an alternative technique for obtaining the Functional Principal Components without requiring the conversion to functional data beforehand and to investigate this methodology to determine the effect of specific physical therapy techniques in balance recovery trends in elderly subjects with hemiplegia post-stroke. A randomized controlled pilot trial was developed. Thirty inpatients post-stroke were included. Control and target groups were treated with the same conventional physical therapy protocol based on functional criteria, but specific techniques were added to the target group depending on the subjects' functional level. Postural stability during standing was quantified by posturography. The assessments were performed once a month from the moment the participants were able to stand up to six months post-stroke. The target group showed a significant improvement in postural control recovery trend six months after stroke that was not present in the control group. Some of the assessed parameters revealed significant differences between treatment groups (P Functional Principal Component Analysis to be performed when data is scarce. Moreover, it allowed the dynamics of recovery of two different treatment groups to be determined, showing that the techniques added in the target group increased postural stability compared to the base protocol. Copyright © 2018 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Meyer, Ryan M.; Coble, Jamie B.; Hirt, Evelyn H.; Ramuhalli, Pradeep; Mitchell, Mark R.; Wootan, David W.; Berglin, Eric J.; Bond, Leonard J.; Henager, Charles H.
2013-05-17
This report identifies a number of requirements for prognostics health management of passive systems in AdvSMRs, documents technical gaps in establishing a prototypical prognostic methodology for this purpose, and describes a preliminary research plan for addressing these technical gaps. AdvSMRs span multiple concepts; therefore a technology- and design-neutral approach is taken, with the focus being on characteristics that are likely to be common to all or several AdvSMR concepts. An evaluation of available literature is used to identify proposed concepts for AdvSMRs along with likely operational characteristics. Available operating experience of advanced reactors is used in identifying passive components that may be subject to degradation, materials likely to be used for these components, and potential modes of degradation of these components. This information helps in assessing measurement needs for PHM systems, as well as defining functional requirements of PHM systems. An assessment of current state-of-the-art approaches to measurements, sensors and instrumentation, diagnostics and prognostics is also documented. This state-of-the-art evaluation, combined with the requirements, may be used to identify technical gaps and research needs in the development, evaluation, and deployment of PHM systems for AdvSMRs. A preliminary research plan to address high-priority research needs for the deployment of PHM systems to AdvSMRs is described, with the objective being the demonstration of prototypic prognostics technology for passive components in AdvSMRs. Greater efficiency in achieving this objective can be gained through judicious selection of materials and degradation modes that are relevant to proposed AdvSMR concepts, and for which significant knowledge already exists. These selections were made based on multiple constraints including the analysis performed in this document, ready access to laboratory-scale facilities for materials testing and measurement, and
Adler, Ronald S.; Swanson, Scott D.; Yeung, Hong N.
1996-01-01
A projection-operator technique is applied to a general three-component model for magnetization transfer, extending our previous two-component model [R. S. Adler and H. N. Yeung,J. Magn. Reson. A104,321 (1993), and H. N. Yeung, R. S. Adler, and S. D. Swanson,J. Magn. Reson. A106,37 (1994)]. The PO technique provides an elegant means of deriving a simple, effective rate equation in which there is natural separation of relaxation and source terms and allows incorporation of Redfield-Provotorov theory without any additional assumptions or restrictive conditions. The PO technique is extended to incorporate more general, multicomponent models. The three-component model is used to fit experimental data from samples of human hyaline cartilage and fibrocartilage. The fits of the three-component model are compared to the fits of the two-component model.
Optimization benefits analysis in production process of fabrication components
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.
Multi-spectrometer calibration transfer based on independent component analysis.
Liu, Yan; Xu, Hao; Xia, Zhenzhen; Gong, Zhiyong
2018-02-26
Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.
Fault tree technique: advances in probabilistic and logical analysis
International Nuclear Information System (INIS)
Clarotti, C.A.; Amendola, A.; Contini, S.; Squellati, G.
1982-01-01
Fault tree reliability analysis is used for assessing the risk associated to systems of increasing complexity (phased mission systems, systems with multistate components, systems with non-monotonic structure functions). Much care must be taken to make sure that fault tree technique is not used beyond its correct validity range. To this end a critical review of mathematical foundations of reliability fault tree analysis is carried out. Limitations are enlightened and potential solutions to open problems are suggested. Moreover an overview is given on the most recent developments in the implementation of an integrated software (SALP-MP, SALP-NOT, SALP-CAFT Codes) for the analysis of a wide class of systems
Reliability Analysis of Load-Sharing K-out-of-N System Considering Component Degradation
Directory of Open Access Journals (Sweden)
Chunbo Yang
2015-01-01
Full Text Available The K-out-of-N configuration is a typical form of redundancy techniques to improve system reliability, where at least K-out-of-N components must work for successful operation of system. When the components are degraded, more components are needed to meet the system requirement, which means that the value of K has to increase. The current reliability analysis methods overestimate the reliability, because using constant K ignores the degradation effect. In a load-sharing system with degrading components, the workload shared on each surviving component will increase after a random component failure, resulting in higher failure rate and increased performance degradation rate. This paper proposes a method combining a tampered failure rate model with a performance degradation model to analyze the reliability of load-sharing K-out-of-N system with degrading components. The proposed method considers the value of K as a variable which is derived by the performance degradation model. Also, the load-sharing effect is evaluated by the tampered failure rate model. Monte-Carlo simulation procedure is used to estimate the discrete probability distribution of K. The case of a solar panel is studied in this paper, and the result shows that the reliability considering component degradation is less than that ignoring component degradation.
Progress Towards Improved Analysis of TES X-ray Data Using Principal Component Analysis
Busch, S. E.; Adams, J. S.; Bandler, S. R.; Chervenak, J. A.; Eckart, M. E.; Finkbeiner, F. M.; Fixsen, D. J.; Kelley, R. L.; Kilbourne, C. A.; Lee, S.-J.;
2015-01-01
The traditional method of applying a digital optimal filter to measure X-ray pulses from transition-edge sensor (TES) devices does not achieve the best energy resolution when the signals have a highly non-linear response to energy, or the noise is non-stationary during the pulse. We present an implementation of a method to analyze X-ray data from TESs, which is based upon principal component analysis (PCA). Our method separates the X-ray signal pulse into orthogonal components that have the largest variance. We typically recover pulse height, arrival time, differences in pulse shape, and the variation of pulse height with detector temperature. These components can then be combined to form a representation of pulse energy. An added value of this method is that by reporting information on more descriptive parameters (as opposed to a single number representing energy), we generate a much more complete picture of the pulse received. Here we report on progress in developing this technique for future implementation on X-ray telescopes. We used an 55Fe source to characterize Mo/Au TESs. On the same dataset, the PCA method recovers a spectral resolution that is better by a factor of two than achievable with digital optimal filters.
Robust LOD scores for variance component-based linkage analysis.
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.
Constrained independent component analysis approach to nonobtrusive pulse rate measurements
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.
Cost analysis and estimating tools and techniques
Nussbaum, Daniel
1990-01-01
Changes in production processes reflect the technological advances permeat ing our products and services. U. S. industry is modernizing and automating. In parallel, direct labor is fading as the primary cost driver while engineering and technology related cost elements loom ever larger. Traditional, labor-based ap proaches to estimating costs are losing their relevance. Old methods require aug mentation with new estimating tools and techniques that capture the emerging environment. This volume represents one of many responses to this challenge by the cost analysis profession. The Institute of Cost Analysis (lCA) is dedicated to improving the effective ness of cost and price analysis and enhancing the professional competence of its members. We encourage and promote exchange of research findings and appli cations between the academic community and cost professionals in industry and government. The 1990 National Meeting in Los Angeles, jointly spo~sored by ICA and the National Estimating Society (NES),...
Population estimation techniques for routing analysis
International Nuclear Information System (INIS)
Sathisan, S.K.; Chagari, A.K.
1994-01-01
A number of on-site and off-site factors affect the potential siting of a radioactive materials repository at Yucca Mountain, Nevada. Transportation related issues such route selection and design are among them. These involve evaluation of potential risks and impacts, including those related to population. Population characteristics (total population and density) are critical factors in the risk assessment, emergency preparedness and response planning, and ultimately in route designation. This paper presents an application of Geographic Information System (GIS) technology to facilitate such analyses. Specifically, techniques to estimate critical population information are presented. A case study using the highway network in Nevada is used to illustrate the analyses. TIGER coverages are used as the basis for population information at a block level. The data are then synthesized at tract, county and state levels of aggregation. Of particular interest are population estimates for various corridor widths along transport corridors -- ranging from 0.5 miles to 20 miles in this paper. A sensitivity analysis based on the level of data aggregation is also presented. The results of these analysis indicate that specific characteristics of the area and its population could be used as indicators to aggregate data appropriately for the analysis
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
Research on Air Quality Evaluation based on Principal Component Analysis
Wang, Xing; Wang, Zilin; Guo, Min; Chen, Wei; Zhang, Huan
2018-01-01
Economic growth has led to environmental capacity decline and the deterioration of air quality. Air quality evaluation as a fundamental of environmental monitoring and air pollution control has become increasingly important. Based on the principal component analysis (PCA), this paper evaluates the air quality of a large city in Beijing-Tianjin-Hebei Area in recent 10 years and identifies influencing factors, in order to provide reference to air quality management and air pollution control.
Techniques for Analysis of Plant Phenolic Compounds
Directory of Open Access Journals (Sweden)
Thomas H. Roberts
2013-02-01
Full Text Available Phenolic compounds are well-known phytochemicals found in all plants. They consist of simple phenols, benzoic and cinnamic acid, coumarins, tannins, lignins, lignans and flavonoids. Substantial developments in research focused on the extraction, identification and quantification of phenolic compounds as medicinal and/or dietary molecules have occurred over the last 25 years. Organic solvent extraction is the main method used to extract phenolics. Chemical procedures are used to detect the presence of total phenolics, while spectrophotometric and chromatographic techniques are utilized to identify and quantify individual phenolic compounds. This review addresses the application of different methodologies utilized in the analysis of phenolic compounds in plant-based products, including recent technical developments in the quantification of phenolics.
Radio-analysis. Definitions and techniques
International Nuclear Information System (INIS)
Bourrel, F.; Courriere, Ph.
2003-01-01
This paper presents the different steps of the radio-labelling of a molecule for two purposes: the radio-immuno-analysis and the auto-radiography: 1 - definitions, radiations and radioprotection: activity of a radioactive source; half-life; radioactivity (alpha-, beta- and gamma radioactivity, internal conversion); radioprotection (irradiation, contamination); 2 - radionuclides used in medical biology and obtention of labelled molecules: gamma emitters ( 125 I, 57 Co); beta emitters; obtention of labelled molecules (general principles, high specific activity and choice of the tracer, molecule to be labelled); main labelling techniques (iodation, tritium); purification of the labelled compound (dialysis, gel-filtering or molecular exclusion chromatography, high performance liquid chromatography); quality estimation of the labelled compound (labelling efficiency calculation, immuno-reactivity conservation, stability and preservation). (J.S.)
Allen, Edwin B; Walls, Richard T; Reilly, Frank D
2008-02-01
This study investigated the effects of interactive instructional techniques in a web-based peripheral nervous system (PNS) component of a first year medical school human anatomy course. Existing data from 9 years of instruction involving 856 students were used to determine (1) the effect of web-based interactive instructional techniques on written exam item performance and (2) differences between student opinions of the benefit level of five different types of interactive learning objects used. The interactive learning objects included Patient Case studies, review Games, Simulated Interactive Patients (SIP), Flashcards, and unit Quizzes. Exam item analysis scores were found to be significantly higher (p < 0.05) for students receiving the instructional treatment incorporating the web-based interactive learning objects than for students not receiving this treatment. Questionnaires using a five-point Likert scale were analysed to determine student opinion ratings of the interactive learning objects. Students reported favorably on the benefit level of all learning objects. Students rated the benefit level of the Simulated Interactive Patients (SIP) highest, and this rating was significantly higher (p < 0.05) than all other learning objects. This study suggests that web-based interactive instructional techniques improve student exam performance. Students indicated a strong acceptance of Simulated Interactive Patient learning objects.
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.
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.
Missing data is a common problem in the application of statistical techniques. In principal component analysis (PCA), a technique for dimensionality reduction, incomplete data points are either discarded or imputed using interpolation methods. Such approaches are less valid when ...
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.
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
Portable XRF and principal component analysis for bill characterization in forensic science.
Appoloni, C R; Melquiades, F L
2014-02-01
Several modern techniques have been applied to prevent counterfeiting of money bills. The objective of this study was to demonstrate the potential of Portable X-ray Fluorescence (PXRF) technique and the multivariate analysis method of Principal Component Analysis (PCA) for classification of bills in order to use it in forensic science. Bills of Dollar, Euro and Real (Brazilian currency) were measured directly at different colored regions, without any previous preparation. Spectra interpretation allowed the identification of Ca, Ti, Fe, Cu, Sr, Y, Zr and Pb. PCA analysis separated the bills in three groups and subgroups among Brazilian currency. In conclusion, the samples were classified according to its origin identifying the elements responsible for differentiation and basic pigment composition. PXRF allied to multivariate discriminate methods is a promising technique for rapid and no destructive identification of false bills in forensic science. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.)
Optimized inspection techniques and structural analysis in lifetime management
International Nuclear Information System (INIS)
Aguado, M.T.; Marcelles, I.
1993-01-01
Preservation of the option of extending the service lifetime of a nuclear power plant beyond its normal design lifetime requires correct remaining lifetime management from the very beginning of plant operation. The methodology used in plant remaining lifetime management is essentially based on the use of standard inspections, surveillance and monitoring programs and calculations, such as thermal-stress and fracture mechanics analysis. The inspection techniques should be continuously optimized, in order to be able to detect and dimension existing defects with the highest possible degree of accuracy. The information obtained during the inspection is combined with the historical data of the components: design, quality, operation, maintenance, and transients, and with the results of destructive testing, fracture mechanics and thermal fatigue analysis. These data are used to estimate the remaining lifetime of nuclear power plant components, systems and structures with the highest degree possible of accuracy. The use of this methodology allows component repairs and replacements to be reduced or avoided and increases the safety levels and availability of the nuclear power plant. Use of this strategy avoids the need for heavy investments at the end of the licensing period
A component analysis of positive behaviour support plans.
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.
Representation for dialect recognition using topographic independent component analysis
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.
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)
Flame analysis using image processing techniques
Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng
2018-04-01
This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.
Analysis of obsidians by PIXE technique
International Nuclear Information System (INIS)
Nuncio Q, A.E.
1998-01-01
This work presents the characterization of obsydian samples from different mineral sites in Mexico, undertaken by an Ion Beam Analysis: PIXE (Proton Induced X-ray Emission). As part of an intensive investigation of obsidian in Mesoamerica by anthropologists from Mexico National Institute of Anthropology and History, 818 samples were collected from different volcanic sources in central Mexico for the purpose of establishing a data bank of element concentrations of each source. Part of this collection was analyzed by Neutron activation analysis and most of the important elements concentrations reported. In this work, a non-destructive IBA technique (PIXE) are used to analyze obsydian samples. The application of this technique were carried out at laboratories of the ININ Nuclear Center facilities. The samples consisted of of obsydians from ten different volcanic sources. This pieces were mounted on a sample holder designed for the purpose of exposing each sample to the proton beam. This PIXE analysis was carried out with an ET Tandem Accelerator at the ININ. X-ray spectrometry was carried out with an external beam facility employing a Si(Li) detector set at 52.5 degrees in relation to the target normal (parallel to the beam direction) and 4.2 cm away from the target center. A filter was set in front of the detector, to determine the best attenuation conditions to obtain most of the elements, taking into account that X-ray spectra from obsydians are dominated by intense major elements lines. Thus, a 28 μ m- thick aluminium foil absorber was selected and used to reduce the intensity of the major lines as well as pile-up effects. The mean proton energy was 2.62 MeV, and the beam profile was about 4 mm in diameter. As results were founded elemental concentrations of a set of samples from ten different sources: Altotonga (Veracruz), Penjamo (Guanajuato), Otumba (Mexico), Zinapecuaro (Michoacan), Ucareo (Michoacan), Tres Cabezas (Puebla), Sierra Navajas (Hidalgo), Zaragoza
The Use of Isotope Techniques to Separate of Hydrography Components. Case Study: Ankara-Guvenc Basin
International Nuclear Information System (INIS)
Tekeli, Y.I.; Sorman, A.U.; Sayin, M.
2002-01-01
In this research, a stable environmental isotope study was carried out from analysis of water samples collected from rainfall, runoff (total discharge), springs (subsurface flows), and wells (ground waters)in Ankara-Guevenc basin having a drainage area of about 16.125 km 2 between 1996-2000. The aim of the study was to investigate the rainfall-runoff relationship for the basin. Recorded total ten discharge hydrographs are separated to their components using stable isotopes (Oxygen-18, Deuterium) contents. Among these samples, unit hydrographs from two one-peak storm hydrographs were derived using both isotope and graphical methods, and the derived unit hydrographs values including peaks were compared. Peak values of 10 and 20 minutes unit hydrographs of the basin derived by using isotope method (Q p = 1322 1/s and Q p = 1327 l/s) are compared with those of graphical method (Q p = 1656 1/s, and Q p = 1250 1/s) using Barnes semi-log approach. It was found out that, the contribution of subsurface flow which is component of total discharge hydrograph and originating from various sub layers are important in the total flow of basin using isotope method of approach
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.
Handbook of Qualitative Research Techniques and Analysis in Entrepreneurship
DEFF Research Database (Denmark)
One of the most challenging tasks in the research design process is choosing the most appropriate data collection and analysis techniques. This Handbook provides a detailed introduction to five qualitative data collection and analysis techniques pertinent to exploring entreprneurial phenomena....
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
A further component analysis for illicit drugs mixtures with THz-TDS
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.
Wang, Yanru; Li, Bincheng
2012-11-01
The laser calorimetry (LCA) technique is used to determine simultaneously the absorptances and thermal diffusivities of optical components. An accurate temperature model, in which both the finite thermal conductivity and the finite sample size are taken into account, is employed to fit the experimental temperature data measured with an LCA apparatus for a precise determination of the absorptance and thermal diffusivity via a multiparameter fitting procedure. The uniqueness issue of the multiparameter fitting is discussed in detail. Experimentally, highly reflective (HR) samples prepared with electron-beam evaporation on different substrates (BK7, fused silica, and Ge) are measured with LCA. For the HR-coated sample on a fused silica substrate, the absorptance is determined to be 15.4 ppm, which is close to the value of 17.6 ppm, determined with a simplified temperature model recommended in the international standard ISO11551. The thermal diffusivity is simultaneously determined via multiparameter fitting to be approximately 6.63 × 10-7 m2 · s-1 with a corresponding square variance of 4.8 × 10-4. The fitted thermal diffusivity is in reasonably good agreement with the literature value (7.5 × 10-7 m2 · s -1). Good agreement is also obtained for samples with BK7 and Ge substrates.
Leddy, Michael T; Belter, Joseph T; Gemmell, Kevin D; Dollar, Aaron M
2015-01-01
Additive manufacturing techniques are becoming more prominent and cost-effective as 3D printing becomes higher quality and more inexpensive. The idea of 3D printed prosthetics components promises affordable, customizable devices, but these systems currently have major shortcomings in durability and function. In this paper, we propose a fabrication method for custom composite prostheses utilizing additive manufacturing, allowing for customizability, as well the durability of professional prosthetics. The manufacturing process is completed using 3D printed molds in a multi-stage molding system, which creates a custom finger or palm with a lightweight epoxy foam core, a durable composite outer shell, and soft urethane gripping surfaces. The composite material was compared to 3D printed and aluminum materials using a three-point bending test to compare stiffness, as well as gravimetric measurements to compare weight. The composite finger demonstrates the largest stiffness with the lowest weight compared to other tested fingers, as well as having customizability and lower cost, proving to potentially be a substantial benefit to the development of upper-limb prostheses.
International Nuclear Information System (INIS)
Ebata, Makoto; Okuyama, Gen; Chiba, Shigeru; Matsunaga, Tsunebumi
1991-01-01
In view of the growing need for prolongation of lives of reprocessing plant installations, we recently investigated the applicability of highly corrosion-resistant amorphous coating techniques to such plant components as to be subjected to a badly corrosive environment created by high temperatures, boiling nitric acid (HNO 3 ), etc. As the result, giving a preference to the Ta-based amorphous alloys exhibiting high corrosion-resistance in HNO 3 solutions, we made specimens of stainless steel plates coated with the above amorphous alloys through the sputtering process thereof. To our satisfaction, these specimens successfully passed various HNO 3 corrosion tests as described later on. Ta-based amorphous films give cathodic protection to 310 Nb stainless steel plates, and that with extremely low corrosion rates of themselves as protecting agents. For these reasons, we are confident that there will be no practical problems at all, in case we adopt stainless steel plates partially coated with such amorphous alloys for use in a nitric-acid environment. In this paper, we explain the comparative tests for various amorphous alloys with different compositions, referring also to the thus-selected Ta-based amorphous alloy along with several kinds of corrosion tests specially arranged for the same alloy. (author)
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.
Fast principal component analysis for stacking seismic data
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.
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.
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.)
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...
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)
International Nuclear Information System (INIS)
Leonard, J.W.
1975-01-01
This work is concerned with the evaluation of a quasi-static method as applied to a swing check valve designed to provide emergency shut-off capability subsequent to a postulated break in a steam line. The impact analysis of swinging disk upon the valve seat is an asymmetric problem in dynamic elastoplasticity with potentially large displacements and strains resulting from the impact. To perform a quasi-static analysis for this component the disk and seat region of the valve was isolated from the piping system by special boundary elements and an elastic-plastic finite element model was generated assuming axisymmetric solid ring elements. An equivalent static axisymmetric incremental load system was used to approximate the nonsymmetric initial velocity of impact. Subsequent to the nonlinear incremental finite element analysis by a standard computer software package (MARC-CDC program), a special post-processing program was employed to calculate the incremental sum of external work due to the defined load system. Equating this external work to the initial kinetic energy of impact, parametric curves for displacements, stresses, and strains were obtained as functions of various levels of kinetic energy imparted to the valve at closure. To verify the conservative nature of the assumptions made in the quasi-static model, a comparison was made with a time-dependent, nonlinear, axisymmetric, elastic-plastic finite difference simulation. Another standard computer software package (PISCES-2DL) was used for this dynamic simulation. For a check-point value of initial impact kinetic energy, correlation between the quasi-static finite element and dynamic finite difference analyses is presented. Validations of the assumptions made in the quasi-static analysis and of the results obtained are discussed in detail
Robustness analysis of bogie suspension components Pareto optimised values
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.
Sparse principal component analysis in medical shape modeling
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.
Computational techniques for inelastic analysis and numerical experiments
International Nuclear Information System (INIS)
Yamada, Y.
1977-01-01
A number of formulations have been proposed for inelastic analysis, particularly for the thermal elastic-plastic creep analysis of nuclear reactor components. In the elastic-plastic regime, which principally concerns with the time independent behavior, the numerical techniques based on the finite element method have been well exploited and computations have become a routine work. With respect to the problems in which the time dependent behavior is significant, it is desirable to incorporate a procedure which is workable on the mechanical model formulation as well as the method of equation of state proposed so far. A computer program should also take into account the strain-dependent and/or time-dependent micro-structural changes which often occur during the operation of structural components at the increasingly high temperature for a long period of time. Special considerations are crucial if the analysis is to be extended to large strain regime where geometric nonlinearities predominate. The present paper introduces a rational updated formulation and a computer program under development by taking into account the various requisites stated above. (Auth.)
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
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.)
VENUS-III two-dimensional multi-component thermal hydraulic techniques
International Nuclear Information System (INIS)
Weber, D.P.
1979-01-01
In recent analyses of the initiating phase in LMFBR core disruptive accidents the energy deposition rate may not be nearly so high as originally thought and the development of material motion and interaction may take place on a time scale considerably larger than the classic disassembly time scale of milliseconds. This introduces a considerably different twist to the problem and it becomes apparent that processes heretofore ignored, such as differential motion and heat exchange, may become important. In addition, time scales may become long enough that substantial core material motion may take place and since rearrangement in more critical configurations cannot be absolutely precluded, capability for extended motion analysis, not easily performed with Lagrangian techniques in multi-dimensions, become desirable. Such considerations provided the motivation for developing a hydrodynamic algorithm to resolve these questions, and an Eulerian rather than Lagrangian frame of reference was chosen, primarily to handle extended motion and interpenetration. The results of the study are described
Numerical modeling techniques for flood analysis
Anees, Mohd Talha; Abdullah, K.; Nawawi, M. N. M.; Ab Rahman, Nik Norulaini Nik; Piah, Abd. Rahni Mt.; Zakaria, Nor Azazi; Syakir, M. I.; Mohd. Omar, A. K.
2016-12-01
Topographic and climatic changes are the main causes of abrupt flooding in tropical areas. It is the need to find out exact causes and effects of these changes. Numerical modeling techniques plays a vital role for such studies due to their use of hydrological parameters which are strongly linked with topographic changes. In this review, some of the widely used models utilizing hydrological and river modeling parameters and their estimation in data sparse region are discussed. Shortcomings of 1D and 2D numerical models and the possible improvements over these models through 3D modeling are also discussed. It is found that the HEC-RAS and FLO 2D model are best in terms of economical and accurate flood analysis for river and floodplain modeling respectively. Limitations of FLO 2D in floodplain modeling mainly such as floodplain elevation differences and its vertical roughness in grids were found which can be improve through 3D model. Therefore, 3D model was found to be more suitable than 1D and 2D models in terms of vertical accuracy in grid cells. It was also found that 3D models for open channel flows already developed recently but not for floodplain. Hence, it was suggested that a 3D model for floodplain should be developed by considering all hydrological and high resolution topographic parameter's models, discussed in this review, to enhance the findings of causes and effects of flooding.
Techniques of production and analysis of polarized synchrotron radiation
International Nuclear Information System (INIS)
Mills, D.M.
1992-01-01
The use of the unique polarization properties of synchrotron radiation in the hard x-ray spectral region (E>3 KeV) is becoming increasingly important to many synchrotron radiation researchers. The radiation emitted from bending magnets and conventional (planar) insertion devices (IDs) is highly linearly polarized in the plane of the particle's orbit. Elliptically polarized x-rays can also be obtained by going off axis on a bending magnet source, albeit with considerable loss of flux. The polarization properties of synchrotron radiation can be further tailored to the researcher's specific needs through the use of specialized insertion devices such as helical and crossed undulators and asymmetrical wigglers. Even with the possibility of producing a specific polarization, there is still the need to develop x-ray optical components which can manipulate the polarization for both analysis and further modification of the polarization state. A survey of techniques for producing and analyzing both linear and circular polarized x-rays will be presented with emphasis on those techniques which rely on single crystal optical components
Principal Component Analysis Based Measure of Structural Holes
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.
Fast and accurate methods of independent component analysis: A survey
Czech Academy of Sciences Publication Activity Database
Tichavský, Petr; Koldovský, Zbyněk
2011-01-01
Roč. 47, č. 3 (2011), s. 426-438 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/09/1278 Institutional research plan: CEZ:AV0Z10750506 Keywords : Blind source separation * artifact removal * electroencephalogram * audio signal processing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/tichavsky-fast and accurate methods of independent component analysis a survey.pdf
Fetal ECG extraction using independent component analysis by Jade approach
Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian
2017-11-01
Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.
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.
Advances in independent component analysis and learning machines
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
Wei, Ying-Jie; Jing, Li-Jun; Zhan, Yang; Sun, E; Jia, Xiao-Bin
2014-05-01
To break through the restrictions of the evaluation model and the quantity of compounds by using the two-dimensional zebrafish model combined with chromatographic techniques, and establish a new method for the high-throughput screening of active anti-osteoporosis components. According to the research group-related studies and relevant foreign literatures, on the basis of the fact that the zebrafish osteoporosis model could efficiently evaluate the activity, the zebrafish metabolism model could efficiently enrich metabolites and the chromatographic techniques could efficiently separate and analyze components of traditional Chinese medicines, we proposed that the inherent combination of the three methods is expected to efficiently decode in vivo and in vitro efficacious anti-osteoporosis materials of traditional Chinese medicines. The method makes it simple and efficient in the enrichment, separation and analysis on components of traditional Chinese medicines, particularly micro-components and metabolites and the screening anti-osteoporosis activity, fully reflects that efficacious materials of traditional Chinese medicines contain original components and metabolites, with characteristic of "multi-components, multi-targets and integral effect", which provides new ideas and methods for the early and rapid discovery of active anti-osteoporosis components of traditional Chinese medicines.
International Nuclear Information System (INIS)
Nigran, K.S.; Barber, D.C.
1985-01-01
A method is proposed for automatic analysis of dynamic radionuclide studies using the mathematical technique of principal-components factor analysis. This method is considered as a possible alternative to the conventional manual regions-of-interest method widely used. The method emphasises the importance of introducing a priori information into the analysis about the physiology of at least one of the functional structures in a study. Information is added by using suitable mathematical models to describe the underlying physiological processes. A single physiological factor is extracted representing the particular dynamic structure of interest. Two spaces 'study space, S' and 'theory space, T' are defined in the formation of the concept of intersection of spaces. A one-dimensional intersection space is computed. An example from a dynamic 99 Tcsup(m) DTPA kidney study is used to demonstrate the principle inherent in the method proposed. The method requires no correction for the blood background activity, necessary when processing by the manual method. The careful isolation of the kidney by means of region of interest is not required. The method is therefore less prone to operator influence and can be automated. (author)
Development of motion image prediction method using principal component analysis
International Nuclear Information System (INIS)
Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma
2012-01-01
Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)
Fast grasping of unknown objects using principal component analysis
Lei, Qujiang; Chen, Guangming; Wisse, Martijn
2017-09-01
Fast grasping of unknown objects has crucial impact on the efficiency of robot manipulation especially subjected to unfamiliar environments. In order to accelerate grasping speed of unknown objects, principal component analysis is utilized to direct the grasping process. In particular, a single-view partial point cloud is constructed and grasp candidates are allocated along the principal axis. Force balance optimization is employed to analyze possible graspable areas. The obtained graspable area with the minimal resultant force is the best zone for the final grasping execution. It is shown that an unknown object can be more quickly grasped provided that the component analysis principle axis is determined using single-view partial point cloud. To cope with the grasp uncertainty, robot motion is assisted to obtain a new viewpoint. Virtual exploration and experimental tests are carried out to verify this fast gasping algorithm. Both simulation and experimental tests demonstrated excellent performances based on the results of grasping a series of unknown objects. To minimize the grasping uncertainty, the merits of the robot hardware with two 3D cameras can be utilized to suffice the partial point cloud. As a result of utilizing the robot hardware, the grasping reliance is highly enhanced. Therefore, this research demonstrates practical significance for increasing grasping speed and thus increasing robot efficiency under unpredictable environments.
Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.
Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J
2018-03-01
Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.
Quantitative blood flow analysis with digital techniques
International Nuclear Information System (INIS)
Forbes, G.
1984-01-01
The general principles of digital techniques in quantitating absolute blood flow during arteriography are described. Results are presented for a phantom constructed to correlate digitally calculated absolute flow with direct flow measurements. The clinical use of digital techniques in cerebrovascular angiography is briefly described. (U.K.)
Pasadakis, Nikos; Kardamakis, Andreas A
2006-09-25
A new method is proposed that enables the identification of five refinery fractions present in commercial gasoline mixtures using infrared spectroscopic analysis. The data analysis and interpretation was carried out based on independent component analysis (ICA) and spectral similarity techniques. The FT-IR spectra of the gasoline constituents were determined using the ICA method, exclusively based on the spectra of their mixtures as a blind separation procedure, i.e. assuming unknown the spectra of the constituents. The identity of the constituents was subsequently determined using similarity measures commonly employed in spectra library searches against the spectra of the constituent components. The high correlation scores that were obtained in the identification of the constituents indicates that the developed method can be employed as a rapid and effective tool in quality control, fingerprinting or forensic applications, where gasoline constituents are suspected.
Directory of Open Access Journals (Sweden)
Joseph P. Kenny
2008-01-01
Full Text Available Cutting-edge scientific computing software is complex, increasingly involving the coupling of multiple packages to combine advanced algorithms or simulations at multiple physical scales. Component-based software engineering (CBSE has been advanced as a technique for managing this complexity, and complex component applications have been created in the quantum chemistry domain, as well as several other simulation areas, using the component model advocated by the Common Component Architecture (CCA Forum. While programming models do indeed enable sound software engineering practices, the selection of programming model is just one building block in a comprehensive approach to large-scale collaborative development which must also address interface and data standardization, and language and package interoperability. We provide an overview of the development approach utilized within the Quantum Chemistry Science Application Partnership, identifying design challenges, describing the techniques which we have adopted to address these challenges and highlighting the advantages which the CCA approach offers for collaborative development.
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)
Nuclear fuel cycle cost analysis using a probabilistic simulation technique
International Nuclear Information System (INIS)
Won, Il Ko; Jong, Won Choi; Chul, Hyung Kang; Jae, Sol Lee; Kun, Jai Lee
1998-01-01
A simple approach was described to incorporate the Monte Carlo simulation technique into a fuel cycle cost estimate. As a case study, the once-through and recycle fuel cycle options were tested with some alternatives (ie. the change of distribution type for input parameters), and the simulation results were compared with the values calculated by a deterministic method. A three-estimate approach was used for converting cost inputs into the statistical parameters of assumed probabilistic distributions. It was indicated that the Monte Carlo simulation by a Latin Hypercube Sampling technique and subsequent sensitivity analyses were useful for examining uncertainty propagation of fuel cycle costs, and could more efficiently provide information to decisions makers than a deterministic method. It was shown from the change of distribution types of input parameters that the values calculated by the deterministic method were set around a 40 th ∼ 50 th percentile of the output distribution function calculated by probabilistic simulation. Assuming lognormal distribution of inputs, however, the values calculated by the deterministic method were set around an 85 th percentile of the output distribution function calculated by probabilistic simulation. It was also indicated from the results of the sensitivity analysis that the front-end components were generally more sensitive than the back-end components, of which the uranium purchase cost was the most important factor of all. It showed, also, that the discount rate made many contributions to the fuel cycle cost, showing the rank of third or fifth of all components. The results of this study could be useful in applications to another options, such as the Dcp (Direct Use of PWR spent fuel In Candu reactors) cycle with high cost uncertainty
Blind Component Separation in Wavelet Space: Application to CMB Analysis
Directory of Open Access Journals (Sweden)
J. Delabrouille
2005-09-01
Full Text Available It is a recurrent issue in astronomical data analysis that observations are incomplete maps with missing patches or intentionally masked parts. In addition, many astrophysical emissions are nonstationary processes over the sky. All these effects impair data processing techniques which work in the Fourier domain. Spectral matching ICA (SMICA is a source separation method based on spectral matching in Fourier space designed for the separation of diffuse astrophysical emissions in cosmic microwave background observations. This paper proposes an extension of SMICA to the wavelet domain and demonstrates the effectiveness of wavelet-based statistics for dealing with gaps in the data.
Portable XRF and principal component analysis for bill characterization in forensic science
International Nuclear Information System (INIS)
Appoloni, C.R.; Melquiades, F.L.
2014-01-01
Several modern techniques have been applied to prevent counterfeiting of money bills. The objective of this study was to demonstrate the potential of Portable X-ray Fluorescence (PXRF) technique and the multivariate analysis method of Principal Component Analysis (PCA) for classification of bills in order to use it in forensic science. Bills of Dollar, Euro and Real (Brazilian currency) were measured directly at different colored regions, without any previous preparation. Spectra interpretation allowed the identification of Ca, Ti, Fe, Cu, Sr, Y, Zr and Pb. PCA analysis separated the bills in three groups and subgroups among Brazilian currency. In conclusion, the samples were classified according to its origin identifying the elements responsible for differentiation and basic pigment composition. PXRF allied to multivariate discriminate methods is a promising technique for rapid and no destructive identification of false bills in forensic science. - Highlights: • The paper is about a direct method for bills discrimination by EDXRF and principal component analysis. • The bills are analyzed directly, without sample preparation and non destructively. • The results demonstrates that the methodology is feasible and could be applied in forensic science for identification of origin and false banknotes. • The novelty is that portable EDXRF is very fast and efficient for bills characterization
PRINCIPAL COMPONENT ANALYSIS STUDIES OF TURBULENCE IN OPTICALLY THICK GAS
Energy Technology Data Exchange (ETDEWEB)
Correia, C.; Medeiros, J. R. De [Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, 59072-970, Natal (Brazil); Lazarian, A. [Astronomy Department, University of Wisconsin, Madison, 475 N. Charter St., WI 53711 (United States); Burkhart, B. [Harvard-Smithsonian Center for Astrophysics, 60 Garden St, MS-20, Cambridge, MA 02138 (United States); Pogosyan, D., E-mail: caioftc@dfte.ufrn.br [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON (Canada)
2016-02-20
In this work we investigate the sensitivity of principal component analysis (PCA) to the velocity power spectrum in high-opacity regimes of the interstellar medium (ISM). For our analysis we use synthetic position–position–velocity (PPV) cubes of fractional Brownian motion and magnetohydrodynamics (MHD) simulations, post-processed to include radiative transfer effects from CO. We find that PCA analysis is very different from the tools based on the traditional power spectrum of PPV data cubes. Our major finding is that PCA is also sensitive to the phase information of PPV cubes and this allows PCA to detect the changes of the underlying velocity and density spectra at high opacities, where the spectral analysis of the maps provides the universal −3 spectrum in accordance with the predictions of the Lazarian and Pogosyan theory. This makes PCA a potentially valuable tool for studies of turbulence at high opacities, provided that proper gauging of the PCA index is made. However, we found the latter to not be easy, as the PCA results change in an irregular way for data with high sonic Mach numbers. This is in contrast to synthetic Brownian noise data used for velocity and density fields that show monotonic PCA behavior. We attribute this difference to the PCA's sensitivity to Fourier phase information.
PRINCIPAL COMPONENT ANALYSIS STUDIES OF TURBULENCE IN OPTICALLY THICK GAS
International Nuclear Information System (INIS)
Correia, C.; Medeiros, J. R. De; Lazarian, A.; Burkhart, B.; Pogosyan, D.
2016-01-01
In this work we investigate the sensitivity of principal component analysis (PCA) to the velocity power spectrum in high-opacity regimes of the interstellar medium (ISM). For our analysis we use synthetic position–position–velocity (PPV) cubes of fractional Brownian motion and magnetohydrodynamics (MHD) simulations, post-processed to include radiative transfer effects from CO. We find that PCA analysis is very different from the tools based on the traditional power spectrum of PPV data cubes. Our major finding is that PCA is also sensitive to the phase information of PPV cubes and this allows PCA to detect the changes of the underlying velocity and density spectra at high opacities, where the spectral analysis of the maps provides the universal −3 spectrum in accordance with the predictions of the Lazarian and Pogosyan theory. This makes PCA a potentially valuable tool for studies of turbulence at high opacities, provided that proper gauging of the PCA index is made. However, we found the latter to not be easy, as the PCA results change in an irregular way for data with high sonic Mach numbers. This is in contrast to synthetic Brownian noise data used for velocity and density fields that show monotonic PCA behavior. We attribute this difference to the PCA's sensitivity to Fourier phase information
CSIR Research Space (South Africa)
Nel, W
2009-10-01
Full Text Available to estimate the 3-D position of scatterers as a by-product of the analysis. The technique is based on principal component analysis of accurate scatterer range histories and is shown only in simulation. Future research should focus on practical application....
International Nuclear Information System (INIS)
Wu, D.; Landsberger, S.; Larson, S.M.
1997-01-01
Cigarette smoking is a major source of particle released in indoor environments. A comprehensive study of the elemental distribution in cigarettes and cigarette smoke has been completed. Specifically, concentrations of thirty elements have been determined for the components of 15 types of cigarettes. Components include tobacco, ash, butts, filters, and cigarette paper. In addition, particulate matter from mainstream smoke (MS) and sidesstream smoke (SS) were analyzed. The technique of elemental determination used in the study is instrumental neutron activation analysis. The results show that certain heavy metals, such as As, Cd, K, Sb and Zn, are released into the MS and SS. These metals may then be part of the health risk of exposure to smoke. Other elements are retained, for the most part, in cigarette ash and butts. The elemental distribution among the cigarette components and smoke changes for different smoking conditions. (author)
Mapping brain activity in gradient-echo functional MRI using principal component analysis
Khosla, Deepak; Singh, Manbir; Don, Manuel
1997-05-01
The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.
The Analysis of Dimensionality Reduction Techniques in Cryptographic Object Code Classification
Energy Technology Data Exchange (ETDEWEB)
Jason L. Wright; Milos Manic
2010-05-01
This paper compares the application of three different dimension reduction techniques to the problem of locating cryptography in compiled object code. A simple classi?er is used to compare dimension reduction via sorted covariance, principal component analysis, and correlation-based feature subset selection. The analysis concentrates on the classi?cation accuracy as the number of dimensions is increased.
Hospitals Productivity Measurement Using Data Envelopment Analysis Technique.
Torabipour, Amin; Najarzadeh, Maryam; Arab, Mohammad; Farzianpour, Freshteh; Ghasemzadeh, Roya
2014-11-01
This study aimed to measure the hospital productivity using data envelopment analysis (DEA) technique and Malmquist indices. This is a cross sectional study in which the panel data were used in a 4 year period from 2007 to 2010. The research was implemented in 12 teaching and non-teaching hospitals of Ahvaz County. Data envelopment analysis technique and the Malmquist indices with an input-orientation approach, was used to analyze the data and estimation of productivity. Data were analyzed using the SPSS.18 and DEAP.2 software. Six hospitals (50%) had a value lower than 1, which represents an increase in total productivity and other hospitals were non-productive. the average of total productivity factor (TPF) was 1.024 for all hospitals, which represents a decrease in efficiency by 2.4% from 2007 to 2010. The average technical, technologic, scale and managerial efficiency change was 0.989, 1.008, 1.028, and 0.996 respectively. There was not a significant difference in mean productivity changes among teaching and non-teaching hospitals (P>0.05) (except in 2009 years). Productivity rate of hospitals had an increasing trend generally. However, the total average of productivity was decreased in hospitals. Besides, between the several components of total productivity, variation of technological efficiency had the highest impact on reduce of total average of productivity.
Failure cause analysis and improvement for magnetic component cabinet
International Nuclear Information System (INIS)
Ge Bing
1999-01-01
The magnetic component cabinet is an important thermal control device fitted on the nuclear power. Because it used a self-saturation amplifier as a primary component, the magnetic component cabinet has some boundness. For increasing the operation safety on the nuclear power, the author describes a new scheme. In order that the magnetic component cabinet can be replaced, the new type component cabinet is developed. Integrate circuit will replace the magnetic components of every function parts. The author has analyzed overall failure cause for magnetic component cabinet and adopted some measures
The Heliospheric Cataloguing, Analysis and Techniques Service (HELCATS) project
Barnes, D.; Harrison, R. A.; Davies, J. A.; Perry, C. H.; Moestl, C.; Rouillard, A.; Bothmer, V.; Rodriguez, L.; Eastwood, J. P.; Kilpua, E.; Gallagher, P.; Odstrcil, D.
2017-12-01
Understanding solar wind evolution is fundamental to advancing our knowledge of energy and mass transport in the solar system, whilst also being crucial to space weather and its prediction. The advent of truly wide-angle heliospheric imaging has revolutionised the study of solar wind evolution, by enabling direct and continuous observation of both transient and background components of the solar wind as they propagate from the Sun to 1 AU and beyond. The recently completed, EU-funded FP7 Heliospheric Cataloguing, Analysis and Techniques Service (HELCATS) project (1st May 2014 - 30th April 2017) combined European expertise in heliospheric imaging, built up over the last decade in particular through leadership of the Heliospheric Imager (HI) instruments aboard NASA's STEREO mission, with expertise in solar and coronal imaging as well as the interpretation of in-situ and radio diagnostic measurements of solar wind phenomena. HELCATS involved: (1) the cataloguing of transient (coronal mass ejections) and background (stream/corotating interaction regions) solar wind structures observed by the STEREO/HI instruments, including estimates of their kinematic properties based on a variety of modelling techniques; (2) the verification of these kinematic properties through comparison with solar source observations and in-situ measurements at multiple points throughout the heliosphere; (3) the assessment of the potential for initialising numerical models based on the derived kinematic properties of transient and background solar wind components; and (4) the assessment of the complementarity of radio observations (Type II radio bursts and interplanetary scintillation) in the detection and analysis of heliospheric structure in combination with heliospheric imaging observations. In this presentation, we provide an overview of the HELCATS project emphasising, in particular, the principal achievements and legacy of this unprecedented project.
Quality Aware Compression of Electrocardiogram Using Principal Component Analysis.
Gupta, Rajarshi
2016-05-01
Electrocardiogram (ECG) compression finds wide application in various patient monitoring purposes. Quality control in ECG compression ensures reconstruction quality and its clinical acceptance for diagnostic decision making. In this paper, a quality aware compression method of single lead ECG is described using principal component analysis (PCA). After pre-processing, beat extraction and PCA decomposition, two independent quality criteria, namely, bit rate control (BRC) or error control (EC) criteria were set to select optimal principal components, eigenvectors and their quantization level to achieve desired bit rate or error measure. The selected principal components and eigenvectors were finally compressed using a modified delta and Huffman encoder. The algorithms were validated with 32 sets of MIT Arrhythmia data and 60 normal and 30 sets of diagnostic ECG data from PTB Diagnostic ECG data ptbdb, all at 1 kHz sampling. For BRC with a CR threshold of 40, an average Compression Ratio (CR), percentage root mean squared difference normalized (PRDN) and maximum absolute error (MAE) of 50.74, 16.22 and 0.243 mV respectively were obtained. For EC with an upper limit of 5 % PRDN and 0.1 mV MAE, the average CR, PRDN and MAE of 9.48, 4.13 and 0.049 mV respectively were obtained. For mitdb data 117, the reconstruction quality could be preserved up to CR of 68.96 by extending the BRC threshold. The proposed method yields better results than recently published works on quality controlled ECG compression.
Directory of Open Access Journals (Sweden)
Anna Maria Stellacci
2012-07-01
Full Text Available Hyperspectral (HS data represents an extremely powerful means for rapidly detecting crop stress and then aiding in the rational management of natural resources in agriculture. However, large volume of data poses a challenge for data processing and extracting crucial information. Multivariate statistical techniques can play a key role in the analysis of HS data, as they may allow to both eliminate redundant information and identify synthetic indices which maximize differences among levels of stress. In this paper we propose an integrated approach, based on the combined use of Principal Component Analysis (PCA and Canonical Discriminant Analysis (CDA, to investigate HS plant response and discriminate plant status. The approach was preliminary evaluated on a data set collected on durum wheat plants grown under different nitrogen (N stress levels. Hyperspectral measurements were performed at anthesis through a high resolution field spectroradiometer, ASD FieldSpec HandHeld, covering the 325-1075 nm region. Reflectance data were first restricted to the interval 510-1000 nm and then divided into five bands of the electromagnetic spectrum [green: 510-580 nm; yellow: 581-630 nm; red: 631-690 nm; red-edge: 705-770 nm; near-infrared (NIR: 771-1000 nm]. PCA was applied to each spectral interval. CDA was performed on the extracted components to identify the factors maximizing the differences among plants fertilised with increasing N rates. Within the intervals of green, yellow and red only the first principal component (PC had an eigenvalue greater than 1 and explained more than 95% of total variance; within the ranges of red-edge and NIR, the first two PCs had an eigenvalue higher than 1. Two canonical variables explained cumulatively more than 81% of total variance and the first was able to discriminate wheat plants differently fertilised, as confirmed also by the significant correlation with aboveground biomass and grain yield parameters. The combined
Multi-component controllers in reactor physics optimality analysis
International Nuclear Information System (INIS)
Aldemir, T.
1978-01-01
An algorithm is developed for the optimality analysis of thermal reactor assemblies with multi-component control vectors. The neutronics of the system under consideration is assumed to be described by the two-group diffusion equations and constraints are imposed upon the state and control variables. It is shown that if the problem is such that the differential and algebraic equations describing the system can be cast into a linear form via a change of variables, the optimal control components are piecewise constant functions and the global optimal controller can be determined by investigating the properties of the influence functions. Two specific problems are solved utilizing this approach. A thermal reactor consisting of fuel, burnable poison and moderator is found to yield maximal power when the assembly consists of two poison zones and the power density is constant throughout the assembly. It is shown that certain variational relations have to be considered to maintain the activeness of the system equations as differential constraints. The problem of determining the maximum initial breeding ratio for a thermal reactor is solved by treating the fertile and fissile material absorption densities as controllers. The optimal core configurations are found to consist of three fuel zones for a bare assembly and two fuel zones for a reflected assembly. The optimum fissile material density is determined to be inversely proportional to the thermal flux
Constrained Null Space Component Analysis for Semiblind Source Separation Problem.
Hwang, Wen-Liang; Lu, Keng-Shih; Ho, Jinn
2018-02-01
The blind source separation (BSS) problem extracts unknown sources from observations of their unknown mixtures. A current trend in BSS is the semiblind approach, which incorporates prior information on sources or how the sources are mixed. The constrained independent component analysis (ICA) approach has been studied to impose constraints on the famous ICA framework. We introduced an alternative approach based on the null space component (NCA) framework and referred to the approach as the c-NCA approach. We also presented the c-NCA algorithm that uses signal-dependent semidefinite operators, which is a bilinear mapping, as signatures for operator design in the c-NCA approach. Theoretically, we showed that the source estimation of the c-NCA algorithm converges with a convergence rate dependent on the decay of the sequence, obtained by applying the estimated operators on corresponding sources. The c-NCA can be formulated as a deterministic constrained optimization method, and thus, it can take advantage of solvers developed in optimization society for solving the BSS problem. As examples, we demonstrated electroencephalogram interference rejection problems can be solved by the c-NCA with proximal splitting algorithms by incorporating a sparsity-enforcing separation model and considering the case when reference signals are available.
Autonomous learning in gesture recognition by using lobe component analysis
Lu, Jian; Weng, Juyang
2007-02-01
Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.
Improvement of retinal blood vessel detection using morphological component analysis.
Imani, Elaheh; Javidi, Malihe; Pourreza, Hamid-Reza
2015-03-01
Detection and quantitative measurement of variations in the retinal blood vessels can help diagnose several diseases including diabetic retinopathy. Intrinsic characteristics of abnormal retinal images make blood vessel detection difficult. The major problem with traditional vessel segmentation algorithms is producing false positive vessels in the presence of diabetic retinopathy lesions. To overcome this problem, a novel scheme for extracting retinal blood vessels based on morphological component analysis (MCA) algorithm is presented in this paper. MCA was developed based on sparse representation of signals. This algorithm assumes that each signal is a linear combination of several morphologically distinct components. In the proposed method, the MCA algorithm with appropriate transforms is adopted to separate vessels and lesions from each other. Afterwards, the Morlet Wavelet Transform is applied to enhance the retinal vessels. The final vessel map is obtained by adaptive thresholding. The performance of the proposed method is measured on the publicly available DRIVE and STARE datasets and compared with several state-of-the-art methods. An accuracy of 0.9523 and 0.9590 has been respectively achieved on the DRIVE and STARE datasets, which are not only greater than most methods, but are also superior to the second human observer's performance. The results show that the proposed method can achieve improved detection in abnormal retinal images and decrease false positive vessels in pathological regions compared to other methods. Also, the robustness of the method in the presence of noise is shown via experimental result. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Analysis of tangible and intangible hotel service quality components
Directory of Open Access Journals (Sweden)
Marić Dražen
2016-01-01
Full Text Available The issue of service quality is one of the essential areas of marketing theory and practice, as high quality can lead to customer satisfaction and loyalty, i.e. successful business results. It is vital for any company, especially in services sector, to understand and grasp the consumers' expectations and perceptions pertaining to the broad range of factors affecting consumers' evaluation of services, their satisfaction and loyalty. Hospitality is a service sector where the significance of these elements grows exponentially. The aim of this study is to identify the significance of individual quality components in hospitality industry. The questionnaire used for gathering data comprised 19 tangible and 14 intangible attributes of service quality, which the respondents rated on a five-degree scale. The analysis also identified the factorial structure of the tangible and intangible elements of hotel service. The paper aims to contribute to the existing literature by pointing to the significance of tangible and intangible components of service quality. A very small number of studies conducted in hospitality and hotel management identify the sub-factors within these two dimensions of service quality. The paper also provides useful managerial implications. The obtained results help managers in hospitality to establish the service offers that consumers find the most important when choosing a given hotel.
Real analysis modern techniques and their applications
Folland, Gerald B
1999-01-01
An in-depth look at real analysis and its applications-now expanded and revised.This new edition of the widely used analysis book continues to cover real analysis in greater detail and at a more advanced level than most books on the subject. Encompassing several subjects that underlie much of modern analysis, the book focuses on measure and integration theory, point set topology, and the basics of functional analysis. It illustrates the use of the general theories and introduces readers to other branches of analysis such as Fourier analysis, distribution theory, and probability theory.This edi
Liang, Min
TDS transmitter and receiver. Good agreement between simulation and experiment is obtained. Finally, a design of a Principal Component Analysis (PCA) based microwave compressive sensing system using reconfigurable array is presented. An iterative beam synthesis process is used to realize the required radiation patterns obtained from PCA. A human body scanning system is studied as an example to investigate the compressive sensing performance using PCA generated radiation patterns. Optical images are used as surrogates for the RF images in implementation of the training PCA dictionary. Compared to random patterns based compressive sensing system, this PCA based compressive sensing system requires fewer numbers of measurements to achieve the same performance.
A first application of independent component analysis to extracting structure from stock returns.
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).
International Nuclear Information System (INIS)
Bunshah, R.F.
1976-01-01
A number of different techniques which range over several different aspects of materials research are covered in this volume. They are concerned with property evaluation of 4 0 K and below, surface characterization, coating techniques, techniques for the fabrication of composite materials, computer methods, data evaluation and analysis, statistical design of experiments and non-destructive test techniques. Topics covered in this part include internal friction measurements; nondestructive testing techniques; statistical design of experiments and regression analysis in metallurgical research; and measurement of surfaces of engineering materials
Analysis of European Union Economy in Terms of GDP Components
Directory of Open Access Journals (Sweden)
Simona VINEREAN
2013-12-01
Full Text Available The impact of the crises on national economies represented a subject of analysis and interest for a wide variety of research studies. Thus, starting from the GDP composition, the present research exhibits an analysis of the impact of European economies, at an EU level, of the events that followed the crisis of 2007 – 2008. Firstly, the research highlighted the existence of two groups of countries in 2012 in European Union, namely segments that were compiled in relation to the structure of the GDP’s components. In the second stage of the research, a factor analysis was performed on the resulted segments, that showed that the economies of cluster A are based more on personal consumption compared to the economies of cluster B, and in terms of government consumption, the situation is reversed. Thus, between the two groups of countries, a different approach regarding the role of fiscal policy in the economy can be noted, with a greater emphasis on savings in cluster B. Moreover, besides the two groups of countries resulted, Ireland and Luxembourg stood out because these two countries did not fit in either of the resulted segments and their economies are based, to a large extent, on the positive balance of the external balance.
Principal component analysis of 1/fα noise
International Nuclear Information System (INIS)
Gao, J.B.; Cao Yinhe; Lee, J.-M.
2003-01-01
Principal component analysis (PCA) is a popular data analysis method. One of the motivations for using PCA in practice is to reduce the dimension of the original data by projecting the raw data onto a few dominant eigenvectors with large variance (energy). Due to the ubiquity of 1/f α noise in science and engineering, in this Letter we study the prototypical stochastic model for 1/f α processes--the fractional Brownian motion (fBm) processes using PCA, and find that the eigenvalues from PCA of fBm processes follow a power-law, with the exponent being the key parameter defining the fBm processes. We also study random-walk-type processes constructed from DNA sequences, and find that the eigenvalue spectrum from PCA of those random-walk processes also follow power-law relations, with the exponent characterizing the correlation structures of the DNA sequence. In fact, it is observed that PCA can automatically remove linear trends induced by patchiness in the DNA sequence, hence, PCA has a similar capability to the detrended fluctuation analysis. Implications of the power-law distributed eigenvalue spectrum are discussed
Surface composition of biomedical components by ion beam analysis
International Nuclear Information System (INIS)
Kenny, M.J.; Wielunski, L.S.; Baxter, G.R.
1991-01-01
Materials used for replacement body parts must satisfy a number of requirements such as biocompatibility and mechanical ability to handle the task with regard to strength, wear and durability. When using a CVD coated carbon fibre reinforced carbon ball, the surface must be ion implanted with uniform dose of nitrogen ions in order to make it wear resistant. The mechanism by which the wear resistance is improved is one of radiation damage and the required dose of about 10 16 cm -2 can have a tolerance of about 20%. To implant a spherical surface requires manipulation of the sample within the beam and control system (either computer or manually operated) to enable uniform dose all the way from polar to equatorial regions on the surface. A manipulator has been designed and built for this purpose. In order to establish whether the dose is uniform, nuclear reaction analysis using the reaction 14 N(d,α) 12 C is an ideal method of profiling. By taking measurements at a number of points on the surface, the uniformity of nitrogen dose can be ascertained. It is concluded that both Rutherford Backscattering and Nuclear Reaction Analysis can be used for rapid analysis of surface composition of carbon based materials used for replacement body components. 2 refs., 2 figs
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.
Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation
Directory of Open Access Journals (Sweden)
Deniz Erdogmus
2004-10-01
Full Text Available Principal components analysis is an important and well-studied subject in statistics and signal processing. The literature has an abundance of algorithms for solving this problem, where most of these algorithms could be grouped into one of the following three approaches: adaptation based on Hebbian updates and deflation, optimization of a second-order statistical criterion (like reconstruction error or output variance, and fixed point update rules with deflation. In this paper, we take a completely different approach that avoids deflation and the optimization of a cost function using gradients. The proposed method updates the eigenvector and eigenvalue matrices simultaneously with every new sample such that the estimates approximately track their true values as would be calculated from the current sample estimate of the data covariance matrix. The performance of this algorithm is compared with that of traditional methods like Sanger's rule and APEX, as well as a structurally similar matrix perturbation-based method.
Preliminary study of soil permeability properties using principal component analysis
Yulianti, M.; Sudriani, Y.; Rustini, H. A.
2018-02-01
Soil permeability measurement is undoubtedly important in carrying out soil-water research such as rainfall-runoff modelling, irrigation water distribution systems, etc. It is also known that acquiring reliable soil permeability data is rather laborious, time-consuming, and costly. Therefore, it is desirable to develop the prediction model. Several studies of empirical equations for predicting permeability have been undertaken by many researchers. These studies derived the models from areas which soil characteristics are different from Indonesian soil, which suggest a possibility that these permeability models are site-specific. The purpose of this study is to identify which soil parameters correspond strongly to soil permeability and propose a preliminary model for permeability prediction. Principal component analysis (PCA) was applied to 16 parameters analysed from 37 sites consist of 91 samples obtained from Batanghari Watershed. Findings indicated five variables that have strong correlation with soil permeability, and we recommend a preliminary permeability model, which is potential for further development.
Principal Component Analysis for Normal-Distribution-Valued Symbolic Data.
Wang, Huiwen; Chen, Meiling; Shi, Xiaojun; Li, Nan
2016-02-01
This paper puts forward a new approach to principal component analysis (PCA) for normal-distribution-valued symbolic data, which has a vast potential of applications in the economic and management field. We derive a full set of numerical characteristics and variance-covariance structure for such data, which forms the foundation for our analytical PCA approach. Our approach is able to use all of the variance information in the original data than the prevailing representative-type approach in the literature which only uses centers, vertices, etc. The paper also provides an accurate approach to constructing the observations in a PC space based on the linear additivity property of normal distribution. The effectiveness of the proposed method is illustrated by simulated numerical experiments. At last, our method is applied to explain the puzzle of risk-return tradeoff in China's stock market.
Iris recognition based on robust principal component analysis
Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong
2014-11-01
Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.
Size distribution measurements and chemical analysis of aerosol components
Energy Technology Data Exchange (ETDEWEB)
Pakkanen, T.A.
1995-12-31
The principal aims of this work were to improve the existing methods for size distribution measurements and to draw conclusions about atmospheric and in-stack aerosol chemistry and physics by utilizing size distributions of various aerosol components measured. A sample dissolution with dilute nitric acid in an ultrasonic bath and subsequent graphite furnace atomic absorption spectrometric analysis was found to result in low blank values and good recoveries for several elements in atmospheric fine particle size fractions below 2 {mu}m of equivalent aerodynamic particle diameter (EAD). Furthermore, it turned out that a substantial amount of analyses associated with insoluble material could be recovered since suspensions were formed. The size distribution measurements of in-stack combustion aerosols indicated two modal size distributions for most components measured. The existence of the fine particle mode suggests that a substantial fraction of such elements with two modal size distributions may vaporize and nucleate during the combustion process. In southern Norway, size distributions of atmospheric aerosol components usually exhibited one or two fine particle modes and one or two coarse particle modes. Atmospheric relative humidity values higher than 80% resulted in significant increase of the mass median diameters of the droplet mode. Important local and/or regional sources of As, Br, I, K, Mn, Pb, Sb, Si and Zn were found to exist in southern Norway. The existence of these sources was reflected in the corresponding size distributions determined, and was utilized in the development of a source identification method based on size distribution data. On the Finnish south coast, atmospheric coarse particle nitrate was found to be formed mostly through an atmospheric reaction of nitric acid with existing coarse particle sea salt but reactions and/or adsorption of nitric acid with soil derived particles also occurred. Chloride was depleted when acidic species reacted
Application of functional analysis techniques to supervisory systems
International Nuclear Information System (INIS)
Lambert, Manuel; Riera, Bernard; Martel, Gregory
1999-01-01
The aim of this paper is to apply firstly two interesting functional analysis techniques for the design of supervisory systems for complex processes, and secondly to discuss the strength and the weaknesses of each of them. Two functional analysis techniques have been applied, SADT (Structured Analysis and Design Technique) and FAST (Functional Analysis System Technique) on a process, an example of a Water Supply Process Control (WSPC) system. These techniques allow a functional description of industrial processes. The paper briefly discusses the functions of a supervisory system and some advantages of the application of functional analysis for the design of a 'human' centered supervisory system. Then the basic principles of the two techniques applied on the WSPC system are presented. Finally, the different results obtained from the two techniques are discussed
IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES
Institute of Scientific and Technical Information of China (English)
纳瑟; 刘重庆
2002-01-01
A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.
SNIa detection in the SNLS photometric analysis using Morphological Component Analysis
Energy Technology Data Exchange (ETDEWEB)
Möller, A.; Ruhlmann-Kleider, V.; Neveu, J.; Palanque-Delabrouille, N. [Irfu, SPP, CEA Saclay, F-91191 Gif sur Yvette cedex (France); Lanusse, F.; Starck, J.-L., E-mail: anais.moller@cea.fr, E-mail: vanina.ruhlmann-kleider@cea.fr, E-mail: francois.lanusse@cea.fr, E-mail: jeremy.neveu@cea.fr, E-mail: nathalie.palanque-delabrouille@cea.fr, E-mail: jstarck@cea.fr [Laboratoire AIM, UMR CEA-CNRS-Paris 7, Irfu, SAp, CEA Saclay, F-91191 Gif sur Yvette cedex (France)
2015-04-01
Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000 detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.
MCNP perturbation technique for criticality analysis
International Nuclear Information System (INIS)
McKinney, G.W.; Iverson, J.L.
1995-01-01
The differential operator perturbation technique has been incorporated into the Monte Carlo N-Particle transport code MCNP and will become a standard feature of future releases. This feature includes first and/or second order terms of the Taylor Series expansion for response perturbations related to cross-section data (i.e., density, composition, etc.). Criticality analyses can benefit from this technique in that predicted changes in the track-length tally estimator of K eff may be obtained for multiple perturbations in a single run. A key advantage of this method is that a precise estimate of a small change in response (i.e., < 1%) is easily obtained. This technique can also offer acceptable accuracy, to within a few percent, for up to 20-30% changes in a response
Data Analysis Techniques for Physical Scientists
Pruneau, Claude A.
2017-10-01
Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.
Comparison of correlation analysis techniques for irregularly sampled time series
Directory of Open Access Journals (Sweden)
K. Rehfeld
2011-06-01
Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.
All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.
We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ^{18}O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.
Schreurs, B.W.; Arts, J.J.C.; Verdonschot, N.J.J.; Buma, P.; Slooff, T.J.J.H.; Gardeniers, J.W.M.
2006-01-01
BACKGROUND: The purpose of this study was to evaluate the clinical and radiographic outcomes of revision of the femoral component of a hip arthroplasty with use of an impaction bone-grafting technique and a cemented polished stem. METHODS: Thirty-three consecutive femoral reconstructions that were
Surface analysis and techniques in biology
Smentkowski, Vincent S
2014-01-01
This book highlights state-of-the-art surface analytical instrumentation, advanced data analysis tools, and the use of complimentary surface analytical instrumentation to perform a complete analysis of biological systems.
International Nuclear Information System (INIS)
Vasconcelos, Vanderley de; Soares, Wellington Antonio; Marques, Raíssa Oliveira; Silva Júnior, Silvério Ferreira da; Raso, Amanda Laureano
2017-01-01
Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. NDI is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI methods are reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components. Among these can be highlighted Failure Modes and Effects Analysis (FMEA) and THERP (Technique for Human Error Rate Prediction). The application of these techniques is illustrated in an example of qualitative and quantitative studies to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues. (author)
Energy Technology Data Exchange (ETDEWEB)
Vasconcelos, Vanderley de; Soares, Wellington Antonio; Marques, Raíssa Oliveira; Silva Júnior, Silvério Ferreira da; Raso, Amanda Laureano, E-mail: vasconv@cdtn.br, E-mail: soaresw@cdtn.br, E-mail: raissaomarques@gmail.com, E-mail: silvasf@cdtn.br, E-mail: amandaraso@hotmail.com [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2017-07-01
Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. NDI is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI methods are reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components. Among these can be highlighted Failure Modes and Effects Analysis (FMEA) and THERP (Technique for Human Error Rate Prediction). The application of these techniques is illustrated in an example of qualitative and quantitative studies to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues. (author)
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. The structural model includes five lumped masses (floors) connected by four elastic members. The base is supported by three translational springs and two horizontal torsional springs. In general, the mass center and shear center of a building floor are distinct locations. Hence, inertia forces, which act at the mass center, induce twisting in the structure. Through this induced torsion, the lateral (x and y) displacements of the mass elements are coupled. The ground motion components used for this study are artificial earthquake records generated from recorded accelerograms by a spectrum modification technique. The accelerograms have response spectra which are compatible with U.S. NRC Regulatory Guide 1.60. 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 modal 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 sum of the squares, the double sum approach, the method of closely spaced modes, and Lin's method
A Principal Component Analysis of 39 Scientific Impact Measures
Bollen, Johan; Van de Sompel, Herbert
2009-01-01
Background The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. Methodology We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Conclusions Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution. PMID:19562078
Cnn Based Retinal Image Upscaling Using Zero Component Analysis
Nasonov, A.; Chesnakov, K.; Krylov, A.
2017-05-01
The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.
A principal component analysis of 39 scientific impact measures.
Directory of Open Access Journals (Sweden)
Johan Bollen
Full Text Available BACKGROUND: The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. METHODOLOGY: We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. CONCLUSIONS: Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.
International Nuclear Information System (INIS)
Chen, Zhenmao
2000-03-01
In this report, research works performed in the Structural Safety Engineering Group of OEC/JNC are summarized as the final report of the doctoral fellowship. The main objective of this study is for the enhancement of the nondestructive evaluation techniques for structural components of both magnetic and nonmagnetic material. Studies in three topics have been carried out aiming at the quantitative evaluation of crack with the eddy current testing and the validation of a natural magnetic field based NDE method for detecting mechanical damages in a paramagnetic material. In the first part of the study, an approach to the reconstruction of the natural crack was proposed and implemented with an idealized crack model for its validation. In the second part, the correlation of the natural magnetization and the mechanical damages in the SUS304 stainless steel was investigated by using an experimental approach. In part 3, an inverse method of the measured magnetic fields is proposed for the reconstruction of magnetic charges in the inspected material by using an optimization method and wavelet. As the first work, an approach to the reconstruction of an idealized natural crack of non-vanishing conductivity is proposed with use of signals of eddy current testing. Two numerical models are introduced at first for modeling the natural crack in order to represented it with a set of crack parameters. A method for the rapid prediction of the eddy current testing signals coming from these idealized cracks is given then by extending a knowledge based fast forward solver to the case of a non-vanishing conductivity. Based on this fast forward solver, the inverse algorithm of conjugate gradient method is updated to identify the crack parameters. Several examples are presented finally as a validation of the proposed strategy. The results show that both the two numerical models can give reasonable reconstruction results for signal of low noise. The model concerning the touch of crack
Survey of immunoassay techniques for biological analysis
International Nuclear Information System (INIS)
Burtis, C.A.
1986-10-01
Immunoassay is a very specific, sensitive, and widely applicable analytical technique. Recent advances in genetic engineering have led to the development of monoclonal antibodies which further improves the specificity of immunoassays. Originally, radioisotopes were used to label the antigens and antibodies used in immunoassays. However, in the last decade, numerous types of immunoassays have been developed which utilize enzymes and fluorescent dyes as labels. Given the technical, safety, health, and disposal problems associated with using radioisotopes, immunoassays that utilize the enzyme and fluorescent labels are rapidly replacing those using radioisotope labels. These newer techniques are as sensitive, are easily automated, have stable reagents, and do not have a disposal problem. 6 refs., 1 fig., 2 tabs
Quantitative Analysis of TDLUs using Adaptive Morphological Shape Techniques.
Rosebrock, Adrian; Caban, Jesus J; Figueroa, Jonine; Gierach, Gretchen; Linville, Laura; Hewitt, Stephen; Sherman, Mark
2013-03-29
Within the complex branching system of the breast, terminal duct lobular units (TDLUs) are the anatomical location where most cancer originates. With aging, TDLUs undergo physiological involution, reflected in a loss of structural components (acini) and a reduction in total number. Data suggest that women undergoing benign breast biopsies that do not show age appropriate involution are at increased risk of developing breast cancer. To date, TDLU assessments have generally been made by qualitative visual assessment, rather than by objective quantitative analysis. This paper introduces a technique to automatically estimate a set of quantitative measurements and use those variables to more objectively describe and classify TDLUs. To validate the accuracy of our system, we compared the computer-based morphological properties of 51 TDLUs in breast tissues donated for research by volunteers in the Susan G. Komen Tissue Bank and compared results to those of a pathologist, demonstrating 70% agreement. Secondly, in order to show that our method is applicable to a wider range of datasets, we analyzed 52 TDLUs from biopsies performed for clinical indications in the National Cancer Institute's Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project and obtained 82% correlation with visual assessment. Lastly, we demonstrate the ability to uncover novel measures when researching the structural properties of the acini by applying machine learning and clustering techniques. Through our study we found that while the number of acini per TDLU increases exponentially with the TDLU diameter, the average elongation and roundness remain constant.
Hybrid chemical and nondestructive-analysis technique
International Nuclear Information System (INIS)
Hsue, S.T.; Marsh, S.F.; Marks, T.
1982-01-01
A hybrid chemical/NDA technique has been applied at the Los Alamos National Laboratory to the assay of plutonium in ion-exchange effluents. Typical effluent solutions contain low concentrations of plutonium and high concentrations of americium. A simple trioctylphosphine oxide (TOPO) separation can remove 99.9% of the americium. The organic phase that contains the separated plutonium can be accurately assayed by monitoring the uranium L x-ray intensities
Failure characteristic analysis of a component on standby state
International Nuclear Information System (INIS)
Shin, Sungmin; Kang, Hyungook
2013-01-01
Periodic operations for a specific type of component, however, can accelerate aging effects which increase component unavailability. For the other type of components, the aging effect caused by operation can be ignored. Therefore frequent operations can decrease component unavailability. Thus, to get optimum unavailability proper operation period and method should be studied considering the failure characteristics of each component. The information of component failure is given according to the main causes of failure depending on time flow. However, to get the optimal unavailability, proper interval of operation for inspection should be decided considering the time dependent and independent causes together. According to this study, gradually shorter operation interval for inspection is better to get the optimal component unavailability than that of specific period
International Nuclear Information System (INIS)
Di Pietro, E.; Visca, E.; Orsini, A.; Sacchetti, M.; Borruto, T.M.R.; Varone, P.; Vesprini, R.
1995-01-01
The design of plasma-facing components for ITER, as for any of the envisaged next-step machines, relies heavily on the use of brazed junctions to couple armour materials to the heat sink and cooling tubes. Moreover, the typical number of brazed components and the envisaged effects of local overheating due to failure in a single brazed junction stress the importance of having a set of NDE techniques developed that can ensure the flawless quality of the joint. The qualification and application of two NDE techniques (ultrasonic and thermographic analysis) for inspection of CFC-to-metal joints is described with particular regard to the annular geometry typical of macroblock/monoblock solutions for divertor high-heat-flux components. The results of the eddy current inspection are not reported. The development has been focused specifically on the joint between carbon-fiber composite and TZM molybdenum alloy; techniques for the production of reference defect samples have been devised and a set of reference defect samples produced. The comparative results of the NDE inspections are reported and discussed, also on the basis of the destructive examination of the samples. The nature and size of relevant and detectable defects are discussed together with hints for a possible NDE strategy for divertor high-heat-flux components
Quality of Life after Ventral Hernia Repair with Endoscopic Component Separation Technique
DEFF Research Database (Denmark)
Thomsen, C Ø; Brøndum, T L; Jørgensen, Lars Nannestad
2016-01-01
of the hernia size. Demographic data, operative information, and postoperative complications were recorded. All patients completed two similar questionnaires regarding their function level, cosmetic satisfaction, analgesic medication, alcohol consumption, and self-estimated physical and mental health before...... center operated on with endoscopic components separation. MATERIAL AND METHODS: A total of 19 consecutive patients scheduled for open hernia repair with endoscopic components separation from October 2010 to June 2012 were included. All procedures included endoscopic components separation because...... and after the hernia repair. Patients were assessed as outpatient median 2 months and 16 months after operation for exclusion of hernia recurrence and completion of the postoperative questionnaire. RESULTS AND CONCLUSIONS: Operating room time was median 204 min and correlated significantly with the hernia...
Data analysis techniques for gravitational wave observations
Indian Academy of Sciences (India)
Astrophysical sources of gravitational waves fall broadly into three categories: (i) transient and bursts, (ii) periodic or continuous wave and (iii) stochastic. Each type of source requires a different type of data analysis strategy. In this talk various data analysis strategies will be reviewed. Optimal filtering is used for extracting ...
Directory of Open Access Journals (Sweden)
Zhisheng Xie
2013-01-01
Full Text Available Volatile components from Exocarpium Citri Grandis (ECG were, respectively, extracted by three methods, that is, steam distillation (SD, headspace solid-phase microextraction (HS-SPME, and solvent extraction (SE. A total of 81 compounds were identified by gas chromatography-mass spectrometry including 77 (SD, 56 (HS-SPME, and 48 (SE compounds, respectively. Despite of the extraction method, terpenes (39.98~57.81% were the main volatile components of ECG, mainly germacrene-D, limonene, 2,6,8,10,14-hexadecapentaene, 2,6,11,15-tetramethyl-, (E,E,E-, and trans-caryophyllene. Comparison was made among the three methods in terms of extraction profile and property. SD relatively gave an entire profile of volatile in ECG by long-time extraction; SE enabled the analysis of low volatility and high molecular weight compounds but lost some volatiles components; HS-SPME generated satisfactory extraction efficiency and gave similar results to those of SD at analytical level when consuming less sample amount, shorter extraction time, and simpler procedure. Although SD and SE were treated as traditionally preparative extractive techniques for volatiles in both small batches and large scale, HS-SPME coupled with GC/MS could be useful and appropriative for the rapid extraction and qualitative analysis of volatile components from medicinal plants at analytical level.
Energy Technology Data Exchange (ETDEWEB)
Palacio Garcia, L.; Andrzejak, R.; Prchkovska, V.; Rodrigues, P.
2016-07-01
It is commonly thought that our brain is not active when it does not receive any external input. However, during rest, there are still certain distant regions of the brain that are functionally correlated between them: the so-called resting-state networks. This functional connectivity of the brain is disrupted in many neurological diseases. In particular, it has been shown that one of the most studied resting-state networks (the default-mode network) is affected in multiple sclerosis, which is the most common disabling neurological condition affecting the central nervous system of young adults. In this work, I focus on the study of the differences in the resting-state networks between multiple sclerosis patients and healthy volunteers. In order to study the effects of multiple sclerosis on the functional connectivity of the brain, a numerical method known as independent component analysis (ICA) is applied. This technique divides the resting-state fMRI data into independent components. Nonetheless, noise, which could be due to head motion or physiological artifacts, may corrupt the data by indicating a false activation. Therefore, I create a web user interface that allows the user to manually classify all the independent components for a given subject. Eventually, the components classified as noise should be removed from the functional data in order to prevent them from taking part in any further analysis. (Author)
A multi-dimensional functional principal components analysis of EEG data.
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.
Levis, Denise M; Westbrook, Kyresa
2013-01-01
Many health organizations and practitioners in the United States promote preconception health (PCH) to consumers. However, summaries and evaluations of PCH promotional activities are limited. We conducted a content analysis of PCH health education materials collected from local-, state-, national-, and federal-level partners by using an existing database of partners, outreach to maternal and child health organizations, and a snowball sampling technique. Not applicable. Not applicable. Thirty-two materials were included for analysis, based on inclusion/exclusion criteria. A codebook guided coding of materials' characteristics (type, authorship, language, cost), use of marketing and behavioral strategies to reach the target population (target audience, message framing, call to action), and inclusion of PCH subject matter (clinical-behavioral components). The self-assessment of PCH behaviors was the most common material (28%) to appear in the sample. Most materials broadly targeted women, and there was a near-equal distribution in targeting by pregnancy planning status segments (planners and nonplanners). "Practicing PCH benefits the baby's health" was the most common message frame used. Materials contained a wide range of clinical-behavioral components. Strategic targeting of subgroups of consumers is an important but overlooked strategy. More research is needed around PCH components, in terms of packaging and increasing motivation, which could guide use and placement of clinical-behavioral components within promotional materials.
International Nuclear Information System (INIS)
Souza, Iracelia Torres de Toledo e
1977-01-01
When human plasma is filtered on Sephadex G-SO fine, insulin immunoreactivity is recovered in two peaks: 'big insulin', the higher molecular weight component and 'little insulin', the lower molecular component, having elution volumes that correspond to those of porcine proinsulin 125 I and porcine insulin 125 I respectively. The presence of another form of immunoreactive insulin 'big big insulin' was detected from an insuloma suspect and its elution pattern corresponding to serum albumin. The eluates correspondent to 'big' and 'little' insulin as well as 'big big' component were assayed by radioimmunoassay using crystalline human insulin as a standard, porcine insulin 125 tracer and anti insulin serum. The antibody, raised in guinea-pigs, was sensitive and potent being adequate for the assay. The reactivity of insulin and proinsulin was tested against the antibody. The relative proportions of several components of total immunoreactive insulin in plasma were studied in basal conditions in five normal subjects and in the patient JSC with pancreatic insulin-secreting tumor as well as after glucose stimuli in all tolbutamide in JSC. (author)
Examination of uranium recovery technique from sea water using natural components for adsorbent
International Nuclear Information System (INIS)
Tanaka, Nobuyuki; Masaki, Hiroyuki; Shimizu, Takao; Tokiwai, Moriyasu
2010-01-01
In this study, we investigated the potency of natural components as adsorbent for uranium recovery from seawater. In addition, cost evaluation of uranium recovery from seawater using natural components for adsorbents was performed. Furthermore, new ideas on reservation system of adsorbents at sea area were proposed. Several poly-phenols were selected as adsorbent reagents, then they were adsorbed on the support such as cotton fiber by several methods as the followings; chemical syntheses, electrical beam irradiation, and traditional dyeing. As a result, the adsorbent made by traditional dyeing method using gallnut tannin as natural component, was showed high performance for uranium recovery from seawater on only the first. It was evaluated that traditional dyeing method had also advantage in the manufacturing cost, comparing with earlier method. Additionally, it was considered that reservation system of adsorbent at sea was able to be simplified compared with earlier system. Consequently, uranium recovery from sea water using natural components as adsorbent proposed in this study had a potency of practical use. (author)
Visualization techniques for malware behavior analysis
Grégio, André R. A.; Santos, Rafael D. C.
2011-06-01
Malware spread via Internet is a great security threat, so studying their behavior is important to identify and classify them. Using SSDT hooking we can obtain malware behavior by running it in a controlled environment and capturing interactions with the target operating system regarding file, process, registry, network and mutex activities. This generates a chain of events that can be used to compare them with other known malware. In this paper we present a simple approach to convert malware behavior into activity graphs and show some visualization techniques that can be used to analyze malware behavior, individually or grouped.
INVERSE FILTERING TECHNIQUES IN SPEECH ANALYSIS
African Journals Online (AJOL)
Dr Obe
domain or in the frequency domain. However their .... computer to speech analysis led to important elaborations ... tool for the estimation of formant trajectory (10), ... prediction Linear prediction In effect determines the filter .... Radio Res. Lab.
Techniques for Intelligence Analysis of Networks
National Research Council Canada - National Science Library
Cares, Jeffrey R
2005-01-01
...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...
Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M
2014-04-15
Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject "at rest"). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing "signal" (brain activity) can be distinguished form the "noise" components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX ("FMRIB's ICA-based X-noiseifier"), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original
The Network Protocol Analysis Technique in Snort
Wu, Qing-Xiu
Network protocol analysis is a network sniffer to capture data for further analysis and understanding of the technical means necessary packets. Network sniffing is intercepted by packet assembly binary format of the original message content. In order to obtain the information contained. Required based on TCP / IP protocol stack protocol specification. Again to restore the data packets at protocol format and content in each protocol layer. Actual data transferred, as well as the application tier.
Hallin, M.; Hörmann, S.; Piegorsch, W.; El Shaarawi, A.
2012-01-01
Principal Components are probably the best known and most widely used of all multivariate analysis techniques. The essential idea consists in performing a linear transformation of the observed k-dimensional variables in such a way that the new variables are vectors of k mutually orthogonal
Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen
2016-01-01
Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.
Major component analysis of dynamic networks of physiologic organ interactions
International Nuclear Information System (INIS)
Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P
2015-01-01
The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)
Sensor Failure Detection of FASSIP System using Principal Component Analysis
Sudarno; Juarsa, Mulya; Santosa, Kussigit; Deswandri; Sunaryo, Geni Rina
2018-02-01
In the nuclear reactor accident of Fukushima Daiichi in Japan, the damages of core and pressure vessel were caused by the failure of its active cooling system (diesel generator was inundated by tsunami). Thus researches on passive cooling system for Nuclear Power Plant are performed to improve the safety aspects of nuclear reactors. The FASSIP system (Passive System Simulation Facility) is an installation used to study the characteristics of passive cooling systems at nuclear power plants. The accuracy of sensor measurement of FASSIP system is essential, because as the basis for determining the characteristics of a passive cooling system. In this research, a sensor failure detection method for FASSIP system is developed, so the indication of sensor failures can be detected early. The method used is Principal Component Analysis (PCA) to reduce the dimension of the sensor, with the Squarred Prediction Error (SPE) and statistic Hotteling criteria for detecting sensor failure indication. The results shows that PCA method is capable to detect the occurrence of a failure at any sensor.
A meta-analysis of executive components of working memory.
Nee, Derek Evan; Brown, Joshua W; Askren, Mary K; Berman, Marc G; Demiralp, Emre; Krawitz, Adam; Jonides, John
2013-02-01
Working memory (WM) enables the online maintenance and manipulation of information and is central to intelligent cognitive functioning. Much research has investigated executive processes of WM in order to understand the operations that make WM "work." However, there is yet little consensus regarding how executive processes of WM are organized. Here, we used quantitative meta-analysis to summarize data from 36 experiments that examined executive processes of WM. Experiments were categorized into 4 component functions central to WM: protecting WM from external distraction (distractor resistance), preventing irrelevant memories from intruding into WM (intrusion resistance), shifting attention within WM (shifting), and updating the contents of WM (updating). Data were also sorted by content (verbal, spatial, object). Meta-analytic results suggested that rather than dissociating into distinct functions, 2 separate frontal regions were recruited across diverse executive demands. One region was located dorsally in the caudal superior frontal sulcus and was especially sensitive to spatial content. The other was located laterally in the midlateral prefrontal cortex and showed sensitivity to nonspatial content. We propose that dorsal-"where"/ventral-"what" frameworks that have been applied to WM maintenance also apply to executive processes of WM. Hence, WM can largely be simplified to a dual selection model.
Principal Component Analysis of Process Datasets with Missing Values
Directory of Open Access Journals (Sweden)
Kristen A. Severson
2017-07-01
Full Text Available Datasets with missing values arising from causes such as sensor failure, inconsistent sampling rates, and merging data from different systems are common in the process industry. Methods for handling missing data typically operate during data pre-processing, but can also occur during model building. This article considers missing data within the context of principal component analysis (PCA, which is a method originally developed for complete data that has widespread industrial application in multivariate statistical process control. Due to the prevalence of missing data and the success of PCA for handling complete data, several PCA algorithms that can act on incomplete data have been proposed. Here, algorithms for applying PCA to datasets with missing values are reviewed. A case study is presented to demonstrate the performance of the algorithms and suggestions are made with respect to choosing which algorithm is most appropriate for particular settings. An alternating algorithm based on the singular value decomposition achieved the best results in the majority of test cases involving process datasets.
Finite element elastic-plastic analysis of LMFBR components
International Nuclear Information System (INIS)
Levy, A.; Pifko, A.; Armen, H. Jr.
1978-01-01
The present effort involves the development of computationally efficient finite element methods for accurately predicting the isothermal elastic-plastic three-dimensional response of thick and thin shell structures subjected to mechanical and thermal loads. This work will be used as the basis for further development of analytical tools to be used to verify the structural integrity of liquid metal fast breeder reactor (LMFBR) components. The methods presented here have been implemented into the three-dimensional solid element module (HEX) of the Grumman PLANS finite element program. These methods include the use of optimal stress points as well as a variable number of stress points within an element. This allows monitoring the stress history at many points within an element and hence provides an accurate representation of the elastic-plastic boundary using a minimum number of degrees of freedom. Also included is an improved thermal stress analysis capability in which the temperature variation and corresponding thermal strain variation are represented by the same functional form as the displacement variation. Various problems are used to demonstrate these improved capabilities. (Auth.)
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...
Uncertainty analysis technique for OMEGA Dante measurementsa)
May, M. J.; Widmann, K.; Sorce, C.; Park, H.-S.; Schneider, M.
2010-10-01
The Dante is an 18 channel x-ray filtered diode array which records the spectrally and temporally resolved radiation flux from various targets (e.g., hohlraums, etc.) at x-ray energies between 50 eV and 10 keV. It is a main diagnostic installed on the OMEGA laser facility at the Laboratory for Laser Energetics, University of Rochester. The absolute flux is determined from the photometric calibration of the x-ray diodes, filters and mirrors, and an unfold algorithm. Understanding the errors on this absolute measurement is critical for understanding hohlraum energetic physics. We present a new method for quantifying the uncertainties on the determined flux using a Monte Carlo parameter variation technique. This technique combines the uncertainties in both the unfold algorithm and the error from the absolute calibration of each channel into a one sigma Gaussian error function. One thousand test voltage sets are created using these error functions and processed by the unfold algorithm to produce individual spectra and fluxes. Statistical methods are applied to the resultant set of fluxes to estimate error bars on the measurements.
Uncertainty analysis technique for OMEGA Dante measurements
International Nuclear Information System (INIS)
May, M. J.; Widmann, K.; Sorce, C.; Park, H.-S.; Schneider, M.
2010-01-01
The Dante is an 18 channel x-ray filtered diode array which records the spectrally and temporally resolved radiation flux from various targets (e.g., hohlraums, etc.) at x-ray energies between 50 eV and 10 keV. It is a main diagnostic installed on the OMEGA laser facility at the Laboratory for Laser Energetics, University of Rochester. The absolute flux is determined from the photometric calibration of the x-ray diodes, filters and mirrors, and an unfold algorithm. Understanding the errors on this absolute measurement is critical for understanding hohlraum energetic physics. We present a new method for quantifying the uncertainties on the determined flux using a Monte Carlo parameter variation technique. This technique combines the uncertainties in both the unfold algorithm and the error from the absolute calibration of each channel into a one sigma Gaussian error function. One thousand test voltage sets are created using these error functions and processed by the unfold algorithm to produce individual spectra and fluxes. Statistical methods are applied to the resultant set of fluxes to estimate error bars on the measurements.
Uncertainty Analysis Technique for OMEGA Dante Measurements
International Nuclear Information System (INIS)
May, M.J.; Widmann, K.; Sorce, C.; Park, H.; Schneider, M.
2010-01-01
The Dante is an 18 channel X-ray filtered diode array which records the spectrally and temporally resolved radiation flux from various targets (e.g. hohlraums, etc.) at X-ray energies between 50 eV to 10 keV. It is a main diagnostics installed on the OMEGA laser facility at the Laboratory for Laser Energetics, University of Rochester. The absolute flux is determined from the photometric calibration of the X-ray diodes, filters and mirrors and an unfold algorithm. Understanding the errors on this absolute measurement is critical for understanding hohlraum energetic physics. We present a new method for quantifying the uncertainties on the determined flux using a Monte-Carlo parameter variation technique. This technique combines the uncertainties in both the unfold algorithm and the error from the absolute calibration of each channel into a one sigma Gaussian error function. One thousand test voltage sets are created using these error functions and processed by the unfold algorithm to produce individual spectra and fluxes. Statistical methods are applied to the resultant set of fluxes to estimate error bars on the measurements.
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.
Shah, Syed Muhammad Saqlain; Batool, Safeera; Khan, Imran; Ashraf, Muhammad Usman; Abbas, Syed Hussnain; Hussain, Syed Adnan
2017-09-01
Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.
Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis
DEFF Research Database (Denmark)
Flores Alsina, Xavier; Comas, J.; Rodríguez-Roda, I.
2007-01-01
The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant...... analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii......) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation...
Analysis of Jordanian Cigarettes Using XRF Techniques
International Nuclear Information System (INIS)
Kullab, M.; Ismail, A.; AL-kofahi, M.
2002-01-01
Sixteen brands of Jordanian cigarettes were analyzed using X-ray Fluorescence (XRF) techniques. These cigarettes were found to contain the elements: Si, S, Cl, K, Ca, P, Ti, Mn, Fe, Cu, Zn, Br.Rb and Sr. The major elements with concentrations of more than 1% by weight were Cl,K and Ca. The elements with minor concentrations, Between 0.1 and 1% by weight, were Si, S and P. The trace elements with concentrations below 0.1% by weight were Ti, Mn, Fe, Cu, Zn, Br, Rb and Sr. The toxicity of some trace elements, like Br, Rb, and Sr, which are present in some brands of Jordanian cigarettes, is discussed. (Author's) 24 refs., 1 tab., 1 fig
International Nuclear Information System (INIS)
Hirsch, E.; Mayer, K.H.; Rodrian, U.; Scheidemantel, N.; Schweizer, R.
1990-07-01
Technically and economically important machinery components (helical gear wheels, camshafts, rams, valve rockers) were to be optimized with regard to their wear behaviour under operation-oriented load conditions, and the process parameters required both for peripheral layer heating and surface coating were to be determined. Based on earlier experiments, the treatment parameters and the basic materials were varied. The layer structure was studied, characterized and correlated wi the wear behaviour. The wearing parts were activated in the reactor by thermal neutrons, or in the cyclotron by charged particles. By labelling various parts by means of different radioisotopes, up to three components may be measured at the same time in practice, provided that the circumstances are favourable. (BBR) [de
Closure of giant omphaloceles by the abdominal wall component separation technique in infants.
Eijck, F.C. van; Blaauw, I. de; Bleichrodt, R.P.; Rieu, P.N.M.A.; Staak, F.H.J.M. van der; Wijnen, M.H.W.A.; Wijnen, R.M.H.
2008-01-01
BACKGROUND/PURPOSE: Several techniques have been described to repair giant omphaloceles. There is no procedure considered to be the criterion standard worldwide. The aim of the present prospective study was to analyze the early and late results of secondary closure of giant omphaloceles using the
Trimming of mammalian transcriptional networks using network component analysis
Directory of Open Access Journals (Sweden)
Liao James C
2010-10-01
Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm
Decentralized control using compositional analysis techniques
Kerber, F.; van der Schaft, A. J.
2011-01-01
Decentralized control strategies aim at achieving a global control target by means of distributed local controllers acting on individual subsystems of the overall plant. In this sense, decentralized control is a dual problem to compositional analysis where a global verification task is decomposed
Evaluating Dynamic Analysis Techniques for Program Comprehension
Cornelissen, S.G.M.
2009-01-01
Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.
Data analysis of x-ray fluorescence holography by subtracting normal component from inverse hologram
International Nuclear Information System (INIS)
Happo, Naohisa; Hayashi, Kouichi; Hosokawa, Shinya
2010-01-01
X-ray fluorescence holography (XFH) is a powerful technique for determining three-dimensional local atomic arrangements around a specific fluorescing element. However, the raw experimental hologram is predominantly a mixed hologram, i.e., a mixture of hologram generated in both normal and inverse modes, which produces unreliable atomic images. In this paper, we propose a practical subtraction method of the normal component from the inverse XFH data by a Fourier transform for the calculated hologram of a model ZnTe cluster. Many spots originating from the normal components could be properly removed using a mask function, and clear atomic images were reconstructed at adequate positions of the model cluster. This method was successfully applied to the analysis of experimental ZnTe single crystal XFH data. (author)
Directory of Open Access Journals (Sweden)
Reinhold Orglmeister
2010-01-01
Full Text Available When a number of speakers are simultaneously active, for example in meetings or noisy public places, the sources of interest need to be separated from interfering speakers and from each other in order to be robustly recognized. Independent component analysis (ICA has proven a valuable tool for this purpose. However, ICA outputs can still contain strong residual components of the interfering speakers whenever noise or reverberation is high. In such cases, nonlinear postprocessing can be applied to the ICA outputs, for the purpose of reducing remaining interferences. In order to improve robustness to the artefacts and loss of information caused by this process, recognition can be greatly enhanced by considering the processed speech feature vector as a random variable with time-varying uncertainty, rather than as deterministic. The aim of this paper is to show the potential to improve recognition of multiple overlapping speech signals through nonlinear postprocessing together with uncertainty-based decoding techniques.
Analysis of Minor Component Segregation in Ternary Powder Mixtures
Directory of Open Access Journals (Sweden)
Asachi Maryam
2017-01-01
Full Text Available In many powder handling operations, inhomogeneity in powder mixtures caused by segregation could have significant adverse impact on the quality as well as economics of the production. Segregation of a minor component of a highly active substance could have serious deleterious effects, an example is the segregation of enzyme granules in detergent powders. In this study, the effects of particle properties and bulk cohesion on the segregation tendency of minor component are analysed. The minor component is made sticky while not adversely affecting the flowability of samples. The segregation extent is evaluated using image processing of the photographic records taken from the front face of the heap after the pouring process. The optimum average sieve cut size of components for which segregation could be reduced is reported. It is also shown that the extent of segregation is significantly reduced by applying a thin layer of liquid to the surfaces of minor component, promoting an ordered mixture.
Barriga, E. Simon; Pattichis, Marios; Ts’o, Dan; Abramoff, Michael; Kardon, Randy; Kwon, Young; Soliz, Peter
2011-01-01
Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about
International Nuclear Information System (INIS)
Kapoor, K.
2015-01-01
Ultrasonic phased array technique has been applied in fabrication of nuclear fuel and structural at NFC. The integrity of the nuclear fuel and structural components is most crucial as they are exposed to severe environment during operation leading to rapid degradation of its properties during its lifecycle. Nuclear Fuel Complex has mandate for the fabrication of the nuclear fuel and core structurals for Indian PHWRs/BWR, sub-assemblies for the PFBR and steam generator tubing for PFBR and PHWRs which are the most critical materials for the Indian Nuclear Power program. NDE during fabrication of these materials is thus most crucial as it provides the confidence to the designer for safe operation during its lifetime. Many of these techniques have to be developed in-house to meet unique requirements of high sensitivity, resolution and shape of the components. Some of the advancements in the NDE during the fabrication include use of ultrasonic phased array which is detailed in this paper
10th Australian conference on nuclear techniques of analysis. Proceedings
International Nuclear Information System (INIS)
1998-01-01
These proceedings contains abstracts and extended abstracts of 80 lectures and posters presented at the 10th Australian conference on nuclear techniques of analysis hosted by the Australian National University in Canberra, Australia from 24-26 of November 1997. The conference was divided into sessions on the following topics : ion beam analysis and its applications; surface science; novel nuclear techniques of analysis, characterization of thin films, electronic and optoelectronic material formed by ion implantation, nanometre science and technology, plasma science and technology. A special session was dedicated to new nuclear techniques of analysis, future trends and developments. Separate abstracts were prepared for the individual presentation included in this volume
10th Australian conference on nuclear techniques of analysis. Proceedings
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-06-01
These proceedings contains abstracts and extended abstracts of 80 lectures and posters presented at the 10th Australian conference on nuclear techniques of analysis hosted by the Australian National University in Canberra, Australia from 24-26 of November 1997. The conference was divided into sessions on the following topics : ion beam analysis and its applications; surface science; novel nuclear techniques of analysis, characterization of thin films, electronic and optoelectronic material formed by ion implantation, nanometre science and technology, plasma science and technology. A special session was dedicated to new nuclear techniques of analysis, future trends and developments. Separate abstracts were prepared for the individual presentation included in this volume.
A methodological comparison of customer service analysis techniques
James Absher; Alan Graefe; Robert Burns
2003-01-01
Techniques used to analyze customer service data need to be studied. Two primary analysis protocols, importance-performance analysis (IP) and gap score analysis (GA), are compared in a side-by-side comparison using data from two major customer service research projects. A central concern is what, if any, conclusion might be different due solely to the analysis...
Nuclear techniques for analysis of environmental samples
International Nuclear Information System (INIS)
1986-12-01
The main purposes of this meeting were to establish the state-of-the-art in the field, to identify new research and development that is required to provide an adequate framework for analysis of environmental samples and to assess needs and possibilities for international cooperation in problem areas. This technical report was prepared on the subject based on the contributions made by the participants. A separate abstract was prepared for each of the 9 papers
Application of activation techniques to biological analysis
International Nuclear Information System (INIS)
Bowen, H.J.M.
1981-01-01
Applications of activation analysis in the biological sciences are reviewed for the period of 1970 to 1979. The stages and characteristics of activation analysis are described, and its advantages and disadvantages enumerated. Most applications involve activation by thermal neutrons followed by either radiochemical or instrumental determination. Relatively little use has been made of activation by fast neutrons, photons, or charged particles. In vivo analyses are included, but those based on prompt gamma or x-ray emission are not. Major applications include studies of reference materials, and the elemental analysis of plants, marine biota, animal and human tissues, diets, and excreta. Relatively little use of it has been made in biochemistry, microbiology, and entomology, but it has become important in toxicology and environmental science. The elements most often determined are Ag, As, Au, Br, Ca, Cd, Cl, Co, Cr, Cs, Cu, Fe, Hg, I, K, Mn, Mo, Na, Rb, Sb, Sc, Se, and Zn, while few or no determinations of B, Be, Bi, Ga, Gd, Ge, H, In, Ir, Li, Nd, Os, Pd, Pr, Pt, Re, Rh, Ru, Te, Tl, or Y have been made in biological materials
International Nuclear Information System (INIS)
Sanchez Miro, J.J.
1980-01-01
A panorama of actual state of acoustic emission as non destructive testing technique, from stand point of its safety applications to nuclear reactor is offered. In first place the physic grounds of acoustic emission phenomenon is briefly exposed. After we speak about the experimental methods for detection, and overall is made an explanation of the problems which are found during the application of this technology to on-line inspection of nuclear oower plants. It is hoped that this repport makes a contribution in the sense of to create a favourable atmosphere toward the introduction in our country of this important technique, and concretely within the nuclear power industry. In this last field the employ of acoustic emission is overcoming the experimental stage. (author)
Structured behavioral observation techniques as components of an effective fitness-for-duty program
International Nuclear Information System (INIS)
Hauth, J.T.; Barnes, V.E.; Moore, C.J.; Toquam, J.L.
1989-01-01
Performance-based tests are designed to evaluate physical and cognitive performance and have several attractive features that may be useful in nuclear power plant fitness-for-duty programs. Three types of performance-based testing that may eventually be useful in the nuclear power industry are reviewed in this paper: (a) the Los Angeles Police Department's Drug Recognition Expert program, (b) performance assessment batteries, and (c) performance assessment devices. Each of these techniques is evaluated here in terms of the following measures of effectiveness: (1) scope, or the range of potential problems that can be detected; (2) reliability, or the consistency of results; (3) sensitivity, or the ability of the test to detect impairment or the presence of drugs at low levels; (4) specificity, or the ability of the test to correctly identify the source of impairment or the drug present; (5) implementation, or the practicality of using the technique in the nuclear power plant setting. This information analyzed in this paper indicates that although performance and cognitive assessment techniques currently lack the reliability, sensitivity, and specificity of random chemical screening to detect and deter substance abuse, they can address a variety of fitness-for-duty concerns that may not be adequately addressed by a urinalysis testing program alone. These include detection of drug use not detected by urinalysis, psychological stress, or physical injury or illness
Directory of Open Access Journals (Sweden)
Shengkun Xie
2014-01-01
Full Text Available Classification of electroencephalography (EEG is the most useful diagnostic and monitoring procedure for epilepsy study. A reliable algorithm that can be easily implemented is the key to this procedure. In this paper a novel signal feature extraction method based on dynamic principal component analysis and nonoverlapping moving window is proposed. Along with this new technique, two detection methods based on extracted sparse features are applied to deal with signal classification. The obtained results demonstrated that our proposed methodologies are able to differentiate EEGs from controls and interictal for epilepsy diagnosis and to separate EEGs from interictal and ictal for seizure detection. Our approach yields high classification accuracy for both single-channel short-term EEGs and multichannel long-term EEGs. The classification performance of the method is also compared with other state-of-the-art techniques on the same datasets and the effect of signal variability on the presented methods is also studied.
International Nuclear Information System (INIS)
Banchet, J.; Chahbaz, A.; Sicard, R.; Zellouf, D.E.
2003-01-01
In aircraft structures, titanium parts and engine members are critical structural components, and their inspection crucial. However, these structures are very difficult to inspect ultrasonically because of their large grain structure that increases noise drastically. In this work, phased array inspection setups were developed to detected small defects such as simulated inclusions and porosity contained in thick titanium casting blocks, which are frequently used in the aerospace industry. A Cut Spectrum Processing (CSP)-based algorithm was then implemented on the acquired data by employing a set of parallel bandpass filters with different center frequencies. This process led in substantial improvement of the signal to noise ratio and thus, of detectability
Components installation. Scheduling techniques applied at Framatome for the French nuclear program
International Nuclear Information System (INIS)
Cremese, G.
1982-09-01
The first scheduling objective is a timely delivery of heavy components manufactured by FRAMATOME factories: reactor vessel, steam generators and pressurizer. The second scheduling function is the preparation and updating of overall and detailed schedules for the coordination and follow-up of: design activities, progress at equipment suppliers, construction and erection activities of sub-contractors, test and start-up tasks by FRAMATOME and customer teams, and maintenance operations by FRAMATOME teams. I shall first describe the schedules for the contract first unit then show how the following units of the contract are scheduled in their turn
International Nuclear Information System (INIS)
Jung, Young Mee
2003-01-01
Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra
New analytical techniques for cuticle chemical analysis
International Nuclear Information System (INIS)
Schulten, H.R.
1994-01-01
1) The analytical methodology of pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and direct pyrolysis-mass spectrometry (Py-MS) using soft ionization techniques by high electric fields (FL) are briefly described. Recent advances of Py-GC/MS and Py-FIMS for the analyses of complex organic matter such as plant materials, humic substances, dissolved organic matter in water (DOM) and soil organic matter (SOM) in agricultural and forest soils are given to illustrate the potential and limitations of the applied methods. 2) Novel applications of Py-GC/MS and Py-MS in combination with conventional analytical data in an integrated, chemometric approach to investigate the dynamics of plant lipids are reported. This includes multivariate statistical investigations on maturation, senescence, humus genesis, and environmental damages in spruce ecosystems. 3) The focal point is the author's integrated investigations on emission-induced changes of selected conifer plant constituents. Pattern recognition of Py-MS data of desiccated spruce needles provides a method for distinguishing needles damaged in different ways and determining the cause. Spruce needles were collected from both controls and trees treated with sulphur dioxide (acid rain), nitrogen dioxide, and ozone under controlled conditions. Py-MS and chemometric data evaluation are employed to characterize and classify leaves and their epicuticular waxes. Preliminary mass spectrometric evaluations of isolated cuticles of different plants such as spruce, ivy, holly, and philodendron, as well as ivy cuticles treated in vivo with air pollutants such as surfactants and pesticides are given. (orig.)
A technique for human error analysis (ATHEANA)
Energy Technology Data Exchange (ETDEWEB)
Cooper, S.E.; Ramey-Smith, A.M.; Wreathall, J.; Parry, G.W. [and others
1996-05-01
Probabilistic risk assessment (PRA) has become an important tool in the nuclear power industry, both for the Nuclear Regulatory Commission (NRC) and the operating utilities. Human reliability analysis (HRA) is a critical element of PRA; however, limitations in the analysis of human actions in PRAs have long been recognized as a constraint when using PRA. A multidisciplinary HRA framework has been developed with the objective of providing a structured approach for analyzing operating experience and understanding nuclear plant safety, human error, and the underlying factors that affect them. The concepts of the framework have matured into a rudimentary working HRA method. A trial application of the method has demonstrated that it is possible to identify potentially significant human failure events from actual operating experience which are not generally included in current PRAs, as well as to identify associated performance shaping factors and plant conditions that have an observable impact on the frequency of core damage. A general process was developed, albeit in preliminary form, that addresses the iterative steps of defining human failure events and estimating their probabilities using search schemes. Additionally, a knowledge- base was developed which describes the links between performance shaping factors and resulting unsafe actions.
A technique for human error analysis (ATHEANA)
International Nuclear Information System (INIS)
Cooper, S.E.; Ramey-Smith, A.M.; Wreathall, J.; Parry, G.W.
1996-05-01
Probabilistic risk assessment (PRA) has become an important tool in the nuclear power industry, both for the Nuclear Regulatory Commission (NRC) and the operating utilities. Human reliability analysis (HRA) is a critical element of PRA; however, limitations in the analysis of human actions in PRAs have long been recognized as a constraint when using PRA. A multidisciplinary HRA framework has been developed with the objective of providing a structured approach for analyzing operating experience and understanding nuclear plant safety, human error, and the underlying factors that affect them. The concepts of the framework have matured into a rudimentary working HRA method. A trial application of the method has demonstrated that it is possible to identify potentially significant human failure events from actual operating experience which are not generally included in current PRAs, as well as to identify associated performance shaping factors and plant conditions that have an observable impact on the frequency of core damage. A general process was developed, albeit in preliminary form, that addresses the iterative steps of defining human failure events and estimating their probabilities using search schemes. Additionally, a knowledge- base was developed which describes the links between performance shaping factors and resulting unsafe actions
Organizational Design Analysis of Fleet Readiness Center Southwest Components Department
National Research Council Canada - National Science Library
Montes, Jose F
2007-01-01
.... The purpose of this MBA Project is to analyze the proposed organizational design elements of the FRCSW Components Department that resulted from the integration of the Naval Aviation Depot at North Island (NADEP N.I...
Directory of Open Access Journals (Sweden)
Kim eDe Roover
2014-06-01
Full Text Available The issue of measurement invariance is ubiquitous in the behavioral sciences nowadays as more and more studies yield multivariate multigroup data. When measurement invariance cannot be established across groups, this is often due to different loadings on only a few items. Within the multigroup CFA framework, methods have been proposed to trace such non-invariant items, but these methods have some disadvantages in that they require researchers to run a multitude of analyses and in that they imply assumptions that are often questionable. In this paper, we propose an alternative strategy which builds on clusterwise simultaneous component analysis (SCA. Clusterwise SCA, being an exploratory technique, assigns the groups under study to a few clusters based on differences and similarities in the covariance matrices, and thus based on the component structure of the items. Non-invariant items can then be traced by comparing the cluster-specific component loadings via congruence coefficients, which is far more parsimonious than comparing the component structure of all separate groups. In this paper we present a heuristic for this procedure. Afterwards, one can return to the multigroup CFA framework and check whether removing the non-invariant items or removing some of the equality restrictions for these items, yields satisfactory invariance test results. An empirical application concerning cross-cultural emotion data is used to demonstrate that this novel approach is useful and can co-exist with the traditional CFA approaches.
Registration of dynamic dopamine D2receptor images using principal component analysis
International Nuclear Information System (INIS)
Acton, P.D.; Ell, P.J.; Pilowsky, L.S.; Brammer, M.J.; Suckling, J.
1997-01-01
This paper describes a novel technique for registering a dynamic sequence of single-photon emission tomography (SPET) dopamine D 2 receptor images, using principal component analysis (PCA). Conventional methods for registering images, such as count difference and correlation coefficient algorithms, fail to take into account the dynamic nature of the data, resulting in large systematic errors when registering time-varying images. However, by using principal component analysis to extract the temporal structure of the image sequence, misregistration can be quantified by examining the distribution of eigenvalues. The registration procedures were tested using a computer-generated dynamic phantom derived from a high-resolution magnetic resonance image of a realistic brain phantom. Each method was also applied to clinical SPET images of dopamine D 2 receptors, using the ligands iodine-123 iodobenzamide and iodine-123 epidepride, to investigate the influence of misregistration on kinetic modelling parameters and the binding potential. The PCA technique gave highly significant (P 123 I-epidepride scans. The PCA method produced data of much greater quality for subsequent kinetic modelling, with an improvement of nearly 50% in the χ 2 of the fit to the compartmental model, and provided superior quality registration of particularly difficult dynamic sequences. (orig.)
Measuring two-phase and two-component mixtures by radiometric technique
International Nuclear Information System (INIS)
Mackuliak, D.; Rajniak, I.
1984-01-01
The possibility was tried of the application of the radiometric method in measuring steam water content. The experiments were carried out in model conditions where steam was replaced with the two-component mixture of water and air. The beta radiation source was isotope 204 Tl (Esub(max)=0.765 MeV) with an activity of 19.35 MBq. Measurements were carried out within the range of the surface density of the mixture from 0.119 kg.m -2 to 0.130 kg.m -2 . Mixture speed was 5.1 m.s -1 to 7.1 m.s -1 . The observed dependence of relative pulse frequency on the specific water content in the mixture was approximated by a linear regression. (B.S.)
International Nuclear Information System (INIS)
Shigorina, I.I.; Egorov, B.N.; Timofeeva, L.N.
1978-01-01
The problems of choosing the volatile part (v.p.) for varnishes on the basis of different flourocopolymers are considered. Ketones, esters, freons, dimethylformamide, tetrahydrofuran, aromatic and chlorinated hydrocarbons have been used as solvents. The volatile component has been estimated by the quality of the varnish film obtained (transparency, bubbles), viscosity of the varnishes, completeness of solvent volatility, porosity degree. Besides, analyzed are such factors as kinetics of solvent evaporation, working life time of varnishes, and the degree of their inflammability. Optimum solvents and their mixtures have been found for different grades of fluorolones. The possibility of producing fluorolone lackuers with a reduced degree of inflammability and of incombustible fluorolone varnishes is shown. Fluorolone varnishes find ever increasing application for radiation-protective coating of the equipment
Hot radial pressing: An alternative technique for the manufacturing of plasma-facing components
International Nuclear Information System (INIS)
Visca, E.; Libera, S.; Mancini, A.; Mazzone, G.; Pizzuto, A.; Testani, C.
2005-01-01
The Hot radial pressing (HRP) manufacturing technique is based on the radial diffusion bonding principle performed between the cooling tube and the armour tile. The bonding is achieved by pressurizing the cooling tube while the joining interface is kept at the vacuum and temperature conditions. This technique has been used for the manufacturing of relevant mock-ups of the ITER divertor vertical target. Tungsten monoblock mock-ups were successfully tested to high heat flux thermal fatigue (20 MW/m 2 of absorbed heat flux for 1000 cycles). After these good results the activity is now focused on the developing of a manufacturing process suitable also for the CFC monoblock mock-ups. A FE calculation was performed to investigate the stress involved in the CFC tiles during the process and to avoid the CFC fracture. The results obtained by the FE calculation and by the test performed in air simulating a HRP manufacturing process for a CFC monoblock mock-ups is reported in the paper
Development of BWR components SCC mitigation method by the TiO{sub 2} treating technique
Energy Technology Data Exchange (ETDEWEB)
Takamori, K.; Suzuki, J.; Suzuki, S.; Miyazaki, A. [Tokyo Electric Power Co., Tokohama-city (Japan); Okamura, M.; Osato, T.; Ichikawa, N. [Toshiba Corp., Kawasaki-city (Japan); Urata, H.; Takagi, J. [Toshiba Corp., Yokohama-city (Japan)
2007-07-01
Stress Corrosion Cracking (SCC) susceptibility of Boiling Water Reactor (BWR) materials is mitigated by reduction of the electrochemical corrosion potential (ECP). In the reactor there is a photo-excitation reaction between TiO{sub 2} and ultraviolet Cherenkov radiation. The TiO{sub 2} treatment technique plans to mitigate SCC by reducing the ECP without hydrogen addition. We conducted the demonstration tests of the TiO{sub 2} treatment technique in a test reactor and in BWR plant piping systems. The test results showed that the ECP of TiO{sub 2} treated type 316L stainless steel and the Ni based alloy 600 were reduced to -350 mV vs. the standard hydrogen electrode (SHE) in the reactor system in normal water chemistry (NWC). In the no Cherenkov radiation area, the ECP of the TiO{sub 2} treated stainless steel still decreased as the dissolved hydrogen concentration in feed water up to 0.3 ppm. (a condition that will be referred as 'low HWC.') (author)
Machine Learning Techniques for Arterial Pressure Waveform Analysis
Directory of Open Access Journals (Sweden)
João Cardoso
2013-05-01
Full Text Available The Arterial Pressure Waveform (APW can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1 a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2 the acquired position and amplitude of onset, Systolic Peak (SP, Point of Inflection (Pi and Dicrotic Wave (DW were used for the computation of some morphological attributes; (3 pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4 classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic, J48 (decision tree and RIPPER (rule-based induction; and (5 we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx. Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95% and high area under the curve (AUC of a Receiver Operating Characteristic (ROC curve (0.961. Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation.
Zhang, Qiong; Peng, Cong; Lu, Yiming; Wang, Hao; Zhu, Kaiguang
2018-04-01
A novel technique is developed to level airborne geophysical data using principal component analysis based on flight line difference. In the paper, flight line difference is introduced to enhance the features of levelling error for airborne electromagnetic (AEM) data and improve the correlation between pseudo tie lines. Thus we conduct levelling to the flight line difference data instead of to the original AEM data directly. Pseudo tie lines are selected distributively cross profile direction, avoiding the anomalous regions. Since the levelling errors of selective pseudo tie lines show high correlations, principal component analysis is applied to extract the local levelling errors by low-order principal components reconstruction. Furthermore, we can obtain the levelling errors of original AEM data through inverse difference after spatial interpolation. This levelling method does not need to fly tie lines and design the levelling fitting function. The effectiveness of this method is demonstrated by the levelling results of survey data, comparing with the results from tie-line levelling and flight-line correlation levelling.
Machine learning of frustrated classical spin models. I. Principal component analysis
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.
Detailed Structural Analysis of Critical Wendelstein 7-X Magnet System Components
International Nuclear Information System (INIS)
Egorov, K.
2006-01-01
The Wendelstein 7-X (W7-X) stellarator experiment is presently under construction and assembly in Greifswald, Germany. The goal of the experiment is to verify that the stellarator magnetic confinement concept is a viable option for a fusion reactor. The complex W7-X magnet system requires a multi-level approach to structural analysis for which two types of finite element models are used: Firstly, global models having reasonably coarse meshes with a number of simplifications and assumptions, and secondly, local models with detailed meshes of critical regions and elements. Widely known sub-modelling technique with boundary conditions extracted from the global models is one of the approaches for local analysis with high assessment efficiency. In particular, the winding pack (WP) of the magnet coils is simulated in the global model as a homogeneous orthotropic material with effective mechanical characteristic representing its real composite structure. This assumption allows assessing the whole magnet system in terms of general structural factors like forces and moments on the support elements, displacements of the main components, deformation and stress in the coil casings, etc. In a second step local models with a detailed description of more critical WP zones are considered in order to analyze their internal components like conductor jackets, turn insulation, etc. This paper provides an overview of local analyses of several critical W7-X magnet system components with particular attention on the coil winding packs. (author)
Development of chemical analysis techniques: pt. 3
International Nuclear Information System (INIS)
Kim, K.J.; Chi, K.Y.; Choi, G.C.
1981-01-01
For the purpose of determining trace rare earths a spectrofluorimetric method has been studied. Except Ce and Tb, the fluorescence intensities are not enough to allow satisfactory analysis. Complexing agents such as tungstate and hexafluoroacetylacetone should be employed to increase fluorescence intensities. As a preliminary experiment for the separation of individual rare earth element and uranium, the distribution coefficient, % S here, are obtained on the Dowex 50 W against HCl concentration by a batch method. These % S data are utilized to obtain elution curves. The % S data showed a minimum at around 4 M HCl. To understand this previously known phenomenon the adsorption of Cl - on Dowex 50 W is examined as a function of HCl concentration and found to be decreasing while % S of rare earths increasing. It is interpreted that Cl - and rare earth ions are moved into the resin phase separately and that the charge and the charge densities of these ions are responsible for the different % S curves. Dehydration appears to play an important role in the upturn of the % S curves at higher HCl concentrations
An elementary components of variance analysis for multi-centre quality control
International Nuclear Information System (INIS)
Munson, P.J.; Rodbard, D.
1978-01-01
The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality-control (QC) studies. Simple graphical display of data in the form of histograms is useful but insufficient. The paper discusses statistical analysis methods for such studies using an ''analysis of variance with components of variance estimation''. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Problems with RIA data, e.g. severe non-uniformity of variance and/or departure from a normal distribution violate some of the usual assumptions underlying analysis of variance. In order to correct these problems, it is often necessary to transform the data before analysis by using a logarithmic, square-root, percentile, ranking, RIDIT, ''Studentizing'' or other transformation. Ametric transformations such as ranks or percentiles protect against the undue influence of outlying observations, but discard much intrinsic information. Several possible relationships of standard deviation to the laboratory mean are considered. Each relationship corresponds to an underlying statistical model and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine whether an appropriate model has been chosen, although the exact functional relationship of standard deviation to laboratory mean may be difficult to establish. Appropriate graphical display aids visual understanding of the data. A plot of the ranked standard deviation versus 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
Analysis of the frequency components of X-ray images
International Nuclear Information System (INIS)
Matsuo, Satoru; Komizu, Mitsuru; Kida, Tetsuo; Noma, Kazuo; Hashimoto, Keiji; Onishi, Hideo; Masuda, Kazutaka
1997-01-01
We examined the relation between the frequency components of x-ray images of the chest and phalanges and their read sizes for digitizing. Images of the chest and phalanges were radiographed using three types of screens and films, and the noise images in background density were digitized with a drum scanner, changing the read sizes. The frequency components for these images were evaluated by converting them to the secondary Fourier to obtain the power spectrum and signal to noise ratio (SNR). After changing the cut-off frequency on the power spectrum to process a low pass filter, we also examined the frequency components of the images in relation to the normalized mean square error (NMSE) for the image converted to reverse Fourier and the original image. Results showed that the frequency components were 2.0 cycles/mm for the chest image and 6.0 cycles/mm for the phalanges. Therefore, it is necessary to collect data applying the read sizes of 200 μm and 50 μm for the chest and phalangeal images, respectively, in order to digitize these images without loss of their frequency components. (author)
Gradl, Paul
2016-01-01
NASA Marshall Space Flight Center (MSFC) has been advancing dynamic optical measurement systems, primarily Digital Image Correlation, for extreme environment rocket engine test applications. The Digital Image Correlation (DIC) technology is used to track local and full field deformations, displacement vectors and local and global strain measurements. This technology has been evaluated at MSFC through lab testing to full scale hotfire engine testing of the J-2X Upper Stage engine at Stennis Space Center. It has been shown to provide reliable measurement data and has replaced many traditional measurement techniques for NASA applications. NASA and AMRDEC have recently signed agreements for NASA to train and transition the technology to applications for missile and helicopter testing. This presentation will provide an overview and progression of the technology, various testing applications at NASA MSFC, overview of Army-NASA test collaborations and application lessons learned about Digital Image Correlation.
Use of the thin layer activation technique to measure on-line aeronautical components wear
International Nuclear Information System (INIS)
Chevalier, A.; Dubois, G.; Escuriol, M.; Monnot, R.; Pommier, S.; Fehsenfeld, P.; Kleinrahm, A.; Delvigne, T.; Le Menestrel, M.
1992-01-01
The superficial activation technique was applied in order to study the phenomena odscaling at the level of a reactor bearing. The exterior path of the bearing roller was activated on its whole contact surface and to a depth of 80 μm, according to the reaction 56 Fe(p, n) 56 Co. In spite of a very low rate of activation of 0.5 MBq, the first signs of scaling were detected 30 min before a notable rise in the vibratory level could be recorded. Then, the amount of scaled matter escaping from the outer ring of the roller could be followed continuously, with a precision of 0.2 mg. 5 refs., 7 figs
Contributions to fuzzy polynomial techniques for stability analysis and control
Pitarch Pérez, José Luis
2014-01-01
The present thesis employs fuzzy-polynomial control techniques in order to improve the stability analysis and control of nonlinear systems. Initially, it reviews the more extended techniques in the field of Takagi-Sugeno fuzzy systems, such as the more relevant results about polynomial and fuzzy polynomial systems. The basic framework uses fuzzy polynomial models by Taylor series and sum-of-squares techniques (semidefinite programming) in order to obtain stability guarantees...
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.
Independent component analysis of edge information for face recognition
Karande, Kailash Jagannath
2013-01-01
The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also propos
Directory of Open Access Journals (Sweden)
Dong-Sup Lee
2015-01-01
Full Text Available Independent Component Analysis (ICA, one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.
Ferrero, A; Campos, J; Rabal, A M; Pons, A; Hernanz, M L; Corróns, A
2011-09-26
The Bidirectional Reflectance Distribution Function (BRDF) is essential to characterize an object's reflectance properties. This function depends both on the various illumination-observation geometries as well as on the wavelength. As a result, the comprehensive interpretation of the data becomes rather complex. In this work we assess the use of the multivariable analysis technique of Principal Components Analysis (PCA) applied to the experimental BRDF data of a ceramic colour standard. It will be shown that the result may be linked to the various reflection processes occurring on the surface, assuming that the incoming spectral distribution is affected by each one of these processes in a specific manner. Moreover, this procedure facilitates the task of interpolating a series of BRDF measurements obtained for a particular sample. © 2011 Optical Society of America
Processing of spectral X-ray data with principal components analysis
Butler, A P H; Cook, N J; Butzer, J; Schleich, N; Tlustos, L; Scott, N; Grasset, R; de Ruiter, N; Anderson, N G
2011-01-01
The goal of the work was to develop a general method for processing spectral x-ray image data. Principle component analysis (PCA) is a well understood technique for multivariate data analysis and so was investigated. To assess this method, spectral (multi-energy) computed tomography (CT) data was obtained using a Medipix2 detector in a MARS-CT (Medipix All Resolution System). PCA was able to separate bone (calcium) from two elements with k-edges in the X-ray spectrum used (iodine and barium) within a mouse. This has potential clinical application in dual-energy CT systems and future Medipix3 based spectral imaging where up to eight energies can be recorded simultaneously with excellent energy resolution. (c) 2010 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Lebach, D. E.; Ratner, M. I.; Shapiro, I. I.; Bartel, N.; Bietenholz, M. F.; Lederman, J. I.; Ransom, R. R.; Campbell, R. M.; Gordon, D.; Lestrade, J.-F.
2012-01-01
When very long baseline interferometry (VLBI) observations are used to determine the position or motion of a radio source relative to reference sources nearby on the sky, the astrometric information is usually obtained via (1) phase-referenced maps or (2) parametric model fits to measured fringe phases or multiband delays. In this paper, we describe a 'merged' analysis technique which combines some of the most important advantages of these other two approaches. In particular, our merged technique combines the superior model-correction capabilities of parametric model fits with the ability of phase-referenced maps to yield astrometric measurements of sources that are too weak to be used in parametric model fits. We compare the results from this merged technique with the results from phase-referenced maps and from parametric model fits in the analysis of astrometric VLBI observations of the radio-bright star IM Pegasi (HR 8703) and the radio source B2252+172 nearby on the sky. In these studies we use central-core components of radio sources 3C 454.3 and B2250+194 as our positional references. We obtain astrometric results for IM Peg with our merged technique even when the source is too weak to be used in parametric model fits, and we find that our merged technique yields astrometric results superior to the phase-referenced mapping technique. We used our merged technique to estimate the proper motion and other astrometric parameters of IM Peg in support of the NASA/Stanford Gravity Probe B mission.
An operator expansion technique for path integral analysis
International Nuclear Information System (INIS)
Tsvetkov, I.V.
1995-01-01
A new method of path integral analysis in the framework of a power series technique is presented. The method is based on the operator expansion of an exponential. A regular procedure to calculate the correction terms is found. (orig.)
Search for the top quark using multivariate analysis techniques
International Nuclear Information System (INIS)
Bhat, P.C.
1994-08-01
The D0 collaboration is developing top search strategies using multivariate analysis techniques. We report here on applications of the H-matrix method to the eμ channel and neural networks to the e+jets channel
Design and analysis of automobile components using industrial procedures
Kedar, B.; Ashok, B.; Rastogi, Nisha; Shetty, Siddhanth
2017-11-01
Today’s automobiles depend upon mechanical systems that are crucial for aiding in the movement and safety features of the vehicle. Various safety systems such as Antilock Braking System (ABS) and passenger restraint systems have been developed to ensure that in the event of a collision be it head on or any other type, the safety of the passenger is ensured. On the other side, manufacturers also want their customers to have a good experience while driving and thus aim to improve the handling and the drivability of the vehicle. Electronics systems such as Cruise Control and active suspension systems are designed to ensure passenger comfort. Finally, to ensure optimum and safe driving the various components of a vehicle must be manufactured using the latest state of the art processes and must be tested and inspected with utmost care so that any defective component can be prevented from being sent out right at the beginning of the supply chain. Therefore, processes which can improve the lifetime of their respective components are in high demand and much research and development is done on these processes. With a solid base research conducted, these processes can be used in a much more versatile manner for different components, made up of different materials and under different input conditions. This will help increase the profitability of the process and also upgrade its value to the industry.
Analysis of soft rock mineral components and roadway failure mechanism
Institute of Scientific and Technical Information of China (English)
陈杰
2001-01-01
The mineral components and microstructure of soft rock sampled from roadway floor inXiagou pit are determined by X-ray diffraction and scanning electron microscope. Ccmbined withthe test of expansion and water softening property of the soft rock, the roadway failure mechanism is analyzed, and the reasonable repair supporting principle of roadway is put forward.
Analysis Of The Executive Components Of The Farmer Field School ...
African Journals Online (AJOL)
The purpose of this study was to investigate the executive components of the Farmer Field School (FFS) project in Uromieh county of West Azerbaijan Province, Iran. All the members and non-members (as control group) of FFS pilots in Uromieh county (N= 98) were included in the study. Data were collected by use of ...
Principal Components Analysis of Job Burnout and Coping ...
African Journals Online (AJOL)
The key component structure of job burnout were feelings of disgust, insomnia, headaches, weight loss or gain feeling of omniscient, pain of unexplained origin, hopelessness, agitation and workaholics, while the factor structure of coping strategies were development of self realistic picture, retaining hope, asking for help ...
Phenolic components, antioxidant activity, and mineral analysis of ...
African Journals Online (AJOL)
In addition to being consumed as food, caper (Capparis spinosa L.) fruits are also used in folk medicine to treat inflammatory disorders, such as rheumatism. C. spinosa L. is rich in phenolic compounds, making it increasingly popular because of its components' potential benefits to human health. We analyzed a number of ...
Neutron activation analysis: an emerging technique for conservation/preservation
International Nuclear Information System (INIS)
Sayre, E.V.
1976-01-01
The diverse applications of neutron activation in analysis, preservation, and documentation of art works and artifacts are described with illustrations for each application. The uses of this technique to solve problems of attribution and authentication, to reveal the inner structure and composition of art objects, and, in some instances to recreate details of the objects are described. A brief discussion of the theory and techniques of neutron activation analysis is also included
Development of evaluation method for software safety analysis techniques
International Nuclear Information System (INIS)
Huang, H.; Tu, W.; Shih, C.; Chen, C.; Yang, W.; Yih, S.; Kuo, C.; Chen, M.
2006-01-01
Full text: Full text: Following the massive adoption of digital Instrumentation and Control (I and C) system for nuclear power plant (NPP), various Software Safety Analysis (SSA) techniques are used to evaluate the NPP safety for adopting appropriate digital I and C system, and then to reduce risk to acceptable level. However, each technique has its specific advantage and disadvantage. If the two or more techniques can be complementarily incorporated, the SSA combination would be more acceptable. As a result, if proper evaluation criteria are available, the analyst can then choose appropriate technique combination to perform analysis on the basis of resources. This research evaluated the applicable software safety analysis techniques nowadays, such as, Preliminary Hazard Analysis (PHA), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Markov chain modeling, Dynamic Flowgraph Methodology (DFM), and simulation-based model analysis; and then determined indexes in view of their characteristics, which include dynamic capability, completeness, achievability, detail, signal/ noise ratio, complexity, and implementation cost. These indexes may help the decision makers and the software safety analysts to choose the best SSA combination arrange their own software safety plan. By this proposed method, the analysts can evaluate various SSA combinations for specific purpose. According to the case study results, the traditional PHA + FMEA + FTA (with failure rate) + Markov chain modeling (without transfer rate) combination is not competitive due to the dilemma for obtaining acceptable software failure rates. However, the systematic architecture of FTA and Markov chain modeling is still valuable for realizing the software fault structure. The system centric techniques, such as DFM and Simulation-based model analysis, show the advantage on dynamic capability, achievability, detail, signal/noise ratio. However, their disadvantage are the completeness complexity
International Nuclear Information System (INIS)
Lofgren, E.V.
1985-08-01
This course in System Reliability and Analysis Techniques focuses on the quantitative estimation of reliability at the systems level. Various methods are reviewed, but the structure provided by the fault tree method is used as the basis for system reliability estimates. The principles of fault tree analysis are briefly reviewed. Contributors to system unreliability and unavailability are reviewed, models are given for quantitative evaluation, and the requirements for both generic and plant-specific data are discussed. Also covered are issues of quantifying component faults that relate to the systems context in which the components are embedded. All reliability terms are carefully defined. 44 figs., 22 tabs
Research on digital multi-channel pulse height analysis techniques
International Nuclear Information System (INIS)
Xiao Wuyun; Wei Yixiang; Ai Xianyun; Ao Qi
2005-01-01
Multi-channel pulse height analysis techniques are developing in the direction of digitalization. Based on digital signal processing techniques, digital multi-channel analyzers are characterized by powerful pulse processing ability, high throughput, improved stability and flexibility. This paper analyzes key techniques of digital nuclear pulse processing. With MATLAB software, main algorithms are simulated, such as trapezoidal shaping, digital baseline estimation, digital pole-zero/zero-pole compensation, poles and zeros identification. The preliminary general scheme of digital MCA is discussed, as well as some other important techniques about its engineering design. All these lay the foundation of developing homemade digital nuclear spectrometers. (authors)
International Nuclear Information System (INIS)
Maciga, G.; Papponetti, M.; Crutzen, S.; Jehenson, P.
1990-01-01
Performance demonstration for NDT has been an active topic for several years. Interest in it came to the fore in the early 1980's when several institutions started to propose to use of realistic training assemblies and the formal approach of Validation Centers. These steps were justified for example by the results of the PISC exercises which concluded that there was a need for performance demonstration starting with capability assessment of techniques and procedure as they were routinely applied. If the PISC programme is put under the general ''Nuclear Motivation'', the PISC Methodology could be extended to problems to structural components in general, such as on conventional power plants, chemical, aerospace and offshore industries, where integrity and safety have regarded as being of great importance. Some themes of NDT inspections of fossil power plant and offshore components that could be objects of validation studies will be illustrated. (author)
Principal component analysis of solar flares in the soft X-ray flux
International Nuclear Information System (INIS)
Teuber, D.L.; Reichmann, E.J.; Wilson, R.M.; National Aeronautics and Space Administration, Huntsville, AL
1979-01-01
Principal component analysis is a technique for extracting the salient features from a mass of data. It applies, in particular, to the analysis of nonstationary ensembles. Computational schemes for this task require the evaluation of eigenvalues of matrices. We have used EISPACK Matrix Eigen System Routines on an IBM 360-75 to analyze full-disk proportional-counter data from the X-ray event analyzer (X-REA) which was part of the Skylab ATM/S-056 experiment. Empirical orthogonal functions have been derived for events in the soft X-ray spectrum between 2.5 and 20 A during different time frames between June 1973 and January 1974. Results indicate that approximately 90% of the cumulative power of each analyzed flare is contained in the largest eigenvector. The first two largest eigenvectors are sufficient for an empirical curve-fit through the raw data and a characterization of solar flares in the soft X-ray flux. Power spectra of the two largest eigenvectors reveal a previously reported periodicity of approximately 5 min. Similar signatures were also obtained from flares that are synchronized on maximum pulse-height when subjected to a principal component analysis. (orig.)
Sensitivity analysis and related analysis : A survey of statistical techniques
Kleijnen, J.P.C.
1995-01-01
This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical
Development of environmental sample analysis techniques for safeguards
International Nuclear Information System (INIS)
Magara, Masaaki; Hanzawa, Yukiko; Esaka, Fumitaka
1999-01-01
JAERI has been developing environmental sample analysis techniques for safeguards and preparing a clean chemistry laboratory with clean rooms. Methods to be developed are a bulk analysis and a particle analysis. In the bulk analysis, Inductively-Coupled Plasma Mass Spectrometer or Thermal Ionization Mass Spectrometer are used to measure nuclear materials after chemical treatment of sample. In the particle analysis, Electron Probe Micro Analyzer and Secondary Ion Mass Spectrometer are used for elemental analysis and isotopic analysis, respectively. The design of the clean chemistry laboratory has been carried out and construction will be completed by the end of March, 2001. (author)
IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION
International Nuclear Information System (INIS)
Casini, R.; Lites, B. W.; Ramos, A. Asensio; Ariste, A. López
2013-01-01
We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2 4n bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of a given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2 4n as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing
Key-space analysis of double random phase encryption technique
Monaghan, David S.; Gopinathan, Unnikrishnan; Naughton, Thomas J.; Sheridan, John T.
2007-09-01
We perform a numerical analysis on the double random phase encryption/decryption technique. The key-space of an encryption technique is the set of possible keys that can be used to encode data using that technique. In the case of a strong encryption scheme, many keys must be tried in any brute-force attack on that technique. Traditionally, designers of optical image encryption systems demonstrate only how a small number of arbitrary keys cannot decrypt a chosen encrypted image in their system. However, this type of demonstration does not discuss the properties of the key-space nor refute the feasibility of an efficient brute-force attack. To clarify these issues we present a key-space analysis of the technique. For a range of problem instances we plot the distribution of decryption errors in the key-space indicating the lack of feasibility of a simple brute-force attack.
Analysis and test of insulated components for rotary engine
Badgley, Patrick R.; Doup, Douglas; Kamo, Roy
1989-01-01
The direct-injection stratified-charge (DISC) rotary engine, while attractive for aviation applications due to its light weight, multifuel capability, and potentially low fuel consumption, has until now required a bulky and heavy liquid-cooling system. NASA-Lewis has undertaken the development of a cooling system-obviating, thermodynamically superior adiabatic rotary engine employing state-of-the-art thermal barrier coatings to thermally insulate engine components. The thermal barrier coating material for the cast aluminum, stainless steel, and ductile cast iron components was plasma-sprayed zirconia. DISC engine tests indicate effective thermal barrier-based heat loss reduction, but call for superior coefficient-of-thermal-expansion matching of materials and better tribological properties in the coatings used.
Nuclear techniques for bulk and surface analysis of materials
International Nuclear Information System (INIS)
D'Agostino, M.D.; Kamykowski, E.A.; Kuehne, F.J.; Padawer, G.M.; Schneid, E.J.; Schulte, R.L.; Stauber, M.C.; Swanson, F.R.
1978-01-01
A review is presented summarizing several nondestructive bulk and surface analysis nuclear techniques developed in the Grumman Research Laboratories. Bulk analysis techniques include 14-MeV-neutron activation analysis and accelerator-based neutron radiography. The surface analysis techniques include resonant and non-resonant nuclear microprobes for the depth profile analysis of light elements (H, He, Li, Be, C, N, O and F) in the surface of materials. Emphasis is placed on the description and discussion of the unique nuclear microprobe analytical capacibilities of immediate importance to a number of current problems facing materials specialists. The resolution and contrast of neutron radiography was illustrated with an operating heat pipe system. The figure shows that the neutron radiograph has a resolution of better than 0.04 cm with sufficient contrast to indicate Freon 21 on the inner capillaries of the heat pipe and pooling of the liquid at the bottom. (T.G.)
COMPONENTS OF THE UNEMPLOYMENT ANALYSIS IN CONTEMPORARY ECONOMIES
Directory of Open Access Journals (Sweden)
Ion Enea-SMARANDACHE
2010-03-01
Full Text Available The unemployment is a permanent phenomenon in majority countries of the world, either with advanced economies, either in course of developed economies, and the implications and the consequences are more complexes, so that, practically, the fight with unemployment becomes a fundamental objective for the economy politics. In context, the authors proposed to set apart essentially components for unemployment analyse with the scope of identification the measures and the instruments of counteracted.
Analysis of Femtosecond Timing Noise and Stability in Microwave Components
International Nuclear Information System (INIS)
2011-01-01
To probe chemical dynamics, X-ray pump-probe experiments trigger a change in a sample with an optical laser pulse, followed by an X-ray probe. At the Linac Coherent Light Source, LCLS, timing differences between the optical pulse and x-ray probe have been observed with an accuracy as low as 50 femtoseconds. This sets a lower bound on the number of frames one can arrange over a time scale to recreate a 'movie' of the chemical reaction. The timing system is based on phase measurements from signals corresponding to the two laser pulses; these measurements are done by using a double-balanced mixer for detection. To increase the accuracy of the system, this paper studies parameters affecting phase detection systems based on mixers, such as signal input power, noise levels, temperature drift, and the effect these parameters have on components such as the mixers, splitters, amplifiers, and phase shifters. Noise data taken with a spectrum analyzer show that splitters based on ferrite cores perform with less noise than strip-line splitters. The data also shows that noise in specific mixers does not correspond with the changes in sensitivity per input power level. Temperature drift is seen to exist on a scale between 1 and 27 fs/ o C for all of the components tested. Results show that any components using more metallic conductor tend to exhibit more noise as well as more temperature drift. The scale of these effects is large enough that specific care should be given when choosing components and designing the housing of high precision microwave mixing systems for use in detection systems such as the LCLS. With these improvements, the timing accuracy can be improved to lower than currently possible.
Analysis of the Components of Economic Potential of Agricultural Enterprises
Vyacheslav Skobara; Volodymyr Podkopaev
2014-01-01
Problems of efficiency of enterprises are increasingly associated with the use of the economic potential of the company. This article addresses the structural components of the economic potential of agricultural enterprise, development and substantiation of the model of economic potential with due account of the peculiarities of agricultural production. Based on the study of various approaches to the potential structure established is the definition of of production, labour, financial and man...