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Sample records for cognitive component analysis

  1. 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...

  2. Cognitive Component Analysis

    DEFF Research Database (Denmark)

    Feng, Ling

    2008-01-01

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

  3. Latent semantics as cognitive components

    DEFF Research Database (Denmark)

    Petersen, Michael Kai; Mørup, Morten; Hansen, Lars Kai

    2010-01-01

    Cognitive component analysis, defined as an unsupervised learning of features resembling human comprehension, suggests that the sensory structures we perceive might often be modeled by reducing dimensionality and treating objects in space and time as linear mixtures incorporating sparsity...... emotional responses can be encoded in words, we propose a simplified cognitive approach to model how we perceive media. Representing song lyrics in a vector space of reduced dimensionality using LSA, we combine bottom-up defined term distances with affective adjectives, that top-down constrain the latent......, which we suggest might function as cognitive components for perceiving the underlying structure in lyrics....

  4. Large-scale network analysis of imagination reveals extended but limited top-down components in human visual cognition.

    Directory of Open Access Journals (Sweden)

    Verkhlyutov V.M.

    2014-12-01

    Full Text Available We investigated whole-brain functional magnetic resonance imaging (fMRI activation in a group of 21 healthy adult subjects during perception, imagination and remembering of two dynamic visual scenarios. Activation of the posterior parts of the cortex prevailed when watching videos. The cognitive tasks of imagination and remembering were accompanied by a predominant activity in the anterior parts of the cortex. An independent component analysis identified seven large-scale cortical networks with relatively invariant spatial distributions across all experimental conditions. The time course of their activation over experimental sessions was task-dependent. These detected networks can be interpreted as a recombination of resting state networks. Both central and peripheral networks were identified within the primary visual cortex. The central network around the caudal pole of BA17 and centers of other visual areas was activated only by direct visual stimulation, while the peripheral network responded to the presentation of visual information as well as to the cognitive tasks of imagination and remembering. The latter result explains the particular susceptibility of peripheral and twilight vision to cognitive top-down influences that often result in false-alarm detections.

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

    Science.gov (United States)

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

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

  6. The Effect of Corrective Feedback on Performance in Basic Cognitive Tasks: An Analysis of RT Components

    Directory of Open Access Journals (Sweden)

    Carmen Moret-Tatay

    2016-12-01

    Full Text Available The current work examines the effect of trial-by-trial feedback about correct and error responding on performance in two basic cognitive tasks: a classic Stroop task (n = 40 and a color-word matching task ('n' = 30. Standard measures of both RT and accuracy were examined in addition to measures obtained from fitting the ex-Gaussian distributional model to the correct RTs. For both tasks, RTs were faster in blocks of trials with feedback than in blocks without feedback, but this difference was not significant. On the other hand, with respect to the distributional analyses, providing feedback served to significantly reduce the size of the tails of the RT distributions. Such results suggest that, for conditions in which accuracy is fairly high, the effect of corrective feedback might either be to reduce the tendency to double-check before responding or to decrease the amount of attentional lapsing.

  7. Cognitive components of rural tourism destination images

    DEFF Research Database (Denmark)

    Kokkali, Panagiota; Koutsouris, Alex; Chrysochou, Polymeros

    This paper aims at exploring issues related to rural tourism destination image focusing on TDI cognitive components. By means of empirical research addressing tourists visiting the Lake Plastiras area, Central Greece, the cognitive components of the area's TDI were identified along with their eff......This paper aims at exploring issues related to rural tourism destination image focusing on TDI cognitive components. By means of empirical research addressing tourists visiting the Lake Plastiras area, Central Greece, the cognitive components of the area's TDI were identified along......; (3) visitors can be classified in four clusters according the cognitive factors; (4) tourists' clusters differ in terms of age, education and income as well as number of visits and perception of the area's attractiveness. Such findings point towards the need of both a new strategy for the area...

  8. On Low-level Cognitive Components of Speech

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2005-01-01

    In this paper we analyze speech for low-level cognitive features using linear component analysis. We demonstrate generalizable component 'fingerprints' stemming from both phonemes and speaker. Phonemes are fingerprints found at the basic analysis window time scale (20 msec), while speaker...... 'voiceprints' are found at time scales around 1000 msec. The analysis is based on homomorphic filtering features and energy based sparsification....

  9. Cognitive components of picture naming.

    Science.gov (United States)

    Johnson, C J; Paivio, A; Clark, J M

    1996-07-01

    A substantial research literature documents the effects of diverse item attributes, task conditions, and participant characteristics on the case of picture naming. The authors review what the research has revealed about 3 generally accepted stages of naming a pictured object: object identification, name activation, and response generation. They also show that dual coding theory gives a coherent and plausible account of these findings without positing amodal conceptual representations, and they identify issues and methods that may further advance the understanding of picture naming and related cognitive tasks.

  10. Effects of a cognitive dual task on variability and local dynamic stability in sustained repetitive arm movements using principal component analysis: a pilot study.

    Science.gov (United States)

    Longo, Alessia; Federolf, Peter; Haid, Thomas; Meulenbroek, Ruud

    2018-06-01

    In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

  11. Electrophysiological analysis of the cognitive component of social creativity in young males and females with different individual characteristics.

    Directory of Open Access Journals (Sweden)

    Saakyan, O. S.

    2015-07-01

    Full Text Available This article sets forth the problem of studying social creativity from the psychophysiological perspective. Presented here are the first experimental records of studying the cognitive component of social activity. This article describes the peculiar hemispheric activity during the resolution of interpersonal problems by students of different individual peculiarities and professional achievement levels. The author shows that when the solution to a verbal divergent task by young males and females of high creativity and professional achievement is reached, the frequency-spatial EEG indexes are higher in the parietal and frontal brain regions. In the solution of a convergent task, these indexes are higher in the frontal, central and cervical brain zones. In case of young males and females of low creativity and average and low levels of professional achievement, the solution of a convergent task is accompanied by increased EEG power in the central, frontal, parietal zones of both hemispheres. Thus, the assessment of the psychophysiological mechanisms of the cognitive component in social activity has shown that a definite picture of hemispheric activation stipulates the peculiarities of divergent and convergent thinking in young males and females of various levels of creativity and professional success. This difference, revealed at the initial stage of investigation, demands a deeper study of the phenomenon of social creativity in the professional training of a personality that is inclusive of this personality’s individual peculiarities.

  12. On Low-level Cognitive Components of Speech

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2006-01-01

    In this paper we analyze speech for low-level cognitive features using linear component analysis. We demonstrate generalizable component ‘fingerprints’ stemming from both phonemes and speakers. Phonemes are fingerprints found at the basic analysis window time scale (20 msec), while speaker...... ‘voiceprints’ are found at time scales around 1000 msec. The analysis is based on homomorphic filtering features and energy based sparsification....

  13. Designing simulator-based training: An approach integrating cognitive task analysis and four-component instructional design

    NARCIS (Netherlands)

    Tjiam, I.M.; Schout, B.M.; Hendrikx, A.J.M.; Scherpbier, A.J.J.A.; Witjes, J.A.; Van Merrienboer, J.J.

    2012-01-01

    Most studies of simulator-based surgical skills training have focused on the acquisition of psychomotor skills, but surgical procedures are complex tasks requiring both psychomotor and cognitive skills. As skills training is modelled on expert performance consisting partly of unconscious automatic

  14. Cognitive task analysis

    NARCIS (Netherlands)

    Schraagen, J.M.C.

    2000-01-01

    Cognitive task analysis is defined as the extension of traditional task analysis techniques to yield information about the knowledge, thought processes and goal structures that underlie observable task performance. Cognitive task analyses are conducted for a wide variety of purposes, including the

  15. 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

  16. Euler principal component analysis

    NARCIS (Netherlands)

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

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

  17. 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...

  18. Functional Components of Cognitive Impairment in Multiple Sclerosis: A Cross-Sectional Investigation

    Directory of Open Access Journals (Sweden)

    Jordi A. Matias-Guiu

    2017-11-01

    Full Text Available BackgroundCognitive impairment is frequent and disabling in multiple sclerosis (MS. Changes in information processing speed constitute the most important cognitive deficit in MS. However, given the clinical and topographical variability of the disease, cognitive impairment may vary greatly and appear in other forms in addition to slower information processing speed. Our aim was to determine the frequency of cognitive impairment, the principal cognitive domains, and components involved in MS and to identify factors associated with presence of cognitive impairment in these patients in a large series of patients.MethodsCross-sectional study of 311 patients with MS [236 with relapsing-remitting MS (RRMS, 52 with secondary progressive MS (SPMS, and 23 with primary progressive MS (PPMS]. Patients’ cognitive function was assessed with a comprehensive neuropsychological assessment protocol. Patients displaying deficits in 2 or more cognitive domains were considered to have cognitive impairment associated with MS. We conducted a principal component analysis to detect different cognitive patterns by identifying clusters of tests highly correlated to one another.ResultsCognitive impairment was detected in 41.5% of the sample, and it was more frequent in patients with SPMS and PPMS (P = 0.002. Expanded Disability Status Scale scores and education were independent predictors of cognitive impairment. Principal component analysis identified seven clusters: attention and basic executive function (including information processing speed, planning and high-level executive function, verbal memory and language, executive and visuospatial performance time, fatigue-depression, visuospatial function, and basic attention and verbal/visual working memory. Mean scoring of components 2 (high-order executive functioning and 3 (verbal memory-language was higher in patients with RRMS than in those with PPMS (component 2 and SPMS (component 3.ConclusionMS is linked to

  19. Cognitive component of Tolerance in Pedagogic Education

    Directory of Open Access Journals (Sweden)

    O. V. Akimova

    2013-01-01

    Full Text Available The paper looks at one of the urgent educational problems of tolerance development by teachers and students; tolerance being viewed as the openness to the new knowledge acquisition, willingness to understand other people and cooperate with them, and therefore the opportunity for self- development.The paper outlines the ways of tolerant attitudes formation by all the human subjects of educational process; the concept of person oriented teaching is considered to be the basic one for tolerance development. To optimize the specialists’ training for communication at any level of professional environment, the cognitive activity educational model is suggested, providing the ways out of any complicated pedagogical situation. The cognitive psychology concepts give the background for the above model. The education in question promotes the intellectual level of the prospective teachers, intensifies their creative potential, methodological thinking and practical experience, as well as tolerance development in professional communication process. 

  20. The cognitive treatment components and therapies of cognitive behavioral therapy for insomnia: A systematic review.

    Science.gov (United States)

    Jansson-Fröjmark, Markus; Norell-Clarke, Annika

    2018-06-07

    Since the beginning of the twenty-first century, there has been an increased focus on developing and testing cognitive components and therapies for insomnia disorder. The aim of the current review was thus to describe and review the efficacy of cognitive components and therapies for insomnia. A systematic review was conducted on 32 studies (N = 1455 subjects) identified through database searches. Criteria for inclusion required that each study constituted a report of outcome from a cognitive component or therapy, that the study had a group protocol, adult participants with diagnosed insomnia or undiagnosed insomnia symptoms or reported poor sleep, and that the study was published until and including 2016 in English. Each study was systematically reviewed with a standard coding sheet. Several cognitive components, a multi-component cognitive program, and cognitive therapy were identified. It is concluded that there is support for paradoxical intention and cognitive therapy. There are also other cognitive interventions that appears promising, such as cognitive refocusing and behavioral experiments. For most interventions, the study quality was rated as low to moderate. We conclude that several cognitive treatment components and therapies can be viewed as efficacious or promising interventions for patients with insomnia disorder. Methodologically stronger studies are, however, warranted. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Phonemes as short time cognitive components

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2006-01-01

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

  2. Independent component analysis: recent advances

    OpenAIRE

    Hyv?rinen, Aapo

    2013-01-01

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

  3. On Phonemes As Cognitive Components of Speech

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2008-01-01

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

  4. 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...

  5. Neurally dissociable cognitive components of reading deficits in subacute stroke.

    Science.gov (United States)

    Boukrina, Olga; Barrett, A M; Alexander, Edward J; Yao, Bing; Graves, William W

    2015-01-01

    According to cognitive models of reading, words are processed by interacting orthographic (spelling), phonological (sound), and semantic (meaning) information. Despite extensive study of the neural basis of reading in healthy participants, little group data exist on patients with reading deficits from focal brain damage pointing to critical neural systems for reading. Here, we report on one such study. We have performed neuropsychological testing and magnetic resonance imaging on 11 patients with left-hemisphere stroke (picture or word choices to a target based on meaning), phonology (matching word choices to a target based on rhyming), and orthography (a two-alternative forced choice of the most plausible non-word). They also read aloud pseudowords and words with high or low levels of usage frequency, imageability, and spelling-sound consistency. As predicted by the cognitive model, when averaged across patients, the influence of semantics was most salient for low-frequency, low-consistency words, when phonological decoding is especially difficult. Qualitative subtraction analyses revealed lesion sites specific to phonological processing. These areas were consistent with those shown previously to activate for phonology in healthy participants, including supramarginal, posterior superior temporal, middle temporal, inferior frontal gyri, and underlying white matter. Notable divergence between this analysis and previous functional imaging is the association of lesions in the mid-fusiform gyrus and anterior temporal lobe with phonological reading deficits. This study represents progress toward identifying brain lesion-deficit relationships in the cognitive components of reading. Such correspondences are expected to help not only better understand the neural mechanisms of reading, but may also help tailor reading therapy to individual neurocognitive deficit profiles.

  6. 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....

  7. Some Cognitive Components of the Diagnostic Thinking Process.

    Science.gov (United States)

    Gale, Janet

    1982-01-01

    Identifies 14 cognitive components of the diagnostic thinking process in clinical problem solving. Analyzes the differences between medical students, hospital house officers, and hospital registrars in London, England, on the relative use of such thinking processes. Suggests that diagnostic thinking processes cannot be incorporated into medical…

  8. Cognitive control components and speech symptoms in people with schizophrenia.

    Science.gov (United States)

    Becker, Theresa M; Cicero, David C; Cowan, Nelson; Kerns, John G

    2012-03-30

    Previous schizophrenia research suggests poor cognitive control is associated with schizophrenia speech symptoms. However, cognitive control is a broad construct. Two important cognitive control components are poor goal maintenance and poor verbal working memory storage. In the current research, people with schizophrenia (n=45) performed three cognitive tasks that varied in their goal maintenance and verbal working memory storage demands. Speech symptoms were assessed using clinical rating scales, ratings of disorganized speech from typed transcripts, and self-reported disorganization. Overall, alogia was associated with both goal maintenance and verbal working memory tasks. Objectively rated disorganized speech was associated with poor goal maintenance and with a task that included both goal maintenance and verbal working memory storage demands. In contrast, self-reported disorganization was unrelated to either amount of objectively rated disorganized speech or to cognitive control task performance, instead being associated with negative mood symptoms. Overall, our results suggest that alogia is associated with both poor goal maintenance and poor verbal working memory storage and that disorganized speech is associated with poor goal maintenance. In addition, patients' own assessment of their disorganization is related to negative mood, but perhaps not to objective disorganized speech or to cognitive control task performance. Published by Elsevier Ireland Ltd.

  9. Effective Components of TORDIA Cognitive-Behavioral Therapy for Adolescent Depression: Preliminary Findings

    Science.gov (United States)

    Kennard, Betsy D.; Clarke, Greg N.; Weersing, V. Robin; Asarnow, Joan Rosenbaum; Shamseddeen, Wael; Porta, Giovanna; Berk, Michele; Hughes, Jennifer L.; Spirito, Anthony; Emslie, Graham J.; Keller, Martin B.; Wagner, Karen D.; Brent, David A.

    2009-01-01

    In this report, we conducted a secondary analysis of the Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) study to explore the impact of specific cognitive-behavioral therapy (CBT) treatment components on outcome. In TORDIA, 334 youths (ages 12 to 18 years) with major depressive disorder who had failed to respond to an adequate…

  10. Cognitive and affective components of challenge and threat states.

    Science.gov (United States)

    Meijen, Carla; Jones, Marc V; McCarthy, Paul J; Sheffield, David; Allen, Mark S

    2013-01-01

    We explored the cognitive and affective components of the Theory of Challenge and Threat States in Athletes (TCTSA) using a cross-sectional design. One hundred and seventy-seven collegiate athletes indicated how they typically approached an important competition on measures of self-efficacy, perceived control, achievement goals, emotional states and interpretation of emotional states. Participants also indicated to what extent they typically perceived the important competition as a challenge and/or a threat. The results suggest that a perception of challenge was not predicted by any of the cognitive components. A perception of threat was positively predicted by avoidance goals and negatively predicted by self-efficacy and approach goals. Both challenge and threat had a positive relationship with anxiety. Practical implications of this study are that an avoidance orientation appeared to be related to potentially negative constructs such as anxiety, threat and dejection. The findings may suggest that practitioners and researchers should focus on reducing an avoidance orientation, however the results should be treated with caution in applied settings, as this study did not examine how the combination of constructs exactly influences sport performance. The results provided partial support for the TCTSA with stronger support for proposed relationships with threat rather than challenge states.

  11. Cognitive components of regularity processing in the auditory domain.

    Directory of Open Access Journals (Sweden)

    Stefan Koelsch

    Full Text Available BACKGROUND: Music-syntactic irregularities often co-occur with the processing of physical irregularities. In this study we constructed chord-sequences such that perceived differences in the cognitive processing between regular and irregular chords could not be due to the sensory processing of acoustic factors like pitch repetition or pitch commonality (the major component of 'sensory dissonance'. METHODOLOGY/PRINCIPAL FINDINGS: Two groups of subjects (musicians and nonmusicians were investigated with electroencephalography (EEG. Irregular chords elicited an early right anterior negativity (ERAN in the event-related brain potentials (ERPs. The ERAN had a latency of around 180 ms after the onset of the music-syntactically irregular chords, and had maximum amplitude values over right anterior electrode sites. CONCLUSIONS/SIGNIFICANCE: Because irregular chords were hardly detectable based on acoustical factors (such as pitch repetition and sensory dissonance, this ERAN effect reflects for the most part cognitive (not sensory components of regularity-based, music-syntactic processing. Our study represents a methodological advance compared to previous ERP-studies investigating the neural processing of music-syntactically irregular chords.

  12. Functional Generalized Structured Component Analysis.

    Science.gov (United States)

    Suk, Hye Won; Hwang, Heungsun

    2016-12-01

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

  13. The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model

    Directory of Open Access Journals (Sweden)

    Fatemeh PooraghaRoodbarde

    2017-04-01

    Full Text Available Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation.Methods: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test.Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation.Conclusions: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation.

  14. Interpretable functional principal component analysis.

    Science.gov (United States)

    Lin, Zhenhua; Wang, Liangliang; Cao, Jiguo

    2016-09-01

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

  15. Components of Effective Cognitive-Behavioral Therapy for Pediatric Headache: A Mixed Methods Approach.

    Science.gov (United States)

    Law, Emily F; Beals-Erickson, Sarah E; Fisher, Emma; Lang, Emily A; Palermo, Tonya M

    2017-01-01

    Internet-delivered treatment has the potential to expand access to evidence-based cognitive-behavioral therapy (CBT) for pediatric headache, and has demonstrated efficacy in small trials for some youth with headache. We used a mixed methods approach to identify effective components of CBT for this population. In Study 1, component profile analysis identified common interventions delivered in published RCTs of effective CBT protocols for pediatric headache delivered face-to-face or via the Internet. We identified a core set of three treatment components that were common across face-to-face and Internet protocols: 1) headache education, 2) relaxation training, and 3) cognitive interventions. Biofeedback was identified as an additional core treatment component delivered in face-to-face protocols only. In Study 2, we conducted qualitative interviews to describe the perspectives of youth with headache and their parents on successful components of an Internet CBT intervention. Eleven themes emerged from the qualitative data analysis, which broadly focused on patient experiences using the treatment components and suggestions for new treatment components. In the Discussion, these mixed methods findings are integrated to inform the adaptation of an Internet CBT protocol for youth with headache.

  16. 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

  17. 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)

  18. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Cognitive Task Analysis of Prioritization in Air Traffic Control.

    Science.gov (United States)

    Redding, Richard E.; And Others

    A cognitive task analysis was performed to analyze the key cognitive components of the en route air traffic controllers' jobs. The goals were to ascertain expert mental models and decision-making strategies and to identify important differences in controller knowledge, skills, and mental models as a function of expertise. Four groups of…

  20. Meta-Analysis of Social Cognition in Mild Cognitive Impairment.

    Science.gov (United States)

    Bora, Emre; Yener, Görsev G

    2017-07-01

    Social cognitive abilities are impaired in Alzheimer disease and other dementias. Recent studies suggested that social cognitive abilities might be also impaired in mild cognitive impairment (MCI). Current meta-analysis aimed to summarize available evidence for deficits in theory of mind (ToM) and emotion recognition in MCI. In this meta-analysis of 17 studies, facial emotion recognition and ToM performances of 513 individuals with MCI and 693 healthy controls were compared. Mild cognitive impairment was associated with significant impairments falling in the medium effect sizes range in ToM ( d = 0.63) and facial emotion recognition ( d = 0.58). Among individual emotions, recognition of fear and sadness were particularly impaired. There were no significant between-group differences in recognition of disgust, happiness, and surprise. Social cognitive deficits were more severe in multidomain MCI. There is a need for longitudinal studies investigating the potential role of social cognitive impairment in predicting conversion to dementia.

  1. Principal component regression analysis with SPSS.

    Science.gov (United States)

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

    2003-06-01

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

  2. Model reduction by weighted Component Cost Analysis

    Science.gov (United States)

    Kim, Jae H.; Skelton, Robert E.

    1990-01-01

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

  3. 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

  4. 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

  5. Mediated moderation in combined cognitive behavioral therapy versus component treatments for generalized anxiety disorder.

    Science.gov (United States)

    Newman, Michelle G; Fisher, Aaron J

    2013-06-01

    This study examined (a) duration of generalized anxiety disorder (GAD) as a moderator of cognitive behavioral therapy (CBT) versus its components (cognitive therapy and self-control desensitization) and (b) increases in dynamic flexibility of anxious symptoms during the course of psychotherapy as a mediator of this moderation. Degree of dynamic flexibility in daily symptoms was quantified as the inverse of spectral power due to daily to intradaily oscillations in four-times-daily diary data (Fisher, Newman, & Molenaar, 2011). This was a secondary analysis of the data of Borkovec, Newman, Pincus, and Lytle (2002). Seventy-six participants with a principle diagnosis of GAD were assigned randomly to combined CBT (n = 24), cognitive therapy (n = 25), or self-control desensitization (n = 27). Duration of GAD moderated outcome such that those with longer duration showed greater reliable change from component treatments than they showed from CBT, whereas those with shorter duration fared better in response to CBT. Decreasing predictability in daily and intradaily oscillations of anxiety symptoms during therapy reflected less rigidity and more flexible responding. Increases in flexibility over the course of therapy fully mediated the moderating effect of GAD duration on condition, indicating a mediated moderation process. Individuals with longer duration of GAD may respond better to more focused treatments, whereas those with shorter duration of GAD may respond better to a treatment that offers more coping strategies. Importantly, the mechanism by which this moderation occurs appears to be the establishment of flexible responding during treatment.

  6. Ecological, psychological, and cognitive components of reading difficulties: testing the component model of reading in fourth graders across 38 countries.

    Science.gov (United States)

    Chiu, Ming Ming; McBride-Chang, Catherine; Lin, Dan

    2012-01-01

    The authors tested the component model of reading (CMR) among 186,725 fourth grade students from 38 countries (45 regions) on five continents by analyzing the 2006 Progress in International Reading Literacy Study data using measures of ecological (country, family, school, teacher), psychological, and cognitive components. More than 91% of the differences in student difficulty occurred at the country (61%) and classroom (30%) levels (ecological), with less than 9% at the student level (cognitive and psychological). All three components were negatively associated with reading difficulties: cognitive (student's early literacy skills), ecological (family characteristics [socioeconomic status, number of books at home, and attitudes about reading], school characteristics [school climate and resources]), and psychological (students' attitudes about reading, reading self-concept, and being a girl). These results extend the CMR by demonstrating the importance of multiple levels of factors for reading deficits across diverse cultures.

  7. Exploratory and Confirmatory Factor Analyses in Reading-Related Cognitive Component among Grade Four Students in Thailand

    Science.gov (United States)

    Liao, Chen-Huei; Kuo, Bor-Chen; Deenang, Exkarach; Mok, Magdalena Mo Ching

    2016-01-01

    This study aimed to investigate the structure and the validity of the cognitive components of reading in Thai, which is a language with a high degree of grapheme-phoneme correspondence. The participants were 1181 fourth-grade students in 29 schools in Thailand, divided into two subsamples for data analysis. Phoneme isolation, rapid colour naming,…

  8. Neurally-dissociable cognitive components of reading deficits in subacute stroke

    Directory of Open Access Journals (Sweden)

    Olga eBoukrina

    2015-05-01

    Full Text Available According to cognitive models of reading, words are processed by interacting orthographic (spelling, phonological (sound and semantic (meaning information. Despite extensive study of the neural basis of reading in healthy participants, little group data exist on patients with reading deficits from focal brain damage pointing to critical neural systems for reading. Here we report on one such study. We have performed neuropsychological testing and MRI on 11 patients with left-hemisphere stroke (<= 5 weeks post stroke. Patients completed tasks assessing cognitive components of reading such as semantics (matching picture or word choices to a target based on meaning, phonology (matching word choices to a target based on rhyming, and orthography (a two-alternative forced choice of the most plausible nonword. They also read aloud pseudowords and words with high or low levels of usage frequency, imageability, and spelling-sound consistency. As predicted by the cognitive model, when averaged across patients, the influence of semantics was most salient for low-frequency, low-consistency words, when phonological decoding is especially difficult. Qualitative subtraction analyses revealed lesion sites specific to phonological processing. These areas were consistent with those shown previously to activate for phonology in healthy participants, including supramarginal, posterior superior temporal, middle temporal, inferior frontal gyri, and underlying white matter. Notable divergence between this analysis and previous functional imaging is the association of lesions in the mid-fusiform gyrus and anterior temporal lobe with phonological reading deficits. This study represents progress toward identifying brain lesion-deficit relationships in the cognitive components of reading. Such correspondences are expected to help not only better understand the neural mechanisms of reading, but may also help tailor reading therapy to individual neurocognitive deficit

  9. 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...

  10. Helpful Components Involved in the Cognitive-Experiential Model of Dream Work

    Science.gov (United States)

    Tien, Hsiu-Lan Shelley; Chen, Shuh-Chi; Lin, Chia-Huei

    2009-01-01

    The purpose of the study was to examine the helpful components involved in the Hill's cognitive-experiential dream work model. Participants were 27 volunteer clients from colleges and universities in northern and central parts of Taiwan. Each of the clients received 1-2 sessions of dream interpretations. The cognitive-experiential dream work model…

  11. Mediated Moderation in Combined Cognitive Behavioral Therapy versus Component Treatments for Generalized Anxiety Disorder

    Science.gov (United States)

    Newman, Michelle G.; Fisher, Aaron J.

    2013-01-01

    Objective: This study examined (a) duration of generalized anxiety disorder (GAD) as a moderator of cognitive behavioral therapy (CBT) versus its components (cognitive therapy and self-control desensitization) and (b) increases in dynamic flexibility of anxious symptoms during the course of psychotherapy as a mediator of this moderation. Degree of…

  12. A computerized method of estimation of sensor motor reaction, complicated with additional cognitive component

    Directory of Open Access Journals (Sweden)

    Gennadij V. Ganin

    2011-05-01

    Full Text Available This article is related to new integrated approach to objective computerizing evaluation of cognitive-component which delays the latent period of the sensor-motor reaction on specific visual stimuli, which carried different semantic information. It is recommended to use this method for clinical diagnostic of pathologies associated with disorders of cognitive human activity and for assessment of mental fatigue.

  13. Integrating Data Transformation in Principal Components Analysis

    KAUST Repository

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

    2015-01-01

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

  14. NEPR Principle Component Analysis - NOAA TIFF Image

    Data.gov (United States)

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

  15. Structured Performance Analysis for Component Based Systems

    OpenAIRE

    Salmi , N.; Moreaux , Patrice; Ioualalen , M.

    2012-01-01

    International audience; The Component Based System (CBS) paradigm is now largely used to design software systems. In addition, performance and behavioural analysis remains a required step for the design and the construction of efficient systems. This is especially the case of CBS, which involve interconnected components running concurrent processes. % This paper proposes a compositional method for modeling and structured performance analysis of CBS. Modeling is based on Stochastic Well-formed...

  16. Cognitive Components Predict Virtual Reality-Induced Analgesia: Repeated Measures in Healthy Subjects

    Directory of Open Access Journals (Sweden)

    Naor Demeter

    2018-01-01

    Full Text Available Virtual reality (VR is an advanced and useful technology in the distraction from pain. The efficacy of VR for reducing pain is well established. Yet, the literature analyzing the unique attributes of VR which impact pain reduction is scarce. The present study evaluated the effect of two VR environments on experimental pain levels. Both VR environments are games used with an EyeToy application which is part of the video capture VR family. The VR environments were analyzed by expert occupational therapists using a method of activity analysis, allowing for a thorough evaluation of the VR activity performance requirements. The VR environments were found to differ in the cognitive load (CL demands they apply upon subjects. Sixty-two healthy students underwent psychophysical thermal pain tests, followed by exposure to tonic heat stimulation under one of three conditions: Low CL (LCL VR, high CL (HCL VR, and control. In addition, following participation in VR, the subjects completed a self-feedback inventory evaluating their experience in VR. The results showed significantly greater pain reduction during both VR conditions compared to the control condition (p = 0.001. Hierarchical regression revealed cognitive components which were evaluated in the self-feedback inventory to be predictive factors for pain reduction only during the high cognitive load (HCL VR environment (20.2%. CL involved in VR may predict the extent of pain decrease, a finding that should be considered in future clinical and laboratory research.

  17. Constrained principal component analysis and related techniques

    CERN Document Server

    Takane, Yoshio

    2013-01-01

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

  18. 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.

  19. 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.

  20. Disentangling the cognitive components supporting Austin Maze performance in left versus right temporal lobe epilepsy.

    Science.gov (United States)

    Hocking, Julia; Thomas, Hannah J; Dzafic, Ilvana; Williams, Rebecca J; Reutens, David C; Spooner, Donna M

    2013-12-01

    Neuropsychological tests requiring patients to find a path through a maze can be used to assess visuospatial memory performance in temporal lobe pathology, particularly in the hippocampus. Alternatively, they have been used as a task sensitive to executive function in patients with frontal lobe damage. We measured performance on the Austin Maze in patients with unilateral left and right temporal lobe epilepsy (TLE), with and without hippocampal sclerosis, compared to healthy controls. Performance was correlated with a number of other neuropsychological tests to identify the cognitive components that may be associated with poor Austin Maze performance. Patients with right TLE were significantly impaired on the Austin Maze task relative to patients with left TLE and controls, and error scores correlated with their performance on the Block Design task. The performance of patients with left TLE was also impaired relative to controls; however, errors correlated with performance on tests of executive function and delayed recall. The presence of hippocampal sclerosis did not have an impact on maze performance. A discriminant function analysis indicated that the Austin Maze alone correctly classified 73.5% of patients as having right TLE. In summary, impaired performance on the Austin Maze task is more suggestive of right than left TLE; however, impaired performance on this visuospatial task does not necessarily involve the hippocampus. The relationship of the Austin Maze task with other neuropsychological tests suggests that differential cognitive components may underlie performance decrements in right versus left TLE. © 2013.

  1. Behavioral Analysis of Cognitive Content

    Science.gov (United States)

    Markle, Susan M.; Tiemann, Philip W

    1970-01-01

    The authors examine two prominent learning theories, Bruner's cognitive approach and Skinner's operant conditioning approach, hoping to "construct a 'mix' of the two traditions that really has something to say to educational practitioners. (Authors/LS)

  2. Cognitive components of rural tourism destination images: The case of Lake Plastiras, Greece

    DEFF Research Database (Denmark)

    Kokkali, Panagiota; Koutsouris, Alex; Chrysochou, Polymeros

    2009-01-01

    This paper aims at exploring issues related to rural tourism destination image (TDI) focusing on the cognitive component. By means of empirical research addressing tourists visiting the Lake Plastiras area, Central Greece, factors comprising the cognitive component of the area's TDI were identified...... of these factors; (3) visitors can be classified in four clusters according to the cognitive factors; (4) tourists' clusters differ in terms of age, education and income as well as number of visits and perception of the area's attractiveness. Such findings point towards the need of both a new strategy for the area...

  3. Social Skills Training for Young Adolescents: Cognitive and Performance Components.

    Science.gov (United States)

    Thompson, Kathryn L.; And Others

    1996-01-01

    An assertiveness training curriculum that was an expansion of two previous programs with young adolescents was presented to 22 fifth graders. Results did not show that training facilitated assertiveness on the performance components. Suggestions are offered for designing programs aimed at developing adolescents' assertive behavior in ways that…

  4. 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.

  5. Brain insulin signaling: a key component of cognitive processes and a potential basis for cognitive impairment in type 2 diabetes

    Science.gov (United States)

    McNay, Ewan C.; Recknagel, Andrew K.

    2011-01-01

    Understanding of the role of insulin in the brain has gradually expanded, from initial conceptions of the brain as insulin-insensitive through identification of a role in regulation of feeding to recent demonstration of insulin as a key component of hippocampal memory processes. Conversely, systemic insulin resistance such as that seen in type 2 diabetes is associated with a range of cogntive and neural deficits. Here we review the evidence for insulin as a cognitive and neural modulator, including potential effector mechanisms, and examine the impact that type 2 diabetes has on these mechanisms in order to identify likely bases for the cognitive impairments seen in type 2 diabetic patients. PMID:21907815

  6. Analysis and training of cognitive skills

    International Nuclear Information System (INIS)

    Mumaw, R.J.

    1991-01-01

    Cognitive skills (e.g., decision making, problem solving) are critical to many jobs in the nuclear power industry, and yet the standard approach to training development does not always train these skills most effectively. In most cases, these skills are not described in sufficient detail, and training programs fail to address them explicitly. Cognitive psychologists have developed a set of techniques, based on analysis of expertise, for describing cognitive skills in more detail. These techniques incorporate a diverse set of human performance measures. An example is given to illustrate a method for determining how experts represent problems mentally. Cognitive psychologists have also established a set of empirical findings concerning skill acquisition. These findings can be used to provide some general rules for structuring the training of cognitive skills

  7. Principal components analysis in clinical studies.

    Science.gov (United States)

    Zhang, Zhongheng; Castelló, Adela

    2017-09-01

    In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

  8. 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 ...

  9. 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 ...

  10. 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...

  11. The multi-component model of working memory: explorations in experimental cognitive psychology.

    Science.gov (United States)

    Repovs, G; Baddeley, A

    2006-04-28

    There are a number of ways one can hope to describe and explain cognitive abilities, each of them contributing a unique and valuable perspective. Cognitive psychology tries to develop and test functional accounts of cognitive systems that explain the capacities and properties of cognitive abilities as revealed by empirical data gathered by a range of behavioral experimental paradigms. Much of the research in the cognitive psychology of working memory has been strongly influenced by the multi-component model of working memory [Baddeley AD, Hitch GJ (1974) Working memory. In: Recent advances in learning and motivation, Vol. 8 (Bower GA, ed), pp 47-90. New York: Academic Press; Baddeley AD (1986) Working memory. Oxford, UK: Clarendon Press; Baddeley A. Working memory: Thought and action. Oxford: Oxford University Press, in press]. By expanding the notion of a passive short-term memory to an active system that provides the basis for complex cognitive abilities, the model has opened up numerous questions and new lines of research. In this paper we present the current revision of the multi-component model that encompasses a central executive, two unimodal storage systems: a phonological loop and a visuospatial sketchpad, and a further component, a multimodal store capable of integrating information into unitary episodic representations, termed episodic buffer. We review recent empirical data within experimental cognitive psychology that has shaped the development of the multicomponent model and the understanding of the capacities and properties of working memory. Research based largely on dual-task experimental designs and on neuropsychological evidence has yielded valuable information about the fractionation of working memory into independent stores and processes, the nature of representations in individual stores, the mechanisms of their maintenance and manipulation, the way the components of working memory relate to each other, and the role they play in other

  12. 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.

  13. PCA: Principal Component Analysis for spectra modeling

    Science.gov (United States)

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

    2012-07-01

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

  14. 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.

  15. Examining adherence to components of cognitive-behavioral therapy for youth anxiety after training and consultation

    OpenAIRE

    Edmunds, Julie M.; Brodman, Douglas M.; Ringle, Vanesa A.; Read, Kendra L.; Kendall, Philip C.; Beidas, Rinad S.

    2016-01-01

    The present study examined 115 service providers’ adherence to components of cognitive-behavioral therapy (CBT) for youth anxiety prior to training, post workshop training, and after three months of weekly consultation. Adherence was measured using a role-play with a trained actor. We examined differences in individual adherence to CBT components across time and the relationship between number of consultation sessions attended and adherence ratings following consultation. Findings indicated t...

  16. Increased plasma concentration of serum amyloid P component in centenarians with impaired cognitive performance

    DEFF Research Database (Denmark)

    Nybo, M; Olsen, H; Jeune, B

    1998-01-01

    these to the cognitive performance evaluated by Mini Mental State Examination (MMSE). We observed a significantly (p gender-matched controls (32.8+/-11.4 microg/ml). Six severely demented centenarians had an even......Serum amyloid P component (SAP) binds to all amyloid fibrils including those in the plaques and tangles of Alzheimer patients. To investigate whether the plasma SAP concentration correlated to cognitive impairment, we measured SAP levels in blood samples from 41 centenarians and compared...... higher SAP concentration (60.2 microg/ml), while the subgroup of cognitive intact centenarians (MMSE score >24) showed a normal SAP concentration (38.4+/-9.3 microg/ml). No dehydration or hepatic dysfunction was demonstrable in the centenarians. We conclude that the centenarians with impaired cognitive...

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  18. Improvement of Binary Analysis Components in Automated Malware Analysis Framework

    Science.gov (United States)

    2017-02-21

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

  19. 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

  20. Multilevel sparse functional principal component analysis.

    Science.gov (United States)

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

    2014-01-29

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

  1. A Genealogical Interpretation of Principal Components Analysis

    Science.gov (United States)

    McVean, Gil

    2009-01-01

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

  2. Thinking versus feeling: differentiating between cognitive and affective components of perceived cancer risk.

    Science.gov (United States)

    Janssen, Eva; van Osch, Liesbeth; Lechner, Lilian; Candel, Math; de Vries, Hein

    2012-01-01

    Despite the increased recognition of affect in guiding probability estimates, perceived risk has been mainly operationalised in a cognitive way and the differentiation between rational and intuitive judgements is largely unexplored. This study investigated the validity of a measurement instrument differentiating cognitive and affective probability beliefs and examined whether behavioural decision making is mainly guided by cognition or affect. Data were obtained from four surveys focusing on smoking (N=268), fruit consumption (N=989), sunbed use (N=251) and sun protection (N=858). Correlational analyses showed that affective likelihood was more strongly correlated with worry compared to cognitive likelihood and confirmatory factor analysis provided support for a two-factor model of perceived likelihood instead of a one-factor model (i.e. cognition and affect combined). Furthermore, affective likelihood was significantly associated with the various outcome variables, whereas the association for cognitive likelihood was absent in three studies. The findings provide support for the construct validity of the measures used to assess cognitive and affective likelihood. Since affective likelihood might be a better predictor of health behaviour than the commonly used cognitive operationalisation, both dimensions should be considered in future research.

  3. Advanced Analysis Cognition: Improving the Cognition of Intelligence Analysis

    Science.gov (United States)

    2013-09-01

    Reviews, 3rd ed., Sage Publications, Thousand Oaks, CA, 1998. 5 Higgins, J.P.T. & Green , S. (eds) Cochrane Handbook for Systematic Reviews of...Structured Analytic Techniques for Intelligence Analysis, CQ Press, Washington, D.C., 2011. Higgins, J.P.T. & Green , S. (eds) Cochrane Handbook...RW 3989) Bleicher, J. Contemporary Hermeneutics: Hermeneutics as Method, Philosophy, and Critique, Routledge & Kegan Paul, London; Boston, 1980

  4. Radar fall detection using principal component analysis

    Science.gov (United States)

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

    2016-05-01

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

  5. 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...

  6. 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

  7. 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)

  8. Reformulating Component Identification as Document Analysis Problem

    NARCIS (Netherlands)

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

    2007-01-01

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

  9. Nonlinear principal component analysis and its applications

    CERN Document Server

    Mori, Yuichi; Makino, Naomichi

    2016-01-01

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

  10. 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.

  11. The Relationship Between Empathy and Reading Fiction: Separate Roles for Cognitive and Affective Components

    Directory of Open Access Journals (Sweden)

    John Stansfield

    2014-07-01

    Full Text Available Research suggests that both life-time experience of reading fiction and the extent to which a reader feels ‘transported’ by the narrative are associated with empathy. This study examined these relationships further by delineating empathy into cognitive and affective components. Thirty-three participants were tested on prior exposure to fiction, transportation, and different measures of cognitive empathy, affective empathy and helping tendency. The results revealed that exposure to fiction was associated with trait cognitive, but not affective, empathy, while the experience of being transported was associated with story-induced affective empathy. Story-induced affective empathy was also associated with helping tendency. The results are discussed by considering implications for relationships between reactions to fictional worlds and reactions to real-world behaviours.

  12. Cognitive analysis of physicians' medication ordering activity.

    Science.gov (United States)

    Pelayo, Sylvia; Leroy, Nicolas; Guerlinger, Sandra; Degoulet, Patrice; Meaux, Jean-Jacques; Beuscart-Zéphir, Marie-Catherine

    2005-01-01

    Computerized Physician Order Entry (CPOE) addresses critical functions in healthcare systems. As the name clearly indicates, these systems focus on order entry. With regard to medication orders, such systems generally force physicians to enter exhaustively documented orders. But a cognitive analysis of the physician's medication ordering task shows that order entry is the last (and least) important step of the entire cognitive therapeutic decision making task. We performed a comparative analysis of these complex cognitive tasks in two working environments, computer-based and paper-based. The results showed that information gathering, selection and interpretation are critical cognitive functions to support the therapeutic decision making. Thus the most important requirement from the physician's perspective would be an efficient display of relevant information provided first in the form of a summarized view of the patient's current treatment, followed by in a more detailed focused display of those items pertinent to the current situation. The CPOE system examined obviously failed to provide the physicians this critical summarized view. Following these results, consistent with users' complaints, the Company decided to engage in a significant re-engineering process of their application.

  13. 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

  14. 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

  15. Integrating Data Transformation in Principal Components Analysis

    KAUST Repository

    Maadooliat, Mehdi

    2015-01-02

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

  16. The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model

    OpenAIRE

    Fatemeh PooraghaRoodbarde; Siavash Talepasand; Issac Rahimian Boogar

    2017-01-01

    Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation.Methods: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation inter...

  17. (Re)defining component structures in morphological constructions: a cognitive grammar perspective

    CSIR Research Space (South Africa)

    Van Huyssteen, GB

    2010-01-01

    Full Text Available )defining Component Structures in Morphological Constructions: A Cognitive Grammar Perspective Gerhard B van Huyssteen 1. Introduction The study of words, parts of words, and word-formation is one of the fields of enquiry that has kept language philosophers... and linguists busy for centuries. Despite this long tradition, the literature on word morphology sometimes remains rather imprecise, ambiguous and/or vague; for example, Tuggy (1992: 287) illustrates that ?(d)efinitions, when given, are frequently circular...

  18. Cognitive and collaborative demands of freight conductor activities: results and implications of a cognitive task analysis

    Science.gov (United States)

    2012-07-31

    This report presents the results of a cognitive task analysis (CTA) that examined the cognitive and collaborative demands placed on conductors, as well as the knowledge and skills that experienced conductors have developed that enable them to operate...

  19. Concurrent hippocampal induction of MHC II pathway components and glial activation with advanced aging is not correlated with cognitive impairment

    Directory of Open Access Journals (Sweden)

    Sonntag William E

    2011-10-01

    Full Text Available Abstract Background Age-related cognitive dysfunction, including impairment of hippocampus-dependent spatial learning and memory, affects approximately half of the aged population. Induction of a variety of neuroinflammatory measures has been reported with brain aging but the relationship between neuroinflammation and cognitive decline with non-neurodegenerative, normative aging remains largely unexplored. This study sought to comprehensively investigate expression of the MHC II immune response pathway and glial activation in the hippocampus in the context of both aging and age-related cognitive decline. Methods Three independent cohorts of adult (12-13 months and aged (26-28 months F344xBN rats were behaviorally characterized by Morris water maze testing. Expression of MHC II pathway-associated genes identified by transcriptomic analysis as upregulated with advanced aging was quantified by qPCR in synaptosomal fractions derived from whole hippocampus and in hippocampal subregion dissections (CA1, CA3, and DG. Activation of astrocytes and microglia was assessed by GFAP and Iba1 protein expression, and by immunohistochemical visualization of GFAP and both CD74 (Ox6 and Iba1. Results We report a marked age-related induction of neuroinflammatory signaling transcripts (i.e., MHC II components, toll-like receptors, complement, and downstream signaling factors throughout the hippocampus in all aged rats regardless of cognitive status. Astrocyte and microglial activation was evident in CA1, CA3 and DG of intact and impaired aged rat groups, in the absence of differences in total numbers of GFAP+ astrocytes or Iba1+ microglia. Both mild and moderate microglial activation was significantly increased in all three hippocampal subregions in aged cognitively intact and cognitively impaired rats compared to adults. Neither induction of MHCII pathway gene expression nor glial activation correlated to cognitive performance. Conclusions These data demonstrate a

  20. 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.)

  1. 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.)

  2. Error analysis of nuclear power plant operator cognitive behavior

    International Nuclear Information System (INIS)

    He Xuhong; Zhao Bingquan; Chen Yulong

    2001-01-01

    Nuclear power plant is a complex human-machine system integrated with many advanced machines, electron devices and automatic controls. It demands operators to have high cognitive ability and correct analysis skill. The author divides operator's cognitive process into five stages to analysis. With this cognitive model, operator's cognitive error is analysed to get the root causes and stages that error happens. The results of the analysis serve as a basis in design of control rooms and training and evaluation of operators

  3. Group-wise Principal Component Analysis for Exploratory Data Analysis

    NARCIS (Netherlands)

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

    2017-01-01

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

  4. Relationships between the emotional and cognitive components of alexithymia and dependency in alcoholics.

    Science.gov (United States)

    Loas, G; Otmani, O; Lecercle, C; Jouvent, R

    2000-09-25

    Several authors have shown that alexithymia, emotional and perceptual dependency characterize patients suffering from substance abuse. The aim of the study is to test the hypothesis that the emotional and cognitive components of alexithymia are associated with dependency in alcoholics. Three groups were investigated: 60 inpatients meeting the DSM-IV criteria for alcohol dependence, 57 healthy subjects, 144 university students. All subjects completed the following rating scales: The 20-item Toronto Alexithymia Scale (TAS-20), the Interpersonal Dependency Inventory (IDI), the Beck Depression Inventory (BDI), and the Embedded Figures Test (EFT). Partial correlations, using the BDI score as constant, were calculated. In normal subjects, the 'Emotion' subscale of the TAS-20 correlated with the 'Lack of social self-confidence' subscale of the IDI and the 'Cognitive' subscale of the TAS-20 did not correlate with the EFT score. In alcoholics, the 'Cognitive' subscale of the TAS-20 correlated with the 'Lack of social self-confidence' subscale, with the EFT score and with the 'Affirmation of autonomy' subscale. A particular cognitive style characterized by externally oriented thinking, affirmation of autonomy as denial of emotional dependency and field dependence could characterize alcoholics.

  5. Gene set analysis using variance component tests.

    Science.gov (United States)

    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.

  6. The projected hand illusion: component structure in a community sample and association with demographics, cognition, and psychotic-like experiences.

    Science.gov (United States)

    Graham, Kyran T; Martin-Iverson, Mathew T; Holmes, Nicholas P; Waters, Flavie A

    2015-01-01

    The projected hand illusion (PHI) is a variant of the rubber hand illusion (RHI), and both are commonly used to study mechanisms of self-perception. A questionnaire was developed by Longo et al. (2008) to measure qualitative changes in the RHI. Such psychometric analyses have not yet been conducted on the questionnaire for the PHI. The present study is an attempt to validate minor modifications of the questionnaire of Longo et al. to assess the PHI in a community sample (n = 48) and to determine the association with selected demographic (age, sex, years of education), cognitive (Digit Span), and clinical (psychotic-like experiences) variables. Principal components analysis on the questionnaire data extracted four components: Embodiment of "Other" Hand, Disembodiment of Own Hand, Deafference, and Agency-in both synchronous and asynchronous PHI conditions. Questions assessing "Embodiment" and "Agency" loaded onto orthogonal components. Greater illusion ratings were positively associated with being female, being younger, and having higher scores on psychotic-like experiences. There was no association with cognitive performance. Overall, this study confirmed that self-perception as measured with PHI is a multicomponent construct, similar in many respects to the RHI. The main difference lies in the separation of Embodiment and Agency into separate constructs, and this likely reflects the fact that the "live" image of the PHI presents a more realistic picture of the hand and of the stroking movements of the experimenter compared with the RHI.

  7. The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic.

    Science.gov (United States)

    Han, Hye Joo; Schweickert, Richard; Xi, Zhuangzhuang; Viau-Quesnel, Charles

    2016-04-01

    For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream social network is not a copy of the cognitive social network. Waking life social networks tend to have positive assortativity; that is, people tend to be connected to others with similar connectivity. Instead, in our sample of dream social networks assortativity is more often negative or near 0, as in online social networks. We show that if characters appear via a random walk, negative assortativity can result, particularly if the random walk is biased as suggested by remote associations. Copyright © 2015 Cognitive Science Society, Inc.

  8. Iso-α-acids, bitter components of beer, prevent obesity-induced cognitive decline.

    Science.gov (United States)

    Ayabe, Tatsuhiro; Ohya, Rena; Kondo, Keiji; Ano, Yasuhisa

    2018-03-19

    Dementia and cognitive decline have become worldwide public health problems, and it was recently reported that life-style related diseases and obesity are key risk factors in dementia. Iso-α-acids, hop-derived bitter components of beer, have been reported to have various physiological functions via activation of peroxisome proliferator-activated receptor γ. In this report, we demonstrated that daily intake of iso-α-acids suppresses inflammations in the hippocampus and improves cognitive decline induced by high fat diet (HFD). Body weight, epididymal fat weight, and plasma triglyceride levels were increased in HFD-fed mice, and significantly decreased in iso-α-acids supplemented HFD-fed mice. HFD feeding enhances the production of inflammatory cytokines and chemokines, such as TNF-α, which was significantly suppressed by iso-α-acids administration. HFD-induced neuroinflammation caused lipid peroxidation, neuronal loss, and atrophy in hippocampus, and those were not observed in iso-α-acids-treated mice. Furthermore, iso-α-acids intake significantly improved cognitive decline induced by HFD-feeding. Iso-α-acids are food derived components that suppressing both lipid accumulation and brain inflammation, thus iso-α-acids might be beneficial for the risk of dementia increased by obesity and lifestyle-related diseases.

  9. 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...

  10. Is It the Cognitive or the Behavioral Component Which Makes Cognitive-Behavior Modification Effective in Test Anxiety?

    Science.gov (United States)

    Kaplan, Robert M.; And Others

    1979-01-01

    Test-anxious subjects were assigned to condition groups: (1) desensitization only; (2) cognitive only; (3) cognitive plus desensitization; and (4) neither cognitive nor desensitization. On test anxiety and self-rating measures, combined treatment and desensitization were less effective than the cognitive-only treatment. Results are consistent with…

  11. Examining adherence to components of cognitive-behavioral therapy for youth anxiety after training and consultation.

    Science.gov (United States)

    Edmunds, Julie M; Brodman, Douglas M; Ringle, Vanesa A; Read, Kendra L; Kendall, Philip C; Beidas, Rinad S

    2017-02-01

    The present study examined 115 service providers' adherence to components of cognitive-behavioral therapy (CBT) for youth anxiety prior to training, post workshop training, and after three months of weekly consultation. Adherence was measured using a role-play with a trained actor. We examined differences in individual adherence to CBT components across time and the relationship between number of consultation sessions attended and adherence ratings following consultation. Findings indicated that somatic arousal identification and relaxation were the most used treatment components prior to training. Adherence to all components of CBT increased following workshop training, except the usage of problem-solving. Adherence to problem-solving, positive reinforcement, the identification of anxious self-talk, and the creation of coping thoughts increased following consultation but usage of problem-solving remained low compared to other treatment components. Overall adherence remained less than optimal at the final measurement point. Number of consultation sessions attended predicted post-consultation adherence to identification of somatic arousal, identification of anxious self-talk, and positive reinforcement. Implications include tailoring future training based on baseline levels of adherence and spending more time during training and consultation on underutilized CBT components, such as problem-solving. Limitations of the present study, including how adherence was measured, are discussed. This study adds to the implementation science literature by providing more nuanced information on changes in adherence over the course of training and consultation of service providers.

  12. Recoding of Information as a Component of Cognitive Training Technologies in the Course "Engineering Graphics"

    Directory of Open Access Journals (Sweden)

    I. N. Lunina

    2015-01-01

    Full Text Available The efficiency to understand scientific and technical information is a relevant problem for a modern type of students. It is particularly acute for the freshmen learning the course of engineering graphics, which is one of the basic disciplines in engineering education.This problem, generally, arises from the information blow-up and cognitive students’ deficiency. The students need to perceive, understand, take in, and apply a huge amount of information to acquire obligatory professional competencies. The cognitive deficiency is because of the poor school knowledge in geometry and graphics, underdeveloped spatial and logical thinking, lack of skills to work with educational and reference books, clip thinking.The modern engineering graphics teaches a technology for the visual presentation of information, graphical illustration, and interpretation of scientific and technical texts. The text is considered to be a completed piece of information that is described in any way – verbal, graphical, symbolic. Graphical language is a professionally oriented language of engineers.One of the components of cognitive learning technologies aimed at understanding the meaning of the studied texts is the development the skills for recoding some information, because a criterion of understanding the meaning of the text is the independent student’s ability to represent the verbal texts in the form of drawings, blueprints, charts, diagrams, tables, formulae, and numeric entries.The article explores some examples of transcoding texts used in the course of engineering graphics (in lectures, seminars, homework, tests. It is emphasized that integrated presentation (verbal + graphical + symbolic that creates the cohesion of the verbal and figurative components of thinking allows students to gain the most thorough understanding the meaning of educational information. This enables students to minimize their cognitive deficiency, elevate scientific mind, and promote

  13. Analysis of failed nuclear plant components

    Science.gov (United States)

    Diercks, D. R.

    1993-12-01

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

  14. 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

  15. 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

  16. 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.

  17. 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

  18. Mapping ash properties using principal components analysis

    Science.gov (United States)

    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

  19. Generalized structured component analysis a component-based approach to structural equation modeling

    CERN Document Server

    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...

  20. Cognitive task load analysis : Allocating tasks and designing support

    NARCIS (Netherlands)

    Neerincx, M.A.

    2003-01-01

    We present a method for Cognitive Task Analysis that guides the early stages of software development, aiming at an optimal cognitive load for operators of process control systems. The method is based on a practical theory of cognitive task load and support. In addition to the classical measure

  1. Components of a Mediterranean diet and their impact on cognitive functions in aging

    Directory of Open Access Journals (Sweden)

    Sebastian eHuhn

    2015-07-01

    Full Text Available Background: Adhering to the Mediterranean diet (MeDi is known to be beneficial with regard to age-associated diseases including cardiovascular diseases and type 2 diabetes. Recent studies also suggest an impact on cognition and brain structure, and increasing effort is made to track effects down to single nutrients.Aims: To review whether two MeDi components, i.e. long-chain omega-3 fatty acids (LC-n3-FA derived from sea-fish, and plant polyphenols including resveratrol (RSV, exert positive effects on brain health in aging. Content: We summarized health benefits associated with the MeDi and evaluated available studies on the effect of (1 fish-consumption and LC-n3-FA supplementation as well as (2 diet-derived or supplementary polyphenols such as RSV, on cognitive performance and brain structure in animal models and human studies. Also, we discussed possible underlying mechanisms.Conclusion: A majority of available studies suggest that consumption of LC-n3-FA with fish or fishoil-supplements exerts positive effects on brain health and cognition in older humans. However, more large-scale randomized controlled trials are needed to draw definite recommendations. Considering polyphenols and RSV, only a few controlled studies are available to date, yet the evidence based on animal research and first interventional human trials is promising and warrants further investigation. In addition, the concept of food synergy within the MeDi encourages future trials that evaluate the impact of comprehensive lifestyle patterns to help maintaining cognitive functions into old age.

  2. 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...

  3. 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

  4. Applying pause analysis to explore cognitive processes in the copying of sentences by second language users

    OpenAIRE

    Zulkifli, Putri Afzan Maria Binti

    2013-01-01

    Pause analysis is a method that investigates processes of writing by measuring the amount of time between pen strokes. It provides the field of second language studies with a means to explore the cognitive processes underpinning the nature of writing. This study examined the potential of using free handwritten copying of sentences as a means of investigating components of the cognitive processes of adults who have English as their Second Language (ESL).\\ud \\ud A series of one pilot and three ...

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

    Science.gov (United States)

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

    2016-10-03

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

  6. A meta-analysis of executive components of working memory.

    Science.gov (United States)

    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.

  7. 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.

  8. Visual behaviour analysis and driver cognitive model

    Energy Technology Data Exchange (ETDEWEB)

    Baujon, J.; Basset, M.; Gissinger, G.L. [Mulhouse Univ., (France). MIPS/MIAM Lab.

    2001-07-01

    Recent studies on driver behaviour have shown that perception - mainly visual but also proprioceptive perception - plays a key role in the ''driver-vehicle-road'' system and so considerably affects the driver's decision making. Within the framework of the behaviour analysis and studies low-cost system (BASIL), this paper presents a correlative, qualitative and quantitative study, comparing the information given by visual perception and by the trajectory followed. This information will help to obtain a cognitive model of the Rasmussen type according to different driver classes. Many experiments in real driving situations have been carried out for different driver classes and for a given trajectory profile, using a test vehicle and innovative, specially designed, real-time tools, such as the vision system or the positioning module. (orig.)

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  10. Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis

    OpenAIRE

    Nickl-Jockschat, Thomas; Kleiman, Alexandra; Schulz, Jörg B.; Schneider, Frank; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.; Reetz, Kathrin

    2011-01-01

    Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in st...

  11. 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.

  12. 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 ...

  13. Effects of the Cognitive-Behavioral Therapy for Stress Management on Executive Function Components.

    Science.gov (United States)

    Santos-Ruiz, Ana; Robles-Ortega, Humbelina; Pérez-García, Miguel; Peralta-Ramírez, María Isabel

    2017-02-13

    This study aims to determine whether it is possible to modify executive function in stressed individuals by means of cognitive-behavioral therapy for stress management. Thirty-one people with high levels of perceived stress were recruited into the study (treatment group = 18; wait-list group = 13). The treatment group received 14 weeks of stress management program. Psychological and executive function variables were evaluated in both groups pre and post-intervention. The treatment group showed improved psychological variables of perceived stress (t = 5.492; p = .001), vulnerability to stress (t = 4.061; p = .001) and superstitious thinking (t = 2.961; p = .009). Likewise, the results showed statistically significant differences in personality variables related to executive function, positive urgency (t = 3.585; p = .002) and sensitivity to reward (t = -2.201; p = .042), which improved after the therapy. These variables showed a moderate to high effect size (oscillates between 1.30 for perceived stress and .566 for sensitivity to reward). The cognitive-behavioral therapy for stress management may be an appropriate strategy for improving personality construct components related to executive function, however effects of the therapy are not showed on performance on the tests of executive function applied, as presented studies previous.

  14. Cross-cultural aging in cognitive and affective components of subjective well-being.

    Science.gov (United States)

    Pethtel, Olivia; Chen, Yiwei

    2010-09-01

    The present study examined age and cultural differences in cognitive and affective components of subjective well-being. A sample of 188 American and Chinese young and older adults completed surveys measuring self-life satisfaction, perceived family's life satisfaction, positive affect, and negative affect. Across cultures, older adults reported lower negative affect than did young adults. Americans reported higher self-life satisfaction, perceived family's life satisfaction, and positive affect than did Chinese. In addition, perceived family's life satisfaction was more related to self-life satisfaction for Chinese than for Americans. Findings are discussed in light of socioemotional selectivity theory and theories on culture and self-construal. (c) 2010 APA, all rights reserved.

  15. Short-term changes in affective, behavioral, and cognitive components of body image after bariatric surgery.

    Science.gov (United States)

    Williams, Gail A; Hudson, Danae L; Whisenhunt, Brooke L; Stone, Megan; Heinberg, Leslie J; Crowther, Janis H

    2018-04-01

    Many bariatric surgery candidates report body image concerns before surgery. Research has reported post-surgical improvements in body satisfaction, which may be associated with weight loss. However, research has failed to comprehensively examine changes in affective, behavioral, and cognitive body image. This research examined (1) short-term changes in affective, behavioral, and cognitive components of body image from pre-surgery to 1- and 6-months after bariatric surgery, and (2) the association between percent weight loss and these changes. Participants were recruited from a private hospital in the midwestern United States. Eighty-eight females (original N = 123; lost to follow-up: n = 15 at 1-month and n = 20 at 6-months post-surgery) completed a questionnaire battery, including the Body Attitudes Questionnaire, Body Checking Questionnaire, Body Image Avoidance Questionnaire, and Body Shape Questionnaire, and weights were obtained from patients' medical records before and at 1- and 6-months post-surgery. Results indicated significant decreases in body dissatisfaction, feelings of fatness, and body image avoidance at 1- and 6-months after bariatric surgery, with the greatest magnitude of change occurring for body image avoidance. Change in feelings of fatness was significantly correlated with percent weight loss at 6-months, but not 1-month, post-surgery. These findings highlight the importance of examining short-term changes in body image from a multidimensional perspective in the effort to improve postsurgical outcomes. Unique contributions include the findings regarding the behavioral component of body image, as body image avoidance emerges as a particularly salient concern that changes over time among bariatric surgery candidates. Copyright © 2018 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  16. 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

  17. 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....

  18. Nonparametric inference in nonlinear principal components analysis : exploration and beyond

    NARCIS (Netherlands)

    Linting, Mariëlle

    2007-01-01

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

  19. Principal component analysis networks and algorithms

    CERN Document Server

    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.

  20. Relationship between cognition, clinical and cognitive insight in psychotic disorders : A review and meta-analysis

    NARCIS (Netherlands)

    Nair, Akshay; Palmer, Emma Claire; Aleman, Andre; David, Anthony S.

    The neurocognitive theory of insight posits that poor insight in psychotic illnesses is related to cognitive deficits in cognitive self-appraisal mechanisms. In this paper we perform a comprehensive meta-analysis examining relationships between clinical insight and neurocognition in psychotic

  1. Blind source separation dependent component analysis

    CERN Document Server

    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.

  2. 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....

  3. 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...

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

    Science.gov (United States)

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

    2015-01-01

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

  5. 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)

  6. Cognitive component of psychomotor retardation in unipolar and bipolar depression: Is verbal fluency a relevant marker? Impact of repetitive transcranial stimulation.

    Science.gov (United States)

    Thomas-Ollivier, Véronique; Foyer, Emmanuelle; Bulteau, Samuel; Pichot, Anne; Valriviere, Pierre; Sauvaget, Anne; Deschamps, Thibault

    2017-09-01

    In the literature, psychomotor retardation (PMR) is increasingly highlighted as a relevant marker for depression. Currently, we chose to focus on the fluency capacities as an evaluation of the frontal lobes functioning to reach a better understanding of cognitive and neurobiological mechanisms involved in PMR in depression. The aims of this study were: (i) to explore the cognitive component of PMR through the analysis of verbal fluency (VF) performance in unipolar and bipolar depression; and (ii) to examine whether a repetitive transcranial magnetic stimulation treatment could improve concomitantly the PMR and VF capacities, as a relevant marker characteristic of the cognitive component of PMR. Fifteen unipolar and 15 bipolar patients were compared to 15 healthy adults. Before treatment, the results showed VF deficits, particularly marked in the bipolar group. The investigation of the interplay between PMR, VF performance, Montgomery-Åsberg Depression Rating Scale scores, and Montreal Cognitive Assessment scores showed that the deficits in these various dimensions were not homogeneous. The absence of correlation between the psychomotor retardation scale (the French Retardation Rating Scale for Depression) and VF, and the correlation with MoCA raise the hypothesis of a more global cognitive impairment associated with PMR in the BD group. The repetitive transcranial magnetic stimulation treatment had a positive impact on depression, PMR, and fluency scores. Correlations between the Retardation Rating Scale for Depression and VF performances appeared after treatment, showing the cognitive role of psychomotor functioning in depression. Further analyses, including other cognitive measures in an objective evaluation of PMR, are required for a better understanding of these complex relationships. © 2017 The Authors. Psychiatry and Clinical Neurosciences © 2017 Japanese Society of Psychiatry and Neurology.

  7. 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

  8. Cognitive governance, cognitive mapping and cognitive conflicts: Structural analysis with the MICMAC method

    Directory of Open Access Journals (Sweden)

    Garoui Nassreddine

    2014-12-01

    Full Text Available This research aims to achieve a better understanding of the modes of conceptualization and thinking on issues of governance. It is part of a cognitive approach, to our knowledge unprecedented. This research has shown that the mapping concepts of governance can provide the original performance and meaningful. The purpose was to plot the thought of governance actors in the form of a cognitive map and analyze it. The results highlighted the relative importance of the concepts they used, the dimensions from which they structured more or less consciously, here own thoughts, and the nature and characteristics of the concepts they considered primarily as an explanation or consequences. They allowed characterizing very special or very precise structure and content of the thought of these actors. The construction of collective cognitive maps is to help structure the relationship between governance actors in the sense that it will detect the conflict relations of cognitive order. The cognitive map is by definition a representation of mental models of actors on any topic. Actors of governance do not have the same definitions of the concepts of governance that represents for us a sort of cognitive conflict and hence through cognitive mapping can map the concentration of these conflicts and we are still looking for more to show the effectiveness governance mechanisms to resolve these conflicts.

  9. Positive effects of combined cognitive and physical exercise training on cognitive function in older adults with mild cognitive impairment or dementia : A meta-analysis

    NARCIS (Netherlands)

    Karssemeijer, Esther G. A.; Aaronson, Justine A.; Bossers, Willem J.; Smits, Tara; Rikkert, Marcel G. M. Olde; Kessels, Roy P. C.

    2017-01-01

    Combined cognitive and physical exercise interventions have potential to elicit cognitive benefits in older adults with mild cognitive impairment (MCI) or dementia. This meta-analysis aims to quantify the overall effect of these interventions on global cognitive functioning in older adults with MCI

  10. Positive effects of combined cognitive and physical exercise training on cognitive function in older adults with mild cognitive impairment or dementia : A meta-analysis

    NARCIS (Netherlands)

    Karssemeijer, Esther G. A.; Aaronson, Justine A.; Bossers, Willem J.; Smits, Tara; Rikkert, Marcel G. M. Olde; Kessels, Roy P. C.

    Combined cognitive and physical exercise interventions have potential to elicit cognitive benefits in older adults with mild cognitive impairment (MCI) or dementia. This meta-analysis aims to quantify the overall effect of these interventions on global cognitive functioning in older adults with MCI

  11. Cognitive components of self esteem for individuals with severe mental illness.

    Science.gov (United States)

    Blankertz, L

    2001-10-01

    In a sample of 182 individuals with severe mental illness, the applicability of reflected appraisals and self-enhancement theories as explanations for global self-esteem was examined at two time points on components of stigma, mastery, overall functioning, education, and job prestige. Path analysis demonstrated that the two theories work independently; and that stigma, mastery, and overall functioning are significant, persist over time, and have an enduring effect on self-esteem.

  12. 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.

  13. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

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

    2003-01-01

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

  14. Key components of financial-analysis education for clinical nurses.

    Science.gov (United States)

    Lim, Ji Young; Noh, Wonjung

    2015-09-01

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

  15. Dynamic Modal Analysis of Vertical Machining Centre Components

    OpenAIRE

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

    2009-01-01

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

  16. An electrophysiological analysis of altered cognitive functions in Huntington disease.

    Science.gov (United States)

    Münte, T F; Ridao-Alonso, M E; Preinfalk, J; Jung, A; Wieringa, B M; Matzke, M; Dengler, R; Johannes, S

    1997-09-01

    Neuropsychological deficits are a main feature of Huntington disease (HD) with previous data suggesting involvement of memory functions and visual processing. To increase the knowledge about cognitive malfunction in HD in the domains of visual processing and memory by the use of modern electrophysiological techniques (event-related potentials [ERPs]). A case-control design was used. Three ERP paradigms were used; a parallel visual search paradigm allowed for the simultaneous processing of a multi-element visual array in search of a target stimulus, while a serial search paradigm with varied numbers of distractor items necessitated a serial one by one scanning of the arrays. The third experiment was a word-recognition memory task. The measurements were obtained in a neurophysiological laboratory of a university hospital. Nine patients with HD and 9 control subjects matched for age, sex, and education were studied. Components of averaged ERPs were quantified by latency and amplitude measures and subjected to statistical analysis. Behavioral measures (search time, hit rate, and recognition accuracy) were assessed as well. The early visual components showed a significant latency shift (delay of about 50 milliseconds) in HD. In the search paradigms the P3 components differentiating target and standard stimuli were virtually absent in HD as was the ERP effect indexing word recognition. This was accompanied by a marked delay in search times and lower hit rates in the search tasks and a grossly reduced recognition accuracy in the memory task. The results suggest marked impairments of patients with HD in early visual sensory processing (early components). Deficits in visual search might be attributed to an impairment to deploy attentional resources across the visual field and/or an inability to control eye movements. The ERPs in the memory task differed grossly from similar data obtained by others in patients with Alzheimer disease, suggesting a different neural basis for

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

    Science.gov (United States)

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

    2010-12-01

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

  18. Motivation and Justice at Work: The Role of Emotion and Cognition Components of Personal and Collective Work Identity.

    Science.gov (United States)

    Nordhall, Ola; Knez, Igor

    2017-01-01

    The aim of this study was to investigate the role of personal and collective work identity (including emotion and cognition components), in predicting work motivation (operationalized as work self-determined motivation) and organizational justice (operationalized as organizational pay justice). Digitized questionnaires were distributed by e-mail to 2905 members, teachers, of a Swedish trade union. A total of 768 individuals answered the questionnaire and by that participated in this study. Personal- compared to collective work identity was shown to positively associate with self-determined motivation accounted for by the emotion component of personal work identity. Collective compared to personal work identity was reported to positively associate with organizational pay justice accounted for by the cognition component of collective work identity. All this suggests that both work-related motivation and organizational justice might be, to some extent, accounted for by the psychological mechanisms of work identity and that, as predicted, different types of work identity, play different significant roles in predicting motivation and justice at work. More precisely, the emotion component of work identity was more pronounced in personal work-bonding relationships, and the cognitive component, of work identity in contrast, was more pronounced in collective work-bonding relationships.

  19. Motivation and Justice at Work: The Role of Emotion and Cognition Components of Personal and Collective Work Identity

    Directory of Open Access Journals (Sweden)

    Ola Nordhall

    2018-01-01

    Full Text Available The aim of this study was to investigate the role of personal and collective work identity (including emotion and cognition components, in predicting work motivation (operationalized as work self-determined motivation and organizational justice (operationalized as organizational pay justice. Digitized questionnaires were distributed by e-mail to 2905 members, teachers, of a Swedish trade union. A total of 768 individuals answered the questionnaire and by that participated in this study. Personal- compared to collective work identity was shown to positively associate with self-determined motivation accounted for by the emotion component of personal work identity. Collective compared to personal work identity was reported to positively associate with organizational pay justice accounted for by the cognition component of collective work identity. All this suggests that both work-related motivation and organizational justice might be, to some extent, accounted for by the psychological mechanisms of work identity and that, as predicted, different types of work identity, play different significant roles in predicting motivation and justice at work. More precisely, the emotion component of work identity was more pronounced in personal work-bonding relationships, and the cognitive component, of work identity in contrast, was more pronounced in collective work-bonding relationships.

  20. Motivation and Justice at Work: The Role of Emotion and Cognition Components of Personal and Collective Work Identity

    Science.gov (United States)

    Nordhall, Ola; Knez, Igor

    2018-01-01

    The aim of this study was to investigate the role of personal and collective work identity (including emotion and cognition components), in predicting work motivation (operationalized as work self-determined motivation) and organizational justice (operationalized as organizational pay justice). Digitized questionnaires were distributed by e-mail to 2905 members, teachers, of a Swedish trade union. A total of 768 individuals answered the questionnaire and by that participated in this study. Personal- compared to collective work identity was shown to positively associate with self-determined motivation accounted for by the emotion component of personal work identity. Collective compared to personal work identity was reported to positively associate with organizational pay justice accounted for by the cognition component of collective work identity. All this suggests that both work-related motivation and organizational justice might be, to some extent, accounted for by the psychological mechanisms of work identity and that, as predicted, different types of work identity, play different significant roles in predicting motivation and justice at work. More precisely, the emotion component of work identity was more pronounced in personal work-bonding relationships, and the cognitive component, of work identity in contrast, was more pronounced in collective work-bonding relationships. PMID:29379454

  1. Cognitive Task Analysis of the Battalion Level Visualization Process

    National Research Council Canada - National Science Library

    Leedom, Dennis K; McElroy, William; Shadrick, Scott B; Lickteig, Carl; Pokorny, Robet A; Haynes, Jacqueline A; Bell, James

    2007-01-01

    ... position or as a battalion Operations Officer or Executive Officer. Bases on findings from the cognitive task analysis, 11 skill areas were identified as potential focal points for future training development...

  2. Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

    Science.gov (United States)

    Lewandowski, Kathryn E; Baker, Justin T; McCarthy, Julie M; Norris, Lesley A; Öngür, Dost

    2018-04-01

    Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2018, 24, 382-390).

  3. The 'cognitive' and the 'emotive' component in Christian songs: Tracing the shifts in traditional and contemporary songs

    Directory of Open Access Journals (Sweden)

    J. Gertrud T�nsing

    2015-03-01

    Full Text Available This research article is based on the author�s doctoral research into the question of quality criteria for Christian songs. In many Christian congregations today, the question of music is an emotive issue as the service and its music touch the heart of people�s faith life and shapes people�s theology. Of the many issues that were investigated in the dissertation, this article focuses on one question only, the question of the �cognitive� and the �emotive� value of the songs that are sung in a Sunday service. It will be argued that, in �good� songs, there needs to be a good balance between �cognitive� and �emotive� value. The general question is how to identify songs that can nurture faith and sustain people through life. Characteristic of such songs is, amongst many other criteria, a good balance between the cognitive and emotive value of the text and the tune. In the discussion, the author focusses largely on her own Lutheran liturgical and hymnological tradition as well as on the �Praise and Worship� movement which has a dramatic impact on churches all over the world. The author argues that finding songs that balance the emotive and the cognitive component is an effective way to bridge the divides on worship music within a congregation.Intradisciplinary and/or interdisciplinary implications: Within the discipline of hymnological studies, the article opens a ground-breaking new way to analyse and critique music used in worship with objective tools for analysis. This is, as far as the author knows, new for this discipline, and it also has an effect on other disciplines.

  4. Cognitive Task Analysis Based Training for Cyber Situation Awareness

    OpenAIRE

    Huang , Zequn; Shen , Chien-Chung; Doshi , Sheetal; Thomas , Nimmi; Duong , Ha

    2015-01-01

    Part 1: Innovative Methods; International audience; Cyber attacks have been increasing significantly in both number and complexity, prompting the need for better training of cyber defense analysts. To conduct effective training for cyber situation awareness, it becomes essential to design realistic training scenarios. In this paper, we present a Cognitive Task Analysis based approach to address this training need. The technique of Cognitive Task Analysis is to capture and represent knowledge ...

  5. 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

  6. 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)

  7. 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.

  8. 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...

  9. 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 ...

  10. Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

    Science.gov (United States)

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

    2016-01-01

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

  11. Mental model construction, not just memory, is a central component of cognitive change in psychotherapy.

    Science.gov (United States)

    von Hecker, Ulrich; McIntosh, Daniel N; Sedek, Grzegorz

    2015-01-01

    We challenge the idea that a cognitive perspective on therapeutic change concerns only memory processes. We argue that inclusion of impairments in more generative cognitive processes is necessary for complete understanding of cases such as depression. In such cases what is identified in the target article as an "integrative memory structure" is crucially supported by processes of mental model construction.

  12. 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.

  13. 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)

  14. 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

  15. All the way up?, All the way down?: From cognitive science to cognitive Curriculum; what about the affective component?

    Directory of Open Access Journals (Sweden)

    Montes de Oca Rodríguez, Raúl

    2004-06-01

    Full Text Available Este artículo está dirigido a profesores de inglés y estudiantes de enseñanza del inglés como lengua extranjera o como segundo idioma (EFL (ESL principalmente, pero lectores de otras disciplinas son bienvenidos. El propósito del artículo es presentar una panorámica general de la ciencia cognoscitiva en relación con la enseñanza y aprendizaje de un idioma. Áreas como la psicología cognitiva, la enseñanza y el aprendizaje cognitivos, y la adquisición de un segundo idioma se incluyen como parte de lo que se quiere dar a conocer. Los objetivos son el delinear someramente algunos puntos visibles e importantes de la ciencia cognitiva y relacionarlos con las características de las tendencias en cuanto a enseñanza y aprendizaje de un idioma hoy en día. El autor propone tomar en cuenta dos áreas de ESL/EFL simultáneamente: la cognitiva y la afectiva, ya que esta última pareciera haberse dejado de lado últimamente, dándosele más énfasis a elementos cognitivos como las estrategias de aprendizaje. En la conclusión, el autor insiste en dar el mismo status al desarrollo eventual de ambos programas: a los del desarrollo de la autoestima y los de estrategias de aprendizaje que eventualmente se puedan estar diseñando tanto en escuelas como en colegios. This article is directed to English language teachers and / or students of teaching English as a Foreign/Second Language (EFL (ESL mainly, but readers from other disciplines are welcome aboard. Its purpose is to present an overview of cognitive science in relation to language teaching and learning. Areas like cognitive psychology, cognitive teaching and learning, and second language acquisition are explored as part of the panorama that is portrayed. The objectives are to briefly delineate some visible historic points and remarkable features of cognitive science, and to relate these characteristics to today`s language teaching and learning trends. The author´s proposal involves taking

  16. 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

  17. 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

  18. Multi-component separation and analysis of bat echolocation calls.

    Science.gov (United States)

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

    2013-01-01

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

  19. The Fear of Positive Evaluation Scale: assessing a proposed cognitive component of social anxiety.

    Science.gov (United States)

    Weeks, Justin W; Heimberg, Richard G; Rodebaugh, Thomas L

    2008-01-01

    Cognitive-behavioral models propose that fear of negative evaluation is the core feature of social anxiety disorder. However, it may be that fear of evaluation in general is important in social anxiety, including fears of positive as well as negative evaluation. To test this hypothesis, we developed the Fear of Positive Evaluation Scale (FPES) and conducted analyses to examine the psychometric properties of the FPES, as well as test hypotheses regarding the construct of fear of positive evaluation (FPE). Responses from a large (n = 1711) undergraduate sample were utilized. The reliability, construct validity, and factorial validity of the FPES were examined; the distinction of FPE from fear of negative evaluation was evaluated utilizing confirmatory factor analysis; and the ability of FPE to predict social interaction anxiety above and beyond fear of negative evaluation was assessed. Results provide preliminary support for the psychometric properties of the FPES and the validity of the construct of FPE. The implications of FPE with respect to the study and treatment of social anxiety disorder are discussed.

  20. Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability Analysis

    NARCIS (Netherlands)

    Murungweni, C.; Wijk, van M.T.; Andersson, J.A.; Smaling, E.M.A.; Giller, K.E.

    2011-01-01

    Feedback mechanisms are important in the analysis of vulnerability and resilience of social-ecological systems, as well as in the analysis of livelihoods, but how to evaluate systems with direct feedbacks has been a great challenge. We applied fuzzy cognitive mapping, a tool that allows analysis of

  1. Cognitive distortions as a component and treatment focus of pathological gambling: a review.

    Science.gov (United States)

    Fortune, Erica E; Goodie, Adam S

    2012-06-01

    The literature on the role of cognitive distortions in the understanding and treatment of pathological gambling (PG) is reviewed, with sections focusing on (a) conceptual underpinnings of cognitive distortions, (b) cognitive distortions related to PG, (c) PG therapies that target cognitive distortions, (d) methodological factors and outcome variations, and (e) conclusions and prescriptive recommendations. The conceptual background for distortions related to PG lies in the program of heuristics and biases (Kahneman & Tversky, 1974) as well as other errors identified in basic psychology. The literature has focused on distortions arising from the representativeness heuristic (gambler's fallacy, overconfidence, and trends in number picking), the availability heuristic (illusory correlation, other individuals' wins, and inherent memory bias), and other sources (the illusion of control and double switching). Some therapies have incorporated cognitive restructuring within broader cognitive-behavioral therapies, with success. Other therapies have focused more narrowly on correcting distorted beliefs, more often with limited success. It is concluded that the literature establishes the role of cognitive distortions in PG and suggests therapies with particularly good promise, but is in need of further enrichment.

  2. Cognitive modelling: a basic complement of human reliability analysis

    International Nuclear Information System (INIS)

    Bersini, U.; Cacciabue, P.C.; Mancini, G.

    1988-01-01

    In this paper the issues identified in modelling humans and machines are discussed in the perspective of the consideration of human errors managing complex plants during incidental as well as normal conditions. The dichotomy between the use of a cognitive versus a behaviouristic model approach is discussed and the complementarity aspects rather than the differences of the two methods are identified. A cognitive model based on a hierarchical goal-oriented approach and driven by fuzzy logic methodology is presented as the counterpart to the 'classical' THERP methodology for studying human errors. Such a cognitive model is discussed at length and its fundamental components, i.e. the High Level Decision Making and the Low Level Decision Making models, are reviewed. Finally, the inadequacy of the 'classical' THERP methodology to deal with cognitive errors is discussed on the basis of a simple test case. For the same case the cognitive model is then applied showing the flexibility and adequacy of the model to dynamic configuration with time-dependent failures of components and with consequent need for changing of strategy during the transient itself. (author)

  3. 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...

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

    Science.gov (United States)

    Brown, Judith C.; Smaragdis, Paris

    2004-05-01

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

  5. 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

  6. Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

    Science.gov (United States)

    Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

    2016-09-01

    In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

  7. Automatic ECG analysis using principal component analysis and wavelet transformation

    OpenAIRE

    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.

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

    Science.gov (United States)

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

    2018-02-01

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

  9. Motivation and Justice at Work: The Role of Emotion and Cognition Components of Personal and Collective Work Identity

    OpenAIRE

    Ola Nordhall; Ola Nordhall; Igor Knez

    2018-01-01

    The aim of this study was to investigate the role of personal and collective work identity (including emotion and cognition components), in predicting work motivation (operationalized as work self-determined motivation) and organizational justice (operationalized as organizational pay justice). Digitized questionnaires were distributed by e-mail to 2905 members, teachers, of a Swedish trade union. A total of 768 individuals answered the questionnaire and by that participated in this study. Pe...

  10. 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...

  11. 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...

  12. 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.)

  13. Are cognitive functions in post-menopausal women related with the contents of macro- and micro-components in the diet?

    Directory of Open Access Journals (Sweden)

    Iwona Bojar

    2015-02-01

    Full Text Available [b]The objective[/b] of the study was an evaluation of the relationship between the level of cognitive functions and contents of micro- and macro-components in the diet of postmenopausal women. A group of 402 women was recruited to the study. The inclusion criteria were: minimum two years after the last menstruation, FSH concentration 30 U/ml and no dementia signs on the Montreal Cognitive Assessment (MoCA. A computerized battery of the Central Nervous System Vital Signs (CNS VS test was used to diagnose cognitive functions. The dietary questionnaire was evaluated based on observation of a seven-day diet. The data obtained were introduced into the database and analyzed using computer software DIETICIAN. Statistical analysis was performed using statistical software STATISTICA. [b]Results[/b]. The results of the study concerning diet unequivocally indicate a very poor quality of diet in the group of postmenopausal women examined. The daily diet had a too high energetic value. The women consumed an excessive amount of total fat, including definitely too much monounsaturated fatty acids, and insufficient polyunsaturated fatty acids. The dietary intake of sodium and phosphorus was too high, whereas deficiencies were observed in the consumption of iron, copper, potassium, calcium, magnesium and zinc. No significant correlations were found in the analysis of cognitive functions according to the energetic value of daily diet and contents of macro- and micro-components. The results concerning verbal memory significantly depended on the daily intake of polyunsaturated fatty acids. Women who consumed polyunsaturated fatty acids below the daily normal or normal level obtained significantly higher results in verbal memory.

  14. Are cognitive functions in post-menopausal women related with the contents of macro- and micro-components in the diet?

    Science.gov (United States)

    Bojar, Iwona; Wierzbińska-Stępniak, Anna; Witczak, Mariusz; Raczkiewicz, Dorota; Owoc, Alfred

    2015-01-01

    The objective of the study was an evaluation of the relationship between the level of cognitive functions and contents of micro- and macro-components in the diet of postmenopausal women. A group of 402 women was recruited to the study. The inclusion criteria were: minimum two years after the last menstruation, FSH concentration 30 U/ml and no dementia signs on the Montreal Cognitive Assessment (MoCA). A computerized battery of the Central Nervous System Vital Signs (CNS VS) test was used to diagnose cognitive functions. The dietary questionnaire was evaluated based on observation of a seven-day diet. The data obtained were introduced into the database and analyzed using computer software DIETICIAN. Statistical analysis was performed using statistical software STATISTICA. The results of the study concerning diet unequivocally indicate a very poor quality of diet in the group of postmenopausal women examined. The daily diet had a too high energetic value. The women consumed an excessive amount of total fat, including definitely too much monounsaturated fatty acids, and insufficient polyunsaturated fatty acids. The dietary intake of sodium and phosphorus was too high, whereas deficiencies were observed in the consumption of iron, copper, potassium, calcium, magnesium and zinc. No significant correlations were found in the analysis of cognitive functions according to the energetic value of daily diet and contents of macro- and micro-components. The results concerning verbal memory significantly depended on the daily intake of polyunsaturated fatty acids. Women who consumed polyunsaturated fatty acids below the daily normal or normal level obtained significantly higher results in verbal memory.

  15. The analysis of multivariate group differences using common principal components

    NARCIS (Netherlands)

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

    2014-01-01

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

  16. 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.

  17. 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...

  18. 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....

  19. Principal component analysis of image gradient orientations for face recognition

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

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

  20. 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....

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

    Science.gov (United States)

    Zhang, Sheng; Li, Chiang-Shan R

    2017-11-01

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

  2. 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

  3. Meta-analysis of social cognition in amyotrophic lateral sclerosis.

    Science.gov (United States)

    Bora, Emre

    2017-03-01

    Amyotrophic lateral sclerosis (ALS) is associated with executive dysfunction and behavioural impairment. Recent studies suggested that social cognitive deficits might also be a prominent feature of ALS. Current meta-analysis aimed to summarize available evidence for deficits in social cognition including theory of mind (ToM) and emotion recognition in ALS. In this meta-analysis of 15 studies, facial emotion recognition and ToM performances of 389 patients with ALS and 471 healthy controls were compared. ALS was associated with significant impairments with medium effect sizes in ToM (d = .65) and facial emotion recognition (d = .69). Among individual emotions recognition of disgust and surprise were particularly impaired. Deficits in perspective taking (d = .73) aspects of ToM (ToM-PT) was more pronounced in comparison to decoding (d = .28) aspects of ToM (ToM-decoding). The severity of social cognitive impairment was similar to level of executive dysfunction and there was a significant relationship between social cognition and executive dysfunction. Deficits in social cognition are part of the cognitive phenotype of ALS. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. EEG Based Analysis of Cognitive Load Enhance Instructional Analysis

    Science.gov (United States)

    Dan, Alex; Reiner, Miriam

    2017-01-01

    One of the recommended approaches in instructional design methods is to optimize the value of working memory capacity and avoid cognitive overload. Educational neuroscience offers novel processes and methodologies to analyze cognitive load based on physiological measures. Observing psychophysiological changes when they occur in response to the…

  5. Cognitive costs of decision-making strategies: A resource demand decomposition analysis with a cognitive architecture.

    Science.gov (United States)

    Fechner, Hanna B; Schooler, Lael J; Pachur, Thorsten

    2018-01-01

    Several theories of cognition distinguish between strategies that differ in the mental effort that their use requires. But how can the effort-or cognitive costs-associated with a strategy be conceptualized and measured? We propose an approach that decomposes the effort a strategy requires into the time costs associated with the demands for using specific cognitive resources. We refer to this approach as resource demand decomposition analysis (RDDA) and instantiate it in the cognitive architecture Adaptive Control of Thought-Rational (ACT-R). ACT-R provides the means to develop computer simulations of the strategies. These simulations take into account how strategies interact with quantitative implementations of cognitive resources and incorporate the possibility of parallel processing. Using this approach, we quantified, decomposed, and compared the time costs of two prominent strategies for decision making, take-the-best and tallying. Because take-the-best often ignores information and foregoes information integration, it has been considered simpler than strategies like tallying. However, in both ACT-R simulations and an empirical study we found that under increasing cognitive demands the response times (i.e., time costs) of take-the-best sometimes exceeded those of tallying. The RDDA suggested that this pattern is driven by greater requirements for working memory updates, memory retrievals, and the coordination of mental actions when using take-the-best compared to tallying. The results illustrate that assessing the relative simplicity of strategies requires consideration of the overall cognitive system in which the strategies are embedded. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. A cognitive task analysis of the SGTR scenario

    International Nuclear Information System (INIS)

    Hollnagel, E.; Edland, A.; Svenson, O.

    1996-04-01

    This report constitutes a contribution to the NKS/RAK-1:3 project on Integrated Sequence Analysis. Following the meeting at Ringhals, the work was proposed to be performed by the following three steps: Task 1. Cognitive Task Analysis of the E-3 procedure. Task 2. Evaluation and revision of task analysis with Ringhals/KSU experts. Task 3. Integration with simulator data. The Cognitive Task Analysis (CTA) of Task 1 uses the Goals-Means Task Analysis (GMTA) method to identify the sequence of tasks and task steps necessary to achieve the goals of the procedure. It is based on material supplied by Ringhals, which describes the E-3 procedure, including the relevant ES and ECA procedures. The analysis further outlines the cognitive demands profile associated with individual task steps as well as with the task as a whole, as an indication of the nominal task load. The outcome of the cognitive task analysis provides a basis for proposing an adequate event tree. This report describes the results from Task 1. The work has included a two-day meeting between the three contributors, as well as the exchange of intermediate results and comments throughout the period. After the initial draft of the report was prepared, an opportunity was given to observe the SGTR scenario in a full-scope training simulator, and to discuss the details with the instructors. This led to several improvements from the initial draft. (EG)

  7. 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.

  8. Experimental modal analysis of components of the LHC experiments

    CERN Document Server

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

    2007-01-01

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

  9. 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

  10. Sparse logistic principal components analysis for binary data

    KAUST Repository

    Lee, Seokho

    2010-09-01

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

  11. 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.

  12. Social cognition and the brain: a meta-analysis.

    Science.gov (United States)

    Van Overwalle, Frank

    2009-03-01

    This meta-analysis explores the location and function of brain areas involved in social cognition, or the capacity to understand people's behavioral intentions, social beliefs, and personality traits. On the basis of over 200 fMRI studies, it tests alternative theoretical proposals that attempt to explain how several brain areas process information relevant for social cognition. The results suggest that inferring temporary states such as goals, intentions, and desires of other people-even when they are false and unjust from our own perspective--strongly engages the temporo-parietal junction (TPJ). Inferring more enduring dispositions of others and the self, or interpersonal norms and scripts, engages the medial prefrontal cortex (mPFC), although temporal states can also activate the mPFC. Other candidate tasks reflecting general-purpose brain processes that may potentially subserve social cognition are briefly reviewed, such as sequence learning, causality detection, emotion processing, and executive functioning (action monitoring, attention, dual task monitoring, episodic memory retrieval), but none of them overlaps uniquely with the regions activated during social cognition. Hence, it appears that social cognition particularly engages the TPJ and mPFC regions. The available evidence is consistent with the role of a TPJ-related mirror system for inferring temporary goals and intentions at a relatively perceptual level of representation, and the mPFC as a module that integrates social information across time and allows reflection and representation of traits and norms, and presumably also of intentionality, at a more abstract cognitive level.

  13. Optimization benefits analysis in production process of fabrication components

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2018-02-26

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

  15. Determining team cognition from delay analysis using cross recurrence plot.

    Science.gov (United States)

    Hajari, Nasim; Cheng, Irene; Bin Zheng; Basu, Anup

    2016-08-01

    Team cognition is an important factor in evaluating and determining team performance. Forming a team with good shared cognition is even more crucial for laparoscopic surgery applications. In this study, we analyzed the eye tracking data of two surgeons during a laparoscopic simulation operation, then performed Cross Recurrence Analysis (CRA) on the recorded data to study the delay behaviour for good performer and poor performer teams. Dual eye tracking data for twenty two dyad teams were recorded during a laparoscopic task and then the teams were divided into good performer and poor performer teams based on the task times. Eventually we studied the delay between two team members for good and poor performer teams. The results indicated that the good performer teams show a smaller delay comparing to poor performer teams. This study is compatible with gaze overlap analysis between team members and therefore it is a good evidence of shared cognition between team members.

  16. Probabilistic structural analysis methods for select space propulsion system components

    Science.gov (United States)

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

    1989-01-01

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

  17. 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.

  18. Robust LOD scores for variance component-based linkage analysis.

    Science.gov (United States)

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

    2000-01-01

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

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

    Science.gov (United States)

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

    2012-07-01

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

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

    NARCIS (Netherlands)

    Saccenti, E.; Camacho, J.

    2015-01-01

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

  1. Research on Air Quality Evaluation based on Principal Component Analysis

    Science.gov (United States)

    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.

  2. Measurement of mental attention: Assessing a cognitive component underlying performance on standardized intelligence tests

    OpenAIRE

    Steven J. Howard; Janice Johnson; Juan Pascual-Leone

    2013-01-01

    Despite the widespread use of standardized IQ tests to measure human intelligence, problems with such measures have led some to suggest that better indices may derive from measurement of cognitive processes underlying performance on IQ tests (e.g., working memory capacity). However, measures from both approaches may exhibit performance biases in favour of majority groups, due to the influence of prior learning and experience. Mental attentional (M-) capacity is proposed to be a causal factor ...

  3. 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

  4. Partial Derivative Games in Thermodynamics: A Cognitive Task Analysis

    Science.gov (United States)

    Kustusch, Mary Bridget; Roundy, David; Dray, Tevian; Manogue, Corinne A.

    2014-01-01

    Several studies in recent years have demonstrated that upper-division students struggle with the mathematics of thermodynamics. This paper presents a task analysis based on several expert attempts to solve a challenging mathematics problem in thermodynamics. The purpose of this paper is twofold. First, we highlight the importance of cognitive task…

  5. 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.)

  6. The Mediator Roles of Life Satisfaction and Self-Esteem between the Affective Components of Psychological Well-Being and the Cognitive Symptoms of Problematic Internet Use

    Science.gov (United States)

    Senol-Durak, Emre; Durak, Mithat

    2011-01-01

    The factors associated with cognitions about problematic Internet use have been empirically tested in various studies. The aim of the present study was to examine the mediator roles of both life satisfaction and self-esteem between affective components of subjective well-being and cognitions about problematic Internet use. For this purpose, the…

  7. A component analysis of positive behaviour support plans.

    Science.gov (United States)

    McClean, Brian; Grey, Ian

    2012-09-01

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

  8. Representation for dialect recognition using topographic independent component analysis

    Science.gov (United States)

    Wei, Qu

    2004-10-01

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

  9. 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

  10. 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)

  11. Integrative sparse principal component analysis of gene expression data.

    Science.gov (United States)

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

    2017-12-01

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

  12. Analysis of dynamic characteristics of stochastic influences in cognitive systems

    Directory of Open Access Journals (Sweden)

    Alexander A. Solodov

    2017-01-01

    Full Text Available The aim of the study is to provide an analytical description of the dynamics of the processes to form images in the cognitive system and their subsequent processing by the consciousness, as well as the study of the simplest characteristics of the quality of the cognitive system functioning in the form of the signal/noise ratio.In accordance with the ideas of the cognitive theory, it is believed that images (schemes, categories, Gestalt, systems, archetypes, etc. are firstly generated in the human brain and then processed by the consciousness.These images are formed at random in time and are characterized by a random force of effects and subsequently processed by the consciousness.The images are characterized by random numbers, the common interpretation of which is the amount of information corresponding to the appearance of a certain image. The times of appearance are points on the time axis; their number and position are random as well.The work consists of a logically completed model including the following components:• Justification of a statistical model of the appearance of effects during the operation of the cognitive system in the form of the Poisson point process, characterized by the intensity of occurrence of effects and the random values of those effects.• Development of a mathematical model in the consciousness processing of the random effects in the form of reducing response function, which depends on the current time, the time of occurrence of effects and the magnitudes of these effects. To obtain applied results, exponential response function was applied and the analytical results for the mathematical expectations of the processed and not processed information by the consciousness were received.• Introduction for consideration of the signal/noise ratio, characterizing the performance of cognitive systems in the presence of interference and study of its behavior in the situations with the presence of random background noise

  13. 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.

  14. A Cognitive Task Analysis for Dental Hygiene.

    Science.gov (United States)

    Cameron, Cheryl A.; Beemsterboer, Phyllis L.; Johnson, Lynn A.; Mislevy, Robert J.; Steinberg, Linda S.; Breyer, F. Jay

    2000-01-01

    As part of the development of a scoring algorithm for a simulation-based dental hygiene initial licensure examination, this effort conducted a task analysis of the dental hygiene domain. Broad classes of behaviors that distinguish along the dental hygiene expert-novice continuum were identified and applied to the design of nine paper-based cases…

  15. Cognitive Work Analysis: Foundations, Extensions, and Challenges

    Science.gov (United States)

    2011-11-01

    preserves the information and relationships in the abstraction-decomposition space. This will serve as an externalised mental representation of work domain...C., & Sanderson, P. M. (2002b). Work domain analysis and sensors II: Pasteurizer II case study. International Journal of Human-Computer Studies, 56(6

  16. 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

  17. 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.

  18. Fast principal component analysis for stacking seismic data

    Science.gov (United States)

    Wu, Juan; Bai, Min

    2018-04-01

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

  19. Demixed principal component analysis of neural population data.

    Science.gov (United States)

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

    2016-04-12

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

  20. Effects of early language, speech, and cognition on later reading: A mediation analysis

    Directory of Open Access Journals (Sweden)

    Vanessa N Durand

    2013-09-01

    Full Text Available This longitudinal secondary analysis examined which early language and speech abilities are associated with school-aged reading skills, and whether these associations are mediated by cognitive ability. We analyzed vocabulary, syntax, speech sound maturity, and cognition in a sample of healthy children at age 3 years (N=241 in relation to single word reading (decoding, comprehension, and oral reading fluency in the same children at age 9 to 11 years. All predictor variables and the mediator variable were associated with the three reading outcomes. The predictor variables were all associated with cognitive abilities, the mediator. Cognitive abilities partially mediated the effects of language on reading. After mediation, decoding was associated with speech sound maturity; comprehension was associated with receptive vocabulary; and oral fluency was associated with speech sound maturity, receptive vocabulary, and syntax. In summary, all of the effects of language on reading could not be explained by cognition as a mediator. Specific components of language and speech skills in preschool made independent contributions to reading skills 6 to 8 years later. These early precursors to later reading skill represent potential targets for early intervention to improve reading.

  1. 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.

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

    Science.gov (United States)

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

    2018-03-01

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

  3. Robustness analysis of bogie suspension components Pareto optimised values

    Science.gov (United States)

    Mousavi Bideleh, Seyed Milad

    2017-08-01

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

  4. Sparse principal component analysis in medical shape modeling

    Science.gov (United States)

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

    2006-03-01

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

  5. 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

  6. Caffeine synergizes with another coffee component to increase plasma GCSF: linkage to cognitive benefits in Alzheimer's mice.

    Science.gov (United States)

    Cao, Chuanhai; Wang, Li; Lin, Xiaoyang; Mamcarz, Malgorzata; Zhang, Chi; Bai, Ge; Nong, Jasson; Sussman, Sam; Arendash, Gary

    2011-01-01

    Retrospective and prospective epidemiologic studies suggest that enhanced coffee/caffeine intake during aging reduces risk of Alzheimer's disease (AD). Underscoring this premise, our studies in AD transgenic mice show that long-term caffeine administration protects against cognitive impairment and reduces brain amyloid-β levels/deposition through suppression of both β- and γ-secretase. Because coffee contains many constituents in addition to caffeine that may provide cognitive benefits against AD, we examined effects of caffeinated and decaffeinated coffee on plasma cytokines, comparing their effects to caffeine alone. In both AβPPsw+PS1 transgenic mice and non-transgenic littermates, acute i.p. treatment with caffeinated coffee greatly and specifically increased plasma levels of granulocyte-colony stimulating factor (GCSF), IL-10, and IL-6. Neither caffeine solution alone (which provided high plasma caffeine levels) or decaffeinated coffee provided this effect, indicating that caffeine synergized with some as yet unidentified component of coffee to selectively elevate these three plasma cytokines. The increase in GCSF is particularly important because long-term treatment with coffee (but not decaffeinated coffee) enhanced working memory in a fashion that was associated only with increased plasma GCSF levels among all cytokines. Since we have previously reported that long-term GCSF treatment enhances cognitive performance in AD mice through three possible mechanisms (e.g., recruitment of microglia from bone marrow, synaptogenesis, and neurogenesis), the same mechanisms could be complimentary to caffeine's established ability to suppress Aβ production. We conclude that coffee may be the best source of caffeine to protect against AD because of a component in coffee that synergizes with caffeine to enhance plasma GCSF levels, resulting in multiple therapeutic actions against AD.

  7. 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.

  8. Principal Component Analysis Based Measure of Structural Holes

    Science.gov (United States)

    Deng, Shiguo; Zhang, Wenqing; Yang, Huijie

    2013-02-01

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

  9. 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

  10. 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.

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

    Science.gov (United States)

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

    2017-11-01

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

  12. 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.

  13. Nonlinear Principal Component Analysis Using Strong Tracking Filter

    Institute of Scientific and Technical Information of China (English)

    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.

  14. 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...

  15. Advances in independent component analysis and learning machines

    CERN Document Server

    Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

    2015-01-01

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

  16. A framework for cognitive task analysis in systems design

    International Nuclear Information System (INIS)

    Rasmussen, J.

    1985-08-01

    The present rapid development if advanced information technology and its use for support of operators of complex technical systems are changing the content of task analysis towards the analysis of mental activities in decision making. Automation removes the humans from routine tasks, and operators are left with disturbance control and critical diagnostic tasks, for which computers are suitable for support, if it is possible to match the computer strategies and interface formats dynamically to the requirements of the current task by means of an analysis of the cognitive task. Such a cognitive task analysis will not aim at a description of the information processes suited for particular control situations. It will rather aim at an analysis in order to identify the requirements to be considered along various dimensions of the decision tasks, in order to give the user - i.e. a decision maker - the freedom to adapt his performance to system requirements in a way which matches his process resources and subjective preferences. To serve this purpose, a number of analyses at various levels are needed to relate the control requirements of the system to the information processes and to the processing resources offered by computers and humans. The paper discusses the cognitive task analysis in terms of the following domains: The problem domain, which is a representation of the functional properties of the system giving a consistent framework for identification of the control requirements of the system; the decision sequences required for typical situations; the mental strategies and heuristics which are effective and acceptable for the different decision functions; and the cognitive control mechanisms used, depending upon the level of skill which can/will be applied. Finally, the end-users' criteria for choice of mental strategies in the actual situation are considered, and the need for development of criteria for judging the ultimate user acceptance of computer support is

  17. 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)

  18. The fallacy of the cognitive free fall in communication metaphor - a semiotic analysis

    DEFF Research Database (Denmark)

    Thellefsen, Martin Muderspach; Thellefsen, Torkild Leo; Sørensen, Bent

    2015-01-01

    This article is a theoretical analysis of the cognitive free fall metaphor, used within the cognitive view, as model for explaining the communication process between a generator and receiver of a message. The aim is to demonstrate that the idea of a cognitive free fall taking place within...... as a complex interrelation of emotion, information and cognition....

  19. Cognitive Systems

    DEFF Research Database (Denmark)

    The tutorial will discuss the definition of cognitive systems as the possibilities to extend the current systems engineering paradigm in order to perceive, learn, reason and interact robustly in open-ended changing environments. I will also address cognitive systems in a historical perspective...... to be modeled within a limited set of predefined specifications. There will inevitably be a need for robust decisions and behaviors in novel situations that include handling of conflicts and ambiguities based on the capability and knowledge of the artificial cognitive system. Further, there is a need...... in cognitive systems include e.g. personalized information systems, sensor network systems, social dynamics system and Web2.0, and cognitive components analysis. I will use example from our own research and link to other research activities....

  20. Fast grasping of unknown objects using principal component analysis

    Science.gov (United States)

    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.

  1. Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.

    Science.gov (United States)

    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.

  2. 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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  4. A Framework for the Cognitive Task Analysis in Systems Design

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    he present rapid development of advanced information technology and its use for support of operators of complex technical systems are changing the content of task analysis towards the analysis of mental activities in decision making. Automation removes the humans from routine tasks, and operators...... are left with disturbance control and critical diagnostic tasks, for which computers are suitable for support, if it is possible to match the computer strategies and interface formats dynamically to the requirements of the current task by means of an analysis of the cognitive task....

  5. Cognitive approaches for patterns analysis and security applications

    Science.gov (United States)

    Ogiela, Marek R.; Ogiela, Lidia

    2017-08-01

    In this paper will be presented new opportunities for developing innovative solutions for semantic pattern classification and visual cryptography, which will base on cognitive and bio-inspired approaches. Such techniques can be used for evaluation of the meaning of analyzed patterns or encrypted information, and allow to involve such meaning into the classification task or encryption process. It also allows using some crypto-biometric solutions to extend personalized cryptography methodologies based on visual pattern analysis. In particular application of cognitive information systems for semantic analysis of different patterns will be presented, and also a novel application of such systems for visual secret sharing will be described. Visual shares for divided information can be created based on threshold procedure, which may be dependent on personal abilities to recognize some image details visible on divided images.

  6. Performance analysis of Cognitive Pilot Channel in wireless Heterogeneous networks

    OpenAIRE

    Hussein, Tahseen Ali

    2009-01-01

    This thesis aims to investigate and analyze the performance of the Cognitive Pilot Channel (CPC) in heterogeneous network. The thesis uses simulation to simulate the environment and the scenarios and by using this simulation, the analysis is done. First task this thesis carrying is the validation the simulation results with the numerical results. This is done by introducing a single cell scenario and validates the results out of this scenario with the numerical calculation. Ana...

  7. A Computational Analysis Model for Open-ended Cognitions

    Science.gov (United States)

    Morita, Junya; Miwa, Kazuhisa

    In this paper, we propose a novel usage for computational cognitive models. In cognitive science, computational models have played a critical role of theories for human cognitions. Many computational models have simulated results of controlled psychological experiments successfully. However, there have been only a few attempts to apply the models to complex realistic phenomena. We call such a situation ``open-ended situation''. In this study, MAC/FAC (``many are called, but few are chosen''), proposed by [Forbus 95], that models two stages of analogical reasoning was applied to our open-ended psychological experiment. In our experiment, subjects were presented a cue story, and retrieved cases that had been learned in their everyday life. Following this, they rated inferential soundness (goodness as analogy) of each retrieved case. For each retrieved case, we computed two kinds of similarity scores (content vectors/structural evaluation scores) using the algorithms of the MAC/FAC. As a result, the computed content vectors explained the overall retrieval of cases well, whereas the structural evaluation scores had a strong relation to the rated scores. These results support the MAC/FAC's theoretical assumption - different similarities are involved on the two stages of analogical reasoning. Our study is an attempt to use a computational model as an analysis device for open-ended human cognitions.

  8. 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.

  9. 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

  10. 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

  11. Cognitive and affective components of mental workload: Understanding the effects of each on human decision making behavior

    Science.gov (United States)

    Nygren, Thomas E.

    1992-01-01

    Human factors and ergonomics researchers have recognized for some time the increasing importance of understanding the role of the construct of mental workload in flight research. Current models of mental workload suggest that it is a multidimensional and complex construct, but one that has proved difficult to measure. Because of this difficulty, emphasis has usually been placed on using direct reports through subjective measures such as rating scales to assess levels of mental workload. The NASA Task Load Index (NASA/TLX, Hart and Staveland) has been shown to be a highly reliable and sensitive measure of perceived mental workload. But a problem with measures like TLX is that there is still considerable disagreement as to what it is about mental workload that these subjective measures are actually measuring. The empirical use of subjective workload measures has largely been to provide estimates of the cognitive components of the actual mental workload required for a task. However, my research suggests that these measures may, in fact have greater potential in accurately assessing the affective components of workload. That is, for example, TLX may be more likely to assess the positive and negative feelings associated with varying workload levels, which in turn may potentially influence the decision making behavior that directly bears on performance and safety issues. Pilots, for example, are often called upon to complete many complex tasks that are high in mental workload, stress, and frustration, and that have significant dynamic decision making components -- often ones that involve risk as well.

  12. Quality Aware Compression of Electrocardiogram Using Principal Component Analysis.

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Yixuan Ku

    2007-08-01

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

  14. Relationships between self-reported sleep quality components and cognitive functioning in breast cancer survivors up to 10 years following chemotherapy.

    Science.gov (United States)

    Henneghan, Ashley M; Carter, Patricia; Stuifbergan, Alexa; Parmelee, Brennan; Kesler, Shelli

    2018-04-23

    Links have been made between aspects of sleep quality and cognitive function in breast cancer survivors (BCS), but findings are heterogeneous. The objective of this study is to examine relationships between specific sleep quality components (latency, duration, efficiency, daytime sleepiness, sleep disturbance, use of sleep aids) and cognitive impairment (performance and perceived), and determine which sleep quality components are the most significant contributors to cognitive impairments in BCS 6 months to 10 years post chemotherapy. Women 21 to 65 years old with a history of non-metastatic breast cancer following chemotherapy completion were recruited. Data collection included surveys to evaluate sleep quality and perceived cognitive impairments, and neuropsychological testing to evaluate verbal fluency and memory. Descriptive statistics, bivariate correlations, and hierarchical multiple regression were calculated. 90 women (mean age 49) completed data collection. Moderate significant correlations were found between daytime dysfunction, sleep efficiency, sleep latency, and sleep disturbance and perceived cognitive impairment (Rs = -0.37 to -0.49, Ps<.00049), but not objective cognitive performance of verbal fluency, memory or attention. After accounting for individual and clinical characteristics, the strongest predictors of perceived cognitive impairments were daytime dysfunction, sleep efficiency, and sleep disturbance. Findings support links between sleep quality and perceived cognitive impairments in BCS and suggest specific components of sleep quality (daytime dysfunction, sleep efficiency, and sleep disturbance) are associated with perceived cognitive functioning in this population. Findings can assist clinicians in guiding survivors to manage sleep and cognitive problems and aid in the design of interventional research. This article is protected by copyright. All rights reserved.

  15. Sensory processes modulate differences in multi-component behavior and cognitive control between childhood and adulthood.

    Science.gov (United States)

    Gohil, Krutika; Bluschke, Annet; Roessner, Veit; Stock, Ann-Kathrin; Beste, Christian

    2017-10-01

    Many everyday tasks require executive functions to achieve a certain goal. Quite often, this requires the integration of information derived from different sensory modalities. Children are less likely to integrate information from different modalities and, at the same time, also do not command fully developed executive functions, as compared to adults. Yet still, the role of developmental age-related effects on multisensory integration processes has not been examined within the context of multicomponent behavior until now (i.e., the concatenation of different executive subprocesses). This is problematic because differences in multisensory integration might actually explain a significant amount of the developmental effects that have traditionally been attributed to changes in executive functioning. In a system, neurophysiological approach combining electroencephaloram (EEG) recordings and source localization analyses, we therefore examined this question. The results show that differences in how children and adults accomplish multicomponent behavior do not solely depend on developmental differences in executive functioning. Instead, the observed developmental differences in response selection processes (reflected by the P3 ERP) were largely dependent on the complexity of integrating temporally separated stimuli from different modalities. This effect was related to activation differences in medial frontal and inferior parietal cortices. Primary perceptual gating or attentional selection processes (P1 and N1 ERPs) were not affected. The results show that differences in multisensory integration explain parts of transformations in cognitive processes between childhood and adulthood that have traditionally been attributed to changes in executive functioning, especially when these require the integration of multiple modalities during response selection. Hum Brain Mapp 38:4933-4945, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  16. 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

  17. Constrained Null Space Component Analysis for Semiblind Source Separation Problem.

    Science.gov (United States)

    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.

  18. Autonomous learning in gesture recognition by using lobe component analysis

    Science.gov (United States)

    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.

  19. Improvement of retinal blood vessel detection using morphological component analysis.

    Science.gov (United States)

    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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. Preliminary study of soil permeability properties using principal component analysis

    Science.gov (United States)

    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.

  6. Principal Component Analysis for Normal-Distribution-Valued Symbolic Data.

    Science.gov (United States)

    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.

  7. Iris recognition based on robust principal component analysis

    Science.gov (United States)

    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.

  8. Are cognitive functions in post-menopausal women related with the contents of macro- and micro-components in the diet?

    Directory of Open Access Journals (Sweden)

    Iwona Bojar

    2015-02-01

    The results of the study concerning diet unequivocally indicate a very poor quality of diet in the group of postmenopausal women examined. The daily diet had a too high energetic value. The women consumed an excessive amount of total fat, including definitely too much monounsaturated fatty acids, and insufficient polyunsaturated fatty acids. The dietary intake of sodium and phosphorus was too high, whereas deficiencies were observed in the consumption of iron, copper, potassium, calcium, magnesium and zinc. No significant correlations were found in the analysis of cognitive functions according to the energetic value of daily diet and contents of macro- and micro-components. The results concerning verbal memory significantly depended on the daily intake of polyunsaturated fatty acids. Women who consumed polyunsaturated fatty acids below the daily normal or normal level obtained significantly higher results in verbal memory.

  9. The effects of cognitive and somatic anxiety and self-confidence on components of performance during competition.

    Science.gov (United States)

    Parfitt, G; Pates, J

    1999-05-01

    This study considered the influence of competitive anxiety and self-confidence state responses upon components of performance. Basketball players (n = 12) were trained to self-report their cognitive anxiety, somatic anxiety and self-confidence as a single response on several occasions immediately before going on court to play. Performance was video-recorded and aspects of performance that could be characterized as requiring either largely anaerobic power (height jumped) or working memory (successful passes and assists) were measured. Intra-individual performance scores were computed from these measures and the data from seven matches were subjected to regression analyses and then hierarchical regression analyses. The results indicated that, as anticipated, somatic anxiety positively predicted performance that involved anaerobic demands. Self-confidence, and not cognitive anxiety, was the main predictor of performance scores with working memory demands. It would appear that different competitive state responses exert differential effects upon aspects of actual performance. Identifying these differences will be valuable in recommending intervention strategies designed to facilitate performance.

  10. 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

  11. Variational Bayesian Learning for Wavelet Independent Component Analysis

    Science.gov (United States)

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

    2005-11-01

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

  12. Expert cognition in the production sequence of Acheulian cleavers at Gesher Benot Ya'aqov, Israel: A lithic and cognitive analysis.

    Science.gov (United States)

    Herzlinger, Gadi; Wynn, Thomas; Goren-Inbar, Naama

    2017-01-01

    Stone cleavers are one of the most distinctive components of the Acheulian toolkit. These tools were produced as part of a long and complex reduction sequence and they provide indications for planning and remarkable knapping skill. These aspects hold implications regarding the cognitive complexity and abilities of their makers and users. In this study we have analyzed a cleaver assemblage originating from the Acheulian site of Gesher Benot Ya'aqov, Israel, to provide a reconstruction of the chaîne opératoire which structured their production. This reduction sequence was taken as the basis for a cognitive analysis which allowed us to draw conclusion regarding numerous behavioral and cognitive aspects of the GBY hominins. The results indicate that the cleavers production incorporated a highly specific sequence of decisions and actions which resulted in three distinct modes of cleavers modification. Furthermore, the decision to produce a cleaver must have been taken very early in the sequence, thus differentiating its production from that of handaxes. The substantial predetermination and the specific reduction sequence provide evidence that the Gesher Benot Ya'aqov hominins had a number of cognitive categories such as a general 'tool concept' and a more specific 'cleaver concept', setting them apart from earlier tool-producing hominins and extant tool-using non-human primates. Furthermore, it appears that the Gesher Benot Ya'aqov lithic technology was governed by expert cognition, which is the kind of thinking typical of modern human experts in their various domains. Thus, the results provide direct indications that important components of modern cognition have been well established in the minds of the Gesher Benot Ya'aqov hominins.

  13. Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

    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)

  14. Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

    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)

  15. Immigrant Students’ Emotional and Cognitive Engagement at School: A Multilevel Analysis of Students in 41 countries

    Science.gov (United States)

    Chiu, Ming Ming; Pong, Suet-ling; Mori, Izumi; Chow, Bonnie Wing-Yin

    2014-01-01

    Central to student learning and academic success, the school engagement of immigrant children also reflects their adaptation to a primary institution in their new country. Analysis of questionnaire responses of 276,165 fifteen-year-olds (50 % female) and their 10,789 school principals in 41 countries showed that school engagement has distinct, weakly-linked cognitive and emotional components. Native students had weaker attitudes toward school (cognitive engagement) but greater sense of belonging at school (emotional engagement) than immigrant students or students who spoke a foreign language at home. Students with better teacher–student relationships, teacher support or a classroom disciplinary climate often had a greater sense of belonging at school and had better attitudes toward school than other students. While immigrant students often have solid attitudes toward school, teachers can help them feel a greater sense of belonging at school. PMID:22484548

  16. Maternal Obesity and Excessive Gestational Weight Gain Are Associated with Components of Child Cognition.

    Science.gov (United States)

    Pugh, Sarah J; Richardson, Gale A; Hutcheon, Jennifer A; Himes, Katherine P; Brooks, Maria M; Day, Nancy L; Bodnar, Lisa M

    2015-11-01

    Maternal overweight and obesity affect two-thirds of women of childbearing age and may increase the risk of impaired child cognition. Our objective was to test the hypothesis that high/low gestational weight gain (GWG) and high/low prepregnancy BMI were associated with offspring intelligence quotient (IQ) and executive function at age 10. Mother-infant dyads (n = 763) enrolled in a birth cohort study were followed from early pregnancy to 10 y postpartum. IQ was assessed by trained examiners with the use of the Stanford Binet Intelligence Scale-4th edition. Executive function was assessed by the number of perseverative errors on the Wisconsin Card Sorting Test and time to complete Part B on the Trail Making Test. Self-reported total GWG was converted to gestational-age-standardized GWG z score. Multivariable linear regression and negative binomial regression were used to estimate independent and joint effects of GWG and BMI on outcomes while adjusting for covariates. At enrollment, the majority of women in the Maternal Health Practices and Child Development cohort were unmarried and unemployed, and more than one-half reported their race as black. The mean ± SD GWG z score was -0.5 ± 1.8, and 27% of women had a pregravid BMI ≥ 25. The median (IQR) number of perseverative errors was 23 (17, 29), the mean ± SD time on Part B was 103 ± 42.6 s, and 44% of children had a low average IQ (≤ 89). Maternal obesity was associated with 3.2 lower IQ points (95% CI: -5.6, -0.8) and a slower time to complete the executive function scale Part B (adjusted β: 12.7 s; 95% CI: 2.8, 23 s) compared with offspring of normal-weight mothers. Offspring of mothers whose GWG was >+1 SD, compared with -1 to +1 SD, performed 15 s slower on the executive function task (95% CI: 1.8, 28 s). There was no association between GWG z score and offspring composite IQ score (adjusted β: -0.32; 95% CI: -0.72, 0.10). Prepregnancy BMI did not modify these associations. Although GWG may be important

  17. Outage analysis for underlay relay-assisted cognitive networks

    KAUST Repository

    Tourki, Kamel; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

    2012-01-01

    Cooperative relay technology was recently introduced into cognitive radio networks in order to enhance network capacity, scalability, and reliability of end-to-end communication. In this paper, we investigate an underlay cognitive network where the quality of service of the secondary link is maintained by triggering an opportunistic regenerative relaying once it falls under an unacceptable level. We first provide the exact cumulative density function (CDF) of received signal-to-noise (SNR) over each hop with co-located relays. Then, the CDFs are used to determine very accurate closed-form expression for the outage probability for a transmission rate R. We validate our analysis by showing that simulation results coincide with our analytical results in Rayleigh fading channels. © 2012 IEEE.

  18. Outage analysis for underlay relay-assisted cognitive networks

    KAUST Repository

    Tourki, Kamel

    2012-12-01

    Cooperative relay technology was recently introduced into cognitive radio networks in order to enhance network capacity, scalability, and reliability of end-to-end communication. In this paper, we investigate an underlay cognitive network where the quality of service of the secondary link is maintained by triggering an opportunistic regenerative relaying once it falls under an unacceptable level. We first provide the exact cumulative density function (CDF) of received signal-to-noise (SNR) over each hop with co-located relays. Then, the CDFs are used to determine very accurate closed-form expression for the outage probability for a transmission rate R. We validate our analysis by showing that simulation results coincide with our analytical results in Rayleigh fading channels. © 2012 IEEE.

  19. COGNITIVE COMPETENCE COMPARED TO COGNITIVE INDEPENDENCE AND COGNITIVE ACTIVITY

    Directory of Open Access Journals (Sweden)

    Irina B. Shmigirilova

    2014-01-01

    Full Text Available The research is aimed at identifying the essence of the cognitive competence concept in comparison with the concepts of cognitive independence and activity.Methods: The methodology implies a theoretical analysis of psychopedagogical and methodological materials on the cognitive competence formation; generalized teaching experience; empirical methods of direct observations of educational process in the secondary school classrooms; interviews with school teachers and pupils.Results: The research outcomes reveal a semantic intersection between the cognitive competence, independence and activity, and their distinctive features. The paper emphasizes the importance of cognitive competence as an adaptive mechanism in situations of uncertainty and instability.Scientific novelty: The author clarifies the concept of cognitive competence regarding it as a multi-component and systematic characteristic of a personality.Practical significance: The research findings can be used by specialists in didactics developing the teaching techniques of cognitive competence formation for schoolchildren.

  20. A Principal Component Analysis of 39 Scientific Impact Measures

    Science.gov (United States)

    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

  1. 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

  2. Cnn Based Retinal Image Upscaling Using Zero Component Analysis

    Science.gov (United States)

    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.

  3. 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.

  4. 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

  5. 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

  6. 3D Assembly Group Analysis for Cognitive Automation

    Directory of Open Access Journals (Sweden)

    Christian Brecher

    2012-01-01

    Full Text Available A concept that allows the cognitive automation of robotic assembly processes is introduced. An assembly cell comprised of two robots was designed to verify the concept. For the purpose of validation a customer-defined part group consisting of Hubelino bricks is assembled. One of the key aspects for this process is the verification of the assembly group. Hence a software component was designed that utilizes the Microsoft Kinect to perceive both depth and color data in the assembly area. This information is used to determine the current state of the assembly group and is compared to a CAD model for validation purposes. In order to efficiently resolve erroneous situations, the results are interactively accessible to a human expert. The implications for an industrial application are demonstrated by transferring the developed concepts to an assembly scenario for switch-cabinet systems.

  7. Effectiveness of multi-component non-pharmacologic delirium interventions: A Meta-analysis

    Science.gov (United States)

    Hshieh, Tammy T.; Yue, Jirong; Oh, Esther; Puelle, Margaret; Dowal, Sarah; Travison, Thomas; Inouye, Sharon K.

    2015-01-01

    Importance Delirium, an acute disorder with high morbidity and mortality, is often preventable through multi-component non-pharmacologic strategies. The efficacy of these strategies for preventing subsequent adverse outcomes has been limited to small studies. Objective Evaluate available evidence on multi-component non-pharmacologic delirium interventions in reducing incident delirium and preventing poor outcomes associated with delirium. Data Sources PubMed, Google Scholar, ScienceDirect and Cochrane Database of Systematic Reviews from January 1, 1999–December 31, 2013. Study Selection Studies examining the following outcomes were included: delirium incidence, falls, length of stay, rate of discharge to a long-term care institution, change in functional or cognitive status. Data Extraction and Synthesis Two experienced physician reviewers independently and blindly abstracted data on outcome measures using a standardized approach. The reviewers conducted quality ratings based on the Cochrane Risk of Bias criteria for each study. Main Outcomes and Measures We identified 14 interventional studies. Results for outcomes of delirium, falls, length of stay and institutionalization data were pooled for meta-analysis but heterogeneity limited meta-analysis of results for outcomes of functional and cognitive decline. Overall, eleven studies demonstrated significant reductions in delirium incidence (Odds Ratio 0.47, 95% Confidence Interval 0.38–0.58). The four randomized or matched (RMT) studies reduced delirium incidence by 44% (95% CI 0.42–0.76). Rate of falls decreased significantly among intervention patients in four studies (OR 0.38, 95% CI 0.25–0.60); in the two RMTs, the fall rate was reduced by 64% (95% CI 0.22–0.61). Lengths of stay and institutionalization rates also trended towards decreases in the intervention groups, mean difference −0.16 days shorter (95% CI −0.97–0.64) and odds of institutionalization 5% lower (OR 0.95, 95% CI 0.71–1

  8. The Effect of Occupation-based Cognitive Rehabilitation for Traumatic Brain Injury: A Meta-analysis of Randomized Controlled Trials.

    Science.gov (United States)

    Park, Hae Yean; Maitra, Kinsuk; Martinez, Kristina Marie

    2015-06-01

    Traumatic brain injury (TBI) is the leading cause of death and disability among people younger than 35 years in the United States. Cognitive difficulty is a common consequence of TBI. To address cognitive deficits of patients with TBI, various cognitive rehabilitation approaches have been used for the clinical setting. The purpose of this study was to investigate the overall effect of occupation-based cognitive rehabilitation on patients' improvement in cognitive performance components, activity of daily living (ADL) performance, and values, beliefs and spirituality functions of patients with TBI. The papers used in this study were retrieved from the Cochrane Database, EBSCO (CINAHL), PsycINFO, PubMed and Web of Science published between 1997 and 2014. The keywords for searching were cognitive, rehabilitation, occupation, memory, attention, problem-solving, executive function, ADL, values, beliefs, spirituality, randomized controlled trials and TBI. For the meta-analysis, we examined 60 effect sizes from nine studies that are related to the occupation-based cognitive rehabilitation on persons with TBI. In persons with TBI, overall mental functions, ADL, and values, beliefs and spirituality were significantly improved in the groups that received occupation-based cognitive rehabilitation compared with comparison groups (mean d = 0.19, p cognitive rehabilitation would be beneficial for individuals with TBI for improving daily functioning and positively be able to affect their psychosocial functions. Collecting many outcome measures in studies with relatively few participants and the final data are less reliable than the whole instrument itself. Future research should evaluate the effectiveness of specific occupation-based cognitive rehabilitations programmes in order to improve consistency among rehabilitation providers. Copyright © 2015 John Wiley & Sons, Ltd.

  9. An advanced human reliability analysis methodology: analysis of cognitive errors focused on

    International Nuclear Information System (INIS)

    Kim, J. H.; Jeong, W. D.

    2001-01-01

    The conventional Human Reliability Analysis (HRA) methods such as THERP/ASEP, HCR and SLIM has been criticised for their deficiency in analysing cognitive errors which occurs during operator's decision making process. In order to supplement the limitation of the conventional methods, an advanced HRA method, what is called the 2 nd generation HRA method, including both qualitative analysis and quantitative assessment of cognitive errors has been being developed based on the state-of-the-art theory of cognitive systems engineering and error psychology. The method was developed on the basis of human decision-making model and the relation between the cognitive function and the performance influencing factors. The application of the proposed method to two emergency operation tasks is presented

  10. Comparing the Cognitive Process of Circular Causality in Two Patients with Strokes through Qualitative Analysis.

    Science.gov (United States)

    Derakhshanrad, Seyed Alireza; Piven, Emily; Ghoochani, Bahareh Zeynalzadeh

    2017-10-01

    Walter J. Freeman pioneered the neurodynamic model of brain activity when he described the brain dynamics for cognitive information transfer as the process of circular causality at intention, meaning, and perception (IMP) levels. This view contributed substantially to establishment of the Intention, Meaning, and Perception Model of Neuro-occupation in occupational therapy. As described by the model, IMP levels are three components of the brain dynamics system, with nonlinear connections that enable cognitive function to be processed in a circular causality fashion, known as Cognitive Process of Circular Causality (CPCC). Although considerable research has been devoted to study the brain dynamics by sophisticated computerized imaging techniques, less attention has been paid to study it through investigating the adaptation process of thoughts and behaviors. To explore how CPCC manifested thinking and behavioral patterns, a qualitative case study was conducted on two matched female participants with strokes, who were of comparable ages, affected sides, and other characteristics, except for their resilience and motivational behaviors. CPCC was compared by matrix analysis between two participants, using content analysis with pre-determined categories. Different patterns of thinking and behavior may have happened, due to disparate regulation of CPCC between two participants.

  11. 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)

  12. Sensor Failure Detection of FASSIP System using Principal Component Analysis

    Science.gov (United States)

    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.

  13. 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.

  14. 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.)

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

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Cota Navin Gupta

    2017-09-01

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

  17. 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.

  18. 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.

  19. Role of Dietary Pattern Analysis in Determining Cognitive Status in Elderly Australian Adults

    Directory of Open Access Journals (Sweden)

    Kimberly Ashby-Mitchell

    2015-02-01

    Full Text Available Principal Component Analysis (PCA was used to determine the association between dietary patterns and cognitive function and to examine how classification systems based on food groups and food items affect levels of association between diet and cognitive function. The present study focuses on the older segment of the Australian Diabetes, Obesity and Lifestyle Study (AusDiab sample (age 60+ that completed the food frequency questionnaire at Wave 1 (1999/2000 and the mini-mental state examination and tests of memory, verbal ability and processing speed at Wave 3 (2012. Three methods were used in order to classify these foods before applying PCA. In the first instance, the 101 individual food items asked about in the questionnaire were used (no categorisation. In the second and third instances, foods were combined and reduced to 32 and 20 food groups, respectively, based on nutrient content and culinary usage—a method employed in several other published studies for PCA. Logistic regression analysis and generalized linear modelling was used to analyse the relationship between PCA-derived dietary patterns and cognitive outcome. Broader food group classifications resulted in a greater proportion of food use variance in the sample being explained (use of 101 individual foods explained 23.22% of total food use, while use of 32 and 20 food groups explained 29.74% and 30.74% of total variance in food use in the sample, respectively. Three dietary patterns were found to be associated with decreased odds of cognitive impairment (CI. Dietary patterns derived from 101 individual food items showed that for every one unit increase in ((Fruit and Vegetable Pattern: p = 0.030, OR 1.061, confidence interval: 1.006–1.118; (Fish, Legumes and Vegetable Pattern: p = 0.040, OR 1.032, confidence interval: 1.001–1.064; (Dairy, Cereal and Eggs Pattern: p = 0.003, OR 1.020, confidence interval: 1.007–1.033, the odds of cognitive impairment decreased. Different

  20. 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

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

    Science.gov (United States)

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

    2017-07-01

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

  2. 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.

  3. Outage analysis for underlay cognitive networks using incremental regenerative relaying

    KAUST Repository

    Tourki, Kamel

    2013-02-01

    Cooperative relay technology has recently been introduced into cognitive radio (CR) networks to enhance the network capacity, scalability, and reliability of end-to-end communication. In this paper, we investigate an underlay cognitive network where the quality of service (QoS) of the secondary link is maintained by triggering an opportunistic regenerative relaying once it falls under an unacceptable level. Analysis is conducted for two schemes, referred to as the channel-state information (CSI)-based and fault-tolerant schemes, respectively, where different amounts of CSI were considered. We first provide the exact cumulative distribution function (cdf) of the received signal-to-noise ratio (SNR) over each hop with colocated relays. Then, the cdf\\'s are used to determine a very accurate closed-form expression for the outage probability for a transmission rate $R$. In a high-SNR region, a floor of the secondary outage probability occurs, and we derive its corresponding expression. We validate our analysis by showing that the simulation results coincide with our analytical results in Rayleigh fading channels. © 1967-2012 IEEE.

  4. Communicating uncertainty in cost-benefit analysis : A cognitive psychological perspective

    NARCIS (Netherlands)

    Mouter, N.; Holleman, M.; Calvert, S.C.; Annema, J.A.

    2013-01-01

    Based on a cognitive psychological theory, this paper aims to improve the communication of uncertainty in Cost-Benefit Analysis. The theory is based on different cognitive-personality and cognitive-social psychological constructs that may help explain individual differences in the processing of

  5. Cognitive systems engineering analysis of the JCO criticality accident

    International Nuclear Information System (INIS)

    Tanabe, Fumiya; Yamaguchi, Yukichi

    2000-01-01

    The JCO Criticality Accident is analyzed with a framework based on cognitive systems engineering. With the framework, analysis is conducted integrally both from the system viewpoint and actors viewpoint. The occupational chemical risk was important as safety constraint for the actors as well as the nuclear risk, which is due to criticality accident, to the public and to actors. The inappropriate actor's mental model of the work system played a critical role and several factors (e.g. poor training and education, lack of information on criticality safety control in the procedures and instructions, and lack of warning signs at workplace) contributed to form and shape the mental model. Based on the analysis, several countermeasures, such as warning signs, information system for supporting actors and improved training and education, are derived to prevent such an accident. (author)

  6. 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...

  7. Motor-cognitive dual-task performance: effects of a concurrent motor task on distinct components of visual processing capacity.

    Science.gov (United States)

    Künstler, E C S; Finke, K; Günther, A; Klingner, C; Witte, O; Bublak, P

    2018-01-01

    Dual tasking, or the simultaneous execution of two continuous tasks, is frequently associated with a performance decline that can be explained within a capacity sharing framework. In this study, we assessed the effects of a concurrent motor task on the efficiency of visual information uptake based on the 'theory of visual attention' (TVA). TVA provides parameter estimates reflecting distinct components of visual processing capacity: perceptual threshold, visual processing speed, and visual short-term memory (VSTM) storage capacity. Moreover, goodness-of-fit values and bootstrapping estimates were derived to test whether the TVA-model is validly applicable also under dual task conditions, and whether the robustness of parameter estimates is comparable in single- and dual-task conditions. 24 subjects of middle to higher age performed a continuous tapping task, and a visual processing task (whole report of briefly presented letter arrays) under both single- and dual-task conditions. Results suggest a decline of both visual processing capacity and VSTM storage capacity under dual-task conditions, while the perceptual threshold remained unaffected by a concurrent motor task. In addition, goodness-of-fit values and bootstrapping estimates support the notion that participants processed the visual task in a qualitatively comparable, although quantitatively less efficient way under dual-task conditions. The results support a capacity sharing account of motor-cognitive dual tasking and suggest that even performing a relatively simple motor task relies on central attentional capacity that is necessary for efficient visual information uptake.

  8. Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis.

    Science.gov (United States)

    Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M

    2017-06-01

    The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.

  9. Combining Automatic Item Generation and Experimental Designs to Investigate the Contribution of Cognitive Components to the Gender Difference in Mental Rotation

    Science.gov (United States)

    Arendasy, Martin E.; Sommer, Markus; Gittler, Georg

    2010-01-01

    Marked gender differences in three-dimensional mental rotation have been broadly reported in the literature in the last few decades. Various theoretical models and accounts were used to explain the observed differences. Within the framework of linking item design features of mental rotation tasks to cognitive component processes associated with…

  10. Outage analysis for underlay cognitive networks using incremental regenerative relaying

    KAUST Repository

    Tourki, Kamel; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

    2013-01-01

    Cooperative relay technology has recently been introduced into cognitive radio (CR) networks to enhance the network capacity, scalability, and reliability of end-to-end communication. In this paper, we investigate an underlay cognitive network where

  11. A framework for the analysis of cognitive reliability in complex systems: a recovery centred approach

    International Nuclear Information System (INIS)

    Kontogiannis, Tom

    1997-01-01

    Managing complex industrial systems requires reliable performance of cognitive tasks undertaken by operating crews. The infrequent practice of cognitive skills and the reliance on operator performance for novel situations raised cognitive reliability into an urgent and essential aspect in system design and risk analysis. The aim of this article is to contribute to the development of methods for the analysis of cognitive tasks in complex man-machine interactions. A practical framework is proposed for analysing cognitive errors and enhancing error recovery through interface design. Cognitive errors are viewed as failures in problem solving which are difficult to recover under the task constrains imposed by complex systems. In this sense, the interaction between context and cognition, on the one hand, and the process of error recovery, on the other hand, become the focal points of the proposed framework which is illustrated in an analysis of a simulated emergency

  12. Physical and cognitive task analysis in interventional radiology

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, S [School of Psychology, University of Liverpool, Liverpool (United Kingdom); Healey, A [Royal Liverpool University Hospital, Liverpool (United Kingdom); Evans, J [Royal Liverpool University Hospital, Liverpool (United Kingdom); Murphy, M [Royal Liverpool University Hospital, Liverpool (United Kingdom); Crawshaw, M [Department of Psychology, University of Hull, Hull (United Kingdom); Gould, D [Royal Liverpool University Hospital, Liverpool (United Kingdom)

    2006-01-15

    AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model.

  13. Physical and cognitive task analysis in interventional radiology

    International Nuclear Information System (INIS)

    Johnson, S.; Healey, A.; Evans, J.; Murphy, M.; Crawshaw, M.; Gould, D.

    2006-01-01

    AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model

  14. Cognitive Systems Modeling and Analysis of Command and Control Systems

    Science.gov (United States)

    Norlander, Arne

    2012-01-01

    Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

  15. Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability Analysis

    Directory of Open Access Journals (Sweden)

    Chrispen Murungweni

    2011-12-01

    Full Text Available Feedback mechanisms are important in the analysis of vulnerability and resilience of social-ecological systems, as well as in the analysis of livelihoods, but how to evaluate systems with direct feedbacks has been a great challenge. We applied fuzzy cognitive mapping, a tool that allows analysis of both direct and indirect feedbacks and can be used to explore the vulnerabilities of livelihoods to identified hazards. We studied characteristics and drivers of rural livelihoods in the Great Limpopo Transfrontier Conservation Area in southern Africa to assess the vulnerability of inhabitants to the different hazards they face. The process involved four steps: (1 surveys and interviews to identify the major livelihood types; (2 description of specific livelihood types in a system format using fuzzy cognitive maps (FCMs, a semi-quantitative tool that models systems based on people's knowledge; (3 linking variables and drivers in FCMs by attaching weights; and (4 defining and applying scenarios to visualize the effects of drought and changing park boundaries on cash and household food security. FCMs successfully gave information concerning the nature (increase or decrease and magnitude by which a livelihood system changed under different scenarios. However, they did not explain the recovery path in relation to time and pattern (e.g., how long it takes for cattle to return to desired numbers after a drought. Using FCMs revealed that issues of policy, such as changing situations at borders, can strongly aggravate effects of climate change such as drought. FCMs revealed hidden knowledge and gave insights that improved the understanding of the complexity of livelihood systems in a way that is better appreciated by stakeholders.

  16. 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)

  17. Approaches to analysis in model-based cognitive neuroscience

    NARCIS (Netherlands)

    Turner, B.M.; Forstmann, B.U.; Love, B.C.; Palmeri, T.J.; Van Maanen, L.

    Our understanding of cognition has been advanced by two traditionally non-overlapping and non-interacting groups. Mathematical psychologists rely on behavioral data to evaluate formal models of cognition, whereas cognitive neuroscientists rely on statistical models to understand patterns of neural

  18. Abstract Interfaces for Data Analysis Component Architecture for Data Analysis Tools

    CERN Document Server

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

    2001-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Stefania Salvatore

    2016-07-01

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

  20. Independent component analysis of edge information for face recognition

    CERN Document Server

    Karande, Kailash Jagannath

    2013-01-01

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

  1. 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...

  2. Combining network analysis with Cognitive Work Analysis: insights into social organisational and cooperation analysis.

    Science.gov (United States)

    Houghton, Robert J; Baber, Chris; Stanton, Neville A; Jenkins, Daniel P; Revell, Kirsten

    2015-01-01

    Cognitive Work Analysis (CWA) allows complex, sociotechnical systems to be explored in terms of their potential configurations. However, CWA does not explicitly analyse the manner in which person-to-person communication is performed in these configurations. Consequently, the combination of CWA with Social Network Analysis provides a means by which CWA output can be analysed to consider communication structure. The approach is illustrated through a case study of a military planning team. The case study shows how actor-to-actor and actor-to-function mapping can be analysed, in terms of centrality, to produce metrics of system structure under different operating conditions. In this paper, a technique for building social network diagrams from CWA is demonstrated.The approach allows analysts to appreciate the potential impact of organisational structure on a command system.

  3. 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

  4. Design and analysis of automobile components using industrial procedures

    Science.gov (United States)

    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.

  5. 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.

  6. 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 ...

  7. 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 ...

  8. 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 ...

  9. Roles of Vascular and Metabolic Components in Cognitive Dysfunction of Alzheimer disease: Short- and Long-term Modification by Non-genetic Risk Factors

    Directory of Open Access Journals (Sweden)

    Naoyuki eSato

    2013-11-01

    Full Text Available It is well known that a specific set of genetic and non-genetic risk factors contributes to the onset of Alzheimer disease (AD. Non-genetic risk factors include diabetes, hypertension in mid-life, and probably dyslipidemia in mid-life. This review focuses on the vascular and metabolic components of non-genetic risk factors. The mechanisms whereby non-genetic risk factors modify cognitive dysfunction are divided into four components, short- and long-term effects of vascular and metabolic factors. These consist of 1 compromised vascular reactivity, 2 vascular lesions, 3 hypo/hyperglycemia, and 4 exacerbated AD histopathological features, respectively. Vascular factors compromise cerebrovascular reactivity in response to neuronal activity and also cause irreversible vascular lesions. On the other hand, representative short-term effects of metabolic factors on cognitive dysfunction occur due to hypoglycemia or hyperglycemia. Non-genetic risk factors also modify the pathological manifestations of AD in the long-term. Therefore, vascular and metabolic factors contribute to aggravation of cognitive dysfunction in AD through short-term and long-term effects. Beta-amyloid could be involved in both vascular and metabolic components. It might be beneficial to support treatment in AD patients by appropriate therapeutic management of non-genetic risk factors, considering the contributions of these four elements to the manifestation of cognitive dysfunction in individual patients, though all components are not always present. It should be clarified how these four components interact with each other. To answer this question, a clinical prospective study that follows up clinical features with respect to these four components: 1 functional MRI or SPECT for cerebrovascular reactivity, 2 MRI for ischemic lesions and atrophy, 3 clinical episodes of hypoglycemia and hyperglycemia, 4 amyloid-PET and tau-PET for pathological features of AD, would be required.

  10. Roles of vascular and metabolic components in cognitive dysfunction of Alzheimer disease: short- and long-term modification by non-genetic risk factors.

    Science.gov (United States)

    Sato, Naoyuki; Morishita, Ryuichi

    2013-11-05

    It is well known that a specific set of genetic and non-genetic risk factors contributes to the onset of Alzheimer disease (AD). Non-genetic risk factors include diabetes, hypertension in mid-life, and probably dyslipidemia in mid-life. This review focuses on the vascular and metabolic components of non-genetic risk factors. The mechanisms whereby non-genetic risk factors modify cognitive dysfunction are divided into four components, short- and long-term effects of vascular and metabolic factors. These consist of (1) compromised vascular reactivity, (2) vascular lesions, (3) hypo/hyperglycemia, and (4) exacerbated AD histopathological features, respectively. Vascular factors compromise cerebrovascular reactivity in response to neuronal activity and also cause irreversible vascular lesions. On the other hand, representative short-term effects of metabolic factors on cognitive dysfunction occur due to hypoglycemia or hyperglycemia. Non-genetic risk factors also modify the pathological manifestations of AD in the long-term. Therefore, vascular and metabolic factors contribute to aggravation of cognitive dysfunction in AD through short-term and long-term effects. β-amyloid could be involved in both vascular and metabolic components. It might be beneficial to support treatment in AD patients by appropriate therapeutic management of non-genetic risk factors, considering the contributions of these four elements to the manifestation of cognitive dysfunction in individual patients, though all components are not always present. It should be clarified how these four components interact with each other. To answer this question, a clinical prospective study that follows up clinical features with respect to these four components: (1) functional MRI or SPECT for cerebrovascular reactivity, (2) MRI for ischemic lesions and atrophy, (3) clinical episodes of hypoglycemia and hyperglycemia, (4) amyloid-PET and tau-PET for pathological features of AD, would be required.

  11. Talented football players' development of achievement motives, volitional components, and self-referential cognitions: A longitudinal study.

    Science.gov (United States)

    Feichtinger, Philip; Höner, Oliver

    2015-01-01

    Adolescence is regarded as a key developmental phase in the course of talented football players' careers. The present study focuses on early adolescent players' development of achievement motives, volitional components, and self-referential cognitions. Based on the multidimensional and dynamic nature of talent, the development of multifaceted personality characteristics is an important issue in the context of sports talent research. According to previous findings in psychology, personality characteristics' development is defined by both stability and change, and the current study analyses four different types: differential stability (I), mean-level change (II), individual-level change (III), and structural stability (IV). The sample consists of 151 male players in the talent development programme of the German Football Association. Psychological diagnostics of the personality characteristics are implemented across longitudinal sections over a time period of three seasons, from the U12 to U14 age classes. The results reveal that the personality characteristics show (I) moderate test-retest correlations over one-year intervals (.43 ≤ rtt ≤ .62), and lower coefficients for a two-year period (.26 ≤ rtt ≤ .53). (II) Most of the personality characteristics' mean values differ significantly across the age classes with small effect sizes (.01 ≤ [Formula: see text] ≤ .03). (III) Only minor individual-level changes in the football players' development are found. (IV) The personality characteristics' associations within a two-factor structure do not stay invariant over time. From the results of the present study, conclusions are drawn regarding the talent identification and development process.

  12. The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

    Science.gov (United States)

    Lamb, Richard L.

    Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student

  13. HUMAN RELIABILITY ANALYSIS DENGAN PENDEKATAN COGNITIVE RELIABILITY AND ERROR ANALYSIS METHOD (CREAM

    Directory of Open Access Journals (Sweden)

    Zahirah Alifia Maulida

    2015-01-01

    Full Text Available Kecelakaan kerja pada bidang grinding dan welding menempati urutan tertinggi selama lima tahun terakhir di PT. X. Kecelakaan ini disebabkan oleh human error. Human error terjadi karena pengaruh lingkungan kerja fisik dan non fisik.Penelitian kali menggunakan skenario untuk memprediksi serta mengurangi kemungkinan terjadinya error pada manusia dengan pendekatan CREAM (Cognitive Reliability and Error Analysis Method. CREAM adalah salah satu metode human reliability analysis yang berfungsi untuk mendapatkan nilai Cognitive Failure Probability (CFP yang dapat dilakukan dengan dua cara yaitu basic method dan extended method. Pada basic method hanya akan didapatkan nilai failure probabailty secara umum, sedangkan untuk extended method akan didapatkan CFP untuk setiap task. Hasil penelitian menunjukkan faktor- faktor yang mempengaruhi timbulnya error pada pekerjaan grinding dan welding adalah kecukupan organisasi, kecukupan dari Man Machine Interface (MMI & dukungan operasional, ketersediaan prosedur/ perencanaan, serta kecukupan pelatihan dan pengalaman. Aspek kognitif pada pekerjaan grinding yang memiliki nilai error paling tinggi adalah planning dengan nilai CFP 0.3 dan pada pekerjaan welding yaitu aspek kognitif execution dengan nilai CFP 0.18. Sebagai upaya untuk mengurangi nilai error kognitif pada pekerjaan grinding dan welding rekomendasi yang diberikan adalah memberikan training secara rutin, work instrucstion yang lebih rinci dan memberikan sosialisasi alat. Kata kunci: CREAM (cognitive reliability and error analysis method, HRA (human reliability analysis, cognitive error Abstract The accidents in grinding and welding sectors were the highest cases over the last five years in PT. X and it caused by human error. Human error occurs due to the influence of working environment both physically and non-physically. This study will implement an approaching scenario called CREAM (Cognitive Reliability and Error Analysis Method. CREAM is one of human

  14. Analysis and test of insulated components for rotary engine

    Science.gov (United States)

    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.

  15. 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.

  16. 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.

  17. Analysis of the Components of Economic Potential of Agricultural Enterprises

    OpenAIRE

    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...

  18. Cognitive IT-systems for big data analysis in medicine.

    Science.gov (United States)

    Isakova, J

    2015-01-01

    Rapid development of medicine requires regular update of clinical data evidence. This task accomplishment requires participation of numerous specialists in evidence-based medicine, who are proficient in various statistical methods and can work with big data analysis tools in biomedical sciences. This, in turn, requires significant time and other resources. Today, at the peak of IT development, cognitive systems in the field of medicine with special technologies of data collection and analysis, is the start of a new trend. The development of cognitive IT system for drug prescription with the potential to analyze automatically the information about drugs effectiveness and safety on the basis of clinical practice experience and scientific data according to evidence levels and patients' personal characteristics. The cognitive system was developed with the use of United Medical Knowledge Base (UMKB). UMKB is a semantic network of medical knowledge, which is structured according to the medical ontologies and the theory of fuzzy logic. UMKB is being filled simultaneously in all the areas of medicine. From one side it is filled by means of the linguistic module analyzing medical texts, from the second side - by academic institutions, from the third side - by the cognitive IT systems with the data from electronic health records (EHRs). Native language of UMKB is Russian. It is designed primarily for use in the Russian clinical practice. However the platform for filling knowledge is multilingual and supports any other languages. This means that the practice of world schools may also be integrated and used in UMKB. The peculiarity lies in the fact that UMKB is presented as a semantic network where biomedical knowledge are structured according to certain medical ontologies (special rules of information storage that carries data: phenomena, processes, simple and complex concepts in medicine, - in the form of interrelated objects). The keystone underlying UMKB is the model of

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

    Science.gov (United States)

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

    2015-01-01

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

  20. The importance of human cognitive models in the safety analysis report of nuclear power plants - a comparative review

    International Nuclear Information System (INIS)

    Alvarenga, Marco A.B.; Araujo Goes, Alexandre G. de

    1997-01-01

    The chapter 18 of the Brazilian NPPs Safety Analysis Report (SAR) deals with Human Factor Engineering (HFE). The chapter evaluation is distributed among ten topics. One of them, the HRA (Human Reliability Analysis) becomes the central subject of the whole analysis, generating information to the other topics, as for example, high risk operational critical sequences. The HRA methods used in the past concerned the approach of modeling the human being as a component (hardware), based in a failure or success bivalent logic. In the last ten years, several human cognitive models were developed to be used in the nuclear field as well as in the conventional industry, mainly in the military aviation. In this paper, we describe their main features, comparing some models to each other, with the main purpose of determining the minimal characteristics acceptable for NPPs licensing, being part of these cognitive models, to be used mainly in the evaluation of HRAs from SARs in the NPPs. (author). 10 refs

  1. Probabilistic structural analysis of aerospace components using NESSUS

    Science.gov (United States)

    Shiao, Michael C.; Nagpal, Vinod K.; Chamis, Christos C.

    1988-01-01

    Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

  2. Body image disturbance in binge eating disorder: a comparison of obese patients with and without binge eating disorder regarding the cognitive, behavioral and perceptual component of body image.

    Science.gov (United States)

    Lewer, Merle; Nasrawi, Nadia; Schroeder, Dorothea; Vocks, Silja

    2016-03-01

    Whereas the manifestation of body image disturbance in binge eating disorder (BED) has been intensively investigated concerning the cognitive-affective component, with regard to the behavioral and the perceptual components of body image disturbance in BED, research is limited and results are inconsistent. Therefore, the present study assessed body image disturbance in BED with respect to the different components of body image in a sample of obese females (n = 31) with BED compared to obese females without an eating disorder (n = 28). The Eating Disorder Inventory-2, the Eating Disorder Examination-Questionnaire, the Body Image Avoidance Questionnaire and the Body Checking Questionnaire as well as a Digital Photo Distortion Technique based on a picture of each participant taken under standardized conditions were employed. Using two-sample t tests, we found that the participants with BED displayed significantly greater impairments concerning the cognitive-affective component of body image than the control group. Concerning the behavioral component, participants with BED reported more body checking and avoidance behavior than the controls, but group differences failed to reach significance after the Bonferroni corrections. Regarding the perceptual component, a significant group difference was found for the perceived "ideal" figure, with the individuals suffering from BED displaying a greater wish for a slimmer ideal figure than the control group. These results support the assumption that body image disturbance is a relevant factor in BED, similar to other eating disorders.

  3. Genome-wide meta-analysis of cognitive empathy : heritability, and correlates with sex, neuropsychiatric conditions and cognition

    NARCIS (Netherlands)

    Warrier, V; Grasby, K L; Uzefovsky, F; Toro, R.; Smith, P.; Chakrabarti, B; Khadake, J.; Mawbey-Adamson, E; Litterman, N; Hottenga, J-J; Lubke, G; Boomsma, D I; Martin, Nicholas G; Hatemi, P.K.; Medland, Sarah E; Hinds, D.A.; Bourgeron, T; Baron-Cohen, S.

    2017-01-01

    We conducted a genome-wide meta-analysis of cognitive empathy using the 'Reading the Mind in the Eyes' Test (Eyes Test) in 88,056 research volunteers of European Ancestry (44,574 females and 43,482 males) from 23andMe Inc., and an additional 1497 research volunteers of European Ancestry (891 females

  4. Compressive Online Robust Principal Component Analysis with Multiple Prior Information

    DEFF Research Database (Denmark)

    Van Luong, Huynh; Deligiannis, Nikos; Seiler, Jürgen

    -rank components. Unlike conventional batch RPCA, which processes all the data directly, our method considers a small set of measurements taken per data vector (frame). Moreover, our method incorporates multiple prior information signals, namely previous reconstructed frames, to improve these paration...... and thereafter, update the prior information for the next frame. Using experiments on synthetic data, we evaluate the separation performance of the proposed algorithm. In addition, we apply the proposed algorithm to online video foreground and background separation from compressive measurements. The results show...

  5. Seismic fragility analysis of structural components for HFBR facilities

    International Nuclear Information System (INIS)

    Park, Y.J.; Hofmayer, C.H.

    1992-01-01

    The paper presents a summary of recently completed seismic fragility analyses of the HFBR facilities. Based on a detailed review of past PRA studies, various refinements were made regarding the strength and ductility evaluation of structural components. Available laboratory test data were analysed to evaluate the formulations used to predict the ultimate strength and deformation capacities of steel, reinforced concrete and masonry structures. The biasness and uncertainties were evaluated within the framework of the fragility evaluation methods widely accepted in the nuclear industry. A few examples of fragility calculations are also included to illustrate the use of the presented formulations

  6. The ethical component of professional competence in nursing: an analysis.

    Science.gov (United States)

    Paganini, Maria Cristina; Yoshikawa Egry, Emiko

    2011-07-01

    The purpose of this article is to initiate a philosophical discussion about the ethical component of professional competence in nursing from the perspective of Brazilian nurses. Specifically, this article discusses professional competence in nursing practice in the Brazilian health context, based on two different conceptual frameworks. The first framework is derived from the idealistic and traditional approach while the second views professional competence through the lens of historical and dialectical materialism theory. The philosophical analyses show that the idealistic view of professional competence differs greatly from practice. Combining nursing professional competence with philosophical perspectives becomes a challenge when ideals are opposed by the reality and implications of everyday nursing practice.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-06-15

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

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

    International Nuclear Information System (INIS)

    Kang, Ho Yang; Kim, Ki Bok

    2003-01-01

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

  9. Iso-α-acids, Bitter Components of Beer, Prevent Inflammation and Cognitive Decline Induced in a Mouse Model of Alzheimer's Disease.

    Science.gov (United States)

    Ano, Yasuhisa; Dohata, Atsushi; Taniguchi, Yoshimasa; Hoshi, Ayaka; Uchida, Kazuyuki; Takashima, Akihiko; Nakayama, Hiroyuki

    2017-03-03

    Alongside the rapid growth in aging populations worldwide, prevention and therapy for age-related memory decline and dementia are in great demand to maintain a long, healthy life. Here we found that iso-α-acids, hop-derived bitter compounds in beer, enhance microglial phagocytosis and suppress inflammation via activation of the peroxisome proliferator-activated receptor γ. In normal mice, oral administration of iso-α-acids led to a significant increase both in CD11b and CD206 double-positive anti-inflammatory type microglia ( p iso-α-acids resulted in a 21% reduction in amyloid β in the cerebral cortex as observed by immunohistochemical analysis, a significant reduction in inflammatory cytokines such as IL-1β and chemokines including macrophage inflammatory protein-1α in the cerebral cortex ( p iso-α-acid-fed mice were due to the induction of microglia to an anti-inflammatory phenotype. The present study is the first to report that amyloid β deposition and inflammation are suppressed in a mouse model of Alzheimer's disease by a single component, iso-α-acids, via the regulation of microglial activation. The suppression of neuroinflammation and improvement in cognitive function suggests that iso-α-acids contained in beer may be useful for the prevention of dementia. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  10. Iso-α-acids, Bitter Components of Beer, Prevent Inflammation and Cognitive Decline Induced in a Mouse Model of Alzheimer's Disease*

    Science.gov (United States)

    Ano, Yasuhisa; Dohata, Atsushi; Taniguchi, Yoshimasa; Hoshi, Ayaka; Uchida, Kazuyuki; Takashima, Akihiko; Nakayama, Hiroyuki

    2017-01-01

    Alongside the rapid growth in aging populations worldwide, prevention and therapy for age-related memory decline and dementia are in great demand to maintain a long, healthy life. Here we found that iso-α-acids, hop-derived bitter compounds in beer, enhance microglial phagocytosis and suppress inflammation via activation of the peroxisome proliferator-activated receptor γ. In normal mice, oral administration of iso-α-acids led to a significant increase both in CD11b and CD206 double-positive anti-inflammatory type microglia (p iso-α-acids resulted in a 21% reduction in amyloid β in the cerebral cortex as observed by immunohistochemical analysis, a significant reduction in inflammatory cytokines such as IL-1β and chemokines including macrophage inflammatory protein-1α in the cerebral cortex (p iso-α-acid-fed mice were due to the induction of microglia to an anti-inflammatory phenotype. The present study is the first to report that amyloid β deposition and inflammation are suppressed in a mouse model of Alzheimer's disease by a single component, iso-α-acids, via the regulation of microglial activation. The suppression of neuroinflammation and improvement in cognitive function suggests that iso-α-acids contained in beer may be useful for the prevention of dementia. PMID:28087694

  11. The Blame Game: Performance Analysis of Speaker Diarization System Components

    NARCIS (Netherlands)

    Huijbregts, M.A.H.; Wooters, Chuck

    2007-01-01

    In this paper we discuss the performance analysis of a speaker diarization system similar to the system that was submitted by ICSI at the NIST RT06s evaluation benchmark. The analysis that is based on a series of oracle experiments, provides a good understanding of the performance of each system

  12. Principal components analysis based control of a multi-dof underactuated prosthetic hand

    Directory of Open Access Journals (Sweden)

    Magenes Giovanni

    2010-04-01

    Full Text Available Abstract Background Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG. Driving a multi degrees of freedom (DoF hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user. Methods A Principal Components Analysis (PCA based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs. Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control. Results Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture may be achieved. Conclusions This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.

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

    Science.gov (United States)

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

    2018-05-22

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

  14. Cognitive reserve in Parkinson's disease: a systematic review and meta-analysis.

    Science.gov (United States)

    Hindle, John V; Martyr, Anthony; Clare, Linda

    2014-01-01

    The concept of cognitive reserve is proposed to explain the mismatch between the degree of pathological changes and their clinical manifestations and has been used to help understand the variation in the rate of cognitive decline and the development of dementias. It is not clear whether this concept applies to cognitive performance, cognitive decline and dementia in Parkinson's disease (PD). A systematic review was conducted using the most commonly described proxies for cognitive reserve of education, occupation and leisure activities. Thirty four papers were found on education and cognition in PD but there were no studies of the other proxies of reserve. A random effects meta-analysis was used to assess the associations between education and cross-sectional cognitive assessments, longitudinal global cognitive decline and a long term dementia diagnosis. There was a significant association between higher education and cross-sectional performance of MMSE, global cognition, mild cognitive impairment, attention, executive function, visuospatial function and memory. There was a small but significant association between higher education and a reduced rate of cognitive decline. There was no association with a final dementia diagnosis. There was not enough information to perform an analysis on the rate and timing of transition to dementia. Higher levels of education are associated with significantly better cognitive performance and a small but significant slowing in cognitive decline but are not associated with a reduction in long-term dementia in PD. More detailed, standardized, longitudinal studies are required to study conclusively the effects cognitive reserve in PD. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Dynamic analysis and qualification test of nuclear components

    International Nuclear Information System (INIS)

    Kim, B.K.; Lee, C.H.; Park, S.H.; Kim, Y.M.; Kim, B.S.; Kim, I.G.; Chung, C.W.; Kim, Y.M.

    1981-01-01

    This report contains the study on the dynamic characteristics of Wolsung fuel rod and on the dynamic balancing of rotating machinery to evaluate the performance of nuclear reactor components. The study on the dynamic characteristics of Wolsung fuel rod was carried out by both experimental and theoretical methods. Forced vibration testing of actual Wolsung fuel rod using sine sweep and sine dwell excitation was conducted to find the dynamic and nonlinear characteristics of the fuel rod. The data obtained by the test were used to analyze the nonlinear impact characteristics of the fuel rod which has a motion-constraint stop in the center of the rod. The parameters used in the test were the input force level of the exciter, the clearance gap between the fuel rod and the motion constraints, and the frequencies. Test results were in good agreement with the analytical results

  16. A component analysis of the generation and release of isometric force in Parkinson's disease.

    OpenAIRE

    Jordan, N; Sagar, H J; Cooper, J A

    1992-01-01

    Paradigms of isometric force control allow study of the generation and release of movement in the absence of complications due to disordered visuomotor coordination. The onset and release of isometric force in Parkinson's disease (PD) was studied, using computerised determinants of latency of response and rate of force generation and release. Components of isometric force control were related to measures of cognitive, affective and clinical motor disability. The effects of treatment were dete...

  17. Dissolution And Analysis Of Yellowcake Components For Fingerprinting UOC Sources

    International Nuclear Information System (INIS)

    Hexel, Cole R.; Bostick, Debra A.; Kennedy, Angel K.; Begovich, John M.; Carter, Joel A.

    2012-01-01

    There are a number of chemical and physical parameters that might be used to help elucidate the ore body from which uranium ore concentrate (UOC) was derived. It is the variation in the concentration and isotopic composition of these components that can provide information as to the identity of the ore body from which the UOC was mined and the type of subsequent processing that has been undertaken. Oak Ridge National Laboratory (ORNL) in collaboration with Lawrence Livermore and Los Alamos National Laboratories is surveying ore characteristics of yellowcake samples from known geologic origin. The data sets are being incorporated into a national database to help in sourcing interdicted material, as well as aid in safeguards and nonproliferation activities. Geologic age and attributes from chemical processing are site-specific. Isotopic abundances of lead, neodymium, and strontium provide insight into the provenance of geologic location of ore material. Variations in lead isotopes are due to the radioactive decay of uranium in the ore. Likewise, neodymium isotopic abundances are skewed due to the radiogenic decay of samarium. Rubidium decay similarly alters the isotopic signature of strontium isotopic composition in ores. This paper will discuss the chemical processing of yellowcake performed at ORNL. Variations in lead, neodymium, and strontium isotopic abundances are being analyzed in UOC from two geologic sources. Chemical separation and instrumental protocols will be summarized. The data will be correlated with chemical signatures (such as elemental composition, uranium, carbon, and nitrogen isotopic content) to demonstrate the utility of principal component and cluster analyses to aid in the determination of UOC provenance.

  18. A Content Analysis of Cognitive Health Promotion in Popular Magazines

    Science.gov (United States)

    Friedman, Daniela B.; Laditka, Sarah B.; Laditka, James N.; Price, Anna E.

    2011-01-01

    Health behaviors, particularly physical activity, may promote cognitive health. The public agenda for health behaviors is influenced by popular media. We analyzed the cognitive health content of 20 United States magazines, examining every page of every 2006-2007 issue of the highest circulating magazines for general audiences, women, men, African…

  19. Predicting cognitive decline in Alzheimer's disease: an integrated analysis

    DEFF Research Database (Denmark)

    Lopez, Oscar L; Schwam, Elias; Cummings, Jeffrey

    2010-01-01

    Numerous patient- and disease-related factors increase the risk of rapid cognitive decline in patients with Alzheimer's disease (AD). The ability of pharmacological treatment to attenuate this risk remains undefined.......Numerous patient- and disease-related factors increase the risk of rapid cognitive decline in patients with Alzheimer's disease (AD). The ability of pharmacological treatment to attenuate this risk remains undefined....

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

    Science.gov (United States)

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

    2011-11-01

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

  1. Interference Management And Game Theoretic Analysis of Cognitive Radio

    DEFF Research Database (Denmark)

    Di Taranto, Rocco

    dynamics between independent primary and cognitive user and to derive rules of local action at the independent cognitive users that result in stable and efficient system operation. We have modeled our scenario via a non-cooperative power control game so that the corresponding Nash equilibriums are taken......Cognitive Radio systems are intended to dynamically access the spectrum that is underutilized by its owner at certain time, geographical location or frequency. Dynamic spectrum access presents a great opportunity to increase the available bandwidth, but it has also posed new challenges...... to the research community. This Ph.D. thesis deals with interference management in Cognitive Radio systems: interference management is a conditio sine qua non for cognitive radio systems, as they can re-use the primary resources underused or not utilized by the respective owners, provided that primary...

  2. Cognitive approaches to analysis of emotions in music listening

    DEFF Research Database (Denmark)

    Hansen, Niels Chr.

    2013-01-01

    In recent years research into music cognition and perception has increasingly gained territory. A fact which is not always realised by music theorists is that, from the perspective of cognitive psychology and empirical methodology, the representatives of the expanding field of cognitive music...... research frequently address questions and propose theoretical frameworks that ought to have implications for music theory of a more traditional kind. Yet, such cognitive theories and empirical findings have not had radical impact on general analytical practice and teaching of music theory. For theorists...... interested in musical meaning the emotional impact of music has always been a major concern. In this paper I will explore how multiple cognitive theories and empirical findings can be applied to account for emotional response to three subjectively chosen excerpts of strongly emotion-inducing music: Namely...

  3. Multivariate analysis of remote LIBS spectra using partial least squares, principal component analysis, and related techniques

    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.

  4. Topochemical Analysis of Cell Wall Components by TOF-SIMS.

    Science.gov (United States)

    Aoki, Dan; Fukushima, Kazuhiko

    2017-01-01

    Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is a recently developing analytical tool and a type of imaging mass spectrometry. TOF-SIMS provides mass spectral information with a lateral resolution on the order of submicrons, with widespread applicability. Sometimes, it is described as a surface analysis method without the requirement for sample pretreatment; however, several points need to be taken into account for the complete utilization of the capabilities of TOF-SIMS. In this chapter, we introduce methods for TOF-SIMS sample treatments, as well as basic knowledge of wood samples TOF-SIMS spectral and image data analysis.

  5. Failure analysis of storage tank component in LNG regasification unit using fault tree analysis method (FTA)

    Science.gov (United States)

    Mulyana, Cukup; Muhammad, Fajar; Saad, Aswad H.; Mariah, Riveli, Nowo

    2017-03-01

    Storage tank component is the most critical component in LNG regasification terminal. It has the risk of failure and accident which impacts to human health and environment. Risk assessment is conducted to detect and reduce the risk of failure in storage tank. The aim of this research is determining and calculating the probability of failure in regasification unit of LNG. In this case, the failure is caused by Boiling Liquid Expanding Vapor Explosion (BLEVE) and jet fire in LNG storage tank component. The failure probability can be determined by using Fault Tree Analysis (FTA). Besides that, the impact of heat radiation which is generated is calculated. Fault tree for BLEVE and jet fire on storage tank component has been determined and obtained with the value of failure probability for BLEVE of 5.63 × 10-19 and for jet fire of 9.57 × 10-3. The value of failure probability for jet fire is high enough and need to be reduced by customizing PID scheme of regasification LNG unit in pipeline number 1312 and unit 1. The value of failure probability after customization has been obtained of 4.22 × 10-6.

  6. Multilevel component analysis of time-resolved metabolic fingerprinting data

    NARCIS (Netherlands)

    Jansen, J.J.; Hoefsloot, H.C.J.; Greef, J. van der; Timmerman, M.E.; Smilde, A.K.

    2005-01-01

    Genomics-based technologies in systems biology have gained a lot of popularity in recent years. These technologies generate large amounts of data. To obtain information from this data, multivariate data analysis methods are required. Many of the datasets generated in genomics are multilevel

  7. A Principal Components Analysis of the Rathus Assertiveness Schedule.

    Science.gov (United States)

    Law, H. G.; And Others

    1979-01-01

    Investigated the adequacy of the Rathus Assertiveness Schedule (RAS) as a global measure of assertiveness. Analysis indicated that the RAS does not provide a unidimensional index of assertiveness, but rather measures a number of factors including situation-specific assertive behavior, aggressiveness, and a more general assertiveness. (Author)

  8. Physical Activity and Cognitive Development: A Meta-Analysis.

    Science.gov (United States)

    Jackson, William M; Davis, Nicholas; Sands, Stephen A; Whittington, Robert A; Sun, Lena S

    2016-10-01

    Is there an association between regular exercise, defined as a structured program of increased physical activity at least 1 month in duration, and improvements in measures of executive functions compared with children who engage in their normal daily activities? The association between increased physical activity and changes in performance on tasks of executive functions have not been well elucidated in children. Executive functioning is important to intellectual development and academic success in children, and inexpensive, nonpharmacological methods for the treatment of executive dysfunction represent an attractive interventional target. To estimate the effect of a structured regular exercise program on neuropsychological domains of executive function in children ages 7 to 12. We performed a systematic review of English and non-English articles using Cochrane Library, EBSCO CINAHL, Ovid MEDLINE, PSYCInfo, Pubmed, and Web of Science, including all years allowed by each individual search engine. The search string used was "(exercise OR phys*) AND (cognit* OR executive) AND (child* OR preadolesc*)." The authors of the studies selected for review were contacted for any unpublished data. Randomized controlled trials, which enrolled children between the ages of 7 and 12, with randomization to either normal activity or a structured physical activity intervention consisting of scheduled aerobic exercise, at least once per week, for a period of at least 1 month. Eligible studies must have included a neuropsychological battery of tests that measured at least 1 executive function both before and after the intervention was completed. Two independent reviewers examined the screened studies in detail for potential inclusion. The results of the individual examinations were compared; if any discrepancies were present, a third party analyzed the study to determine if it should be included in the meta-analysis. A total of 18 studies were identified by abstract as candidates for

  9. Interoperability Assets for Patient Summary Components: A Gap Analysis.

    Science.gov (United States)

    Heitmann, Kai U; Cangioli, Giorgio; Melgara, Marcello; Chronaki, Catherine

    2018-01-01

    The International Patient Summary (IPS) standards aim to define the specifications for a minimal and non-exhaustive Patient Summary, which is specialty-agnostic and condition-independent, but still clinically relevant. Meanwhile, health systems are developing and implementing their own variation of a patient summary while, the eHealth Digital Services Infrastructure (eHDSI) initiative is deploying patient summary services across countries in the Europe. In the spirit of co-creation, flexible governance, and continuous alignment advocated by eStandards, the Trillum-II initiative promotes adoption of the patient summary by engaging standards organizations, and interoperability practitioners in a community of practice for digital health to share best practices, tools, data, specifications, and experiences. This paper compares operational aspects of patient summaries in 14 case studies in Europe, the United States, and across the world, focusing on how patient summary components are used in practice, to promote alignment and joint understanding that will improve quality of standards and lower costs of interoperability.

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  11. Gray and white matter changes in subjective cognitive impairment, amnestic mild cognitive impairment and Alzheimer's disease: a voxel-based analysis study.

    Directory of Open Access Journals (Sweden)

    Kuniaki Kiuchi

    Full Text Available Subjective cognitive impairment may be a very early at-risk period of the continuum of dementia. However, it is difficult to discriminate at-risk states from normal aging. Thus, detection of the early pathological changes in the subjective cognitive impairment period is needed. To elucidate these changes, we employed diffusion tensor imaging and volumetry analysis, and compared subjective cognitive impairment with normal, mild cognitive impairment and Alzheimer's disease. The subjects in this study were 39 Alzheimer's disease, 43 mild cognitive impairment, 28 subjective cognitive impairment and 41 normal controls. There were no statistically significant differences between the normal control and subjective cognitive impairment groups in all measures. Alzheimer's disease and mild cognitive impairment had the same extent of brain atrophy and diffusion changes. These results are consistent with the hypothetical model of the dynamic biomarkers of Alzheimer's disease.

  12. PV System Component Fault and Failure Compilation and Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Klise, Geoffrey Taylor; Lavrova, Olga; Gooding, Renee Lynne

    2018-02-01

    This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.

  13. INTEGRATION OF SYSTEM COMPONENTS AND UNCERTAINTY ANALYSIS - HANFORD EXAMPLES

    International Nuclear Information System (INIS)

    Wood, M.I.

    2009-01-01

    (sm b ullet) Deterministic 'One Off' analyses as basis for evaluating sensitivity and uncertainty relative to reference case (sm b ullet) Spatial coverage identical to reference case (sm b ullet) Two types of analysis assumptions - Minimax parameter values around reference case conditions - 'What If' cases that change reference case condition and associated parameter values (sm b ullet) No conclusions about likelihood of estimated result other than' qualitative expectation that actual outcome should tend toward reference case estimate

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

    OpenAIRE

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

    2013-01-01

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

  15. Principle Component Analysis of AIRS and CrIS Data

    Science.gov (United States)

    Aumann, H. H.; Manning, Evan

    2015-01-01

    Synthetic Eigen Vectors (EV) used for the statistical analysis of the PC reconstruction residual of large ensembles of data are a novel tool for the analysis of data from hyperspectral infrared sounders like the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua and the Cross-track Infrared Sounder (CrIS) on the SUOMI polar orbiting satellites. Unlike empirical EV, which are derived from the observed spectra, the synthetic EV are derived from a large ensemble of spectra which are calculated assuming that, given a state of the atmosphere, the spectra created by the instrument can be accurately calculated. The synthetic EV are then used to reconstruct the observed spectra. The analysis of the differences between the observed spectra and the reconstructed spectra for Simultaneous Nadir Overpasses of tropical oceans reveals unexpected differences at the more than 200 mK level under relatively clear conditions, particularly in the mid-wave water vapor channels of CrIS. The repeatability of these differences using independently trained SEV and results from different years appears to rule out inconsistencies in the radiative transfer algorithm or the data simulation. The reasons for these discrepancies are under evaluation.

  16. Sensitivity of cognitive tests in four cognitive domains in discriminating MDD patients from healthy controls: a meta-analysis.

    Science.gov (United States)

    Lim, JaeHyoung; Oh, In Kyung; Han, Changsu; Huh, Yu Jeong; Jung, In-Kwa; Patkar, Ashwin A; Steffens, David C; Jang, Bo-Hyoung

    2013-09-01

    We performed a meta-analysis in order to determine which neuropsychological domains and tasks would be most sensitive for discriminating between patients with major depressive disorder (MDD) and healthy controls. Relevant articles were identified through a literature search of the PubMed and Cochrane Library databases for the period between January 1997 and May 2011. A meta-analysis was conducted using the standardized means of individual cognitive tests in each domain. The heterogeneity was assessed, and subgroup analyses according to age and medication status were performed to explore the sources of heterogeneity. A total of 22 trials involving 955 MDD patients and 7,664 healthy participants were selected for our meta-analysis. MDD patients showed significantly impaired results compared with healthy participants on the Digit Span and Continuous Performance Test in the attention domain; the Trail Making Test A (TMT-A) and the Digit Symbol Test in the processing speed domain; the Stroop Test, the Wisconsin Card Sorting Test, and Verbal Fluency in the executive function domain; and immediate verbal memory in the memory domain. The Finger Tapping Task, TMT-B, delayed verbal memory, and immediate and delayed visual memory failed to separate MDD patients from healthy controls. The results of subgroup analysis showed that performance of Verbal Fluency was significantly impaired in younger depressed patients (memory was significantly reduced in depressed patients using antidepressants. Our findings have inevitable limitations arising from methodological issues inherent in the meta-analysis and we could not explain high heterogeneity between studies. Despite such limitations, current study has the strength of being the first meta-analysis which tried to specify cognitive function of depressed patients compared with healthy participants. And our findings may provide clinicians with further evidences that some cognitive tests in specific cognitive domains have sensitivity

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

    Indian Academy of Sciences (India)

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

  18. The effects of parental components in a trauma-focused cognitive behavioral based therapy for children exposed to interparental violence: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Visser, Margreet M; Telman, Machteld D; de Schipper, J Clasien; Lamers-Winkelman, Francien; Schuengel, Carlo; Finkenauer, Catrin

    2015-06-23

    Interparental violence is both common and harmful and impacts children's lives directly and indirectly. Direct effects refer to affective, behavioral, and cognitive responses to interparental violence and psychosocial adjustment. Indirect effects refer to deteriorated parental availability and parent-child interaction. Standard Trauma Focused Cognitive Behavioral Therapy may be insufficient for children traumatized by exposure to interparental violence, given the pervasive impact of interparental violence on the family system. HORIZON is a trauma focused cognitive behavioral therapy based group program with the added component of a preparatory parenting program aimed at improving parental availability; and the added component of parent-child sessions to improve parent-child interaction. This is a multicenter, multi-informant and multi-method randomized clinical trial study with a 2 by 2 factorial experimental design. Participants (N = 100) are children (4-12 years), and their parents, who have been exposed to interparental violence. The main aim of the study is to test the effects of two parental components as an addition to a trauma focused cognitive behavioral based group therapy for reducing children's symptoms. Primary outcome measures are posttraumatic stress symptoms, and internalizing and externalizing problems in children. The secondary aim of the study is to test the effect of the two added components on adjustment problems in children and to test whether enhanced effects can be explained by changes in children's responses towards experienced violence, in parental availability, and in quality of parent-child interaction. To address this secondary aim, the main parameters are observational and questionnaire measures of parental availability, parent-child relationship variables, children's adjustment problems and children's responses to interparental violence. Data are collected three times: before and after the program and six months later. Both

  19. Nuclear plant components: mechanical analysis and lifetime evaluation

    International Nuclear Information System (INIS)

    Chator, T.

    1993-09-01

    This paper concerns the methodology adopted by the Research and Development Division to handle mechanical problems found in structures and machines. Usually, these often very complex studies (3-D structures, complex loadings, non linear behavior laws) call for advanced tools and calculation means. In order to do these complex studies, R and D Division is developing a software. It handles very complex thermo-mechanical analysis using the Finite Element Method. It enables us to analyse static, dynamic, elasto-plastic problems as well as contact problems or evaluating damage and lifetime of structures. This paper will be illustrated by actual industrial case examples. The major ones will be dealing with: 1. Analysis of a new impeller/shaft assembly of a primary coolant pump. The 3D meshing is submitted simultaneously to thermal load, pressure, hydraulic, centrifugal and axial forces and clamping of studs; contacts between shaft/impeller, nuts bearing side/shaft bearing side. For this study, we have developed a new method to handle the clamping of studs. The stud elongation value is given into the software which automatically computes the distorsions between both the structures in contact and then the final position of bearing areas (using an iterative non-linear algorithm of modified Newton-Raphson type). 2. Analysis of the stress intensity factor of crack. The 3D meshing (representing the crack) is submitted simultaneously to axial and radial forces. In this case, we use the Theta method to calculate the energy restitution rate in order to determine the stress intensity factors. (authors). 7 figs., 1 tab., 3 refs

  20. 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.

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

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  2. Modeling and Analysis of Component Faults and Reliability

    DEFF Research Database (Denmark)

    Le Guilly, Thibaut; Olsen, Petur; Ravn, Anders Peter

    2016-01-01

    This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets that are automati......This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets...... that are automatically generated. The stochastic information on the faults is used to estimate the reliability of the fault affected system. The reliability is given with respect to properties of the system state space. We illustrate the process on a concrete example using the Uppaal model checker for validating...... the ideal system model and the fault modeling. Then the statistical version of the tool, UppaalSMC, is used to find reliability estimates....

  3. Use of cognitive enhancers for mild cognitive impairment: protocol for a systematic review and network meta-analysis

    Directory of Open Access Journals (Sweden)

    Tricco Andrea C

    2012-05-01

    Full Text Available Abstract Background Elderly individuals who have memory problems without significant limitations in activities of daily living are often diagnosed as having mild cognitive impairment (MCI. Some of these individuals progress to dementia. Several cognitive enhancers (for example donepezil, galantamine, rivastigmine, memantine have been approved for use in people with Alzheimer’s dementia but their use in patients with MCI is unclear. We aimed to determine the comparative effectiveness, safety, and cost of cognitive enhancers for MCI through a systematic review and network (that is, indirect comparisons meta-analysis. Design/Methods We will include studies that examine the use of cognitive enhancers compared to placebo, supportive care, or other cognitive enhancers among patients diagnosed with MCI. Outcomes of interest include cognition and function (primary outcomes, as well as behavior, quality of life, safety, and cost (secondary outcomes. We will include all experimental studies (randomized controlled trials, quasi-randomized controlled trials, controlled clinical trials, quasi-experimental studies (controlled before-after, interrupted time series, and observational studies (cohort, case–control. Studies will be included regardless of publication status (that is, we will include unpublished studies, year, or language of dissemination. To identify potentially relevant material, we will search the following electronic databases from inception onwards: MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, CINAHL, and Ageline. The electronic database search will be supplemented by scanning the reference lists of included studies, searching Google and organization websites for unpublished or difficult to locate material literature, and contacting experts. Two reviewers will independently screen the studies for inclusion using the eligibility criteria established a priori and independently extract data. Risk of bias will be assessed

  4. A Content Analysis of General Chemistry Laboratory Manuals for Evidence of Higher-Order Cognitive Tasks

    Science.gov (United States)

    Domin, Daniel S.

    1999-01-01

    The science laboratory instructional environment is ideal for fostering the development of problem-solving, manipulative, and higher-order thinking skills: the skills needed by today's learner to compete in an ever increasing technology-based society. This paper reports the results of a content analysis of ten general chemistry laboratory manuals. Three experiments from each manual were examined for evidence of higher-order cognitive activities. Analysis was based upon the six major cognitive categories of Bloom's Taxonomy of Educational Objectives: knowledge, comprehension, application, analysis, synthesis, and evaluation. The results of this study show that the overwhelming majority of general chemistry laboratory manuals provide tasks that require the use of only the lower-order cognitive skills: knowledge, comprehension, and application. Two of the laboratory manuals were disparate in having activities that utilized higher-order cognition. I describe the instructional strategies used within these manuals to foster higher-order cognitive development.

  5. Qualitative analysis of the Clock Drawing Test by educational level and cognitive profile

    Directory of Open Access Journals (Sweden)

    Aline Teixeira Fabricio

    2014-04-01

    Full Text Available The use of a qualitative scale for the Clock Drawing Test (CDT may add information about the pattern of errors committed. Objective: To translate and adapt the Modified Qualitative Error Analysis of Rouleau into Brazilian Portuguese and to examine the pattern of errors according to educational level and cognitive profile. Method: 180 adults (47-82 years completed the CDT. Participants were stratified into age and educational levels and separated between those with and without changes in cognitive screening tests (Mini-Mental State Examination, Verbal Fluency. Results: No significant differences were found in CDT scores among age groups. Among participants without cognitive impairment, those with lower education often presented graphic difficulties, conceptual deficits and spatial deficits. Participants with cognitive deficits, demonstrated more frequently conceptual and spatial errors. Conclusion: The qualitative analysis of the CDT may contribute to the identification of cognitive changes. Education level has to be taken into consideration during the analysis.

  6. Analysis of problem solving in terms of cognitive style

    Science.gov (United States)

    Anthycamurty, Rr C. C.; Mardiyana; Saputro, D. R. S.

    2018-03-01

    The purpose of this study was to analyze the problem solving based on the type of cognitive style. Subjects used in this study are students of class X SMK located in Purworejo. The method used in this research is qualitative descriptive. Data collection techniques used in this research is a problem-solving test to determine student problem solving and GEFT to determine the type of cognitive style possessed by students. The result of this research is to determine the mastery of each type in cognitive style, that is Field Independent type and Field Dependent type on problem solving indicator. The impact of this research is the teacher can know the mastery of student problem solving on each type of cognitive style so that teacher can determine the proper way of delivering to student at next meeting.

  7. Cognitive Task Analysis for Instruction in Single-Injection Ultrasound Guided-Regional Anesthesia

    Science.gov (United States)

    Gucev, Gligor V.

    2012-01-01

    Cognitive task analysis (CTA) is methodology for eliciting knowledge from subject matter experts. CTA has been used to capture the cognitive processes, decision-making, and judgments that underlie expert behaviors. A review of the literature revealed that CTA has not yet been used to capture the knowledge required to perform ultrasound guided…

  8. Social Cognitive Career Theory, Conscientiousness, and Work Performance: A Meta-Analytic Path Analysis

    Science.gov (United States)

    Brown, Steven D.; Lent, Robert W.; Telander, Kyle; Tramayne, Selena

    2011-01-01

    We performed a meta-analytic path analysis of an abbreviated version of social cognitive career theory's (SCCT) model of work performance (Lent, Brown, & Hackett, 1994). The model we tested included the central cognitive predictors of performance (ability, self-efficacy, performance goals), with the exception of outcome expectations. Results…

  9. Protocol Analysis of Group Problem Solving in Mathematics: A Cognitive-Metacognitive Framework for Assessment.

    Science.gov (United States)

    Artzt, Alice F.; Armour-Thomas, Eleanor

    The roles of cognition and metacognition were examined in the mathematical problem-solving behaviors of students as they worked in small groups. As an outcome, a framework that links the literature of cognitive science and mathematical problem solving was developed for protocol analysis of mathematical problem solving. Within this framework, each…

  10. The cognitive profile of ALS : A systematic review and meta-analysis update

    NARCIS (Netherlands)

    Beeldman, E.; Raaphorst, J.; Klein Twennaar, M.; de Visser, M.; Schmand, B.A.; de Haan, R.J.

    Cognitive impairment is present in approximately 30% of patients with amyotrophic lateral sclerosis (ALS) and, especially when severe, has a negative impact on survival and caregiver burden. Our 2010 meta-analysis of the cognitive profile of ALS showed impairment of fluency, executive function,

  11. The cognitive profile of ALS: a systematic review and meta-analysis update

    NARCIS (Netherlands)

    Beeldman, Emma; Raaphorst, Joost; Klein Twennaar, Michelle; de Visser, Marianne; Schmand, Ben A.; de Haan, Rob J.

    2016-01-01

    Cognitive impairment is present in approximately 30% of patients with amyotrophic lateral sclerosis (ALS) and, especially when severe, has a negative impact on survival and caregiver burden. Our 2010 meta-analysis of the cognitive profile of ALS showed impairment of fluency, executive function,

  12. Thermal Analysis of Fermilab Mu2e Beamstop and Structural Analysis of Beamline Components

    Energy Technology Data Exchange (ETDEWEB)

    Narug, Colin S. [Northern Illinois U.

    2018-01-01

    The Mu2e project at Fermilab National Accelerator Laboratory aims to observe the unique conversion of muons to electrons. The success or failure of the experiment to observe this conversion will further the understanding of the standard model of physics. Using the particle accelerator, protons will be accelerated and sent to the Mu2e experiment, which will separate the muons from the beam. The muons will then be observed to determine their momentum and the particle interactions occur. At the end of the Detector Solenoid, the internal components will need to absorb the remaining particles of the experiment using polymer absorbers. Because the internal structure of the beamline is in a vacuum, the heat transfer mechanisms that can disperse the energy generated by the particle absorption is limited to conduction and radiation. To determine the extent that the absorbers will heat up over one year of operation, a transient thermal finite element analysis has been performed on the Muon Beam Stop. The levels of energy absorption were adjusted to determine the thermal limit for the current design. Structural finite element analysis has also been performed to determine the safety factors of the Axial Coupler, which connect and move segments of the beamline. The safety factor of the trunnion of the Instrument Feed Through Bulk Head has also been determined for when it is supporting the Muon Beam Stop. The results of the analysis further refine the design of the beamline components prior to testing, fabrication, and installation.

  13. Data-Parallel Mesh Connected Components Labeling and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Harrison, Cyrus; Childs, Hank; Gaither, Kelly

    2011-04-10

    We present a data-parallel algorithm for identifying and labeling the connected sub-meshes within a domain-decomposed 3D mesh. The identification task is challenging in a distributed-memory parallel setting because connectivity is transitive and the cells composing each sub-mesh may span many or all processors. Our algorithm employs a multi-stage application of the Union-find algorithm and a spatial partitioning scheme to efficiently merge information across processors and produce a global labeling of connected sub-meshes. Marking each vertex with its corresponding sub-mesh label allows us to isolate mesh features based on topology, enabling new analysis capabilities. We briefly discuss two specific applications of the algorithm and present results from a weak scaling study. We demonstrate the algorithm at concurrency levels up to 2197 cores and analyze meshes containing up to 68 billion cells.

  14. A Bayesian Analysis of Unobserved Component Models Using Ox

    Directory of Open Access Journals (Sweden)

    Charles S. Bos

    2011-05-01

    Full Text Available This article details a Bayesian analysis of the Nile river flow data, using a similar state space model as other articles in this volume. For this data set, Metropolis-Hastings and Gibbs sampling algorithms are implemented in the programming language Ox. These Markov chain Monte Carlo methods only provide output conditioned upon the full data set. For filtered output, conditioning only on past observations, the particle filter is introduced. The sampling methods are flexible, and this advantage is used to extend the model to incorporate a stochastic volatility process. The volatility changes both in the Nile data and also in daily S&P 500 return data are investigated. The posterior density of parameters and states is found to provide information on which elements of the model are easily identifiable, and which elements are estimated with less precision.

  15. Determination of inorganic component in plastics by neutron activation analysis

    International Nuclear Information System (INIS)

    Mateus, Sandra Fonseca; Saiki, Mitiko

    1995-01-01

    In order to identify possible sources of heavy metals in municipal solid waste incinerator ashes, plastic materials originated mainly from household waste were analyzed by using instrumental neutron activation analysis method. Plastic samples and synthetic standards of elements were irradiated at the IEA-R1 nuclear reactor for 8 h under thermal neutron flux of about 10 13 n cm -2 s -1 . After adequate decay time, counting were carried out using a hyperpure Ge detector and the concentrations of the elements As, Ba, Br, Cd, Co, Cr, Fe, Sb, Sc, Se, Sn, Ti and Zn were determined. For some samples, not all these elements were detected. Besides, the range of concentrations determined in similar type and colored samples varied from a few ppb to percentage. In general, colored and opaque plastic samples presented higher concentrations of the elements than those obtained from transparent and milky plastics. Precision of the results was also evaluated. (author). 3 refs., 2 tabs

  16. Component Analysis of Bee Venom from lune to September

    Directory of Open Access Journals (Sweden)

    Ki Rok Kwon

    2007-06-01

    Full Text Available Objectives : The aim of this study was to observe variation of Bee Venom content from the collection period. Methods : Content analysis of Bee Venom was rendered using HPLC method by standard melittin Results : Analyzing melittin content using HPLC, 478.97mg/g at june , 493.89mg/g at july, 468.18mg/g at August and 482.15mg/g was containing in Bee Venom at september. So the change of melittin contents was no significance from June to September. Conclusion : Above these results, we concluded carefully that collecting time was not important factor for the quality control of Bee Venom, restricted the period from June to September.

  17. Plant operator performance evaluation based on cognitive process analysis experiment

    International Nuclear Information System (INIS)

    Ujita, H.; Fukuda, M.

    1990-01-01

    This paper reports on an experiment to clarify plant operators' cognitive processes that has been performed, to improve the man-machine interface which supports their diagnoses and decisions. The cognitive processes under abnormal conditions were evaluated by protocol analyses interviews, etc. in the experiment using a plant training simulator. A cognitive process model is represented by a stochastic network, based on Rasmussen's decision making model. Each node of the network corresponds to an element of the cognitive process, such as observation, interpretation, execution, etc. Some observations were obtained as follows, by comparison of Monte Carlo simulation results with the experiment results: A process to reconfirm the plant parameters after execution of a task and feedback paths from this process to the observation and the task definition of next task were observed. The feedback probability average and standard deviation should be determined for each incident type to explain correctly the individual differences in the cognitive processes. The tendency for the operator's cognitive level to change from skill-based to knowledge-based via rule-based behavior was observed during the feedback process

  18. Competition analysis on the operating system market using principal component analysis

    Directory of Open Access Journals (Sweden)

    Brătucu, G.

    2011-01-01

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

  19. Nonlinear Denoising and Analysis of Neuroimages With Kernel Principal Component Analysis and Pre-Image Estimation

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Abrahamsen, Trine Julie; Madsen, Kristoffer Hougaard

    2012-01-01

    We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising...... procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes. We...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-10-07

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

  1. Progress Towards Improved Analysis of TES X-ray Data Using Principal Component Analysis

    Science.gov (United States)

    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.; hide

    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.

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

    Science.gov (United States)

    E, Jianwei; Bao, Yanling; Ye, Jimin

    2017-10-01

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

  3. Decoding the auditory brain with canonical component analysis.

    Science.gov (United States)

    de Cheveigné, Alain; Wong, Daniel D E; Di Liberto, Giovanni M; Hjortkjær, Jens; Slaney, Malcolm; Lalor, Edmund

    2018-05-15

    The relation between a stimulus and the evoked brain response can shed light on perceptual processes within the brain. Signals derived from this relation can also be harnessed to control external devices for Brain Computer Interface (BCI) applications. While the classic event-related potential (ERP) is appropriate for isolated stimuli, more sophisticated "decoding" strategies are needed to address continuous stimuli such as speech, music or environmental sounds. Here we describe an approach based on Canonical Correlation Analysis (CCA) that finds the optimal transform to apply to both the stimulus and the response to reveal correlations between the two. Compared to prior methods based on forward or backward models for stimulus-response mapping, CCA finds significantly higher correlation scores, thus providing increased sensitivity to relatively small effects, and supports classifier schemes that yield higher classification scores. CCA strips the brain response of variance unrelated to the stimulus, and the stimulus representation of variance that does not affect the response, and thus improves observations of the relation between stimulus and response. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Using principal component analysis for selecting network behavioral anomaly metrics

    Science.gov (United States)

    Gregorio-de Souza, Ian; Berk, Vincent; Barsamian, Alex

    2010-04-01

    This work addresses new approaches to behavioral analysis of networks and hosts for the purposes of security monitoring and anomaly detection. Most commonly used approaches simply implement anomaly detectors for one, or a few, simple metrics and those metrics can exhibit unacceptable false alarm rates. For instance, the anomaly score of network communication is defined as the reciprocal of the likelihood that a given host uses a particular protocol (or destination);this definition may result in an unrealistically high threshold for alerting to avoid being flooded by false positives. We demonstrate that selecting and adapting the metrics and thresholds, on a host-by-host or protocol-by-protocol basis can be done by established multivariate analyses such as PCA. We will show how to determine one or more metrics, for each network host, that records the highest available amount of information regarding the baseline behavior, and shows relevant deviances reliably. We describe the methodology used to pick from a large selection of available metrics, and illustrate a method for comparing the resulting classifiers. Using our approach we are able to reduce the resources required to properly identify misbehaving hosts, protocols, or networks, by dedicating system resources to only those metrics that actually matter in detecting network deviations.

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

    Science.gov (United States)

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

    2016-03-01

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

  6. THE COACH-ATHLETE RELATIONSHIP IN BASKETBALL. ANALYSIS OF THE ANTECEDENTS, COMPONENTS AND OUTCOMES

    Directory of Open Access Journals (Sweden)

    Jos\\u00E9 M. S\\u00E1nchez

    2009-01-01

    Full Text Available The aim of the study was to examine the coach-athlete relationship by analyzing the determinants of the quality of that relationship, the components emerged from previous constraints and the outcomes of the relationship. We accomplished a qualitative study using semistructured in-depth interviews with a total of 4 dyads (2 coaches and 4 players selected deliberately. The data obtained suggested that the coach-athlete relationship in basketball is organized into three layers: a relationship antecedent variables (coach's and athlete's behaviour and values wanted, b components (behaviours, feelings, cognitions, improvement and maintenance strategies, and management of differences and c the consequences or outcomes (the coach and the player. In conclusion, we found that the different antecedents determine the components of the relationship, generating, in the case of positive relationships, satisfaction, wellbeing and performance, representing a personal and professional growth in both members of the dyad.

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

    Science.gov (United States)

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

    2017-01-01

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

  8. Differentiating Motivational from Affective Influence of Performance-contingent Reward on Cognitive Control: The Wanting Component Enhances Both Proactive and Reactive Control.

    Science.gov (United States)

    Chaillou, Anne-Clémence; Giersch, Anne; Hoonakker, Marc; Capa, Rémi L; Bonnefond, Anne

    2017-04-01

    Positive affect strongly modulates goal-directed behaviors and cognitive control mechanisms. It often results from the presence of a pleasant stimulus in the environment, whether that stimulus appears unpredictably or as a consequence of a particular behavior. The influence of positive affect linked to a random pleasant stimulus differs from the influence of positive affect resulting from performance-contingent pleasant stimuli. However, the mechanisms by which the performance contingency of pleasant stimuli modulates the influence of positive affect on cognitive control mechanisms have not been elucidated. Here, we tested the hypothesis that these differentiated effects are the consequence of the activation of the motivational "wanting" component specifically under performance contingency conditions. To that end, we directly compared the effects on cognitive control of pleasant stimuli (a monetary reward) attributed in a performance contingent manner, and of random pleasant stimuli (positive picture) not related to performance, during an AX-CPT task. Both proactive and reactive modes of control were increased specifically by performance contingency, as reflected by faster reaction times and larger amplitude of the CNV and P3a components. Our findings advance our understanding of the respective effects of affect and motivation, which is of special interest regarding alterations of emotion-motivation interaction found in several psychopathological disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. The Protective Effect of Lavender Essential Oil and Its Main Component Linalool against the Cognitive Deficits Induced by D-Galactose and Aluminum Trichloride in Mice

    Directory of Open Access Journals (Sweden)

    Pan Xu

    2017-01-01

    Full Text Available Lavender essential oil (LO is a traditional medicine used for the treatment of Alzheimer’s disease (AD. It was extracted from Lavandula angustifolia Mill. This study was designed to investigate the effects of lavender essential oil (LO and its active component, linalool (LI, against cognitive impairment induced by D-galactose (D-gal and AlCl3 in mice and to explore the related mechanisms. Our results revealed that LO (100 mg/kg or LI (100 mg/kg significantly protected the cognitive impairments as assessed by the Morris water maze test and step-though test. The mechanisms study demonstrated that LO and LI significantly protected the decreased activity of superoxide dismutase (SOD, glutathione peroxidase (GPX, and protected the increased activity of acetylcholinesterase (AChE and content of malondialdehyde (MDA. Besides, they protected the suppressed nuclear factor-erythroid 2-related factor 2 (Nrf2 and heme oxygenase-1 (HO-1 expression significantly. Moreover, the decreased expression of synapse plasticity-related proteins, calcium-calmodulin-dependent protein kinase II (CaMKII, p-CaMKII, brain-derived neurotrophic factor (BDNF, and TrkB in the hippocampus were increased with drug treatment. In conclusion, LO and its active component LI have protected the oxidative stress, activity of cholinergic function and expression of proteins of Nrf2/HO-1 pathway, and synaptic plasticity. It suggest that LO, especially LI, could be a potential agent for improving cognitive impairment in AD.

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

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  11. Analysis Components of the Digital Consumer Behavior in Romania

    Directory of Open Access Journals (Sweden)

    Cristian Bogdan Onete

    2016-08-01

    Full Text Available This article is investigating the Romanian consumer behavior in the context of the evolution of the online shopping. Given that online stores are a profitable business model in the area of electronic commerce and because the relationship between consumer digital Romania and its decision to purchase products or services on the Internet has not been sufficiently explored, this study aims to identify specific features of the new type of consumer and to examine the level of online shopping in Romania. Therefore a documentary study was carried out with statistic data regarding the volume and the number of transactions of the online shopping in Romania during 2010-2014, the type of products and services that Romanians are searching the Internet for and demographics of these people. In addition, to study more closely the online consumer behavior, and to interpret the detailed secondary data provided, an exploratory research was performed as a structured questionnaire with five closed questions on the distribution of individuals according to the gender category they belong (male or female; decision to purchase products / services in the virtual environment in the past year; the source of the goods / services purchased (Romanian or foreign sites; factors that have determined the consumers to buy products from foreign sites; categories of products purchased through online transactions from foreign merchants. The questionnaire was distributed electronically via Facebook social network users and the data collected was processed directly in the Facebook official app to create and interpret responses to surveys. The results of this research correlated with the official data reveals the following characteristics of the digital consumer in Romania: atypical European consumer, interested more in online purchases from abroad, influenced by the quality and price of the purchase. This paper assumed a careful analysis of the online acquisitions phenomenon and also

  12. Analysis of cognitive status in patients with type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Irina V. Gatckikh

    2018-02-01

    Full Text Available Background: Cognitive impairment is a common complication of type 2 diabetes, greatly reduce the quality of life and daily functioning of patients, as well as have an impact on their compliance to therapy. Aim: Explore the nature and frequency of cognitive impairment in patients with type 2 diabetes, their relation to carbohydrate metabolism. Materials and methods: The study involved 113 patients with type 2 diabetes aged 40–70 years, with disease duration of more than 12 months; Control group consisted of 33 persons, stateless persons with type 2 diabetes, matched by age, sex, level of education, the presence of cardiovascular diseases such as hypertension and coronary heart disease. The complex included a survey of clinical and laboratory tests, instrumental, neuropsychological testing. To screen for cognitive impairment used by the Montreal Cognitive Assessment Scale (MоСа test, for the study of the frontal functions FAB (frontal dysfunction battery. Results: The study of cognitive impairment were diagnosed in 53,1 ± 9,2% of patients with type 2 diabetes, which is statistically significantly higher than in those in the control group 15,2 ± 12,2%. In patients with type 2 diabetes prevailed violations fronto-subcortical type with a reduction in short-term memory function, attention and constructive praxis. Cognitive impairment correlated with indices of carbohydrate metabolism (HbA1c, fasting glucose, disease duration 7 [5, 12] years and the patient's. Conclusions: These data confirm the impact of hyperglycemia as a major pathogenic factor and duration of the disease on the formation and progression of cognitive impairment in patients with type 2 diabetes.

  13. Personality and Cognitive Decline in Older Adults: Data From a Longitudinal Sample and Meta-Analysis

    Science.gov (United States)

    Terracciano, Antonio; Stephan, Yannick; Sutin, Angelina R.

    2016-01-01

    Objectives: Personality traits are associated with risk of dementia; less is known about their association with the trajectory of cognitive functioning. This research examines the association between the 5 major dimensions of personality and cognitive function and decline in older adulthood and includes a meta-analysis of published studies. Method: Personality traits, objective and subjective memory, and cognitive status were collected in a large national sample (N = 13,987) with a 4-year follow-up period. For each trait, the meta-analysis pooled results from up to 5 prospective studies to examine personality and change in global cognition. Results: Higher Neuroticism was associated with worse performance on all cognitive measures and greater decline in memory, whereas higher Conscientiousness and Openness were associated with better memory performance concurrently and less decline over time. All traits were associated with subjective memory. Higher Conscientiousness and lower Extraversion were associated with better cognitive status and less decline. Although modest, these associations were generally larger than that of hypertension, diabetes, history of psychological treatment, obesity, smoking, and physical inactivity. The meta-analysis supported the association between Neuroticism and Conscientiousness and cognitive decline. Discussion: Personality is associated with cognitive decline in older adults, with effects comparable to established clinical and lifestyle risk factors. PMID:25583598

  14. Experimental study on the operators' cognitive behavior analysis for the plant anomaly diagnosis

    International Nuclear Information System (INIS)

    Takahashi, Makoto; Kubo, Osamu; Yasuta, Akira

    1996-01-01

    In this paper, a method of human cognitive state estimation based on physiological measures has been applied to the analysis of cognitive behavior during anomaly diagnosis observed with nuclear power plant simulator. This method has also been combined with the conventional experimental protocol such as operational sequence and questionnaire results. The simulator experiments have been performed using plant experts and the results demonstrate that the cognitive state estimation method can be an effective way for understanding cognitive behavior during the anomaly diagnosis of the nuclear power plant. It has also been shown from the results that the combined use of the human cognitive state estimation and the conventional experimental protocol can provide effective information in decreasing the ambiguity of the analysis results. (author)

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

    Science.gov (United States)

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

    2018-02-01

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

  16. The main component of an alarm pheromone of kissing bugs plays multiple roles in the cognitive modulation of the escape response

    Directory of Open Access Journals (Sweden)

    Sebastián eMinoli

    2013-07-01

    Full Text Available Innate responses in animals can be modulated by experience. Disturbed adults of the triatomine bug Triatoma infestans release an alarm pheromone (AP that elicits an escape response in conspecific larvae. The main component of this AP, the isobutyric acid (IsoAc, alone has already shown to generate an escape response in this species. However, not much is known about the modulation of this behavior by non-associative and associative cognitive processes. We present here evidences of the cognitive capacities of T. infestans larvae in an escape context under different conditioning paradigms, including IsoAc in different roles. We show that: 1 the duration of a pre-exposure to IsoAc plays a main role in determining the type of non-associative learning expressed: short time pre-exposures elicit a sensitization while a longer pre-exposure time triggers a switch from repellence to attractiveness; 2 a simple pre-exposure event is enough to modulate the escape response of larvae to the AP and to its main component: IsoAc; 3 IsoAc and the AP are perceived as different chemical entities; 4 an association between IsoAc and an aversive stimulus can be created under a classical conditioning paradigm; 5 an association between IsoAc and a self-action can be generated under an operant conditioning. These results evince that IsoAc can attain multiple and different cognitive roles in the modulation of the escape response of triatomines and show how cognitive processes can modulate a key behavior for surviving, as it is the escaping response in presence of a potential danger in insects.

  17. Outage performance analysis of underlay cognitive RF and FSO wireless channels

    KAUST Repository

    Ansari, Imran Shafique; Abdallah, Mohamed M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2014-01-01

    In this work, the outage performance analysis of a dual-hop transmission system composed of asymmetric radio frequency (RF) channel cascaded with a free-space optical (FSO) link is presented. For the RF link, an underlay cognitive network

  18. A cognitive-pragmatic model for translation-shift analysis in ...

    African Journals Online (AJOL)

    A cognitive-pragmatic model for translation-shift analysis in descriptive case ... This model responds to the tendency of descriptive studies to analyse all translation shifts under the same rubric of neutrality. ... AJOL African Journals Online.

  19. Cognitive behavioural therapy for MS-related fatigue explained: A longitudinal mediation analysis

    NARCIS (Netherlands)

    Akker, L.E. van den; Beckerman, H.; Collette, E.H.; Knoop, H.; Bleijenberg, G.; Twisk, J.W.; Dekker, J.; Groot, V. de

    2018-01-01

    BACKGROUND: Cognitive behavioural therapy (CBT) effectively reduces fatigue directly following treatment in patients with Multiple Sclerosis (MS), but little is known about the process of change during and after CBT. DESIGN: Additional analysis of a randomized clinical trial. OBJECTIVE: To

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

    Science.gov (United States)

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

    2018-07-16

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

  1. Analysis of operators' diagnosis tasks based on cognitive process

    International Nuclear Information System (INIS)

    Zhou Yong; Zhang Li

    2012-01-01

    Diagnosis tasks in nuclear power plants characterized as high-dynamic uncertainties are complex reasoning tasks. Diagnosis errors are the main causes for the error of commission. Firstly, based on mental model theory and perception/action cycle theory, a cognitive model for analyzing operators' diagnosis tasks is proposed. Then, the model is used to investigate a trip event which occurred at crystal river nuclear power plant. The application demonstrates typical cognitive bias and mistakes which operators may make when performing diagnosis tasks. They mainly include the strong confirmation tendency, difficulty to produce complete hypothesis sets, group mindset, non-systematic errors in hypothesis testing, and etc. (authors)

  2. Cognitive task analysis of nuclear power plant operators for man-machine interface design

    International Nuclear Information System (INIS)

    Itoh, J.I.; Yoshimura, S.; Ohtsuka, T.

    1990-01-01

    This paper aims to ascertain and further develop design guidelines for a man-machine interface compatible with plant operators' problem solving strategies. As the framework for this study, operator's information processing activities were modeled, based on J. Rasmussen's framework for cognitive task analysis. Two experiments were carried out. One was an experiment aimed at gaining an understanding of internal mechanisms involved in mistakes and slips which occurred in operators' responses to incidents and accidents. As a result of fifteen cases of operator performance analysis, sixty one human errors were identified. Further analysis of the errors showed that frequently occurring error mechanisms were absent-mindedness, lack of recognition of patterns in diagnosis and failed procedure formulation due to memory lapses. The other kind of experiment was carried out to identify the envelope of trajectories for the operator's search in the problem space consisting of the two dimensions of means-ends and whole-part relations while dealing with transients. Two cases of experimental sessions were conducted with the thinking-aloud method. From analyses based on verbal protocols, trajectories of operator's search were derived, covering from the whole plant level through the component level in the whole-part dimension and covering from the functional purpose level through the physical form level in the means-ends dimension. The findings obtained from these analyses serve as a basis for developing design guidelines for man-machine interfaces in control rooms of nuclear power plants

  3. Automotive Exterior Noise Optimization Using Grey Relational Analysis Coupled with Principal Component Analysis

    Science.gov (United States)

    Chen, Shuming; Wang, Dengfeng; Liu, Bo

    This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

  4. Multiobjective Optimization of ELID Grinding Process Using Grey Relational Analysis Coupled with Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    S. Prabhu

    2014-06-01

    Full Text Available Carbon nanotube (CNT mixed grinding wheel has been used in the electrolytic in-process dressing (ELID grinding process to analyze the surface characteristics of AISI D2 Tool steel material. CNT grinding wheel is having an excellent thermal conductivity and good mechanical property which is used to improve the surface finish of the work piece. The multiobjective optimization of grey relational analysis coupled with principal component analysis has been used to optimize the process parameters of ELID grinding process. Based on the Taguchi design of experiments, an L9 orthogonal array table was chosen for the experiments. The confirmation experiment verifies the proposed that grey-based Taguchi method has the ability to find out the optimal process parameters with multiple quality characteristics of surface roughness and metal removal rate. Analysis of variance (ANOVA has been used to verify and validate the model. Empirical model for the prediction of output parameters has been developed using regression analysis and the results were compared for with and without using CNT grinding wheel in ELID grinding process.

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

    Science.gov (United States)

    Zheng, Juanqing; Yeh, Yichun; Ogai, Harutoshi

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

  6. Enhancing CBT for Chronic Insomnia: A Randomised Clinical Trial of Additive Components of Mindfulness or Cognitive Therapy.

    Science.gov (United States)

    Wong, Mei Yin; Ree, Melissa J; Lee, Christopher W

    2016-09-01

    Although cognitive behavioural therapy (CBT) for insomnia has resulted in significant reductions in symptoms, most patients are not classified as good sleepers after treatment. The present study investigated whether additional sessions of cognitive therapy (CT) or mindfulness-based therapy (MBT) could enhance CBT in 64 participants with primary insomnia. All participants were given four sessions of standard CBT as previous research had identified this number of sessions as an optimal balance between therapist guidance and patient independence. Participants were then allocated to further active treatment (four sessions of CT or MBT) or a no further treatment control. The additional treatments resulted in significant improvements beyond CBT on self-report and objective measures of sleep and were well tolerated as evidenced by no dropouts from either treatment. The effect sizes for each of these additional treatments were large and clinically significant. The mean scores on the primary outcome measure, the Insomnia Severity Index, were 5.74 for CT and 6.69 for MBT, which are within the good-sleeper range. Treatment effects were maintained at follow-up. There were no significant differences between CT and MBT on any outcome measure. These results provide encouraging data on how to enhance CBT for treatment of insomnia. Copyright © 2015 John Wiley & Sons, Ltd. CBT treatments for insomnia can be enhanced using recent developments in cognitive therapy. CBT treatments for insomnia can be enhanced using mindfulness-based treatments. Both cognitive therapy and mindfulness produce additional clinically significant change. Copyright © 2015 John Wiley & Sons, Ltd.

  7. Complex Information Coordination Performance: Differential Changes in Working Memory Contributions Following Training. Cognitive Components of Information Coordination

    Science.gov (United States)

    1993-06-30

    UNIVERSITY DEPARTMENT OF PSYCHOLOGY EDUCATION BUILDING TALLAHASSEE FL 32306 W LAFAYETTE IN 47907 DR NEIL DORANS DR RODNEY COCKING EDUCATIONAL TESTING SERVICE...DR LORRAINE D EYDE PSYCHOLOGY DEPARTMENT US OFFICE OF PERSONNEL MGMT IOWA STATE UNIVERSITY OFFICE OF PERSONNEL RESEARCH AMES IA 50010 AND DEVELOP...judgments were performed under the added cognitive load of the coordination task. Method Subjects A total of eighty subjects were tested , with one

  8. Post-hoc principal component analysis on a largely illiterate elderly population from North-west India to identify important elements of mini-mental state examination

    Directory of Open Access Journals (Sweden)

    Sunil Kumar Raina

    2016-01-01

    Full Text Available Background: Mini-mental state examination (MMSE scale measures cognition using specific elements that can be isolated, defined, and subsequently measured. This study was conducted with the aim to analyze the factorial structure of MMSE in a largely, illiterate, elderly population in India and to reduce the number of variables to a few meaningful and interpretable combinations. Methodology: Principal component analysis (PCA was performed post-hoc on the data generated by a research project conducted to estimate the prevalence of dementia in four geographically defined habitations in Himachal Pradesh state of India. Results: Questions on orientation and registration account for high percentage of cumulative variance in comparison to other questions. Discussion: The PCA conducted on the data derived from a largely, illiterate population reveals that the most important components to consider for the estimation of cognitive impairment in illiterate Indian population are temporal orientation, spatial orientation, and immediate memory.

  9. Post-hoc principal component analysis on a largely illiterate elderly population from North-west India to identify important elements of mini-mental state examination.

    Science.gov (United States)

    Raina, Sunil Kumar; Chander, Vishav; Raina, Sujeet; Grover, Ashoo

    2016-01-01

    Mini-mental state examination (MMSE) scale measures cognition using specific elements that can be isolated, defined, and subsequently measured. This study was conducted with the aim to analyze the factorial structure of MMSE in a largely, illiterate, elderly population in India and to reduce the number of variables to a few meaningful and interpretable combinations. Principal component analysis (PCA) was performed post-hoc on the data generated by a research project conducted to estimate the prevalence of dementia in four geographically defined habitations in Himachal Pradesh state of India. Questions on orientation and registration account for high percentage of cumulative variance in comparison to other questions. The PCA conducted on the data derived from a largely, illiterate population reveals that the most important components to consider for the estimation of cognitive impairment in illiterate Indian population are temporal orientation, spatial orientation, and immediate memory.

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

    Directory of Open Access Journals (Sweden)

    S. Mahmoudishadi

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  12. Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

    Science.gov (United States)

    Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

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

    NARCIS (Netherlands)

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

    2003-01-01

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

  14. A Note on McDonald's Generalization of Principal Components Analysis

    Science.gov (United States)

    Shine, Lester C., II

    1972-01-01

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

  15. Understanding Oral Reading Fluency among Adults with Low Literacy: Dominance Analysis of Contributing Component Skills

    Science.gov (United States)

    Mellard, Daryl F.; Anthony, Jason L.; Woods, Kari L.

    2012-01-01

    This study extends the literature on the component skills involved in oral reading fluency. Dominance analysis was applied to assess the relative importance of seven reading-related component skills in the prediction of the oral reading fluency of 272 adult literacy learners. The best predictors of oral reading fluency when text difficulty was…

  16. Combined approach based on principal component analysis and canonical discriminant analysis for investigating hyperspectral plant response

    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

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

    Science.gov (United States)

    Rajagopal, K. R.

    1992-01-01

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

  18. Using team cognitive work analysis to reveal healthcare team interactions in a birthing unit.

    Science.gov (United States)

    Ashoori, Maryam; Burns, Catherine M; d'Entremont, Barbara; Momtahan, Kathryn

    2014-01-01

    Cognitive work analysis (CWA) as an analytical approach for examining complex sociotechnical systems has shown success in modelling the work of single operators. The CWA approach incorporates social and team interactions, but a more explicit analysis of team aspects can reveal more information for systems design. In this paper, Team CWA is explored to understand teamwork within a birthing unit at a hospital. Team CWA models are derived from theories and models of teamwork and leverage the existing CWA approaches to analyse team interactions. Team CWA is explained and contrasted with prior approaches to CWA. Team CWA does not replace CWA, but supplements traditional CWA to more easily reveal team information. As a result, Team CWA may be a useful approach to enhance CWA in complex environments where effective teamwork is required. This paper looks at ways of analysing cognitive work in healthcare teams. Team Cognitive Work Analysis, when used to supplement traditional Cognitive Work Analysis, revealed more team information than traditional Cognitive Work Analysis. Team Cognitive Work Analysis should be considered when studying teams.

  19. Using team cognitive work analysis to reveal healthcare team interactions in a birthing unit

    Science.gov (United States)

    Ashoori, Maryam; Burns, Catherine M.; d'Entremont, Barbara; Momtahan, Kathryn

    2014-01-01

    Cognitive work analysis (CWA) as an analytical approach for examining complex sociotechnical systems has shown success in modelling the work of single operators. The CWA approach incorporates social and team interactions, but a more explicit analysis of team aspects can reveal more information for systems design. In this paper, Team CWA is explored to understand teamwork within a birthing unit at a hospital. Team CWA models are derived from theories and models of teamworkand leverage the existing CWA approaches to analyse team interactions. Team CWA is explained and contrasted with prior approaches to CWA. Team CWA does not replace CWA, but supplements traditional CWA to more easily reveal team information. As a result, Team CWA may be a useful approach to enhance CWA in complex environments where effective teamwork is required. Practitioner Summary: This paper looks at ways of analysing cognitive work in healthcare teams. Team Cognitive Work Analysis, when used to supplement traditional Cognitive Work Analysis, revealed more team information than traditional Cognitive Work Analysis. Team Cognitive Work Analysis should be considered when studying teams PMID:24837514

  20. Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

    Science.gov (United States)

    Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

    2012-01-01

    Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

  1. Simulation and Formal Analysis of Visual Attention in Cognitive Systems

    NARCIS (Netherlands)

    Bosse, T.; Maanen, P.P. van; Treur, J.

    2007-01-01

    In this paper a simulation model for visual attention is discussed and formally analysed. The model is part of the design of a cognitive system which comprises an agent that supports a naval officer in its task to compile a tactical picture of the situation in the field. A case study is described in

  2. Cognitive Analysis of Educational Games: The Number Game

    NARCIS (Netherlands)

    Van der Maas, Han; Nyamsuren, Enkhbold

    2018-01-01

    We analyze the cognitive strategies underlying performance in the Number task, a Math game that requires both arithmetic fluency and mathematical creativity. In this game all elements in a set of numbers (for instance, 2, 5, 9) have to be used precisely once to create a target number (for

  3. Cognitive Analysis of Educational Games : The Number Game

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Nyamsuren, E.

    We analyze the cognitive strategies underlying performance in the Number task, a Math game that requires both arithmetic fluency and mathematical creativity. In this game all elements in a set of numbers (for instance, 2, 5, 9) have to be used precisely once to create a target number (for instance,

  4. Formal Analysis of Cognitive Agent Behavior: formal theoretical basis

    NARCIS (Netherlands)

    Sharpanskykh, A.; Treur, J.

    2006-01-01

    In cognitive systems the behavior of an actor (an agent) can be considered from both an external and an internal perspective. This paper contributes an automated procedure for translating a given external behavioral specification into an executable specification of internal dynamics, by which the

  5. Exploring EFL Teachers’ Cognitive Models Through Metaphor Analysis

    Directory of Open Access Journals (Sweden)

    Hui Xiong

    2015-10-01

    Full Text Available This study aims to investigate how a group of Chinese university teachers developed their cognitive models by using “English as a Foreign Language (EFL teachers” metaphors. The research method includes an open-ended questionnaire, a checklist questionnaire, and verbal reports. The goal for this research is twofold. First, we will present those metaphors we believe to be the most frequently used or most central in shaping the thoughts or ideas they have had for EFL teaching and learning. Second, we will provide a description of their internal process of developing cognitive models, as well as factors that could account for such models. The findings showed that (a most of us had three ways of understanding EFL teachers in terms of the educational journey metaphor, the educational building metaphor, and the educational conduit metaphor; (b we used such a cluster of converging cognitive models as the instructor model, the transmitter model, and the builder model to construct definitions for EFL teachers, with the instructor model as a central model; and (c metaphor can actually serve as a useful, effective, and analytic tool for making us aware of the cognitive model underlying our conceptual framework.

  6. Cost analysis of small hydroelectric power plants components and preliminary estimation of global cost

    International Nuclear Information System (INIS)

    Basta, C.; Olive, W.J.; Antunes, J.S.

    1990-01-01

    An analysis of cost for each components of Small Hydroelectric Power Plant, taking into account the real costs of these projects is shown. It also presents a global equation which allows a preliminary estimation of cost for each construction. (author)

  7. Assessment of oil weathering by gas chromatography-mass spectrometry, time warping and principal component analysis

    DEFF Research Database (Denmark)

    Malmquist, Linus M.V.; Olsen, Rasmus R.; Hansen, Asger B.

    2007-01-01

    weathering state and to distinguish between various weathering processes is investigated and discussed. The method is based on comprehensive and objective chromatographic data processing followed by principal component analysis (PCA) of concatenated sections of gas chromatography–mass spectrometry...

  8. Northeast Puerto Rico and Culebra Island Principle Component Analysis - NOAA TIFF Image

    Data.gov (United States)

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

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

    International Nuclear Information System (INIS)

    Jesse, Stephen; Kalinin, Sergei V

    2009-01-01

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

  10. Towards automatic analysis of dynamic radionuclide studies using principal-components factor analysis

    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)

  11. Using the Cluster Analysis and the Principal Component Analysis in Evaluating the Quality of a Destination

    Directory of Open Access Journals (Sweden)

    Ida Vajčnerová

    2016-01-01

    Full Text Available The objective of the paper is to explore possibilities of evaluating the quality of a tourist destination by means of the principal components analysis (PCA and the cluster analysis. In the paper both types of analysis are compared on the basis of the results they provide. The aim is to identify advantage and limits of both methods and provide methodological suggestion for their further use in the tourism research. The analyses is based on the primary data from the customers’ satisfaction survey with the key quality factors of a destination. As output of the two statistical methods is creation of groups or cluster of quality factors that are similar in terms of respondents’ evaluations, in order to facilitate the evaluation of the quality of tourist destinations. Results shows the possibility to use both tested methods. The paper is elaborated in the frame of wider research project aimed to develop a methodology for the quality evaluation of tourist destinations, especially in the context of customer satisfaction and loyalty.

  12. Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

    Science.gov (United States)

    Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

    2014-01-01

    The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

  13. Cognitive and Behavioral Skills Exercises Completed by Patients with Major Depression During Smartphone Cognitive Behavioral Therapy: Secondary Analysis of a Randomized Controlled Trial

    Science.gov (United States)

    Horikoshi, Masaru; Fujita, Hirokazu; Tsujino, Naohisa; Jinnin, Ran; Kako, Yuki; Ogawa, Sei; Sato, Hirotoshi; Kitagawa, Nobuki; Shinagawa, Yoshihiro; Ikeda, Yoshio; Imai, Hissei; Tajika, Aran; Ogawa, Yusuke; Akechi, Tatsuo; Yamada, Mitsuhiko; Shimodera, Shinji; Watanabe, Norio; Inagaki, Masatoshi; Hasegawa, Akio

    2018-01-01

    Background A strong and growing body of evidence has demonstrated the effectiveness of cognitive behavioral therapy (CBT), either face-to-face, in person, or as self-help via the Internet, for depression. However, CBT is a complex intervention consisting of several putatively effective components, and how each component may or may not contribute to the overall effectiveness of CBT is poorly understood. Objective The aim of this study was to investigate how the users of smartphone CBT use and benefit from various components of the program. Methods This is a secondary analysis from a 9-week, single-blind, randomized controlled trial that has demonstrated the effectiveness of adjunctive use of smartphone CBT (Kokoro-App) over antidepressant pharmacotherapy alone among patients with drug-resistant major depressive disorder (total n=164, standardized mean difference in depression severity at week 9=0.40, J Med Internet Res). Kokoro-App consists of three cognitive behavioral skills of self-monitoring, behavioral activation, and cognitive restructuring, with corresponding worksheets to fill in. All activities of the participants learning each session of the program and completing each worksheet were uploaded onto Kokoro-Web, which each patient could use for self-check. We examined what use characteristics differentiated the more successful users of the CBT app from the less successful ones, split at the median of change in depression severity. Results A total of 81 patients with major depression were allocated to the smartphone CBT. On average, they completed 7.0 (standard deviation [SD] 1.4) out of 8 sessions of the program; it took them 10.8 (SD 4.2) days to complete one session, during which they spent 62 min (SD 96) on the app. There were no statistically significant differences in the number of sessions completed, time spent for the program, or the number of completed self-monitoring worksheets between the beneficiaries and the nonbeneficiaries. However, the former

  14. Cognitive and Behavioral Skills Exercises Completed by Patients with Major Depression During Smartphone Cognitive Behavioral Therapy: Secondary Analysis of a Randomized Controlled Trial.

    Science.gov (United States)

    Furukawa, Toshi A; Horikoshi, Masaru; Fujita, Hirokazu; Tsujino, Naohisa; Jinnin, Ran; Kako, Yuki; Ogawa, Sei; Sato, Hirotoshi; Kitagawa, Nobuki; Shinagawa, Yoshihiro; Ikeda, Yoshio; Imai, Hissei; Tajika, Aran; Ogawa, Yusuke; Akechi, Tatsuo; Yamada, Mitsuhiko; Shimodera, Shinji; Watanabe, Norio; Inagaki, Masatoshi; Hasegawa, Akio

    2018-01-11

    A strong and growing body of evidence has demonstrated the effectiveness of cognitive behavioral therapy (CBT), either face-to-face, in person, or as self-help via the Internet, for depression. However, CBT is a complex intervention consisting of several putatively effective components, and how each component may or may not contribute to the overall effectiveness of CBT is poorly understood. The aim of this study was to investigate how the users of smartphone CBT use and benefit from various components of the program. This is a secondary analysis from a 9-week, single-blind, randomized controlled trial that has demonstrated the effectiveness of adjunctive use of smartphone CBT (Kokoro-App) over antidepressant pharmacotherapy alone among patients with drug-resistant major depressive disorder (total n=164, standardized mean difference in depression severity at week 9=0.40, J Med Internet Res). Kokoro-App consists of three cognitive behavioral skills of self-monitoring, behavioral activation, and cognitive restructuring, with corresponding worksheets to fill in. All activities of the participants learning each session of the program and completing each worksheet were uploaded onto Kokoro-Web, which each patient could use for self-check. We examined what use characteristics differentiated the more successful users of the CBT app from the less successful ones, split at the median of change in depression severity. A total of 81 patients with major depression were allocated to the smartphone CBT. On average, they completed 7.0 (standard deviation [SD] 1.4) out of 8 sessions of the program; it took them 10.8 (SD 4.2) days to complete one session, during which they spent 62 min (SD 96) on the app. There were no statistically significant differences in the number of sessions completed, time spent for the program, or the number of completed self-monitoring worksheets between the beneficiaries and the nonbeneficiaries. However, the former completed more behavioral activation

  15. Power Transformer Differential Protection Based on Neural Network Principal Component Analysis, Harmonic Restraint and Park's Plots

    OpenAIRE

    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...

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

    International Nuclear Information System (INIS)

    Castro Silva, Luiz Euripedes Massiere de

    1995-01-01

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

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

    OpenAIRE

    Geroukis, Asterios; Brorson, Erik

    2014-01-01

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

  18. Root cause analysis in support of reliability enhancement of engineering components

    International Nuclear Information System (INIS)

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

    2014-01-01

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

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

    CERN Document Server

    Nguyen, Cam

    2014-01-01

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

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

    International Nuclear Information System (INIS)

    Bao Shiyi; Zhou Yu; He Shuyan; Wu Honglin

    2005-01-01

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

  1. The efficacy of cognitive behavioral therapy for Chinese people: A meta-analysis.

    Science.gov (United States)

    Ng, Ting Kin; Wong, Daniel Fu Keung

    2018-07-01

    Over the past decade, cognitive behavioral therapy has been applied to an increasingly wider range of disorders and problems in Chinese societies. However, no meta-analysis has been conducted to synthesize the studies on cognitive behavioral therapy for Chinese clients. The purpose of this meta-analytic study was to examine the overall efficacy of cognitive behavioral therapy for Chinese people. A literature search was conducted using electronic databases, including Web of Science, PsycINFO and PubMed. Pooled mean effect sizes were calculated using the random-effects model. The literature search identified 55 studies with 6763 Chinese participants. The overall short-term effect of cognitive behavioral therapy on the primary outcome was medium in size. Effect sizes were medium for anxiety, depression/well-being and caregiving stress and small for psychotic symptoms and addictive behaviors. The effects of cognitive behavioral therapy on process variables, dysfunctional thoughts and coping, were in the small range. The overall longer-term effect of cognitive behavioral therapy on the primary outcome was medium in size. Moderator analyses showed that the short-term effect was stronger for culturally adapted cognitive behavioral therapy than for unadapted cognitive behavioral therapy. Type of primary outcome, type of control group, recruitment method, study design, the format of delivery and region were found to moderate the efficacy of cognitive behavioral therapy. The findings of this study provide evidence for the overall efficacy of cognitive behavioral therapy for Chinese people and the benefit of cultural adaptation of cognitive behavioral therapy to Chinese culture.

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

    Directory of Open Access Journals (Sweden)

    Glogovac Svetlana

    2012-01-01

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

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

    International Nuclear Information System (INIS)

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

    1987-01-01

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

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Liying Wang

    2017-01-01

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

  6. Failure trend analysis for safety related components of Korean standard NPPs

    International Nuclear Information System (INIS)

    Choi, Sun Yeong; Han, Sang Hoon

    2005-01-01

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

  7. Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

    Science.gov (United States)

    Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

    2017-02-01

    Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  8. A prospectus for ethical analysis of ageing individuals' responsibility to prevent cognitive decline.

    Science.gov (United States)

    Forlini, Cynthia; Hall, Wayne

    2017-11-01

    As the world's population ages, governments and non-governmental organizations in developed countries are promoting healthy cognitive ageing to reduce the rate of age-related cognitive decline and sustain economic productivity in an ageing workforce. Recommendations from the Productivity Commission (Australia), Dementia Australia, Government Office for Science (UK), Presidential Commission for the Study of Bioethical Issues (USA), Institute of Medicine (USA), among others, are encouraging older adults to engage in mental, physical, and social activities. These lifestyle recommendations for healthy cognitive ageing are timely and well supported by scientific evidence but they make implicit normative judgments about the responsibility of ageing individuals to prevent cognitive decline. Ethical tensions arise when this individual responsibility collides with social and personal realities of ageing populations. First, we contextualize the priority given to healthy cognitive ageing within the current brain-based medical and social discourses. Second, we explore the individual responsibility by examining the economic considerations, medical evidence and individual interests that relate to the priority given to healthy cognitive ageing. Third, we identify three key ethical challenges for policymakers seeking to implement lifestyle recommendations as an effective population-level approach to healthy cognitive ageing. The result is a prospectus for future in-depth analysis of ethical tensions that arise from current policy discussions of healthy cognitive ageing. © 2017 John Wiley & Sons Ltd.

  9. Social Activity and Cognitive Functioning Over Time: A Coordinated Analysis of Four Longitudinal Studies

    Directory of Open Access Journals (Sweden)

    Cassandra L. Brown

    2012-01-01

    Full Text Available Social activity is typically viewed as part of an engaged lifestyle that may help mitigate the deleterious effects of advanced age on cognitive function. As such, social activity has been examined in relation to cognitive abilities later in life. However, longitudinal evidence for this hypothesis thus far remains inconclusive. The current study sought to clarify the relationship between social activity and cognitive function over time using a coordinated data analysis approach across four longitudinal studies. A series of multilevel growth models with social activity included as a covariate is presented. Four domains of cognitive function were assessed: reasoning, memory, fluency, and semantic knowledge. Results suggest that baseline social activity is related to some, but not all, cognitive functions. Baseline social activity levels failed to predict rate of decline in most cognitive abilities. Changes in social activity were not consistently associated with cognitive functioning. Our findings do not provide consistent evidence that changes in social activity correspond to immediate benefits in cognitive functioning, except perhaps for verbal fluency.

  10. 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.

  11. [Effects of a 'theory of mind' cognitive development pilot programme in three children with autism: emotional component].

    Science.gov (United States)

    Villanueva-Bonilla, Cristian; Bonilla-Santos, Jasmín; Arana-Guzmán, Fernanda; Ninco-Cuenca, Ingrid; Quintero-Lozano, Andrea

    2016-03-16

    Theory of mind is defined as the capacity to predict, understand and act when faced with other people's behaviour, their knowledge, their intentions, their emotions and their beliefs. It is proposed as a feasible alternative for establishing a programme adapted to the characteristics of children diagnosed with autism spectrum disorder. The effect of a 'theory of mind' cognitive development pilot programme on the emotional skills of three children with autism spectrum disorder is reported. Case 1: 9-year-old boy, with scarce emotional identification and expression, as well as difficulties to hold fluent and coherent conversations. Case 2: 10-year-old boy, with mechanical, not very fluent language, and difficulties to start and maintain a conversation. Case 3: 8-year-old girl who presents deficits in the non-verbal communicative behaviours used in social interaction and difficulties to adapt to situations other than everyday ones. In the three cases there is an improvement in the emotional capacities following implementation of the programme; moreover, their parents, teachers or therapists perceived positive changes in the children's adaptive skills. The methodological and structural aspects of the cognitive development programme were well-suited to the children with autism who took part in the research study. Due to the preliminary nature of this study, it is suggested that future research should utilise a larger sample and a double-blind design with randomised case-controls that allow the findings to be generalised.

  12. The cognitive organization of music knowledge: a clinical analysis.

    Science.gov (United States)

    Omar, Rohani; Hailstone, Julia C; Warren, Jane E; Crutch, Sebastian J; Warren, Jason D

    2010-04-01

    Despite much recent interest in the clinical neuroscience of music processing, the cognitive organization of music as a domain of non-verbal knowledge has been little studied. Here we addressed this issue systematically in two expert musicians with clinical diagnoses of semantic dementia and Alzheimer's disease, in comparison with a control group of healthy expert musicians. In a series of neuropsychological experiments, we investigated associative knowledge of musical compositions (musical objects), musical emotions, musical instruments (musical sources) and music notation (musical symbols). These aspects of music knowledge were assessed in relation to musical perceptual abilities and extra-musical neuropsychological functions. The patient with semantic dementia showed relatively preserved recognition of musical compositions and musical symbols despite severely impaired recognition of musical emotions and musical instruments from sound. In contrast, the patient with Alzheimer's disease showed impaired recognition of compositions, with somewhat better recognition of composer and musical era, and impaired comprehension of musical symbols, but normal recognition of musical emotions and musical instruments from sound. The findings suggest that music knowledge is fractionated, and superordinate musical knowledge is relatively more robust than knowledge of particular music. We propose that music constitutes a distinct domain of non-verbal knowledge but shares certain cognitive organizational features with other brain knowledge systems. Within the domain of music knowledge, dissociable cognitive mechanisms process knowledge derived from physical sources and the knowledge of abstract musical entities.

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

    Science.gov (United States)

    Singh, S; Gupta, R

    2012-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Han-Jui Lee

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

  15. Performance assessment of air quality monitoring networks using principal component analysis and cluster analysis

    International Nuclear Information System (INIS)

    Lu, Wei-Zhen; He, Hong-Di; Dong, Li-yun

    2011-01-01

    This study aims to evaluate the performance of two statistical methods, principal component analysis and cluster analysis, for the management of air quality monitoring network of Hong Kong and the reduction of associated expenses. The specific objectives include: (i) to identify city areas with similar air pollution behavior; and (ii) to locate emission sources. The statistical methods were applied to the mass concentrations of sulphur dioxide (SO 2 ), respirable suspended particulates (RSP) and nitrogen dioxide (NO 2 ), collected in monitoring network of Hong Kong from January 2001 to December 2007. The results demonstrate that, for each pollutant, the monitoring stations are grouped into different classes based on their air pollution behaviors. The monitoring stations located in nearby area are characterized by the same specific air pollution characteristics and suggested with an effective management of air quality monitoring system. The redundant equipments should be transferred to other monitoring stations for allowing further enlargement of the monitored area. Additionally, the existence of different air pollution behaviors in the monitoring network is explained by the variability of wind directions across the region. The results imply that the air quality problem in Hong Kong is not only a local problem mainly from street-level pollutions, but also a region problem from the Pearl River Delta region. (author)

  16. Analysis of cognitive disorders in older people with diabetes – preliminary study

    Directory of Open Access Journals (Sweden)

    Aneta Kozieł

    2016-04-01

    Full Text Available Introduction : Diabetes is a growing public health problem. Epidemiological studies indicate that the disease shortens life and significantly deteriorates its quality. The impact of diabetes on physical health of patients is well documented, but its impact on cognitive abilities has not been studied in detail so far. The deficit of reports regarding this problem among Polish researchers was an inspiration to start new studies. Aim of the research: To evaluate mild cognitive disorders in elderly patients with diabetes. Material and methods: The study was conducted in 2015. The study group included 7 elderly people with type 2 diabetes for more than 10 years. The control group consisted of 7 individuals of the same age without diabetes. The research tool was a self-made questionnaire to examine the cognitive abilities. An analysis of cognitive functions such as short-term memory, performing analysis and synthesis processes, understanding and creating metaphorical examples, narration and performing metalinguistic operations was performed. Results : Differences in cognitive functioning in the field of the studied variables were observed between examined groups. Elderly people with diabetes achieved significantly lower scores in all examined cognitive functions than healthy respondents. Conclusions : Elderly patients with type 2 diabetes are particularly susceptible to mild cognitive impairment. It is necessary to take this group of patients under diagnosis and early secondary prevention in order to prevent the negative impact of the disease.

  17. Adult Empathy: Possible Gender Differences in Gene-Environment Architecture for Cognitive and Emotional Components in a Large Italian Twin Sample.

    Science.gov (United States)

    Toccaceli, Virgilia; Fagnani, Corrado; Eisenberg, Nancy; Alessandri, Guido; Vitale, Augusto; Stazi, Maria Antonietta

    2018-04-15

    Empathy plays a central role in prosocial behavior and human cooperation. Very few twin researchers have investigated innate and environmental effects in adult empathy, and twin research on gender differences in these effects is sparse. The goal of this study was to examine innate and environmental influences on three components of an empathy scale frequently used with adults - the expression of cognitive (CE), emotional (EE), and social skills (SS) empathy - and to explore gender differences in the influences. Study participants were ~1,700 twins (18-65 years) enrolled in the Italian Twin Registry. Empathy was assessed with the Italian version of the Empathy Quotient (EQ), for which the three-factor structure (i.e., CE, EE, and SS) was confirmed. Twin correlations in monozygotic and dizygotic pairs, and males and females were estimated for the total EQ and subscale scores, and univariate genetic model fitting was carried out. Women's empathy (i.e., total EQ as well as CE and EE subdimensions) was predominantly driven by genetic factors and individual experiences, whereas for males, no genetic contribution or important shared and individual environmental effects emerged. Although of large magnitude, the gender differences did not reach statistical significance. Age did not moderate empathy heritability in adulthood. Only for the SS subscale were genetic and environmental proportions of variance similar for men and women. This study suggests possible gender-specific innate and environmental influences on empathy and its cognitive and emotional components that need to be confirmed in future studies.

  18. Clinical usefulness of the clock drawing test applying rasch analysis in predicting of cognitive impairment.

    Science.gov (United States)

    Yoo, Doo Han; Lee, Jae Shin

    2016-07-01

    [Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.

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

    International Nuclear Information System (INIS)

    Veeramany, Arun; Pandey, Mahesh D.

    2011-01-01

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

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

    Science.gov (United States)

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

    2017-09-11

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