Recognising Workplace Learning: The Emerging Practices of e-RPL and e-PR

ERIC Educational Resources Information Center

Cameron, Roslyn

2012-01-01

Purpose: The use of e-portfolios in recognition of prior learning (RPL) processes in workplace and professional practice contexts has attracted little attention in the literature due to its emergent nature. This study seeks to explore the growing incidence of e-portfolio-based RPL (e-RPL) and professional recognition (e-PR) processes in Australia…

C-Terminal Helical Domains of Dengue Virus Type 4 E Protein Affect the Expression/Stability of prM Protein and Conformation of prM and E Proteins

PubMed Central

Tsai, Wen-Yang; Hsieh, Szu-Chia; Lai, Chih-Yun; Lin, Hong-En; Nerurkar, Vivek R.; Wang, Wei-Kung

2012-01-01

Background The envelope (E) protein of dengue virus (DENV) is the major immunogen for dengue vaccine development. At the C-terminus are two α-helices (EH1 and EH2) and two transmembrane domains (ET1 and ET2). After synthesis, E protein forms a heterodimer with the precursor membrane (prM) protein, which has been shown as a chaperone for E protein and could prevent premature fusion of E protein during maturation. Recent reports of enhancement of DENV infectivity by anti-prM monoclonal antibodies (mAbs) suggest the presence of prM protein in dengue vaccine is potentially harmful. A better understanding of prM-E interaction and its effect on recognition of E and prM proteins by different antibodies would provide important information for future design of safe and effective subunit dengue vaccines. Methodology/Principal Findings In this study, we examined a series of C-terminal truncation constructs of DENV4 prME, E and prM. In the absence of E protein, prM protein expressed poorly. In the presence of E protein, the expression of prM protein increased in a dose-dependent manner. Radioimmunoprecipitation, sucrose gradient sedimentation and pulse-chase experiments revealed ET1 and EH2 were involved in prM-E interaction and EH2 in maintaining the stability of prM protein. Dot blot assay revealed E protein affected the recognition of prM protein by an anti-prM mAb; truncation of EH2 or EH1 affected the recognition of E protein by several anti-E mAbs, which was further verified by capture ELISA. The E protein ectodomain alone can be recognized well by all anti-E mAbs tested. Conclusions/Significance A C-terminal domain (EH2) of DENV E protein can affect the expression and stability of its chaperone prM protein. These findings not only add to our understanding of the interaction between prM and E proteins, but also suggest the ectodomain of E protein alone could be a potential subunit immunogen without inducing anti-prM response. PMID:23300717

Bayesian multi-task learning for decoding multi-subject neuroimaging data.

PubMed

Marquand, Andre F; Brammer, Michael; Williams, Steven C R; Doyle, Orla M

2014-05-15

Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In contrast to alternative (mass-univariate) encoding approaches that use hierarchical models to capture inter-subject variability, inter-subject differences are not typically handled efficiently in PR. In this work, we propose to overcome this problem by recasting the decoding problem in a multi-task learning (MTL) framework. In MTL, a single PR model is used to learn different but related "tasks" simultaneously. The primary advantage of MTL is that it makes more efficient use of the data available and leads to more accurate models by making use of the relationships between tasks. In this work, we construct MTL models where each subject is modelled by a separate task. We use a flexible covariance structure to model the relationships between tasks and induce coupling between them using Gaussian process priors. We present an MTL method for classification problems and demonstrate a novel mapping method suitable for PR models. We apply these MTL approaches to classifying many different contrasts in a publicly available fMRI dataset and show that the proposed MTL methods produce higher decoding accuracy and more consistent discriminative activity patterns than currently used techniques. Our results demonstrate that MTL provides a promising method for multi-subject decoding studies by focusing on the commonalities between a group of subjects rather than the idiosyncratic properties of different subjects. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Hyperkalemia masked by pseudo-stemi infarct pattern and cardiac arrest.

PubMed

Peerbhai, Shareez; Masha, Luke; DaSilva-DeAbreu, Adrian; Dhoble, Abhijeet

2017-12-01

Hyperkalemia is a common electrolyte abnormality and has well-recognized early electrocardiographic manifestations including PR prolongation and symmetric T wave peaking. With severe increase in serum potassium, dysrhythmias and atrioventricular and bundle branch blocks can be seen on electrocardiogram. Although cardiac arrest is a worrisome consequence of untreated hyperkalemia, rarely does hyperkalemia electrocardiographically manifest as acute ischemia. We present a case of acute renal failure complicated by malignant hyperkalemia and eventual ventricular fibrillation cardiac arrest. Recognition of this disorder was delayed secondary to an initial ECG pattern suggesting an acute ST segment elevation myocardial infarction (STEMI). Emergent coronary angiography performed showed no evidence of coronary artery disease. Pseudo-STEMI patterns are rarely seen in association with acute hyperkalemia and are most commonly described with patient without acute cardiac symptomatology. This is the first such case presenting concurrently with cardiac arrest. A brief review of this rare pseudo-infarct pattern is also given.

Identifying the Tuskegee Syphilis Study: implications of results from recall and recognition questions

PubMed Central

2009-01-01

Background This analysis assessed whether Blacks, Whites and Puerto-Rican (PR) Hispanics differed in their ability to identify the Tuskegee Syphilis Study (TSS) via open-ended questions following lead-in recognition and recall questions. Methods The Tuskegee Legacy Project (TLP) Questionnaire was administered via a Random-Digit Dial (RDD) telephone survey to a stratified random sample of Black, White and PR Hispanic adults in three U.S. cities. Results The TLP Questionnaire was administered to 1,162 adults (356 African-Americans, 313 PR Hispanics, and 493 non-Hispanic Whites) in San Juan, PR, Baltimore, MD and New York City, NY. Recall question data revealed: 1) that 89% or more of Blacks, Whites, and PR Hispanics were not able to name or definitely identify the Tuskegee Syphilis Study by giving study attributes; and, 2) that Blacks were the most likely to provide an open-ended answer that identified the Tuskegee Syphilis Study as compared to Whites and PR Hispanics (11.5% vs 6.3% vs 2.9%, respectively) (p ≤ 0.002). Even when probed by a recognition question, only a minority of each racial/ethnic group (37.1%, 26.9%, and 8.6%, for Blacks, Whites and PR Hispanics, respectively) was able to clearly identify the TSS (p < 0.001). Conclusions The two major implications of these findings for health disparity researchers are 1) that it is unlikely that detailed knowledge of the Tuskegee Syphilis Study has any current widespread influence on the willingness of minorities to participate in biomedical research, and 2) that caution should be applied before assuming that what community leaders 'know and are aware of' is equally 'well known' within their community constituencies. PMID:20015361

Identifying the Tuskegee Syphilis Study: implications of results from recall and recognition questions.

PubMed

Katz, Ralph V; Jean-Charles, Germain; Green, B Lee; Kressin, Nancy R; Claudio, Cristina; Wang, Minqi; Russell, Stefanie L; Outlaw, Jason

2009-12-16

This analysis assessed whether Blacks, Whites and Puerto-Rican (PR) Hispanics differed in their ability to identify the Tuskegee Syphilis Study (TSS) via open-ended questions following lead-in recognition and recall questions. The Tuskegee Legacy Project (TLP) Questionnaire was administered via a Random-Digit Dial (RDD) telephone survey to a stratified random sample of Black, White and PR Hispanic adults in three U.S. cities. The TLP Questionnaire was administered to 1,162 adults (356 African-Americans, 313 PR Hispanics, and 493 non-Hispanic Whites) in San Juan, PR, Baltimore, MD and New York City, NY. Recall question data revealed: 1) that 89% or more of Blacks, Whites, and PR Hispanics were not able to name or definitely identify the Tuskegee Syphilis Study by giving study attributes; and, 2) that Blacks were the most likely to provide an open-ended answer that identified the Tuskegee Syphilis Study as compared to Whites and PR Hispanics (11.5% vs 6.3% vs 2.9%, respectively) (p

Correlates of problem recognition and intentions to change among caregivers of abused and neglected children.

PubMed

Littell, Julia H; Girvin, Heather

2006-12-01

To identify individual, family, and caseworker characteristics associated with problem recognition (PR) and intentions to change (ITC) in a sample of caregivers who received in-home child welfare services following substantiated reports of child abuse or neglect. Caregivers were interviewed at 4 weeks, 16 weeks, and 1 year after referral for in-home services. In these interviews, the University of Rhode Island Change Assessment scale assessed PR and ITC in relation to caregiving practices. Additional data were obtained from administrative records and surveys of in-home services caseworkers. We used growth models to identify caregiver, family, and caseworker characteristics associated with initial levels of PR and ITC, and with changes in PR and ITC over time. Contrary to expectations, there were no overall increases in PR and ITC during the first 4 months of in-home services. PR and ITC scores fluctuated over time, in relation to some external events, case characteristics, and caseworker characteristics; however, we were able to account for small portions of the variance in PR and ITC. Controlling for social desirability bias and other variables in the analysis, negative life events, lack of network support, and the severity of caregiver depression were associated with greater PR; housing problems were associated with lower PR. Caregiver depression and age were associated with ITC. Caregivers whose children had been removed from their homes showed significant increases in ITC in the first few months of in-home services. The duration of caseworkers' child welfare experience predicted increases in their clients' PR in the first 4 months and more frequent contacts with an experienced caseworker predicted small, but significant increases in ITC over time. PR and ITC are associated with somewhat different case characteristics and may be affected by caseworkers' experience.

Your Way to a Better Theory of Mind: A Healthy Diet Relates to Better Faux Pas Recognition in Older Adults.

PubMed

Ruffman, Ted; Zhang, Julie; Taumoepeau, Mele; Skeaff, Sheila

2016-01-01

Aging is characterized by a well-documented worsening of general cognition, and also a decline in social understanding such as the ability to recognize emotions or detect socially inappropriate behavior (faux pas). Several studies have demonstrated that lifestyle factors (diet, exercise, social integration, smoking) tend to offset general cognitive decline, and we examined whether they also help to offset age-related declines in social cognition. There were 56 participants aged 60 years or over. General cognition was measured using a matrices task and the Mini-Mental State Examination (MMSE). Emotion recognition was measured by the matching of faces to emotion sounds and bodies to sounds. Faux pas recognition was measured by 16 videos, examining participants' ability to differentiate appropriate and inappropriate social behavior. Diet, exercise, social integration, and smoking habits were measured via questionnaires. For general cognition, diet, pr = .32, p < .02, smoking, pr = -.32, p = .02, and education, pr = .48, p < .001, explained unique variance in matrices performance. For social cognition, even after accounting for participants' education, age, exercise habits, smoking, and social integration, a healthy diet explained independent variance in the ability to identify appropriate social behavior, pr = .29, p = .04. We replicated previous research in finding that lifestyle factors were related to fluid intelligence. In addition, we obtained the novel finding that a healthy diet is associated with better recognition of faux pas in older adults, likely acting through facilitation of brain health, and providing initial support for a means of enhancing social functioning and well-being in old age.

Molecular insights of protein contour recognition with ligand pharmacophoric sites through combinatorial library design and MD simulation in validating HTLV-1 PR inhibitors.

PubMed

Selvaraj, Chandrabose; Omer, Ankur; Singh, Poonam; Singh, Sanjeev Kumar

2015-01-01

Retroviruses HIV-1 and HTLV-1 are chiefly considered to be the most dangerous pathogens in Homo sapiens. These two viruses have structurally unique protease (PR) enzymes, which are having common function of its replication mechanism. Though HIV PR drugs failed to inhibit HTLV-1 infections, they emphatically emphasise the need for designing new lead compounds against HTLV-1 PR. Therefore, we tried to understand the binding level interactions through the charge environment present in both ligand and protein active sites. The domino effect illustrates that libraries of purvalanol-A are attuned to fill allosteric binding site of HTLV-1 PR through molecular recognition and shows proper binding of ligand pharmacophoric features in receptor contours. Our screening evaluates seven compounds from purvalanol-A libraries, and these compounds' pharmacophore searches for an appropriate place in the binding site and it places well according to respective receptor contour surfaces. Thus our result provides a platform for the progress of more effective compounds, which are better in free energy calculation, molecular docking, ADME and molecular dynamics studies. Finally, this research provided novel chemical scaffolds for HTLV-1 drug discovery.

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamics of Preferential Substrate Recognition in HIV-1 Protease: Redefining the Substrate Envelope

PubMed Central

Özen, Ayşegül; Haliloğlu, Türkan; Schiffer, Celia A.

2011-01-01

HIV-1 protease (PR) permits viral maturation by processing the Gag and Gag-Pro-Pol polyproteins. Though HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy, the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates the consideration of drug resistance in novel drug-design strategies. Drug-resistant HIV-1 PR variants, while no longer efficiently inhibited, continue to efficiently hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we defined as the “substrate envelope”. We previously showed that resistance mutations arise where PIs protrude beyond the substrate envelope, as these regions are crucial for drug binding but not for substrate recognition. Here, we extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. Seven molecular dynamics simulations of PR-substrate complexes were performed to estimate the conformational flexibility of substrates in their complexes. Interdependency of the substrate-protease interactions may compensate for the variations in cleavage-site sequences, and explain how a diverse set of sequences can be recognized as substrates by the same enzyme. This diversity may be essential for regulating sequential processing of substrates. We also define a dynamic substrate envelope as a more accurate representation of PR-substrate interactions. This dynamic substrate envelope, described by a probability distribution function, is a powerful tool for drug design efforts targeting ensembles of resistant HIV-1 PR variants with the aim of developing drugs that are less susceptible to resistance. PMID:21762811

Progesterone Impairs Social Recognition in Male Rats

PubMed Central

Auger, Catherine J.

2012-01-01

The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppresses AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependant behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment lead to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. PMID:22366506

Progesterone impairs social recognition in male rats.

PubMed

Bychowski, Meaghan E; Auger, Catherine J

2012-04-01

The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppress AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependent behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment leads to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. Copyright © 2012 Elsevier Inc. All rights reserved.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

Multicategory nets of single-layer perceptrons: complexity and sample-size issues.

PubMed

Raudys, Sarunas; Kybartas, Rimantas; Zavadskas, Edmundas Kazimieras

2010-05-01

The standard cost function of multicategory single-layer perceptrons (SLPs) does not minimize the classification error rate. In order to reduce classification error, it is necessary to: 1) refuse the traditional cost function, 2) obtain near to optimal pairwise linear classifiers by specially organized SLP training and optimal stopping, and 3) fuse their decisions properly. To obtain better classification in unbalanced training set situations, we introduce the unbalance correcting term. It was found that fusion based on the Kulback-Leibler (K-L) distance and the Wu-Lin-Weng (WLW) method result in approximately the same performance in situations where sample sizes are relatively small. The explanation for this observation is by theoretically known verity that an excessive minimization of inexact criteria becomes harmful at times. Comprehensive comparative investigations of six real-world pattern recognition (PR) problems demonstrated that employment of SLP-based pairwise classifiers is comparable and as often as not outperforming the linear support vector (SV) classifiers in moderate dimensional situations. The colored noise injection used to design pseudovalidation sets proves to be a powerful tool for facilitating finite sample problems in moderate-dimensional PR tasks.

Use of Biometrics within Sub-Saharan Refugee Communities

DTIC Science & Technology

2013-12-01

fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity. Biometrics creates and...Biometrics typically comprises fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity...authentication because it identifies an individual based on mathematical analysis of the random pattern visible within the iris. Facial recognition is

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Correlates of Problem Recognition and Intentions to Change among Caregivers of Abused and Neglected Children

ERIC Educational Resources Information Center

Littell, Julia H.; Girvin, Heather

2006-01-01

Objective: To identify individual, family, and caseworker characteristics associated with problem recognition (PR) and intentions to change (ITC) in a sample of caregivers who received in-home child welfare services following substantiated reports of child abuse or neglect. Methods: Caregivers were interviewed at 4 weeks, 16 weeks, and 1 year…

Novel receptor-like kinases in cacao contain PR-1 extracellular domains.

PubMed

Teixeira, Paulo José Pereira Lima; Costa, Gustavo Gilson Lacerda; Fiorin, Gabriel Lorencini; Pereira, Gonçalo Amarante Guimarães; Mondego, Jorge Maurício Costa

2013-08-01

Members of the pathogenesis-related protein 1 (PR-1) family are well-known markers of plant defence responses, forming part of the arsenal of the secreted proteins produced on pathogen recognition. Here, we report the identification of two cacao (Theobroma cacao L.) PR-1s that are fused to transmembrane regions and serine/threonine kinase domains, in a manner characteristic of receptor-like kinases (RLKs). These proteins (TcPR-1f and TcPR-1g) were named PR-1 receptor kinases (PR-1RKs). Phylogenetic analysis of RLKs and PR-1 proteins from cacao indicated that PR-1RKs originated from a fusion between sequences encoding PR-1 and the kinase domain of a LecRLK (Lectin Receptor-Like Kinase). Retrotransposition marks surround TcPR-1f, suggesting that retrotransposition was involved in the origin of PR-1RKs. Genes with a similar domain architecture to cacao PR-1RKs were found in rice (Oryza sativa), barrel medic (Medicago truncatula) and a nonphototrophic bacterium (Herpetosiphon aurantiacus). However, their kinase domains differed from those found in LecRLKs, indicating the occurrence of convergent evolution. TcPR-1g expression was up-regulated in the biotrophic stage of witches' broom disease, suggesting a role for PR-1RKs during cacao defence responses. We hypothesize that PR-1RKs transduce a defence signal by interacting with a PR-1 ligand. © 2013 BSPP AND JOHN WILEY & SONS LTD.

An automatic method for skeletal patterns classification using craniomaxillary variables on a Colombian population.

PubMed

Niño-Sandoval, Tania Camila; Guevara Perez, Sonia V; González, Fabio A; Jaque, Robinson Andrés; Infante-Contreras, Clementina

2016-04-01

The mandibular bone is an important part of the forensic facial reconstruction and it has the possibility of getting lost in skeletonized remains; for this reason, it is necessary to facilitate the identification process simulating the mandibular position only through craniomaxillary measures, for this task, different modeling techniques have been performed, but they only contemplate a straight facial profile that belong to skeletal pattern Class I, but the 24.5% corresponding to the Colombian skeletal patterns Class II and III are not taking into account, besides, craniofacial measures do not follow a parametric trend or a normal distribution. The aim of this study was to employ an automatic non-parametric method as the Support Vector Machines to classify skeletal patterns through craniomaxillary variables, in order to simulate the natural mandibular position on a contemporary Colombian sample. Lateral cephalograms (229) of Colombian young adults of both sexes were collected. Landmark coordinates protocols were used to create craniomaxillary variables. A Support Vector Machine with a linear kernel classifier model was trained on a subset of the available data and evaluated over the remaining samples. The weights of the model were used to select the 10 best variables for classification accuracy. An accuracy of 74.51% was obtained, defined by Pr-A-N, N-Pr-A, A-N-Pr, A-Te-Pr, A-Pr-Rhi, Rhi-A-Pr, Pr-A-Te, Te-Pr-A, Zm-A-Pr and PNS-A-Pr angles. The Class Precision and the Class Recall showed a correct distinction of the Class II from the Class III and vice versa. Support Vector Machines created an important model of classification of skeletal patterns using craniomaxillary variables that are not commonly used in the literature and could be applicable to the 24.5% of the contemporary Colombian sample. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Characterization and mechanism of He plasma pretreatment of nanoscale polymer masks for improved pattern transfer fidelity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weilnboeck, F.; Metzler, D.; Kumar, N.

2011-12-26

Roughening of nanoscale polymer masks during plasma etching (PE) limits feature critical dimensions in current and future lithographic technologies. Roughness formation of 193 nm photoresist (PR) is mechanistically explained by plasma-induced changes in mechanical properties introduced at the PR surface ({approx}2 nm) by ions and in parallel in the material bulk ({approx}200 nm) by ultraviolet (UV) plasma radiation. Synergistic roughening of polymer masks can be prevented by pretreating PR patterns with a high dose of He plasma UV exposure to saturate bulk material modifications. During subsequent PE, PR patterns are stabilized and exhibit improved etch resistance and reduced surface/line-edge roughness.

Neural correlates of free recall of "famous events" in a "hypermnestic" individual as compared to an age- and education-matched reference group.

PubMed

Fehr, Thorsten; Staniloiu, Angelica; Markowitsch, Hans J; Erhard, Peter; Herrmann, Manfred

2018-06-19

Memory performance of an individual (within the age range: 50-55 years old) showing superior memory abilities (protagonist PR) was compared to an age- and education-matched reference group in a historical facts ("famous events") retrieval task. Contrasting task versus baseline performance both PR and the reference group showed fMRI activation patterns in parietal and occipital brain regions. The reference group additionally demonstrated activation patterns in cingulate gyrus, whereas PR showed additional widespread activation patterns comprising frontal and cerebellar brain regions. The direct comparison between PR and the reference group revealed larger fMRI contrasts for PR in right frontal, superior temporal and cerebellar brain regions. It was concluded that PR generally recruits brain regions as normal memory performers do, but in a more elaborate way, and furthermore, that he applied a memory-strategy that potentially includes executively driven multi-modal transcoding of information and recruitment of implicit memory resources.

Differing specificities and isotypes of anti-citrullinated peptide/protein antibodies in palindromic rheumatism and rheumatoid arthritis.

PubMed

Cabrera-Villalba, Sonia; Gomara, María José; Cañete, Juan D; Ramírez, Julio; Salvador, Georgina; Ruiz-Esquide, Virginia; Hernández, Maria Victoria; Inciarte-Mundo, José; Haro, Isabel; Sanmartí, Raimon

2017-06-15

To analyze differences in the recognition of anti-citrullinated peptide/protein antibody (ACPA) citrullinated epitopes and isotypes in patients with palindromic rheumatism (PR) and rheumatoid arthritis (RA). ACPA fine specificities (citrullinated peptides of enolase, fibrin, and vimentin) and isotypes (IgG, IgM, and IgA) were analyzed in 54 patients with longstanding PR and 54 patients with established RA. CCP2 tested positive in 66.7% of patients with PR and RA. The ACPA distribution of fine specificities and isotypes differed between PR and RA patients. PR patients had a lower frequency of fine ACPA specificities than RA patients, which was significant in the case of a peptide derived from vimentin (PR 24.1% vs. 59.3% RA; p < 0.001). The mean number of ACPA specificities was lower in PR than in RA patients, and only 25.9% of PR patients recognized ≥2 additional specificities compared with 46.3% of RA patients. Significantly less isotype usage, especially IgA, was observed in PR patients. The ACPA immune response differed in patients with PR and RA, with fewer fine specificities and isotype usage in patients with PR. Some patients with PR may have impaired maturation of the B-cell response against citrullinated peptides with no progression to RA.

Lifestyle Changes and Pressure Ulcer Prevention in Adults With Spinal Cord Injury in the Pressure Ulcer Prevention Study Lifestyle Intervention

PubMed Central

Ghaisas, Samruddhi; Pyatak, Elizabeth A.; Blanche, Erna; Clark, Florence

2015-01-01

Pressure ulcers (PrUs) are a major burden to patients with spinal cord injury (SCI), affecting their psychological, physical, and social well-being. Lifestyle choices are thought to contribute to the risk of developing PrUs. This article focuses on the interaction between lifestyle choices and the development of PrUs in community settings among participants in the University of Southern California–Rancho Los Amigos National Rehabilitation Center Pressure Ulcer Prevention Study (PUPS II), a randomized controlled trial of a lifestyle intervention for adults with SCI. We conducted a secondary cross-case analysis of treatment notes of 47 PUPS II participants and identified four patterns relating PrU development to lifestyle changes: positive PrU changes (e.g., healing PrUs) with positive lifestyle changes, negative or no PrU changes with positive lifestyle changes, positive PrU changes with minor lifestyle changes, and negative or no PrU changes with no lifestyle changes. We present case studies exemplifying each pattern. PMID:25553751

Prediction of apatite lattice constants from their constituent elemental radii and artificial intelligence methods.

PubMed

Wu, P; Zeng, Y Z; Wang, C M

2004-03-01

Lattice constants (LCs) of all possible 96 apatite compounds, A(5)(BO(4))(3)C, constituted by A[double bond]Ba(2+), Ca(2+), Cd(2+), Pb(2+), Sr(2+), Mn(2+); B[double bond]As(5+), Cr(5+), P(5+), V(5+); and C[double bond]F(1-), Cl(1-), Br(1-), OH(1-), are predicted from their elemental ionic radii, using pattern recognition (PR) and artificial neural networks (ANN) techniques. In particular, by a PR study it is demonstrated that ionic radii predominantly govern the LCs of apatites. Furthermore, by using ANN techniques, prediction models of LCs a and c are developed, which reproduce well the measured LCs (R(2)=0.98). All the literature reported on 30 pure and 22 mixed apatite compounds are collected and used in the present work. LCs of all possible 66 new apatites (assuming they exist) are estimated by the developed ANN models. These proposed new apatites may be of interest to biomedical research especially in the design of new apatite biomaterials for bone remodeling. Similarly these techniques may also be applied in the study of interface growth behaviors involving other biomaterials.

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

Retroviral proteases and their roles in virion maturation.

PubMed

Konvalinka, Jan; Kräusslich, Hans-Georg; Müller, Barbara

2015-05-01

Proteolytic processing of viral polyproteins is essential for retrovirus infectivity. Retroviral proteases (PR) become activated during or after assembly of the immature, non-infectious virion. They cleave viral polyproteins at specific sites, inducing major structural rearrangements termed maturation. Maturation converts retroviral enzymes into their functional form, transforms the immature shell into a metastable state primed for early replication events, and enhances viral entry competence. Not only cleavage at all PR recognition sites, but also an ordered sequence of cleavages is crucial. Proteolysis is tightly regulated, but the triggering mechanisms and kinetics and pathway of morphological transitions remain enigmatic. Here, we outline PR structures and substrate specificities focusing on HIV PR as a therapeutic target. We discuss design and clinical success of HIV PR inhibitors, as well as resistance development towards these drugs. Finally, we summarize data elucidating the role of proteolysis in maturation and highlight unsolved questions regarding retroviral maturation. Copyright © 2015 Elsevier Inc. All rights reserved.

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

Association between dietary patterns and mental disorders in pregnant women in Southern Brazil.

PubMed

Paskulin, Jéssica T A; Drehmer, Michele; Olinto, Maria T; Hoffmann, Juliana F; Pinheiro, Andréa P; Schmidt, Maria I; Nunes, Maria A

2017-01-01

To evaluate the association between dietary patterns and mental disorders among pregnant women in southern Brazil. Cross-sectional study with 712 pregnant women recruited from the Study of Food Intake and Eating Behaviors in Pregnancy (ECCAGe). Food intake assessment was performed using the Food Frequency Questionnaire. Dietary patterns were identified by cluster analysis. The Primary Care Evaluation of Mental Disorders (PRIME-MD) was used to evaluate participants' mental health. Poisson regression models with robust variance were fitted to estimate prevalence ratios (PR). In the adjusted models, there was a high prevalence of major depressive disorder among women with low fruit intake (43%, PR 1.43, 95%CI 1.04-1.95) and high sweets and sugars intake (91%, PR 1.91, 95%CI 1.19-3.07). Women with a common-Brazilian dietary pattern had higher prevalence of major depressive disorder compared to those with a varied consumption pattern (PR 1.43, 95%CI 1.01-2.02). Low intake of beans was significantly associated with generalized anxiety disorder (PR 1.40, 95%CI 1.01-1.93). Low consumption of fruits and beans and intake of the common-Brazilian dietary pattern during pregnancy were associated with higher prevalence of mental disorders. These results reinforce the importance of an adequate dietary intake to ensure better mental health in pregnancy.

Analysis of the HIV-2 protease's adaptation to various ligands: characterization of backbone asymmetry using a structural alphabet.

PubMed

Triki, Dhoha; Cano Contreras, Mario Enrique; Flatters, Delphine; Visseaux, Benoit; Descamps, Diane; Camproux, Anne-Claude; Regad, Leslie

2018-01-15

The HIV-2 protease (PR2) is a homodimer of 99 residues with asymmetric assembly and binding various ligands. We propose an exhaustive study of the local structural asymmetry between the two monomers of all available PR2 structures complexed with various inhibitors using a structural alphabet approach. On average, PR2 exhibits asymmetry in 31% of its positions-i.e., exhibiting different backbone local conformations in the two monomers. This asymmetry was observed all along its structure, particularly in the elbow and flap regions. We first differentiated structural asymmetry conserved in most PR2 structures from the one specific to some PR2. Then, we explored the origin of the detected asymmetry in PR2. We localized asymmetry that could be induced by PR2's flexibility, allowing transition from the semi-open to closed conformations and the asymmetry potentially induced by ligand binding. This latter could be important for the PR2's adaptation to diverse ligands. Our results highlighted some differences between asymmetry of PR2 bound to darunavir and amprenavir that could explain their differences of affinity. This knowledge is critical for a better description of PR2's recognition and adaptation to various ligands and for a better understanding of the resistance of PR2 to most PR2 inhibitors, a major antiretroviral class.

Auditory Pattern Recognition and Brief Tone Discrimination of Children with Reading Disorders

ERIC Educational Resources Information Center

Walker, Marianna M.; Givens, Gregg D.; Cranford, Jerry L.; Holbert, Don; Walker, Letitia

2006-01-01

Auditory pattern recognition skills in children with reading disorders were investigated using perceptual tests involving discrimination of frequency and duration tonal patterns. A behavioral test battery involving recognition of the pattern of presentation of tone triads was used in which individual components differed in either frequency or…

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Understanding eye movements in face recognition using hidden Markov models.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

Biochemical Characterization of Prions.

PubMed

Fiorini, Michele; Bongianni, Matilde; Monaco, Salvatore; Zanusso, Gianluigi

2017-01-01

Prion disease or transmissible spongiform encephalopathies are characterized by the presence of the abnormal form of the prion protein (PrP Sc ). The pathological and transmissible properties of PrP Sc are enciphered in its secondary and tertiary structures. Since it's well established that different strains of prions are linked to different conformations of PrP Sc , biochemical characterization of prions seems a preliminary but reliable approach to detect, analyze, and compare prion strains. Experimental biochemical procedures might be helpful in distinguishing PrP Sc physicochemical properties and include resistance to proteinase K (PK) digestion, insolubility in nonionic detergents, PK-resistance under denaturing conditions and sedimentation properties in sucrose gradients. This biochemical approach has been extensively applied in human prion disorders and subsequently expanded for PrP Sc characterization in animals. In particular, in sporadic Creutzfedlt-Jakob disease (sCJD) PrP Sc is characterized by two main glycotypes conventionally named Type 1 and Type 2, based on the apparent gel migration at 21 and 19kDa of the PrP Sc PK-resistant fragment. An additional PrP Sc type was identified in sCJD characterized by an unglycosylated dominant glycoform pattern and in 2010 a variably protease-sensitive prionopathy (VPSPr) was reported showing a PrP Sc with an electrophoretic ladder like pattern. Additionally, the presence of PrP Sc truncated fragments completes the electrophoretic characterization of different prion strains. By two-dimensional (2D) electrophoretic analysis additional PrP Sc pattern was identified, since this procedure provides information about the isoelectric point and the different peptides length related to PK cleavage, as well as to glycosylation extent or GPI anchor presence. We here provide and extensive review on PrP Sc biochemical analysis in human and animal prion disorders. Further, we show that PrP Sc glycotypes observed in CJD share similarities with PrP Sc in bovine spongiform encephalopathy forms (BSE). © 2017 Elsevier Inc. All rights reserved.

Resolution of Site-Specific Conformational Heterogeneity in Proline-Rich Molecular Recognition by Src Homology 3 Domains.

PubMed

Horness, Rachel E; Basom, Edward J; Mayer, John P; Thielges, Megan C

2016-02-03

Conformational heterogeneity and dynamics are increasingly evoked in models of protein molecular recognition but are challenging to experimentally characterize. Here we combine the inherent temporal resolution of infrared (IR) spectroscopy with the spatial resolution afforded by selective incorporation of carbon-deuterium (C-D) bonds, which provide frequency-resolved absorptions within a protein IR spectrum, to characterize the molecular recognition of the Src homology 3 (SH3) domain of the yeast protein Sho1 with its cognate proline-rich (PR) sequence of Pbs2. The IR absorptions of C-D bonds introduced at residues along a peptide of the Pbs2 PR sequence report on the changes in the local environments upon binding to the SH3 domain. Interestingly, upon forming the complex the IR spectra of the peptides labeled with C-D bonds at either of the two conserved prolines of the PXXP consensus recognition sequence show more absorptions than there are C-D bonds, providing evidence for the population of multiple states. In contrast, the NMR spectra of the peptides labeled with (13)C at the same residues show only single resonances, indicating rapid interconversion on the NMR time scale. Thus, the data suggest that the SH3 domain recognizes its cognate peptide with a component of induced fit molecular recognition involving the adoption of multiples states, which have previously gone undetected due to interconversion between the populated states that is too fast to resolve using conventional methods.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study.

PubMed

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-06-19

In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study

PubMed Central

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-01-01

Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386

Patterns and Correlates of PrEP Drug Detection among MSM and Transgender Women in the Global iPrEx Study

PubMed Central

Liu, Albert; Glidden, David V.; Anderson, Peter L.; Amico, K.R.; McMahan, Vanessa; Mehrotra, Megha; Lama, Javier R.; MacRae, John; Hinojosa, Juan Carlos; Montoya, Orlando; Veloso, Valdilea G.; Schechter, Mauro; Kallas, Esper G.; Chariyalerstak, Suwat; Bekker, Linda-Gail; Mayer, Kenneth; Buchbinder, Susan; Grant, Robert

2014-01-01

Background Adherence to pre-exposure prophylaxis (PrEP) is critical for efficacy. Antiretroviral concentrations are an objective measure of PrEP use and correlate with efficacy. Understanding patterns and correlates of drug detection can identify populations at risk for non-adherence and inform design of PrEP adherence interventions. Methods Blood antiretroviral concentrations were assessed among active-arm participants in iPrEx, a randomized, placebo-controlled trial of emtricitabine/tenofovir in men who have sex with men (MSM) and transgender women in 6 countries. We evaluated rates and correlates of drug detection among a random sample of 470 participants at week 8 and a longitudinal cohort of 303 participants through 72 weeks of follow-up. Results Overall, 55% (95% CI 49–60%) of participants tested at week 8 had drug detected. Drug detection was associated with older age and varied by study site. In longitudinal analysis, 31% never had drug detected, 30% always had drug detected, and 39% had an inconsistent pattern. Overall detection rates declined over time. Drug detection at some or all visits was associated with older age; indices of sexual risk, including condomless receptive anal sex; and responding "don't know" to a question about belief of PrEP efficacy (0–10 scale). Conclusions Distinct patterns of study-product use were identified, with a significant proportion demonstrating no drug detection at any visit. Research literacy may explain greater drug detection among populations having greater research experience, such as older MSM in the US. Greater drug detection among those reporting highest-risk sexual practices is expected to increase the impact and cost-effectiveness of PrEP. PMID:25230290

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Vibration mode shape recognition using image processing

NASA Astrophysics Data System (ADS)

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

2009-10-01

Currently the most widely used method for comparing mode shapes from finite elements and experimental measurements is the modal assurance criterion (MAC), which can be interpreted as the cosine of the angle between the numerical and measured eigenvectors. However, the eigenvectors only contain the displacement of discrete coordinates, so that the MAC index carries no explicit information on shape features. New techniques, based upon the well-developed philosophies of image processing (IP) and pattern recognition (PR) are considered in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD) are the most popular shape descriptors due to their outstanding properties in IP and PR. These include (1) for the ZMD-rotational invariance, expression and computing efficiency, ease of reconstruction and robustness to noise; (2) for the FD—separation of the global shape and shape-details by low and high frequency components, respectively, invariance under geometric transformation; (3) for the WD—multi-scale representation and local feature detection. Once a shape descriptor has been adopted, the comparison of mode shapes is transformed to a comparison of multidimensional shape feature vectors. Deterministic and statistical methods are presented. The deterministic problem of measuring the degree of similarity between two mode shapes (possibly one from a vibration test and the other from a finite element model) may be carried out using Pearson's correlation. Similar shape feature vectors may be arranged in clusters separated by Euclidian distances in the feature space. In the statistical analysis we are typically concerned with the classification of a test mode shape according to clusters of shape feature vectors obtained from a randomised finite element model. The dimension of the statistical problem may often be reduced by principal component analysis. Then, in addition to the Euclidian distance, the Mahalanobis distance, defining the separation of the test point from the cluster in terms of its standard deviation, becomes an important measure. Bayesian decision theory may be applied to formally minimise the risk of misclassification of the test shape feature vector. In this paper the ZMD is applied to the problem of mode shape recognition for a circular plate. Results show that the ZMD has considerable advantages over the traditional MAC index when identifying the cyclically symmetric mode shapes that occur in axisymmetric structures at identical frequencies. Mode shape recognition of rectangular plates is carried out by the FD. Also, the WD is applied to the problem of recognising the mode shapes in the thin and thick regions of a plate with different thicknesses. It shows the benefit of using the WD to identify mode-shapes having both local and global components. The comparison and classification of mode shapes using IP and PR provides a 'toolkit' to complement the conventional MAC approach. The selection of a particular shape descriptor and classification method will depend upon the problem in hand and the experience of the analyst.

Deformed Palmprint Matching Based on Stable Regions.

PubMed

Wu, Xiangqian; Zhao, Qiushi

2015-12-01

Palmprint recognition (PR) is an effective technology for personal recognition. A main problem, which deteriorates the performance of PR, is the deformations of palmprint images. This problem becomes more severe on contactless occasions, in which images are acquired without any guiding mechanisms, and hence critically limits the applications of PR. To solve the deformation problems, in this paper, a model for non-linearly deformed palmprint matching is derived by approximating non-linear deformed palmprint images with piecewise-linear deformed stable regions. Based on this model, a novel approach for deformed palmprint matching, named key point-based block growing (KPBG), is proposed. In KPBG, an iterative M-estimator sample consensus algorithm based on scale invariant feature transform features is devised to compute piecewise-linear transformations to approximate the non-linear deformations of palmprints, and then, the stable regions complying with the linear transformations are decided using a block growing algorithm. Palmprint feature extraction and matching are performed over these stable regions to compute matching scores for decision. Experiments on several public palmprint databases show that the proposed models and the KPBG approach can effectively solve the deformation problem in palmprint verification and outperform the state-of-the-art methods.

Physiological reactivity during autobiographical narratives in older adults: the roles of depression and anxiety.

PubMed

Robertson, Sarah M C; Swickert, Rhonda J; Connelly, Kathryn; Galizio, Ann

2015-01-01

Physiological reactivity (PR) describes the change in physiological functioning (e.g., heart rate, blood pressure, pulse pressure) that occurs after the induction of a stressful task. This study aims to understand the influence of mental health symptoms on patterns of PR during autobiographical narratives in an older adult sample. Eighty older adults completed self-report measures regarding their symptoms of depression and anxiety. Next, their blood pressure was recorded while they completed two verbal autobiographical narratives. During the positive narrative, anxiety was positively associated with increased PR while depression was negatively associated with PR. During the negative narrative, a significant interaction occurred whereby anxiety was significantly positively associated with PR for those participants low in depression. The above results are explained in the context of the Tripartite Model of Depression and Anxiety, which predicts different patterns of PR as a function of mental health symptoms. Limitations and future directions are also discussed.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Gemella sanguinis endocarditis with c-ANCA/anti-PR-3-associated immune complex necrotizing glomerulonephritis with a ‘full-house’ pattern on immunofluorescence microscopy

PubMed Central

Rousseau-Gagnon, Mathieu; Riopel, Julie; Desjardins, Anne; Garceau, Daniel; Agharazii, Mohsen; Desmeules, Simon

2013-01-01

A 67-year-old man was evaluated for haematuria, with a rising creatinine level from 88 to 906 µmol/L and positive c-anti-neutrophil cytoplasm antibody (ANCA)/anti-proteinase 3 (anti-PR3). A kidney biopsy revealed necrotizing glomerulonephritis with a ‘full-house’ pattern on immunofluorescence microscopy. Echocardiography and blood cultures growing Gemella sanguinis diagnosed endocarditis. Dialysis was required for a month. Three months later, following valve replacement, glucocorticoids and 2 months of antibiotic therapy, the creatinine level decreased to 62 µmol/L and c-ANCA/anti-PR3 disappeared. This first case of c-ANCA/anti-PR3 positive glomerulonephritis with a ‘full-house’ immunofluorescence pattern due to bacterial endocarditis underlines the importance of ruling out infection with ANCA positivity or kidney biopsy suggestive of lupus nephritis. PMID:26064489

Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

NASA Astrophysics Data System (ADS)

Heger, Daniel; Krischer, Katharina

2016-08-01

Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

An Analysis of EMG Electrode Configuration for Targeted Muscle Reinnervation Based Neural Machine Interface

PubMed Central

Huang, He; Zhou, Ping; Li, Guanglin; Kuiken, Todd A.

2015-01-01

Targeted muscle reinnervation (TMR) is a novel neural machine interface for improved myoelectric prosthesis control. Previous high-density (HD) surface electromyography (EMG) studies have indicated that tremendous neural control information can be extracted from the reinnervated muscles by EMG pattern recognition (PR). However, using a large number of EMG electrodes hinders clinical application of the TMR technique. This study investigated a reduced number of electrodes and the placement required to extract sufficient neural control information for accurate identification of user movement intents. An electrode selection algorithm was applied to the HD EMG recordings from each of 4 TMR amputee subjects. The results show that when using only 12 selected bipolar electrodes the average accuracy over subjects for classifying 16 movement intents was 93.0(±3.3)%, just 1.2% lower than when using the entire HD electrode complement. The locations of selected electrodes were consistent with the anatomical reinnervation sites. Additionally, a practical protocol for clinical electrode placement was developed, which does not rely on complex HD EMG experiment and analysis while maintaining a classification accuracy of 88.7±4.5%. These outcomes provide important guidelines for practical electrode placement that can promote future clinical application of TMR and EMG PR in the control of multifunctional prostheses. PMID:18303804

FLT3-regulated antigens as targets for leukemia-reactive cytotoxic T lymphocytes

PubMed Central

Brackertz, B; Conrad, H; Daniel, J; Kast, B; Krönig, H; Busch, D H; Adamski, J; Peschel, C; Bernhard, H

2011-01-01

The FMS-like tyrosine kinase 3 (FLT3) is highly expressed in acute myeloid leukemia (AML). Internal tandem duplications (ITD) of the juxtamembrane domain lead to the constitutive activation of the FLT3 kinase inducing the activation of multiple genes, which may result in the expression of leukemia-associated antigens (LAAs). We analyzed the regulation of LAA in FLT3-wild-type (WT)- and FLT3-ITD+ myeloid cells to identify potential targets for antigen-specific immunotherapy for AML patients. Antigens, such as PR-3, RHAMM, Survivin, WT-1 and PRAME, were upregulated by constitutively active FLT3-ITD as well as FLT3-WT activated by FLT3 ligand (FL). Cytotoxic T-cell (CTL) clones against PR-3, RHAMM, Survivin and an AML-directed CTL clone recognized AML cell lines and primary AML blasts expressing FLT3-ITD, as well as FLT3-WT+ myeloid dendritic cells in the presence of FL. Downregulation of FLT3 led to the abolishment of CTL recognition. Comparing our findings concerning LAA upregulation by the FLT3 kinase with those already made for the Bcr-Abl kinase, we found analogies in the LAA expression pattern. Antigens upregulated by both FLT3 and Bcr-Abl may be promising targets for the development of immunotherapeutical approaches against myeloid leukemia of different origin. PMID:22829124

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

PubMed

Watts, Joel C; Huo, Hairu; Bai, Yu; Ehsani, Sepehr; Jeon, Amy Hye Won; Won, Amy Hye; Shi, Tujin; Daude, Nathalie; Lau, Agnes; Young, Rebecca; Xu, Lei; Carlson, George A; Williams, David; Westaway, David; Schmitt-Ulms, Gerold

2009-10-01

The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C)) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C) interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrP(C) paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C) and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C) with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc). A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C) organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

Patterns of exchange of forensic DNA data in the European Union through the Prüm system.

PubMed

Santos, Filipe; Machado, Helena

2017-07-01

This paper presents a study of the 5-year operation (2011-2015) of the transnational exchange of forensic DNA data between Member States of the European Union (EU) for the purpose of combating cross-border crime and terrorism within the so-called Prüm system. This first systematisation of the full official statistical dataset provides an overall assessment of the match figures and patterns of operation of the Prüm system for DNA exchange. These figures and patterns are analysed in terms of the differentiated contributions by participating EU Member States. The data suggest a trend for West and Central European countries to concentrate the majority of Prüm matches, while DNA databases of Eastern European countries tend to contribute with profiles of people that match stains in other countries. In view of the necessary transparency and accountability of the Prüm system, more extensive and informative statistics would be an important contribution to the assessment of its functioning and societal benefits. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2018-01-01

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

Que nous apprennent les petits frères et sœurs sur les signes précoces d’autisme?1

PubMed Central

Rogers, Sally J.

2010-01-01

L’objectif de cette revue est de présenter une synthèse des réponses que l’on peut actuellement apporter à la question de savoir quelles sont les premières caractéristiques comportementales qui prédisent le développement de l’autisme. L’article se centre sur 5 points : la présence de Troubles du Spectre Autistique (TSA) dans des groupes de frères et sœurs puînés d’enfants déjà diagnostiqués, les patterns et caractéristiques du développement moteur, les patterns et caractéristiques du développement social et émotionnel, les patterns et caractéristiques de la communication intentionnelle verbale et non verbale, et les patterns qui marquent le début de comportements pathognomoniques de TSA. La discussion porte sur les aspects inattendus des résultats et les pistes de recherche nouvelles qu’ils peuvent engendrer. PMID:20890377

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

NASA Astrophysics Data System (ADS)

Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.; MicroBooNE Collaboration

2017-09-01

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Patterning with metal-oxide EUV photoresist: patterning capability, resist smoothing, trimming, and selective stripping

NASA Astrophysics Data System (ADS)

Mao, Ming; Lazzarino, Frederic; De Schepper, Peter; De Simone, Danilo; Piumi, Daniele; Luong, Vinh; Yamashita, Fumiko; Kocsis, Michael; Kumar, Kaushik

2017-03-01

Inpria metal-oxide photoresist (PR) serves as a thin spin-on patternable hard mask for EUV lithography. Compared to traditional organic photoresists, the ultrathin metal-oxide photoresist ( 12nm after development) effectively mitigates pattern collapse. Because of the high etch resistance of the metal-oxide resist, this may open up significant scope for more aggressive etches, new chemistries, and novel integration schemes. We have previously shown that metal-oxide PR can be successfully used to pattern the block layer for the imec 7-nm technology node[1] and advantageously replace a multiple patterning approach, which significantly reduces the process complexity and effectively decreases the cost. We also demonstrated the formation of 16nm half pitch 1:1 line/space with EUV single print[2], which corresponds to a metal 2 layer for the imec 7-nm technology node. In this paper, we investigate the feasibility of using Inpria's metal-oxide PR for 16nm line/space patterning. In meanwhile, we also explore the different etch process for LWR smoothing, resist trimming and resist stripping.

The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

PubMed

Marée, Raphaël

2017-01-01

Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

Optical Pattern Recognition With Self-Amplification

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1994-01-01

In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

Uncovering the defence responses of Eucalyptus to pests and pathogens in the genomics age.

PubMed

Naidoo, Sanushka; Külheim, Carsten; Zwart, Lizahn; Mangwanda, Ronishree; Oates, Caryn N; Visser, Erik A; Wilken, Febé E; Mamni, Thandekile B; Myburg, Alexander A

2014-09-01

Long-lived tree species are subject to attack by various pests and pathogens during their lifetime. This problem is exacerbated by climate change, which may increase the host range for pathogens and extend the period of infestation by pests. Plant defences may involve preformed barriers or induced resistance mechanisms based on recognition of the invader, complex signalling cascades, hormone signalling, activation of transcription factors and production of pathogenesis-related (PR) proteins with direct antimicrobial or anti-insect activity. Trees have evolved some unique defence mechanisms compared with well-studied model plants, which are mostly herbaceous annuals. The genome sequence of Eucalyptus grandis W. Hill ex Maiden has recently become available and provides a resource to extend our understanding of defence in large woody perennials. This review synthesizes existing knowledge of defence mechanisms in model plants and tree species and features mechanisms that may be important for defence in Eucalyptus, such as anatomical variants and the role of chemicals and proteins. Based on the E. grandis genome sequence, we have identified putative PR proteins based on sequence identity to the previously described plant PR proteins. Putative orthologues for PR-1, PR-2, PR-4, PR-5, PR-6, PR-7, PR-8, PR-9, PR-10, PR-12, PR-14, PR-15 and PR-17 have been identified and compared with their orthologues in Populus trichocarpa Torr. & A. Gray ex Hook and Arabidopsis thaliana (L.) Heynh. The survey of PR genes in Eucalyptus provides a first step in identifying defence gene targets that may be employed for protection of the species in future. Genomic resources available for Eucalyptus are discussed and approaches for improving resistance in these hardwood trees, earmarked as a bioenergy source in future, are considered. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Sonar Recognition Training: An Investigation of Whole VS. Part and Analytic VS. Synthetic Procedures.

ERIC Educational Resources Information Center

Annett, John

An experienced person, in such tasks as sonar detection and recognition, has a considerable superiority over a machine recognition system in auditory pattern recognition. However, people require extensive exposure to auditory patterns before achieving a high level of performance. In an attempt to discover a method of training people to recognize…

Degraded character recognition based on gradient pattern

NASA Astrophysics Data System (ADS)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acciarri, R.; Adams, C.; An, R.

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2018-01-29

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

Finger Vein Recognition Based on Local Directional Code

PubMed Central

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger vein recognition based on local directional code.

PubMed

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-11-05

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

Pattern recognition technique

NASA Technical Reports Server (NTRS)

Hong, J. P.

1971-01-01

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements

PubMed Central

2014-01-01

Myoelectric control has been used for decades to control powered upper limb prostheses. Conventional, amplitude-based control has been employed to control a single prosthesis degree of freedom (DOF) such as closing and opening of the hand. Within the last decade, new and advanced arm and hand prostheses have been constructed that are capable of actuating numerous DOFs. Pattern recognition control has been proposed to control a greater number of DOFs than conventional control, but has traditionally been limited to sequentially controlling DOFs one at a time. However, able-bodied individuals use multiple DOFs simultaneously, and it may be beneficial to provide amputees the ability to perform simultaneous movements. In this study, four amputees who had undergone targeted motor reinnervation (TMR) surgery with previous training using myoelectric prostheses were configured to use three control strategies: 1) conventional amplitude-based myoelectric control, 2) sequential (one-DOF) pattern recognition control, 3) simultaneous pattern recognition control. Simultaneous pattern recognition was enabled by having amputees train each simultaneous movement as a separate motion class. For tasks that required control over just one DOF, sequential pattern recognition based control performed the best with the lowest average completion times, completion rates and length error. For tasks that required control over 2 DOFs, the simultaneous pattern recognition controller performed the best with the lowest average completion times, completion rates and length error compared to the other control strategies. In the two strategies in which users could employ simultaneous movements (conventional and simultaneous pattern recognition), amputees chose to use simultaneous movements 78% of the time with simultaneous pattern recognition and 64% of the time with conventional control for tasks that required two DOF motions to reach the target. These results suggest that when amputees are given the ability to control multiple DOFs simultaneously, they choose to perform tasks that utilize multiple DOFs with simultaneous movements. Additionally, they were able to perform these tasks with higher performance (faster speed, lower length error and higher completion rates) without losing substantial performance in 1 DOF tasks. PMID:24410948

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

The purple cauliflower arises from activation of a MYB transcription factor.

PubMed

Chiu, Li-Wei; Zhou, Xiangjun; Burke, Sarah; Wu, Xianli; Prior, Ronald L; Li, Li

2010-11-01

Anthocyanins are responsible for the color of many flowers, fruits, and vegetables. An interesting and unique Purple (Pr) gene mutation in cauliflower (Brassica oleracea var botrytis) confers an abnormal pattern of anthocyanin accumulation, giving the striking mutant phenotype of intense purple color in curds and a few other tissues. To unravel the nature of the Pr mutation in cauliflower, we isolated the Pr gene via a combination of candidate gene analysis and fine mapping. Pr encoded a R2R3 MYB transcription factor that exhibited tissue-specific expression, consistent with an abnormal anthocyanin accumulation pattern in the mutant. Transgenic Arabidopsis (Arabidopsis thaliana) and cauliflower plants expressing the Pr-D allele recapitulated the mutant phenotype, confirming the isolation of the Pr gene. Up-regulation of Pr specifically activated a basic helix-loop-helix transcription factor and a subset of anthocyanin structural genes encoding flavonoid 3'-hydroxylase, dihydroflavonol 4-reductase, and leucoanthocyanidin dioxygenase to confer ectopic accumulation of pigments in the purple cauliflower. Our results indicate that the genetic variation including a Harbinger DNA transposon insertion in the upstream regulatory region of the Pr-D allele is responsible for the up-regulation of the Pr gene in inducing phenotypic change in the plant. The successful isolation of Pr provides important information on the regulatory control of anthocyanin biosynthesis in Brassica vegetables, and offers a genetic resource for development of new varieties with enhanced health-promoting properties and visual appeal.

The Purple Cauliflower Arises from Activation of a MYB Transcription Factor1[W][OA

PubMed Central

Chiu, Li-Wei; Zhou, Xiangjun; Burke, Sarah; Wu, Xianli; Prior, Ronald L.; Li, Li

2010-01-01

Anthocyanins are responsible for the color of many flowers, fruits, and vegetables. An interesting and unique Purple (Pr) gene mutation in cauliflower (Brassica oleracea var botrytis) confers an abnormal pattern of anthocyanin accumulation, giving the striking mutant phenotype of intense purple color in curds and a few other tissues. To unravel the nature of the Pr mutation in cauliflower, we isolated the Pr gene via a combination of candidate gene analysis and fine mapping. Pr encoded a R2R3 MYB transcription factor that exhibited tissue-specific expression, consistent with an abnormal anthocyanin accumulation pattern in the mutant. Transgenic Arabidopsis (Arabidopsis thaliana) and cauliflower plants expressing the Pr-D allele recapitulated the mutant phenotype, confirming the isolation of the Pr gene. Up-regulation of Pr specifically activated a basic helix-loop-helix transcription factor and a subset of anthocyanin structural genes encoding flavonoid 3’-hydroxylase, dihydroflavonol 4-reductase, and leucoanthocyanidin dioxygenase to confer ectopic accumulation of pigments in the purple cauliflower. Our results indicate that the genetic variation including a Harbinger DNA transposon insertion in the upstream regulatory region of the Pr-D allele is responsible for the up-regulation of the Pr gene in inducing phenotypic change in the plant. The successful isolation of Pr provides important information on the regulatory control of anthocyanin biosynthesis in Brassica vegetables, and offers a genetic resource for development of new varieties with enhanced health-promoting properties and visual appeal. PMID:20855520

Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2017-01-01

The success of myoelectric pattern recognition (M-PR) mostly relies on the features extracted and classifier employed. This paper proposes and evaluates a fast classifier, extreme learning machine (ELM), to classify individual and combined finger movements on amputees and non-amputees. ELM is a single hidden layer feed-forward network (SLFN) that avoids iterative learning by determining input weights randomly and output weights analytically. Therefore, it can accelerate the training time of SLFNs. In addition to the classifier evaluation, this paper evaluates various feature combinations to improve the performance of M-PR and investigate some feature projections to improve the class separability of the features. Different from other studies on the implementation of ELM in the myoelectric controller, this paper presents a complete and thorough investigation of various types of ELMs including the node-based and kernel-based ELM. Furthermore, this paper provides comparisons of ELMs and other well-known classifiers such as linear discriminant analysis (LDA), k-nearest neighbour (kNN), support vector machine (SVM) and least-square SVM (LS-SVM). The experimental results show the most accurate ELM classifier is radial basis function ELM (RBF-ELM). The comparison of RBF-ELM and other well-known classifiers shows that RBF-ELM is as accurate as SVM and LS-SVM but faster than the SVM family; it is superior to LDA and kNN. The experimental results also indicate that the accuracy gap of the M-PR on the amputees and non-amputees is not too much with the accuracy of 98.55% on amputees and 99.5% on the non-amputees using six electromyography (EMG) channels. Copyright © 2016 Elsevier Ltd. All rights reserved.

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

A machine-learning approach for damage detection in aircraft structures using self-powered sensor data

NASA Astrophysics Data System (ADS)

Salehi, Hadi; Das, Saptarshi; Chakrabartty, Shantanu; Biswas, Subir; Burgueño, Rigoberto

2017-04-01

This study proposes a novel strategy for damage identification in aircraft structures. The strategy was evaluated based on the simulation of the binary data generated from self-powered wireless sensors employing a pulse switching architecture. The energy-aware pulse switching communication protocol uses single pulses instead of multi-bit packets for information delivery resulting in discrete binary data. A system employing this energy-efficient technology requires dealing with time-delayed binary data due to the management of power budgets for sensing and communication. This paper presents an intelligent machine-learning framework based on combination of the low-rank matrix decomposition and pattern recognition (PR) methods. Further, data fusion is employed as part of the machine-learning framework to take into account the effect of data time delay on its interpretation. Simulated time-delayed binary data from self-powered sensors was used to determine damage indicator variables. Performance and accuracy of the damage detection strategy was examined and tested for the case of an aircraft horizontal stabilizer. Damage states were simulated on a finite element model by reducing stiffness in a region of the stabilizer's skin. The proposed strategy shows satisfactory performance to identify the presence and location of the damage, even with noisy and incomplete data. It is concluded that PR is a promising machine-learning algorithm for damage detection for time-delayed binary data from novel self-powered wireless sensors.

PrEFiNe Plan: Strategic plan for Fabry diseases in Nephrology.

PubMed

Del Pino, M D; Ortiz, A; Torra, R; Hernandez, D

2016-01-01

Renal failure is one of the main causes of death in patients with Fabry disease (FD). Due to the low prevalence of FD, delayed diagnosis and misdiagnosis, often the correct diagnosis is made when organ damage is already present. Early recognition of the disease would allow the prevention of severe complications and the premature death of patients with FD. We present here the PrEFiNE project, which includes a wide spectrum of activities with the aim of improve knowledge and diagnosis of FD. The project is sponsored by Shire Iberia (http://shireiberica.com/) From January 2016 to the end of 2017 several activities will be carried out, starting with a survey to evaluate current FD knowledge among nephrologists; in addition some studies to assess prevalence of this disease will be performed. One study will include patients receiving dialysis, another study will cover kidney transplant patients, and a pilot study in chronic kidney disease in stage 3-5 predialysis. Also planned is a pharmacoeconomic study to focus on burden of FD. At the same time medical education activities will be conducted both on line and on site. Plan for dissemination will include medical publications and diffusion to media. PrEFiNE Project will finish with the publication of a compilation book on FD in Nephrology including all planned activities and proposing recommendations based on results and detected unmet needs. PrEfiNE Plan will be coordinated by severa scientific committees, one at national level and 10 other regionals comittees, tha will be responsible to ensure the maximum scientific quality of proposed activities. An advisory board will supervise the project. PrEfiNE project will evaluate an action plan focused on improving FD knowledge to make necessary recommendations for an early recognition of the disease. In addition will generate a plan to improve previously undetected needs. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

NASA Astrophysics Data System (ADS)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

Gender Difference on the Association between Dietary Patterns and Obesity in Chinese Middle-Aged and Elderly Populations.

PubMed

Yuan, Ya-Qun; Li, Fan; Meng, Pai; You, Jie; Wu, Min; Li, Shu-Guang; Chen, Bo

2016-07-23

Dietary patterns are linked to obesity, but the gender difference in the association between dietary patterns and obesity remains unclear. We explored this gender difference in a middle-aged and elderly populations in Shanghai. Residents (n = 2046; aged ≥45 years; 968 men and 1078 women) who participated in the Shanghai Food Consumption Survey were studied. Factor analysis of data from four periods of 24-h dietary recalls (across 2012-2014) identified dietary patterns. Height, body weight, and waist circumference were measured to calculate the body mass index. A log binominal model examined the association between dietary patterns and obesity, stratified by gender. Four dietary patterns were identified for both genders: rice staple, wheat staple, snacks, and prudent patterns. The rice staple pattern was associated positively with abdominal obesity in men (prevalence ratio (PR) = 1.358; 95% confidence interval (CI) 1.132-1.639; p = 0.001), but was associated negatively with general obesity in women (PR = 0.745; 95% CI: 0.673-0.807; p = 0.031). Men in the highest quartile of the wheat staple pattern had significantly greater risk of central obesity (PR = 1.331; 95% CI: 1.094-1.627; p = 0.005). There may be gender differences in the association between dietary patterns and obesity in middle-aged and elderly populations in Shanghai, China.

Gender Difference on the Association between Dietary Patterns and Obesity in Chinese Middle-Aged and Elderly Populations

PubMed Central

Yuan, Ya-Qun; Li, Fan; Meng, Pai; You, Jie; Wu, Min; Li, Shu-Guang; Chen, Bo

2016-01-01

Dietary patterns are linked to obesity, but the gender difference in the association between dietary patterns and obesity remains unclear. We explored this gender difference in a middle-aged and elderly populations in Shanghai. Residents (n = 2046; aged ≥45 years; 968 men and 1078 women) who participated in the Shanghai Food Consumption Survey were studied. Factor analysis of data from four periods of 24-h dietary recalls (across 2012–2014) identified dietary patterns. Height, body weight, and waist circumference were measured to calculate the body mass index. A log binominal model examined the association between dietary patterns and obesity, stratified by gender. Four dietary patterns were identified for both genders: rice staple, wheat staple, snacks, and prudent patterns. The rice staple pattern was associated positively with abdominal obesity in men (prevalence ratio (PR) = 1.358; 95% confidence interval (CI) 1.132–1.639; p = 0.001), but was associated negatively with general obesity in women (PR = 0.745; 95% CI: 0.673–0.807; p = 0.031). Men in the highest quartile of the wheat staple pattern had significantly greater risk of central obesity (PR = 1.331; 95% CI: 1.094–1.627; p = 0.005). There may be gender differences in the association between dietary patterns and obesity in middle-aged and elderly populations in Shanghai, China. PMID:27455322

Mechanisms of Photoreceptor Patterning in Vertebrates and Invertebrates.

PubMed

Viets, Kayla; Eldred, Kiara; Johnston, Robert J

2016-10-01

Across the animal kingdom, visual systems have evolved to be uniquely suited to the environments and behavioral patterns of different species. Visual acuity and color perception depend on the distribution of photoreceptor (PR) subtypes within the retina. Retinal mosaics can be organized into three broad categories: stochastic/regionalized, regionalized, and ordered. We describe here the retinal mosaics of flies, zebrafish, chickens, mice, and humans, and the gene regulatory networks controlling proper PR specification in each. By drawing parallels in eye development between these divergent species, we identify a set of conserved organizing principles and transcriptional networks that govern PR subtype differentiation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

NASA Astrophysics Data System (ADS)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Enhanced host immune recognition of E.coli causing mastitis in CD-14 transgenic mice.

USDA-ARS?s Scientific Manuscript database

Escherchia coli causes mastitis, an economically significant disease in dairy animals. E. coli endotoxin (lipopolysaccharide, LPS) when bound by host membrane proteins such as CD-14, causes release of pro-inflammatory cytokines recruiting neutrophils as a early innate immune response. Excessive pr...

Using Soil Apparent Electrical Conductivity to Optimize Sampling of Soil Penetration Resistance and to Improve the Estimations of Spatial Patterns of Soil Compaction

PubMed Central

Siqueira, Glécio Machado; Dafonte, Jorge Dafonte; Bueno Lema, Javier; Valcárcel Armesto, Montserrat; Silva, Ênio Farias França e

2014-01-01

This study presents a combined application of an EM38DD for assessing soil apparent electrical conductivity (ECa) and a dual-sensor vertical penetrometer Veris-3000 for measuring soil electrical conductivity (ECveris) and soil resistance to penetration (PR). The measurements were made at a 6 ha field cropped with forage maize under no-tillage after sowing and located in Northwestern Spain. The objective was to use data from ECa for improving the estimation of soil PR. First, data of ECa were used to determine the optimized sampling scheme of the soil PR in 40 points. Then, correlation analysis showed a significant negative relationship between soil PR and ECa, ranging from −0.36 to −0.70 for the studied soil layers. The spatial dependence of soil PR was best described by spherical models in most soil layers. However, below 0.50 m the spatial pattern of soil PR showed pure nugget effect, which could be due to the limited number of PR data used in these layers as the values of this parameter often were above the range measured by our equipment (5.5 MPa). The use of ECa as secondary variable slightly improved the estimation of PR by universal cokriging, when compared with kriging. PMID:25610899

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

SUPPLEMENTARY COMPARISON: Final report on APMP.PR-S1.1: Bilateral comparison of irradiance responsivity of UVA detectors

NASA Astrophysics Data System (ADS)

Huang, Xuebo

2009-01-01

In order to assess the performance of the standards and techniques used for calibration and measurement of UVA irradiance responsivity of photodetectors in NMISA, South Africa, a new comparison was decided as a follow-up to comparison APMP.PR-S1. It is registered in the Key Comparison Data Base (KCDB) of BIPM as a bilateral supplementary comparison, with the identifier APMP.PR-S1.1. The comparison was carried out following the same technical protocol as that of supplementary comparison APMP PR-S1. The principle, organization and method of the comparison, as well as the preliminary measurements at the pilot laboratory NMC-A*STAR Singapore, were described in the Final Report of the APMP.PR-S1 comparison. The results of this bilateral comparison show that the NMISA's results lie within ±2% against the comparison reference values of APMP.PR-S1, which is a great improvement. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the APMP, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

HIV-negative male couples' attitudes about pre-exposure prophylaxis (PrEP) and using PrEP with a sexual agreement.

PubMed

Mitchell, Jason W; Lee, Ji-Young; Woodyatt, Cory; Bauermeister, José; Sullivan, Patrick; Stephenson, Rob

2016-08-01

One efficacious strategy to help prevent HIV is oral pre-exposure prophylaxis (PrEP), a daily regimen of antiretroviral treatment taken by HIV-negative individuals. Two of the recommendations of Centers for Disease Control and Prevention (CDC) guidelines for PrEP pertain to being in a relationship (i.e., male couples). Despite the recognition of how primary partners in male couples' relationships shape HIV risk and CDC's PrEP guidelines, there is a paucity of data that examine HIV-negative male couples' attitudes toward PrEP use and using PrEP with a sexual agreement. A sexual agreement is an explicit agreement made between two individuals about what sex and other related behaviors may occur within and outside of their relationship. In this qualitative study, we examine HIV-negative male couples' attitudes toward PrEP use and whether they thought PrEP could be integrated into a sexual agreement. Data for this study are drawn from couple-level interviews conducted in 2014 with 29 HIV-negative male couples who had a sexual agreement and were from Atlanta or Detroit. Both passive (e.g., flyers) and active (e.g., targeted Facebook advertisements) recruitment methods were used; the sample was stratified by agreement type. Thematic analysis was applied to identify the following themes regarding HIV-negative male couples' attitudes toward PrEP use: (1) PrEP and condom use; (2) concerns about PrEP (e.g., effectiveness, side effects, and promoting sexually risky behavior); and (3) accessibility of PrEP. Some thought PrEP could be a part of couples' agreement because it could help reduce sexual anxiety and sexual risk, and would help keep the couple safe. Others described PrEP use with an agreement as something for "others". Some were also concerned that incorporating PrEP could usurp the need for a sexual agreement in a couples' relationship. These themes highlight the need to improve informational messaging and promotion efforts about PrEP among HIV-negative male couples who may benefit from using it.

A novel capture-ELISA for detection of anti-neutrophil cytoplasmic antibodies (ANCA) based on c-myc peptide recognition in carboxy-terminally tagged recombinant neutrophil serine proteases.

PubMed

Lee, Augustine S; Finkielman, Javier D; Peikert, Tobias; Hummel, Amber M; Viss, Margaret A; Specks, Ulrich

2005-12-20

Testing for antineutrophil cytoplasmic antibodies (ANCA) reacting with proteinase 3 (PR3) is part of the routine diagnostic evaluation of patients with small vessel vasculitis. For PR3-ANCA detection, capture ELISAs are reported to be superior to direct ELISAs. Standard capture ELISAs, in which PR3 is anchored by anti-PR3 monoclonal antibodies (moAB), have two potential disadvantages. First, the capturing moAB may compete for epitopes recognized by some PR3-ANCA, causing occasional false-negative results. Second, the capture of recombinant PR3 mutant molecules becomes unpredictable as modifications of specific conformational epitopes may not only affect the binding of PR3-ANCA, but also the affinity of the capturing anti-PR3 moAB. Here, we describe a new capture ELISA, and its application for PR3-ANCA detection. This new assay is based on the standardized capture of a variety of different carboxy-terminally c-myc tagged recombinant ANCA target antigens using anti-c-myc coated ELISA plates. Antigen used include c-myc tagged human rPR3 variants (mature and pro-form conformations), mouse mature rPR3 and human recombinant neutrophil elastase. This new anti-c-myc-capture ELISA for PR3-ANCA detection has an intra- and inter-assay coefficient of variation of 3.6% to 7.7%, and 15.8% to 18.4%, respectively. The analytical sensitivity and specificity for PR3-ANCA positive serum samples were 93% and 100%, respectively when rPR3 with mature conformation was used as target antigen, and 83% and 100% when the pro-enzyme conformation was employed. In conclusion, this new anti-c-myc capture ELISA compares favorably to our standard capture ELISA for PR3-ANCA detection, enables the unified capture of different ANCA target antigens through binding to a c-myc tag, and allows capture of rPR3 mutants necessary for PR3-ANCA epitope mapping studies.

Differences in change in coping styles between good responders, moderate responders and non-responders to pulmonary rehabilitation.

PubMed

Stoilkova-Hartmann, Ana; Janssen, Daisy J A; Franssen, Frits M E; Wouters, Emiel F M

2015-12-01

Pulmonary rehabilitation (PR) improves exercise tolerance and health status in patients with chronic obstructive pulmonary disease (COPD). Data on the effects of PR on coping styles are limited. Aim of the present study was to compare changes in coping styles between patients who had a good, moderate and no improvement in either exercise tolerance or health status after PR. Coping styles of 439 COPD patients undergoing PR were assessed by the Utrecht Coping List (UCL) at baseline and after PR. Patients' pulmonary function, six-minute walking distance (6MWD), St. George's Respiratory Questionnaire (SGRQ) and Hospital Anxiety and Depression Scale (HADS-A and HADS-D) were recorded. Good, moderate and non-responders were defined on the basis of minimally clinically important difference (MCID) for SGRQ total score and/or 6MWD. Overall, 54.0% of the patients fulfilled the criteria for good responders, while 22.1% were moderate responders. Change in passive reaction pattern coping style differed significantly between good responders and non-responders following PR (p < 0.001). Moreover, within the groups, changes in coping styles after PR occurred among the good responders, whereas the majority of moderate responders' and non-responders' coping styles were not significantly influenced by PR. Good responders decreased their passive reaction pattern coping style in contrast to non-responders after PR. In general, PR did not change the coping among moderate and non-responders. Further research is warranted to determine whether including interventions targeting coping styles may modify coping behaviour of COPD patients, as well as improvement in exercise tolerance or health status after PR. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pattern association--a key to recognition of shark attacks.

PubMed

Cirillo, G; James, H

2004-12-01

Investigation of a number of shark attacks in South Australian waters has lead to recognition of pattern similarities on equipment recovered from the scene of such attacks. Six cases are presented in which a common pattern of striations has been noted.

Recognition vs Reverse Engineering in Boolean Concepts Learning

ERIC Educational Resources Information Center

Shafat, Gabriel; Levin, Ilya

2012-01-01

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

A Comprehensive Program to Reduce Rates of Hospital-Acquired Pressure Ulcers in a System of Community Hospitals.

PubMed

Englebright, Jane; Westcott, Ruth; McManus, Kathryn; Kleja, Kacie; Helm, Colleen; Korwek, Kimberly M; Perlin, Jonathan B

2018-03-01

The prevention of hospital-acquired pressure ulcers (PrUs) has significant consequences for patient outcomes and the cost of care. Providers are challenged with evaluating available evidence and best practices, then implementing programs and motivating change in various facility environments. In a large system of community hospitals, the Reducing Hospital Acquired-PrUs Program was developed to provide a toolkit of best practices, timely and appropriate data for focusing efforts, and continuous implementation support. Baseline data on PrU rates helped focus efforts on the most vulnerable patients and care situations. Facilities were empowered to use and adapt available resources to meet local needs and to share best practices for implementation across the system. Outcomes were measured by the rate of hospital-acquired PrUs, as gathered from patient discharge records. The rate of hospital-acquired stage III and IV PrUs decreased 66.3% between 2011 and 2013. Of the 149 participating facilities, 40 (27%) had zero hospital-acquired stage III and IV PrUs and 77 (52%) had a reduction in their PrU rate. Rates of all PrUs documented as present on admission did not change during this period. A comparison of different strategies used by the most successful facilities illustrated the necessity of facility-level flexibility and recognition of local workflows and patient demographics. Driven by the combination of a repository of evidence-based tools and best practices, readily available data on PrU rates, and local flexibility with processes, the Reducing Hospital Acquired-PrUs Program represents the successful operationalization of improvement in a wide variety of facilities.

Novel multiplex bead-based assay for detection of IDH1 and IDH2 mutations in myeloid malignancies.

PubMed

Shivarov, Velizar; Ivanova, Milena; Hadjiev, Evgueniy; Naumova, Elissaveta

2013-01-01

Isocitrate dehydrogenase 1 and 2 (IDH) mutations are frequently found in various cancer types such as gliomas, chondrosarcomas and myeloid malignancies. Their molecular detection has recently gained wide recognition in the diagnosis and prognosis of these neoplasms. For that purpose various molecular approaches have been used but a universally accepted method is still lacking. In this study we aimed to develop a novel bead-based liquid assay using Locked nucleic acids (LNA)-modified oligonucleotide probes for multiplexed detection of the most frequent IDH1 (p.R132C, p.R132G, p.R132H, p.R132L, p.R132S) and IDH2 (p.R140Q, p.R172K) mutations. The method includes four steps: 1) PCR amplification of the targeted fragments with biotinylated primers; 2) Direct hybridization to barcoded microbeads with specific LNA-modified oligonucleotide probes; 3) Incubation with phycoerythrin coupled streptavidin; 4) Acquisition of fluorescent intensities of each set of beads on a flow platform (LuminexCorp., USA). We tested the performance of the assay on both artificial plasmid constructs and on clinical samples from 114 patients with known or suspected myeloid malignancies. The method appeared to be superior to direct sequencing having a much higher sensitivity of 2.5% mutant alleles. Applying this method to patients' samples we identified a total of 9 mutations (one IDH1 p.R132C, seven IDH2 p.R140Q and one IDH2 p.R172K). In conclusion, this method could be successfully implemented in the diagnostic work-up for various tumors known to harbor IDH1/2 mutations (e.g. myeloid malignancies, gliomas, etc.). International initiatives are needed to validate the different existing methods for detection of IDH1/2 mutations in clinical settings.

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

The Relationship between Alcohol Drinking Patterns and Sleep Duration among Black and White Men and Women in the United States.

PubMed

Jackson, Chandra L; Gaston, Symielle A; Liu, Rui; Mukamal, Kenneth; Rimm, Eric B

2018-03-20

In the United States, racial minorities generally experience poorer cardiovascular health compared to whites, and differences in alcohol consumption and sleep could contribute to these disparities. With a nationally representative sample of 187,950 adults in the National Health Interview Survey from 2004 to 2015, we examined the relationship between alcohol-drinking patterns and sleep duration/quality by race and sex. Using Poisson regression models with robust variance, we estimated sex-specific prevalence ratios for each sleep duration/quality category among blacks compared to whites within categories of alcohol-drinking pattern, adjusting for socioeconomic status and other potential confounders. Across alcohol drinking patterns, blacks were less likely than whites to report recommended sleep of 7-<9 h/day. Short (PR = 1.30 [95% CI: 1.22-1.39]) and long (PR = 1.30 [95% CI: 1.07-1.58]) sleep were 30% more prevalent among black-male infrequent heavy drinkers compared to white-male infrequent heavy drinkers. Short (PR = 1.27 [95% CI: 1.21-1.34]) sleep was more prevalent among black-female infrequent heavy drinkers compared to white-female infrequent heavy drinkers, but there was no difference for long sleep (PR = 1.09 [95% CI: 0.97-1.23]). Black female infrequent moderate drinkers, however, had a 16% higher (PR = 1.16 [95% CI: 1.01-1.33]) prevalence of long sleep compared to their white counterparts. Environmental, social, and biological factors contributing to these findings, along with their impact on disparate health outcomes, should be studied in greater detail.

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Optical Pattern Recognition for Missile Guidance.

DTIC Science & Technology

1982-11-15

directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

Recognition as Support for Reasoning about Horizontal Motion: A Further Resource for School Science?

ERIC Educational Resources Information Center

Howe, Christine; Taylor Tavares, Joana; Devine, Amy

2016-01-01

Background: Even infants can recognize whether patterns of motion are or are not natural, yet an acknowledged challenge for science education is to promote adequate reasoning about such patterns. Since research indicates linkage between the conceptual bases of recognition and reasoning, it seems possible that recognition can be engaged to support…

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

A protocol for searching the most probable phase-retrieved maps in coherent X-ray diffraction imaging by exploiting the relationship between convergence of the retrieved phase and success of calculation.

PubMed

Sekiguchi, Yuki; Hashimoto, Saki; Kobayashi, Amane; Oroguchi, Tomotaka; Nakasako, Masayoshi

2017-09-01

Coherent X-ray diffraction imaging (CXDI) is a technique for visualizing the structures of non-crystalline particles with size in the submicrometer to micrometer range in material sciences and biology. In the structural analysis of CXDI, the electron density map of a specimen particle projected along the direction of the incident X-rays can be reconstructed only from the diffraction pattern by using phase-retrieval (PR) algorithms. However, in practice, the reconstruction, relying entirely on the computational procedure, sometimes fails because diffraction patterns miss the data in small-angle regions owing to the beam stop and saturation of the detector pixels, and are modified by Poisson noise in X-ray detection. To date, X-ray free-electron lasers have allowed us to collect a large number of diffraction patterns within a short period of time. Therefore, the reconstruction of correct electron density maps is the bottleneck for efficiently conducting structure analyses of non-crystalline particles. To automatically address the correctness of retrieved electron density maps, a data analysis protocol to extract the most probable electron density maps from a set of maps retrieved from 1000 different random seeds for a single diffraction pattern is proposed. Through monitoring the variations of the phase values during PR calculations, the tendency for the PR calculations to succeed when the retrieved phase sets converged on a certain value was found. On the other hand, if the phase set was in persistent variation, the PR calculation tended to fail to yield the correct electron density map. To quantify this tendency, here a figure of merit for the variation of the phase values during PR calculation is introduced. In addition, a PR protocol to evaluate the similarity between a map of the highest figure of merit and other independently reconstructed maps is proposed. The protocol is implemented and practically examined in the structure analyses for diffraction patterns from aggregates of gold colloidal particles. Furthermore, the feasibility of the protocol in the structure analysis of organelles from biological cells is examined.

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

PubMed

Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats displayed a significant interaction between the two groups and the number of available objects suggesting impairment in a pattern completion function for object cues. Copyright © 2015 Elsevier Inc. All rights reserved.

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed Central

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-01-01

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Empathy and Facial Expression Recognition in Children With and Without Attention-Deficit/Hyperactivity Disorder: Effects of Stimulant Medication on Empathic Skills in Children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Gumustas, Funda; Yilmaz, Ibrahim; Yulaf, Yasemin; Gokce, Sebla; Sabuncuoglu, Osman

2017-06-01

The aim of this study was to compare children and adolescents with attention-deficit/hyperactivity disorder (ADHD) to healthy children and adolescents in terms of state and trait empathy and emotion expression recognition skills. The goal was also to determine whether there are changes in emotion recognition and empathy measures in children with ADHD after methylphenidate (MPH) treatment. The research sample consisted of outpatient drug-naive children and adolescents between the age of 8 and 14 years (n = 65) with ADHD according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. criteria, and healthy children and adolescents of the same age (n = 61). Scores of the oppositional problems (OPs) and conduct problems (CPs) were obtained to evaluate their impact on children's empathy skills with the Child Behavior Checklist. Self-reported (Bryant Index of Empathy, BEI) and parent-reported (Griffith Empathy Measurement-Parent Rating, GEM-PR) scales were used to evaluate trait empathy. The Empathy Response Task (ERT) was used to evaluate state empathy, and the Diagnostic Analysis of Nonverbal Accuracy-2 (DANVA-2) was used to evaluate facial expression recognition skills. The scales and tests were repeated after 12 weeks of MPH treatment in the ADHD group. There were no significant statistical differences in trait empathy skills evaluated by parent-reported and self-reported measures, ERT, and DANVA-2 scores. In self-reported measures, the girls had higher scores than boys. From the results of the regression analysis, it was concluded that OPs were not associated with the measures. However, CPs were associated with the scores of the BEI, GEM-PR, and the match scores of the ERT. The average dosage of MPH in the group with ADHD was 0.83 ± 0.21 mg/(kg·d). While there was no change in the BEI and GEM-PR scores after 12 weeks of treatment, there was a significant increase in the ERT interpretation subscore and a significant decrease in the recognition error of anger and sadness expressions in the DANVA-2. The findings of our study suggest that children with ADHD have similar levels of trait and state empathy skills and facial expressions as healthy controls and CPs negatively affect their empathy skills. MPH treatment does not change trait empathy skills, yet there are some improvements in state empathy skills.

Solution NMR studies provide structural basis for endotoxin pattern recognition by the innate immune receptor CD14

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Seth; Chen Bin; Holbrook, Kristen

CD14 functions as a key pattern recognition receptor for a diverse array of Gram-negative and Gram-positive cell-wall components in the host innate immune response by binding to pathogen-associated molecular patterns (PAMPs) at partially overlapping binding site(s). To determine the potential contribution of CD14 residues in this pattern recognition, we have examined using solution NMR spectroscopy, the binding of three different endotoxin ligands, lipopolysaccharide, lipoteichoic acid, and a PGN-derived compound, muramyl dipeptide to a {sup 15}N isotopically labeled 152-residue N-terminal fragment of sCD14 expressed in Pichia pastoris. Mapping of NMR spectral changes upon addition of ligands revealed that the pattern ofmore » residues affected by binding of each ligand is partially similar and partially different. This first direct structural observation of the ability of specific residue combinations of CD14 to differentially affect endotoxin binding may help explain the broad specificity of CD14 in ligand recognition and provide a structural basis for pattern recognition. Another interesting finding from the observed spectral changes is that the mode of binding may be dynamically modulated and could provide a mechanism for binding endotoxins with structural diversity through a common binding site.« less

Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools.

PubMed

Canizo, Brenda V; Escudero, Leticia B; Pérez, María B; Pellerano, Roberto G; Wuilloud, Rodolfo G

2018-03-01

The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Puerto Rican women's perceptions of heart disease risk.

PubMed

Lange, Jean; Evans-Benard, Sharon; Cooper, Jennifer; Fahey, Ellen; Kalapos, Marlain; Tice, Donna; Wang-D'Amato, Nancy; Watsky, Nancy

2009-11-01

Women frequently fail to recognize that coronary heart disease (CHD), not breast cancer, is the primary cause of female mortality. CHD mortality among U.S. mainland Puerto Rican (PR) women is second only to African American women. It is unknown what PR women understand about their risk, what factors they believe contribute to CHD, or whether they know the atypical symptoms often experienced by women. Most CHD studies exclude Hispanic women. Those that do often aggregate their results, making subgroup variations invisible. This study explored awareness of CHD symptoms, risks, and help-seeking behaviors among 12 PR women. Focus group methodology revealed that participants were unaware of their risk and had misconceptions about CHD symptoms and contributing factors. Barriers to early recognition and treatment included lack of knowledge, gender role conflict (caregiver vs. care recipient), and fears of falsely alarming family members or the embarrassment of feeling "dismissed" by health care providers.

Interspecific Sex in Grass Smuts and the Genetic Diversity of Their Pheromone-Receptor System

PubMed Central

Kellner, Ronny; Vollmeister, Evelyn; Feldbrügge, Michael; Begerow, Dominik

2011-01-01

The grass smuts comprise a speciose group of biotrophic plant parasites, so-called Ustilaginaceae, which are specifically adapted to hosts of sweet grasses, the Poaceae family. Mating takes a central role in their life cycle, as it initiates parasitism by a morphological and physiological transition from saprobic yeast cells to pathogenic filaments. As in other fungi, sexual identity is determined by specific genomic regions encoding allelic variants of a pheromone-receptor (PR) system and heterodimerising transcription factors. Both operate in a biphasic mating process that starts with PR–triggered recognition, directed growth of conjugation hyphae, and plasmogamy of compatible mating partners. So far, studies on the PR system of grass smuts revealed diverse interspecific compatibility and mating type determination. However, many questions concerning the specificity and evolutionary origin of the PR system remain unanswered. Combining comparative genetics and biological approaches, we report on the specificity of the PR system and its genetic diversity in 10 species spanning about 100 million years of mating type evolution. We show that three highly syntenic PR alleles are prevalent among members of the Ustilaginaceae, favouring a triallelic determination as the plesiomorphic characteristic of this group. Furthermore, the analysis of PR loci revealed increased genetic diversity of single PR locus genes compared to genes of flanking regions. Performing interspecies sex tests, we detected a high potential for hybridisation that is directly linked to pheromone signalling as known from intraspecies sex. Although the PR system seems to be optimised for intraspecific compatibility, the observed functional plasticity of the PR system increases the potential for interspecific sex, which might allow the hybrid-based genesis of newly combined host specificities. PMID:22242007

Southern African guidelines on the safe use of pre-exposure prophylaxis in persons at risk of acquiring HIV-1 infection

PubMed Central

Rebe, Kevin; Venter, Francois; Maartens, Gary; Moorhouse, Michelle; Conradie, Francesca; Wallis, Carole; Black, Vivian; Harley, Beth; Eakles, Robyn

2016-01-01

The Southern African HIV Clinicians Society published its first set of oral pre-exposure prophylaxis (PrEP) guidelines in June 2012 for men who have sex with men (MSM) who are at risk of HIV infection. With the flurry of data that has been generated in PrEP clinical research since the first guideline, it became evident that there was a need to revise and expand the PrEP guidelines with new evidence of safety and efficacy of PrEP in several populations, including MSM, transgender persons, heterosexual men and women, HIV-serodiscordant couples and people who inject drugs. This need is particularly relevant following the World Health Organization (WHO) Consolidated Treatment Guidelines released in September 2015. These guidelines advise that PrEP is a highly effective, safe, biomedical option for HIV prevention that can be incorporated with other combination prevention strategies in Southern Africa, given the high prevalence of HIV in the region. PrEP should be tailored to populations at highest risk of HIV acquisition, whilst further data from studies in the region accrue to guide optimal deployment to realise the greatest impact regionally. PrEP may be used intermittently during periods of perceived HIV acquisition risk, rather than continually and lifelong, as is the case with antiretroviral treatment. Recognition and accurate measurement of potential risk in individuals and populations also warrants discussion, but are not extensively covered in these guidelines. PMID:29568613

Pulmonary rehabilitation: WHAT WE KNOW AND WHAT WE NEED TO KNOW.

PubMed

Nici, Linda; Raskin, Jonathan; Rochester, Carolyn L; Bourbeau, Jean C; Carlin, Brian W; Casaburi, Richard; Celli, Bartolome R; Cote, Claudia; Crouch, Rebecca H; Diez-Morales, Luis F; Donner, Claudio F; Fahy, Bonnie F; Garvey, Chris; Goldstein, Roger; Lane-Reticker, Alison; Lareau, Suzanne C; Make, Barry; Maltais, François; McCormick, James; Morgan, Michael D L; Ries, Andrew; Troosters, Thierry; ZuWallack, Richard

2009-01-01

The multidisciplinary treatment of pulmonary rehabilitation (PR), which includes exercise training, self-management education, and psychosocial and nutritional intervention, is now a standard of care for chronic obstructive pulmonary disease (COPD) and has been incorporated into major guidelines. We must now focus efforts on improving its impact and widening its applicability. What is the direction of PR; where does it fit in the comprehensive care of the COPD patient; and how can clinicians best apply this important intervention? This was the charge of the roundtable discussion, Pulmonary Rehabilitation: Moving Forward, involving 20 experts from North America and Europe, which was convened in Fort Lauderdale, Florida, in early 2008. It is not meant to be an exhaustive review; rather, this report summarizes the roundtable proceedings, while providing direction to best position PR into the continuum of COPD care. By consensus, it was agreed upon that although PR is effective for other chronic respiratory diseases, the discussion focus was COPD since most of the evidence base and patient referral are for this disease. These proceedings provide insight into 3 broad areas appropriate for investigation or implementation: positioning PR in an integrated care model for COPD patients; improving the effectiveness of this intervention; and expanding the recognition, application, and accessibility to PR. It is the hope that this document will provide a catalyst for clinicians, investigators, and healthcare policy makers to help realize these goals as well as serve to suggest important areas for future research and development in PR.

Use of Murine Bioassay to Resolve Ovine Transmissible Spongiform Encephalopathy Cases Showing a Bovine Spongiform Encephalopathy Molecular Profile

PubMed Central

Beck, Katy E; Sallis, Rosemary E; Lockey, Richard; Vickery, Christopher M; Béringue, Vincent; Laude, Hubert; Holder, Thomas M; Thorne, Leigh; Terry, Linda A; Tout, Anna C; Jayasena, Dhanushka; Griffiths, Peter C; Cawthraw, Saira; Ellis, Richard; Balkema-Buschmann, Anne; Groschup, Martin H; Simmons, Marion M; Spiropoulos, John

2012-01-01

Two cases of unusual transmissible spongiform encephalopathy (TSE) were diagnosed on the same farm in ARQ/ARQ PrP sheep showing attributes of both bovine spongiform encephalopathy (BSE) and scrapie. These cases, UK-1 and UK-2, were investigated further by transmissions to wild-type and ovine transgenic mice. Lesion profiles (LP) on primary isolation and subpassage, incubation period (IP) of disease, PrPSc immunohistochemical (IHC) deposition pattern and Western blot profiles were used to characterize the prions causing disease in these sheep. Results showed that both cases were compatible with scrapie. The presence of BSE was contraindicated by the following: LP on primary isolation in RIII and/or MR (modified RIII) mice; IP and LP after serial passage in wild-type mice; PrPSc deposition pattern in wild-type mice; and IP and Western blot data in transgenic mice. Furthermore, immunohistochemistry (IHC) revealed that each case generated two distinct PrPSc deposition patterns in both wild-type and transgenic mice, suggesting that two scrapie strains coexisted in the ovine hosts. Critically, these data confirmed the original differential IHC categorization that these UK-1 and UK-2 cases were not compatible with BSE. PMID:21919992

Forecasting of hourly load by pattern recognition in a small area power system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

Optical character recognition based on nonredundant correlation measurements.

PubMed

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

PubMed

Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

2017-11-01

Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

A strip chart recorder pattern recognition tool kit for Shuttle operations

NASA Technical Reports Server (NTRS)

Hammen, David G.; Moebes, Travis A.; Shelton, Robert O.; Savely, Robert T.

1993-01-01

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Modulation of Progesterone Receptor Isoform Expression in Pregnant Human Myometrium

PubMed Central

2017-01-01

Background. Regulation of myometrial progesterone receptor (PR) expression is an unresolved issue central to understanding the mechanism of functional progesterone withdrawal and initiation of labor in women. Objectives. To determine whether pregnant human myometrium undergoes culture-induced changes in PR isoform expression ex situ and, further, to determine if conditions approaching the in vivo environment stabilise PR isoform expression in culture. Methods. Term nonlaboring human myometrial tissues were cultured under specific conditions: serum supplementation, steroids, stretch, cAMP, PMA, PGF2α, NF-κB inhibitors, or TSA. Following 48 h culture, PR-T, PR-A, and PR-B mRNA levels were determined using qRT-PCR. PR-A/PR-B ratios were calculated. Results. PR-T and PR-A expression and the PR-A/PR-B ratio significantly increased in culture. Steroids prevented the culture-induced increase in PR-T and PR-A expression. Stretch blocked the effects of steroids on PR-T and PR-A expression. PMA further increased the PR-A/PR-B ratio, while TSA blocked culture-induced increases of PR-A expression and the PR-A/PR-B ratio. Conclusion. Human myometrial tissue in culture undergoes changes in PR gene expression consistent with transition toward a laboring phenotype. TSA maintained the nonlaboring PR isoform expression pattern. This suggests that preserving histone and/or nonhistone protein acetylation is critical for maintaining the progesterone dependent quiescent phenotype of human myometrium in culture. PMID:28540297

Using pattern recognition as a method for predicting extreme events in natural and socio-economic systems

NASA Astrophysics Data System (ADS)

Intriligator, M.

2011-12-01

Vladimir (Volodya) Keilis-Borok has pioneered the use of pattern recognition as a technique for analyzing and forecasting developments in natural as well as socio-economic systems. Keilis-Borok's work on predicting earthquakes and landslides using this technique as a leading geophysicist has been recognized around the world. Keilis-Borok has also been a world leader in the application of pattern recognition techniques to the analysis and prediction of socio-economic systems. He worked with Allan Lichtman of American University in using such techniques to predict presidential elections in the U.S. Keilis-Borok and I have worked together with others on the use of pattern recognition techniques to analyze and to predict socio-economic systems. We have used this technique to study the pattern of macroeconomic indicators that would predict the end of an economic recession in the U.S. We have also worked with officers in the Los Angeles Police Department to use this technique to predict surges of homicides in Los Angeles.

Running Improves Pattern Separation during Novel Object Recognition.

PubMed

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Influenza virus site recognized by a murine helper T cell specific for H1 strains. Localization to a nine amino acid sequence in the hemagglutinin molecule.

PubMed

Hackett, C J; Dietzschold, B; Gerhard, W; Ghrist, B; Knorr, R; Gillessen, D; Melchers, F

1983-08-01

The functional helper T cell line Vir-2, derived from a PR8 (H1N1) influenza virus-immunized BALB/c mouse, proliferates in response to syngeneic antigen-presenting cells and naturally occurring strains of subtype H1 human influenza virus from 1934-1957 and 1977-1980 isolates. A conserved region of the hemagglutinin molecule around amino acid position 115 in the heavy chain (HA1) was implicated as being important in this recognition by the lack of stimulatory activity associated with a glutamic acid to lysine substitution at position 115 in the laboratory mutant RV6, derived from wild-type PR8. Characterization of the stimulatory determinant on the wild-type hemagglutinin molecule was then undertaken using cleavage products and synthetic peptides. Vir-2 cells recognized the reduced and alkylated purified HA1 of PR8 virus, and this reactivity was retained after cleavage at methionine and tryptophan residues. High-pressure liquid chromatography separation of cleavage fragments indicated that a short sequence of the HA1 containing residue 115 was being recognized. This recognition was localized to a nine amino acid segment (positions 111-119) by assaying stimulation with synthetic peptide homologues of different lengths from that region. As with native hemagglutinin, Vir-2 cells responded to active peptides when presented by H-2d but not H-2k antigen-presenting cells.

A Compact Prototype of an Optical Pattern Recognition System

NASA Technical Reports Server (NTRS)

Jin, Y.; Liu, H. K.; Marzwell, N. I.

1996-01-01

In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Photonic correlator pattern recognition: Application to autonomous docking

NASA Technical Reports Server (NTRS)

Sjolander, Gary W.

1991-01-01

Optical correlators for real-time automatic pattern recognition applications have recently become feasible due to advances in high speed devices and filter formulation concepts. The devices are discussed in the context of their use in autonomous docking.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Overcoming etch challenges related to EUV based patterning (Conference Presentation)

NASA Astrophysics Data System (ADS)

Metz, Andrew W.; Cottle, Hongyun; Honda, Masanobu; Morikita, Shinya; Kumar, Kaushik A.; Biolsi, Peter

2017-04-01

Research and development activities related to Extreme Ultra Violet [EUV] defined patterning continue to grow for < 40 nm pitch applications. The confluence of high cost and extreme process control challenges of Self-Aligned Quad Patterning [SAQP] with continued momentum for EUV ecosystem readiness could provide cost advantages in addition to improved intra-level overlay performance relative to multiple patterning approaches. However, Line Edge Roughness [LER] and Line Width Roughness [LWR] performance of EUV defined resist images are still far from meeting technology needs or ITRS spec performance. Furthermore, extreme resist height scaling to mitigate flop over exacerbates the plasma etch trade-offs related to traditional approaches of PR smoothing, descum implementation and maintaining 2D aspect ratios of short lines or elliptical contacts concurrent with ultra-high photo resist [PR] selectivity. In this paper we will discuss sources of LER/LWR, impact of material choice, integration, and innovative plasma process techniques and describe how TELTM VigusTM CCP Etchers can enhance PR selectivity, reduce LER/LWR, and maintain 2D aspect ratio of incoming patterns. Beyond traditional process approaches this paper will show the utility of: [1] DC Superposition in enhancing EUV resist hardening and selectivity, increasing resistance to stress induced PR line wiggle caused by CFx passivation, and mitigating organic planarizer wiggle; [2] Quasi Atomic Layer Etch [Q-ALE] for ARC open eliminating the tradeoffs between selectivity, CD, and shrink ratio control; and [3] ALD+Etch FUSION technology for feature independent CD shrink and LER reduction. Applicability of these concepts back transferred to 193i based lithography is also confirmed.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Large-memory real-time multichannel multiplexed pattern recognition

NASA Technical Reports Server (NTRS)

Gregory, D. A.; Liu, H. K.

1984-01-01

The principle and experimental design of a real-time multichannel multiplexed optical pattern recognition system via use of a 25-focus dichromated gelatin holographic lens (hololens) are described. Each of the 25 foci of the hololens may have a storage and matched filtering capability approaching that of a single-lens correlator. If the space-bandwidth product of an input image is limited, as is true in most practical cases, the 25-focus hololens system has 25 times the capability of a single lens. Experimental results have shown that the interfilter noise is not serious. The system has already demonstrated the storage and recognition of over 70 matched filters - which is a larger capacity than any optical pattern recognition system reported to date.

Listening for Recollection: A Multi-Voxel Pattern Analysis of Recognition Memory Retrieval Strategies

PubMed Central

Quamme, Joel R.; Weiss, David J.; Norman, Kenneth A.

2010-01-01

Recent studies of recognition memory indicate that subjects can strategically vary how much they rely on recollection of specific details vs. feelings of familiarity when making recognition judgments. One possible explanation of these results is that subjects can establish an internally directed attentional state (“listening for recollection”) that enhances retrieval of studied details; fluctuations in this attentional state over time should be associated with fluctuations in subjects’ recognition behavior. In this study, we used multi-voxel pattern analysis of fMRI data to identify brain regions that are involved in listening for recollection. We looked for brain regions that met the following criteria: (1) Distinct neural patterns should be present when subjects are instructed to rely on recollection vs. familiarity, and (2) fluctuations in these neural patterns should be related to recognition behavior in the manner predicted by dual-process theories of recognition: Specifically, the presence of the recollection pattern during the pre-stimulus interval (indicating that subjects are “listening for recollection” at that moment) should be associated with a selective decrease in false alarms to related lures. We found that pre-stimulus activity in the right supramarginal gyrus met all of these criteria, suggesting that this region proactively establishes an internally directed attentional state that fosters recollection. We also found other regions (e.g., left middle temporal gyrus) where the pattern of neural activity was related to subjects’ responding to related lures after stimulus onset (but not before), suggesting that these regions implement processes that are engaged in a reactive fashion to boost recollection. PMID:20740073

Auditory orientation in crickets: Pattern recognition controls reactive steering

NASA Astrophysics Data System (ADS)

Poulet, James F. A.; Hedwig, Berthold

2005-10-01

Many groups of insects are specialists in exploiting sensory cues to locate food resources or conspecifics. To achieve orientation, bees and ants analyze the polarization pattern of the sky, male moths orient along the females' odor plume, and cicadas, grasshoppers, and crickets use acoustic signals to locate singing conspecifics. In comparison with olfactory and visual orientation, where learning is involved, auditory processing underlying orientation in insects appears to be more hardwired and genetically determined. In each of these examples, however, orientation requires a recognition process identifying the crucial sensory pattern to interact with a localization process directing the animal's locomotor activity. Here, we characterize this interaction. Using a sensitive trackball system, we show that, during cricket auditory behavior, the recognition process that is tuned toward the species-specific song pattern controls the amplitude of auditory evoked steering responses. Females perform small reactive steering movements toward any sound patterns. Hearing the male's calling song increases the gain of auditory steering within 2-5 s, and the animals even steer toward nonattractive sound patterns inserted into the speciesspecific pattern. This gain control mechanism in the auditory-to-motor pathway allows crickets to pursue species-specific sound patterns temporarily corrupted by environmental factors and may reflect the organization of recognition and localization networks in insects. localization | phonotaxis

Receptor-like cytoplasmic kinases are pivotal components in pattern recognition receptor-mediated signaling in plant immunity.

PubMed

Yamaguchi, Koji; Yamada, Kenta; Kawasaki, Tsutomu

2013-10-01

Innate immunity is generally initiated with recognition of conserved pathogen-associated molecular patterns (PAMPs). PAMPs are perceived by pattern recognition receptors (PRRs), leading to activation of a series of immune responses, including the expression of defense genes, ROS production and activation of MAP kinase. Recent progress has indicated that receptor-like cytoplasmic kinases (RLCKs) are directly activated by ligand-activated PRRs and initiate pattern-triggered immunity (PTI) in both Arabidopsis and rice. To suppress PTI, pathogens inhibit the RLCKs by many types of effectors, including AvrAC, AvrPphB and Xoo1488. In this review, we summarize recent advances in RLCK-mediated PTI in plants.

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Students' Dichotomous Experiences of the Illuminating and Illusionary Nature of Pattern Recognition in Mathematics

ERIC Educational Resources Information Center

Mhlolo, Michael Kainose

2016-01-01

The concept of pattern recognition lies at the heart of numerous deliberations concerned with new mathematics curricula, because it is strongly linked to improved generalised thinking. However none of these discussions has made the deceptive nature of patterns an object of exploration and understanding. Yet there is evidence showing that pattern…

Solar-panel and parasol strategies shape the proteorhodopsin distribution pattern in marine Flavobacteriia.

PubMed

Kumagai, Yohei; Yoshizawa, Susumu; Nakajima, Yu; Watanabe, Mai; Fukunaga, Tsukasa; Ogura, Yoshitoshi; Hayashi, Tetsuya; Oshima, Kenshiro; Hattori, Masahira; Ikeuchi, Masahiko; Kogure, Kazuhiro; DeLong, Edward F; Iwasaki, Wataru

2018-05-01

Proteorhodopsin (PR) is a light-driven proton pump that is found in diverse bacteria and archaea species, and is widespread in marine microbial ecosystems. To date, many studies have suggested the advantage of PR for microorganisms in sunlit environments. The ecophysiological significance of PR is still not fully understood however, including the drivers of PR gene gain, retention, and loss in different marine microbial species. To explore this question we sequenced 21 marine Flavobacteriia genomes of polyphyletic origin, which encompassed both PR-possessing as well as PR-lacking strains. Here, we show that the possession or alternatively the lack of PR genes reflects one of two fundamental adaptive strategies in marine bacteria. Specifically, while PR-possessing bacteria utilize light energy ("solar-panel strategy"), PR-lacking bacteria exclusively possess UV-screening pigment synthesis genes to avoid UV damage and would adapt to microaerobic environment ("parasol strategy"), which also helps explain why PR-possessing bacteria have smaller genomes than those of PR-lacking bacteria. Collectively, our results highlight the different strategies of dealing with light, DNA repair, and oxygen availability that relate to the presence or absence of PR phototrophy.

Effects of Hearing Loss on Heart-Rate Variability and Skin Conductance Measured During Sentence Recognition in Noise

PubMed Central

Mackersie, Carol L.; MacPhee, Imola X.; Heldt, Emily W.

2014-01-01

SHORT SUMMARY (précis) Sentence recognition by participants with and without hearing loss was measured in quiet and in babble noise while monitoring two autonomic nervous system measures: heart-rate variability and skin conductance. Heart-rate variability decreased under difficult listening conditions for participants with hearing loss, but not for participants with normal hearing. Skin conductance noise reactivity was greater for those with hearing loss, than for those with normal hearing, but did not vary with the signal-to-noise ratio. Subjective ratings of workload/stress obtained after each listening condition were similar for the two participant groups. PMID:25170782

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

Facial emotion recognition in patients with focal and diffuse axonal injury.

PubMed

Yassin, Walid; Callahan, Brandy L; Ubukata, Shiho; Sugihara, Genichi; Murai, Toshiya; Ueda, Keita

2017-01-01

Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Application of pattern recognition techniques to crime analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Directing an appropriate immune response: the role of defense collagens and other soluble pattern recognition molecules.

PubMed

Fraser, D A; Tenner, A J

2008-02-01

Defense collagens and other soluble pattern recognition receptors contain the ability to recognize and bind molecular patterns associated with pathogens (PAMPs) or apoptotic cells (ACAMPs) and signal appropriate effector-function responses. PAMP recognition by defense collagens C1q, MBL and ficolins leads to rapid containment of infection via complement activation. However, in the absence of danger, such as during the clearance of apoptotic cells, defense collagens such as C1q, MBL, ficolins, SP-A, SP-D and even adiponectin have all been shown to facilitate enhanced phagocytosis and modulate induction of cytokines towards an anti-inflammatory profile. In this way, cellular debris can be removed without provoking an inflammatory immune response which may be important in the prevention of autoimmunity and/or resolving inflammation. Indeed, deficiencies and/or knock-out mouse studies have highlighted critical roles for soluble pattern recognition receptors in the clearance of apoptotic bodies and protection from autoimmune diseases along with mediating protection from specific infections. Understanding the mechanisms involved in defense collagen and other soluble pattern recognition receptor modulation of the immune response may provide important novel insights into therapeutic targets for infectious and/or autoimmune diseases and additionally may identify avenues for more effective vaccine design.

Investigation on the structural, magnetic and magnetocaloric properties of nanocrystalline Pr-deficient Pr1-xSrxMnO3-δ manganites

NASA Astrophysics Data System (ADS)

Arun, B.; Athira, M.; Akshay, V. R.; Sudakshina, B.; Mutta, Geeta R.; Vasundhara, M.

2018-02-01

We have investigated the structural, magnetic and magnetocaloric properties of nanocrystalline Pr-deficient Pr1-xSrxMnO3-δ Perovskite manganites. Rietveld refinement of the X-ray powder diffraction patterns confirms that all the studied compounds have crystallized into an orthorhombic structure with Pbnm space group. Transmission electron microscopy analysis reveals nanocrystalline compounds with crystallite size less than 50 nm. The selected area electron diffraction patterns reveal the highly crystalline nature of the compounds and energy dispersive X-ray spectroscopic analysis shows that the obtained compositions are nearly identical with the nominal one. The oxygen stoichiometry is estimated by iodometric titration method and stoichiometric compositions are confirmed by X-ray Fluorescence Spectrometry analysis. A large bifurcation is observed in the ZFC/FC curves and Arrott plots not show a linear relation but have a convex curvature nature. The temperature dependence of inverse magnetic susceptibility at higher temperature confirms the existence of ferromagnetic clusters. The experimental results reveal that the reduction of crystallite size to nano metric scale in Pr-deficient manganites adversely influences structural, magnetic and magnetocaloric properties as compared to its bulk counterparts reported earlier.

Visual scanning behavior is related to recognition performance for own- and other-age faces

PubMed Central

Proietti, Valentina; Macchi Cassia, Viola; dell’Amore, Francesca; Conte, Stefania; Bricolo, Emanuela

2015-01-01

It is well-established that our recognition ability is enhanced for faces belonging to familiar categories, such as own-race faces and own-age faces. Recent evidence suggests that, for race, the recognition bias is also accompanied by different visual scanning strategies for own- compared to other-race faces. Here, we tested the hypothesis that these differences in visual scanning patterns extend also to the comparison between own and other-age faces and contribute to the own-age recognition advantage. Participants (young adults with limited experience with infants) were tested in an old/new recognition memory task where they encoded and subsequently recognized a series of adult and infant faces while their eye movements were recorded. Consistent with findings on the other-race bias, we found evidence of an own-age bias in recognition which was accompanied by differential scanning patterns, and consequently differential encoding strategies, for own-compared to other-age faces. Gaze patterns for own-age faces involved a more dynamic sampling of the internal features and longer viewing time on the eye region compared to the other regions of the face. This latter strategy was extensively employed during learning (vs. recognition) and was positively correlated to discriminability. These results suggest that deeply encoding the eye region is functional for recognition and that the own-age bias is evident not only in differential recognition performance, but also in the employment of different sampling strategies found to be effective for accurate recognition. PMID:26579056

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

Comparing the visual spans for faces and letters

PubMed Central

He, Yingchen; Scholz, Jennifer M.; Gage, Rachel; Kallie, Christopher S.; Liu, Tingting; Legge, Gordon E.

2015-01-01

The visual span—the number of adjacent text letters that can be reliably recognized on one fixation—has been proposed as a sensory bottleneck that limits reading speed (Legge, Mansfield, & Chung, 2001). Like reading, searching for a face is an important daily task that involves pattern recognition. Is there a similar limitation on the number of faces that can be recognized in a single fixation? Here we report on a study in which we measured and compared the visual-span profiles for letter and face recognition. A serial two-stage model for pattern recognition was developed to interpret the data. The first stage is characterized by factors limiting recognition of isolated letters or faces, and the second stage represents the interfering effect of nearby stimuli on recognition. Our findings show that the visual span for faces is smaller than that for letters. Surprisingly, however, when differences in first-stage processing for letters and faces are accounted for, the two visual spans become nearly identical. These results suggest that the concept of visual span may describe a common sensory bottleneck that underlies different types of pattern recognition. PMID:26129858

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Training Strategies for Mitigating the Effect of Proportional Control on Classification in Pattern Recognition Based Myoelectric Control

PubMed Central

Scheme, Erik; Englehart, Kevin

2013-01-01

The performance of pattern recognition based myoelectric control has seen significant interest in the research community for many years. Due to a recent surge in the development of dexterous prosthetic devices, determining the clinical viability of multifunction myoelectric control has become paramount. Several factors contribute to differences between offline classification accuracy and clinical usability, but the overriding theme is that the variability of the elicited patterns increases greatly during functional use. Proportional control has been shown to greatly improve the usability of conventional myoelectric control systems. Typically, a measure of the amplitude of the electromyogram (a rectified and smoothed version) is used to dictate the velocity of control of a device. The discriminatory power of myoelectric pattern classifiers, however, is also largely based on amplitude features of the electromyogram. This work presents an introductory look at the effect of contraction strength and proportional control on pattern recognition based control. These effects are investigated using typical pattern recognition data collection methods as well as a real-time position tracking test. Training with dynamically force varying contractions and appropriate gain selection is shown to significantly improve (p<0.001) the classifier’s performance and tolerance to proportional control. PMID:23894224

The Human Periallocortex: Layer Pattern in Presubiculum, Parasubiculum and Entorhinal Cortex. A Review

PubMed Central

Insausti, Ricardo; Muñoz-López, Mónica; Insausti, Ana M.; Artacho-Pérula, Emilio

2017-01-01

The cortical mantle is not homogeneous, so that three types of cortex can be distinguished: allocortex, periallocortex and isocortex. The main distinction among those three types is based on morphological differences, in particular the number of layers, overall organization, appearance, etc., as well as its connectivity. Additionally, in the phylogenetic scale, this classification is conserved among different mammals. The most primitive and simple cortex is the allocortex, which is characterized by the presence of three layers, with one cellular main layer; it is continued by the periallocortex, which presents six layers, although with enough differences in the layer pattern to separate three different fields: presubiculum (PrS), parasubiculum (PaS), and entorhinal cortex (EC). The closest part to the allocortex (represented by the subiculum) is the PrS, which shows outer (layers I–III) and inner (V–VI) principal layers (lamina principalis externa and lamina principalis interna), both separated by a cell poor band, parallel to the pial surface (layer IV or lamina dissecans). This layer organization is present throughout the anterior-posterior axis. The PaS continues the PrS, but its rostrocaudal extent is shorter than the PrS. The organization of the PaS shows the layer pattern more clearly than in the PrS. Up to six layers are recognizable in the PaS, with layer IV as lamina dissecans between superficial (layers I–III) and deep (V–VI) layers, as in the PrS. The EC presents even more clearly the layer pattern along both mediolateral and rostrocaudal extent. The layer pattern is a thick layer I, layer II in islands, layer III medium pyramids, layer IV as lamina dissecans (not present throughout the EC extent), layer V with dark and big pyramids and a multiform layer VI. The EC borders laterally the proisocortex (incomplete type of isocortex). Variations in the appearance of its layers justify the distinction of subfields in the EC, in particular in human and nonhuman primates. EC layers are not similar to those in the neocortex. The transition between the periallocortical EC and isocortex is not sharp, so that the proisocortex forms an intervening cortex, which fills the gap between the periallocortex and the isocortex. PMID:29046628

The Human Periallocortex: Layer Pattern in Presubiculum, Parasubiculum and Entorhinal Cortex. A Review.

PubMed

Insausti, Ricardo; Muñoz-López, Mónica; Insausti, Ana M; Artacho-Pérula, Emilio

2017-01-01

The cortical mantle is not homogeneous, so that three types of cortex can be distinguished: allocortex, periallocortex and isocortex. The main distinction among those three types is based on morphological differences, in particular the number of layers, overall organization, appearance, etc., as well as its connectivity. Additionally, in the phylogenetic scale, this classification is conserved among different mammals. The most primitive and simple cortex is the allocortex, which is characterized by the presence of three layers, with one cellular main layer; it is continued by the periallocortex, which presents six layers, although with enough differences in the layer pattern to separate three different fields: presubiculum (PrS), parasubiculum (PaS), and entorhinal cortex (EC). The closest part to the allocortex (represented by the subiculum) is the PrS, which shows outer (layers I-III) and inner (V-VI) principal layers ( lamina principalis externa and lamina principalis interna ), both separated by a cell poor band, parallel to the pial surface (layer IV or lamina dissecans ). This layer organization is present throughout the anterior-posterior axis. The PaS continues the PrS, but its rostrocaudal extent is shorter than the PrS. The organization of the PaS shows the layer pattern more clearly than in the PrS. Up to six layers are recognizable in the PaS, with layer IV as lamina dissecans between superficial (layers I-III) and deep (V-VI) layers, as in the PrS. The EC presents even more clearly the layer pattern along both mediolateral and rostrocaudal extent. The layer pattern is a thick layer I, layer II in islands, layer III medium pyramids, layer IV as lamina dissecans (not present throughout the EC extent), layer V with dark and big pyramids and a multiform layer VI. The EC borders laterally the proisocortex (incomplete type of isocortex). Variations in the appearance of its layers justify the distinction of subfields in the EC, in particular in human and nonhuman primates. EC layers are not similar to those in the neocortex. The transition between the periallocortical EC and isocortex is not sharp, so that the proisocortex forms an intervening cortex, which fills the gap between the periallocortex and the isocortex.

Addressing the issue of insufficient information in data-based bridge health monitoring : final report.

DOT National Transportation Integrated Search

2015-11-01

One of the most efficient ways to solve the damage detection problem using the statistical pattern recognition : approach is that of exploiting the methods of outlier analysis. Cast within the pattern recognition framework, : damage detection assesse...

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Threefold Increase in PrEP Uptake Over Time with High Adherence Among Young Men Who Have Sex With Men in Chicago.

PubMed

Morgan, Ethan; Moran, Kevin; Ryan, Daniel T; Mustanski, Brian; Newcomb, Michael E

2018-05-04

The goal of this work is to better understand utilization and uptake of pre-exposure prophylaxis (PrEP) among young men who have sex with men (YMSM) and transgender women (TGW). We assessed trends and correlates of PrEP use and adherence across three time points of longitudinal data collection among 885 YMSM and TGW (aged 16-29) from the RADAR cohort in Chicago, 2015-2017. Past 6-month PrEP use increased across three visits: from 6.6 to 17.5%. In multivariable models, past 6-month PrEP use was significantly associated with participation in condomless sex, having more sexual partners, and older age. At least three-quarters of current PrEP users reported being ≥ 90% adherent to PrEP medication across all visits. Past 6-month PrEP use increased over time with those who participated in high-risk HIV behaviors also those most likely to have taken PrEP. As PrEP uptake continues to rise, more research will be needed to understand predictors of PrEP usage, as well as patterns of sexual behavior change following uptake.

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

2018-03-01

We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

HIV-1 protease-substrate coevolution in nelfinavir resistance.

PubMed

Kolli, Madhavi; Ozen, Ayşegül; Kurt-Yilmaz, Nese; Schiffer, Celia A

2014-07-01

Resistance to various human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. The virus accumulates mutations within the protease (PR) that render the PIs less potent. Occasionally, Gag sequences also coevolve with mutations at PR cleavage sites contributing to drug resistance. In this study, we investigated the structural basis of coevolution of the p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations by determining crystal structures of wild-type and NFV-resistant HIV-1 protease in complex with p1-p6 substrate peptide variants with L449F and/or S451N. Alterations of residue 30's interaction with the substrate are compensated by the coevolving L449F and S451N cleavage site mutations. This interdependency in the PR-p1-p6 interactions enhances intermolecular contacts and reinforces the overall fit of the substrate within the substrate envelope, likely enabling coevolution to sustain substrate recognition and cleavage in the presence of PR resistance mutations. Resistance to human immunodeficiency virus type 1 (HIV-1) protease inhibitors challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. Mutations in HIV-1 protease selected under the pressure of protease inhibitors render the inhibitors less potent. Occasionally, Gag sequences also mutate and coevolve with protease, contributing to maintenance of viral fitness and to drug resistance. In this study, we investigated the structural basis of coevolution at the Gag p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations. Our structural analysis reveals the interdependency of protease-substrate interactions and how coevolution may restore substrate recognition and cleavage in the presence of protease drug resistance mutations. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Word Recognition in Auditory Cortex

ERIC Educational Resources Information Center

DeWitt, Iain D. J.

2013-01-01

Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

A study of structure of phenomenology of consciousness in meditative and non-meditative states.

PubMed

Venkatesh, S; Raju, T R; Shivani, Y; Tompkins, G; Meti, B L

1997-04-01

Twelve senior Kundalini (Chakra) meditators were assessed during meditation session and non-meditation or control session using Phenomenology of Consciousness Inventory. The data has been analyzed using structural analysis to measure the altered state of consciousness and the identity state by comparing meditative state with non-meditative state. The structural analysis of pattern of consciousness during the meditative state revealed altered experience in perception (percentile rank PR = 90), meaning (PR = 82) and time sense (PR = 87), while positive affect dimension showed increased joy (PR = 73) and love (PR = 67). The imagery vividness (PR = 72), self-awareness (PR = 77), rationality (PR = 73) and arousal (PR = 69) were found to be structurally different from the ordinary state. With regards to identity state meditative experience was found to produce statistically significant changes in terms of intensity in meaning (P < 0.05), time sense (P < 0.05), joy (P < 0.05), love (P < 0.05) and state of awareness (P < 0.01). Our results indicate that long term practice of meditation appears to produce structural as well as intensity changes in phenomenological experiences of consciousness.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

Genetic dissection of the maize (Zea mays L.) MAMP response

USDA-ARS?s Scientific Manuscript database

Microbe-associated molecular patterns (MAMPs) are highly conserved molecules commonly found in microbes which can be recognized by plant pattern recognition receptors (PRRs). Recognition triggers a suite of responses including production of reactive oxygen species (ROS) and nitric oxide (NO) and ex...

The Functional Architecture of Visual Object Recognition

DTIC Science & Technology

1991-07-01

different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-01-01

This report describes a study conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information. The study gathered data from a large number of pilots who conduct all type...

Spatial pattern recognition of seismic events in South West Colombia

NASA Astrophysics Data System (ADS)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Study and response time for the visual recognition of 'similarity' and identity

NASA Technical Reports Server (NTRS)

Derks, P. L.; Bauer, T. M.

1974-01-01

Four subjects compared successively presented pairs of line patterns for a match between any lines in the pattern (similarity) and for a match between all lines (identity). The encoding or study times for pattern recognition from immediate memory and the latency in responses to comparison stimuli were examined. Qualitative differences within and between subjects were most evident in study times.

Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

NASA Technical Reports Server (NTRS)

Amador, Jose J (Inventor)

2007-01-01

A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.

The chemical structure of DNA sequence signals for RNA transcription

NASA Technical Reports Server (NTRS)

George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

2003-01-01

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

Fourier transform magnitudes are unique pattern recognition templates.

PubMed

Gardenier, P H; McCallum, B C; Bates, R H

1986-01-01

Fourier transform magnitudes are commonly used in the generation of templates in pattern recognition applications. We report on recent advances in Fourier phase retrieval which are relevant to pattern recognition. We emphasise in particular that the intrinsic form of a finite, positive image is, in general, uniquely related to the magnitude of its Fourier transform. We state conditions under which the Fourier phase can be reconstructed from samples of the Fourier magnitude, and describe a method of achieving this. Computational examples of restoration of Fourier phase (and hence, by Fourier transformation, the intrinsic form of the image) from samples of the Fourier magnitude are also presented.

Detection and recognition of analytes based on their crystallization patterns

DOEpatents

Morozov, Victor [Manassas, VA; Bailey, Charles L [Cross Junction, VA; Vsevolodov, Nikolai N [Kensington, MD; Elliott, Adam [Manassas, VA

2008-05-06

The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

Infectious particles, stress, and induced prion amyloids

PubMed Central

2013-01-01

Transmissible encephalopathies (TSEs) are believed by many to arise by spontaneous conversion of host prion protein (PrP) into an infectious amyloid (PrP-res, PrPSc) without nucleic acid. Many TSE agents reside in the environment, with infection controlled by public health measures. These include the disappearance of kuru with the cessation of ritual cannibalism, the dramatic reduction of epidemic bovine encephalopathy (BSE) by removal of contaminated feed, and the lack of endemic scrapie in geographically isolated Australian sheep with susceptible PrP genotypes. While prion protein modeling has engendered an intense focus on common types of protein misfolding and amyloid formation in diverse organisms and diseases, the biological characteristics of infectious TSE agents, and their recognition by the host as foreign entities, raises several fundamental new directions for fruitful investigation such as: (1) unrecognized microbial agents in the environmental metagenome that may cause latent neurodegenerative disease, (2) the evolutionary social and protective functions of different amyloid proteins in diverse organisms from bacteria to mammals, and (3) amyloid formation as a beneficial innate immune response to stress (infectious and non-infectious). This innate process however, once initiated, can become unstoppable in accelerated neuronal aging. PMID:23633671

Progesterone from maternal circulation binds to progestin receptors in fetal brain.

PubMed

Wagner, Christine K; Quadros-Mennella, Princy

2017-06-01

Steroid hormones activate nuclear receptors which, as transcription factors, can regulate critical aspects of neural development. Many regions of the rat forebrain, midbrain and hindbrain express progestin receptors (PR) during perinatal life, suggesting that progesterone may play an important role in the development of the brain. An immunohistochemical approach using two antibodies with differential recognition of ligand-bound PR was used to examine whether fetuses are exposed to maternal progesterone during pregnancy and whether progesterone from maternal circulation can bind to PR within the fetal brain. Findings demonstrate that maternal and fetal serum progesterone levels are positively correlated at the end of gestation, suggesting a common source of progesterone in mothers and fetuses (e.g., the maternal ovary). Additional findings suggest that administration of exogenous progesterone to mothers not only increases fetal serum progesterone levels within 2 h, but appears to increase ligand-bound PR in fetal brain. These findings suggest that progesterone of maternal origin may play a previously overlooked role in neural development. In addition, there are implications for the ongoing prophylactic use of synthetic progestins in pregnant women for the prevention of premature birth. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 767-774, 2017. © 2016 Wiley Periodicals, Inc.

Recognition of neural brain activity patterns correlated with complex motor activity

NASA Astrophysics Data System (ADS)

Kurkin, Semen; Musatov, Vyacheslav Yu.; Runnova, Anastasia E.; Grubov, Vadim V.; Efremova, Tatyana Yu.; Zhuravlev, Maxim O.

2018-04-01

In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.

Perception of pathogenic or beneficial bacteria and their evasion of host immunity: pattern recognition receptors in the frontline

PubMed Central

Trdá, Lucie; Boutrot, Freddy; Claverie, Justine; Brulé, Daphnée; Dorey, Stephan; Poinssot, Benoit

2015-01-01

Plants are continuously monitoring the presence of microorganisms to establish an adapted response. Plants commonly use pattern recognition receptors (PRRs) to perceive microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) which are microorganism molecular signatures. Located at the plant plasma membrane, the PRRs are generally receptor-like kinases (RLKs) or receptor-like proteins (RLPs). MAMP detection will lead to the establishment of a plant defense program called MAMP-triggered immunity (MTI). In this review, we overview the RLKs and RLPs that assure early recognition and control of pathogenic or beneficial bacteria. We also highlight the crucial function of PRRs during plant-microbe interactions, with a special emphasis on the receptors of the bacterial flagellin and peptidoglycan. In addition, we discuss the multiple strategies used by bacteria to evade PRR-mediated recognition. PMID:25904927

Peptidoglycan recognition proteins in Drosophila immunity.

PubMed

Kurata, Shoichiro

2014-01-01

Innate immunity is the front line of self-defense against infectious non-self in vertebrates and invertebrates. The innate immune system is mediated by germ-line encoding pattern recognition molecules (pathogen sensors) that recognize conserved molecular patterns present in the pathogens but absent in the host. Peptidoglycans (PGN) are essential cell wall components of almost all bacteria, except mycoplasma lacking a cell wall, which provides the host immune system an advantage for detecting invading bacteria. Several families of pattern recognition molecules that detect PGN and PGN-derived compounds have been indentified, and the role of PGRP family members in host defense is relatively well-characterized in Drosophila. This review focuses on the role of PGRP family members in the recognition of invading bacteria and the activation and modulation of immune responses in Drosophila. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

NASA Astrophysics Data System (ADS)

Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

1993-03-01

The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

Age-related increases in false recognition: the role of perceptual and conceptual similarity.

PubMed

Pidgeon, Laura M; Morcom, Alexa M

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499-510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.'s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous "old/new" responses at test, while in Experiment 2 participants were also asked to judge lures as "similar," to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.'s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation.

Age-related increases in false recognition: the role of perceptual and conceptual similarity

PubMed Central

Pidgeon, Laura M.; Morcom, Alexa M.

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499–510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.’s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous “old/new” responses at test, while in Experiment 2 participants were also asked to judge lures as “similar,” to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.’s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation. PMID:25368576

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Enemy at the gates: traffic at the plant cell pathogen interface.

PubMed

Hoefle, Caroline; Hückelhoven, Ralph

2008-12-01

The plant apoplast constitutes a space for early recognition of potentially harmful non-self. Basal pathogen recognition operates via dynamic sensing of conserved microbial patterns by pattern recognition receptors or of elicitor-active molecules released from plant cell walls during infection. Recognition elicits defence reactions depending on cellular export via SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex-mediated vesicle fusion or plasma membrane transporter activity. Lipid rafts appear also involved in focusing immunity-associated proteins to the site of pathogen contact. Simultaneously, pathogen effectors target recognition, apoplastic host proteins and transport for cell wall-associated defence. This microreview highlights most recent reports on the arms race for plant disease and immunity at the cell surface.

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-04-28

A study was conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information, such as electronic charts and moving map displays. The goal of this research is to support t...

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns.

PubMed

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10- and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns

PubMed Central

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J.

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10− and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities. PMID:27932941

MR-based attenuation correction methods for improved PET quantification in lesions within bone and susceptibility artifact regions.

PubMed

Bezrukov, Ilja; Schmidt, Holger; Mantlik, Frédéric; Schwenzer, Nina; Brendle, Cornelia; Schölkopf, Bernhard; Pichler, Bernd J

2013-10-01

Hybrid PET/MR systems have recently entered clinical practice. Thus, the accuracy of MR-based attenuation correction in simultaneously acquired data can now be investigated. We assessed the accuracy of 4 methods of MR-based attenuation correction in lesions within soft tissue, bone, and MR susceptibility artifacts: 2 segmentation-based methods (SEG1, provided by the manufacturer, and SEG2, a method with atlas-based susceptibility artifact correction); an atlas- and pattern recognition-based method (AT&PR), which also used artifact correction; and a new method combining AT&PR and SEG2 (SEG2wBONE). Attenuation maps were calculated for the PET/MR datasets of 10 patients acquired on a whole-body PET/MR system, allowing for simultaneous acquisition of PET and MR data. Eighty percent iso-contour volumes of interest were placed on lesions in soft tissue (n = 21), in bone (n = 20), near bone (n = 19), and within or near MR susceptibility artifacts (n = 9). Relative mean volume-of-interest differences were calculated with CT-based attenuation correction as a reference. For soft-tissue lesions, none of the methods revealed a significant difference in PET standardized uptake value relative to CT-based attenuation correction (SEG1, -2.6% ± 5.8%; SEG2, -1.6% ± 4.9%; AT&PR, -4.7% ± 6.5%; SEG2wBONE, 0.2% ± 5.3%). For bone lesions, underestimation of PET standardized uptake values was found for all methods, with minimized error for the atlas-based approaches (SEG1, -16.1% ± 9.7%; SEG2, -11.0% ± 6.7%; AT&PR, -6.6% ± 5.0%; SEG2wBONE, -4.7% ± 4.4%). For lesions near bone, underestimations of lower magnitude were observed (SEG1, -12.0% ± 7.4%; SEG2, -9.2% ± 6.5%; AT&PR, -4.6% ± 7.8%; SEG2wBONE, -4.2% ± 6.2%). For lesions affected by MR susceptibility artifacts, quantification errors could be reduced using the atlas-based artifact correction (SEG1, -54.0% ± 38.4%; SEG2, -15.0% ± 12.2%; AT&PR, -4.1% ± 11.2%; SEG2wBONE, 0.6% ± 11.1%). For soft-tissue lesions, none of the evaluated methods showed statistically significant errors. For bone lesions, significant underestimations of -16% and -11% occurred for methods in which bone tissue was ignored (SEG1 and SEG2). In the present attenuation correction schemes, uncorrected MR susceptibility artifacts typically result in reduced attenuation values, potentially leading to highly reduced PET standardized uptake values, rendering lesions indistinguishable from background. While AT&PR and SEG2wBONE show accurate results in both soft tissue and bone, SEG2wBONE uses a two-step approach for tissue classification, which increases the robustness of prediction and can be applied retrospectively if more precision in bone areas is needed.

Identification and characterisation of seventeen glutathione S-transferase genes from the cabbage white butterfly Pieris rapae.

PubMed

Liu, Su; Zhang, Yu-Xing; Wang, Wen-Long; Zhang, Bang-Xian; Li, Shi-Guang

2017-11-01

Insect glutathione S-transferases (GSTs) play essential roles in the detoxification of insecticides and other xenobiotic compounds. The cabbage white butterfly, Pieris rapae, is an economically important agricultural pest. In this study, 17 cDNA sequences encoding putative GSTs were identified in P. rapae. All cDNAs include a complete open reading frame and were designated PrGSTd1-PrGSTz2. Based on phylogenetic analysis, PrGSTs were divided into six classes (delta, epsilon, omega, sigma, theta and zeta). The exon-intron organizations of these PrGSTs were also analysed. Recombinant proteins of eight PrGSTs (PrGSTD1, PrGSTD2, PrGSTE1, PrGSTE2, PrGSTO1, PrGSTS1, PrGSTT1 and PrGSTZ1) were heterologously expressed in Escherichia coli, and all of these proteins displayed glutathione-conjugating activity towards 1-chloro-2,4-dinitrobenzene (CDNB). Expression patterns in various larval tissues, at different life stages, and following exposure to sublethal doses of abamectin, chlorantraniliprole or lambda-cyhalothrin were determined by reverse transcription-quantitative PCR. The results showed that PrGSTe3, PrGSTs1, PrGSTs2, and PrGSTs4 were mainly transcribed in the fat body, while PrGSTe2 was expressed predominantly in the Malpighian tubules. Four genes (PrGSTe2, PrGSTo4, PrGSTs4 and PrGSTt1) were mainly expressed in fourth-instar larvae, while others were ubiquitously expressed in egg, larval, pupa and/or adult stages. Abamectin treatment significantly upregulated ten genes (PrGSTd1, PrGSTd3, PrGSTe1, PrGSTe2, PrGSTo1, PrGSTo3, PrGSTs1, PrGSTs3, PrGSTs4 and PrGSTt1). Chlorantraniliprole and lambda-cyhalothrin treatment significantly upregulated nine genes (PrGSTd1, PrGSTd2, PrGSTe1, PrGSTe2, PrGSTe3, PrGSTs1, PrGSTs3, PrGSTs4 and PrGSTz1) and ten genes (PrGSTd1, PrGSTd3, PrGSTe1, PrGSTe2, PrGSTo1, PrGSTo2, PrGSTs1, PrGSTs2, PrGSTs3 and PrGSTz2), respectively. These GSTs are potentially involved in the detoxification of insecticides. Copyright © 2017 Elsevier Inc. All rights reserved.

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes

ERIC Educational Resources Information Center

Bufford, Carolyn A.; Mettler, Everett; Geller, Emma H.; Kellman, Philip J.

2014-01-01

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM)…

Summary of 1971 pattern recognition program development

NASA Technical Reports Server (NTRS)

Whitley, S. L.

1972-01-01

Eight areas related to pattern recognition analysis at the Earth Resources Laboratory are discussed: (1) background; (2) Earth Resources Laboratory goals; (3) software problems/limitations; (4) operational problems/limitations; (5) immediate future capabilities; (6) Earth Resources Laboratory data analysis system; (7) general program needs and recommendations; and (8) schedule and milestones.

Pattern Recognition by Retina-Like Devices.

ERIC Educational Resources Information Center

Weiman, Carl F. R.; Rothstein, Jerome

This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

Cognitive Development and Reading Processes. Developmental Program Report Number 76.

ERIC Educational Resources Information Center

West, Richard F.

In discussing the relationship between cognitive development (perception, pattern recognition, and memory) and reading processes, this paper especially emphasizes developmental factors. After an overview of some issues that bear on how written language is processed, the paper presents a discussion of pattern recognition, including general pattern…

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Performance Study of the First 2D Prototype of Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deptuch, Gregory; Hoff, James; Jindariani, Sergo

Extremely fast pattern recognition capabilities are necessary to find and fit billions of tracks at the hardware trigger level produced every second anticipated at high luminosity LHC (HL-LHC) running conditions. Associative Memory (AM) based approaches for fast pattern recognition have been proposed as a potential solution to the tracking trigger. However, at the HL-LHC, there is much less time available and speed performance must be improved over previous systems while maintaining a comparable number of patterns. The Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) Project aims to achieve the target pattern density and performance goal using 3DIC technology. The firstmore » step taken in the VIPRAM work was the development of a 2D prototype (protoVIPRAM00) in which the associative memory building blocks were designed to be compatible with the 3D integration. In this paper, we present the results from extensive performance studies of the protoVIPRAM00 chip in both realistic HL-LHC and extreme conditions. Results indicate that the chip operates at the design frequency of 100 MHz with perfect correctness in realistic conditions and conclude that the building blocks are ready for 3D stacking. We also present performance boundary characterization of the chip under extreme conditions.« less

Do pattern recognition skills transfer across sports? A preliminary analysis.

PubMed

Smeeton, Nicholas J; Ward, Paul; Williams, A Mark

2004-02-01

The ability to recognize patterns of play is fundamental to performance in team sports. While typically assumed to be domain-specific, pattern recognition skills may transfer from one sport to another if similarities exist in the perceptual features and their relations and/or the strategies used to encode and retrieve relevant information. A transfer paradigm was employed to compare skilled and less skilled soccer, field hockey and volleyball players' pattern recognition skills. Participants viewed structured and unstructured action sequences from each sport, half of which were randomly represented with clips not previously seen. The task was to identify previously viewed action sequences quickly and accurately. Transfer of pattern recognition skill was dependent on the participant's skill, sport practised, nature of the task and degree of structure. The skilled soccer and hockey players were quicker than the skilled volleyball players at recognizing structured soccer and hockey action sequences. Performance differences were not observed on the structured volleyball trials between the skilled soccer, field hockey and volleyball players. The skilled field hockey and soccer players were able to transfer perceptual information or strategies between their respective sports. The less skilled participants' results were less clear. Implications for domain-specific expertise, transfer and diversity across domains are discussed.

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

A novel methodology for litho-to-etch pattern fidelity correction for SADP process

NASA Astrophysics Data System (ADS)

Chen, Shr-Jia; Chang, Yu-Cheng; Lin, Arthur; Chang, Yi-Shiang; Lin, Chia-Chi; Lai, Jun-Cheng

2017-03-01

For 2x nm node semiconductor devices and beyond, more aggressive resolution enhancement techniques (RETs) such as source-mask co-optimization (SMO), litho-etch-litho-etch (LELE) and self-aligned double patterning (SADP) are utilized for the low k1 factor lithography processes. In the SADP process, the pattern fidelity is extremely critical since a slight photoresist (PR) top-loss or profile roughness may impact the later core trim process, due to its sensitivity to environment. During the subsequent sidewall formation and core removal processes, the core trim profile weakness may worsen and induces serious defects that affect the final electrical performance. To predict PR top-loss, a rigorous lithography simulation can provide a reference to modify mask layouts; but it takes a much longer run time and is not capable of full-field mask data preparation. In this paper, we first brought out an algorithm which utilizes multi-intensity levels from conventional aerial image simulation to assess the physical profile through lithography to core trim etching steps. Subsequently, a novel correction method was utilized to improve the post-etch pattern fidelity without the litho. process window suffering. The results not only matched PR top-loss in rigorous lithography simulation, but also agreed with post-etch wafer data. Furthermore, this methodology can also be incorporated with OPC and post-OPC verification to improve core trim profile and final pattern fidelity at an early stage.

STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

Healthcare decision-tools a growing Web trend: three-pronged public relations campaign heightens presence, recognition for online healthcare information provider.

PubMed

2006-01-01

Schwartz Communications, LLC, executes a successful PR campaign to position Subimo, a provider of online healthcare decision tools, as a leader in the industry that touts names such as WebMD.com and HealthGrades.com. Through a three-pronged media relations strategy, Schwartz and Subimo together branded the company as an industry thought-leader.

Defense Against Threat. Threat Recognition and Analysis Project

DTIC Science & Technology

1975-09-01

but clustering around it ( land affecting it) are other action structures of different character, now entering strongly on the world scene...seeks .o cap ur ^^’^^try to gestalts of cognition and affect , ^[Jj^ f c!anrPr or country, that put the signature of...TRAMSPORT 8, PETROL PRODUCTS 7.*, USR 27, JAP 18, IND Ik, - FRUITS +NUTS Ik, NATURAL GAS 17, LAMBSKINS 12, USR 30, PAK

Face Recognition Using Local Quantized Patterns and Gabor Filters

NASA Astrophysics Data System (ADS)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

Speaker normalization for chinese vowel recognition in cochlear implants.

PubMed

Luo, Xin; Fu, Qian-Jie

2005-07-01

Because of the limited spectra-temporal resolution associated with cochlear implants, implant patients often have greater difficulty with multitalker speech recognition. The present study investigated whether multitalker speech recognition can be improved by applying speaker normalization techniques to cochlear implant speech processing. Multitalker Chinese vowel recognition was tested with normal-hearing Chinese-speaking subjects listening to a 4-channel cochlear implant simulation, with and without speaker normalization. For each subject, speaker normalization was referenced to the speaker that produced the best recognition performance under conditions without speaker normalization. To match the remaining speakers to this "optimal" output pattern, the overall frequency range of the analysis filter bank was adjusted for each speaker according to the ratio of the mean third formant frequency values between the specific speaker and the reference speaker. Results showed that speaker normalization provided a small but significant improvement in subjects' overall recognition performance. After speaker normalization, subjects' patterns of recognition performance across speakers changed, demonstrating the potential for speaker-dependent effects with the proposed normalization technique.

Visual Scanning Patterns and Executive Function in Relation to Facial Emotion Recognition in Aging

PubMed Central

Circelli, Karishma S.; Clark, Uraina S.; Cronin-Golomb, Alice

2012-01-01

Objective The ability to perceive facial emotion varies with age. Relative to younger adults (YA), older adults (OA) are less accurate at identifying fear, anger, and sadness, and more accurate at identifying disgust. Because different emotions are conveyed by different parts of the face, changes in visual scanning patterns may account for age-related variability. We investigated the relation between scanning patterns and recognition of facial emotions. Additionally, as frontal-lobe changes with age may affect scanning patterns and emotion recognition, we examined correlations between scanning parameters and performance on executive function tests. Methods We recorded eye movements from 16 OA (mean age 68.9) and 16 YA (mean age 19.2) while they categorized facial expressions and non-face control images (landscapes), and administered standard tests of executive function. Results OA were less accurate than YA at identifying fear (p<.05, r=.44) and more accurate at identifying disgust (p<.05, r=.39). OA fixated less than YA on the top half of the face for disgust, fearful, happy, neutral, and sad faces (p’s<.05, r’s≥.38), whereas there was no group difference for landscapes. For OA, executive function was correlated with recognition of sad expressions and with scanning patterns for fearful, sad, and surprised expressions. Conclusion We report significant age-related differences in visual scanning that are specific to faces. The observed relation between scanning patterns and executive function supports the hypothesis that frontal-lobe changes with age may underlie some changes in emotion recognition. PMID:22616800

Recognition of surface lithologic and topographic patterns in southwest Colorado with ADP techniques

NASA Technical Reports Server (NTRS)

Melhorn, W. N.; Sinnock, S.

1973-01-01

Analysis of ERTS-1 multispectral data by automatic pattern recognition procedures is applicable toward grappling with current and future resource stresses by providing a means for refining existing geologic maps. The procedures used in the current analysis already yield encouraging results toward the eventual machine recognition of extensive surface lithologic and topographic patterns. Automatic mapping of a series of hogbacks, strike valleys, and alluvial surfaces along the northwest flank of the San Juan Basin in Colorado can be obtained by minimal man-machine interaction. The determination of causes for separable spectral signatures is dependent upon extensive correlation of micro- and macro field based ground truth observations and aircraft underflight data with the satellite data.

Infrared Ship Classification Using A New Moment Pattern Recognition Concept

NASA Astrophysics Data System (ADS)

Casasent, David; Pauly, John; Fetterly, Donald

1982-03-01

An analysis of the statistics of the moments and the conventional invariant moments shows that the variance of the latter become quite large as the order of the moments and the degree of invariance increases. Moreso, the need to whiten the error volume increases with the order and degree, but so does the computational load associated with computing the whitening operator. We thus advance a new estimation approach to the use of moments in pattern recog-nition that overcomes these problems. This work is supported by experimental verification and demonstration on an infrared ship pattern recognition problem. The computational load associated with our new algorithm is also shown to be very low.

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Transient expression of progesterone receptor and cathepsin-l in human granulosa cells during the periovulatory period.

PubMed

García, Víctor; Kohen, Paulina; Maldonado, Carola; Sierralta, Walter; Muñoz, Alex; Villarroel, Claudio; Strauss, Jerome F; Devoto, Luigi

2012-03-01

To study in vivo the progesterone receptor (PR) expression levels in human granulosa cells (GCs) during the periovulatory period and the affect of the protein kinase A (PKA) pathway on PR expression and cathepsin-L expression-activation. Experimental study. University research unit. Twenty-five women of reproductive age. Follicular fluid and GCs obtained from spontaneous cycles before and during the normal luteinizing hormone surge, and samples obtained 36 hours after human chorionic gonadotropin (hCG) administration in patients undergoing in vitro fertilization. To determine PR, cathepsin-L messenger RNA (mRNA) analysis via real-time polymerase chain reaction, and protein of PR, cathepsin-L, and PKA in human GCs. The Western blot analysis revealed that bands of PR (isoform A) were the most abundant and that mRNA (PR-A and PR-B) have a temporal pattern of expression throughout the periovulatory period. The protein levels of PR and cathepsin-L were up-regulated by hCG. The abundance of PR was diminished in the presence of PKA inhibitor, and cathepsin-L with PR receptor antagonist. The transient expression of PR in human GCs of the preovulatory follicle suggests that PR and its ligand play a role in the activation of cathepsin-L, which is presumably involved in the degradation of the follicular extracellular matrix during human ovulation. Copyright © 2012 American Society for Reproductive Medicine. All rights reserved.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

The time course of individual face recognition: A pattern analysis of ERP signals.

PubMed

Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

2016-05-15

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

ERIC Educational Resources Information Center

Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-01-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

Designing Clinical Examples To Promote Pattern Recognition: Nursing Education-Based Research and Practical Applications.

ERIC Educational Resources Information Center

Welk, Dorette Sugg

2002-01-01

Sophomore nursing students (n=162) examined scenarios depicting typical and atypical signs of heart attack. Examples were structured to include essential and nonessential symptoms, enabling pattern recognition and improved performance. The method provides a way to prepare students to anticipate and recognize life-threatening situations. (Contains…

PATTERN RECOGNITION APPROACH TO MEDICAL DIAGNOSIS,

DTIC Science & Technology

A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in...the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced. (Author)

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Classifier dependent feature preprocessing methods

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M., II; Peterson, Gilbert L.

2008-04-01

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Complex auditory behaviour emerges from simple reactive steering

NASA Astrophysics Data System (ADS)

Hedwig, Berthold; Poulet, James F. A.

2004-08-01

The recognition and localization of sound signals is fundamental to acoustic communication. Complex neural mechanisms are thought to underlie the processing of species-specific sound patterns even in animals with simple auditory pathways. In female crickets, which orient towards the male's calling song, current models propose pattern recognition mechanisms based on the temporal structure of the song. Furthermore, it is thought that localization is achieved by comparing the output of the left and right recognition networks, which then directs the female to the pattern that most closely resembles the species-specific song. Here we show, using a highly sensitive method for measuring the movements of female crickets, that when walking and flying each sound pulse of the communication signal releases a rapid steering response. Thus auditory orientation emerges from reactive motor responses to individual sound pulses. Although the reactive motor responses are not based on the song structure, a pattern recognition process may modulate the gain of the responses on a longer timescale. These findings are relevant to concepts of insect auditory behaviour and to the development of biologically inspired robots performing cricket-like auditory orientation.

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection

PubMed Central

Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm. PMID:27711125

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection.

PubMed

Cadavid, Sara; Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm.

Age and geographic patterns of Plasmodium falciparum malaria infection in a representative sample of children living in Burkitt lymphoma-endemic areas of northern Uganda.

PubMed

Maziarz, Marlena; Kinyera, Tobias; Otim, Isaac; Kagwa, Paul; Nabalende, Hadijah; Legason, Ismail D; Ogwang, Martin D; Kirimunda, Samuel; Emmanuel, Benjamin; Reynolds, Steven J; Kerchan, Patrick; Joloba, Moses M; Bergen, Andrew W; Bhatia, Kishor; Talisuna, Ambrose O; Biggar, Robert J; Goedert, James J; Pfeiffer, Ruth M; Mbulaiteye, Sam M

2017-03-20

Falciparum malaria is an important risk factor for African Burkitt lymphoma (BL), but few studies have evaluated malaria patterns in healthy BL-age children in populations where both diseases are endemic. To obtain accurate current data, patterns of asymptomatic malaria were investigated in northern Uganda, where BL is endemic. Between 2011 and 2015, 1150 apparently healthy children under 15 years old were sampled from 100 villages in northern Uganda using a stratified, multi-stage, cluster survey design. Falciparum malaria prevalence (pfPR) was assessed by questionnaire, rapid diagnostic test (RDT) and thick film microscopy (TFM). Weighted pfPR and unadjusted and adjusted associations of prevalence with covariates were calculated using logistic models and survey methods. Based on 1143 children successfully tested, weighted pfPR was 54.8% by RDT and 43.4% by TFM. RDT sensitivity and specificity were 97.5 and 77.8%, respectively, as compared to TFM, because RDT detect malaria antigens, which persist in peripheral blood after clinical malaria, thus results based on RDT are reported. Weighted pfPR increased from 40% in children aged under 2 years to 61.8% in children aged 6-8 years (odds ratio 2.42, 95% confidence interval (CI) 1.26-4.65), then fell slightly to 49% in those aged 12-15 years. Geometric mean parasite density was 1805.5 parasites/µL (95% CI 1344.6-2424.3) among TFM-positive participants, and it was higher in children aged <5 years at 5092.9/µL (95% CI 2892.7-8966.8) and lower in those aged ≥10 years at 983.8/µL (95% CI 472.7-2047.4; P = 0.001). Weighted pfPR was lower in children residing in sub-regions employing indoor residual spraying (IRS) than in those residing in non-IRS sub-regions (32.8 versus 65.7%; OR 0.26, 95% CI 0.14, 0.46). However, pfPR varied both within IRS (3.2-55.3%) and non-IRS sub-regions (29.8-75.8%; Pheterogeneity <0.001). pfPR was inversely correlated with a child's mother's income (P = 0.011) and positively correlated with being enrolled in the wet season (P = 0.076), but sex was irrelevant. The study observed high but geographically and demographically heterogenous patterns of asymptomatic malaria prevalence among children living in northern Uganda. These results provide important baseline data that will enable precise evaluation of associations between malaria and BL.

Talker variability in audio-visual speech perception

PubMed Central

Heald, Shannon L. M.; Nusbaum, Howard C.

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker’s face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker’s face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker’s face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred. PMID:25076919

Talker variability in audio-visual speech perception.

PubMed

Heald, Shannon L M; Nusbaum, Howard C

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker's face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker's face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker's face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred.

Survival Benefits of Small Anatomical Resection of the Liver for Patients with Hepatocellular Carcinoma and Impaired Liver Function, Based on New-Era Imaging Studies.

PubMed

Sakoda, Masahiko; Ueno, Shinichi; Iino, Satoshi; Hiwatashi, Kiyokazu; Minami, Koji; Kawasaki, Yota; Kurahara, Hiroshi; Mataki, Yuko; Maemura, Kosei; Shinchi, Hiroyuki; Natsugoe, Shoji

2016-01-01

It has been reported that anatomical resection of the liver may be preferred for primary hepatocellular carcinoma (HCC), and is at least recommended for systematic removal of a segment confined by tumor-bearing portal tributaries. However, nonanatomical resection (NAR) is often selected because of the patient's background, impairment of liver function, and tumor factors. The aims of the present study were to retrospectively compare the recurrence-free survival (RFS) rates for cases of partial resection (PR) and for small anatomical resection (SAR), which is regarded as NAR for primary HCC with impaired liver function. So-called NAR was performed for a primary and solitary (≤ 5cm) HCC in 47 patients; the patients were classified into PR (n=25) and SAR (n=22) groups. Clinicopathological factors, survival data, and recurrence patterns were compared between groups. There were no significant differences in the preoperative characteristics between the two groups. Operative time was significantly longer in the SAR group than in the PR group. There was no significant difference in the postoperative morbidity and tumor pathological characteristics between the two groups. The RFS of the SAR group was significantly better than those of the PR group. Although there was no significant difference in the pattern of recurrence between the two groups, the rate of intrahepatic recurrence in the same segment as the initial tumor tended to be higher in the PR group than in the SAR group. Multivariate analysis revealed that only the PR operative procedure was significant independent risk factor for poorer RFS. Compared with PR, SAR effectively improves the rate of RFS after surgery for a primary and solitary HCC with impaired liver function.

Prostate cancer incidence and tumor severity in Georgia: descriptive epidemiology, racial disparity, and geographic trends.

PubMed

Wagner, Sara E; Bauer, Sarah E; Bayakly, A Rana; Vena, John E

2013-01-01

Limited research has been conducted to describe the geographical clustering and distribution of prostate cancer (PrCA) incidence in Georgia (GA). This study describes and compares the temporal and geographic trends of PrCA incidence in GA with a specific focus on racial disparities. GA Comprehensive Cancer Registry PrCA incidence data were obtained for 1998-2008. Directly standardized age-adjusted PrCA incidence rates per 100,000 were analyzed by race, stage, grade, and county. County-level hotspots of PrCA incidence were analyzed with the Getis-Ord Gi* statistic in a geographic information system; a census tract-level cluster analysis was performed with a Discrete Poisson model and implemented in SaTScan(®) software. Significant (p < 0.05) hotspots of PrCA incidence were observed in nine southwestern counties and six centrally located counties among men of both races. Six significant (p < 0.1) clusters of PrCA incidence rates were detected for men of both races in north and northwest central Georgia. When stratified by race, clusters among white and black men were similar, although centroids were slightly shifted. Most notably, a large (122 km radius) cluster in northwest central Georgia was detected only in whites, and two smaller clusters (0-32 km radii) were detected in Southwest Georgia only in black men. Clusters of high-grade and late-stage tumors were identified primarily in the northern portion of the state among men of both races. This study revealed a pattern of higher incidence and more advanced disease in northern and northwest central Georgia, highlighting geographic patterns that need more research and investigation of possible environmental determinants.

Classifying performance impairment in response to sleep loss using pattern recognition algorithms on single session testing

PubMed Central

St. Hilaire, Melissa A.; Sullivan, Jason P.; Anderson, Clare; Cohen, Daniel A.; Barger, Laura K.; Lockley, Steven W.; Klerman, Elizabeth B.

2012-01-01

There is currently no “gold standard” marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the “real world” or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26 – 52 hours. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual’s behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in response to sleep loss. PMID:22959616

Imaging in gynaecology: How good are we in identifying endometriomas?

PubMed Central

Van Holsbeke, C.; Van Calster, B.; Guerriero, S.; Savelli, L.; Leone, F.; Fischerova, D; Czekierdowski, A.; Fruscio, R.; Veldman, J.; Van de Putte, G.; Testa, A.C.; Bourne, T.; Valentin, L.; Timmerman, D.

2009-01-01

Aim: To evaluate the performance of subjective evaluation of ultrasound findings (pattern recognition) to discriminate endometriomas from other types of adnexal masses and to compare the demographic and ultrasound characteristics of the true positive cases with those cases that were presumed to be an endometrioma but proved to have a different histology (false positive cases) and the endometriomas missed by pattern recognition (false negative cases). Methods: All patients in the International Ovarian Tumor Analysis (IOTA ) studies were included for analysis. In the IOTA studies, patients with an adnexal mass that were preoperatively examined by expert sonologists following the same standardized ultrasound protocol were prospectively included in 21 international centres. Sensitivity and specificity to discriminate endometriomas from other types of adnexal masses using pattern recognition were calculated. Ultrasound and some demographic variables of the masses presumed to be an endometrioma were analysed (true positives and false positives) and compared with the variables of the endometriomas missed by pattern recognition (false negatives) as well as the true negatives. Results: IOTA phase 1, 1b and 2 included 3511 patients of which 2560 were benign (73%) and 951 malignant (27%). The dataset included 713 endometriomas. Sensitivity and specificity for pattern recognition were 81% (577/713) and 97% (2723/2798). The true positives were more often unilocular with ground glass echogenicity than the masses in any other category. Among the 75 false positive cases, 66 were benign but 9 were malignant (5 borderline tumours, 1 rare primary invasive tumour and 3 endometrioid adenocarcinomas). The presumed diagnosis suggested by the sonologist in case of a missed endometrioma was mostly functional cyst or cystadenoma. Conclusion: Expert sonologists can quite accurately discriminate endometriomas from other types of adnexal masses, but in this dataset 1% of the masses that were classified as endometrioma by pattern recognition proved to be malignancies. PMID:25478066

Remote Video Monitor of Vehicles in Cooperative Information Platform

NASA Astrophysics Data System (ADS)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes.

PubMed

Mosley, Jonathan D; Shoemaker, M Benjamin; Wells, Quinn S; Darbar, Dawood; Shaffer, Christian M; Edwards, Todd L; Bastarache, Lisa; McCarty, Catherine A; Thompson, Will; Chute, Christopher G; Jarvik, Gail P; Crosslin, David R; Larson, Eric B; Kullo, Iftikhar J; Pacheco, Jennifer A; Peissig, Peggy L; Brilliant, Murray H; Linneman, James G; Witte, John S; Denny, Josh C; Roden, Dan M

2017-04-01

One potential use for the PR interval is as a biomarker of disease risk. We hypothesized that quantifying the shared genetic architectures of the PR interval and a set of clinical phenotypes would identify genetic mechanisms contributing to PR variability and identify diseases associated with a genetic predictor of PR variability. We used ECG measurements from the ARIC study (Atherosclerosis Risk in Communities; n=6731 subjects) and 63 genetically modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978). We measured pairwise genetic correlations (rG) between PR phenotypes (PR interval, PR segment, P-wave duration) and each of the 63 phenotypes. The PR segment was genetically correlated with atrial fibrillation (rG=-0.88; P =0.0009). An analysis of metabolic phenotypes in ARIC also showed that the P wave was genetically correlated with waist circumference (rG=0.47; P =0.02). A genetically predicted PR interval phenotype based on 645 714 single-nucleotide polymorphisms was associated with atrial fibrillation (odds ratio=0.89 per SD change; 95% confidence interval, 0.83-0.95; P =0.0006). The differing pattern of associations among the PR phenotypes is consistent with analyses that show that the genetic correlation between the P wave and PR segment was not significantly different from 0 (rG=-0.03 [0.16]). The genetic architecture of the PR interval comprises modulators of atrial fibrillation risk and obesity. © 2017 American Heart Association, Inc.

Review: Potential biotechnological assets related to plant immunity modulation applicable in engineering disease-resistant crops.

PubMed

Silva, Marilia Santos; Arraes, Fabrício Barbosa Monteiro; Campos, Magnólia de Araújo; Grossi-de-Sa, Maira; Fernandez, Diana; Cândido, Elizabete de Souza; Cardoso, Marlon Henrique; Franco, Octávio Luiz; Grossi-de-Sa, Maria Fátima

2018-05-01

This review emphasizes the biotechnological potential of molecules implicated in the different layers of plant immunity, including, pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI), effector-triggered susceptibility (ETS), and effector-triggered immunity (ETI) that can be applied in the development of disease-resistant genetically modified (GM) plants. These biomolecules are produced by pathogens (viruses, bacteria, fungi, oomycetes) or plants during their mutual interactions. Biomolecules involved in the first layers of plant immunity, PTI and ETS, include inhibitors of pathogen cell-wall-degrading enzymes (CWDEs), plant pattern recognition receptors (PRRs) and susceptibility (S) proteins, while the ETI-related biomolecules include plant resistance (R) proteins. The biomolecules involved in plant defense PTI/ETI responses described herein also include antimicrobial peptides (AMPs), pathogenesis-related (PR) proteins and ribosome-inhibiting proteins (RIPs), as well as enzymes involved in plant defensive secondary metabolite biosynthesis (phytoanticipins and phytoalexins). Moreover, the regulation of immunity by RNA interference (RNAi) in GM disease-resistant plants is also considered. Therefore, the present review does not cover all the classes of biomolecules involved in plant innate immunity that may be applied in the development of disease-resistant GM crops but instead highlights the most common strategies in the literature, as well as their advantages and disadvantages. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The Characteristics of Binary Spike-Time-Dependent Plasticity in HfO2-Based RRAM and Applications for Pattern Recognition

NASA Astrophysics Data System (ADS)

Zhou, Zheng; Liu, Chen; Shen, Wensheng; Dong, Zhen; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2017-04-01

A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system including RRAM synapses and CMOS neurons is developed. Our simulations show that the system can efficiently compete the handwritten digits recognition task, which indicates the feasibility of using the RRAM-based binary STDP protocol in neuromorphic computing systems to obtain good performance.

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

2002-01-01

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Cocaine- and amphetamine-regulated transcript and calcium binding proteins immunoreactivity in the subicular complex of the guinea pig.

PubMed

Wasilewska, Barbara; Najdzion, Janusz; Równiak, Maciej; Bogus-Nowakowska, Krystyna; Hermanowicz, Beata; Kolenkiewicz, Małgorzata; Żakowski, Witold; Robak, Anna

2016-03-01

In this study we present the distribution and colocalization pattern of cocaine- and amphetamine-regulated transcript (CART) and three calcium-binding proteins: calbindin (CB), calretinin (CR) and parvalbumin (PV) in the subicular complex (SC) of the guinea pig. The subiculum (S) and presubiculum (PrS) showed higher CART-immunoreactivity (-IR) than the parasubiculum (PaS) as far as the perikarya and neuropil were concerned. CART- IR cells were mainly observed in the pyramidal layer and occasionally in the molecular layer of the S. In the PrS and PaS, single CART-IR perikarya were dispersed, however with a tendency to be found only in superficial layers. CART-IR fibers were observed throughout the entire guinea pig subicular neuropil. Double-labeling immunofluorescence showed that CART-IR perikarya, as well as fibers, did not stain positively for any of the three CaBPs. CART-IR fibers were only located near the CB-, CR-, PV-IR perikarya, whereas CART-IR fibers occasionally intersected fibers containing one of the three CaBPs. The distribution pattern of CART was more similar to that of CB and CR than to that of PV. In the PrS, the CART, CB and CR immunoreactivity showed a laminar distribution pattern. In the case of the PV, this distribution pattern in the PrS was much less prominent than that of CART, CB and CR. We conclude that a heterogeneous distribution of the CART and CaBPs in the guinea pig SC is in keeping with findings from other mammals, however species specific differences have been observed. Copyright © 2015 Elsevier GmbH. All rights reserved.

Conformal Predictions in Multimedia Pattern Recognition

ERIC Educational Resources Information Center

Nallure Balasubramanian, Vineeth

2010-01-01

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

ERIC Educational Resources Information Center

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Pattern Recognition Receptors in Innate Immunity, Host Defense, and Immunopathology

ERIC Educational Resources Information Center

Suresh, Rahul; Mosser, David M.

2013-01-01

Infection by pathogenic microbes initiates a set of complex interactions between the pathogen and the host mediated by pattern recognition receptors. Innate immune responses play direct roles in host defense during the early stages of infection, and they also exert a profound influence on the generation of the adaptive immune responses that ensue.…

Machine Learning Through Signature Trees. Applications to Human Speech.

ERIC Educational Resources Information Center

White, George M.

A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Real-Time Pattern Recognition - An Industrial Example

NASA Astrophysics Data System (ADS)

Fitton, Gary M.

1981-11-01

Rapid advancements in cost effective sensors and micro computers are now making practical the on-line implementation of pattern recognition based systems for a variety of industrial applications requiring high processing speeds. One major application area for real time pattern recognition is in the sorting of packaged/cartoned goods at high speed for automated warehousing and return goods cataloging. While there are many OCR and bar code readers available to perform these functions, it is often impractical to use such codes (package too small, adverse esthetics, poor print quality) and an approach which recognizes an item by its graphic content alone is desirable. This paper describes a specific application within the tobacco industry, that of sorting returned cigarette goods by brand and size.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Receptor Kinases in Plant-Pathogen Interactions: More Than Pattern Recognition[OPEN

PubMed Central

2017-01-01

Receptor-like kinases (RLKs) and Receptor-like proteins (RLPs) play crucial roles in plant immunity, growth, and development. Plants deploy a large number of RLKs and RLPs as pattern recognition receptors (PRRs) that detect microbe- and host-derived molecular patterns as the first layer of inducible defense. Recent advances have uncovered novel PRRs, their corresponding ligands, and mechanisms underlying PRR activation and signaling. In general, PRRs associate with other RLKs and function as part of multiprotein immune complexes at the cell surface. Innovative strategies have emerged for the rapid identification of microbial patterns and their cognate PRRs. Successful pathogens can evade or block host recognition by secreting effector proteins to “hide” microbial patterns or inhibit PRR-mediated signaling. Furthermore, newly identified pathogen effectors have been shown to manipulate RLKs controlling growth and development by mimicking peptide hormones of host plants. The ongoing studies illustrate the importance of diverse plant RLKs in plant disease resistance and microbial pathogenesis. PMID:28302675

Developing Signal-Pattern-Recognition Programs

NASA Technical Reports Server (NTRS)

Shelton, Robert O.; Hammen, David

2006-01-01

Pattern Interpretation and Recognition Application Toolkit Environment (PIRATE) is a block-oriented software system that aids the development of application programs that analyze signals in real time in order to recognize signal patterns that are indicative of conditions or events of interest. PIRATE was originally intended for use in writing application programs to recognize patterns in space-shuttle telemetry signals received at Johnson Space Center's Mission Control Center: application programs were sought to (1) monitor electric currents on shuttle ac power busses to recognize activations of specific power-consuming devices, (2) monitor various pressures and infer the states of affected systems by applying a Kalman filter to the pressure signals, (3) determine fuel-leak rates from sensor data, (4) detect faults in gyroscopes through analysis of system measurements in the frequency domain, and (5) determine drift rates in inertial measurement units by regressing measurements against time. PIRATE can also be used to develop signal-pattern-recognition software for different purposes -- for example, to monitor and control manufacturing processes.

Document Form and Character Recognition using SVM

NASA Astrophysics Data System (ADS)

Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

2009-08-01

Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic.

PubMed

Hou, Shi-Wang; Feng, Shunxiao; Wang, Hui

2016-01-01

Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control. If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impossible to be carried out. Considering four common abnormal control chart patterns, this paper proposed a characteristic numbers based recognition method point by point to quantify the occurrence degree of abnormal patterns under uncertain conditions and a fuzzy inference system based on fuzzy logic to calculate the contribution degree of assignable causes with fuzzy abnormal patterns. Application case results show that the proposed approach can give a ranked causes list under fuzzy control chart abnormal patterns and support the abnormity eliminating.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Quantum Mechanics, Pattern Recognition, and the Mammalian Brain

NASA Astrophysics Data System (ADS)

Chapline, George

2008-10-01

Although the usual way of representing Markov processes is time asymmetric, there is a way of describing Markov processes, due to Schrodinger, which is time symmetric. This observation provides a link between quantum mechanics and the layered Bayesian networks that are often used in automated pattern recognition systems. In particular, there is a striking formal similarity between quantum mechanics and a particular type of Bayesian network, the Helmholtz machine, which provides a plausible model for how the mammalian brain recognizes important environmental situations. One interesting aspect of this relationship is that the "wake-sleep" algorithm for training a Helmholtz machine is very similar to the problem of finding the potential for the multi-channel Schrodinger equation. As a practical application of this insight it may be possible to use inverse scattering techniques to study the relationship between human brain wave patterns, pattern recognition, and learning. We also comment on whether there is a relationship between quantum measurements and consciousness.

Mining sequential patterns for protein fold recognition.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

PubMed

Lavine, B K; Brzozowski, D M; Ritter, J; Moores, A J; Mayfield, H T

2001-12-01

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

Complex Event Recognition Architecture

NASA Technical Reports Server (NTRS)

Fitzgerald, William A.; Firby, R. James

2009-01-01

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Winter diversity and expression of proteorhodopsin genes in a polar ocean

PubMed Central

Nguyen, Dan; Maranger, Roxane; Balagué, Vanessa; Coll-Lladó, Montserrat; Lovejoy, Connie; Pedrós-Alió, Carlos

2015-01-01

Mixotrophy is a valuable functional trait used by microbes when environmental conditions vary broadly or resources are limited. In the sunlit waters of the ocean, photoheterotrophy, a form of mixotrophy, is often mediated by proteorhodopsin (PR), a seven helices transmembrane protein binding the retinal chromophore. Altogether, they allow bacteria to capture photic energy for sensory and proton gradient formation cell functions. The seasonal occurrence and diversity of the gene coding for PR in cold oligotrophic polar oceans is not known and PR expression has not yet been reported. Here we show that PR is widely distributed among bacterial taxa, and that PR expression decreased markedly during the winter months in the Arctic Ocean. Gammaproteobacteria-like PR sequences were always dominant. However, within the second most common affiliation, there was a transition from Flavobacteria-like PR in early winter to Alphaproteobacteria-like PR in late winter. The phylogenetic shifts followed carbon dynamics, where patterns in expression were consistent with community succession, as identified by DNA community fingerprinting. Although genes for PR were always present, the trend in decreasing transcripts from January to February suggested reduced functional utility of PR during winter. Under winter darkness, sustained expression suggests that PR may continue to be useful for non-ATP forming functions, such as environmental sensing or small solute transport. The persistence of PR expression in winter among some bacterial groups may offer a competitive advantage, where its multifunctionality enhances microbial survival under harsh polar conditions. PMID:25700336

Winter diversity and expression of proteorhodopsin genes in a polar ocean.

PubMed

Nguyen, Dan; Maranger, Roxane; Balagué, Vanessa; Coll-Lladó, Montserrat; Lovejoy, Connie; Pedrós-Alió, Carlos

2015-08-01

Mixotrophy is a valuable functional trait used by microbes when environmental conditions vary broadly or resources are limited. In the sunlit waters of the ocean, photoheterotrophy, a form of mixotrophy, is often mediated by proteorhodopsin (PR), a seven helices transmembrane protein binding the retinal chromophore. Altogether, they allow bacteria to capture photic energy for sensory and proton gradient formation cell functions. The seasonal occurrence and diversity of the gene coding for PR in cold oligotrophic polar oceans is not known and PR expression has not yet been reported. Here we show that PR is widely distributed among bacterial taxa, and that PR expression decreased markedly during the winter months in the Arctic Ocean. Gammaproteobacteria-like PR sequences were always dominant. However, within the second most common affiliation, there was a transition from Flavobacteria-like PR in early winter to Alphaproteobacteria-like PR in late winter. The phylogenetic shifts followed carbon dynamics, where patterns in expression were consistent with community succession, as identified by DNA community fingerprinting. Although genes for PR were always present, the trend in decreasing transcripts from January to February suggested reduced functional utility of PR during winter. Under winter darkness, sustained expression suggests that PR may continue to be useful for non-ATP forming functions, such as environmental sensing or small solute transport. The persistence of PR expression in winter among some bacterial groups may offer a competitive advantage, where its multifunctionality enhances microbial survival under harsh polar conditions.

Progesterone receptor isoforms expression pattern in the rat brain during the estrous cycle.

PubMed

Guerra-Araiza, C; Cerbón, M A; Morimoto, S; Camacho-Arroyo, I

2000-03-24

Progesterone receptor (PR) isoforms expression was determined in the hypothalamus, the preoptic area, the hippocampus and the frontal cerebral cortex of the rat at 12:00 h on each day of the estrous cycle by using reverse transcription coupled to polymerase chain reaction. Rats under a 14:10 h light-dark cycle, with lights on at 06:00 h were used. We found that PR-B isoform was predominant in the hypothalamus, the preoptic area and the frontal cerebral cortex. Both PR isoforms were similarly expressed in the hippocampus. The highest PR-B expression was found on proestrus day in the hypothalamus; on metestrus in the preoptic area; and on diestrus in the frontal cortex. We observed no changes in PR isoforms expression in the hippocampus during the estrous cycle. These results indicate that PR isoforms expression is differentially regulated during the estrous cycle in distinct brain regions and that PR-B may be involved in progesterone actions upon the hypothalamus, the preoptic area and the frontal cortex of the rat.

Facial emotion recognition deficits in relatives of children with autism are not associated with 5HTTLPR.

PubMed

Neves, Maila de Castro Lourenço das; Tremeau, Fabien; Nicolato, Rodrigo; Lauar, Hélio; Romano-Silva, Marco Aurélio; Correa, Humberto

2011-09-01

A large body of evidence suggests that several aspects of face processing are impaired in autism and that this impairment might be hereditary. This study was aimed at assessing facial emotion recognition in parents of children with autism and its associations with a functional polymorphism of the serotonin transporter (5HTTLPR). We evaluated 40 parents of children with autism and 41 healthy controls. All participants were administered the Penn Emotion Recognition Test (ER40) and were genotyped for 5HTTLPR. Our study showed that parents of children with autism performed worse in the facial emotion recognition test than controls. Analyses of error patterns showed that parents of children with autism over-attributed neutral to emotional faces. We found evidence that 5HTTLPR polymorphism did not influence the performance in the Penn Emotion Recognition Test, but that it may determine different error patterns. Facial emotion recognition deficits are more common in first-degree relatives of autistic patients than in the general population, suggesting that facial emotion recognition is a candidate endophenotype for autism.

An investigation of potential applications of OP-SAPS: Operational Sampled Analog Processors

NASA Technical Reports Server (NTRS)

Parrish, E. A.; Mcvey, E. S.

1977-01-01

The application of OP-SAP's (operational sampled analog processors) in pattern recognition system is summarized. Areas investigated include: (1) human face recognition; (2) a high-speed programmable transversal filter system; (3) discrete word (speech) recognition; and (4) a resolution enhancement system.

Emergent central pattern generator behavior in chemical coupled two-compartment models with time delay

NASA Astrophysics Data System (ADS)

Li, Shanshan; Zhang, Guoshan; Wang, Jiang; Chen, Yingyuan; Deng, Bin

2018-02-01

This paper proposes that modified two-compartment Pinsky-Rinzel (PR) neural model can be used to develop the simple form of central pattern generator (CPG). The CPG is called as 'half-central oscillator', which constructed by two inhibitory chemical coupled PR neurons with time delay. Some key properties of PR neural model related to CPG are studied and proved to meet the requirements of CPG. Using the simple CPG network, we first study the relationship between rhythmical output and key factors, including ambient noise, sensory feedback signals, morphological character of single neuron as well as the coupling delay time. We demonstrate that, appropriate intensity noise can enhance synchronization between two coupled neurons. Different output rhythm of CPG network can be entrained by sensory feedback signals. We also show that the morphology of single neuron has strong effect on the output rhythm. The phase synchronization indexes decrease with the increase of morphology parameter's difference. Through adjusting coupled delay time, we can get absolutely phase synchronization and antiphase state of CPG. Those results of simulation show the feasibility of PR neural model as a valid CPG as well as the emergent behaviors of the particularly CPG.

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

Apparatus for detecting and recognizing analytes based on their crystallization patterns

DOEpatents

Morozov, Victor; Bailey, Charles L.; Vsevolodov, Nikolai N.; Elliott, Adam

2010-12-14

The invention contemplates apparatuses for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization patterns") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. Changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. Also, changes in the crystallization patterns, as well as the character of such changes, can be used as recognition elements in analysis of protein molecules.

Intraspecific Variation in Learning: Worker Wasps Are Less Able to Learn and Remember Individual Conspecific Faces than Queen Wasps.

PubMed

Tibbetts, Elizabeth A; Injaian, Allison; Sheehan, Michael J; Desjardins, Nicole

2018-05-01

Research on individual recognition often focuses on species-typical recognition abilities rather than assessing intraspecific variation in recognition. As individual recognition is cognitively costly, the capacity for recognition may vary within species. We test how individual face recognition differs between nest-founding queens (foundresses) and workers in Polistes fuscatus paper wasps. Individual recognition mediates dominance interactions among foundresses. Three previously published experiments have shown that foundresses (1) benefit by advertising their identity with distinctive facial patterns that facilitate recognition, (2) have robust memories of individuals, and (3) rapidly learn to distinguish between face images. Like foundresses, workers have variable facial patterns and are capable of individual recognition. However, worker dominance interactions are muted. Therefore, individual recognition may be less important for workers than for foundresses. We find that (1) workers with unique faces receive amounts of aggression similar to those of workers with common faces, indicating that wasps do not benefit from advertising their individual identity with a unique appearance; (2) workers lack robust memories for individuals, as they cannot remember unique conspecifics after a 6-day separation; and (3) workers learn to distinguish between facial images more slowly than foundresses during training. The recognition differences between foundresses and workers are notable because Polistes lack discrete castes; foundresses and workers are morphologically similar, and workers can take over as queens. Overall, social benefits and receiver capacity for individual recognition are surprisingly plastic.

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

NASA Astrophysics Data System (ADS)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase-only implementation with lower detection performance than full complex electronic systems. Our study includes pseudo-random pixel encoding techniques for approximating full complex filtering. Optical filter bank implementation is possible and they have the advantage of time averaging the entire filter bank at real time rates. Time-averaged optical filtering is computational comparable to billions of digital operations-per-second. For this reason, we believe future trends in high speed pattern recognition will involve hybrid architectures of both optical and DSP elements.

Radioimmunotherapy of MCF7 breast cancer cell line with 131I-PR81 monoclonal antibody against MUC1: comparison of direct and indirect radioiodination methods.

PubMed

Mohammadnejad, Javad; Rasaee, Mohammad Javad; Babaei, Mohammad Hosein; Paknejad, Malihe; Hasan, Zahir Mohammad; Salouti, Mojtaba; Gandomkar, Mostafa; Sadri, Keyvan

2010-01-01

PR81 is a monoclonal antibody that binds with high affinity to MUC1, which is over expressed on breast and other tumors. The objective of this study was to compare the two labeling methods (direct and indirect radioiodination) for application of this antibody against MUC1 as a radioimmunotherapeutical agent.Monoclonal antibody (PR81) against the tandem repeat of the core protein (MUC1) was prepared, characterized, purified, and labeled with 131I using the direct (chloramin-T) and indirect (Fmoc-D-Tyr (tBu)-D-Tyr (tBu)-D-Lys (Boc)-OH (YYK) attached to N-hydroxysuccinimide as a linker between PR81 and 131I) methods. The immunoreactivity of 131I-PR81 and 131I-TP-PR81 complexes with MUC1 (the native protein), BSA-P20 (a 20 amino acid corresponding the tandem repeat of MUC1) and MCF7 cell line were performed by RIA. In vitro stability of 131I-PR81 and 131I-YYK-peptide-PR81 complexes in human serum was determined by thin layer chromatography (TLC). Cell toxicity and in vitro internalization studies were performed with the MCF7 cell line, and the tissue biodistribution of the 131I-PR81 and 131I- YYK-peptide -PR81 complexes was evaluated in normal BALB/c mice at 4, 24 and 48 hrs. The labeling efficiency was determined by measuring the percentage recovery of radioactivity in the final product relative to the initial activity in the shipment vial, was found to be 59.9% +/- 7.9% for direct and 50% +/- 3.2% for indirect methods. 131I-PR81 and 131I- YYK- peptide -PR81 complexes showed high immunoreactivity towards MUC1 protein, BSA-P20 and MCF7 cell line. In vitro stability of the labeled products in human serum which was measured by thin layer chromatography (TLC) was found to be more than 50% over 24 hr for 131I-PR81 and 70% for 131I- YYK-peptide -PR81 complexes. Cell toxicity and in vitro internalization studies showed that the 131I-PR81 and 131I- YYK-peptide -PR81 complexes inhibited 80% growth of the MCF7 cultured cell lines in vitro in a high concentration and up to 40% of the 131I-PR81 and 60% of the 131I- YYK-peptide -PR81 complexes internalized after 24 h. Biodistribution studies were performed in normal BALB/c mice at 4, 24 and 48 hrs post-injection. Thyroid and stomach levels from PR81 labeled with 131I- YYK-peptide were two- to three- fold less than those with directly labeled 131I-PR81, suggesting low recognition of its D-iodotyrosine residue by endogenous deiodinase. These results show that the indirect labeling was better than the indirect labeling and 131I- YYK-peptide -PR81 may be considered as a promising candidate for therapy of breast cancer.

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

PubMed

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

Effects of Cooperative Group Work Activities on Pre-School Children's Pattern Recognition Skills

ERIC Educational Resources Information Center

Tarim, Kamuran

2015-01-01

The aim of this research is twofold; to investigate the effects of cooperative group-based work activities on children's pattern recognition skills in pre-school and to examine the teachers' opinions about the implementation process. In line with this objective, for the study, 57 children (25 girls and 32 boys) were chosen from two private schools…

VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Lue, Jaw-Chyng

2009-01-01

A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Training Spiking Neural Models Using Artificial Bee Colony

PubMed Central

Vazquez, Roberto A.; Garro, Beatriz A.

2015-01-01

Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Pattern Recognition Control Design

NASA Technical Reports Server (NTRS)

Gambone, Elisabeth A.

2018-01-01

Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

Conditional random fields for pattern recognition applied to structured data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burr, Tom; Skurikhin, Alexei

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Recognition memory strength is predicted by pupillary responses at encoding while fixation patterns distinguish recollection from familiarity.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2011-10-01

Thirty-five healthy participants incidentally encoded a set of man-made and natural object pictures, while their pupil response and eye movements were recorded. At retrieval, studied and new stimuli were rated as novel, familiar (strong, moderate, or weak), or recollected. We found that both pupil response and fixation patterns at encoding predict later recognition memory strength. The extent of pupillary response accompanying incidental encoding was found to be predictive of subsequent memory. In addition, the number of fixations was also predictive of later recognition memory strength, suggesting that the accumulation of greater visual detail, even for single objects, is critical for the creation of a strong memory. Moreover, fixation patterns at encoding distinguished between recollection and familiarity at retrieval, with more dispersed fixations predicting familiarity and more clustered fixations predicting recollection. These data reveal close links between the autonomic control of pupil responses and eye movement patterns on the one hand and memory encoding on the other. Moreover, the data illustrate quantitative as well as qualitative differences in the incidental visual processing of stimuli, which are differentially predictive of the strength and the kind of memory experienced at recognition.

STATUS OF THE SYSTEM OF SIGNALING PATTERN RECOGNITION RECEPTORS OF MONOCYTES AND GRANULOCYTES IN COSMONAUTS' PERIPHERAL BLOOD BEFORE AND AFTER LONG-DURATION MISSIONS TO THE INTERNATIONAL SPACE STATION.

PubMed

Ponomarev, S A; Berendeeva, T A; Kalinin, S A; Muranova, A V

The system of signaling pattern recognition receptors was studied in 8 cosmonauts aged 35 to 56 years before and after (R+) long-duration missions to the International space station. Peripheral blood samples were analyzed for the content of monocytes and granulocytes that express the signaling pattern recognition Toll- like (TLR) receptors localized as on cell surface (TLR1, TLR2, TLR4, TLR5, TLR6), so inside cells (TLR3, TLR8, TLR9). In parallel, serum concentrations of TLR2 (HSP60) and TLR4 ligands (HSP70, HMGB1) were measured. The results of investigations showed growth of HSP60, HSP70 and HMGB1 concentrations on R+1. In the;majority of cosmonauts increases in endogenous ligands were followed by growth in the number of both monocytes and granulocytes that express TLR2 1 TLR4. This consistency gives ground to assume that changes in the system of signaling pattern recognition receptors can stem .from the predominantly endogenous ligands' response to the effects of long-duration space flight on human organism.

Conditional random fields for pattern recognition applied to structured data

DOE PAGES

Burr, Tom; Skurikhin, Alexei

2015-07-14

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Neonatal Recognition Processes and Attachment: The Masking Experiment.

ERIC Educational Resources Information Center

Cassel, Thomas Z. K.; Sander, Louis W.

This research project was designed to determine whether 1-week-old neonates would indicate biological recognition of their mothers. Biological recognition is defined as the particular configuration of sensory, kinesthetic, and motor cues and the temporal patterning of these cues which characterizes infants' exchange processes with their…

Structural, kinetic, and thermodynamic studies of specificity designed HIV-1 protease.

PubMed

Alvizo, Oscar; Mittal, Seema; Mayo, Stephen L; Schiffer, Celia A

2012-07-01

HIV-1 protease recognizes and cleaves more than 12 different substrates leading to viral maturation. While these substrates share no conserved motif, they are specifically selected for and cleaved by protease during viral life cycle. Drug resistant mutations evolve within the protease that compromise inhibitor binding but allow the continued recognition of all these substrates. While the substrate envelope defines a general shape for substrate recognition, successfully predicting the determinants of substrate binding specificity would provide additional insights into the mechanism of altered molecular recognition in resistant proteases. We designed a variant of HIV protease with altered specificity using positive computational design methods and validated the design using X-ray crystallography and enzyme biochemistry. The engineered variant, Pr3 (A28S/D30F/G48R), was designed to preferentially bind to one out of three of HIV protease's natural substrates; RT-RH over p2-NC and CA-p2. In kinetic assays, RT-RH binding specificity for Pr3 increased threefold compared to the wild-type (WT), which was further confirmed by isothermal titration calorimetry. Crystal structures of WT protease and the designed variant in complex with RT-RH, CA-p2, and p2-NC were determined. Structural analysis of the designed complexes revealed that one of the engineered substitutions (G48R) potentially stabilized heterogeneous flap conformations, thereby facilitating alternate modes of substrate binding. Our results demonstrate that while substrate specificity could be engineered in HIV protease, the structural pliability of protease restricted the propagation of interactions as predicted. These results offer new insights into the plasticity and structural determinants of substrate binding specificity of the HIV-1 protease. Copyright © 2012 The Protein Society.

Enhancing HIV Pre-exposure, Prophylaxis Practices via an Educational Intervention.

PubMed

Newman, Rebecca; Katchi, Tasleem; Karass, Michael; Gennarelli, Melissa; Goutis, Jason; Kifayat, Alina; Solanki, Shantanu; Yandrapalli, Srikanth; Forman, Leanne; Nabors, Christopher

2018-04-20

Pre-exposure prophylaxis (PrEP) for HIV involves using antiretroviral drugs to prevent individuals at high risk from acquiring HIV infection. Most practicing primary care providers believe PrEP to be safe and effective, but less than half have prescribed or referred for PrEP. Attitudes and prescribing patterns among house officers have not been well described previously. Can an educational intervention enhance HIV PrEP practices among internal medicine house officers? This study relied on a pretest/posttest design. All categorical trainees at a medium-sized internal medicine program were offered a baseline survey to assess their knowledge on PrEP. This was followed by a PrEP-focused educational intervention and a postintervention survey. Likert scales captured perceptions regarding safety, effectiveness, barriers, factors that would promote PrEP use, potential side effects, impact on risk-taking behavior, and provider comfort level in assessing behavioral risks and in PrEP prescribing. Data were analyzed using descriptive statistics, Wilcoxon signed rank test, and the Kruskal-Wallis test. Significance was accepted for P < 0.05. Forty-eight (100%) trainees participated in the educational session, 45 (94%) in a preintervention survey, and 36 (75%) in a postintervention survey. Before PrEP training, 22% of respondents were unaware of PrEP, 78% believed PrEP was effective, 66% believed PrEP was safe, 62% had fair or poor awareness of side effects; 18% of residents had referred for or prescribed PrEP, and 31% believed they were likely to prescribe PrEP in the next 6 months. After the intervention, 94% of trainees believed PrEP was effective (P < 0.001), 92% believed PrEP was safe (P < 0.001), and two-thirds believed they were likely to prescribe PrEP in the next 6 months. Brief, focused training on HIV prevention promotes awareness, acceptance, and likelihood of prescribing PrEP by internal medicine trainees.

A novel application of multi-event modeling to estimate class segregation in a highly migratory oceanic vertebrate.

PubMed

Chapple, T K; Chambert, T; Kanive, P E; Jorgensen, S J; Rotella, J J; Anderson, S D; Carlisle, A B; Block, B A

2016-12-01

Spatial segregation of animals by class (i.e., maturity or sex) within a population due to differential rates of temporary emigration (TE) from study sites can be an important life history feature to consider in population assessment and management. However, such rates are poorly known; new quantitative approaches to address these knowledge gaps are needed. We present a novel application of multi-event models that takes advantage of two sources of detections to differentiate temporary emigration from apparent absence to quantify class segregation within a study population of double-marked (photo-identified and tagged with coded acoustic transmitters) white sharks (Carcharodon carcharias) in central California. We use this model to test if sex-specific patterns in TE result in disparate apparent capture probabilities (p o ) between male and female white sharks, which can affect the observed sex ratio. The best-supported model showed a contrasting pattern of Pr(TE) from coastal aggregation sites between sexes (for males Pr[TE] = 0.015 [95% CI = 0.00, 0.31] and Pr[TE]= 0.57 [0.40, 0.72] for females), but not maturity classes. Additionally, by accounting for Pr(TE) and imperfect detection, we were able to estimate class-specific values of true capture probability (p * ) for tagged and untagged sharks. The best-supported model identified differences between maturity classes but no difference between sexes or tagging impacts (tagged mature sharks p *  = 0.55 (0.46-0.63) and sub-adult sharks p*   = 0.36 (0.25, 0.50); and untagged mature sharks p *  = 0.50 (0.39-0.61) and sub-adults p *  = 0.18 (0.10, 0.31). Estimated sex-based differences in p o were linked to sex-specific differences in Pr(TE) but not in p * ; once the Pr(TE) is accounted for, the p * between sexes was not different. These results indicate that the observed sex ratio is not a consequence of unequal detectability and sex-specific values of Pr(TE) are important drivers of the observed male-dominated sex ratio. Our modeling approach reveals complex class-specific patterns in Pr(TE) and p * in a mark-recapture data set, and highlights challenges for the population modeling and conservation of white sharks in central California. The model we develop here can be used to estimate rates of temporary emigration and class segregation when two detection methods are used. © 2016 by the Ecological Society of America.

Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.

Context-aware mobile health monitoring: evaluation of different pattern recognition methods for classification of physical activity.

PubMed

Jatobá, Luciana C; Grossmann, Ulrich; Kunze, Chistophe; Ottenbacher, Jörg; Stork, Wilhelm

2008-01-01

There are various applications of physical activity monitoring for medical purposes, such as therapeutic rehabilitation, fitness enhancement or the use of physical activity as context information for evaluation of other vital data. Physical activity can be estimated using acceleration sensor-systems fixed on a person's body. By means of pattern recognition methods, it is possible to identify with certain accuracy which movement is being performed. This work presents a comparison of different methods for recognition of daily-life activities, which will serve as basis for the development of an online activity monitoring system.

A new approach for cancelable iris recognition

NASA Astrophysics Data System (ADS)

Yang, Kai; Sui, Yan; Zhou, Zhi; Du, Yingzi; Zou, Xukai

2010-04-01

The iris is a stable and reliable biometric for positive human identification. However, the traditional iris recognition scheme raises several privacy concerns. One's iris pattern is permanently bound with him and cannot be changed. Hence, once it is stolen, this biometric is lost forever as well as all the applications where this biometric is used. Thus, new methods are desirable to secure the original pattern and ensure its revocability and alternatives when compromised. In this paper, we propose a novel scheme which incorporates iris features, non-invertible transformation and data encryption to achieve "cancelability" and at the same time increases iris recognition accuracy.

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition.

PubMed

Brown, Shannon; Ortiz-Catalan, Max; Petersson, Joel; Rodby, Kristian; Seoane, Fernando

2016-08-01

Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.

United States Homeland Security and National Biometric Identification

DTIC Science & Technology

2002-04-09

security number. Biometrics is the use of unique individual traits such as fingerprints, iris eye patterns, voice recognition, and facial recognition to...technology to control access onto their military bases using a Defense Manpower Management Command developed software application. FACIAL Facial recognition systems...installed facial recognition systems in conjunction with a series of 200 cameras to fight street crime and identify terrorists. The cameras, which are

The Wireless Ubiquitous Surveillance Testbed

DTIC Science & Technology

2003-03-01

c. Eye Patterns.............................................................................17 d. Facial Recognition ..................................................................19...27). ...........................................98 Table F.4. Facial Recognition Products. (After: Polemi, p. 25 and BiometriTech, 15 May 2002...it applies to homeland security. C. RESEARCH TASKS The main goals of this thesis are to: • Set up the biometric sensors and facial recognition surveillance

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

Asymmetries in Early Word Recognition: The Case of Stops and Fricatives

ERIC Educational Resources Information Center

Altvater-Mackensen, Nicole; van der Feest, Suzanne V. H.; Fikkert, Paula

2014-01-01

Toddlers' discrimination of native phonemic contrasts is generally unproblematic. Yet using those native contrasts in word learning and word recognition can be more challenging. In this article, we investigate perceptual versus phonological explanations for asymmetrical patterns found in early word recognition. We systematically investigated the…

Major Dietary Patterns in Relation to General and Central Obesity among Chinese Adults.

PubMed

Yu, Canqing; Shi, Zumin; Lv, Jun; Du, Huaidong; Qi, Lu; Guo, Yu; Bian, Zheng; Chang, Liang; Tang, Xuefeng; Jiang, Qilian; Mu, Huaiyi; Pan, Dongxia; Chen, Junshi; Chen, Zhengming; Li, Liming

2015-07-15

Limited evidence exists for the association between diet pattern and obesity phenotypes among Chinese adults. In the present study, we analyzed the cross-sectional data from 474,192 adults aged 30-79 years from the China Kadoorie Biobank baseline survey. Food consumption was collected by an interviewer-administered questionnaire. Three dietary patterns were extracted by factor analysis combined with cluster analysis. After being adjusted for potential confounders, individuals following a traditional southern dietary pattern had the lowest body mass index (BMI) and waist circumference (WC); the Western/new affluence dietary pattern had the highest BMI; and the traditional northern dietary pattern had the highest WC. Compared to the traditional southern dietary pattern in multivariable adjusted logistic models, individuals following a Western/new affluence dietary pattern had a significantly increased risk of general obesity (prevalence ratio (PR): 1.06, 95% confidence interval (CI): 1.03-1.08) and central obesity (PR: 1.07, 95% CI: 1.06-1.08). The corresponding risks for the traditional northern dietary pattern were 1.05 (1.02-1.09) and 1.17 (1.25-1.18), respectively. In addition, the associations were modified by lifestyle behaviors, and the combined effects with alcohol drinking, tobacco smoking, and physical activity were analyzed. Further prospective studies are needed to elucidate the diet-obesity relationships.

The impact of direct-to-consumer personal genomic testing on perceived risk of breast, prostate, colorectal, and lung cancer: findings from the PGen study.

PubMed

Carere, Deanna Alexis; VanderWeele, Tyler; Moreno, Tanya A; Mountain, Joanna L; Roberts, J Scott; Kraft, Peter; Green, Robert C

2015-10-15

Direct access to genomic information has the potential to transform cancer risk counseling. We measured the impact of direct-to-consumer genomic risk information on changes to perceived risk (ΔPR) of breast, prostate, colorectal and lung cancer among personal genomic testing (PGT) customers. We hypothesized that ΔPR would reflect directionality of risk estimates, attenuate with time, and be modified by participant characteristics. Pathway Genomics and 23andMe customers were surveyed prior to receiving PGT results, and 2 weeks and 6 months post-results. For each cancer, PR was measured on a 5-point ordinal scale from "much lower than average" to "much higher than average." PGT results, based on genotyping of common genetic variants, were dichotomized as elevated or average risk. The relationship between risk estimate and ΔPR was evaluated with linear regression; generalized estimating equations modeled this relationship over time. With the exception of lung cancer (for which ΔPR was positive regardless of result), elevated risk results were significantly associated with positive ΔPR, and average risk results with negative ΔPR (e.g., prostate cancer, 2 weeks: least squares-adjusted ΔPR = 0.77 for elevated risk versus -0.21 for average risk; p-valuedifference < 0.0001) among 1154 participants. Large changes were rare: for each cancer, <4 % of participants overall reported a ΔPR of ±3 or more units. Effect modification by age, cancer family history, and baseline interest was observed for breast, colorectal, and lung cancer, respectively. A pattern of decreasing impact on ΔPR over time was consistently observed, but this trend was significant only in the case of colorectal cancer. We have quantified the effect on consumer risk perception of returning genetic-based cancer risk information directly to consumers without clinician mediation. Provided via PGT, this information has a measurable but modest effect on perceived cancer risk, and one that is in some cases modified by consumers' non-genetic risk context. Our observations of modest marginal effect sizes, infrequent extreme changes in perceived risk, and a pattern of diminishing impact with time, suggest that the ability of PGT to effect changes to cancer screening and prevention behaviors may be limited by relatively small changes to perceived risk.

Querying Proofs

NASA Technical Reports Server (NTRS)

Aspinall, David; Denney, Ewen; Lueth, Christoph

2012-01-01

We motivate and introduce a query language PrQL designed for inspecting machine representations of proofs. PrQL natively supports hiproofs which express proof structure using hierarchical nested labelled trees. The core language presented in this paper is locally structured (first-order), with queries built using recursion and patterns over proof structure and rule names. We define the syntax and semantics of locally structured queries, demonstrate their power, and sketch some implementation experiments.

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

PubMed Central

Singhal, Hari; Greene, Marianne E.; Tarulli, Gerard; Zarnke, Allison L.; Bourgo, Ryan J.; Laine, Muriel; Chang, Ya-Fang; Ma, Shihong; Dembo, Anna G.; Raj, Ganesh V.; Hickey, Theresa E.; Tilley, Wayne D.; Greene, Geoffrey L.

2016-01-01

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor–positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observed with PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PR modulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER+/PR+ breast cancers should be explored. PMID:27386569

Inconsistent emotion recognition deficits across stimulus modalities in Huntington׳s disease.

PubMed

Rees, Elin M; Farmer, Ruth; Cole, James H; Henley, Susie M D; Sprengelmeyer, Reiner; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z; Tabrizi, Sarah J

2014-11-01

Recognition of negative emotions is impaired in Huntington׳s Disease (HD). It is unclear whether these emotion-specific problems are driven by dissociable cognitive deficits, emotion complexity, test cue difficulty, or visuoperceptual impairments. This study set out to further characterise emotion recognition in HD by comparing patterns of deficits across stimulus modalities; notably including for the first time in HD, the more ecologically and clinically relevant modality of film clips portraying dynamic facial expressions. Fifteen early HD and 17 control participants were tested on emotion recognition from static facial photographs, non-verbal vocal expressions and one second dynamic film clips, all depicting different emotions. Statistically significant evidence of impairment of anger, disgust and fear recognition was seen in HD participants compared with healthy controls across multiple stimulus modalities. The extent of the impairment, as measured by the difference in the number of errors made between HD participants and controls, differed according to the combination of emotion and modality (p=0.013, interaction test). The largest between-group difference was seen in the recognition of anger from film clips. Consistent with previous reports, anger, disgust and fear were the most poorly recognised emotions by the HD group. This impairment did not appear to be due to task demands or expression complexity as the pattern of between-group differences did not correspond to the pattern of errors made by either group; implicating emotion-specific cognitive processing pathology. There was however evidence that the extent of emotion recognition deficits significantly differed between stimulus modalities. The implications in terms of designing future tests of emotion recognition and care giving are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

Results and conclusions are presented on the application of recent developments in pattern recognition to spacecraft star mapping systems. Sensor data for two representative starfields are processed by an adaptive shape-seeking version of the Fc-V algorithm with good results. Cluster validity measures are evaluated, but not found especially useful to this application. Recommendations are given two system configurations worthy of additional study,

Sporadic fatal insomnia in a young woman: A diagnostic challenge: Case Report

PubMed Central

2011-01-01

Background Sporadic fatal insomnia (sFI) and fatal familial insomnia (FFI) are rare human prion diseases. Case Presentation We report a case of a 33-year-old female who died of a prion disease for whom the diagnosis of sFI or FFI was not considered clinically. Following death of this patient, an interview with a close family member indicated the patient's illness included a major change in her sleep pattern, corroborating the reported autopsy diagnosis of sFI. Genetic tests identified no prion protein (PrP) gene mutation, but neuropathological examination and molecular study showed protease-resistant PrP (PrPres) in several brain regions and severe atrophy of the anterior-ventral and medial-dorsal thalamic nuclei similar to that described in FFI. Conclusions In patients with suspected prion disease, a characteristic change in sleep pattern can be an important clinical clue for identifying sFI or FFI; polysomnography (PSG), genetic analysis, and nuclear imaging may aid in diagnosis. PMID:22040318

Eating Patterns and Health Outcomes in Patients With Type 2 Diabetes.

PubMed

Aguiar Sarmento, Roberta; Peçanha Antonio, Juliana; Lamas de Miranda, Ingrid; Bellicanta Nicoletto, Bruna; Carnevale de Almeida, Jussara

2018-01-01

To evaluate the relationship between eating patterns and therapeutic target's achieving in patients with type 2 diabetes. In this cross-sectional study, patients underwent clinical, laboratory, and nutritional evaluations. Dietary intake was assessed by a quantitative food frequency questionnaire and eating patterns identified by cluster analysis. The therapeutic targets were as follows: blood pressure, <140/90 mm Hg; BMI, <25 kg/m 2 (<27 kg/m 2 for elderly); waist circumference, <94 cm for men and <80 cm for women; fasting plasma glucose, <130 mg/dL; HbA1c, <7%; triglycerides, <150 mg/dL; HDL-cholesterol, >40 mg/dL for men and >50 mg/dL for women; LDL-cholesterol, <100 mg/dL. One hundred ninety seven patients were studied. We identified two eating patterns: "unhealthy" (n = 100)-high consumption of refined carbohydrates, ultra-processed foods, sweets and desserts ( P < 0.05); and "healthy" (n = 97)-high intake of whole carbohydrates, dairy, white meat, fish, fruits and vegetables ( P < 0.05). The healthy group more frequently achieved therapeutic targets for fasting plasma glucose, HbA1c, and LDL-cholesterol than the unhealthy group. Poisson regression confirmed the association of healthy eating pattern with attaining the therapeutic target for fasting plasma glucose [PR, 1.59 (95% CI, 1.01 to 2.34); P = 0.018], HbA1c [PR, 2.09 (95% CI, 1.17 to 3.74); P = 0.013], and LDL-cholesterol [PR, 1.37 (95% CI, 1.01 to 1.86); P = 0.042]. A healthy eating pattern, including the frequent intake of whole carbohydrates, dairy, white meat, fish, fruits, and vegetables, is associated with reduced fasting plasma glucose, HbA1c, and LDL cholesterol levels in patients with type 2 diabetes.

Method of synthesized phase objects for pattern recognition with rotation invariance

NASA Astrophysics Data System (ADS)

Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

2015-11-01

We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.

Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

NASA Astrophysics Data System (ADS)

Poock, G. K.; Martin, B. J.

1984-02-01

This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

Brain angiogenesis inhibitor 1 (BAI1) is a pattern recognition receptor that mediates macrophage binding and engulfment of Gram-negative bacteria

PubMed Central

Das, Soumita; Owen, Katherine A.; Ly, Kim T.; Park, Daeho; Black, Steven G.; Wilson, Jeffrey M.; Sifri, Costi D.; Ravichandran, Kodi S.; Ernst, Peter B.; Casanova, James E.

2011-01-01

Bacterial recognition by host cells is essential for initiation of infection and the host response. Bacteria interact with host cells via multiple pattern recognition receptors that recognize microbial products or pathogen-associated molecular patterns. In response to this interaction, host cell signaling cascades are activated that lead to inflammatory responses and/or phagocytic clearance of attached bacteria. Brain angiogenesis inhibitor 1 (BAI1) is a receptor that recognizes apoptotic cells through its conserved type I thrombospondin repeats and triggers their engulfment through an ELMO1/Dock/Rac1 signaling module. Because thrombospondin repeats in other proteins have been shown to bind bacterial surface components, we hypothesized that BAI1 may also mediate the recognition and clearance of pathogenic bacteria. We found that preincubation of bacteria with recombinant soluble BAI1 ectodomain or knockdown of endogenous BAI1 in primary macrophages significantly reduced binding and internalization of the Gram-negative pathogen Salmonella typhimurium. Conversely, overexpression of BAI1 enhanced attachment and engulfment of Salmonella in macrophages and in heterologous nonphagocytic cells. Bacterial uptake is triggered by the BAI1-mediated activation of Rac through an ELMO/Dock-dependent mechanism, and inhibition of the BAI1/ELMO1 interaction prevents both Rac activation and bacterial uptake. Moreover, inhibition of ELMO1 or Rac function significantly impairs the proinflammatory response to infection. Finally, we show that BAI1 interacts with a variety of Gram-negative, but not Gram-positive, bacteria through recognition of their surface lipopolysaccharide. Together these findings identify BAI1 as a pattern recognition receptor that mediates nonopsonic phagocytosis of Gram-negative bacteria by macrophages and directly affects the host response to infection. PMID:21245295

Blockade of the 5-HT transporter contributes to the behavioural, neuronal and molecular effects of cocaine.

PubMed

Simmler, Linda D; Anacker, Allison M J; Levin, Michael H; Vaswani, Nina M; Gresch, Paul J; Nackenoff, Alex G; Anastasio, Noelle C; Stutz, Sonja J; Cunningham, Kathryn A; Wang, Jing; Zhang, Bing; Henry, L Keith; Stewart, Adele; Veenstra-VanderWeele, Jeremy; Blakely, Randy D

2017-08-01

The psychostimulant cocaine induces complex molecular, cellular and behavioural responses as a consequence of inhibiting presynaptic dopamine, noradrenaline and 5-HT transporters. To elucidate 5-HT transporter (SERT)-specific contributions to cocaine action, we evaluated cocaine effects in the SERT Met172 knock-in mouse, which expresses a SERT coding substitution that eliminates high-affinity cocaine recognition. We measured the effects of SERT Met172 on cocaine antagonism of 5-HT re-uptake using ex vivo synaptosome preparations and in vivo microdialysis. We assessed SERT dependence of cocaine actions behaviourally through acute and chronic locomotor activation, sensitization, conditioned place preference (CPP) and oral cocaine consumption. We used c-Fos, quantitative RT-PCR and RNA sequencing methods for insights into cellular and molecular networks supporting SERT-dependent cocaine actions. SERT Met172 mice demonstrated functional insensitivity for cocaine at SERT. Although they displayed wild-type levels of acute cocaine-induced hyperactivity or chronic sensitization, the pattern of acute motor activation was different, with a bias toward thigmotaxis. CPP was increased, and a time-dependent elevation in oral cocaine consumption was observed. SERT Met172 mice displayed relatively higher levels of neuronal activation in the hippocampus, piriform cortex and prelimbic cortex (PrL), accompanied by region-dependent changes in immediate early gene expression. Distinct SERT-dependent gene expression networks triggered by acute and chronic cocaine administration were identified, including PrL Akt and nucleus accumbens ERK1/2 signalling. Our studies reveal distinct SERT contributions to cocaine action, reinforcing the possibility of targeting specific aspects of cocaine addiction by modulation of 5-HT signalling. © 2017 The British Pharmacological Society.

Molecular Features of the Copper Binding Sites in the Octarepeat Domain of the Prion Protein†

PubMed Central

Burns, Colin S.; Aronoff-Spencer, Eliah; Dunham, Christine M.; Lario, Paula; Avdievich, Nikolai I.; Antholine, William E.; Olmstead, Marilyn M.; Vrielink, Alice; Gerfen, Gary J.; Peisach, Jack; Scott, William G.; Millhauser, Glenn L.

2010-01-01

Recent evidence suggests that the prion protein (PrP) is a copper binding protein. The N-terminal region of human PrP contains four sequential copies of the highly conserved octarepeat sequence PHGGGWGQ spanning residues 60–91. This region selectively binds Cu2+ in vivo. In a previous study using peptide design, EPR, and CD spectroscopy, we showed that the HGGGW segment within each octarepeat comprises the fundamental Cu2+ binding unit [Aronoff-Spencer et al. (2000) Biochemistry 40, 13760–13771]. Here we present the first atomic resolution view of the copper binding site within an octarepeat. The crystal structure of HGGGW in a complex with Cu2+ reveals equatorial coordination by the histidine imidazole, two deprotonated glycine amides, and a glycine carbonyl, along with an axial water bridging to the Trp indole. Companion S-band EPR, X-band ESEEM, and HYSCORE experiments performed on a library of 15N-labeled peptides indicate that the structure of the copper binding site in HGGGW and PHGGGWGQ in solution is consistent with that of the crystal structure. Moreover, EPR performed on PrP(23–28, 57–91) and an 15N-labeled analogue demonstrates that the identified structure is maintained in the full PrP octarepeat domain. It has been shown that copper stimulates PrP endocytosis. The identified Gly–Cu linkage is unstable below pH ≈6.5 and thus suggests a pH-dependent molecular mechanism by which PrP detects Cu2+ in the extracellular matrix or releases PrP-bound Cu2+ within the endosome. The structure also reveals an unusual complementary interaction between copper-structured HGGGW units that may facilitate molecular recognition between prion proteins, thereby suggesting a mechanism for transmembrane signaling and perhaps conversion to the pathogenic form. PMID:11900542

Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

PubMed

Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

2013-01-01

The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD. © 2012 Blackwell Publishing Ltd.

Beyond sensory images: Object-based representation in the human ventral pathway

PubMed Central

Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

Diversity in genomic organisation, developmental regulation and distribution of the murine PR72/B" subunits of protein phosphatase 2A

PubMed Central

Zwaenepoel, Karen; Louis, Justin V; Goris, Jozef; Janssens, Veerle

2008-01-01

Background Protein phosphatase 2A (PP2A) is a serine/threonine-specific phosphatase displaying vital functions in growth and development through its role in various signalling pathways. PP2A holoenzymes comprise a core dimer composed of a catalytic C and a structural A subunit, which can associate with a variable B-type subunit. The importance of the B-type subunits for PP2A regulation cannot be overestimated as they determine holoenzyme localisation, activity and substrate specificity. Three B-type subunit families have been identified: PR55/B, PR61/B' and PR72/B", of which the latter is currently the least characterised. Results We deduced the sequences and genomic organisation of the different murine PR72/B" isoforms: three genes encode nine isoforms, five of which are abundantly expressed and give rise to genuine PP2A subunits. Thereby, one novel subunit was identified. Using Northern blotting, we examined the tissue-specific and developmental expression of these subunits. All subunits are highly expressed in heart, suggesting an important cardiac function. Immunohistochemical analysis revealed a striated expression pattern of PR72 and PR130 in heart and skeletal muscle, but not in bladder smooth muscle. The subcellular localisation and cell cycle regulatory ability of several PR72/B" isoforms were determined, demonstrating differences as well as similarities. Conclusion In contrast to PR55/B and PR61/B', the PR72/B" family seems evolutionary more divergent, as only two of the murine genes have a human orthologue. We have integrated these results in a more consistent nomenclature of both human and murine PR72/B" genes and their transcripts/proteins. Our results provide a platform for the future generation of PR72/B" knockout mice. PMID:18715506

Different 2-Aminothiazole Therapeutics Produce Distinct Patterns of Scrapie Prion Neuropathology in Mouse Brains.

PubMed

Giles, Kurt; Berry, David B; Condello, Carlo; Hawley, Ronald C; Gallardo-Godoy, Alejandra; Bryant, Clifford; Oehler, Abby; Elepano, Manuel; Bhardwaj, Sumita; Patel, Smita; Silber, B Michael; Guan, Shenheng; DeArmond, Stephen J; Renslo, Adam R; Prusiner, Stanley B

2015-10-01

Because no drug exists that halts or even slows any neurodegenerative disease, developing effective therapeutics for any prion disorder is urgent. We recently reported two compounds (IND24 and IND81) with the 2-aminothiazole (2-AMT) chemical scaffold that almost doubled the incubation times in scrapie prion-infected, wild-type (wt) FVB mice when given in a liquid diet. Remarkably, oral prophylactic treatment with IND24 beginning 14 days prior to intracerebral prion inoculation extended survival from ∼120 days to over 450 days. In addition to IND24, we evaluated the pharmacokinetics and efficacy of five additional 2-AMTs; one was not followed further because its brain penetration was poor. Of the remaining four new 2-AMTs, IND114338 doubled and IND125 tripled the incubation times of RML-inoculated wt and Tg4053 mice overexpressing wt mouse prion protein (PrP), respectively. Neuropathological examination of the brains from untreated controls showed a widespread deposition of self-propagating, β-sheet-rich "scrapie" isoform (PrP(Sc)) prions accompanied by a profound astrocytic gliosis. In contrast, mice treated with 2-AMTs had lower levels of PrP(Sc) and associated astrocytic gliosis, with each compound resulting in a distinct pattern of deposition. Notably, IND125 prevented both PrP(Sc) accumulation and astrocytic gliosis in the cerebrum. Progressive central nervous system dysfunction in the IND125-treated mice was presumably due to the PrP(Sc) that accumulated in their brainstems. Disappointingly, none of the four new 2-AMTs prolonged the lives of mice expressing a chimeric human/mouse PrP transgene inoculated with Creutzfeldt-Jakob disease prions. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

SYMPTOMS OF ANXIETY ON BOTH SIDES OF THE US-MEXICO BORDER: THE ROLE OF IMMIGRATION

PubMed Central

Borges, Guilherme; Zamora, Beatriz; García, José; Orozco, Ricardo; Cherpitel, Cheryl J.; Zemore, Sarah E.; Breslau, Joshua

2014-01-01

Home to about 15 million people, the US-Mexico border area has suffered stresses from increased border security efforts and a costly drug war in Mexico. Whether immigration patterns add to increasing levels of anxiety for the Mexican population and the Mexican-origin individuals living in the US-Mexico border and near the border is unknown. We used the US-Mexico Study on Alcohol and Related Conditions (UMSARC), a cross-sectional survey (2011–2013) of individuals living in border and non-border cities of the US (n=2,336) and Mexico (n=2,460). In Mexico respondents were asked if they ever migrated to the US or have a family member living in the US (328) or not (2,124), while in the US respondents were asked if they were born in Mexico (697), born in the US with no US-born parents (second generation, 702) or born in the US with at least one US-born parent (third generation, 932). The prevalence and risk factors for symptoms of anxiety using the Beck Anxiety Inventory (>=10) were obtained. Mexicans with no migrant experience had a prevalence of anxiety and adjusted prevalence ratio (PR) within the last month of 6.7% (PR=reference), followed by Mexicans with migration experience of 13.1% (PR=1.8), Mexican-born respondents living in the US of 17.3% (PR=2.6), US born Mexican-Americans of 2nd generation of 18.6% (PR=3.3) and finally US born 3rd+ generation of 25.9% (PR=3.8). Results help to identify regions and migration patterns at high risk for anxiety and may help to unravel causal mechanisms that underlie this risk. PMID:25543519

Understanding the HIV-1 protease nelfinavir resistance mutation D30N in subtypes B and C through molecular dynamics simulations.

PubMed

Soares, Rosemberg O; Batista, Paulo R; Costa, Mauricio G S; Dardenne, Laurent E; Pascutti, Pedro G; Soares, Marcelo A

2010-09-01

A major concern in the antiretroviral (ARV) treatment of HIV infections with protease inhibitors (PI) is the emergence of resistance, which results from the selection of distinct mutations within the viral protease (PR) gene. Among patients who do not respond to treatment with the PI nelfinavir (NFV), the D30N mutation is often observed. However, several reports have shown that D30N emerges with different frequencies in distinct HIV-1 genetic forms or subtypes. In the present work, we analyzed the binding of NFV and the Gag substrate CA/p2 to PR from HIV-1 subtypes B and C through molecular dynamics (MD) simulations. The wild-type and drug-resistant D30N mutants were investigated in both subtypes. The compensatory mutations N83T and N88D, observed in vitro and in vivo when subtype C acquires D30N, were also studied. D30N appears to facilitate conformational changes in subtype B PR, but not in that from subtype C, and this could be associated with disestablishment of an alpha-helical region of the PR. Furthermore, the total contact areas of NFV or the CA/p2 substrate with the mutant PR correlated with changes in the resistance patterns and replicative capacity. Finally, we observed in our MD simulations that mutant PR proteins show different patterns for hydrophobic/van der Waals contact. These findings suggest that different molecular mechanisms contribute to resistance, and we propose that a single mutation has distinct impacts on different HIV-1 subtypes. (c) 2010 Elsevier Inc. All rights reserved.

Identifying the "vulnerables" in biomedical research: the vox populis from the Tuskegee Legacy Project.

PubMed

Chiu, Christopher T; Katz, Ralph V

2011-01-01

This report presents, for the first time, findings on the vox populis as to who constitutes the "vulnerables in biomedical research" The 3-City Tuskegee Legacy Project (TLP) study used the TLP questionnaire as administered via random-digit-dial telephone interviews to 1162 adult Black people, non-Hispanic White people, and two Puerto Rican (PR) Hispanic groups: Mainland United States and San Juan (SJ) in three cities. The classification schema was based upon respondents' answers to an open-ended question asking which groups of people were the most vulnerable when participating in biomedical research. Subjects provided 749 valid open-ended responses, which were grouped into 29 direct response categories, leading to a four-tier classification schema for vulnerability traits. Tier 1, the summary tier, had five vulnerability categories: (1) Race/ ethnicity; (2) Age; (3) SES; (4) Health; and, (5) Gender. Black people and Mainland United States PR Hispanics most frequently identified Race/Ethnicity as a vulnerability trait (42.1 percent of Black people and 42.6 percent of Mainland United States. PR Hispanics versus 15.4 percent of White people and 16.7 percent of SJ R Hispanics) (P < 0.007), while White people and SJ PR Hispanics most frequently identified Age (48.3 percent and 29.2 percent) as a vulnerability trait. The response patterns on "who was vulnerable" were similar for the two minority groups (Black people and Mainland US PR Hispanics), and notably different from the response patterns of the two majority groups (White people and SJ PR Hispanics). Further, the vox populis definition of vulnerables differed from the current official definitions as used by the U.S. federal government.

Symptoms of anxiety on both sides of the US-Mexico border: the role of immigration.

PubMed

Borges, Guilherme; Zamora, Beatriz; García, José; Orozco, Ricardo; Cherpitel, Cheryl J; Zemore, Sarah E; Breslau, Joshua

2015-02-01

Home to about 15 million people, the US-Mexico border area has suffered stresses from increased border security efforts and a costly drug war in Mexico. Whether immigration patterns add to increasing levels of anxiety for the Mexican population and the Mexican-origin individuals living in the US-Mexico border and near the border is unknown. We used the US-Mexico Study on Alcohol and Related Conditions (UMSARC), a cross-sectional survey (2011-2013) of individuals living in border and non-border cities of the US (n = 2336) and Mexico (n = 2460). In Mexico respondents were asked if they ever migrated to the US or have a family member living in the US (328) or not (2124), while in the US respondents were asked if they were born in Mexico (697), born in the US with no US-born parents (second generation, 702) or born in the US with at least one US-born parent (third generation, 932). The prevalence and risk factors for symptoms of anxiety using the Beck Anxiety Inventory (>=10) were obtained. Mexicans with no migrant experience had a prevalence of anxiety and adjusted prevalence ratio (PR) within the last month of 6.7% (PR = reference), followed by Mexicans with migration experience of 13.1% (PR = 1.8), Mexican-born respondents living in the US of 17.3% (PR = 2.6), US born Mexican-Americans of 2nd generation of 18.6% (PR = 3.3) and finally US born 3rd + generation of 25.9% (PR = 3.8). Results help to identify regions and migration patterns at high risk for anxiety and may help to unravel causal mechanisms that underlie this risk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Pattern recognition and feature extraction with an optical Hough transform

NASA Astrophysics Data System (ADS)

Fernández, Ariel

2016-09-01

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

Reading recognition of pointer meter based on pattern recognition and dynamic three-points on a line

NASA Astrophysics Data System (ADS)

Zhang, Yongqiang; Ding, Mingli; Fu, Wuyifang; Li, Yongqiang

2017-03-01

Pointer meters are frequently applied to industrial production for they are directly readable. They should be calibrated regularly to ensure the precision of the readings. Currently the method of manual calibration is most frequently adopted to accomplish the verification of the pointer meter, and professional skills and subjective judgment may lead to big measurement errors and poor reliability and low efficiency, etc. In the past decades, with the development of computer technology, the skills of machine vision and digital image processing have been applied to recognize the reading of the dial instrument. In terms of the existing recognition methods, all the parameters of dial instruments are supposed to be the same, which is not the case in practice. In this work, recognition of pointer meter reading is regarded as an issue of pattern recognition. We obtain the features of a small area around the detected point, make those features as a pattern, divide those certified images based on Gradient Pyramid Algorithm, train a classifier with the support vector machine (SVM) and complete the pattern matching of the divided mages. Then we get the reading of the pointer meter precisely under the theory of dynamic three points make a line (DTPML), which eliminates the error caused by tiny differences of the panels. Eventually, the result of the experiment proves that the proposed method in this work is superior to state-of-the-art works.

Microwave nonlinearity and photoresponse of superconducting resonators with columnar defect micro-channels

NASA Astrophysics Data System (ADS)

Remillard, S. K.; Kirkendall, D.; Ghigo, G.; Gerbaldo, R.; Gozzelino, L.; Laviano, F.; Yang, Z.; Mendelsohn, N. A.; Ghamsari, B. G.; Friedman, B.; Jung, P.; Anlage, S. M.

2014-09-01

Micro-channels of nanosized columnar tracks were planted by heavy-ion irradiation into superconducting microwave microstrip resonators that were patterned from YBa2Cu3O7 - x thin films on LaAlO3 substrates. Three different ion fluences were used, producing different column densities, with each fluence having a successively greater impact on the microwave nonlinearity of the device, as compared to a control sample. Photoresponse (PR) images made with a 638 nm rastered laser beam revealed that the channel is a location of enhanced PR and a hot spot for the generation of intermodulation distortion. The microwave PR technique was also advanced in this work by investigating the role of coupling strength on the distribution of PR between inductive and resistive components.

Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases.

PubMed

Kostopoulos, Spiros A; Asvestas, Pantelis A; Kalatzis, Ioannis K; Sakellaropoulos, George C; Sakkis, Theofilos H; Cavouras, Dionisis A; Glotsos, Dimitris T

2017-09-01

The aim of this study was to propose features that evaluate pictorial differences between melanocytic nevus (mole) and melanoma lesions by computer-based analysis of plain photography images and to design a cross-platform, tunable, decision support system to discriminate with high accuracy moles from melanomas in different publicly available image databases. Digital plain photography images of verified mole and melanoma lesions were downloaded from (i) Edinburgh University Hospital, UK, (Dermofit, 330moles/70 melanomas, under signed agreement), from 5 different centers (Multicenter, 63moles/25 melanomas, publicly available), and from the Groningen University, Netherlands (Groningen, 100moles/70 melanomas, publicly available). Images were processed for outlining the lesion-border and isolating the lesion from the surrounding background. Fourteen features were generated from each lesion evaluating texture (4), structure (5), shape (4) and color (1). Features were subjected to statistical analysis for determining differences in pictorial properties between moles and melanomas. The Probabilistic Neural Network (PNN) classifier, the exhaustive search features selection, the leave-one-out (LOO), and the external cross-validation (ECV) methods were used to design the PR-system for discriminating between moles and melanomas. Statistical analysis revealed that melanomas as compared to moles were of lower intensity, of less homogenous surface, had more dark pixels with intensities spanning larger spectra of gray-values, contained more objects of different sizes and gray-levels, had more asymmetrical shapes and irregular outlines, had abrupt intensity transitions from lesion to background tissue, and had more distinct colors. The PR-system designed by the Dermofit images scored on the Dermofit images, using the ECV, 94.1%, 82.9%, 96.5% for overall accuracy, sensitivity, specificity, on the Multicenter Images 92.0%, 88%, 93.7% and on the Groningen Images 76.2%, 73.9%, 77.8% respectively. The PR-system as designed by the Dermofit image database could be fine-tuned to classify with good accuracy plain photography moles/melanomas images of other databases employing different image capturing equipment and protocols. Copyright © 2017 Elsevier B.V. All rights reserved.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, M.A.

1999-08-31

The CO-concentration in the H{sub 2} feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H{sub 2} fuel stream. 4 figs.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, Mark Alexander

1999-01-01

The CO-concentration in the H.sub.2 feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H.sub.2 fuel stream.

Symbol Recognition Using a Concept Lattice of Graphical Patterns

NASA Astrophysics Data System (ADS)

Rusiñol, Marçal; Bertet, Karell; Ogier, Jean-Marc; Lladós, Josep

In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

An RLP23-SOBIR1-BAK1 complex mediates NLP-triggered immunity.

PubMed

Albert, Isabell; Böhm, Hannah; Albert, Markus; Feiler, Christina E; Imkampe, Julia; Wallmeroth, Niklas; Brancato, Caterina; Raaymakers, Tom M; Oome, Stan; Zhang, Heqiao; Krol, Elzbieta; Grefen, Christopher; Gust, Andrea A; Chai, Jijie; Hedrich, Rainer; Van den Ackerveken, Guido; Nürnberger, Thorsten

2015-10-05

Plants and animals employ innate immune systems to cope with microbial infection. Pattern-triggered immunity relies on the recognition of microbe-derived patterns by pattern recognition receptors (PRRs). Necrosis and ethylene-inducing peptide 1-like proteins (NLPs) constitute plant immunogenic patterns that are unique, as these proteins are produced by multiple prokaryotic (bacterial) and eukaryotic (fungal, oomycete) species. Here we show that the leucine-rich repeat receptor protein (LRR-RP) RLP23 binds in vivo to a conserved 20-amino-acid fragment found in most NLPs (nlp20), thereby mediating immune activation in Arabidopsis thaliana. RLP23 forms a constitutive, ligand-independent complex with the LRR receptor kinase (LRR-RK) SOBIR1 (Suppressor of Brassinosteroid insensitive 1 (BRI1)-associated kinase (BAK1)-interacting receptor kinase 1), and recruits a second LRR-RK, BAK1, into a tripartite complex upon ligand binding. Stable, ectopic expression of RLP23 in potato (Solanum tuberosum) confers nlp20 pattern recognition and enhanced immunity to destructive oomycete and fungal plant pathogens, such as Phytophthora infestans and Sclerotinia sclerotiorum. PRRs that recognize widespread microbial patterns might be particularly suited for engineering immunity in crop plants.

Model driven mobile care for patients with type 1 diabetes.

PubMed

Skrøvseth, Stein Olav; Arsand, Eirik; Godtliebsen, Fred; Joakimsen, Ragnar M

2012-01-01

We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.

PubMed

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks.

Disease associated prion protein may deposit in the peripheral nervous system in human transmissible spongiform encephalopathies.

PubMed

Hainfellner, J A; Budka, H

1999-11-01

There is increasing evidence indicating involvement of the peripheral nervous system (PNS) in the pathogenesis of transmissible spongiform encephalopathies (TSEs). Immunocytochemically detectable deposits of TSE-specific abnormal prion protein (PrP(sc)) are considered as a surrogate marker for infectivity. We used anti-PrP immunocytochemistry to trace PrP(sc) deposition in spinal and enteric ganglia, and peripheral nerve in Creutzfeldt-Jakob disease (CJD), Gerstmann-Sträussler-Scheinker disease (GSS), and fatal familial insomnia. Discrete PrP(sc) deposits were detectable only in a few posterior root nerve fibers in an adaxonal location in one of nine CJD and the one GSS patients examined. Follicular dendritic cells of the gut and enteric nervous system were not labeled. Thus, PrP(sc) may spread to the PNS in different forms of human prion disease. In contrast to our observations in experimental scrapie (Groschup et al., Acta Neuropathol, this issue), the deposits were scant. Possible explanations for this discrepancy comprise strain difference, or centripetal (experimental scrapie) versus centrifugal (sporadic and genetic human prion diseases) spread of PrP(sc), resulting in different patterns and amounts of PrP(sc) accumulation in the PNS.

The effect of inversion on face recognition in adults with autism spectrum disorder.

PubMed

Hedley, Darren; Brewer, Neil; Young, Robyn

2015-05-01

Face identity recognition has widely been shown to be impaired in individuals with autism spectrum disorders (ASD). In this study we examined the influence of inversion on face recognition in 26 adults with ASD and 33 age and IQ matched controls. Participants completed a recognition test comprising upright and inverted faces. Participants with ASD performed worse than controls on the recognition task but did not show an advantage for inverted face recognition. Both groups directed more visual attention to the eye than the mouth region and gaze patterns were not found to be associated with recognition performance. These results provide evidence of a normal effect of inversion on face recognition in adults with ASD.

Physical activity patterns and metabolic syndrome in Costa Rica

PubMed Central

Hastert, Theresa A.; Gong, Jian; Campos, Hannia; Baylin, Ana

2015-01-01

Objective To examine whether total physical activity or activity patterns are associated with metabolic syndrome and its components. Methods Participants include 1,994 controls from a case-control study of non-fatal myocardial infarction in Costa Rica (1994–2004). Physical activity was assessed via self-administered questionnaire and patterns were identified using principal components analysis. Metabolic syndrome was assessed via blood samples and anthropometry measurements from in-home study visits. Prevalence ratios (PR) and 95% confidence intervals (CI) were calculated using log binomial regression. Adjusted least squares means of metabolic syndrome components were calculated by quintile of total activity and pattern scores. Results Four activity patterns were identified: rest/sleep, agricultural, light indoor activity, and manual labor. Total activity was not associated with metabolic syndrome. Metabolic syndrome prevalence was 20% lower in participants with the highest scores on the agricultural job pattern compared to those with the lowest (PR: 0.80, 95% CI: 0.68–0.94). Higher total activity was associated with lower triglycerides and lower HDL cholesterol. Higher scores on each pattern were inversely associated with metabolic syndrome components, particularly waist circumference and fasting blood glucose. Conclusions Patterns or types of physical activity may be more strongly associated with metabolic syndrome and its components than total activity levels. PMID:25445330

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

Determination of polychlorinated biphenyl levels in the serum of residents and in the homogenates of seafood from the New Bedford, Massachusetts Area: A comparison of exposure sources through pattern recognition techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burse, V.W.; Groce, D.F.; Caudill, S.P.

1994-01-01

Gas chromatographic patterns of polychlorinated biophenyls (PCBs) found in the serum of New Bedford, MA residents with high serum PCBs were compared to patterns found in lobsters and bluefish taken from local waters, and goats fed selected technical Aroclors (e.g., Aroclors 1016, 1242, 1254, or 1260) using Jaccard measures of similarity and Principal Component Analysis. Pattern in humans were silimar to patterns in lobsters and both were more similar to those in the goat fed Aroclor 1254 as demonstrated by both pattern recognition techniques. However, patterns observed in humans, lobsters and bluefish all exhibited some presence of PCBs more characteristicmore » of Aroclors 1016 and/or 1242 or 1260.« less

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sobral, G. A. Jr.; Vieira, V. M.; Lyra, M. L.

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonalmore » to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0.« less

Artificial Immune System for Recognizing Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Collocation and Pattern Recognition Effects on System Failure Remediation

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Press, Hayes N.

2007-01-01

Previous research found that operators prefer to have status, alerts, and controls located on the same screen. Unfortunately, that research was done with displays that were not designed specifically for collocation. In this experiment, twelve subjects evaluated two displays specifically designed for collocating system information against a baseline that consisted of dial status displays, a separate alert area, and a controls panel. These displays differed in the amount of collocation, pattern matching, and parameter movement compared to display size. During the data runs, subjects kept a randomly moving target centered on a display using a left-handed joystick and they scanned system displays to find a problem in order to correct it using the provided checklist. Results indicate that large parameter movement aided detection and then pattern recognition is needed for diagnosis but the collocated displays centralized all the information subjects needed, which reduced workload. Therefore, the collocated display with large parameter movement may be an acceptable display after familiarization because of the possible pattern recognition developed with training and its use.

Problems Associated with Statistical Pattern Recognition of Acoustic Emission Signals in a Compact Tension Fatigue Specimen

NASA Technical Reports Server (NTRS)

Hinton, Yolanda L.

1999-01-01

Acoustic emission (AE) data were acquired during fatigue testing of an aluminum 2024-T4 compact tension specimen using a commercially available AE system. AE signals from crack extension were identified and separated from noise spikes, signals that reflected from the specimen edges, and signals that saturated the instrumentation. A commercially available software package was used to train a statistical pattern recognition system to classify the signals. The software trained a network to recognize signals with a 91-percent accuracy when compared with the researcher's interpretation of the data. Reasons for the discrepancies are examined and it is postulated that additional preprocessing of the AE data to focus on the extensional wave mode and eliminate other effects before training the pattern recognition system will result in increased accuracy.

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

COPD: Health Care Utilisation Patterns with Different Disease Management Interventions.

PubMed

Luk, Edwin K; Hutchinson, Anastasia F; Tacey, Mark; Irving, Louis; Khan, Fary

2017-08-01

The management of COPD is a significant and costly issue worldwide, with acute healthcare utilisation consisting of admissions and outpatient attendances being a major contributor to the cost. Pulmonary rehabilitation (PR) and integrated disease management (IDM) are often offered. Whilst there is strong evidence of physical and quality of life outcomes following IDM and PR, few studies have looked into healthcare utilisation. The aims of this study were to confirm whether IDM and PR reduce acute healthcare utilisation and to identify factors which contribute to acute health care utilisation or increased mortality. This was a retrospective cohort study of patients with COPD who were referred to IDM over a 10-year period. Patients were also offered an 8-week PR program. Data collected were matched with the hospital dataset to obtain information on inpatient, ED and outpatient attendances. 517 patients were enrolled to IDM. 315 (61%) also commenced PR and 220 (43%) completed PR. Patients who were referred to PR were younger and had less comorbidities (p < 0.001). Both groups (IDM only and IDM + PR referred) had reductions in healthcare utilisation but the IDM-only group had greater reductions. A survival benefit (HR 0.68, 95% CI 0.50-0.92) was seen in those who were PR completers compared to patients who received IDM only. Patients with COPD who successfully complete PR in addition to participating in IDM have improved survival. IDM alone was effective in the reduction of healthcare utilisation; however, the addition of PR did not reduce healthcare usage further.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words.

PubMed

Gordon-Salant, Sandra; Yeni-Komshian, Grace H; Fitzgibbons, Peter J; Cohen, Julie I

2015-02-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words

PubMed Central

Gordon-Salant, Sandra; Yeni-Komshian, Grace H.; Fitzgibbons, Peter J.; Cohen, Julie I.

2015-01-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech. PMID:25698021

Ultrafast learning in a hard-limited neural network pattern recognizer

NASA Astrophysics Data System (ADS)

Hu, Chia-Lun J.

1996-03-01

As we published in the last five years, the supervised learning in a hard-limited perceptron system can be accomplished in a noniterative manner if the input-output mapping to be learned satisfies a certain positive-linear-independency (or PLI) condition. When this condition is satisfied (for most practical pattern recognition applications, this condition should be satisfied,) the connection matrix required to meet this mapping can be obtained noniteratively in one step. Generally, there exist infinitively many solutions for the connection matrix when the PLI condition is satisfied. We can then select an optimum solution such that the recognition of any untrained patterns will become optimally robust in the recognition mode. The learning speed is very fast and close to real-time because the learning process is noniterative and one-step. This paper reports the theoretical analysis and the design of a practical charter recognition system for recognizing hand-written alphabets. The experimental result is recorded in real-time on an unedited video tape for demonstration purposes. It is seen from this real-time movie that the recognition of the untrained hand-written alphabets is invariant to size, location, orientation, and writing sequence, even the training is done with standard size, standard orientation, central location and standard writing sequence.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Image processing and recognition for biological images

PubMed Central

Uchida, Seiichi

2013-01-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Consonant-recognition patterns and self-assessment of hearing handicap.

PubMed

Hustedde, C G; Wiley, T L

1991-12-01

Two companion experiments were conducted with normal-hearing subjects and subjects with high-frequency, sensorineural hearing loss. In Experiment 1, the validity of a self-assessment device of hearing handicap was evaluated in two groups of hearing-impaired listeners with significantly different consonant-recognition ability. Data for the Hearing Performance Inventory--Revised (Lamb, Owens, & Schubert, 1983) did not reveal differences in self-perceived handicap for the two groups of hearing-impaired listeners; it was sensitive to perceived differences in hearing abilities for listeners who did and did not have a hearing loss. Experiment 2 was aimed at evaluation of consonant error patterns that accounted for observed group differences in consonant-recognition ability. Error patterns on the Nonsense-Syllable Test (NST) across the two subject groups differed in both degree and type of error. Listeners in the group with poorer NST performance always demonstrated greater difficulty with selected low-frequency and high-frequency syllables than did listeners in the group with better NST performance. Overall, the NST was sensitive to differences in consonant-recognition ability for normal-hearing and hearing-impaired listeners.

Syntactic/semantic techniques for feature description and character recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, R.C.

1983-01-01

The Pattern Analysis Branch, Mapping, Charting and Geodesy (MC/G) Division, of the Naval Ocean Research and Development Activity (NORDA) has been involved over the past several years in the development of algorithms and techniques for computer recognition of free-form handprinted symbols as they appear on the Defense Mapping Agency (DMA) maps and charts. NORDA has made significant contributions to the automation of MC/G through advancing the state of the art in such information extraction techniques. In particular, new concepts in character (symbol) skeletonization, rugged feature measurements, and expert system-oriented decision logic have allowed the development of a very high performancemore » Handprinted Symbol Recognition (HSR) system for identifying depth soundings from naval smooth sheets (accuracies greater than 99.5%). The study reported in this technical note is part of NORDA's continuing research and development in pattern and shape analysis as it applies to Navy and DMA ocean/environment problems. The issue addressed in this technical note deals with emerging areas of syntactic and semantic techniques in pattern recognition as they might apply to the free-form symbol problem.« less

Higher-order neural network software for distortion invariant object recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Star Pattern Recognition and Spacecraft Attitude Determination.

DTIC Science & Technology

1978-10-01

Mr. Lawrence D. Ziems, Computer Programuer Prepared For: ,ti U.S. Army Engineer Topographic Laboratories Fort Belvoir, Virginia 22060 Contract No...CONTENTS PORIVAD i SIMARY iii 1.0 Introduction and System Overviev 1 2.0 Reference Frames Geometry and Kinematics 9 3.0 Star Pattern Recognition/Attitude...Laboratories (USAETL). The authors appreciate the capable guidance of Mr. L. A. Gambino, Director of the Computer Science Laboratory (USAETL), who served as

Linear Programming and Its Application to Pattern Recognition Problems

NASA Technical Reports Server (NTRS)

Omalley, M. J.

1973-01-01

Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.

Learning and Inductive Inference

DTIC Science & Technology

1982-07-01

a set of graph grammars to describe visual scenes . Other researchers have applied graph grammars to the pattern recognition of handwritten characters...345 1. Issues / 345 2. Mostows’ operationalizer / 350 0. Learning from ezamples / 360 1. Issues / 3t60 2. Learning in control and pattern recognition ...art.icleis on rote learntinig and ailvice- tAik g. K(ennieth Clarkson contributed Ltte article on grmvit atical inference, anid Geoff’ lroiney wrote

DYNAMIC PATTERN RECOGNITION BY MEANS OF THRESHOLD NETS,

DTIC Science & Technology

A method is expounded for the recognition of visual patterns. A circuit diagram of a device is described which is based on a multilayer threshold ...structure synthesized in accordance with the proposed method. Coded signals received each time an image is displayed are transmitted to the threshold ...circuit which distinguishes the signs, and from there to the layers of threshold resolving elements. The image at each layer is made to correspond

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures in the Human Eye

PubMed Central

Yoshioka, Nayuta; Zangerl, Barbara; Nivison-Smith, Lisa; Khuu, Sieu K.; Jones, Bryan W.; Pfeiffer, Rebecca L.; Marc, Robert E.; Kalloniatis, Michael

2017-01-01

Purpose To characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease. Methods Single eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort. Results Pattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm). Conclusions Pattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease. PMID:28632847

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection

PubMed Central

Katagiri, Fumiaki; Glazebrook, Jane

2003-01-01

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data. PMID:12960373

VIPRAM_L1CMS: a 2-Tier 3D Architecture for Pattern Recognition for Track Finding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoff, J. R.; Joshi, Joshi,S.; Liu, Liu,

In HEP tracking trigger applications, flagging an individual detector hit is not important. Rather, the path of a charged particle through many detector layers is what must be found. Moreover, given the increased luminosity projected for future LHC experiments, this type of track finding will be required within the Level 1 Trigger system. This means that future LHC experiments require not just a chip capable of high-speed track finding but also one with a high-speed readout architecture. VIPRAM_L1CMS is 2-Tier Vertically Integrated chip designed to fulfill these requirements. It is a complete pipelined Pattern Recognition Associative Memory (PRAM) architecture includingmore » pattern recognition, result sparsification, and readout for Level 1 trigger applications in CMS with 15-bit wide detector addresses and eight detector layers included in the track finding. Pattern recognition is based on classic Content Addressable Memories with a Current Race Scheme to reduce timing complexity and a 4-bit Selective Precharge to minimize power consumption. VIPRAM_L1CMS uses a pipelined set of priority-encoded binary readout structures to sparsify and readout active road flags at frequencies of at least 100MHz. VIPRAM_L1CMS is designed to work directly with the Pulsar2b Architecture.« less

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

PubMed

Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

2016-04-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control

PubMed Central

Adewuyi, Adenike A.; Hargrove, Levi J.; Kuiken, Todd A.

2015-01-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications. PMID:25955989

Pattern Recognition Control Design

NASA Technical Reports Server (NTRS)

Gambone, Elisabeth

2016-01-01

Spacecraft control algorithms must know the expected spacecraft response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach can be used to investigate the relationship between the control effector commands and the spacecraft responses. Instead of supplying the approximated vehicle properties and the effector performance characteristics, a database of information relating the effector commands and the desired vehicle response can be used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands can be analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center (Ref. 1) to analyze flight dynamics Monte Carlo data sets through pattern recognition methods can be used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands is established, it can be used in place of traditional control laws and gains set. This pattern recognition approach can be compared with traditional control algorithms to determine the potential benefits and uses.

Within-individual variation in bullfrog vocalizations: implications for a vocally mediated social recognition system.

PubMed

Bee, Mark A

2004-12-01

Acoustic signals provide a basis for social recognition in a wide range of animals. Few studies, however, have attempted to relate the patterns of individual variation in signals to behavioral discrimination thresholds used by receivers to discriminate among individuals. North American bullfrogs (Rana catesbeiana) discriminate among familiar and unfamiliar individuals based on individual variation in advertisement calls. The sources, patterns, and magnitudes of variation in eight acoustic properties of multiple-note advertisement calls were examined to understand how patterns of within-individual variation might either constrain, or provide additional cues for, vocal recognition. Six of eight acoustic properties exhibited significant note-to-note variation within multiple-note calls. Despite this source of within-individual variation, all call properties varied significantly among individuals, and multivariate analyses indicated that call notes were individually distinct. Fine-temporal and spectral call properties exhibited less within-individual variation compared to gross-temporal properties and contributed most toward statistically distinguishing among individuals. Among-individual differences in the patterns of within-individual variation in some properties suggest that within-individual variation could also function as a recognition cue. The distributions of among-individual and within-individual differences were used to generate hypotheses about the expected behavioral discrimination thresholds of receivers.

A Fuzzy Logic Prompting Mechanism Based on Pattern Recognition and Accumulated Activity Effective Index Using a Smartphone Embedded Sensor.

PubMed

Liu, Chung-Tse; Chan, Chia-Tai

2016-08-19

Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health. Reminders that help people change their health behaviors are widely applied in health care services. However, timed-based reminders deliver periodic prompts suffer from flexibility and dependency issues which may decrease prompt effectiveness. We propose a fuzzy logic prompting mechanism, Accumulated Activity Effective Index Reminder (AAEIReminder), based on pattern recognition and activity effective analysis to manage physical activity. AAEIReminder recognizes activity levels using a smartphone-embedded sensor for pattern recognition and analyzing the amount of physical activity in activity effective analysis. AAEIReminder can infer activity situations such as the amount of physical activity and days spent exercising through fuzzy logic, and decides whether a prompt should be delivered to a user. This prompting system was implemented in smartphones and was used in a short-term real-world trial by seventeenth participants for validation. The results demonstrated that the AAEIReminder is feasible. The fuzzy logic prompting mechanism can deliver prompts automatically based on pattern recognition and activity effective analysis. AAEIReminder provides flexibility which may increase the prompts' efficiency.

Benefits of using culturally unfamiliar stimuli in ambiguous emotion identification: A cross-cultural study.

PubMed

Koelkebeck, Katja; Kohl, Waldemar; Luettgenau, Julia; Triantafillou, Susanna; Ohrmann, Patricia; Satoh, Shinji; Minoshita, Seiko

2015-07-30

A novel emotion recognition task that employs photos of a Japanese mask representing a highly ambiguous stimulus was evaluated. As non-Asians perceive and/or label emotions differently from Asians, we aimed to identify patterns of task-performance in non-Asian healthy volunteers with a view to future patient studies. The Noh mask test was presented to 42 adult German participants. Reaction times and emotion attribution patterns were recorded. To control for emotion identification abilities, a standard emotion recognition task was used among others. Questionnaires assessed personality traits. Finally, results were compared to age- and gender-matched Japanese volunteers. Compared to other tasks, German participants displayed slowest reaction times on the Noh mask test, indicating higher demands of ambiguous emotion recognition. They assigned more positive emotions to the mask than Japanese volunteers, demonstrating culture-dependent emotion identification patterns. As alexithymic and anxious traits were associated with slower reaction times, personality dimensions impacted on performance, as well. We showed an advantage of ambiguous over conventional emotion recognition tasks. Moreover, we determined emotion identification patterns in Western individuals impacted by personality dimensions, suggesting performance differences in clinical samples. Due to its properties, the Noh mask test represents a promising tool in the differential diagnosis of psychiatric disorders, e.g. schizophrenia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

33 CFR 105.215 - Security training for all other facility personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... apply to them, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

33 CFR 105.215 - Security training for all other facility personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... apply to them, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

The software peculiarities of pattern recognition in track detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Starkov, N.

The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.

A multimodal approach to emotion recognition ability in autism spectrum disorders.

PubMed

Jones, Catherine R G; Pickles, Andrew; Falcaro, Milena; Marsden, Anita J S; Happé, Francesca; Scott, Sophie K; Sauter, Disa; Tregay, Jenifer; Phillips, Rebecca J; Baird, Gillian; Simonoff, Emily; Charman, Tony

2011-03-01

Autism spectrum disorders (ASD) are characterised by social and communication difficulties in day-to-day life, including problems in recognising emotions. However, experimental investigations of emotion recognition ability in ASD have been equivocal, hampered by small sample sizes, narrow IQ range and over-focus on the visual modality. We tested 99 adolescents (mean age 15;6 years, mean IQ 85) with an ASD and 57 adolescents without an ASD (mean age 15;6 years, mean IQ 88) on a facial emotion recognition task and two vocal emotion recognition tasks (one verbal; one non-verbal). Recognition of happiness, sadness, fear, anger, surprise and disgust were tested. Using structural equation modelling, we conceptualised emotion recognition ability as a multimodal construct, measured by the three tasks. We examined how the mean levels of recognition of the six emotions differed by group (ASD vs. non-ASD) and IQ (≥ 80 vs. < 80). We found no evidence of a fundamental emotion recognition deficit in the ASD group and analysis of error patterns suggested that the ASD group were vulnerable to the same pattern of confusions between emotions as the non-ASD group. However, recognition ability was significantly impaired in the ASD group for surprise. IQ had a strong and significant effect on performance for the recognition of all six emotions, with higher IQ adolescents outperforming lower IQ adolescents. The findings do not suggest a fundamental difficulty with the recognition of basic emotions in adolescents with ASD. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

The effect of oral preexposure prophylaxis on the progression of HIV-1 seroconversion

PubMed Central

Donnell, Deborah; Ramos, Eric; Celum, Connie; Baeten, Jared; Dragavon, Joan; Tappero, Jordan; Lingappa, Jairam R.; Ronald, Allan; Fife, Kenneth; Coombs, Robert W.

2017-01-01

Objective: To investigate whether oral preexposure prophylaxis (PrEP) alters timing and patterns of seroconversion when PrEP use continues after HIV-1 infection. Design: Retrospective testing of the timing of Fiebig stage HIV-1 seroconversion in the Partners PrEP Study, a randomized placebo-controlled clinical trial of PrEP conducted in Kenya and Uganda. Methods: Specimens from 138 seroconverters were collected every 3 months and when HIV-1 infection was suspected based on monthly rapid HIV-1 tests. Progression of seroconversion was compared between randomized groups (PrEP versus placebo) and per-protocol groups (placebo versus PrEP participants with detectable tenofovir during the seroconversion period) using laboratory assessment of Fiebig stage. Delay in site-detection of seroconversion and association with PrEP drug-regimen resistant virus were assessed using logistic regression. Analysis of time to each Fiebig stage used maximum likelihood estimation with a parametric model to accommodate the varying lengths of HIV-infection intervals. Results: There was a significant increase in delayed site detection of infection associated with PrEP (odds ratio = 3.49, P = 0.044). Delay in detection was not associated with increased risk of resistance in the PrEP arm (odds ratio = 0.93, P = 0.95). Estimated time to each Fiebig stage was elongated in seroconverters with evidence of ongoing PrEP use, significantly for only Stage 5 (28 versus 17 days, P = 0.05). Adjusted for Fiebig stage, viral RNA was ∼2/3 log lower in those assigned to PrEP compared with placebo; no differences were found in Architect signal to cut-off at any stage. Conclusion: Ongoing PrEP use in seroconverters may delay detection of infection and elongate seroconversion, although the delay does not increase risk of resistance. PMID:28692542

Adherence to Preexposure Prophylaxis: Current, Emerging, and Anticipated Bases of Evidence

PubMed Central

Amico, K. Rivet; Stirratt, Michael J.

2014-01-01

Despite considerable discussion and debate about adherence to preexposure prophylaxis (PrEP) for human immunodeficiency virus (HIV), scant data are available that characterize patterns of adherence to open-label PrEP. The current evidence base is instead dominated by research on adherence to placebo-controlled investigational drug by way of drug detection in active-arm participants of large randomized controlled trials (RCTs). Important differences between the context of blinded RCTs and open-label use suggest caution when generalizing from study product adherence to real-world PrEP use. Evidence specific to open-label PrEP adherence is presently sparse but will expand rapidly over the next few years as roll-out, demonstration projects, and more rigorous research collect and present findings. The current evidence bases established cannot yet predict uptake, adherence, or persistence with open-label effective PrEP. Emerging evidence suggests that some cohorts could execute better adherence in open-label use vs placebo-controlled research. Uptake of PrEP is presently slow in the United States; whether this changes as grassroots and community efforts increase awareness of PrEP as an effective HIV prevention option remains to be determined. As recommended by multiple guidelines for PrEP use, all current demonstration projects offer PrEP education and/or counseling. PrEP support approaches generally fall into community-based, technology, monitoring, and integrated sexual health promotion approaches. Developing and implementing research that moves beyond simple correlates of either study product use or open-label PrEP adherence toward more comprehensive models of sociobehavioral and socioecological adherence determinants would greatly accelerate progress. Intervention research is needed to identify effective models of support for open-label PrEP adherence. PMID:24926036

The Boundaries of Hemispheric Processing in Visual Pattern Recognition

DTIC Science & Technology

1989-11-01

Allen, M. W. (1968). Impairment in facial recognition in patients cerebral disease. Cortex, 4, 344-358. Bogen, J. E. (1969). The other side of the brain...effects on a facial recognition task in normal subjects. Cortex, 9, 246-258. tliscock, M. (1988). Behavioral asymmetries in normal children. In D. L... facial recognition . Neuropsychologia, 22, 471-477. Ross-Kossak, P., & Turkewitz, G. (1986). A micro and macro developmental view of the nature of changes

Control of antiviral immunity by pattern recognition and the microbiome

PubMed Central

Pang, Iris K.; Iwasaki, Akiko

2013-01-01

Summary Human skin and mucosal surfaces are in constant contact with resident and invasive microbes. Recognition of microbial products by receptors of the innate immune system triggers rapid innate defense and transduces signals necessary for initiating and maintaining the adaptive immune responses. Microbial sensing by innate pattern recognition receptors is not restricted to pathogens. Rather, proper development, function, and maintenance of innate and adaptive immunity rely on continuous recognition of products derived from the microorganisms indigenous to the internal and external surfaces of mammalian host. Tonic immune activation by the resident microbiota governs host susceptibility to intestinal and extra-intestinal infections including those caused by viruses. This review highlights recent developments in innate viral recognition leading to adaptive immunity, and discusses potential link between viruses, microbiota and the host immune system. Further, we discuss the possible roles of microbiome in chronic viral infection and pathogenesis of autoimmune disease, and speculate on the benefit for probiotic therapies against such diseases. PMID:22168422

Human activities recognition by head movement using partial recurrent neural network

NASA Astrophysics Data System (ADS)

Tan, Henry C. C.; Jia, Kui; De Silva, Liyanage C.

2003-06-01

Traditionally, human activities recognition has been achieved mainly by the statistical pattern recognition methods or the Hidden Markov Model (HMM). In this paper, we propose a novel use of the connectionist approach for the recognition of ten simple human activities: walking, sitting down, getting up, squatting down and standing up, in both lateral and frontal views, in an office environment. By means of tracking the head movement of the subjects over consecutive frames from a database of different color image sequences, and incorporating the Elman model of the partial recurrent neural network (RNN) that learns the sequential patterns of relative change of the head location in the images, the proposed system is able to robustly classify all the ten activities performed by unseen subjects from both sexes, of different race and physique, with a recognition rate as high as 92.5%. This demonstrates the potential of employing partial RNN to recognize complex activities in the increasingly popular human-activities-based applications.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

Accurate, fast, and secure biometric fingerprint recognition system utilizing sensor fusion of fingerprint patterns

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Alsharif, Salim; Jagapathi, Rajendarreddy

2011-04-01

Fingerprint recognition is one of the first techniques used for automatically identifying people and today it is still one of the most popular and effective biometric techniques. With this increase in fingerprint biometric uses, issues related to accuracy, security and processing time are major challenges facing the fingerprint recognition systems. Previous work has shown that polarization enhancementencoding of fingerprint patterns increase the accuracy and security of fingerprint systems without burdening the processing time. This is mainly due to the fact that polarization enhancementencoding is inherently a hardware process and does not have detrimental time delay effect on the overall process. Unpolarized images, however, posses a high visual contrast and when fused (without digital enhancement) properly with polarized ones, is shown to increase the recognition accuracy and security of the biometric system without any significant processing time delay.

Design Fragments

DTIC Science & Technology

2007-04-19

define the patterns and are better at analyzing behavior. SPQR (System for Pattern Query and Recognition) [18, 58] can recognize pattern vari- ants...Stotts. SPQR : Flexible automated design pattern extraction from source code. ase, 00:215, 2003. ISSN 1527-1366. doi: http://doi.ieeecomputersociety. org

Infrared sensing of non-observable human biometrics

NASA Astrophysics Data System (ADS)

Willmore, Michael R.

2005-05-01

Interest and growth of biometric recognition technologies surged after 9/11. Once a technology mainly used for identity verification in law enforcement, biometrics are now being considered as a secure means of providing identity assurance in security related applications. Biometric recognition in law enforcement must, by necessity, use attributes of human uniqueness that are both observable and vulnerable to compromise. Privacy and protection of an individual's identity is not assured during criminal activity. However, a security system must rely on identity assurance for access control to physical or logical spaces while not being vulnerable to compromise and protecting the privacy of an individual. The solution resides in the use of non-observable attributes of human uniqueness to perform the biometric recognition process. This discussion will begin by presenting some key perspectives about biometric recognition and the characteristic differences between observable and non-observable biometric attributes. An introduction to the design, development, and testing of the Thermo-ID system will follow. The Thermo-ID system is an emerging biometric recognition technology that uses non-observable patterns of infrared energy naturally emanating from within the human body. As with all biometric systems, the infrared patterns recorded and compared within the Thermo-ID system are unique and individually distinguishable permitting a link to be confirmed between an individual and a claimed or previously established identity. The non-observable characteristics of infrared patterns of human uniqueness insure both the privacy and protection of an individual using this type of biometric recognition system.

Facial expression recognition based on improved deep belief networks

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

Terrain type recognition using ERTS-1 MSS images

NASA Technical Reports Server (NTRS)

Gramenopoulos, N.

1973-01-01

For the automatic recognition of earth resources from ERTS-1 digital tapes, both multispectral and spatial pattern recognition techniques are important. Recognition of terrain types is based on spatial signatures that become evident by processing small portions of an image through selected algorithms. An investigation of spatial signatures that are applicable to ERTS-1 MSS images is described. Artifacts in the spatial signatures seem to be related to the multispectral scanner. A method for suppressing such artifacts is presented. Finally, results of terrain type recognition for one ERTS-1 image are presented.

Exploring Patterns of Awareness and Use of HIV Pre-Exposure Prophylaxis among Young Men Who Have Sex with Men

PubMed Central

Strauss, Benjamin B.; Greene, George J.; Phillips, Gregory; Bhatia, Ramona; Madkins, Krystal; Parsons, Jeffrey T.; Mustanski, Brian

2016-01-01

Pre-exposure prophylaxis (PrEP) has shown promise as a safe and effective HIV prevention strategy, but there is limited research on awareness and use among young men who have sex with men (YMSM). Using baseline data from the “Keep It Up! 2.0” randomized control trial, we examined differences in PrEP awareness and use among racially diverse YMSM (N = 759; mean age = 24.2 years). Participants were recruited from study sites in Atlanta, Chicago, and New York City, as well as through national advertising on social media applications. While 67.5% of participants reported awareness of PrEP, 8.7% indicated using the medication. Awareness, but not use, varied by demographic variables. PrEP-users had twice as many condomless anal sex partners (ERR = 2.05) and more condomless anal sex acts (ERR = 1.60) than non-users. Future research should aim to improve PrEP awareness and uptake among YMSM and address condom use. PMID:27401537

Italians Use Abstract Knowledge about Lexical Stress during Spoken-Word Recognition

ERIC Educational Resources Information Center

Sulpizio, Simone; McQueen, James M.

2012-01-01

In two eye-tracking experiments in Italian, we investigated how acoustic information and stored knowledge about lexical stress are used during the recognition of tri-syllabic spoken words. Experiment 1 showed that Italians use acoustic cues to a word's stress pattern rapidly in word recognition, but only for words with antepenultimate stress.…

Specific Patterns of Emotion Recognition from Faces in Children with ASD: Results of a Cross-Modal Matching Paradigm

ERIC Educational Resources Information Center

Golan, Ofer; Gordon, Ilanit; Fichman, Keren; Keinan, Giora

2018-01-01

Children with ASD show emotion recognition difficulties, as part of their social communication deficits. We examined facial emotion recognition (FER) in intellectually disabled children with ASD and in younger typically developing (TD) controls, matched on mental age. Our emotion-matching paradigm employed three different modalities: facial, vocal…

Major Dietary Patterns in Relation to General and Central Obesity among Chinese Adults

PubMed Central

Yu, Canqing; Shi, Zumin; Lv, Jun; Du, Huaidong; Qi, Lu; Guo, Yu; Bian, Zheng; Chang, Liang; Tang, Xuefeng; Jiang, Qilian; Mu, Huaiyi; Pan, Dongxia; Chen, Junshi; Chen, Zhengming; Li, Liming

2015-01-01

Limited evidence exists for the association between diet pattern and obesity phenotypes among Chinese adults. In the present study, we analyzed the cross-sectional data from 474,192 adults aged 30–79 years from the China Kadoorie Biobank baseline survey. Food consumption was collected by an interviewer-administered questionnaire. Three dietary patterns were extracted by factor analysis combined with cluster analysis. After being adjusted for potential confounders, individuals following a traditional southern dietary pattern had the lowest body mass index (BMI) and waist circumference (WC); the Western/new affluence dietary pattern had the highest BMI; and the traditional northern dietary pattern had the highest WC. Compared to the traditional southern dietary pattern in multivariable adjusted logistic models, individuals following a Western/new affluence dietary pattern had a significantly increased risk of general obesity (prevalence ratio (PR): 1.06, 95% confidence interval (CI): 1.03–1.08) and central obesity (PR: 1.07, 95% CI: 1.06–1.08). The corresponding risks for the traditional northern dietary pattern were 1.05 (1.02–1.09) and 1.17 (1.25–1.18), respectively. In addition, the associations were modified by lifestyle behaviors, and the combined effects with alcohol drinking, tobacco smoking, and physical activity were analyzed. Further prospective studies are needed to elucidate the diet-obesity relationships. PMID:26184308

Impacts of deficit irrigation and altered rooting patterns on soil structure and associated soil properties

USDA-ARS?s Scientific Manuscript database

A better understanding of belowground systems and overall management impacts on soil health is needed to improve crop production and long-term sustainability under deficit irrigation. This study investigates effects of deficit irrigation on rooting patterns in maize and subsequent impacts on soil pr...

Recovery patterns, histological observations and genetic integrity in Malus shoot tips cryopreserved using droplet vitrification and encapsulation-dehydration procedures

USDA-ARS?s Scientific Manuscript database

A droplet-vitrification procedure is described for cryopreservation of Malus shoot tips. Survival patterns, recovery types, histological observations, and genetic integrity were compared for Malus shoot tips cryopreserved using this droplet-vitrification procedure and an encapsulation-dehydration pr...

Quantum Model of Emerging Grammars

NASA Technical Reports Server (NTRS)

Zak, M.

1999-01-01

A special class of quantum recurrent nets simulating Markov chains with absorbing states is introduced. The absorbing states are exploited for pattern recognition: each class of patterns, each combination of patterns acquires its own meaning.

Using Pattern Recognition and Discriminance Analysis to Predict Critical Events in Large Signal Databases

NASA Astrophysics Data System (ADS)

Feller, Jens; Feller, Sebastian; Mauersberg, Bernhard; Mergenthaler, Wolfgang

2009-09-01

Many applications in plant management require close monitoring of equipment performance, in particular with the objective to prevent certain critical events. At each point in time, the information available to classify the criticality of the process, is represented through the historic signal database as well as the actual measurement. This paper presents an approach to detect and predict critical events, based on pattern recognition and discriminance analysis.

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. D.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth.

CNN: a speaker recognition system using a cascaded neural network.

PubMed

Zaki, M; Ghalwash, A; Elkouny, A A

1996-05-01

The main emphasis of this paper is to present an approach for combining supervised and unsupervised neural network models to the issue of speaker recognition. To enhance the overall operation and performance of recognition, the proposed strategy integrates the two techniques, forming one global model called the cascaded model. We first present a simple conventional technique based on the distance measured between a test vector and a reference vector for different speakers in the population. This particular distance metric has the property of weighting down the components in those directions along which the intraspeaker variance is large. The reason for presenting this method is to clarify the discrepancy in performance between the conventional and neural network approach. We then introduce the idea of using unsupervised learning technique, presented by the winner-take-all model, as a means of recognition. Due to several tests that have been conducted and in order to enhance the performance of this model, dealing with noisy patterns, we have preceded it with a supervised learning model--the pattern association model--which acts as a filtration stage. This work includes both the design and implementation of both conventional and neural network approaches to recognize the speakers templates--which are introduced to the system via a voice master card and preprocessed before extracting the features used in the recognition. The conclusion indicates that the system performance in case of neural network is better than that of the conventional one, achieving a smooth degradation in respect of noisy patterns, and higher performance in respect of noise-free patterns.

Extracting semantics from audio-visual content: the final frontier in multimedia retrieval.

PubMed

Naphade, M R; Huang, T S

2002-01-01

Multimedia understanding is a fast emerging interdisciplinary research area. There is tremendous potential for effective use of multimedia content through intelligent analysis. Diverse application areas are increasingly relying on multimedia understanding systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, pattern recognition, multimedia databases, and smart sensors. We review the state-of-the-art techniques in multimedia retrieval. In particular, we discuss how multimedia retrieval can be viewed as a pattern recognition problem. We discuss how reliance on powerful pattern recognition and machine learning techniques is increasing in the field of multimedia retrieval. We review the state-of-the-art multimedia understanding systems with particular emphasis on a system for semantic video indexing centered around multijects and multinets. We discuss how semantic retrieval is centered around concepts and context and the various mechanisms for modeling concepts and context.

Learning pattern recognition and decision making in the insect brain

NASA Astrophysics Data System (ADS)

Huerta, R.

2013-01-01

We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

Pattern recognition of visible and near-infrared spectroscopy from bayberry juice by use of partial least squares and a backpropagation neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cen Haiyan; Bao Yidan; He Yong

2006-10-10

Visible and near-infrared reflectance (visible-NIR) spectroscopy is applied to discriminate different varieties of bayberry juices. The discrimination of visible-NIR spectra from samples is a matter of pattern recognition. By partial least squares (PLS), the spectrum is reduced to certain factors, which are then taken as the input of the backpropagation neural network (BPNN). Through training and prediction, three different varieties of bayberry juice are classified based on the output of the BPNN. In addition, a mathematical model is built and the algorithm is optimized. With proper parameters in the training set,100% accuracy is obtained by the BPNN. Thus it ismore » concluded that the PLS analysis combined with the BPNN is an alternative for pattern recognition based on visible and NIR spectroscopy.« less

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Speech therapy and voice recognition instrument

NASA Technical Reports Server (NTRS)

Cohen, J.; Babcock, M. L.

1972-01-01

Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

Protein classification using sequential pattern mining.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2006-01-01

Protein classification in terms of fold recognition can be employed to determine the structural and functional properties of a newly discovered protein. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. One of the most efficient SPM algorithms, cSPADE, is employed for protein primary structure analysis. Then a classifier uses the extracted sequential patterns for classifying proteins of unknown structure in the appropriate fold category. The proposed methodology exhibited an overall accuracy of 36% in a multi-class problem of 17 candidate categories. The classification performance reaches up to 65% when the three most probable protein folds are considered.

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Impaired Word and Face Recognition in Older Adults with Type 2 Diabetes.

PubMed

Jones, Nicola; Riby, Leigh M; Smith, Michael A

2016-07-01

Older adults with type 2 diabetes mellitus (DM2) exhibit accelerated decline in some domains of cognition including verbal episodic memory. Few studies have investigated the influence of DM2 status in older adults on recognition memory for more complex stimuli such as faces. In the present study we sought to compare recognition memory performance for words, objects and faces under conditions of relatively low and high cognitive load. Healthy older adults with good glucoregulatory control (n = 13) and older adults with DM2 (n = 24) were administered recognition memory tasks in which stimuli (faces, objects and words) were presented under conditions of either i) low (stimulus presented without a background pattern) or ii) high (stimulus presented against a background pattern) cognitive load. In a subsequent recognition phase, the DM2 group recognized fewer faces than healthy controls. Further, the DM2 group exhibited word recognition deficits in the low cognitive load condition. The recognition memory impairment observed in patients with DM2 has clear implications for day-to-day functioning. Although these deficits were not amplified under conditions of increased cognitive load, the present study emphasizes that recognition memory impairment for both words and more complex stimuli such as face are a feature of DM2 in older adults. Copyright © 2016 IMSS. Published by Elsevier Inc. All rights reserved.

How can multi criteria decision analysis support value assessment of pharmaceuticals? - Findings from a systematic literature review.

PubMed

Kolasa, Katarzyna; Zah, Vladimir; Kowalczyk, Marta

2018-04-29

As budget constraints become more and more visible, there is growing recognition for greater transparency and greater stakeholders' engagement in the pharmaceuticals' pric-ing&reimbursement (P&R) decision making. New frameworks of drugs' value assessments are searched for. Among them, the multi-criteria decision analysis (MCDA) receives more and more attention. In 2014, ISPOR established Task Force to provide methodological recommendations for MCDA utilization in the health care decision making. Still, there is not so much knowledge about the real life experience with MCDA's adaptation to the P&R processes. Areas covered: A systematic literature review was performed to understand the rationale for MCDA adaptation, methodology used as well as its impact on P&R outcomes. Expert commentary: In total 102 hits were found through the search of databases, out of which 18 publications were selected. Although limited in scope, the review highlighted how MCDA can im-prove the decision making processes not only regarding pricing & reimbursement but also contribute to the the risk benefit assessment as well as optimization of treatment outcomes. Still none of re-viewed studies did report how MCDA results actually impacted the real life settings.

APMP comparison on luminous flux units (APMP.PR-K4)

NASA Astrophysics Data System (ADS)

Liu, H.; Lin, Y. D.; Yang, C. Z.; Yu, J.

2018-01-01

During the 18th APMP meeting in 2004, TCPR agreed that the luminous flux should be one of the several regional comparisons to be conducted in the field of photometry and radiometry, and the project was named as APMP.PR-K4. Nine laboratories took part in this comparison. A group of LF 200W lamps (no less than three) was used as transfer artifacts by each participant. The National Institute of Metrology (NIM, China) acted as the pilot laboratory. Presented in this report are the detailed procedures and results of the work. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCPR, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Photoluminescence Properties of Ca3Si2O7: Pr3+ Orange-Red Phosphors Prepared by High-Temperature Solid-State Method

NASA Astrophysics Data System (ADS)

Peng, Zhi-Qing; Chen, Rong; Feng, Wen-Lin

2018-06-01

Novel luminescent materials Ca3-xSi2O7: xPr3+ were successfully prepared by the high-temperature solid-state method. The crystal structure, morphology, and optical spectrum were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), and spectroscopy, respectively. The XRD patterns of the samples indicate that the crystal structure is monoclinic symmetry. The SEM shows that the selected sample has good crystallinity although its appearance is irregular and scalelike. The peak of the excitation spectrum of the sample is located at around 449 nm, corresponding to 3H4→3P2 transition of Pr3+. The peak of the emission spectrum of the sample is situated at around 612 nm which is attributed to 3P0→3H6 transition of Pr3+, and the colour is orange-red. The optimum concentration for Pr3+ replaced Ca2+ sites in Ca3Si2O7: Pr3+ is 0.75 mol%. The lifetime (8.48 μs) of a typical sample (Ca2.9925Pr0.0075)Si2O7 is obtained. It reveals that orange-red phosphors Ca3-xSi2O7: xPr3+ possess remarkable optical properties and can be used in white light emitting devices.

Molecular-level insights of early-stage prion protein aggregation on mica and gold surface determined by AFM imaging and molecular simulation.

PubMed

Lou, Zhichao; Wang, Bin; Guo, Cunlan; Wang, Kun; Zhang, Haiqian; Xu, Bingqian

2015-11-01

By in situ time-lapse AFM, we investigated early-stage aggregates of PrP formed at low concentration (100 ng/mL) on mica and Au(111) surfaces in acetate buffer (pH 4.5). Remarkably different PrP assemblies were observed. Oligomeric structures of PrP aggregates were observed on mica surface, which was in sharp contrast to the multi-layer PrP aggregates yielding parallel linear patterns observed Au(111) surface. Combining molecular dynamics and docking simulations, PrP monomers, dimers and trimers were revealed as the basic units of the observed aggregates. Besides, the mechanisms of the observed PrP aggregations and the corresponding molecular-substrate and intermolecular interactions were suggested. These interactions involved gold-sulfur interaction, electrostatic interaction, hydrophobic interaction, and hydrogen binding interaction. In contrast, the PrP aggregates observed in pH 7.2 PBS buffer demonstrated similar large ball-like structures on both mica and Au(111) surfaces. The results indicate that the pH of a solution and the surface of the system can have strong effects on supramolecular assemblies of prion proteins. This study provides in-depth understanding on the structural and mechanistic nature of PrP aggregation, and can be used to study the aggregation mechanisms of other proteins with similar misfolding properties. Copyright © 2015 Elsevier B.V. All rights reserved.

Oestrogen and progesterone receptor assays in breast tumours. The Prince Henry's Hospital experience, 1983-1990.

PubMed

Pearce, P T; Myles, K M; Funder, J W

1993-08-16

To present and analyse the results of eight years of experience (1983-1990) in breast tumour receptor analysis. All female primary breast tumour samples received (4683) were analysed for seasonal variation, patient age, relative risk index, oestrogen receptor (ER) and progesterone receptor (PR) status, ER and PR status as a function of age, ER and PR levels as a function of age, and ER and PR levels as a function of month of analysis. The assays were done at the Medical Research Centre, Prince Henry's Hospital, Melbourne, as a non-profit service to surgeons, oncologists and pathologists. The numbers of samples referred for assay increased progressively each year, from 473 in 1983 to 1097 in 1990, but the receptor status (ER +/-, PR +/-) appeared not to vary from year to year. ER+PR+ tumours were the most common in all age groups, steadily increasing from between 50% and 60% in premenopausal women to 70% or more in those aged over 80. In postmenopausal women, levels of ER in ER+ tumours were three times those in premenopausal women; PR levels in PR+ tumours, however, were bimodal, with higher levels in the age groups 35-49 and 70-89 years than in women aged 50-69 years. No significant seasonal variation was seen, and the overall patterns of receptor status are similar to those seen in Northern hemisphere studies.

Photoluminescent emission of Pr 3+ ions in different zirconia crystalline forms

NASA Astrophysics Data System (ADS)

Ramos-Brito, F.; Alejo-Armenta, C.; García-Hipólito, M.; Camarillo, E.; Hernández A, J.; Murrieta S, H.; Falcony, C.

2008-08-01

Polycrystalline praseodymium doped-zirconia powders were synthesized by crystallization of a saturated solution and annealed in air at T a = 950 °C. Monoclinic, tetragonal and cubic crystalline phases of zirconia were obtained. EDS studies showed homogeneous chemical composition over all the powders particles and chemical elemental contents in good agreement with the incorporation of Pr 3+ ion in Zr 4+ sites. XRD patterns showed stabilization of tetragonal and cubic phases at 1.28 and 2.87 at.% of Pr 3+ doping concentrations, respectively. Both unit cells expand when Pr 3+ content increases. All samples showed a crystallite size lower than 27 nm. Diffuse reflectance studies exhibited the presence of the 4f5d absorption band of Pr 3+, and absorption peaks in 440-610 nm region associated with 4f inter-level electronic transitions in Pr 3+ ion. Low temperature (20 K) photo-luminescent spectroscopic measurements over excitation of 488 nm for praseodymium doped zirconia, showed multiple emission peaks in the 520-900 nm range of the electromagnetic spectrum, associated with typical 4f inter-level electronic transition in Pr 3+. Incorporation of Pr 3+ in more than one zirconia crystalline phase and the incorporation in cubic C 2 sites, were observed. Zirconia powders presented significant differences in its emission spectra as a function of the type of crystalline phase compounds.

Evaluation of electrical propagation delay with cardiomyocytes by photosensitization reaction in vitro

NASA Astrophysics Data System (ADS)

Doi, Marika; Ogawa, Emiyu; Arai, Tsunenori

2017-02-01

In order to study cardiomyocyte electrical conduction damage by a photosensitization reaction (PR) mostly comes from outside of the cells in a few minutes after the PR, we studied propagation delay of contact action potential with cardiomyocyte by the PR. To determine appropriate PR condition for tachyarrhythmia ablation, a precise electrophysiological experiment in vitro has been preferable. We measured the contact action potential using a microelectrode array system of which information may be correct than conventional Ca2+ measurement. We investigated the propagation delays of an evoked potential to evaluate the electrical conduction damage by the PR. Rat cardiomyocytes were cultivated for 5-7 days on a dish with which 64 electrodes were patterned, in an incubator controlled to 37°C, 5% CO2. The following conditions were used for the PR: 40 μg/ml talapordfin sodium and 290 mW/cm2, 40-78 J/cm2 for an irradiation. A 2D map was obtained to visualize the propagation delays of the evoked potential. The propagation speed, which was calculated based on the measured propagation delays, was decreased by about 30-50% on average of all electrodes after the PR. Therefore, we think 2D propagation delays measurement of the evoked potential with contact action potential measuring system might be available to evaluate the acute electrical conduction damage of cardiomyocyte by the PR.

Facial emotion recognition in Williams syndrome and Down syndrome: A matching and developmental study.

PubMed

Martínez-Castilla, Pastora; Burt, Michael; Borgatti, Renato; Gagliardi, Chiara

2015-01-01

In this study both the matching and developmental trajectories approaches were used to clarify questions that remain open in the literature on facial emotion recognition in Williams syndrome (WS) and Down syndrome (DS). The matching approach showed that individuals with WS or DS exhibit neither proficiency for the expression of happiness nor specific impairments for negative emotions. Instead, they present the same pattern of emotion recognition as typically developing (TD) individuals. Thus, the better performance on the recognition of positive compared to negative emotions usually reported in WS and DS is not specific of these populations but seems to represent a typical pattern. Prior studies based on the matching approach suggested that the development of facial emotion recognition is delayed in WS and atypical in DS. Nevertheless, and even though performance levels were lower in DS than in WS, the developmental trajectories approach used in this study evidenced that not only individuals with DS but also those with WS present atypical development in facial emotion recognition. Unlike in the TD participants, where developmental changes were observed along with age, in the WS and DS groups, the development of facial emotion recognition was static. Both individuals with WS and those with DS reached an early maximum developmental level due to cognitive constraints.

Multivariate fMRI and Eye Tracking Reveal Differential Effects of Visual Interference on Recognition Memory Judgments for Objects and Scenes.

PubMed

O'Neil, Edward B; Watson, Hilary C; Dhillon, Sonya; Lobaugh, Nancy J; Lee, Andy C H

2015-09-01

Recent work has demonstrated that the perirhinal cortex (PRC) supports conjunctive object representations that aid object recognition memory following visual object interference. It is unclear, however, how these representations interact with other brain regions implicated in mnemonic retrieval and how congruent and incongruent interference influences the processing of targets and foils during object recognition. To address this, multivariate partial least squares was applied to fMRI data acquired during an interference match-to-sample task, in which participants made object or scene recognition judgments after object or scene interference. This revealed a pattern of activity sensitive to object recognition following congruent (i.e., object) interference that included PRC, prefrontal, and parietal regions. Moreover, functional connectivity analysis revealed a common pattern of PRC connectivity across interference and recognition conditions. Examination of eye movements during the same task in a separate study revealed that participants gazed more at targets than foils during correct object recognition decisions, regardless of interference congruency. By contrast, participants viewed foils more than targets for incorrect object memory judgments, but only after congruent interference. Our findings suggest that congruent interference makes object foils appear familiar and that a network of regions, including PRC, is recruited to overcome the effects of interference.

Perceiving patterns of play in dynamic sport tasks: investigating the essential information underlying skilled performance.

PubMed

Willams, A Mark; Hodges, Nicola J; North, Jamie S; Barton, Gabor

2006-01-01

The perceptual-cognitive information used to support pattern-recognition skill in soccer was examined. In experiment 1, skilled players were quicker and more accurate than less-skilled players at recognising familiar and unfamiliar soccer action sequences presented on film. In experiment 2, these action sequences were converted into point-light displays, with superficial display features removed and the positions of players and the relational information between them made more salient. Skilled players were more accurate than less-skilled players in recognising sequences presented in point-light form, implying that each pattern of play can be defined by the unique relations between players. In experiment 3, various offensive and defensive players were occluded for the duration of each trial in an attempt to identify the most important sources of information underpinning successful performance. A decrease in response accuracy was observed under occluded compared with non-occluded conditions and the expertise effect was no longer observed. The relational information between certain key players, team-mates and their defensive counterparts may provide the essential information for effective pattern-recognition skill in soccer. Structural feature analysis, temporal phase relations, and knowledge-based information are effectively integrated to facilitate pattern recognition in dynamic sport tasks.

Spatial-frequency cutoff requirements for pattern recognition in central and peripheral vision

PubMed Central

Kwon, MiYoung; Legge, Gordon E.

2011-01-01

It is well known that object recognition requires spatial frequencies exceeding some critical cutoff value. People with central scotomas who rely on peripheral vision have substantial difficulty with reading and face recognition. Deficiencies of pattern recognition in peripheral vision, might result in higher cutoff requirements, and may contribute to the functional problems of people with central-field loss. Here we asked about differences in spatial-cutoff requirements in central and peripheral vision for letter and face recognition. The stimuli were the 26 letters of the English alphabet and 26 celebrity faces. Each image was blurred using a low-pass filter in the spatial frequency domain. Critical cutoffs (defined as the minimum low-pass filter cutoff yielding 80% accuracy) were obtained by measuring recognition accuracy as a function of cutoff (in cycles per object). Our data showed that critical cutoffs increased from central to peripheral vision by 20% for letter recognition and by 50% for face recognition. We asked whether these differences could be accounted for by central/peripheral differences in the contrast sensitivity function (CSF). We addressed this question by implementing an ideal-observer model which incorporates empirical CSF measurements and tested the model on letter and face recognition. The success of the model indicates that central/peripheral differences in the cutoff requirements for letter and face recognition can be accounted for by the information content of the stimulus limited by the shape of the human CSF, combined with a source of internal noise and followed by an optimal decision rule. PMID:21854800

Artificial intelligence tools for pattern recognition

NASA Astrophysics Data System (ADS)

Acevedo, Elena; Acevedo, Antonio; Felipe, Federico; Avilés, Pedro

2017-06-01

In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

Bringing an Ecological Perspective to the Study of Aging and Recognition of Emotional Facial Expressions: Past, Current, and Future Methods

PubMed Central

Isaacowitz, Derek M.; Stanley, Jennifer Tehan

2011-01-01

Older adults perform worse on traditional tests of emotion recognition accuracy than do young adults. In this paper, we review descriptive research to date on age differences in emotion recognition from facial expressions, as well as the primary theoretical frameworks that have been offered to explain these patterns. We propose that this is an area of inquiry that would benefit from an ecological approach in which contextual elements are more explicitly considered and reflected in experimental methods. Use of dynamic displays and examination of specific cues to accuracy, for example, may reveal more nuanced age-related patterns and may suggest heretofore unexplored underlying mechanisms. PMID:22125354

What Primary Care Providers Need to Know about Pre-Exposure Prophylaxis (PrEP) for HIV Prevention: Narrative Review

PubMed Central

Krakower, Douglas; Mayer, Kenneth H.

2013-01-01

As HIV prevalence climbs globally, including more than 50,000 new infections per year in the United States, we need effective HIV prevention strategies. The use of antiretrovirals for pre-exposure prophylaxis (known as “PrEP”) among high-risk HIV-uninfected persons is emerging as one such strategy. Randomized controlled trials have demonstrated that once daily oral PrEP decreased HIV incidence among at-risk MSM and African heterosexuals, including HIV serodiscordant couples. An additional randomized control trial of a pericoital topical application of antiretroviral microbicide gel reduced HIV incidence among at-risk heterosexual South African women. Two other studies in African women did not demonstrate the efficacy of oral or topical PrEP, raising concerns about adherence patterns and efficacy in this population. The FDA Antiretroviral Advisory Panel reviewed these studies and additional data in May 2012 and recommended the approval of oral tenofovir-emtricitabine for PrEP in high-risk populations. Patients may seek PrEP from their primary care providers and those on PrEP require monitoring. Thus, primary care providers should become familiar with PrEP. This review outlines the current state of knowledge about PrEP as it pertains to primary care including identification of individuals likely to benefit from PrEP, counseling to maximize adherence and minimize potential increases in risky behavior, and monitoring for potential drug toxicities, HIV acquisition, and antiretroviral drug resistance. Issues related to cost and insurance coverage are also discussed. Recent data suggest that PrEP, in conjunction with other prevention strategies, holds promise in helping to curtail the HIV epidemic. PMID:22821365

Effect of head and limb orientation on trunk muscle activation during abdominal hollowing in chronic low back pain.

PubMed

Parfrey, Kevin; Gibbons, Sean G T; Drinkwater, Eric J; Behm, David G

2014-02-22

Individuals with chronic low back pain (CLBP) have altered activations patterns of the anterior trunk musculature when performing the abdominal hollowing manœuvre (attempt to pull umbilicus inward and upward towards the spine). There is a subgroup of individuals with CLBP who have high neurocognitive and sensory motor deficits with associated primitive reflexes (PR). The objective of the study was to determine if orienting the head and extremities to positions, which mimic PR patterns would alter anterior trunk musculature activation during the hollowing manoeuvre. This study compared surface electromyography (EMG) of bilateral rectus abdominis (RA), external oblique (EO), and internal obliques (IO) of 11 individuals with CLBP and evident PR to 9 healthy controls during the hollowing manoeuvre in seven positions of the upper quarter. Using magnitude based inferences it was likely (>75%) that controls had a higher ratio of left IO:RA activation with supine (cervical neutral), asymmetrical tonic neck reflex (ATNR) left and right, right cervical rotation and cervical extension positions. A higher ratio of right IO:RA was detected in the cervical neutral and ATNR left position for the control group. The CLBP group were more likely to show higher activation of the left RA in the cervical neutral, ATNR left and right, right cervical rotation and cervical flexion positions as well as in the cervical neutral and cervical flexion position for the right RA. Individuals with CLBP and PR manifested altered activation patterns during the hollowing maneuver compared to healthy controls and that altering cervical and upper extremity position can diminish the group differences. Altered cervical and limb positions can change the activation levels of the IO and EO in both groups.

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Bridge Health Monitoring Using a Machine Learning Strategy

DOT National Transportation Integrated Search

2017-01-01

The goal of this project was to cast the SHM problem within a statistical pattern recognition framework. Techniques borrowed from speaker recognition, particularly speaker verification, were used as this discipline deals with problems very similar to...

Exploring a Decrease in Recognition Performance for Non-Antecedents Following the Processing of Anaphors

ERIC Educational Resources Information Center

Dopkins, Stephen; Nordlie, Johanna

2011-01-01

Recognition judgments to the non-antecedents of a repeated-noun anaphor are slower and less accurate after than before the processing of the anaphor. Disagreement exists as to whether this pattern of performance reflects a bias shift carried out by a memory process associated with the recognition of a word that has previously occurred in the…

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Simulation of Biomimetic Recognition between Polymers and Surfaces

NASA Astrophysics Data System (ADS)

Golumbfskie, Aaron J.; Pande, Vijay S.; Chakraborty, Arup K.

1999-10-01

Many biological processes, such as transmembrane signaling and pathogen-host interactions, are initiated by a protein recognizing a specific pattern of binding sites on part of a membrane or cell surface. By recognition, we imply that the polymer quickly finds and then adsorbs strongly on the pattern-matched region and not on others. The development of synthetic systems that can mimic such recognition between polymers and surfaces could have significant impact on advanced applications such as the development of sensors, molecular-scale separation processes, and synthetic viral inhibition agents. Attempting to affect recognition in synthetic systems by copying the detailed chemistries to which nature has been led over millenia of evolution does not seem practical for most applications. This leads us to the following question: Are there any universal strategies that can affect recognition between polymers and surfaces? Such generic strategies may be easier to implement in abiotic applications. We describe results that suggest that biomimetic recognition between synthetic polymers and surfaces is possible by exploiting certain generic strategies, and we elucidate the kinetic mechanisms by which this occurs. Our results suggest convenient model systems for experimental studies of dynamics in free energy landscapes characteristic of frustrated systems.

Facial and prosodic emotion recognition in social anxiety disorder.

PubMed

Tseng, Huai-Hsuan; Huang, Yu-Lien; Chen, Jian-Ting; Liang, Kuei-Yu; Lin, Chao-Cheng; Chen, Sue-Huei

2017-07-01

Patients with social anxiety disorder (SAD) have a cognitive preference to negatively evaluate emotional information. In particular, the preferential biases in prosodic emotion recognition in SAD have been much less explored. The present study aims to investigate whether SAD patients retain negative evaluation biases across visual and auditory modalities when given sufficient response time to recognise emotions. Thirty-one SAD patients and 31 age- and gender-matched healthy participants completed a culturally suitable non-verbal emotion recognition task and received clinical assessments for social anxiety and depressive symptoms. A repeated measures analysis of variance was conducted to examine group differences in emotion recognition. Compared to healthy participants, SAD patients were significantly less accurate at recognising facial and prosodic emotions, and spent more time on emotion recognition. The differences were mainly driven by the lower accuracy and longer reaction times for recognising fearful emotions in SAD patients. Within the SAD patients, lower accuracy of sad face recognition was associated with higher severity of depressive and social anxiety symptoms, particularly with avoidance symptoms. These findings may represent a cross-modality pattern of avoidance in the later stage of identifying negative emotions in SAD. This pattern may be linked to clinical symptom severity.

Baseline Preferences for Daily, Event-Driven, or Periodic HIV Pre-Exposure Prophylaxis among Gay and Bisexual Men in the PRELUDE Demonstration Project.

PubMed

Vaccher, Stefanie J; Gianacas, Christopher; Templeton, David J; Poynten, Isobel M; Haire, Bridget G; Ooi, Catriona; Foster, Rosalind; McNulty, Anna; Grulich, Andrew E; Zablotska, Iryna B

2017-01-01

The effectiveness of daily pre-exposure prophylaxis (PrEP) is well established. However, there has been increasing interest in non-daily dosing schedules among gay and bisexual men (GBM). This paper explores preferences for PrEP dosing schedules among GBM at baseline in the PRELUDE demonstration project. Individuals at high-risk of HIV were enrolled in a free PrEP demonstration project in New South Wales, Australia, between November 2014 and April 2016. At baseline, they completed an online survey containing detailed behavioural, demographic, and attitudinal questions, including their ideal way to take PrEP: daily (one pill taken every day), event-driven (pills taken only around specific risk events), or periodic (daily dosing during periods of increased risk). Overall, 315 GBM (98% of study sample) provided a preferred PrEP dosing schedule at baseline. One-third of GBM expressed a preference for non-daily PrEP dosing: 20% for event-driven PrEP, and 14% for periodic PrEP. Individuals with a trade/vocational qualification were more likely to prefer periodic to daily PrEP [adjusted odds ratio (aOR) = 4.58, 95% confidence intervals (95% CI): (1.68, 12.49)], compared to individuals whose highest level of education was high school. Having an HIV-positive main regular partner was associated with strong preference for daily, compared to event-driven PrEP [aOR = 0.20, 95% CI: (0.04, 0.87)]. Participants who rated themselves better at taking medications were more likely to prefer daily over periodic PrEP [aOR = 0.39, 95% CI: (0.20, 0.76)]. Individuals' preferences for PrEP schedules are associated with demographic and behavioural factors that may impact on their ability to access health services and information about PrEP and patterns of HIV risk. At the time of data collection, there were limited data available about the efficacy of non-daily PrEP schedules, and clinicians only recommended daily PrEP to study participants. Further research investigating how behaviours and PrEP preferences change correspondingly over time is needed. ClinicalTrials.gov NCT02206555. Registered 28 July 2014.

Rapid detection of malignant bio-species using digital holographic pattern recognition and nano-photonics

NASA Astrophysics Data System (ADS)

Sarkisov, Sergey S.; Kukhtareva, Tatiana; Kukhtarev, Nickolai V.; Curley, Michael J.; Edwards, Vernessa; Creer, Marylyn

2013-03-01

There is a great need for rapid detection of bio-hazardous species particularly in applications to food safety and biodefense. It has been recently demonstrated that the colonies of various bio-species could be rapidly detected using culture-specific and reproducible patterns generated by scattered non-coherent light. However, the method heavily relies on a digital pattern recognition algorithm, which is rather complex, requires substantial computational power and is prone to ambiguities due to shift, scale, or orientation mismatch between the analyzed pattern and the reference from the library. The improvement could be made, if, in addition to the intensity of the scattered optical wave, its phase would be also simultaneously recorded and used for the digital holographic pattern recognition. In this feasibility study the research team recorded digital Gabor-type (in-line) holograms of colonies of micro-organisms, such as Salmonella with a laser diode as a low-coherence light source and a lensless high-resolution (2.0x2.0 micron pixel pitch) digital image sensor. The colonies were grown in conventional Petri dishes using standard methods. The digitally recorded holograms were used for computational reconstruction of the amplitude and phase information of the optical wave diffracted on the colonies. Besides, the pattern recognition of the colony fragments using the cross-correlation between the digital hologram was also implemented. The colonies of mold fungi Altenaria sp, Rhizophus, sp, and Aspergillus sp have been also generating nano-colloidal silver during their growth in specially prepared matrices. The silver-specific plasmonic optical extinction peak at 410-nm was also used for rapid detection and growth monitoring of the fungi colonies.

False recall and recognition of brand names increases over time.

PubMed

Sherman, Susan M

2013-01-01

Using the Deese-Roediger-McDermott (DRM) paradigm, participants are presented with lists of associated words (e.g., bed, awake, night). Subsequently, they reliably have false memories for related but nonpresented words (e.g., SLEEP). Previous research has found that false memories can be created for brand names (e.g., Morrisons, Sainsbury's, Waitrose, and TESCO). The present study investigates the effect of a week's delay on false memories for brand names. Participants were presented with lists of brand names followed by a distractor task. In two between-subjects experiments, participants completed a free recall task or a recognition task either immediately or a week later. In two within-subjects experiments, participants completed a free recall task or a recognition task both immediately and a week later. Correct recall for presented list items decreased over time, whereas false recall for nonpresented lure items increased. For recognition, raw scores revealed an increase in false memory across time reflected in an increase in Remember responses. Analysis of Pr scores revealed that false memory for lures stayed constant over a week, but with an increase in Remember responses in the between-subjects experiment and a trend in the same direction in the within-subjects experiment. Implications for theories of false memory are discussed.

Substitutions of PrP N-terminal histidine residues modulate scrapie disease pathogenesis and incubation time in transgenic mice

PubMed Central

Eigenbrod, Sabina; Frick, Petra; Bertsch, Uwe; Mitteregger-Kretzschmar, Gerda; Mielke, Janina; Maringer, Marko; Piening, Niklas; Hepp, Alexander; Daude, Nathalie; Windl, Otto; Levin, Johannes; Giese, Armin; Sakthivelu, Vignesh; Tatzelt, Jörg

2017-01-01

Prion diseases have been linked to impaired copper homeostasis and copper induced-oxidative damage to the brain. Divalent metal ions, such as Cu2+ and Zn2+, bind to cellular prion protein (PrPC) at octapeptide repeat (OR) and non-OR sites within the N-terminal half of the protein but information on the impact of such binding on conversion to the misfolded isoform often derives from studies using either OR and non-OR peptides or bacterially-expressed recombinant PrP. Here we created new transgenic mouse lines expressing PrP with disrupted copper binding sites within all four histidine-containing OR's (sites 1–4, H60G, H68G, H76G, H84G, "TetraH>G" allele) or at site 5 (composed of residues His-95 and His-110; "H95G" allele) and monitored the formation of misfolded PrP in vivo. Novel transgenic mice expressing PrP(TetraH>G) at levels comparable to wild-type (wt) controls were susceptible to mouse-adapted scrapie strain RML but showed significantly prolonged incubation times. In contrast, amino acid replacement at residue 95 accelerated disease progression in corresponding PrP(H95G) mice. Neuropathological lesions in terminally ill transgenic mice were similar to scrapie-infected wt controls, but less severe. The pattern of PrPSc deposition, however, was not synaptic as seen in wt animals, but instead dense globular plaque-like accumulations of PrPSc in TgPrP(TetraH>G) mice and diffuse PrPSc deposition in (TgPrP(H95G) mice), were observed throughout all brain sections. We conclude that OR and site 5 histidine substitutions have divergent phenotypic impacts and that cis interactions between the OR region and the site 5 region modulate pathogenic outcomes by affecting the PrP globular domain. PMID:29220360

TRMM Precipitation Radar Reflectivity Profiles Compared to High-Resolution Airborne and Ground-Based Radar Measurements

NASA Technical Reports Server (NTRS)

Heymsfield, G. M.; Geerts, B.; Tian, L.

1999-01-01

In this paper, TRMM (Tropical Rainfall Measuring Mission Satellite) Precipitation Radar (PR) products are evaluated by means of simultaneous comparisons with data from the high-altitude ER-2 Doppler Radar (EDOP), as well as ground-based radars. The comparison is aimed primarily at the vertical reflectivity structure, which is of key importance in TRMM rain type classification and latent heating estimation. The radars used in this study have considerably different viewing geometries and resolutions, demanding non-trivial mapping procedures in common earth-relative coordinates. Mapped vertical cross sections and mean profiles of reflectivity from the PR, EDOP, and ground-based radars are compared for six cases. These cases cover a stratiform frontal rainband, convective cells of various sizes and stages, and a hurricane. For precipitating systems that are large relative to the PR footprint size, PR reflectivity profiles compare very well to high-resolution measurements thresholded to the PR minimum reflectivity, and derived variables such as bright band height and rain types are accurate, even at high PR incidence angles. It was found that for, the PR reflectivity of convective cells small relative to the PR footprint is weaker than in reality. Some of these differences can be explained by non-uniform beam filling. For other cases where strong reflectivity gradients occur within a PR footprint, the reflectivity distribution is spread out due to filtering by the PR antenna illumination pattern. In these cases, rain type classification may err and be biased towards the stratiform type, and the average reflectivity tends to be underestimated. The limited sensitivity of the PR implies that the upper regions of precipitation systems remain undetected and that the PR storm top height estimate is unreliable, usually underestimating the actual storm top height. This applies to all cases but the discrepancy is larger for smaller cells where limited sensitivity is compounded by incomplete beam filling. Users of level three TRMM PR products should be aware of this scale dependency.

Motion Based Target Acquisition and Evaluation in an Adaptive Machine Vision System

DTIC Science & Technology

1995-05-01

paths in facial recognition and learning. Annals of Neurology, 22, 41-45. Tolman, E.C. (1932) Purposive behavior in Animals and Men. New York: Appleton...Learned scan paths are the active processes of perception. Rizzo et al. (1987) studied the fixation patterns of two patients with impaired facial ... recognition and learning and found an increase in the randomness of the scan patterns compared to controls, indicating that the cortex was failing to direct

Simulation and performance of an artificial retina for 40 MHz track reconstruction

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-05

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40 MHz. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

Pattern recognition tool based on complex network-based approach

NASA Astrophysics Data System (ADS)

Casanova, Dalcimar; Backes, André Ricardo; Martinez Bruno, Odemir

2013-02-01

This work proposed a generalization of the method proposed by the authors: 'A complex network-based approach for boundary shape analysis'. Instead of modelling a contour into a graph and use complex networks rules to characterize it, here, we generalize the technique. This way, the work proposes a mathematical tool for characterization signals, curves and set of points. To evaluate the pattern description power of the proposal, an experiment of plat identification based on leaf veins image are conducted. Leaf vein is a taxon characteristic used to plant identification proposes, and one of its characteristics is that these structures are complex, and difficult to be represented as a signal or curves and this way to be analyzed in a classical pattern recognition approach. Here, we model the veins as a set of points and model as graphs. As features, we use the degree and joint degree measurements in a dynamic evolution. The results demonstrates that the technique has a good power of discrimination and can be used for plant identification, as well as other complex pattern recognition tasks.

Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

NASA Astrophysics Data System (ADS)

Popko, E. A.; Weinstein, I. A.

2016-08-01

Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

Identity Recognition Algorithm Using Improved Gabor Feature Selection of Gait Energy Image

NASA Astrophysics Data System (ADS)

Chao, LIANG; Ling-yao, JIA; Dong-cheng, SHI

2017-01-01

This paper describes an effective gait recognition approach based on Gabor features of gait energy image. In this paper, the kernel Fisher analysis combined with kernel matrix is proposed to select dominant features. The nearest neighbor classifier based on whitened cosine distance is used to discriminate different gait patterns. The approach proposed is tested on the CASIA and USF gait databases. The results show that our approach outperforms other state of gait recognition approaches in terms of recognition accuracy and robustness.

Automatic recognition of postural allocations.

PubMed

Sazonov, Edward; Krishnamurthy, Vidya; Makeyev, Oleksandr; Browning, Ray; Schutz, Yves; Hill, James

2007-01-01

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.