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Sample records for fold recognition problem

  1. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition.

    Science.gov (United States)

    Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

    2007-05-22

    Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at http://svm-fold.c2b2.columbia.edu. Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach

  2. Improving Protein Fold Recognition by Deep Learning Networks

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    Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

    2015-12-01

    For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

  3. Improving Protein Fold Recognition by Deep Learning Networks.

    Science.gov (United States)

    Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

    2015-12-04

    For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl's benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

  4. Improving protein fold recognition by extracting fold-specific features from predicted residue-residue contacts.

    Science.gov (United States)

    Zhu, Jianwei; Zhang, Haicang; Li, Shuai Cheng; Wang, Chao; Kong, Lupeng; Sun, Shiwei; Zheng, Wei-Mou; Bu, Dongbo

    2017-12-01

    Accurate recognition of protein fold types is a key step for template-based prediction of protein structures. The existing approaches to fold recognition mainly exploit the features derived from alignments of query protein against templates. These approaches have been shown to be successful for fold recognition at family level, but usually failed at superfamily/fold levels. To overcome this limitation, one of the key points is to explore more structurally informative features of proteins. Although residue-residue contacts carry abundant structural information, how to thoroughly exploit these information for fold recognition still remains a challenge. In this study, we present an approach (called DeepFR) to improve fold recognition at superfamily/fold levels. The basic idea of our approach is to extract fold-specific features from predicted residue-residue contacts of proteins using deep convolutional neural network (DCNN) technique. Based on these fold-specific features, we calculated similarity between query protein and templates, and then assigned query protein with fold type of the most similar template. DCNN has showed excellent performance in image feature extraction and image recognition; the rational underlying the application of DCNN for fold recognition is that contact likelihood maps are essentially analogy to images, as they both display compositional hierarchy. Experimental results on the LINDAHL dataset suggest that even using the extracted fold-specific features alone, our approach achieved success rate comparable to the state-of-the-art approaches. When further combining these features with traditional alignment-related features, the success rate of our approach increased to 92.3%, 82.5% and 78.8% at family, superfamily and fold levels, respectively, which is about 18% higher than the state-of-the-art approach at fold level, 6% higher at superfamily level and 1% higher at family level. An independent assessment on SCOP_TEST dataset showed consistent

  5. Protein fold recognition using geometric kernel data fusion.

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    Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

    2014-07-01

    Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

  6. Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

    Science.gov (United States)

    Ren, Weitong; Ji, Dongqing; Xu, Xiulian

    2018-01-01

    The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

  7. Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

    Directory of Open Access Journals (Sweden)

    Weitong Ren

    Full Text Available The HIV-1 nucleocapsid 7 (NCp7 plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3 recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

  8. Melody discrimination and protein fold classification

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    Robert P. Bywater

    2016-10-01

    Full Text Available One of the greatest challenges in theoretical biophysics and bioinformatics is the identification of protein folds from sequence data. This can be regarded as a pattern recognition problem. In this paper we report the use of a melody generation software where the inputs are derived from calculations of evolutionary information, secondary structure, flexibility, hydropathy and solvent accessibility from multiple sequence alignment data. The melodies so generated are derived from the sequence, and by inference, of the fold, in ways that give each fold a sound representation that may facilitate analysis, recognition, or comparison with other sequences.

  9. Very low resolution face recognition problem.

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    Zou, Wilman W W; Yuen, Pong C

    2012-01-01

    This paper addresses the very low resolution (VLR) problem in face recognition in which the resolution of the face image to be recognized is lower than 16 × 16. With the increasing demand of surveillance camera-based applications, the VLR problem happens in many face application systems. Existing face recognition algorithms are not able to give satisfactory performance on the VLR face image. While face super-resolution (SR) methods can be employed to enhance the resolution of the images, the existing learning-based face SR methods do not perform well on such a VLR face image. To overcome this problem, this paper proposes a novel approach to learn the relationship between the high-resolution image space and the VLR image space for face SR. Based on this new approach, two constraints, namely, new data and discriminative constraints, are designed for good visuality and face recognition applications under the VLR problem, respectively. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

  10. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

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    Muhammad Hameed Siddiqi

    2013-12-01

    Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

  11. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Science.gov (United States)

    Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

    2013-01-01

    Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

  12. An inverse problem approach to pattern recognition in industry

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    Ali Sever

    2015-01-01

    Full Text Available Many works have shown strong connections between learning and regularization techniques for ill-posed inverse problems. A careful analysis shows that a rigorous connection between learning and regularization for inverse problem is not straightforward. In this study, pattern recognition will be viewed as an ill-posed inverse problem and applications of methods from the theory of inverse problems to pattern recognition are studied. A new learning algorithm derived from a well-known regularization model is generated and applied to the task of reconstruction of an inhomogeneous object as pattern recognition. Particularly, it is demonstrated that pattern recognition can be reformulated in terms of inverse problems defined by a Riesz-type kernel. This reformulation can be employed to design a learning algorithm based on a numerical solution of a system of linear equations. Finally, numerical experiments have been carried out with synthetic experimental data considering a reasonable level of noise. Good recoveries have been achieved with this methodology, and the results of these simulations are compatible with the existing methods. The comparison results show that the Regularization-based learning algorithm (RBA obtains a promising performance on the majority of the test problems. In prospects, this method can be used for the creation of automated systems for diagnostics, testing, and control in various fields of scientific and applied research, as well as in industry.

  13. Recognition of Action as a Bayesian Parameter Estimation Problem over Time

    DEFF Research Database (Denmark)

    Krüger, Volker

    2007-01-01

    In this paper we will discuss two problems related to action recognition: The first problem is the one of identifying in a surveillance scenario whether a person is walking or running and in what rough direction. The second problem is concerned with the recovery of action primitives from observed...... complex actions. Both problems will be discussed within a statistical framework. Bayesian propagation over time offers a framework to treat likelihood observations at each time step and the dynamics between the time steps in a unified manner. The first problem will be approached as a patter recognition...... of the Bayesian framework for action recognition and round up our discussion....

  14. Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

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    Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2016-08-07

    Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Influence of Child Factors on Health-Care Professionals' Recognition of Common Childhood Mental-Health Problems.

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    Burke, Delia A; Koot, Hans M; de Wilde, Amber; Begeer, Sander

    Early recognition of childhood mental-health problems can help minimise long-term negative outcomes. Recognition of mental-health problems, needed for referral and diagnostic evaluation, is largely dependent on health-care professionals' (HCPs) judgement of symptoms presented by the child. This study aimed to establish whether HCPs recognition of mental-health problems varies as a function of three child-related factors (type of problem, number of symptoms, and demographic characteristics). In an online survey, HCPs ( n  = 431) evaluated a series of vignettes describing children with symptoms of mental-health problems. Vignettes varied by problem type (Attention-Deficit/Hyperactivity Disorder (ADHD), Generalised Anxiety Disorder (GAD), Autism Spectrum Disorder (ASD), Conduct Disorder (CD) and Major Depressive Disorder), number of symptoms presented (few and many), and child demographic characteristics (ethnicity, gender, age and socio-economic status (SES)). Results show that recognition of mental-health problems varies by problem type, with ADHD best recognised and GAD worst. Furthermore, recognition varies by the number of symptoms presented. Unexpectedly, a child's gender, ethnicity and family SES did not influence likelihood of problem recognition. These results are the first to reveal differences in HCPs' recognition of various common childhood mental-health problems. HCPs in practice should be advised about poor recognition of GAD, and superior recognition of ADHD, if recognition of all childhood mental-health problems is to be equal.

  16. The Multiple-Minima Problem in Protein Folding

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    Scheraga, Harold A.

    1991-10-01

    The conformational energy surface of a polypeptide or protein has many local minima, and conventional energy minimization procedures reach only a local minimum (near the starting point of the optimization algorithm) instead of the global minimum (the multiple-minima problem). Several procedures have been developed to surmount this problem, the most promising of which are: (a) build up procedure, (b) optimization of electrostatics, (c) Monte Carlo-plus-energy minimization, (d) electrostatically-driven Monte Carlo, (e) inclusion of distance restraints, (f) adaptive importance-sampling Monte Carlo, (g) relaxation of dimensionality, (h) pattern-recognition, and (i) diffusion equation method. These procedures have been applied to a variety of polypeptide structural problems, and the results of such computations are presented. These include the computation of the structures of open-chain and cyclic peptides, fibrous proteins and globular proteins. Present efforts are being devoted to scaling up these procedures from small polypeptides to proteins, to try to compute the three-dimensional structure of a protein from its amino sequence.

  17. Emotion recognition in girls with conduct problems.

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    Schwenck, Christina; Gensthaler, Angelika; Romanos, Marcel; Freitag, Christine M; Schneider, Wolfgang; Taurines, Regina

    2014-01-01

    A deficit in emotion recognition has been suggested to underlie conduct problems. Although several studies have been conducted on this topic so far, most concentrated on male participants. The aim of the current study was to compare recognition of morphed emotional faces in girls with conduct problems (CP) with elevated or low callous-unemotional (CU+ vs. CU-) traits and a matched healthy developing control group (CG). Sixteen girls with CP-CU+, 16 girls with CP-CU- and 32 controls (mean age: 13.23 years, SD=2.33 years) were included. Video clips with morphed faces were presented in two runs to assess emotion recognition. Multivariate analysis of variance with the factors group and run was performed. Girls with CP-CU- needed more time than the CG to encode sad, fearful, and happy faces and they correctly identified sadness less often. Girls with CP-CU+ outperformed the other groups in the identification of fear. Learning effects throughout runs were the same for all groups except that girls with CP-CU- correctly identified fear less often in the second run compared to the first run. Results need to be replicated with comparable tasks, which might result in subgroup-specific therapeutic recommendations.

  18. Amino acid empirical contact energy definitions for fold recognition in the space of contact maps

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    Fogolari Federico

    2003-02-01

    Full Text Available Abstract Background Contradicting evidence has been presented in the literature concerning the effectiveness of empirical contact energies for fold recognition. Empirical contact energies are calculated on the basis of information available from selected protein structures, with respect to a defined reference state, according to the quasi-chemical approximation. Protein-solvent interactions are estimated from residue solvent accessibility. Results In the approach presented here, contact energies are derived from the potential of mean force theory, several definitions of contact are examined and their performance in fold recognition is evaluated on sets of decoy structures. The best definition of contact is tested, on a more realistic scenario, on all predictions including sidechains accepted in the CASP4 experiment. In 30 out of 35 cases the native structure is correctly recognized and best predictions are usually found among the 10 lowest energy predictions. Conclusion The definition of contact based on van der Waals radii of alpha carbon and side chain heavy atoms is seen to perform better than other definitions involving only alpha carbons, only beta carbons, all heavy atoms or only backbone atoms. An important prerequisite for the applicability of the approach is that the protein structure under study should not exhibit anomalous solvent accessibility, compared to soluble proteins whose structure is deposited in the Protein Data Bank. The combined evaluation of a solvent accessibility parameter and contact energy allows for an effective gross screening of predictive models.

  19. The Complexity of Folding Self-Folding Origami

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    Stern, Menachem; Pinson, Matthew B.; Murugan, Arvind

    2017-10-01

    Why is it difficult to refold a previously folded sheet of paper? We show that even crease patterns with only one designed folding motion inevitably contain an exponential number of "distractor" folding branches accessible from a bifurcation at the flat state. Consequently, refolding a sheet requires finding the ground state in a glassy energy landscape with an exponential number of other attractors of higher energy, much like in models of protein folding (Levinthal's paradox) and other NP-hard satisfiability (SAT) problems. As in these problems, we find that refolding a sheet requires actuation at multiple carefully chosen creases. We show that seeding successful folding in this way can be understood in terms of subpatterns that fold when cut out ("folding islands"). Besides providing guidelines for the placement of active hinges in origami applications, our results point to fundamental limits on the programmability of energy landscapes in sheets.

  20. Some problems of geologic relations between the Amazon craton and east margins fold belts

    International Nuclear Information System (INIS)

    Almeida, F.F.M. de

    1986-01-01

    This paper deals with some geologic problems related to the limits between the Amazon craton and the fold belts developed at its margins during the Precambrian. These limits are diversified but clearly recognized. To the north, the Araguaia-Tocantins fold belt, of presumed Middle Proterozoic age, is separated from the cratonic block by a deep marginal fracture zone permeated by mafic and ultramafic rocks. The geologic, magmatic and aeromagnetic characteristics of this zone point out the presence of deep faults, supposed to be of Middle Proterozoic age. The southern Paraguay fold belt constitutes and accurated zone of linear structures supposed to be of Late Proterozoic development. Despite the great increase of knowledge during the last ten years many tectonic, stratigraphic and geochronologic problems remain unsolved. The aim of this paper is to point out some of these problems and suggest specific studies to solve them. (author)

  1. The Complexity of Folding Self-Folding Origami

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    Menachem Stern

    2017-12-01

    Full Text Available Why is it difficult to refold a previously folded sheet of paper? We show that even crease patterns with only one designed folding motion inevitably contain an exponential number of “distractor” folding branches accessible from a bifurcation at the flat state. Consequently, refolding a sheet requires finding the ground state in a glassy energy landscape with an exponential number of other attractors of higher energy, much like in models of protein folding (Levinthal’s paradox and other NP-hard satisfiability (SAT problems. As in these problems, we find that refolding a sheet requires actuation at multiple carefully chosen creases. We show that seeding successful folding in this way can be understood in terms of subpatterns that fold when cut out (“folding islands”. Besides providing guidelines for the placement of active hinges in origami applications, our results point to fundamental limits on the programmability of energy landscapes in sheets.

  2. Covering folded shapes

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    Oswin Aichholzer

    2014-05-01

    Full Text Available Can folding a piece of paper flat make it larger? We explore whether a shape S must be scaled to cover a flat-folded copy of itself. We consider both single folds and arbitrary folds (continuous piecewise isometries \\(S\\to\\mathbb{R}^2\\. The underlying problem is motivated by computational origami, and is related to other covering and fixturing problems, such as Lebesgue's universal cover problem and force closure grasps. In addition to considering special shapes (squares, equilateral triangles, polygons and disks, we give upper and lower bounds on scale factors for single folds of convex objects and arbitrary folds of simply connected objects.

  3. F-Type Lectins: A Highly Diversified Family of Fucose-Binding Proteins with a Unique Sequence Motif and Structural Fold, Involved in Self/Non-Self-Recognition

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    Gerardo R. Vasta

    2017-11-01

    Full Text Available The F-type lectin (FTL family is one of the most recent to be identified and structurally characterized. Members of the FTL family are characterized by a fucose recognition domain [F-type lectin domain (FTLD] that displays a novel jellyroll fold (“F-type” fold and unique carbohydrate- and calcium-binding sequence motifs. This novel lectin family comprises widely distributed proteins exhibiting single, double, or greater multiples of the FTLD, either tandemly arrayed or combined with other structurally and functionally distinct domains, yielding lectin subunits of pleiotropic properties even within a single species. Furthermore, the extraordinary variability of FTL sequences (isoforms that are expressed in a single individual has revealed genetic mechanisms of diversification in ligand recognition that are unique to FTLs. Functions of FTLs in self/non-self-recognition include innate immunity, fertilization, microbial adhesion, and pathogenesis, among others. In addition, although the F-type fold is distinctive for FTLs, a structure-based search revealed apparently unrelated proteins with minor sequence similarity to FTLs that displayed the FTLD fold. In general, the phylogenetic analysis of FTLD sequences from viruses to mammals reveals clades that are consistent with the currently accepted taxonomy of extant species. However, the surprisingly discontinuous distribution of FTLDs within each taxonomic category suggests not only an extensive structural/functional diversification of the FTLs along evolutionary lineages but also that this intriguing lectin family has been subject to frequent gene duplication, secondary loss, lateral transfer, and functional co-option.

  4. Control and Alcohol-Problem Recognition among College Students

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    Simons, Raluca M.; Hahn, Austin M.; Simons, Jeffrey S.; Gaster, Sam

    2015-01-01

    Objective: This study examined negative control (ie, perceived lack of control over life outcomes) and need for control as predictors of alcohol-problem recognition, evaluations (good/bad), and expectancies (likely/unlikely) among college students. The study also explored the interaction between the need for control and alcohol consumption in…

  5. RNA folding: structure prediction, folding kinetics and ion electrostatics.

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    Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

    2015-01-01

    Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

  6. Wrong capital? Problems with recognition of knowledge presented by non-native students in international education

    DEFF Research Database (Denmark)

    Wilken, Lisanne

    This paper presents research on problems of knowledge recognition among students of various nationalities at an international organisation......This paper presents research on problems of knowledge recognition among students of various nationalities at an international organisation...

  7. Linear Programming and Its Application to Pattern Recognition Problems

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    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.

  8. Influence of Child Factors on Health-Care Professionals' Recognition of Common Childhood Mental-Health Problems

    NARCIS (Netherlands)

    Burke, Delia A; Koot, Hans M; de Wilde, Amber; Begeer, Sander

    2016-01-01

    Early recognition of childhood mental-health problems can help minimise long-term negative outcomes. Recognition of mental-health problems, needed for referral and diagnostic evaluation, is largely dependent on health-care professionals' (HCPs) judgement of symptoms presented by the child. This

  9. Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures.

    Science.gov (United States)

    Llanes, Antonio; Muñoz, Andrés; Bueno-Crespo, Andrés; García-Valverde, Teresa; Sánchez, Antonia; Arcas-Túnez, Francisco; Pérez-Sánchez, Horacio; Cecilia, José M

    2016-01-01

    The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.

  10. Definition of new 3D invariants. Applications to pattern recognition problems with neural networks

    International Nuclear Information System (INIS)

    Proriol, J.

    1996-01-01

    We propose a definition of new 3D invariants. Usual pattern recognition methods use 2D descriptions of 3D objects, we propose a 2D approximation of the defined 3D invariants which can be used with neural networks to solve pattern recognition problems. We describe some methods to use the 2 D approximants. This work is an extension of previous 3D invariants used to solve some high energy physics problems. (author)

  11. Complete fold annotation of the human proteome using a novel structural feature space.

    Science.gov (United States)

    Middleton, Sarah A; Illuminati, Joseph; Kim, Junhyong

    2017-04-13

    Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.

  12. How can professionals carry out recognition towards children of parents with alcohol problems? A qualitative interview study.

    Science.gov (United States)

    Werner, Anne; Malterud, Kirsti

    2017-02-01

    The aim of this study was to explore informal adult support experienced by children with parental alcohol problems to understand how professionals can show recognition in a similar way. We conducted a qualitative interview study with retrospective accounts from nine adults growing up with problem-drinking parents. Data were analysed with systematic text condensation. Goffman's concept "frame" offered a lens to study how supportive situations were defined and to understand opportunities and limitations for translation of recognition acts and attitudes to professional contexts. Analysis demonstrated frames of commonplace interaction where children experienced that adults recognised and responded to their needs. However, the silent support from an adult who recognised the problems without responding was an ambiguous frame. The child sometimes felt betrayed. Concentrating on frames of recognition which could be passed over to professional interactions, we noticed that participants called for a safe harbour, providing a sense of normality. Being with friends and their families, escaping difficulties at home without having to tell, was emphasised as important. Recognition was experienced when an adult with respect and dignity offered an open opportunity to address the problems, without pushing towards further communication. Our study indicates some specific lessons to be learnt about recognition for professional service providers from everyday situations. Frames of recognition, communicating availability and normality, and also unconditional confidentiality and safety when sharing problems may also be offered by professionals in public healthcare within their current frames of competency and time.

  13. FRankenstein becomes a cyborg: the automatic recombination and realignment of fold recognition models in CASP6.

    Science.gov (United States)

    Kosinski, Jan; Gajda, Michal J; Cymerman, Iwona A; Kurowski, Michal A; Pawlowski, Marcin; Boniecki, Michal; Obarska, Agnieszka; Papaj, Grzegorz; Sroczynska-Obuchowicz, Paulina; Tkaczuk, Karolina L; Sniezynska, Paulina; Sasin, Joanna M; Augustyn, Anna; Bujnicki, Janusz M; Feder, Marcin

    2005-01-01

    In the course of CASP6, we generated models for all targets using a new version of the "FRankenstein's monster approach." Previously (in CASP5) we were able to build many very accurate full-atom models by selection and recombination of well-folded fragments obtained from crude fold recognition (FR) results, followed by optimization of the sequence-structure fit and assessment of alternative alignments on the structural level. This procedure was however very arduous, as most of the steps required extensive visual and manual input from the human modeler. Now, we have automated the most tedious steps, such as superposition of alternative models, extraction of best-scoring fragments, and construction of a hybrid "monster" structure, as well as generation of alternative alignments in the regions that remain poorly scored in the refined hybrid model. We have also included the ROSETTA method to construct those parts of the target for which no reasonable structures were generated by FR methods (such as long insertions and terminal extensions). The analysis of successes and failures of the current version of the FRankenstein approach in modeling of CASP6 targets reveals that the considerably streamlined and automated method performs almost as well as the initial, mostly manual version, which suggests that it may be a useful tool for accurate protein structure prediction even in the hands of nonexperts. 2005 Wiley-Liss, Inc.

  14. Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

    Science.gov (United States)

    Nasertdinova, A. D.; Bochkarev, V. V.

    2017-11-01

    Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

  15. FOLD-EM: automated fold recognition in medium- and low-resolution (4-15 Å) electron density maps.

    Science.gov (United States)

    Saha, Mitul; Morais, Marc C

    2012-12-15

    Owing to the size and complexity of large multi-component biological assemblies, the most tractable approach to determining their atomic structure is often to fit high-resolution radiographic or nuclear magnetic resonance structures of isolated components into lower resolution electron density maps of the larger assembly obtained using cryo-electron microscopy (cryo-EM). This hybrid approach to structure determination requires that an atomic resolution structure of each component, or a suitable homolog, is available. If neither is available, then the amount of structural information regarding that component is limited by the resolution of the cryo-EM map. However, even if a suitable homolog cannot be identified using sequence analysis, a search for structural homologs should still be performed because structural homology often persists throughout evolution even when sequence homology is undetectable, As macromolecules can often be described as a collection of independently folded domains, one way of searching for structural homologs would be to systematically fit representative domain structures from a protein domain database into the medium/low resolution cryo-EM map and return the best fits. Taken together, the best fitting non-overlapping structures would constitute a 'mosaic' backbone model of the assembly that could aid map interpretation and illuminate biological function. Using the computational principles of the Scale-Invariant Feature Transform (SIFT), we have developed FOLD-EM-a computational tool that can identify folded macromolecular domains in medium to low resolution (4-15 Å) electron density maps and return a model of the constituent polypeptides in a fully automated fashion. As a by-product, FOLD-EM can also do flexible multi-domain fitting that may provide insight into conformational changes that occur in macromolecular assemblies.

  16. PREFACE Protein folding: lessons learned and new frontiers Protein folding: lessons learned and new frontiers

    Science.gov (United States)

    Pappu, Rohit V.; Nussinov, Ruth

    2009-03-01

    multi-scale dynamical problem when one considers the synergies between protein expression, spontaneous folding, chaperonin-assisted folding, protein targeting, the kinetics of post-translational modifications, protein degradation, and of course the drive to avoid aggregation. Further, there is growing recognition that cells not only tolerate but select for proteins that are intrinsically disordered. These proteins are essential for many crucial activities, and yet their inability to fold in isolation makes them prone to proteolytic processing and aggregation. In the series of papers that make up this special focus on protein folding in physical biology, leading researchers provide insights into diverse cross-sections of problems in protein folding. Barrick provides a concise review of what we have learned from the study of two-state folders and draws attention to how several unanswered questions are being approached using studies on large repeat proteins. Dissecting the contribution of hydration-mediated interactions to driving forces for protein folding and assembly has been extremely challenging. There is renewed interest in using hydrostatic pressure as a tool to access folding intermediates and decipher the role of partially hydrated states in folding, misfolding, and aggregation. Silva and Foguel review many of the nuances that have been uncovered by perturbing hydrostatic pressure as a thermodynamic parameter. As noted above, protein folding in vivo is expected to be considerably more complex than the folding of two-state proteins in dilute solutions. Lucent et al review the state-of-the-art in the development of quantitative theories to explain chaperonin-assisted folding in vivo. Additionally, they highlight unanswered questions pertaining to the processing of unfolded/misfolded proteins by the chaperone machinery. Zhuang et al present results that focus on the effects of surface tethering on transition state ensembles and folding mechanisms of a model two

  17. Chaotic Multiquenching Annealing Applied to the Protein Folding Problem

    Directory of Open Access Journals (Sweden)

    Juan Frausto-Solis

    2014-01-01

    Full Text Available The Chaotic Multiquenching Annealing algorithm (CMQA is proposed. CMQA is a new algorithm, which is applied to protein folding problem (PFP. This algorithm is divided into three phases: (i multiquenching phase (MQP, (ii annealing phase (AP, and (iii dynamical equilibrium phase (DEP. MQP enforces several stages of quick quenching processes that include chaotic functions. The chaotic functions can increase the exploration potential of solutions space of PFP. AP phase implements a simulated annealing algorithm (SA with an exponential cooling function. MQP and AP are delimited by different ranges of temperatures; MQP is applied for a range of temperatures which goes from extremely high values to very high values; AP searches for solutions in a range of temperatures from high values to extremely low values. DEP phase finds the equilibrium in a dynamic way by applying least squares method. CMQA is tested with several instances of PFP.

  18. Study of problems met in muon pattern recognition for a deep inelastic scattering experiment at the S.P.S

    International Nuclear Information System (INIS)

    Besson, C.

    1976-01-01

    The problems of the muon pattern recognition are studied for a muon-proton deep inelastic scattering experiment at the S.P.S. The pattern recognition program is described together with the problems caused by some characteristics of the apparatus of the European muon collaboration. Several reconstruction technics are compared, and a way of handling big drift chamber problems is found. Some results on Monte-Carlo tracks are given [fr

  19. Fold-recognition and comparative modeling of human α2,3-sialyltransferases reveal their sequence and structural similarities to CstII from Campylobacter jejuni

    Directory of Open Access Journals (Sweden)

    Balaji Petety V

    2006-04-01

    Full Text Available Abstract Background The 3-D structure of none of the eukaryotic sialyltransferases (SiaTs has been determined so far. Sequence alignment algorithms such as BLAST and PSI-BLAST could not detect a homolog of these enzymes from the protein databank. SiaTs, thus, belong to the hard/medium target category in the CASP experiments. The objective of the current work is to model the 3-D structures of human SiaTs which transfer the sialic acid in α2,3-linkage viz., ST3Gal I, II, III, IV, V, and VI, using fold-recognition and comparative modeling methods. The pair-wise sequence similarity among these six enzymes ranges from 41 to 63%. Results Unlike the sequence similarity servers, fold-recognition servers identified CstII, a α2,3/8 dual-activity SiaT from Campylobacter jejuni as the homolog of all the six ST3Gals; the level of sequence similarity between CstII and ST3Gals is only 15–20% and the similarity is restricted to well-characterized motif regions of ST3Gals. Deriving template-target sequence alignments for the entire ST3Gal sequence was not straightforward: the fold-recognition servers could not find a template for the region preceding the L-motif and that between the L- and S-motifs. Multiple structural templates were identified to model these regions and template identification-modeling-evaluation had to be performed iteratively to choose the most appropriate templates. The modeled structures have acceptable stereochemical properties and are also able to provide qualitative rationalizations for some of the site-directed mutagenesis results reported in literature. Apart from the predicted models, an unexpected but valuable finding from this study is the sequential and structural relatedness of family GT42 and family GT29 SiaTs. Conclusion The modeled 3-D structures can be used for docking and other modeling studies and for the rational identification of residues to be mutated to impart desired properties such as altered stability, substrate

  20. Applications of chaotic neurodynamics in pattern recognition

    Science.gov (United States)

    Baird, Bill; Freeman, Walter J.; Eeckman, Frank H.; Yao, Yong

    1991-08-01

    Network algorithms and architectures for pattern recognition derived from neural models of the olfactory system are reviewed. These span a range from highly abstract to physiologically detailed, and employ the kind of dynamical complexity observed in olfactory cortex, ranging from oscillation to chaos. A simple architecture and algorithm for analytically guaranteed associative memory storage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored. There are N units of capacity in an N node network with 3N2 weights. It costs one unit per static attractor, two per Fourier component of each sequence, and three to four per chaotic attractor. There are no spurious attractors, and for sequences there is a Liapunov function in a special coordinate system which governs the approach of transient states to stored trajectories. Unsupervised or supervised incremental learning algorithms for pattern classification, such as competitive learning or bootstrap Widrow-Hoff can easily be implemented. The architecture can be ''folded'' into a recurrent network with higher order weights that can be used as a model of cortex that stores oscillatory and chaotic attractors by a Hebb rule. Network performance is demonstrated by application to the problem of real-time handwritten digit recognition. An effective system with on-line learning has been written by Eeckman and Baird for the Macintosh. It utilizes static, oscillatory, and/or chaotic attractors of two kinds--Lorenze attractors, or attractors resulting from chaotically interacting oscillatory modes. The successful application to an industrial pattern recognition problem of a network architecture of considerable physiological and dynamical complexity, developed by Freeman and Yao, is described. The data sets of the problem come in three classes of difficulty, and performance of the biological network is

  1. Graphical symbol recognition

    OpenAIRE

    K.C. , Santosh; Wendling , Laurent

    2015-01-01

    International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...

  2. A Comprehensive Analysis on Wearable Acceleration Sensors in Human Activity Recognition.

    Science.gov (United States)

    Janidarmian, Majid; Roshan Fekr, Atena; Radecka, Katarzyna; Zilic, Zeljko

    2017-03-07

    Sensor-based motion recognition integrates the emerging area of wearable sensors with novel machine learning techniques to make sense of low-level sensor data and provide rich contextual information in a real-life application. Although Human Activity Recognition (HAR) problem has been drawing the attention of researchers, it is still a subject of much debate due to the diverse nature of human activities and their tracking methods. Finding the best predictive model in this problem while considering different sources of heterogeneities can be very difficult to analyze theoretically, which stresses the need of an experimental study. Therefore, in this paper, we first create the most complete dataset, focusing on accelerometer sensors, with various sources of heterogeneities. We then conduct an extensive analysis on feature representations and classification techniques (the most comprehensive comparison yet with 293 classifiers) for activity recognition. Principal component analysis is applied to reduce the feature vector dimension while keeping essential information. The average classification accuracy of eight sensor positions is reported to be 96.44% ± 1.62% with 10-fold evaluation, whereas accuracy of 79.92% ± 9.68% is reached in the subject-independent evaluation. This study presents significant evidence that we can build predictive models for HAR problem under more realistic conditions, and still achieve highly accurate results.

  3. Long-Lived Folding Intermediates Predominate the Targeting-Competent Secretome

    DEFF Research Database (Denmark)

    Tsirigotaki, Alexandra; Chatzi, Katerina E; Koukaki, Marina

    2018-01-01

    is unknown, but is generally attributed to signal peptides and chaperones. We herein demonstrate that, during targeting, most mature domains maintain loosely packed folding intermediates. These largely soluble states are signal peptide independent and essential for translocase recognition...

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

    Science.gov (United States)

    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.

  5. A Comprehensive Analysis on Wearable Acceleration Sensors in Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Majid Janidarmian

    2017-03-01

    Full Text Available Sensor-based motion recognition integrates the emerging area of wearable sensors with novel machine learning techniques to make sense of low-level sensor data and provide rich contextual information in a real-life application. Although Human Activity Recognition (HAR problem has been drawing the attention of researchers, it is still a subject of much debate due to the diverse nature of human activities and their tracking methods. Finding the best predictive model in this problem while considering different sources of heterogeneities can be very difficult to analyze theoretically, which stresses the need of an experimental study. Therefore, in this paper, we first create the most complete dataset, focusing on accelerometer sensors, with various sources of heterogeneities. We then conduct an extensive analysis on feature representations and classification techniques (the most comprehensive comparison yet with 293 classifiers for activity recognition. Principal component analysis is applied to reduce the feature vector dimension while keeping essential information. The average classification accuracy of eight sensor positions is reported to be 96.44% ± 1.62% with 10-fold evaluation, whereas accuracy of 79.92% ± 9.68% is reached in the subject-independent evaluation. This study presents significant evidence that we can build predictive models for HAR problem under more realistic conditions, and still achieve highly accurate results.

  6. Evaluating music emotion recognition:Lessons from music genre recognition?

    OpenAIRE

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER syste...

  7. Application of PSO for solving problems of pattern recognition

    Directory of Open Access Journals (Sweden)

    S. N. Chukanov

    2016-01-01

    Full Text Available The problem of estimating the norm of the distance between the two closed smooth curves for pattern recognition is considered. Diffeomorphic transformation curves based on the model of large deformation with the transformation of the starting points of domain in required is formed on the basis of which depends on time-dependent vector field of velocity is considered. The action of the translation, rotation and scaling closed curve, the invariants of the action of these groups are considered. The position of curves is normalized by centering, bringing the principal axes of the image to the axes of the coordinate system and bringing the area of a closed curve corresponding to one. For estimating of the norm of the distance between two closed curves is formed the functional corresponding normalized distance between the two curves, and the equation of evolution diffeomorphic transformations. The equation of evolution allows to move objects along trajectories which correspond to diffeomorphic transformations. The diffeomorphisms do not change the topology along the geodesic trajectories. The problem of inexact comparing the minimized functional contains a term that estimates the exactness of shooting points in the required positions. In the equation of evolution is introduced the variance of conversion error. An algorithm for solving the equation of diffeomorphic transformation is proposed, built on the basis of PSO, which can significantly reduce the number of computing operations, compared with gradient methods for solving. The developed algorithms can be used in bioinformatics and biometrics systems, classification of images and objects, machine vision systems, neuroimaging, for pattern recognition and object tracking systems. Algorithm for estimating the norm of distance between the closed curves by diffeomorphic transformation can spread to spatial objects (curves, surfaces, manifolds.

  8. RNAslider: a faster engine for consecutive windows folding and its application to the analysis of genomic folding asymmetry.

    Science.gov (United States)

    Horesh, Yair; Wexler, Ydo; Lebenthal, Ilana; Ziv-Ukelson, Michal; Unger, Ron

    2009-03-04

    Scanning large genomes with a sliding window in search of locally stable RNA structures is a well motivated problem in bioinformatics. Given a predefined window size L and an RNA sequence S of size N (L free energy (MFE) for the folding of each of the L-sized substrings of S. The consecutive windows folding problem can be naively solved in O(NL3) by applying any of the classical cubic-time RNA folding algorithms to each of the N-L windows of size L. Recently an O(NL2) solution for this problem has been described. Here, we describe and implement an O(NLpsi(L)) engine for the consecutive windows folding problem, where psi(L) is shown to converge to O(1) under the assumption of a standard probabilistic polymer folding model, yielding an O(L) speedup which is experimentally confirmed. Using this tool, we note an intriguing directionality (5'-3' vs. 3'-5') folding bias, i.e. that the minimal free energy (MFE) of folding is higher in the native direction of the DNA than in the reverse direction of various genomic regions in several organisms including regions of the genomes that do not encode proteins or ncRNA. This bias largely emerges from the genomic dinucleotide bias which affects the MFE, however we see some variations in the folding bias in the different genomic regions when normalized to the dinucleotide bias. We also present results from calculating the MFE landscape of a mouse chromosome 1, characterizing the MFE of the long ncRNA molecules that reside in this chromosome. The efficient consecutive windows folding engine described in this paper allows for genome wide scans for ncRNA molecules as well as large-scale statistics. This is implemented here as a software tool, called RNAslider, and applied to the scanning of long chromosomes, leading to the observation of features that are visible only on a large scale.

  9. Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

    Science.gov (United States)

    Chu, Xiakun; Gan, Linfeng; Wang, Erkang; Wang, Jin

    2013-01-01

    Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments. PMID:23754431

  10. A study of fuzzy logic ensemble system performance on face recognition problem

    Science.gov (United States)

    Polyakova, A.; Lipinskiy, L.

    2017-02-01

    Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

  11. Specificity and affinity quantification of flexible recognition from underlying energy landscape topography.

    Directory of Open Access Journals (Sweden)

    Xiakun Chu

    2014-08-01

    Full Text Available Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less flexibility leads to weaker (stronger coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

  12. Natural triple beta-stranded fibrous folds.

    Science.gov (United States)

    Mitraki, Anna; Papanikolopoulou, Katerina; Van Raaij, Mark J

    2006-01-01

    A distinctive family of beta-structured folds has recently been described for fibrous proteins from viruses. Virus fibers are usually involved in specific host-cell recognition. They are asymmetric homotrimeric proteins consisting of an N-terminal virus-binding tail, a central shaft or stalk domain, and a C-terminal globular receptor-binding domain. Often they are entirely or nearly entirely composed of beta-structure. Apart from their biological relevance and possible gene therapy applications, their shape, stability, and rigidity suggest they may be useful as blueprints for biomechanical design. Folding and unfolding studies suggest their globular C-terminal domain may fold first, followed by a "zipping-up" of the shaft domains. The C-terminal domains appear to be important for registration because peptides corresponding to shaft domains alone aggregate into nonnative fibers and/or amyloid structures. C-terminal domains can be exchanged between different fibers and the resulting chimeric proteins are useful as a way to solve structures of unknown parts of the shaft domains. The following natural triple beta-stranded fibrous folds have been discovered by X-ray crystallography: the triple beta-spiral, triple beta-helix, and T4 short tail fiber fold. All have a central longitudinal hydrophobic core and extensive intermonomer polar and nonpolar interactions. Now that a reasonable body of structural and folding knowledge has been assembled about these fibrous proteins, the next challenge and opportunity is to start using this information in medical and industrial applications such as gene therapy and nanotechnology.

  13. Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm.

    Science.gov (United States)

    Li, Bai; Lin, Mu; Liu, Qiao; Li, Ya; Zhou, Changjun

    2015-10-01

    Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques.

  14. Interprofessional, simulation-based technology-enhanced learning to improve physical health care in psychiatry: The recognition and assessment of medical problems in psychiatric settings course.

    Science.gov (United States)

    Akroyd, Mike; Jordan, Gary; Rowlands, Paul

    2016-06-01

    People with serious mental illness have reduced life expectancy compared with a control population, much of which is accounted for by significant physical comorbidity. Frontline clinical staff in mental health often lack confidence in recognition, assessment and management of such 'medical' problems. Simulation provides one way for staff to practise these skills in a safe setting. We produced a multidisciplinary simulation course around recognition and assessment of medical problems in psychiatric settings. We describe an audit of strategic and design aspects of the recognition and assessment of medical problems in psychiatric settings course, using the Department of Health's 'Framework for Technology Enhanced Learning' as our audit standards. At the same time as highlighting areas where recognition and assessment of medical problems in psychiatric settings adheres to these identified principles, such as the strategic underpinning of the approach, and the means by which information is collected, reviewed and shared, it also helps us to identify areas where we can improve. © The Author(s) 2014.

  15. Computational Recognition of RNA Splice Sites by Exact Algorithms for the Quadratic Traveling Salesman Problem

    Directory of Open Access Journals (Sweden)

    Anja Fischer

    2015-06-01

    Full Text Available One fundamental problem of bioinformatics is the computational recognition of DNA and RNA binding sites. Given a set of short DNA or RNA sequences of equal length such as transcription factor binding sites or RNA splice sites, the task is to learn a pattern from this set that allows the recognition of similar sites in another set of DNA or RNA sequences. Permuted Markov (PM models and permuted variable length Markov (PVLM models are two powerful models for this task, but the problem of finding an optimal PM model or PVLM model is NP-hard. While the problem of finding an optimal PM model or PVLM model of order one is equivalent to the traveling salesman problem (TSP, the problem of finding an optimal PM model or PVLM model of order two is equivalent to the quadratic TSP (QTSP. Several exact algorithms exist for solving the QTSP, but it is unclear if these algorithms are capable of solving QTSP instances resulting from RNA splice sites of at least 150 base pairs in a reasonable time frame. Here, we investigate the performance of three exact algorithms for solving the QTSP for ten datasets of splice acceptor sites and splice donor sites of five different species and find that one of these algorithms is capable of solving QTSP instances of up to 200 base pairs with a running time of less than two days.

  16. Crystal structure of the PAC1R extracellular domain unifies a consensus fold for hormone recognition by class B G-protein coupled receptors.

    Directory of Open Access Journals (Sweden)

    Shiva Kumar

    Full Text Available Pituitary adenylate cyclase activating polypeptide (PACAP is a member of the PACAP/glucagon family of peptide hormones, which controls many physiological functions in the immune, nervous, endocrine, and muscular systems. It activates adenylate cyclase by binding to its receptor, PAC1R, a member of class B G-protein coupled receptors (GPCR. Crystal structures of a number of Class B GPCR extracellular domains (ECD bound to their respective peptide hormones have revealed a consensus mechanism of hormone binding. However, the mechanism of how PACAP binds to its receptor remains controversial as an NMR structure of the PAC1R ECD/PACAP complex reveals a different topology of the ECD and a distinct mode of ligand recognition. Here we report a 1.9 Å crystal structure of the PAC1R ECD, which adopts the same fold as commonly observed for other members of Class B GPCR. Binding studies and cell-based assays with alanine-scanned peptides and mutated receptor support a model that PAC1R uses the same conserved fold of Class B GPCR ECD for PACAP binding, thus unifying the consensus mechanism of hormone binding for this family of receptors.

  17. Idiopathic unilateral vocal-fold paralysis in the adult.

    Science.gov (United States)

    Rubin, F; Villeneuve, A; Alciato, L; Slaïm, L; Bonfils, P; Laccourreye, O

    2018-02-02

    To analyze the characteristics of adult idiopathic unilateral vocal-fold paralysis. Retrospective study of diagnostic problems, clinical data and recovery in an inception cohort of 100 adult patients with idiopathic unilateral vocal-fold paralysis (Group A) and comparison with a cohort of 211 patients with isolated non-idiopathic non-traumatic unilateral vocal-fold paralysis (Group B). Diagnostic problems were noted in 24% of cases in Group A: eight patients with concomitant common upper aerodigestive tract infection, five patients with a concomitant condition liable to induce immunodepression and 11 patients in whom a malignant tumor occurred along the path of the ipsilateral vagus and inferior laryngeal nerves or in the ipsilateral paralyzed larynx. There was no recovery of vocal-fold motion beyond 51 months after onset of paralysis. The 5-year actuarial estimate for recovery differed significantly (Pvocal-fold paralysis. In non-traumatic vocal-fold paralysis in adult patients, without recovery of vocal-fold motion, a minimum three years' regular follow-up is recommended. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

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

    Science.gov (United States)

    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…

  19. RNAslider: a faster engine for consecutive windows folding and its application to the analysis of genomic folding asymmetry

    Directory of Open Access Journals (Sweden)

    Ziv-Ukelson Michal

    2009-03-01

    Full Text Available Abstract Background Scanning large genomes with a sliding window in search of locally stable RNA structures is a well motivated problem in bioinformatics. Given a predefined window size L and an RNA sequence S of size N (L 3 by applying any of the classical cubic-time RNA folding algorithms to each of the N-L windows of size L. Recently an O(NL2 solution for this problem has been described. Results Here, we describe and implement an O(NLψ(L engine for the consecutive windows folding problem, where ψ(L is shown to converge to O(1 under the assumption of a standard probabilistic polymer folding model, yielding an O(L speedup which is experimentally confirmed. Using this tool, we note an intriguing directionality (5'-3' vs. 3'-5' folding bias, i.e. that the minimal free energy (MFE of folding is higher in the native direction of the DNA than in the reverse direction of various genomic regions in several organisms including regions of the genomes that do not encode proteins or ncRNA. This bias largely emerges from the genomic dinucleotide bias which affects the MFE, however we see some variations in the folding bias in the different genomic regions when normalized to the dinucleotide bias. We also present results from calculating the MFE landscape of a mouse chromosome 1, characterizing the MFE of the long ncRNA molecules that reside in this chromosome. Conclusion The efficient consecutive windows folding engine described in this paper allows for genome wide scans for ncRNA molecules as well as large-scale statistics. This is implemented here as a software tool, called RNAslider, and applied to the scanning of long chromosomes, leading to the observation of features that are visible only on a large scale.

  20. Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

    Directory of Open Access Journals (Sweden)

    Cai Wingfield

    2017-09-01

    Full Text Available There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG, generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.

  1. Experimental investigation into the mechanism of folding

    NARCIS (Netherlands)

    Kuenen, Ph.H.; Sitter, de L.U.

    1938-01-01

    The investigation of geological structures due to folding led de Sitter to form an opinion on the mechanical problems involved (Bibl. 7). His principal contention is that in simple cases the relative movements of particles with respect to eachother during deformation leading to a fold, have been

  2. Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzyme.

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2011-04-01

    Full Text Available Biomolecular function is realized by recognition, and increasing evidence shows that recognition is determined not only by structure but also by flexibility and dynamics. We explored a biomolecular recognition process that involves a major conformational change - protein folding. In particular, we explore the binding-induced folding of IA3, an intrinsically disordered protein that blocks the active site cleft of the yeast aspartic proteinase saccharopepsin (YPrA by folding its own N-terminal residues into an amphipathic alpha helix. We developed a multi-scaled approach that explores the underlying mechanism by combining structure-based molecular dynamics simulations at the residue level with a stochastic path method at the atomic level. Both the free energy profile and the associated kinetic paths reveal a common scheme whereby IA3 binds to its target enzyme prior to folding itself into a helix. This theoretical result is consistent with recent time-resolved experiments. Furthermore, exploration of the detailed trajectories reveals the important roles of non-native interactions in the initial binding that occurs prior to IA3 folding. In contrast to the common view that non-native interactions contribute only to the roughness of landscapes and impede binding, the non-native interactions here facilitate binding by reducing significantly the entropic search space in the landscape. The information gained from multi-scaled simulations of the folding of this intrinsically disordered protein in the presence of its binding target may prove useful in the design of novel inhibitors of aspartic proteinases.

  3. FRAN and RBF-PSO as two components of a hyper framework to recognize protein folds.

    Science.gov (United States)

    Abbasi, Elham; Ghatee, Mehdi; Shiri, M E

    2013-09-01

    In this paper, an intelligent hyper framework is proposed to recognize protein folds from its amino acid sequence which is a fundamental problem in bioinformatics. This framework includes some statistical and intelligent algorithms for proteins classification. The main components of the proposed framework are the Fuzzy Resource-Allocating Network (FRAN) and the Radial Bases Function based on Particle Swarm Optimization (RBF-PSO). FRAN applies a dynamic method to tune up the RBF network parameters. Due to the patterns complexity captured in protein dataset, FRAN classifies the proteins under fuzzy conditions. Also, RBF-PSO applies PSO to tune up the RBF classifier. Experimental results demonstrate that FRAN improves prediction accuracy up to 51% and achieves acceptable multi-class results for protein fold prediction. Although RBF-PSO provides reasonable results for protein fold recognition up to 48%, it is weaker than FRAN in some cases. However the proposed hyper framework provides an opportunity to use a great range of intelligent methods and can learn from previous experiences. Thus it can avoid the weakness of some intelligent methods in terms of memory, computational time and static structure. Furthermore, the performance of this system can be enhanced throughout the system life-cycle. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Evaluating music emotion recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

  5. Mental Subtraction in High- and Lower Skilled Arithmetic Problem Solvers: Verbal Report versus Operand-Recognition Paradigms

    Science.gov (United States)

    Thevenot, Catherine; Castel, Caroline; Fanget, Muriel; Fayol, Michel

    2010-01-01

    The authors used the operand-recognition paradigm (C. Thevenot, M. Fanget, & M. Fayol, 2007) in order to study the strategies used by adults to solve subtraction problems. This paradigm capitalizes on the fact that algorithmic procedures degrade the memory traces of the operands. Therefore, greater difficulty in recognizing them is expected…

  6. The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

    Science.gov (United States)

    Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

    2011-07-01

    The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

  7. Extreme Mechanics: Self-Folding Origami

    Science.gov (United States)

    Santangelo, Christian D.

    2017-03-01

    Origami has emerged as a tool for designing three-dimensional structures from flat films. Because they can be fabricated by lithographic or roll-to-roll processing techniques, they have great potential for the manufacture of complicated geometries and devices. This article discusses the mechanics of origami and kirigami with a view toward understanding how to design self-folding origami structures. Whether an origami structure can be made to fold autonomously depends strongly on the geometry and kinematics of the origami fold pattern. This article collects some of the results on origami rigidity into a single framework, and discusses how these aspects affect the foldability of origami. Despite recent progress, most problems in origami and origami design remain completely open.

  8. Problems of Face Recognition in Patients with Behavioral Variant Frontotemporal Dementia.

    Science.gov (United States)

    Chandra, Sadanandavalli Retnaswami; Patwardhan, Ketaki; Pai, Anupama Ramakanth

    2017-01-01

    Faces are very special as they are most essential for social cognition in humans. It is partly understood that face processing in its abstractness involves several extra striate areas. One of the most important causes for caregiver suffering in patients with anterior dementia is lack of empathy. This apart from being a behavioral disorder could be also due to failure to categorize the emotions of the people around them. Inlusion criteria: DSM IV for Bv FTD Tested for prosopagnosia - familiar faces, famous face, smiling face, crying face and reflected face using a simple picture card (figure 1). Advanced illness and mixed causes. 46 patients (15 females, 31 males) 24 had defective face recognition. (mean age 51.5),10/15 females (70%) and 14/31males(47. Familiar face recognition defect was found in 6/10 females and 6/14 males. Total- 40%(6/15) females and 19.35%(6/31)males with FTD had familiar face recognition. Famous Face: 9/10 females and 7/14 males. Total- 60% (9/15) females with FTD had famous face recognition defect as against 22.6%(7/31) males with FTD Smiling face defects in 8/10 female and no males. Total- 53.33% (8/15) females. Crying face recognition defect in 3/10 female and 2 /14 males. Total- 20%(3/15) females and 6.5%(2/31) males. Reflected face recognition defect in 4 females. Famous face recognition and positive emotion recognition defect in 80%, only 20% comprehend positive emotions, Face recognition defects are found in only 45% of males and more common in females. Face recognition is more affected in females with FTD There is differential involvement of different aspects of the face recognition could be one of the important factor underlying decline in the emotional and social behavior of these patients. Understanding these pathological processes will give more insight regarding patient behavior.

  9. Traffic sign recognition with deep convolutional neural networks

    OpenAIRE

    Karamatić, Boris

    2016-01-01

    The problem of detection and recognition of traffic signs is becoming an important problem when it comes to the development of self driving cars and advanced driver assistance systems. In this thesis we will develop a system for detection and recognition of traffic signs. For the problem of detection we will use aggregate channel features and for the problem of recognition we will use a deep convolutional neural network. We will describe how convolutional neural networks work, how they are co...

  10. RNAiFold: a web server for RNA inverse folding and molecular design.

    Science.gov (United States)

    Garcia-Martin, Juan Antonio; Clote, Peter; Dotu, Ivan

    2013-07-01

    Synthetic biology and nanotechnology are poised to make revolutionary contributions to the 21st century. In this article, we describe a new web server to support in silico RNA molecular design. Given an input target RNA secondary structure, together with optional constraints, such as requiring GC-content to lie within a certain range, requiring the number of strong (GC), weak (AU) and wobble (GU) base pairs to lie in a certain range, the RNAiFold web server determines one or more RNA sequences, whose minimum free-energy secondary structure is the target structure. RNAiFold provides access to two servers: RNA-CPdesign, which applies constraint programming, and RNA-LNSdesign, which applies the large neighborhood search heuristic; hence, it is suitable for larger input structures. Both servers can also solve the RNA inverse hybridization problem, i.e. given a representation of the desired hybridization structure, RNAiFold returns two sequences, whose minimum free-energy hybridization is the input target structure. The web server is publicly accessible at http://bioinformatics.bc.edu/clotelab/RNAiFold, which provides access to two specialized servers: RNA-CPdesign and RNA-LNSdesign. Source code for the underlying algorithms, implemented in COMET and supported on linux, can be downloaded at the server website.

  11. STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.

    Science.gov (United States)

    Fan, Jianqing; Xue, Lingzhou; Zou, Hui

    2014-06-01

    Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.

  12. Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

    CERN Document Server

    Blacknell, David

    2013-01-01

    The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

  13. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2010-01-01

    Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face

  14. Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate.

    Science.gov (United States)

    Krivov, Sergei V

    2018-06-06

    Recent advances in simulation and experiment have led to dramatic increases in the quantity and complexity of produced data, which makes the development of automated analysis tools very important. A powerful approach to analyze dynamics contained in such data sets is to describe/approximate it by diffusion on a free energy landscape - free energy as a function of reaction coordinates (RC). For the description to be quantitatively accurate, RCs should be chosen in an optimal way. Recent theoretical results show that such an optimal RC exists; however, determining it for practical systems is a very difficult unsolved problem. Here we describe a solution to this problem. We describe an adaptive nonparametric approach to accurately determine the optimal RC (the committor) for an equilibrium trajectory of a realistic system. In contrast to alternative approaches, which require a functional form with many parameters to approximate an RC and thus extensive expertise with the system, the suggested approach is nonparametric and can approximate any RC with high accuracy without system specific information. To avoid overfitting for a realistically sampled system, the approach performs RC optimization in an adaptive manner by focusing optimization on less optimized spatiotemporal regions of the RC. The power of the approach is illustrated on a long equilibrium atomistic folding simulation of HP35 protein. We have determined the optimal folding RC - the committor, which was confirmed by passing a stringent committor validation test. It allowed us to determine a first quantitatively accurate protein folding free energy landscape. We have confirmed the recent theoretical results that diffusion on such a free energy profile can be used to compute exactly the equilibrium flux, the mean first passage times, and the mean transition path times between any two points on the profile. We have shown that the mean squared displacement along the optimal RC grows linear with time as for

  15. Probabilistic Open Set Recognition

    Science.gov (United States)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  16. Markov Models for Handwriting Recognition

    CERN Document Server

    Plotz, Thomas

    2011-01-01

    Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

  17. Accessing Specific Peptide Recognition by Combinatorial Chemistry

    DEFF Research Database (Denmark)

    Li, Ming

    Molecular recognition is at the basis of all processes for life, and plays a central role in many biological processes, such as protein folding, the structural organization of cells and organelles, signal transduction, and the immune response. Hence, my PhD project is entitled “Accessing Specific...... Peptide Recognition by Combinatorial Chemistry”. Molecular recognition is a specific interaction between two or more molecules through noncovalent bonding, such as hydrogen bonding, metal coordination, van der Waals forces, π−π, hydrophobic, or electrostatic interactions. The association involves kinetic....... Combinatorial chemistry was invented in 1980s based on observation of functional aspects of the adaptive immune system. It was employed for drug development and optimization in conjunction with high-throughput synthesis and screening. (chapter 2) Combinatorial chemistry is able to rapidly produce many thousands...

  18. Bio-recognitive photonics of a DNA-guided organic semiconductor

    Science.gov (United States)

    Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

    2016-01-01

    Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

  19. Bio-recognitive photonics of a DNA-guided organic semiconductor.

    Science.gov (United States)

    Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

    2016-01-04

    Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

  20. A Survey on Sentiment Classification in Face Recognition

    Science.gov (United States)

    Qian, Jingyu

    2018-01-01

    Face recognition has been an important topic for both industry and academia for a long time. K-means clustering, autoencoder, and convolutional neural network, each representing a design idea for face recognition method, are three popular algorithms to deal with face recognition problems. It is worthwhile to summarize and compare these three different algorithms. This paper will focus on one specific face recognition problem-sentiment classification from images. Three different algorithms for sentiment classification problems will be summarized, including k-means clustering, autoencoder, and convolutional neural network. An experiment with the application of these algorithms on a specific dataset of human faces will be conducted to illustrate how these algorithms are applied and their accuracy. Finally, the three algorithms are compared based on the accuracy result.

  1. The Pandora software development kit for pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, J.S.; Thomson, M.A. [University of Cambridge, Cavendish Laboratory, Cambridge (United Kingdom)

    2015-09-15

    The development of automated solutions to pattern recognition problems is important in many areas of scientific research and human endeavour. This paper describes the implementation of the Pandora software development kit, which aids the process of designing, implementing and running pattern recognition algorithms. The Pandora Application Programming Interfaces ensure simple specification of the building-blocks defining a pattern recognition problem. The logic required to solve the problem is implemented in algorithms. The algorithms request operations to create or modify data structures and the operations are performed by the Pandora framework. This design promotes an approach using many decoupled algorithms, each addressing specific topologies. Details of algorithms addressing two pattern recognition problems in High Energy Physics are presented: reconstruction of events at a high-energy e{sup +}e{sup -} linear collider and reconstruction of cosmic ray or neutrino events in a liquid argon time projection chamber. (orig.)

  2. The classification problem in machine learning: an overview with study cases in emotion recognition and music-speech differentiation

    OpenAIRE

    Rodríguez Cadavid, Santiago

    2015-01-01

    This work addresses the well-known classification problem in machine learning -- The goal of this study is to approach the reader to the methodological aspects of the feature extraction, feature selection and classifier performance through simple and understandable theoretical aspects and two study cases -- Finally, a very good classification performance was obtained for the emotion recognition from speech

  3. Active exploration and keypoint clustering for object recognition

    NARCIS (Netherlands)

    Kootstra, G.W.; Ypma, J; de Boer, B.

    2008-01-01

    Object recognition is a challenging problem for artificial systems. This is especially true for objects that are placed in cluttered and uncontrolled environments. To challenge this problem, we discuss an active approach to object recognition. Instead of passively observing objects, we use a robot

  4. A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor.

    Science.gov (United States)

    Park, Young Ho; Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

    2015-06-15

    An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM). Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line) sensor instead of a conventional two-dimensional (area) sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD) images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.

  5. A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor

    Directory of Open Access Journals (Sweden)

    Young Ho Park

    2015-06-01

    Full Text Available An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM. Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line sensor instead of a conventional two-dimensional (area sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.

  6. Solitons and protein folding: An In Silico experiment

    Energy Technology Data Exchange (ETDEWEB)

    Ilieva, N., E-mail: nevena.ilieva@parallel.bas.bg [Institute of Information and Communication Technologies, Bulgarian Aacademy of Sciences, Sofia (Bulgaria); Dai, J., E-mail: daijing491@gmail.com [School of Physics, Beijing Institute of Technology, Beijing (China); Sieradzan, A., E-mail: adams86@wp.pl [Faculty of Chemistry, University of Gdańsk, Gdańsk (Poland); Niemi, A., E-mail: Antti.Niemi@physics.uu.se [Department of Physics and Astronomy, Uppsala University, Uppsala (Sweden); LMPT–CNRS, Université de Tours, Tours (France)

    2015-10-28

    Protein folding [1] is the process of formation of a functional 3D structure from a random coil — the shape in which amino-acid chains leave the ribosome. Anfinsen’s dogma states that the native 3D shape of a protein is completely determined by protein’s amino acid sequence. Despite the progress in understanding the process rate and the success in folding prediction for some small proteins, with presently available physics-based methods it is not yet possible to reliably deduce the shape of a biologically active protein from its amino acid sequence. The protein-folding problem endures as one of the most important unresolved problems in science; it addresses the origin of life itself. Furthermore, a wrong fold is a common cause for a protein to lose its function or even endanger the living organism. Soliton solutions of a generalized discrete non-linear Schrödinger equation (GDNLSE) obtained from the energy function in terms of bond and torsion angles κ and τ provide a constructive theoretical framework for describing protein folds and folding patterns [2]. Here we study the dynamics of this process by means of molecular-dynamics simulations. The soliton manifestation is the pattern helix–loop–helix in the secondary structure of the protein, which explains the importance of understanding loop formation in helical proteins. We performed in silico experiments for unfolding one subunit of the core structure of gp41 from the HIV envelope glycoprotein (PDB ID: 1AIK [3]) by molecular-dynamics simulations with the MD package GROMACS. We analyzed 80 ns trajectories, obtained with one united-atom and two different all-atom force fields, to justify the side-chain orientation quantification scheme adopted in the studies and to eliminate force-field based artifacts. Our results are compatible with the soliton model of protein folding and provide first insight into soliton-formation dynamics.

  7. Solitons and protein folding: An In Silico experiment

    International Nuclear Information System (INIS)

    Ilieva, N.; Dai, J.; Sieradzan, A.; Niemi, A.

    2015-01-01

    Protein folding [1] is the process of formation of a functional 3D structure from a random coil — the shape in which amino-acid chains leave the ribosome. Anfinsen’s dogma states that the native 3D shape of a protein is completely determined by protein’s amino acid sequence. Despite the progress in understanding the process rate and the success in folding prediction for some small proteins, with presently available physics-based methods it is not yet possible to reliably deduce the shape of a biologically active protein from its amino acid sequence. The protein-folding problem endures as one of the most important unresolved problems in science; it addresses the origin of life itself. Furthermore, a wrong fold is a common cause for a protein to lose its function or even endanger the living organism. Soliton solutions of a generalized discrete non-linear Schrödinger equation (GDNLSE) obtained from the energy function in terms of bond and torsion angles κ and τ provide a constructive theoretical framework for describing protein folds and folding patterns [2]. Here we study the dynamics of this process by means of molecular-dynamics simulations. The soliton manifestation is the pattern helix–loop–helix in the secondary structure of the protein, which explains the importance of understanding loop formation in helical proteins. We performed in silico experiments for unfolding one subunit of the core structure of gp41 from the HIV envelope glycoprotein (PDB ID: 1AIK [3]) by molecular-dynamics simulations with the MD package GROMACS. We analyzed 80 ns trajectories, obtained with one united-atom and two different all-atom force fields, to justify the side-chain orientation quantification scheme adopted in the studies and to eliminate force-field based artifacts. Our results are compatible with the soliton model of protein folding and provide first insight into soliton-formation dynamics

  8. Three-dimensional fingerprint recognition by using convolution neural network

    Science.gov (United States)

    Tian, Qianyu; Gao, Nan; Zhang, Zonghua

    2018-01-01

    With the development of science and technology and the improvement of social information, fingerprint recognition technology has become a hot research direction and been widely applied in many actual fields because of its feasibility and reliability. The traditional two-dimensional (2D) fingerprint recognition method relies on matching feature points. This method is not only time-consuming, but also lost three-dimensional (3D) information of fingerprint, with the fingerprint rotation, scaling, damage and other issues, a serious decline in robustness. To solve these problems, 3D fingerprint has been used to recognize human being. Because it is a new research field, there are still lots of challenging problems in 3D fingerprint recognition. This paper presents a new 3D fingerprint recognition method by using a convolution neural network (CNN). By combining 2D fingerprint and fingerprint depth map into CNN, and then through another CNN feature fusion, the characteristics of the fusion complete 3D fingerprint recognition after classification. This method not only can preserve 3D information of fingerprints, but also solves the problem of CNN input. Moreover, the recognition process is simpler than traditional feature point matching algorithm. 3D fingerprint recognition rate by using CNN is compared with other fingerprint recognition algorithms. The experimental results show that the proposed 3D fingerprint recognition method has good recognition rate and robustness.

  9. Design and simulation of origami structures with smooth folds.

    Science.gov (United States)

    Peraza Hernandez, E A; Hartl, D J; Lagoudas, D C

    2017-04-01

    Origami has enabled new approaches to the fabrication and functionality of multiple structures. Current methods for origami design are restricted to the idealization of folds as creases of zeroth-order geometric continuity. Such an idealization is not proper for origami structures of non-negligible fold thickness or maximum curvature at the folds restricted by material limitations. For such structures, folds are not properly represented as creases but rather as bent regions of higher-order geometric continuity. Such fold regions of arbitrary order of continuity are termed as smooth folds . This paper presents a method for solving the following origami design problem: given a goal shape represented as a polygonal mesh (termed as the goal mesh ), find the geometry of a single planar sheet, its pattern of smooth folds, and the history of folding motion allowing the sheet to approximate the goal mesh. The parametrization of the planar sheet and the constraints that allow for a valid pattern of smooth folds are presented. The method is tested against various goal meshes having diverse geometries. The results show that every determined sheet approximates its corresponding goal mesh in a known folded configuration having fold angles obtained from the geometry of the goal mesh.

  10. Guiding the folding pathway of DNA origami.

    Science.gov (United States)

    Dunn, Katherine E; Dannenberg, Frits; Ouldridge, Thomas E; Kwiatkowska, Marta; Turberfield, Andrew J; Bath, Jonathan

    2015-09-03

    DNA origami is a robust assembly technique that folds a single-stranded DNA template into a target structure by annealing it with hundreds of short 'staple' strands. Its guiding design principle is that the target structure is the single most stable configuration. The folding transition is cooperative and, as in the case of proteins, is governed by information encoded in the polymer sequence. A typical origami folds primarily into the desired shape, but misfolded structures can kinetically trap the system and reduce the yield. Although adjusting assembly conditions or following empirical design rules can improve yield, well-folded origami often need to be separated from misfolded structures. The problem could in principle be avoided if assembly pathway and kinetics were fully understood and then rationally optimized. To this end, here we present a DNA origami system with the unusual property of being able to form a small set of distinguishable and well-folded shapes that represent discrete and approximately degenerate energy minima in a vast folding landscape, thus allowing us to probe the assembly process. The obtained high yield of well-folded origami structures confirms the existence of efficient folding pathways, while the shape distribution provides information about individual trajectories through the folding landscape. We find that, similarly to protein folding, the assembly of DNA origami is highly cooperative; that reversible bond formation is important in recovering from transient misfoldings; and that the early formation of long-range connections can very effectively enforce particular folds. We use these insights to inform the design of the system so as to steer assembly towards desired structures. Expanding the rational design process to include the assembly pathway should thus enable more reproducible synthesis, particularly when targeting more complex structures. We anticipate that this expansion will be essential if DNA origami is to continue its

  11. Self-organization and mismatch tolerance in protein folding: General theory and an application

    Science.gov (United States)

    Fernández, Ariel; Berry, R. Stephen

    2000-03-01

    The folding of a protein is a process both expeditious and robust. The analysis of this process presented here uses a coarse, discretized representation of the evolving form of the backbone chain, based on its torsional states. This coarse description consists of discretizing the torsional coordinates modulo the Ramachandran basins in the local softmode dynamics. Whenever the representation exhibits "contact patterns" that correspond to topological compatibilities with particular structural forms, secondary and then tertiary, the elements constituting the pattern are effectively entrained by a reduction of their rates of exploration of their discretized configuration space. The properties "expeditious and robust" imply that the folding protein must have some tolerance to both torsional "frustrated" and side-chain contact mismatches which may occur during the folding process. The energy-entropy consequences of the staircase or funnel topography of the potential surface should allow the folding protein to correct these mismatches, eventually. This tolerance lends itself to an iterative pattern-recognition-and-feedback description of the folding process that reflects mismatched local torsional states and hydrophobic/polar contacts. The predictive potential of our algorithm is tested by application to the folding of bovine pancreatic trypsin inhibitor (BPTI), a protein whose ability to form its active structure is contingent upon its frustration tolerance.

  12. A numerical strategy for finite element modeling of frictionless asymmetric vocal fold collision.

    Science.gov (United States)

    Granados, Alba; Misztal, Marek Krzysztof; Brunskog, Jonas; Visseq, Vincent; Erleben, Kenny

    2017-02-01

    Analysis of voice pathologies may require vocal fold models that include relevant features such as vocal fold asymmetric collision. The present study numerically addresses the problem of frictionless asymmetric collision in a self-sustained three-dimensional continuum model of the vocal folds. Theoretical background and numerical analysis of the finite-element position-based contact model are presented, along with validation. A novel contact detection mechanism capable to detect collision in asymmetric oscillations is developed. The effect of inexact contact constraint enforcement on vocal fold dynamics is examined by different variational methods for inequality constrained minimization problems, namely, the Lagrange multiplier method and the penalty method. In contrast to the penalty solution, which is related to classical spring-like contact forces, numerical examples show that the parameter-independent Lagrange multiplier solution is more robust and accurate in the estimation of dynamical and mechanical features at vocal fold contact. Furthermore, special attention is paid to the temporal integration schemes in relation to the contact problem, the results suggesting an advantage of highly diffusive schemes. Finally, vocal fold contact enforcement is shown to affect asymmetric oscillations. The present model may be adapted to existing vocal fold models, which may contribute to a better understanding of the effect of the nonlinear contact phenomenon on phonation. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  13. Assessment of thyroplasty for vocal fold paralysis

    DEFF Research Database (Denmark)

    Grøntved, Ågot Møller; Faber, Christian; Jakobsen, John

    2009-01-01

    INTRODUCTION: Thyroplasty with silicone rubber implantation is a surgical procedure for treatment of patients with vocal fold paralysis. The aim of the present study was to evaluate the outcome of the operation and to monitor which of the analyses were the more beneficial. MATERIAL AND METHODS...... because it offers a quantitative measure of the voice capacity and intensity, which are the major problems experienced by patients with vocal fold paralysis. Used together, these tools are highly instrumental in guiding the patient's choice of surgery or no surgery. Udgivelsesdato: 2009-Jan-12...

  14. Dual Recognition of Human Telomeric G-quadruplex by Neomycin-anthraquinone Conjugate

    Science.gov (United States)

    Ranjan, Nihar; Davis, Erik; Xue, Liang

    2013-01-01

    The authors report the recognition of a G-quadruplex formed by four repeat human telomeric DNA with aminosugar intercalator conjugates. The recognition of G-quadruplex through dual binding mode ligands significantly increased the affinity of ligands for G-quadruplex. One such example is a neomycin-anthraquinone 2 which exhibited nanomolar affinity for the quadruplex, and the affinity of 2 is nearly 1000 fold higher for human telomeric G-quadruplex DNA than its constituent units, neomycin and anthraquinone. PMID:23698792

  15. Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

    Science.gov (United States)

    Muto, Yutaka; Yokoyama, Shigeyuki

    2012-01-01

    'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.

  16. On speech recognition during anaesthesia

    DEFF Research Database (Denmark)

    Alapetite, Alexandre

    2007-01-01

    This PhD thesis in human-computer interfaces (informatics) studies the case of the anaesthesia record used during medical operations and the possibility to supplement it with speech recognition facilities. Problems and limitations have been identified with the traditional paper-based anaesthesia...... and inaccuracies in the anaesthesia record. Supplementing the electronic anaesthesia record interface with speech input facilities is proposed as one possible solution to a part of the problem. The testing of the various hypotheses has involved the development of a prototype of an electronic anaesthesia record...... interface with speech input facilities in Danish. The evaluation of the new interface was carried out in a full-scale anaesthesia simulator. This has been complemented by laboratory experiments on several aspects of speech recognition for this type of use, e.g. the effects of noise on speech recognition...

  17. Mexican sign language recognition using normalized moments and artificial neural networks

    Science.gov (United States)

    Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

    2014-09-01

    This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

  18. A Markov Random Field Groupwise Registration Framework for Face Recognition.

    Science.gov (United States)

    Liao, Shu; Shen, Dinggang; Chung, Albert C S

    2014-04-01

    In this paper, we propose a new framework for tackling face recognition problem. The face recognition problem is formulated as groupwise deformable image registration and feature matching problem. The main contributions of the proposed method lie in the following aspects: (1) Each pixel in a facial image is represented by an anatomical signature obtained from its corresponding most salient scale local region determined by the survival exponential entropy (SEE) information theoretic measure. (2) Based on the anatomical signature calculated from each pixel, a novel Markov random field based groupwise registration framework is proposed to formulate the face recognition problem as a feature guided deformable image registration problem. The similarity between different facial images are measured on the nonlinear Riemannian manifold based on the deformable transformations. (3) The proposed method does not suffer from the generalizability problem which exists commonly in learning based algorithms. The proposed method has been extensively evaluated on four publicly available databases: FERET, CAS-PEAL-R1, FRGC ver 2.0, and the LFW. It is also compared with several state-of-the-art face recognition approaches, and experimental results demonstrate that the proposed method consistently achieves the highest recognition rates among all the methods under comparison.

  19. Flips for 3-folds and 4-folds

    CERN Document Server

    Corti, Alessio

    2007-01-01

    This edited collection of chapters, authored by leading experts, provides a complete and essentially self-contained construction of 3-fold and 4-fold klt flips. A large part of the text is a digest of Shokurov's work in the field and a concise, complete and pedagogical proof of the existence of 3-fold flips is presented. The text includes a ten page glossary and is accessible to students and researchers in algebraic geometry.

  20. Is emotion recognition the only problem in ADHD? effects of pharmacotherapy on face and emotion recognition in children with ADHD.

    Science.gov (United States)

    Demirci, Esra; Erdogan, Ayten

    2016-12-01

    The objectives of this study were to evaluate both face and emotion recognition, to detect differences among attention deficit and hyperactivity disorder (ADHD) subgroups, to identify effects of the gender and to assess the effects of methylphenidate and atomoxetine treatment on both face and emotion recognition in patients with ADHD. The study sample consisted of 41 male, 29 female patients, 8-15 years of age, who were diagnosed as having combined type ADHD (N = 26), hyperactive/impulsive type ADHD (N = 21) or inattentive type ADHD (N = 23) but had not previously used any medication for ADHD and 35 male, 25 female healthy individuals. Long-acting methylphenidate (OROS-MPH) was prescribed to 38 patients, whereas atomoxetine was prescribed to 32 patients. The reading the mind in the eyes test (RMET) and Benton face recognition test (BFRT) were applied to all participants before and after treatment. The patients with ADHD had a significantly lower number of correct answers in child and adolescent RMET and in BFRT than the healthy controls. Among the ADHD subtypes, the hyperactive/impulsive subtype had a lower number of correct answers in the RMET than the inattentive subtypes, and the hyperactive/impulsive subtype had a lower number of correct answers in short and long form of BFRT than the combined and inattentive subtypes. Male and female patients with ADHD did not differ significantly with respect to the number of correct answers on the RMET and BFRT. The patients showed significant improvement in RMET and BFRT after treatment with OROS-MPH or atomoxetine. Patients with ADHD have difficulties in face recognition as well as emotion recognition. Both OROS-MPH and atomoxetine affect emotion recognition. However, further studies on the face and emotion recognition are needed in ADHD.

  1. Recognition of plant parts with problem-specific algorithms

    Science.gov (United States)

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

    1994-06-01

    Automatic micropropagation is necessary to produce cost-effective high amounts of biomass. Juvenile plants are dissected in clean- room environment on particular points on the stem or the leaves. A vision-system detects possible cutting points and controls a specialized robot. This contribution is directed to the pattern- recognition algorithms to detect structural parts of the plant.

  2. Multiphase Simulated Annealing Based on Boltzmann and Bose-Einstein Distribution Applied to Protein Folding Problem.

    Science.gov (United States)

    Frausto-Solis, Juan; Liñán-García, Ernesto; Sánchez-Hernández, Juan Paulo; González-Barbosa, J Javier; González-Flores, Carlos; Castilla-Valdez, Guadalupe

    2016-01-01

    A new hybrid Multiphase Simulated Annealing Algorithm using Boltzmann and Bose-Einstein distributions (MPSABBE) is proposed. MPSABBE was designed for solving the Protein Folding Problem (PFP) instances. This new approach has four phases: (i) Multiquenching Phase (MQP), (ii) Boltzmann Annealing Phase (BAP), (iii) Bose-Einstein Annealing Phase (BEAP), and (iv) Dynamical Equilibrium Phase (DEP). BAP and BEAP are simulated annealing searching procedures based on Boltzmann and Bose-Einstein distributions, respectively. DEP is also a simulated annealing search procedure, which is applied at the final temperature of the fourth phase, which can be seen as a second Bose-Einstein phase. MQP is a search process that ranges from extremely high to high temperatures, applying a very fast cooling process, and is not very restrictive to accept new solutions. However, BAP and BEAP range from high to low and from low to very low temperatures, respectively. They are more restrictive for accepting new solutions. DEP uses a particular heuristic to detect the stochastic equilibrium by applying a least squares method during its execution. MPSABBE parameters are tuned with an analytical method, which considers the maximal and minimal deterioration of problem instances. MPSABBE was tested with several instances of PFP, showing that the use of both distributions is better than using only the Boltzmann distribution on the classical SA.

  3. A Bayesian classifier for symbol recognition

    OpenAIRE

    Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

    2007-01-01

    URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

  4. Conceptual Transformation and Cognitive Processes in Origami Paper Folding

    Science.gov (United States)

    Tenbrink, Thora; Taylor, Holly A.

    2015-01-01

    Research on problem solving typically does not address tasks that involve following detailed and/or illustrated step-by-step instructions. Such tasks are not seen as cognitively challenging problems to be solved. In this paper, we challenge this assumption by analyzing verbal protocols collected during an Origami folding task. Participants…

  5. Haar-like Features for Robust Real-Time Face Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Face recognition is still a very challenging task when the input face image is noisy, occluded by some obstacles, of very low-resolution, not facing the camera, and not properly illuminated. These problems make the feature extraction and consequently the face recognition system unstable....... The proposed system in this paper introduces the novel idea of using Haar-like features, which have commonly been used for object detection, along with a probabilistic classifier for face recognition. The proposed system is simple, real-time, effective and robust against most of the mentioned problems....... Experimental results on public databases show that the proposed system indeed outperforms the state-of-the-art face recognition systems....

  6. Indonesian Sign Language Number Recognition using SIFT Algorithm

    Science.gov (United States)

    Mahfudi, Isa; Sarosa, Moechammad; Andrie Asmara, Rosa; Azrino Gustalika, M.

    2018-04-01

    Indonesian sign language (ISL) is generally used for deaf individuals and poor people communication in communicating. They use sign language as their primary language which consists of 2 types of action: sign and finger spelling. However, not all people understand their sign language so that this becomes a problem for them to communicate with normal people. this problem also becomes a factor they are isolated feel from the social life. It needs a solution that can help them to be able to interacting with normal people. Many research that offers a variety of methods in solving the problem of sign language recognition based on image processing. SIFT (Scale Invariant Feature Transform) algorithm is one of the methods that can be used to identify an object. SIFT is claimed very resistant to scaling, rotation, illumination and noise. Using SIFT algorithm for Indonesian sign language recognition number result rate recognition to 82% with the use of a total of 100 samples image dataset consisting 50 sample for training data and 50 sample images for testing data. Change threshold value get affect the result of the recognition. The best value threshold is 0.45 with rate recognition of 94%.

  7. How Robust Is the Mechanism of Folding-Upon-Binding for an Intrinsically Disordered Protein?

    Science.gov (United States)

    Bonetti, Daniela; Troilo, Francesca; Brunori, Maurizio; Longhi, Sonia; Gianni, Stefano

    2018-04-24

    The mechanism of interaction of an intrinsically disordered protein (IDP) with its physiological partner is characterized by a disorder-to-order transition in which a recognition and a binding step take place. Even if the mechanism is quite complex, IDPs tend to bind their partner in a cooperative manner such that it is generally possible to detect experimentally only the disordered unbound state and the structured complex. The interaction between the disordered C-terminal domain of the measles virus nucleoprotein (N TAIL ) and the X domain (XD) of the viral phosphoprotein allows us to detect and quantify the two distinct steps of the overall reaction. Here, we analyze the robustness of the folding of N TAIL upon binding to XD by measuring the effect on both the folding and binding steps of N TAIL when the structure of XD is modified. Because it has been shown that wild-type XD is structurally heterogeneous, populating an on-pathway intermediate under native conditions, we investigated the binding to 11 different site-directed variants of N TAIL of one particular variant of XD (I504A XD) that populates only the native state. Data reveal that the recognition and the folding steps are both affected by the structure of XD, indicating a highly malleable pathway. The experimental results are briefly discussed in the light of previous experiments on other IDPs. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  8. Computing the Fréchet distance between folded polygons

    NARCIS (Netherlands)

    Cook IV, A.F.; Driemel, A.; Sherette, J.; Wenk, C.

    2015-01-01

    Computing the Fréchet distance for surfaces is a surprisingly hard problem and the only known polynomial-time algorithm is limited to computing it between flat surfaces. We study the problem of computing the Fréchet distance for a class of non-flat surfaces called folded polygons. We present a

  9. Use of designed sequences in protein structure recognition.

    Science.gov (United States)

    Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

    2018-05-09

    Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

  10. Interpreting whether isoclinal folds are antiforms or synforms using FIA succession

    Science.gov (United States)

    Cao, H.

    2012-12-01

    Using the asymmetries of the overprinting foliations preserved as inclusion trails that define the FIAs to investigate whether an enigmatic isoclinal fold in the region is an antiform or synform. This approach also reveals when the fold first formed during the tectonic history of the region. Multiply deformed and isoclinally folded interlayered high metamorphic grade gneisses and schists can be very difficult rocks for resolving early formed stratigraphic and structural relationships. When such rocks contain porphyroblasts a new approach is possible because of the way in which porphyroblast growth is affected by crenulation versus reactivation of compositional layering (Bell et al., 2003). Isoclinally folded rocks in the Arkansas River region of South Central Colorado contain relics of fold hinges that have been very difficult to ascertain whether they are antiforms or synforms because of younger refolding effects and the locally truncated nature of coarse compositional layering. With the realization that rocks with a schistosity parallel to bedding (S0 parallel S1) have undergone lengthy histories of deformation that predate the obvious first deformation (e.g. Bell et al., 2003; Sayab, 2006; Yeh, 2007) came recognition that large scale regional folds can form early during this process and be preserved throughout orogenesis (e.g., Ham and Bell, 2004; Bell and Newman, 2006. This extensive history is lost within the matrix because of reactivational shear on the compositional layering (Bell et al., 1998, 2003, 2004, 2005; Ham and Bell, 2004). However, it can be extracted by measuring FIAs. Recent work using this approach has revealed that the trends of axial planes of all map scale folds, when plotted on a rose diagram, strikingly reflect the FIA trends (e.g., Sanislav, 2009; Shah, 2009). That is, although it was demonstrated by Bell et al. (2003) that the largest scale regional folds commonly form early in the total history, other folds can form and be preserved from

  11. Paleomagnetic and structural evidence for oblique slip in a fault-related fold, Grayback monocline, Colorado

    Science.gov (United States)

    Tetreault, J.; Jones, C.H.; Erslev, E.; Larson, S.; Hudson, M.; Holdaway, S.

    2008-01-01

    Significant fold-axis-parallel slip is accommodated in the folded strata of the Grayback monocline, northeastern Front Range, Colorado, without visible large strike-slip displacement on the fold surface. In many cases, oblique-slip deformation is partitioned; fold-axis-normal slip is accommodated within folds, and fold-axis-parallel slip is resolved onto adjacent strike-slip faults. Unlike partitioning strike-parallel slip onto adjacent strike-slip faults, fold-axis-parallel slip has deformed the forelimb of the Grayback monocline. Mean compressive paleostress orientations in the forelimb are deflected 15??-37?? clockwise from the regional paleostress orientation of the northeastern Front Range. Paleomagnetic directions from the Permian Ingleside Formation in the forelimb are rotated 16??-42?? clockwise about a bedding-normal axis relative to the North American Permian reference direction. The paleostress and paleomagnetic rotations increase with the bedding dip angle and decrease along strike toward the fold tip. These measurements allow for 50-120 m of fold-axis-parallel slip within the forelimb, depending on the kinematics of strike-slip shear. This resolved horizontal slip is nearly equal in magnitude to the ???180 m vertical throw across the fold. For 200 m of oblique-slip displacement (120 m of strike slip and 180 m of reverse slip), the true shortening direction across the fold is N90??E, indistinguishable from the regionally inferred direction of N90??E and quite different from the S53??E fold-normal direction. Recognition of this deformational style means that significant amounts of strike slip can be accommodated within folds without axis-parallel surficial faulting. ?? 2008 Geological Society of America.

  12. Conformational Selection and Induced Fit for RNA Polymerase and RNA/DNA Hybrid Backtracked Recognition

    Directory of Open Access Journals (Sweden)

    Haifeng eChen

    2015-11-01

    Full Text Available RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15 and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS P test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

  13. Synergistic cooperation of PDI family members in peroxiredoxin 4-driven oxidative protein folding.

    Science.gov (United States)

    Sato, Yoshimi; Kojima, Rieko; Okumura, Masaki; Hagiwara, Masatoshi; Masui, Shoji; Maegawa, Ken-ichi; Saiki, Masatoshi; Horibe, Tomohisa; Suzuki, Mamoru; Inaba, Kenji

    2013-01-01

    The mammalian endoplasmic reticulum (ER) harbors disulfide bond-generating enzymes, including Ero1α and peroxiredoxin 4 (Prx4), and nearly 20 members of the protein disulfide isomerase family (PDIs), which together constitute a suitable environment for oxidative protein folding. Here, we clarified the Prx4 preferential recognition of two PDI family proteins, P5 and ERp46, and the mode of interaction between Prx4 and P5 thioredoxin domain. Detailed analyses of oxidative folding catalyzed by the reconstituted Prx4-PDIs pathways demonstrated that, while P5 and ERp46 are dedicated to rapid, but promiscuous, disulfide introduction, PDI is an efficient proofreader of non-native disulfides. Remarkably, the Prx4-dependent formation of native disulfide bonds was accelerated when PDI was combined with ERp46 or P5, suggesting that PDIs work synergistically to increase the rate and fidelity of oxidative protein folding. Thus, the mammalian ER seems to contain highly systematized oxidative networks for the efficient production of large quantities of secretory proteins.

  14. Improved RGB-D-T based Face Recognition

    DEFF Research Database (Denmark)

    Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

    2016-01-01

    years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

  15. Recognition of secretory proteins in Escherichia coli requires signals in addition to the signal sequence and slow folding

    Directory of Open Access Journals (Sweden)

    Flower Ann M

    2002-11-01

    Full Text Available Abstract Background The Sec-dependent protein export apparatus of Escherichia coli is very efficient at correctly identifying proteins to be exported from the cytoplasm. Even bacterial strains that carry prl mutations, which allow export of signal sequence-defective precursors, accurately differentiate between cytoplasmic and mutant secretory proteins. It was proposed previously that the basis for this precise discrimination is the slow folding rate of secretory proteins, resulting in binding by the secretory chaperone, SecB, and subsequent targeting to translocase. Based on this proposal, we hypothesized that a cytoplasmic protein containing a mutation that slows its rate of folding would be recognized by SecB and therefore targeted to the Sec pathway. In a Prl suppressor strain the mutant protein would be exported to the periplasm due to loss of ability to reject non-secretory proteins from the pathway. Results In the current work, we tested this hypothesis using a mutant form of λ repressor that folds slowly. No export of the mutant protein was observed, even in a prl strain. We then examined binding of the mutant λ repressor to SecB. We did not observe interaction by either of two assays, indicating that slow folding is not sufficient for SecB binding and targeting to translocase. Conclusions These results strongly suggest that to be targeted to the export pathway, secretory proteins contain signals in addition to the canonical signal sequence and the rate of folding.

  16. Dynamic Programming Algorithms in Speech Recognition

    Directory of Open Access Journals (Sweden)

    Titus Felix FURTUNA

    2008-01-01

    Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.

  17. Pose-Invariant Face Recognition via RGB-D Images.

    Science.gov (United States)

    Sang, Gaoli; Li, Jing; Zhao, Qijun

    2016-01-01

    Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.

  18. Mathematical symbol hypothesis recognition with rejection option

    OpenAIRE

    Julca-Aguilar , Frank; Hirata , Nina ,; Viard-Gaudin , Christian; Mouchère , Harold; Medjkoune , Sofiane

    2014-01-01

    International audience; In the context of handwritten mathematical expressions recognition, a first step consist on grouping strokes (segmentation) to form symbol hypotheses: groups of strokes that might represent a symbol. Then, the symbol recognition step needs to cope with the identification of wrong segmented symbols (false hypotheses). However, previous works on symbol recognition consider only correctly segmented symbols. In this work, we focus on the problem of mathematical symbol reco...

  19. Classification and recognition of handwritten digits by using ...

    Indian Academy of Sciences (India)

    The problem of handwriting recognition has been studied for decades and ... tially completed work of character recognition using mathematical morphology. ... There are ten digits in English language and each digit is differentiated from the ...

  20. The effect of surface electrical stimulation on vocal fold position.

    Science.gov (United States)

    Humbert, Ianessa A; Poletto, Christopher J; Saxon, Keith G; Kearney, Pamela R; Ludlow, Christy L

    2008-01-01

    Closure of the true and false vocal folds is a normal part of airway protection during swallowing. Individuals with reduced or delayed true vocal fold closure can be at risk for aspiration and may benefit from intervention to ameliorate the problem. Surface electrical stimulation is currently used during therapy for dysphagia, despite limited knowledge of its physiological effects. Prospective single effects study. The immediate physiological effect of surface stimulation on true vocal fold angle was examined at rest in 27 healthy adults using 10 different electrode placements on the submental and neck regions. Fiberoptic nasolaryngoscopic recordings during passive inspiration were used to measure change in true vocal fold angle with stimulation. Vocal fold angles changed only to a small extent during two electrode placements (P vocal fold abduction was 2.4 degrees; while horizontal placements of electrodes in the submental region produced a mean adduction of 2.8 degrees (P = .03). Surface electrical stimulation to the submental and neck regions does not produce immediate true vocal fold adduction adequate for airway protection during swallowing, and one position may produce a slight increase in true vocal fold opening.

  1. The Main Cognitive Model of Visual Recognition: Contour Recognition

    OpenAIRE

    Chen, YongHong

    2017-01-01

    In this paper, we will study the following pattern recognition problem: Every pattern is a 3-dimensional graph, its surface can be split up into some regions, every region is composed of the pixels with the approximately same colour value and the approximately same depth value that is distance to eyes, and there may also be some contours, e.g., literal contours, on a surface of every pattern. For this problem we reveal the inherent laws. Moreover, we establish a cognitive model to reflect the...

  2. Pattern Recognition as a Human Centered non-Euclidean Problem

    NARCIS (Netherlands)

    Duin, R.P.W.

    2010-01-01

    Regularities in the world are human defined. Patterns in the observed phenomena are there because we define and recognize them as such. Automatic pattern recognition tries to bridge the gap between human judgment and measurements made by artificial sensors. This is done in two steps: representation

  3. Robust Face Recognition by Computing Distances from Multiple Histograms of Oriented Gradients

    NARCIS (Netherlands)

    Karaaba, Mahir; Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

    2015-01-01

    The Single Sample per Person Problem is a challenging problem for face recognition algorithms. Patch-based methods have obtained some promising results for this problem. In this paper, we propose a new face recognition algorithm that is based on a combination of different histograms of oriented

  4. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Souvenir Richard

    2009-01-01

    Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  5. Robust recognition via information theoretic learning

    CERN Document Server

    He, Ran; Yuan, Xiaotong; Wang, Liang

    2014-01-01

    This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

  6. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open......CV library is used for signal processing. We conclude that the approach presented here is a viable solution to pattern recognition problems. Since it requires no network connection, it shows promise in fields such as wildlife research....

  7. View based approach to forensic face recognition

    NARCIS (Netherlands)

    Dutta, A.; van Rootseler, R.T.A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    Face recognition is a challenging problem for surveillance view images commonly encountered in a forensic face recognition case. One approach to deal with a non-frontal test image is to synthesize the corresponding frontal view image and compare it with frontal view reference images. However, it is

  8. Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments

    DEFF Research Database (Denmark)

    Seemann, Ernst Stefan; Gorodkin, Jan; Backofen, Rolf

    2008-01-01

    Computational methods for determining the secondary structure of RNA sequences from given alignments are currently either based on thermodynamic folding, compensatory base pair substitutions or both. However, there is currently no approach that combines both sources of information in a single...... the corresponding probability of being single stranded. Furthermore, we found that structurally conserved RNA motifs are mostly supported by folding energies. Other problems (e.g. RNA-folding kinetics) may also benefit from employing the principles of the model we introduce. Our implementation, PETfold, was tested...

  9. Hybrid gesture recognition system for short-range use

    Science.gov (United States)

    Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun

    2012-03-01

    In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.

  10. Iris recognition in the presence of ocular disease.

    Science.gov (United States)

    Aslam, Tariq Mehmood; Tan, Shi Zhuan; Dhillon, Baljean

    2009-05-06

    Iris recognition systems are among the most accurate of all biometric technologies with immense potential for use in worldwide security applications. This study examined the effect of eye pathology on iris recognition and in particular whether eye disease could cause iris recognition systems to fail. The experiment involved a prospective cohort of 54 patients with anterior segment eye disease who were seen at the acute referral unit of the Princess Alexandra Eye Pavilion in Edinburgh. Iris camera images were obtained from patients before treatment was commenced and again at follow-up appointments after treatment had been given. The principal outcome measure was that of mathematical difference in the iris recognition templates obtained from patients' eyes before and after treatment of the eye disease. Results showed that the performance of iris recognition was remarkably resilient to most ophthalmic disease states, including corneal oedema, iridotomies (laser puncture of iris) and conjunctivitis. Problems were, however, encountered in some patients with acute inflammation of the iris (iritis/anterior uveitis). The effects of a subject developing anterior uveitis may cause current recognition systems to fail. Those developing and deploying iris recognition should be aware of the potential problems that this could cause to this key biometric technology.

  11. Learned image representations for visual recognition

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo

    This thesis addresses the problem of extracting image structures for representing images effectively in order to solve visual recognition tasks. Problems from diverse research areas (medical imaging, material science and food processing) have motivated large parts of the methodological development...

  12. Regression-based Multi-View Facial Expression Recognition

    NARCIS (Netherlands)

    Rudovic, Ognjen; Patras, Ioannis; Pantic, Maja

    2010-01-01

    We present a regression-based scheme for multi-view facial expression recognition based on 2蚠D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a

  13. Modeling and imaging of the vocal fold vibration for voice health

    DEFF Research Database (Denmark)

    Granados, Alba

    Identication of abnormalities on the vocal fold by means of dierent diagnostic methods is a key step to determine the cause or causes of a voice disorder, and subsequently give an adequate treatment. To this end, clinical investigations benet from accurate mathematical models for prediction......, analysis and inference. This thesis deals with biomechanical models of the vocal fold, specially of the collision, and laryngeal videoendoscopic analysis procedures suitable for the inference of the underlying vocal fold characteristics. The rst part of this research is devoted to frictionless contact...... modeling during asymmetric vocal fold vibration. The prediction problem is numerically addressed with a self-sustained three-dimensional nite element model of the vocal fold with position-based contact constraints. A novel contact detection mechanism is shown to successfully detect collision in asymmetric...

  14. Gait recognition based on integral outline

    Science.gov (United States)

    Ming, Guan; Fang, Lv

    2017-02-01

    Biometric identification technology replaces traditional security technology, which has become a trend, and gait recognition also has become a hot spot of research because its feature is difficult to imitate and theft. This paper presents a gait recognition system based on integral outline of human body. The system has three important aspects: the preprocessing of gait image, feature extraction and classification. Finally, using a method of polling to evaluate the performance of the system, and summarizing the problems existing in the gait recognition and the direction of development in the future.

  15. Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

    Science.gov (United States)

    Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

    2018-06-01

    The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

  16. State Decision-Makers Guide for Hazardous Waste Management: Defining Hazardous Wastes, Problem Recognition, Land Use, Facility Operations, Conceptual Framework, Policy Issues, Transportation.

    Science.gov (United States)

    Corson, Alan; And Others

    Presented are key issues to be addressed by state, regional, and local governments and agencies in creating effective hazardous waste management programs. Eight chapters broadly frame the topics which state-level decision makers should consider. These chapters include: (1) definition of hazardous waste; (2) problem definition and recognition; (3)…

  17. Stretched versus compressed exponential kinetics in α-helix folding

    International Nuclear Information System (INIS)

    Hamm, Peter; Helbing, Jan; Bredenbeck, Jens

    2006-01-01

    In a recent paper (J. Bredenbeck, J. Helbing, J.R. Kumita, G.A. Woolley, P. Hamm, α-helix formation in a photoswitchable peptide tracked from picoseconds to microseconds by time resolved IR spectroscopy, Proc. Natl. Acad. Sci USA 102 (2005) 2379), we have investigated the folding of a photo-switchable α-helix with a kinetics that could be fit by a stretched exponential function exp(-(t/τ) β ). The stretching factor β became smaller as the temperature was lowered, a result which has been interpreted in terms of activated diffusion on a rugged energy surface. In the present paper, we discuss under which conditions diffusion problems occur with stretched exponential kinetics (β 1). We show that diffusion problems do have a strong tendency to yield stretched exponential kinetics, yet, that there are conditions (strong perturbation from equilibrium, performing the experiment in the folding direction) under which compressed exponential kinetics would be expected instead. We discuss the kinetics on free energy surfaces predicted by simple initiation-propagation models (zipper models) of α-helix folding, as well as by folding funnel models. We show that our recent experiment has been performed under condition for which models with strong downhill driving force, such as the zipper model, would predict compressed, rather than stretched exponential kinetics, in disagreement with the experimental observation. We therefore propose that the free energy surface along a reaction coordinate that governs the folding kinetics must be relatively flat and has a shape similar to a 1D golf course. We discuss how this conclusion can be unified with the thermodynamically well established zipper model by introducing an additional kinetic reaction coordinate

  18. Protein folding simulations by generalized-ensemble algorithms.

    Science.gov (United States)

    Yoda, Takao; Sugita, Yuji; Okamoto, Yuko

    2014-01-01

    In the protein folding problem, conventional simulations in physical statistical mechanical ensembles, such as the canonical ensemble with fixed temperature, face a great difficulty. This is because there exist a huge number of local-minimum-energy states in the system and the conventional simulations tend to get trapped in these states, giving wrong results. Generalized-ensemble algorithms are based on artificial unphysical ensembles and overcome the above difficulty by performing random walks in potential energy, volume, and other physical quantities or their corresponding conjugate parameters such as temperature, pressure, etc. The advantage of generalized-ensemble simulations lies in the fact that they not only avoid getting trapped in states of energy local minima but also allows the calculations of physical quantities as functions of temperature or other parameters from a single simulation run. In this article we review the generalized-ensemble algorithms. Four examples, multicanonical algorithm, replica-exchange method, replica-exchange multicanonical algorithm, and multicanonical replica-exchange method, are described in detail. Examples of their applications to the protein folding problem are presented.

  19. Gender recognition from vocal source

    Science.gov (United States)

    Sorokin, V. N.; Makarov, I. S.

    2008-07-01

    Efficiency of automatic recognition of male and female voices based on solving the inverse problem for glottis area dynamics and for waveform of the glottal airflow volume velocity pulse is studied. The inverse problem is regularized through the use of analytical models of the voice excitation pulse and of the dynamics of the glottis area, as well as the model of one-dimensional glottal airflow. Parameters of these models and spectral parameters of the volume velocity pulse are considered. The following parameters are found to be most promising: the instant of maximum glottis area, the maximum derivative of the area, the slope of the spectrum of the glottal airflow volume velocity pulse, the amplitude ratios of harmonics of this spectrum, and the pitch. On the plane of the first two main components in the space of these parameters, an almost twofold decrease in the classification error relative to that for the pitch alone is attained. The male voice recognition probability is found to be 94.7%, and the female voice recognition probability is 95.9%.

  20. A simple, practical and complete O-time Algorithm for RNA folding using the Four-Russians Speedup

    Directory of Open Access Journals (Sweden)

    Gusfield Dan

    2010-01-01

    Full Text Available Abstract Background The problem of computationally predicting the secondary structure (or folding of RNA molecules was first introduced more than thirty years ago and yet continues to be an area of active research and development. The basic RNA-folding problem of finding a maximum cardinality, non-crossing, matching of complimentary nucleotides in an RNA sequence of length n, has an O(n3-time dynamic programming solution that is widely applied. It is known that an o(n3 worst-case time solution is possible, but the published and suggested methods are complex and have not been established to be practical. Significant practical improvements to the original dynamic programming method have been introduced, but they retain the O(n3 worst-case time bound when n is the only problem-parameter used in the bound. Surprisingly, the most widely-used, general technique to achieve a worst-case (and often practical speed up of dynamic programming, the Four-Russians technique, has not been previously applied to the RNA-folding problem. This is perhaps due to technical issues in adapting the technique to RNA-folding. Results In this paper, we give a simple, complete, and practical Four-Russians algorithm for the basic RNA-folding problem, achieving a worst-case time-bound of O(n3/log(n. Conclusions We show that this time-bound can also be obtained for richer nucleotide matching scoring-schemes, and that the method achieves consistent speed-ups in practice. The contribution is both theoretical and practical, since the basic RNA-folding problem is often solved multiple times in the inner-loop of more complex algorithms, and for long RNA molecules in the study of RNA virus genomes.

  1. Crystal structure and novel recognition motif of rho ADP-ribosylating C3 exoenzyme from Clostridium botulinum: structural insights for recognition specificity and catalysis.

    Science.gov (United States)

    Han, S; Arvai, A S; Clancy, S B; Tainer, J A

    2001-01-05

    Clostridium botulinum C3 exoenzyme inactivates the small GTP-binding protein family Rho by ADP-ribosylating asparagine 41, which depolymerizes the actin cytoskeleton. C3 thus represents a major family of the bacterial toxins that transfer the ADP-ribose moiety of NAD to specific amino acids in acceptor proteins to modify key biological activities in eukaryotic cells, including protein synthesis, differentiation, transformation, and intracellular signaling. The 1.7 A resolution C3 exoenzyme structure establishes the conserved features of the core NAD-binding beta-sandwich fold with other ADP-ribosylating toxins despite little sequence conservation. Importantly, the central core of the C3 exoenzyme structure is distinguished by the absence of an active site loop observed in many other ADP-ribosylating toxins. Unlike the ADP-ribosylating toxins that possess the active site loop near the central core, the C3 exoenzyme replaces the active site loop with an alpha-helix, alpha3. Moreover, structural and sequence similarities with the catalytic domain of vegetative insecticidal protein 2 (VIP2), an actin ADP-ribosyltransferase, unexpectedly implicates two adjacent, protruding turns, which join beta5 and beta6 of the toxin core fold, as a novel recognition specificity motif for this newly defined toxin family. Turn 1 evidently positions the solvent-exposed, aromatic side-chain of Phe209 to interact with the hydrophobic region of Rho adjacent to its GTP-binding site. Turn 2 evidently both places the Gln212 side-chain for hydrogen bonding to recognize Rho Asn41 for nucleophilic attack on the anomeric carbon of NAD ribose and holds the key Glu214 catalytic side-chain in the adjacent catalytic pocket. This proposed bipartite ADP-ribosylating toxin turn-turn (ARTT) motif places the VIP2 and C3 toxin classes into a single ARTT family characterized by analogous target protein recognition via turn 1 aromatic and turn 2 hydrogen-bonding side-chain moieties. Turn 2 centrally anchors

  2. A history of folding in mathematics mathematizing the margins

    CERN Document Server

    Friedman, Michael

    2018-01-01

    While it is well known that the Delian problems are impossible to solve with a straightedge and compass – for example, it is impossible to construct a segment whose length is ∛2 with these instruments – the Italian mathematician Margherita Beloch Piazzolla's discovery in 1934 that one can in fact construct a segment of length ∛2 with a single paper fold was completely ignored (till the end of the 1980s). This comes as no surprise, since with few exceptions paper folding was seldom considered as a mathematical practice, let alone as a mathematical procedure of inference or proof that could prompt novel mathematical discoveries. A few question immediately arise: Why did paper folding become a non-instrument? What caused the marginalisation of this technique? And how was the mathematical knowledge, which was nevertheless transmitted and prompted by paper folding, later treated and conceptualised? Aiming to answer these questions, this volume provides, for the first time, an extensive historical study...

  3. Gesture recognition for smart home applications using portable radar sensors.

    Science.gov (United States)

    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.

  4. Degraded character recognition based on gradient pattern

    Science.gov (United States)

    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.

  5. Applications of evolutionary computation in image processing and pattern recognition

    CERN Document Server

    Cuevas, Erik; Perez-Cisneros, Marco

    2016-01-01

    This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...

  6. Timing of isoclinal folds in multiply deformed high metamorphic grade region using FIA succession

    Science.gov (United States)

    Cao, Hui; Cai, Zhihui

    2013-04-01

    Multiply deformed and isoclinally folded interlayered high metamorphic grade gneisses and schists can be very difficult rocks for resolving early formed stratigraphic and structural relationships. When such rocks contain porphyroblasts a new approach is possible because of the way in which porphyroblast growth is affected by crenulation versus reactivation of compositional layering. The asymmetries of the overprinting foliations preserved as inclusion trails that define the FIAs can be used to investigate whether an enigmatic isoclinal fold is an antiform or synform. This approach also reveals when the fold first formed during the tectonic history of the region. Isoclinally folded rocks in the Arkansas River region of Central Colorado contain relics of fold hinges that have been very difficult to ascertain whether they are antiforms or synforms because of younger refolding effects and the locally truncated nature of coarse compositional layering. With the realization that rocks with a schistosity parallel to bedding (S0 parallel S1) have undergone lengthy histories of deformation that predate the obvious first deformation came recognition that large scale regional folds can form early during this process and be preserved throughout orogenesis. This extensive history is lost within the matrix because of reactivational shear on the compositional layering. However, it can be extracted by measuring FIAs. Recent work using this approach has revealed that the trends of axial planes of all map scale folds, when plotted on a rose diagram, strikingly reflect the FIA trends. That is, although it was demonstrated that the largest scale regional folds commonly form early in the total history, other folds can form and be preserved from subsequent destruction in the strain shadows of plutons or through the partitioning of deformation due to heterogeneities at depth.

  7. Vocal Fold Paralysis

    Science.gov (United States)

    ... here Home » Health Info » Voice, Speech, and Language Vocal Fold Paralysis On this page: What is vocal fold ... Where can I get additional information? What is vocal fold paralysis? Structures involved in speech and voice production ...

  8. Kinetic Dissection of the Pre-existing Conformational Equilibrium in the Trypsin Fold*

    Science.gov (United States)

    Vogt, Austin D.; Chakraborty, Pradipta; Di Cera, Enrico

    2015-01-01

    Structural biology has recently documented the conformational plasticity of the trypsin fold for both the protease and zymogen in terms of a pre-existing equilibrium between closed (E*) and open (E) forms of the active site region. How such plasticity is manifested in solution and affects ligand recognition by the protease and zymogen is poorly understood in quantitative terms. Here we dissect the E*-E equilibrium with stopped-flow kinetics in the presence of excess ligand or macromolecule. Using the clotting protease thrombin and its zymogen precursor prethrombin-2 as relevant models we resolve the relative distribution of the E* and E forms and the underlying kinetic rates for their interconversion. In the case of thrombin, the E* and E forms are distributed in a 1:4 ratio and interconvert on a time scale of 45 ms. In the case of prethrombin-2, the equilibrium is shifted strongly (10:1 ratio) in favor of the closed E* form and unfolds over a faster time scale of 4.5 ms. The distribution of E* and E forms observed for thrombin and prethrombin-2 indicates that zymogen activation is linked to a significant shift in the pre-existing equilibrium between closed and open conformations that facilitates ligand binding to the active site. These findings broaden our mechanistic understanding of how conformational transitions control ligand recognition by thrombin and its zymogen precursor prethrombin-2 and have direct relevance to other members of the trypsin fold. PMID:26216877

  9. Distorted Character Recognition Via An Associative Neural Network

    Science.gov (United States)

    Messner, Richard A.; Szu, Harold H.

    1987-03-01

    The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

  10. Approximate self-similarity in models of geological folding

    NARCIS (Netherlands)

    Budd, C.J.; Peletier, M.A.

    2000-01-01

    We propose a model for the folding of rock under the compression of tectonic plates. This models an elastic rock layer imbedded in a viscous foundation by a fourth-order parabolic equation with a nonlinear constraint. The large-time behavior of solutions of this problem is examined and found to be

  11. Free energy landscape and multiple folding pathways of an H-type RNA pseudoknot.

    Directory of Open Access Journals (Sweden)

    Yunqiang Bian

    Full Text Available How RNA sequences fold to specific tertiary structures is one of the key problems for understanding their dynamics and functions. Here, we study the folding process of an H-type RNA pseudoknot by performing a large-scale all-atom MD simulation and bias-exchange metadynamics. The folding free energy landscapes are obtained and several folding intermediates are identified. It is suggested that the folding occurs via multiple mechanisms, including a step-wise mechanism starting either from the first helix or the second, and a cooperative mechanism with both helices forming simultaneously. Despite of the multiple mechanism nature, the ensemble folding kinetics estimated from a Markov state model is single-exponential. It is also found that the correlation between folding and binding of metal ions is significant, and the bound ions mediate long-range interactions in the intermediate structures. Non-native interactions are found to be dominant in the unfolded state and also present in some intermediates, possibly hinder the folding process of the RNA.

  12. Problems with a False Recognition Paradigm for Developmental Memory Research

    Science.gov (United States)

    Lindauer, Barbara K.; Paris, Scott G.

    1976-01-01

    Developmental changes in memory organization based on synonym and antonym relationships were examined in three experiments. Subjects were 64 second graders and 64 sixth graders. Some inadequacies of a false recognition paradigm for developmental research are identified and some alternative analyses are proposed. (Author/JH)

  13. Preventive maintenance. 'Problem recognition style' can be used to segment the market and promote healthier lifestyles.

    Science.gov (United States)

    Jayanti, R K

    1997-01-01

    Problem recognition styles--desired state types (DSTs) and actual state types (ASTs)--have an effect on preventive health care decision making. Segmenting the market along these lines can help marketers position products and services to educate and attract people who will not see a doctor unless there is something wrong with them. Both groups expect the same benefits from preventive health care actions, but ASTs fail to act on those expectations. Therefore, marketing strategy touting the benefits of preventive health care might be futile. Educational promotional campaigns aimed at both DSTs and ASTs also are wasteful because DSTs already possess much health knowledge, lead wellness-oriented lifestyles, and practice preventive health behaviors.

  14. Recognition of fractal graphs

    NARCIS (Netherlands)

    Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM

    1999-01-01

    Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems

  15. Making 2D face recognition more robust using AAMs for pose compensation

    NARCIS (Netherlands)

    Huisman, Peter; Munster, Ruud; Moro-Ellenberger, Stephanie; Veldhuis, Raymond N.J.; Bazen, A.M.

    2006-01-01

    The problem of pose in 2D face recognition is widely acknowledged. Commercial systems are limited to near frontal face images and cannot deal with pose deviations larger than 15 degrees from the frontal view. This is a problem, when using face recognition for surveillance applications in which

  16. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  17. Recognition of Face and Emotional Facial Expressions in Autism

    Directory of Open Access Journals (Sweden)

    Muhammed Tayyib Kadak

    2013-03-01

    Full Text Available Autism is a genetically transferred neurodevelopmental disorder characterized by severe and permanent deficits in many interpersonal relation areas like communication, social interaction and emotional responsiveness. Patients with autism have deficits in face recognition, eye contact and recognition of emotional expression. Both recognition of face and expression of facial emotion carried on face processing. Structural and functional impairment in fusiform gyrus, amygdala, superior temporal sulcus and other brain regions lead to deficits in recognition of face and facial emotion. Therefore studies suggest that face processing deficits resulted in problems in areas of social interaction and emotion in autism. Studies revealed that children with autism had problems in recognition of facial expression and used mouth region more than eye region. It was also shown that autistic patients interpreted ambiguous expressions as negative emotion. In autism, deficits related in various stages of face processing like detection of gaze, face identity, recognition of emotional expression were determined, so far. Social interaction impairments in autistic spectrum disorders originated from face processing deficits during the periods of infancy, childhood and adolescence. Recognition of face and expression of facial emotion could be affected either automatically by orienting towards faces after birth, or by “learning” processes in developmental periods such as identity and emotion processing. This article aimed to review neurobiological basis of face processing and recognition of emotional facial expressions during normal development and in autism.

  18. Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition

    KAUST Repository

    Alghamdi, Masheal M.

    2014-01-01

    complications to the face recognition research. Many algorithms are devoted to solving the face recognition problem, among which the family of nonnegative matrix factorization (NMF) algorithms has been widely used as a compact data representation method

  19. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  20. The Roles of recognition processes and look-ahead search in time-constrained expert problem solving: Evidence from grandmaster level chess.

    OpenAIRE

    Gobet, F; Simon, H A

    1996-01-01

    Chess has long served as an important standard task environment for research on human memory and problem-solving abilities and processes. In this paper, we report evidence on the relative importance of recognition processes and planning (look-ahead) processes in very high level expert performance in chess. The data show that the rated skill of a top-level grandmaster is only slightly lower when he is playing simultaneously against a half dozen grandmaster opponents than under tournament con...

  1. Diagnosing plant problems

    Science.gov (United States)

    Cheryl A. Smith

    2008-01-01

    Diagnosing Christmas tree problems can be a challenge, requiring a basic knowledge of plant culture and physiology, the effect of environmental influences on plant health, and the ability to identify the possible causes of plant problems. Developing a solution or remedy to the problem depends on a proper diagnosis, a process that requires recognition of a problem and...

  2. Multi-task pose-invariant face recognition.

    Science.gov (United States)

    Ding, Changxing; Xu, Chang; Tao, Dacheng

    2015-03-01

    Face images captured in unconstrained environments usually contain significant pose variation, which dramatically degrades the performance of algorithms designed to recognize frontal faces. This paper proposes a novel face identification framework capable of handling the full range of pose variations within ±90° of yaw. The proposed framework first transforms the original pose-invariant face recognition problem into a partial frontal face recognition problem. A robust patch-based face representation scheme is then developed to represent the synthesized partial frontal faces. For each patch, a transformation dictionary is learnt under the proposed multi-task learning scheme. The transformation dictionary transforms the features of different poses into a discriminative subspace. Finally, face matching is performed at patch level rather than at the holistic level. Extensive and systematic experimentation on FERET, CMU-PIE, and Multi-PIE databases shows that the proposed method consistently outperforms single-task-based baselines as well as state-of-the-art methods for the pose problem. We further extend the proposed algorithm for the unconstrained face verification problem and achieve top-level performance on the challenging LFW data set.

  3. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    Chao Bi

    Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

  4. Domain Regeneration for Cross-Database Micro-Expression Recognition

    Science.gov (United States)

    Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

    2018-05-01

    In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

  5. Fine-grained recognition of plants from images.

    Science.gov (United States)

    Šulc, Milan; Matas, Jiří

    2017-01-01

    Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition "in the wild". We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition "in the wild". The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition "in the wild" where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

  6. Coupled bias-variance tradeoff for cross-pose face recognition.

    Science.gov (United States)

    Li, Annan; Shan, Shiguang; Gao, Wen

    2012-01-01

    Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

  7. Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

    Science.gov (United States)

    Will, Sebastian; Jabbari, Hosna

    2016-01-01

    RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

  8. Semisupervised kernel marginal Fisher analysis for face recognition.

    Science.gov (United States)

    Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

    2013-01-01

    Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

  9. Recognition and Binding of a Helix-Loop-Helix Peptide to Carbonic Anhydrase Occurs via Partly Folded Intermediate Structures

    Science.gov (United States)

    Lignell, Martin; Becker, Hans-Christian

    2010-01-01

    Abstract We have studied the association of a helix-loop-helix peptide scaffold carrying a benzenesulfonamide ligand to carbonic anhydrase using steady-state and time-resolved fluorescence spectroscopy. The helix-loop-helix peptide, developed for biosensing applications, is labeled with the fluorescent probe dansyl, which serves as a polarity-sensitive reporter of the binding event. Using maximum entropy analysis of the fluorescence lifetime of dansyl at 1:1 stoichiometry reveals three characteristic fluorescence lifetime groups, interpreted as differently interacting peptide/protein structures. We characterize these peptide/protein complexes as mostly bound but unfolded, bound and partly folded, and strongly bound and folded. Furthermore, analysis of the fluorescence anisotropy decay resulted in three different dansyl rotational correlation times, namely 0.18, 1.2, and 23 ns. Using the amplitudes of these times, we can correlate the lifetime groups with the corresponding fluorescence anisotropy component. The 23-ns rotational correlation time, which appears with the same amplitude as a 17-ns fluorescence lifetime, shows that the dansyl fluorophore follows the rotational diffusion of carbonic anhydrase when it is a part of the folded peptide/protein complex. A partly folded and partly hydrated interfacial structure is manifested in an 8-ns dansyl fluorescence lifetime and a 1.2-ns rotational correlation time. This structure, we believe, is similar to a molten-globule-like interfacial structure, which allows segmental movement and has a higher degree of solvent exposure of dansyl. Indirect excitation of dansyl on the helix-loop-helix peptide through Förster energy transfer from one or several tryptophans in the carbonic anhydrase shows that the helix-loop-helix scaffold binds to a tryptophan-rich domain of the carbonic anhydrase. We conclude that binding of the peptide to carbonic anhydrase involves a transition from a disordered to an ordered structure of the

  10. An Agent-mediated Ontology-based Approach for Composite Activity Recognition in Smart Homes

    OpenAIRE

    Okeyo, George; Chen, Liming; Wang, H.

    2013-01-01

    Activity recognition enables ambient assisted living applications to provide activity-aware services to users in smart homes. Despite significant progress being made in activity recognition research, the focus has been on simple activity recognition leaving composite activity recognition an open problem. For instance, knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work by introducing a know...

  11. Multi-thread Parallel Speech Recognition for Mobile Applications

    Directory of Open Access Journals (Sweden)

    LOJKA Martin

    2014-05-01

    Full Text Available In this paper, the server based solution of the multi-thread large vocabulary automatic speech recognition engine is described along with the Android OS and HTML5 practical application examples. The basic idea was to bring speech recognition available for full variety of applications for computers and especially for mobile devices. The speech recognition engine should be independent of commercial products and services (where the dictionary could not be modified. Using of third-party services could be also a security and privacy problem in specific applications, when the unsecured audio data could not be sent to uncontrolled environments (voice data transferred to servers around the globe. Using our experience with speech recognition applications, we have been able to construct a multi-thread speech recognition serverbased solution designed for simple applications interface (API to speech recognition engine modified to specific needs of particular application.

  12. Type-2 fuzzy graphical models for pattern recognition

    CERN Document Server

    Zeng, Jia

    2015-01-01

    This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

  13. 8th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej

    2013-01-01

    The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 86 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics Data Stream Classification and Big Data Analytics  Features, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications Pattern recognition and image processing in robotics  Speech and word recognition This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

  14. Iris Recognition Using Feature Extraction of Box Counting Fractal Dimension

    Science.gov (United States)

    Khotimah, C.; Juniati, D.

    2018-01-01

    Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition consists of three step: pre-processing of data, feature extraction, and feature matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman’s rubber sheet model to normalize the iris data set into rectangular blocks. To find the characteristics of the iris, it was used box counting method to get the fractal dimension value of the iris. Tests carried out by used k-fold cross method with k = 5. In each test used 10 different grade K of K-Nearest Neighbor (KNN). The result of iris recognition was obtained with the best accuracy was 92,63 % for K = 3 value on K-Nearest Neighbor (KNN) method.

  15. Adults' strategies for simple addition and multiplication: verbal self-reports and the operand recognition paradigm.

    Science.gov (United States)

    Metcalfe, Arron W S; Campbell, Jamie I D

    2011-05-01

    Accurate measurement of cognitive strategies is important in diverse areas of psychological research. Strategy self-reports are a common measure, but C. Thevenot, M. Fanget, and M. Fayol (2007) proposed a more objective method to distinguish different strategies in the context of mental arithmetic. In their operand recognition paradigm, speed of recognition memory for problem operands after solving a problem indexes strategy (e.g., direct memory retrieval vs. a procedural strategy). Here, in 2 experiments, operand recognition time was the same following simple addition or multiplication, but, consistent with a wide variety of previous research, strategy reports indicated much greater use of procedures (e.g., counting) for addition than multiplication. Operation, problem size (e.g., 2 + 3 vs. 8 + 9), and operand format (digits vs. words) had interactive effects on reported procedure use that were not reflected in recognition performance. Regression analyses suggested that recognition time was influenced at least as much by the relative difficulty of the preceding problem as by the strategy used. The findings indicate that the operand recognition paradigm is not a reliable substitute for strategy reports and highlight the potential impact of difficulty-related carryover effects in sequential cognitive tasks.

  16. Cross-modal face recognition using multi-matcher face scores

    Science.gov (United States)

    Zheng, Yufeng; Blasch, Erik

    2015-05-01

    The performance of face recognition can be improved using information fusion of multimodal images and/or multiple algorithms. When multimodal face images are available, cross-modal recognition is meaningful for security and surveillance applications. For example, a probe face is a thermal image (especially at nighttime), while only visible face images are available in the gallery database. Matching a thermal probe face onto the visible gallery faces requires crossmodal matching approaches. A few such studies were implemented in facial feature space with medium recognition performance. In this paper, we propose a cross-modal recognition approach, where multimodal faces are cross-matched in feature space and the recognition performance is enhanced with stereo fusion at image, feature and/or score level. In the proposed scenario, there are two cameras for stereo imaging, two face imagers (visible and thermal images) in each camera, and three recognition algorithms (circular Gaussian filter, face pattern byte, linear discriminant analysis). A score vector is formed with three cross-matched face scores from the aforementioned three algorithms. A classifier (e.g., k-nearest neighbor, support vector machine, binomial logical regression [BLR]) is trained then tested with the score vectors by using 10-fold cross validations. The proposed approach was validated with a multispectral stereo face dataset from 105 subjects. Our experiments show very promising results: ACR (accuracy rate) = 97.84%, FAR (false accept rate) = 0.84% when cross-matching the fused thermal faces onto the fused visible faces by using three face scores and the BLR classifier.

  17. Iris recognition based on robust principal component analysis

    Science.gov (United States)

    Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

    2014-11-01

    Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

  18. Simultaneous tracking and activity recognition

    DEFF Research Database (Denmark)

    Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

    2011-01-01

    be used to improve the prediction step of the tracking, while, at the same time, tracking information can be used for online activity recognition. Experimental results in two different settings show that our approach 1) decreases the error rate and improves the identity maintenance of the positional......Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...... tracking and 2) identifies the correct activity with higher accuracy than standard approaches....

  19. ETIOLOGICAL FACTORS FOR VOCAL FOLD POLYP FORMATION

    Directory of Open Access Journals (Sweden)

    DAŠA GLUVAJIĆ

    2016-05-01

    Full Text Available Background: Vocal fold polyp is one of the most common causes for hoarseness. Many different etiological factors contribute to vocal fold polyp formation. The aim of the study was to find out whether the etiological factors for polyp formation have changed in the last 30 years.Methods: Eighty-one patients with unilateral vocal fold polyp were included in the study. A control group was composed of 50 volunteers without voice problems who matched the patients by age and gender. The data about etiological factors and the findings of phoniatric examination were obtained from the patients' medical documentation and from the questionnaires for the control group. The incidence of etiological factors was compared between the two groups. The program SPSS, Version 18 was used for statistical analysis.Results: The most frequent etiological factors were occupational voice load, GER, allergy and smoking. In 79% of patients 2 – 6 contemporary acting risk factors were found. Occupational voice load (p=0,018 and GER (p=0,004 were significantly more frequent in the patients than in the controls. The other factors did not significantly influence the polyp formation.Conclusions: There are several factors involved simultaneously in the formation of vocal fold polyps both nowadays and 30 years ago. Some of the most common factors remain the same (voice load, smoking, others are new (GER, allergy, which is probably due to the different lifestyle and working conditions than 30 years ago. Occupational voice load and GER were significantly more frequently present in the patients with polyp than in the control group. Regarding the given results it is important to instruct workers with professional vocal load about etiological factors for vocal fold polyp formation.

  20. Fold maps and positive topological quantum field theories

    Energy Technology Data Exchange (ETDEWEB)

    Wrazidlo, Dominik Johannes

    2017-04-12

    The notion of positive TFT as coined by Banagl is specified by an axiomatic system based on Atiyah's original axioms for TFTs. By virtue of a general framework that is based on the concept of Eilenberg completeness of semirings from computer science, a positive TFT can be produced rigorously via quantization of systems of fields and action functionals - a process inspired by Feynman's path integral from classical quantum field theory. The purpose of the present dissertation thesis is to investigate a new differential topological invariant for smooth manifolds that arises as the state sum of the fold map TFT, which has been constructed by Banagl as a example of a positive TFT. By eliminating an internal technical assumption on the fields of the fold map TFT, we are able to express the informational content of the state sum in terms of an extension problem for fold maps from cobordisms into the plane. Next, we use the general theory of generic smooth maps into the plane to improve known results about the structure of the state sum in arbitrary dimensions, and to determine it completely in dimension two. The aggregate invariant of a homotopy sphere, which is derived from the state sum, naturally leads us to define a filtration of the group of homotopy spheres in order to understand the role of indefinite fold lines beyond a theorem of Saeki. As an application, we show how Kervaire spheres can be characterized by indefinite fold lines in certain dimensions.

  1. Several Similarity Measures of Interval Valued Neutrosophic Soft Sets and Their Application in Pattern Recognition Problems

    Directory of Open Access Journals (Sweden)

    Anjan Mukherjee

    2014-12-01

    Full Text Available Interval valued neutrosophic soft set introduced by Irfan Deli in 2014[8] is a generalization of neutrosophic set introduced by F. Smarandache in 1995[19], which can be used in real scientific and engineering applications. In this paper the Hamming and Euclidean distances between two interval valued neutrosophic soft sets (IVNS sets are defined and similarity measures based on distances between two interval valued neutrosophic soft sets are proposed. Similarity measure based on set theoretic approach is also proposed. Some basic properties of similarity measures between two interval valued neutrosophic soft sets is also studied. A decision making method is established for interval valued neutrosophic soft set setting using similarity measures between IVNS sets. Finally an example is given to demonstrate the possible application of similarity measures in pattern recognition problems.

  2. Innate recognition of bacteria in human milk is mediated by a milk-derived highly expressed pattern recognition receptor, soluble CD14.

    OpenAIRE

    Lab?ta, MO; Vidal, K; Nores, JE; Arias, M; Vita, N; Morgan, BP; Guillemot, JC; Loyaux, D; Ferrara, P; Schmid, D; Affolter, M; Borysiewicz, LK; Donnet-Hughes, A; Schiffrin, EJ

    2000-01-01

    Little is known about innate immunity to bacteria after birth in the hitherto sterile fetal intestine. Breast-feeding has long been associated with a lower incidence of gastrointestinal infections and inflammatory and allergic diseases. We found in human breast milk a 48-kD polypeptide, which we confirmed by mass spectrometry and sequencing to be a soluble form of the bacterial pattern recognition receptor CD14 (sCD14). Milk sCD14 (m-sCD14) concentrations were up to 20-fold higher than serum ...

  3. Innate Recognition of Bacteria in Human Milk Is Mediated by a Milk-Derived Highly Expressed Pattern Recognition Receptor, Soluble Cd14

    OpenAIRE

    Labéta, Mario O.; Vidal, Karine; Nores, Julia E. Rey; Arias, Mauricio; Vita, Natalio; Morgan, B. Paul; Guillemot, Jean Claude; Loyaux, Denis; Ferrara, Pascual; Schmid, Daniel; Affolter, Michael; Borysiewicz, Leszek K.; Donnet-Hughes, Anne; Schiffrin, Eduardo J.

    2000-01-01

    Little is known about innate immunity to bacteria after birth in the hitherto sterile fetal intestine. Breast-feeding has long been associated with a lower incidence of gastrointestinal infections and inflammatory and allergic diseases. We found in human breast milk a 48-kD polypeptide, which we confirmed by mass spectrometry and sequencing to be a soluble form of the bacterial pattern recognition receptor CD14 (sCD14). Milk sCD14 (m-sCD14) concentrations were up to 20-fold higher than serum ...

  4. Enhancing emotion recognition in VIPs with haptic feedback

    NARCIS (Netherlands)

    Buimer, Hendrik; Bittner, Marian; Kostelijk, Tjerk; van der Geest, Thea; van Wezel, Richard Jack Anton; Zhao, Yan; Stephanidis, Constantine

    2016-01-01

    The rise of smart technologies has created new opportunities to support blind and visually impaired persons (VIPs). One of the biggest problems we identified in our previous research on problems VIPs face during activities of daily life concerned the recognition of persons and their facial

  5. Protein folding and protein metallocluster studies using synchrotron small angler X-ray scattering

    International Nuclear Information System (INIS)

    Eliezer, D.

    1994-06-01

    Proteins, biological macromolecules composed of amino-acid building blocks, possess unique three dimensional shapes or conformations which are intimately related to their biological function. All of the information necessary to determine this conformation is stored in a protein's amino acid sequence. The problem of understanding the process by which nature maps protein amino-acid sequences to three-dimensional conformations is known as the protein folding problem, and is one of the central unsolved problems in biophysics today. The possible applications of a solution are broad, ranging from the elucidation of thousands of protein structures to the rational modification and design of protein-based drugs. The scattering of X-rays by matter has long been useful as a tool for the characterization of physical properties of materials, including biological samples. The high photon flux available at synchrotron X-ray sources allows for the measurement of scattering cross-sections of dilute and/or disordered samples. Such measurements do not yield the detailed geometrical information available from crystalline samples, but do allow for lower resolution studies of dynamical processes not observable in the crystalline state. The main focus of the work described here has been the study of the protein folding process using time-resolved small-angle x-ray scattering measurements. The original intention was to observe the decrease in overall size which must accompany the folding of a protein from an extended conformation to its compact native state. Although this process proved too fast for the current time-resolution of the technique, upper bounds were set on the probable compaction times of several small proteins. In addition, an interesting and unexpected process was detected, in which the folding protein passes through an intermediate state which shows a tendency to associate. This state is proposed to be a kinetic molten globule folding intermediate

  6. A simple, practical and complete O(n3/log n)-time algorithm for RNA folding using the Four-Russians speedup.

    Science.gov (United States)

    Frid, Yelena; Gusfield, Dan

    2010-01-04

    The problem of computationally predicting the secondary structure (or folding) of RNA molecules was first introduced more than thirty years ago and yet continues to be an area of active research and development. The basic RNA-folding problem of finding a maximum cardinality, non-crossing, matching of complimentary nucleotides in an RNA sequence of length n, has an O(n3)-time dynamic programming solution that is widely applied. It is known that an o(n3) worst-case time solution is possible, but the published and suggested methods are complex and have not been established to be practical. Significant practical improvements to the original dynamic programming method have been introduced, but they retain the O(n3) worst-case time bound when n is the only problem-parameter used in the bound. Surprisingly, the most widely-used, general technique to achieve a worst-case (and often practical) speed up of dynamic programming, the Four-Russians technique, has not been previously applied to the RNA-folding problem. This is perhaps due to technical issues in adapting the technique to RNA-folding. In this paper, we give a simple, complete, and practical Four-Russians algorithm for the basic RNA-folding problem, achieving a worst-case time-bound of O(n3/log(n)). We show that this time-bound can also be obtained for richer nucleotide matching scoring-schemes, and that the method achieves consistent speed-ups in practice. The contribution is both theoretical and practical, since the basic RNA-folding problem is often solved multiple times in the inner-loop of more complex algorithms, and for long RNA molecules in the study of RNA virus genomes.

  7. Very deep recurrent convolutional neural network for object recognition

    Science.gov (United States)

    Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

    2017-03-01

    In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

  8. Non-cylindrical fold growth in the Zagros fold and thrust belt (Kurdistan, NE-Iraq)

    Science.gov (United States)

    Bartl, Nikolaus; Bretis, Bernhard; Grasemann, Bernhard; Lockhart, Duncan

    2010-05-01

    The Zagros mountains extends over 1800 km from Kurdistan in N-Iraq to the Strait of Hormuz in Iran and is one of the world most promising regions for the future hydrocarbon exploration. The Zagros Mountains started to form as a result of the collision between the Eurasian and Arabian Plates, whose convergence began in the Late Cretaceous as part of the Alpine-Himalayan orogenic system. Geodetic and seismological data document that both plates are still converging and that the fold and thrust belt of the Zagros is actively growing. Extensive hydrocarbon exploration mainly focuses on the antiforms of this fold and thrust belt and therefore the growth history of the folds is of great importance. This work investigates by means of structural field work and quantitative geomorphological techniques the progressive fold growth of the Permam, Bana Bawi- and Safeen- Anticlines located in the NE of the city of Erbil in the Kurdistan region of Northern Iraq. This part of the Zagros fold and thrust belt belongs to the so-called Simply Folded Belt, which is dominated by gentle to open folding. Faults or fault related folds have only minor importance. The mechanical anisotropy of the formations consisting of a succession of relatively competent (massive dolomite and limestone) and incompetent (claystone and siltstone) sediments essentially controls the deformation pattern with open to gentle parallel folding of the competent layers and flexural flow folding of the incompetent layers. The characteristic wavelength of the fold trains is around 10 km. Due to faster erosion of the softer rock layers in the folded sequence, the more competent lithologies form sharp ridges with steeply sloping sides along the eroded flanks of the anticlines. Using an ASTER digital elevation model in combination with geological field data we quantified 250 drainage basins along the different limbs of the subcylindrical Permam, Bana Bawi- and Safeen- Anticlines. Geomorphological indices of the drainage

  9. Surveillance of a nuclear reactor core by use of a pattern recognition method

    International Nuclear Information System (INIS)

    Invernizzi, Michel.

    1982-07-01

    A pattern recognition system is described for the surveillance of a PWR reactor. This report contains four chapters. The first one succinctly deals with statistical pattern recognition principles. In the second chapter we show how a surveillance problem may be treated by pattern recognition and we present methods for surveillances (detection of abnormalities), controls (kind of running recognition) and diagnotics (kind of abnormality recognition). The third chapter shows a surveillance method of a nuclear plant. The signals used are the neutron noise observations made by the ionization chambers inserted in the reactor. Abnormality is defined in opposition with the training set witch is supposed to be an exhaustive summary of normality. In the fourth chapter we propose a scheme for an adaptative recognition and a method based on classes modelisations by hyper-spheres. This method has been tested on simulated training sets in two-dimensional feature spaces. It gives solutions to problems of non-linear separability [fr

  10. Diagnosis of diabetes diseases using an Artificial Immune Recognition System2 (AIRS2) with fuzzy K-nearest neighbor.

    Science.gov (United States)

    Chikh, Mohamed Amine; Saidi, Meryem; Settouti, Nesma

    2012-10-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disease dataset used in our work is retrieved from UCI machine learning repository. The performances of the AIRS2 and MAIRS2 are evaluated regarding classification accuracy, sensitivity and specificity values. The highest classification accuracy obtained when applying the AIRS2 and MAIRS2 using 10-fold cross-validation was, respectively 82.69% and 89.10%.

  11. Data analysis and pattern recognition in multiple databases

    CERN Document Server

    Adhikari, Animesh; Pedrycz, Witold

    2014-01-01

    Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyse them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery, and mining patterns of select items provide different...

  12. Coupling ligand recognition to protein folding in an engineered variant of rabbit ileal lipid binding protein.

    Science.gov (United States)

    Kouvatsos, Nikolaos; Meldrum, Jill K; Searle, Mark S; Thomas, Neil R

    2006-11-28

    We have engineered a variant of the beta-clam shell protein ILBP which lacks the alpha-helical motif that caps the central binding cavity; the mutant protein is sufficiently destabilised that it is unfolded under physiological conditions, however, it unexpectedly binds its natural bile acid substrates with high affinity forming a native-like beta-sheet rich structure and demonstrating strong thermodynamic coupling between ligand binding and protein folding.

  13. Face sketch recognition based on edge enhancement via deep learning

    Science.gov (United States)

    Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

    2017-11-01

    In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

  14. Contemporary deep recurrent learning for recognition

    Science.gov (United States)

    Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

    2017-05-01

    Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

  15. The Risk of Vocal Fold Atrophy after Serial Corticosteroid Injections of the Vocal Fold.

    Science.gov (United States)

    Shi, Lucy L; Giraldez-Rodriguez, Laureano A; Johns, Michael M

    2016-11-01

    The aim of this study was to illustrate the risk of vocal fold atrophy in patients who receive serial subepithelial steroid injections for vocal fold scar. This study is a retrospective case report of two patients who underwent a series of weekly subepithelial infusions of 10 mg/mL dexamethasone for benign vocal fold lesion. Shortly after the procedures, both patients developed a weak and breathy voice. The first patient was a 53-year-old man with radiation-induced vocal fold stiffness. Six injections were performed unilaterally, and 1 week later, he developed unilateral vocal fold atrophy with new glottal insufficiency. The second patient was a 67-year-old woman with severe vocal fold inflammation related to laryngitis and calcinosis, Raynaud's phenomenon, esophagean dysmotility, sclerodactyly, and telangiectasia (CREST) syndrome. Five injections were performed bilaterally, and 1 week later, she developed bilateral vocal fold atrophy with a large midline glottal gap during phonation. In both cases, the steroid-induced vocal atrophy resolved spontaneously after 4 months. Serial subepithelial steroid infusions of the vocal folds, although safe in the majority of patients, carry the risk of causing temporary vocal fold atrophy when given at short intervals. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  16. MARATHON DESPITE UNILATERAL VOCAL FOLD PARALYSIS

    Directory of Open Access Journals (Sweden)

    Matthias Echternach

    2008-06-01

    Full Text Available The principal symptoms of unilateral vocal fold paralysis are hoarseness and difficulty in swallowing. Dyspnea is comparatively rare (Laccourreye et al., 2003. The extent to which unilateral vocal fold paralysis may lead to respiratory problems at all - in contrast to bilateral vocal fold paralysis- has not yet well been determined. On the one hand, inspiration is impaired with unilateral vocal fold paralysis; on the other hand, neither the position of the vocal fold paralysis nor the degree of breathiness correlates with respiratory parameters (Cantarella et al., 2003; 2005. The question of what respiratory stress a patient with a vocal fold paresis can endure has not yet been dealt with.A 43 year-old female patient was suffering from recurrent unspecific respiratory complaints for four months after physical activity. During training for a marathon, she experienced no difficulty in breathing. These unspecific respiratory complaints occurred only after athletic activity and persisted for hours. The patient observed neither an increased coughing nor a stridor. Her voice remained unaltered during the attacks, nor were there any signs of a symptomatic gastroesophageal reflux or infectious disease. A cardio-pulmonary and a radiological examination by means of an X-ray of the thorax also revealed no pathological phenomena. As antiallergic and antiobstructive therapy remained unsuccessful, a laryngological examination was performed in order to exclude a vocal cord dysfunction.Surprisingly enough, the laryngostroboscopy showed, as an initial description, a vocal fold paralysis of the left vocal fold in median position (Figure 1. The anamnestic background for the cause was unclear. The only clue was a thoracotomy on the left side due to a pleuritis in childhood. A subsequent laryngoscopic examination had never been performed. Good mucosa waves and amplitudes were shown bilateral with complete glottal closure. Neither in the acoustic analysis, nor in the

  17. A biphasic and brain-region selective down-regulation of cyclic adenosine monophosphate concentrations supports object recognition in the rat.

    Directory of Open Access Journals (Sweden)

    Maïte Hotte

    Full Text Available BACKGROUND: We aimed to further understand the relationship between cAMP concentration and mnesic performance. METHODS AND FINDINGS: Rats were injected with milrinone (PDE3 inhibitor, 0.3 mg/kg, i.p., rolipram (PDE4 inhibitor, 0.3 mg/kg, i.p. and/or the selective 5-HT4R agonist RS 67333 (1 mg/kg, i.p. before testing in the object recognition paradigm. Cyclic AMP concentrations were measured in brain structures linked to episodic-like memory (i.e. hippocampus, prefrontal and perirhinal cortices before or after either the sample or the testing phase. Except in the hippocampus of rolipram treated-rats, all treatment increased cAMP levels in each brain sub-region studied before the sample phase. After the sample phase, cAMP levels were significantly increased in hippocampus (1.8 fold, prefrontal (1.3 fold and perirhinal (1.3 fold cortices from controls rat while decreased in prefrontal cortex (∼0.83 to 0.62 fold from drug-treated rats (except for milrinone+RS 67333 treatment. After the testing phase, cAMP concentrations were still increased in both the hippocampus (2.76 fold and the perirhinal cortex (2.1 fold from controls animals. Minor increase were reported in hippocampus and perirhinal cortex from both rolipram (respectively, 1.44 fold and 1.70 fold and milrinone (respectively 1.46 fold and 1.56 fold-treated rat. Following the paradigm, cAMP levels were significantly lower in the hippocampus, prefrontal and perirhinal cortices from drug-treated rat when compared to controls animals, however, only drug-treated rats spent longer time exploring the novel object during the testing phase (inter-phase interval of 4 h. CONCLUSIONS: Our results strongly suggest that a "pre-sample" early increase in cAMP levels followed by a specific lowering of cAMP concentrations in each brain sub-region linked to the object recognition paradigm support learning efficacy after a middle-term delay.

  18. HMMerThread: detecting remote, functional conserved domains in entire genomes by combining relaxed sequence-database searches with fold recognition.

    Directory of Open Access Journals (Sweden)

    Charles Richard Bradshaw

    Full Text Available Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10, a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in

  19. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document

  20. Ear recognition from one sample per person.

    Directory of Open Access Journals (Sweden)

    Long Chen

    Full Text Available Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods.

  1. Ear recognition from one sample per person.

    Science.gov (United States)

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods.

  2. The Relative Success of Recognition-Based Inference in Multichoice Decisions

    Science.gov (United States)

    McCloy, Rachel; Beaman, C. Philip; Smith, Philip T.

    2008-01-01

    The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue…

  3. NoFold: RNA structure clustering without folding or alignment.

    Science.gov (United States)

    Middleton, Sarah A; Kim, Junhyong

    2014-11-01

    Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures. © 2014 Middleton and Kim; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  4. LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Jayanti Yusmah Sari

    2015-08-01

    Full Text Available In recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris. Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP, a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is needed

  5. Glycoprotein folding and quality-control mechanisms in protein-folding diseases

    Directory of Open Access Journals (Sweden)

    Sean P. Ferris

    2014-03-01

    Full Text Available Biosynthesis of proteins – from translation to folding to export – encompasses a complex set of events that are exquisitely regulated and scrutinized to ensure the functional quality of the end products. Cells have evolved to capitalize on multiple post-translational modifications in addition to primary structure to indicate the folding status of nascent polypeptides to the chaperones and other proteins that assist in their folding and export. These modifications can also, in the case of irreversibly misfolded candidates, signal the need for dislocation and degradation. The current Review focuses on the glycoprotein quality-control (GQC system that utilizes protein N-glycosylation and N-glycan trimming to direct nascent glycopolypeptides through the folding, export and dislocation pathways in the endoplasmic reticulum (ER. A diverse set of pathological conditions rooted in defective as well as over-vigilant ER quality-control systems have been identified, underlining its importance in human health and disease. We describe the GQC pathways and highlight disease and animal models that have been instrumental in clarifying our current understanding of these processes.

  6. Application Of t-Cherry Junction Trees in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Edith Kovacs

    2010-06-01

    Full Text Available Pattern recognition aims to classify data (patterns based ei-
    ther on a priori knowledge or on statistical information extracted from the data. In this paper we will concentrate on statistical pattern recognition using a new probabilistic approach which makes possible to select the so called 'informative' features. We develop a pattern recognition algorithm which is based on the conditional independence structure underlying the statistical data. Our method was succesfully applied on a real problem of recognizing Parkinson's disease on the basis of voice disorders.

  7. A study on the extraction of feature variables for the pattern recognition for welding flaws

    International Nuclear Information System (INIS)

    Kim, J. Y.; Kim, C. H.; Kim, B. H.

    1996-01-01

    In this study, the researches classifying the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing, feature extraction, feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function classifier, the empirical Bayesian classifier. Also, the pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack, lack of penetration, lack of fusion, porosity, and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately teamed the neural network classifier is better than stastical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

  8. Image quality assessment for video stream recognition systems

    Science.gov (United States)

    Chernov, Timofey S.; Razumnuy, Nikita P.; Kozharinov, Alexander S.; Nikolaev, Dmitry P.; Arlazarov, Vladimir V.

    2018-04-01

    Recognition and machine vision systems have long been widely used in many disciplines to automate various processes of life and industry. Input images of optical recognition systems can be subjected to a large number of different distortions, especially in uncontrolled or natural shooting conditions, which leads to unpredictable results of recognition systems, making it impossible to assess their reliability. For this reason, it is necessary to perform quality control of the input data of recognition systems, which is facilitated by modern progress in the field of image quality evaluation. In this paper, we investigate the approach to designing optical recognition systems with built-in input image quality estimation modules and feedback, for which the necessary definitions are introduced and a model for describing such systems is constructed. The efficiency of this approach is illustrated by the example of solving the problem of selecting the best frames for recognition in a video stream for a system with limited resources. Experimental results are presented for the system for identity documents recognition, showing a significant increase in the accuracy and speed of the system under simulated conditions of automatic camera focusing, leading to blurring of frames.

  9. Robust 3D Face Recognition in the Presence of Realistic Occlusions

    NARCIS (Netherlands)

    Alyuz, Nese; Gökberk, B.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Akarun, Lale

    2012-01-01

    Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems

  10. Kinematics, structural mechanics, and design of origami structures with smooth folds

    Science.gov (United States)

    Peraza Hernandez, Edwin Alexander

    Origami provides novel approaches to the fabrication, assembly, and functionality of engineering structures in various fields such as aerospace, robotics, etc. With the increase in complexity of the geometry and materials for origami structures that provide engineering utility, computational models and design methods for such structures have become essential. Currently available models and design methods for origami structures are generally limited to the idealization of the folds as creases of zeroth-order geometric continuity. Such an idealization is not proper for origami structures having non-negligible thickness or maximum curvature at the folds restricted by material limitations. Thus, for general structures, creased folds of merely zeroth-order geometric continuity are not appropriate representations of structural response and a new approach is needed. The first contribution of this dissertation is a model for the kinematics of origami structures having realistic folds of non-zero surface area and exhibiting higher-order geometric continuity, here termed smooth folds. The geometry of the smooth folds and the constraints on their associated kinematic variables are presented. A numerical implementation of the model allowing for kinematic simulation of structures having arbitrary fold patterns is also described. Examples illustrating the capability of the model to capture realistic structural folding response are provided. Subsequently, a method for solving the origami design problem of determining the geometry of a single planar sheet and its pattern of smooth folds that morphs into a given three-dimensional goal shape, discretized as a polygonal mesh, is presented. The design parameterization of the planar sheet and the constraints that allow for a valid pattern of smooth folds and approximation of the goal shape in a known folded configuration are presented. Various testing examples considering goal shapes of diverse geometries are provided. Afterwards, a

  11. Transferable coarse-grained potential for de novo protein folding and design.

    Directory of Open Access Journals (Sweden)

    Ivan Coluzza

    Full Text Available Protein folding and design are major biophysical problems, the solution of which would lead to important applications especially in medicine. Here we provide evidence of how a novel parametrization of the Caterpillar model may be used for both quantitative protein design and folding. With computer simulations it is shown that, for a large set of real protein structures, the model produces designed sequences with similar physical properties to the corresponding natural occurring sequences. The designed sequences require further experimental testing. For an independent set of proteins, previously used as benchmark, the correct folded structure of both the designed and the natural sequences is also demonstrated. The equilibrium folding properties are characterized by free energy calculations. The resulting free energy profiles not only are consistent among natural and designed proteins, but also show a remarkable precision when the folded structures are compared to the experimentally determined ones. Ultimately, the updated Caterpillar model is unique in the combination of its fundamental three features: its simplicity, its ability to produce natural foldable designed sequences, and its structure prediction precision. It is also remarkable that low frustration sequences can be obtained with such a simple and universal design procedure, and that the folding of natural proteins shows funnelled free energy landscapes without the need of any potentials based on the native structure.

  12. Structural basis of RNA folding and recognition in an AMP-RNA aptamer complex.

    Science.gov (United States)

    Jiang, F; Kumar, R A; Jones, R A; Patel, D J

    1996-07-11

    The catalytic properties of RNA and its well known role in gene expression and regulation are the consequence of its unique solution structures. Identification of the structural determinants of ligand recognition by RNA molecules is of fundamental importance for understanding the biological functions of RNA, as well as for the rational design of RNA Sequences with specific catalytic activities. Towards this latter end, Szostak et al. used in vitro selection techniques to isolate RNA sequences ('aptamers') containing a high-affinity binding site for ATP, the universal currency of cellular energy, and then used this motif to engineer ribozymes with polynucleotide kinase activity. Here we present the solution structure, as determined by multidimensional NMR spectroscopy and molecular dynamics calculations, of both uniformly and specifically 13C-, 15N-labelled 40-mer RNA containing the ATP-binding motif complexed with AMP. The aptamer adopts an L-shaped structure with two nearly orthogonal stems, each capped proximally by a G x G mismatch pair, binding the AMP ligand at their junction in a GNRA-like motif.

  13. Amino acid alphabet reduction preserves fold information contained in contact interactions in proteins.

    Science.gov (United States)

    Solis, Armando D

    2015-12-01

    To reduce complexity, understand generalized rules of protein folding, and facilitate de novo protein design, the 20-letter amino acid alphabet is commonly reduced to a smaller alphabet by clustering amino acids based on some measure of similarity. In this work, we seek the optimal alphabet that preserves as much of the structural information found in long-range (contact) interactions among amino acids in natively-folded proteins. We employ the Information Maximization Device, based on information theory, to partition the amino acids into well-defined clusters. Numbering from 2 to 19 groups, these optimal clusters of amino acids, while generated automatically, embody well-known properties of amino acids such as hydrophobicity/polarity, charge, size, and aromaticity, and are demonstrated to maintain the discriminative power of long-range interactions with minimal loss of mutual information. Our measurements suggest that reduced alphabets (of less than 10) are able to capture virtually all of the information residing in native contacts and may be sufficient for fold recognition, as demonstrated by extensive threading tests. In an expansive survey of the literature, we observe that alphabets derived from various approaches-including those derived from physicochemical intuition, local structure considerations, and sequence alignments of remote homologs-fare consistently well in preserving contact interaction information, highlighting a convergence in the various factors thought to be relevant to the folding code. Moreover, we find that alphabets commonly used in experimental protein design are nearly optimal and are largely coherent with observations that have arisen in this work. © 2015 Wiley Periodicals, Inc.

  14. Utterance independent bimodal emotion recognition in spontaneous communication

    Science.gov (United States)

    Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

    2011-12-01

    Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

  15. Fingerprint recognition system by use of graph matching

    Science.gov (United States)

    Shen, Wei; Shen, Jun; Zheng, Huicheng

    2001-09-01

    Fingerprint recognition is an important subject in biometrics to identify or verify persons by physiological characteristics, and has found wide applications in different domains. In the present paper, we present a finger recognition system that combines singular points and structures. The principal steps of processing in our system are: preprocessing and ridge segmentation, singular point extraction and selection, graph representation, and finger recognition by graphs matching. Our fingerprint recognition system is implemented and tested for many fingerprint images and the experimental result are satisfactory. Different techniques are used in our system, such as fast calculation of orientation field, local fuzzy dynamical thresholding, algebraic analysis of connections and fingerprints representation and matching by graphs. Wed find that for fingerprint database that is not very large, the recognition rate is very high even without using a prior coarse category classification. This system works well for both one-to-few and one-to-many problems.

  16. Cost-Sensitive Learning for Emotion Robust Speaker Recognition

    Directory of Open Access Journals (Sweden)

    Dongdong Li

    2014-01-01

    Full Text Available In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

  17. Cost-sensitive learning for emotion robust speaker recognition.

    Science.gov (United States)

    Li, Dongdong; Yang, Yingchun; Dai, Weihui

    2014-01-01

    In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

  18. Stein and Honneth on Empathy and Emotional Recognition

    DEFF Research Database (Denmark)

    Jardine, James Alexander

    2015-01-01

    My aim in this paper is to make use of Edith Stein’s phenomenological analyses of empathy, emotion, and personhood to clarify and critically assess the recent suggestion by Axel Honneth that a basic form of recognition is affective in nature. I will begin by considering Honneth’s own presentation...... of this claim in his discussion of the role of affect in recognitive gestures, as well as in his notion of ‘elementary recognition,’ arguing that while his account contains much of value it also generates problems. On the basis of this analysis, I will try to show that Stein’s account of empathy demarcates...... an elementary form of recognition in a less problematic fashion than does Honneth’s own treatment of this issue. I will then spell out the consequences of this move for the emotional recognition thesis, arguing that Stein’s treatment lends it further credence, before ending with some remarks on the connection...

  19. A Bayesian Classifier for X-Ray Pulsars Recognition

    Directory of Open Access Journals (Sweden)

    Hao Liang

    2016-01-01

    Full Text Available Recognition for X-ray pulsars is important for the problem of spacecraft’s attitude determination by X-ray Pulsar Navigation (XPNAV. By using the nonhomogeneous Poisson model of the received photons and the minimum recognition error criterion, a classifier based on the Bayesian theorem is proposed. For X-ray pulsars recognition with unknown Doppler frequency and initial phase, the features of every X-ray pulsar are extracted and the unknown parameters are estimated using the Maximum Likelihood (ML method. Besides that, a method to recognize unknown X-ray pulsars or X-ray disturbances is proposed. Simulation results certificate the validity of the proposed Bayesian classifier.

  20. A replica exchange Monte Carlo algorithm for protein folding in the HP model

    Directory of Open Access Journals (Sweden)

    Shmygelska Alena

    2007-09-01

    Full Text Available Abstract Background The ab initio protein folding problem consists of predicting protein tertiary structure from a given amino acid sequence by minimizing an energy function; it is one of the most important and challenging problems in biochemistry, molecular biology and biophysics. The ab initio protein folding problem is computationally challenging and has been shown to be NP MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaat0uy0HwzTfgDPnwy1egaryqtHrhAL1wy0L2yHvdaiqaacqWFneVtcqqGqbauaaa@3961@-hard even when conformations are restricted to a lattice. In this work, we implement and evaluate the replica exchange Monte Carlo (REMC method, which has already been applied very successfully to more complex protein models and other optimization problems with complex energy landscapes, in combination with the highly effective pull move neighbourhood in two widely studied Hydrophobic Polar (HP lattice models. Results We demonstrate that REMC is highly effective for solving instances of the square (2D and cubic (3D HP protein folding problem. When using the pull move neighbourhood, REMC outperforms current state-of-the-art algorithms for most benchmark instances. Additionally, we show that this new algorithm provides a larger ensemble of ground-state structures than the existing state-of-the-art methods. Furthermore, it scales well with sequence length, and it finds significantly better conformations on long biological sequences and sequences with a provably unique ground-state structure, which is believed to be a characteristic of real proteins. We also present evidence that our REMC algorithm can fold sequences which exhibit significant interaction between termini in the hydrophobic core relatively easily. Conclusion We demonstrate that REMC utilizing the pull move

  1. Folding of multidomain proteins: biophysical consequences of tethering even in apparently independent folding.

    Science.gov (United States)

    Arviv, Oshrit; Levy, Yaakov

    2012-12-01

    Most eukaryotic and a substantial fraction of prokaryotic proteins are composed of more than one domain. The tethering of these evolutionary, structural, and functional units raises, among others, questions regarding the folding process of conjugated domains. Studying the folding of multidomain proteins in silico enables one to identify and isolate the tethering-induced biophysical determinants that govern crosstalks generated between neighboring domains. For this purpose, we carried out coarse-grained and atomistic molecular dynamics simulations of two two-domain constructs from the immunoglobulin-like β-sandwich fold. Each of these was experimentally shown to behave as the "sum of its parts," that is, the thermodynamic and kinetic folding behavior of the constituent domains of these constructs seems to occur independently, with the folding of each domain uncoupled from the folding of its partner in the two-domain construct. We show that the properties of the individual domains can be significantly affected by conjugation to another domain. The tethering may be accompanied by stabilizing as well as destabilizing factors whose magnitude depends on the size of the interface, the length, and the flexibility of the linker, and the relative stability of the domains. Accordingly, the folding of a multidomain protein should not be viewed as the sum of the folding patterns of each of its parts, but rather, it involves abrogating several effects that lead to this outcome. An imbalance between these effects may result in either stabilization or destabilization owing to the tethering. Copyright © 2012 Wiley Periodicals, Inc.

  2. The Army word recognition system

    Science.gov (United States)

    Hadden, David R.; Haratz, David

    1977-01-01

    The application of speech recognition technology in the Army command and control area is presented. The problems associated with this program are described as well as as its relevance in terms of the man/machine interactions, voice inflexions, and the amount of training needed to interact with and utilize the automated system.

  3. Gauge Theory and Calibrated Geometry for Calabi-Yau 4-folds

    Science.gov (United States)

    Cao, Yalong

    This thesis is devoted to the study of gauge theory and calibrated geometry for Calabi-Yau 4-folds. More specifically, our study is along the following five directions. 1. We develop Donaldson-Thomas type theory on Calabi-Yau 4-folds. Let X be a compact complex Calabi-Yau 4-fold. We define Donaldson-Thomas type deformation invariants (DT4 invariants) by studying moduli spaces of solutions to the Donaldson- Thomas equations on X. We also study sheaves counting problems on local Calabi-Yau 4-folds. We relate DT4 invariants of KY to the Donaldson-Thomas invariants of the associated Fano 3-fold Y. When the Calabi-Yau 4-fold is toric, we adapt the virtual localization formula to define the corresponding equivariant DT4 invariants. We also discuss the non-commutative version of DT4 invariants for quivers with relations. Finally, we compute DT4 invariants for certain Calabi-Yau 4-folds when moduli spaces are smooth and find a DT 4/GW correspondence for X. Examples of wall-crossing phenomenon in DT4 theory are also given. 2. Given a complex 4-fold X with an (Calabi-Yau 3-fold) anti-canonical divisor Y, we study relative Donaldson-Thomas invariants for this pair, which are elements in the Donaldson-Thomas cohomologies of Y. We also discuss gluing formulas which relate relative invariants and DT4 invariants for Calabi-Yau 4-folds. 3. We study orientability issues of moduli spaces from gauge theories on Calabi-Yau manifolds. Our results generalize and strengthen those for Donaldson-Thomas theory on Calabi-Yau manifolds of dimensions 3 and 4. We also prove a corresponding result in the relative situation which is relevant to the gluing formula in DT theory. 4. Motivated by Strominger-Yau-Zaslow's mirror symmetry proposal and Kontsevich's homological mirror symmetry conjecture, we study mirror phenomena (in A-model) of certain results from Donaldson-Thomas theory for Calabi-Yau 4-folds. More precisely, we study calibrated geometry in the sense of Harvey-Lawson and Lagrangian

  4. Finite element modeling of the vocal folds with deformable interface tracking

    DEFF Research Database (Denmark)

    Granados Corsellas, Alba; Brunskog, Jonas; Misztal, Marek Krzysztof

    2014-01-01

    Continuous and prolonged use of the sp eaking voice may lead to functional sp eech disorders that are not apparent for voice clinicians from high-sp eed imaging of the vo cal folds' vibration. However, it is hyp othesized that time dep endent tissue prop erties provide some insight into the injury...... pro cess. To infer material parameters via an inverse optimization problem from recorded deformation, a self sustained theoretical mo del of the vo cal folds is needed. With this purp ose, a transversely isotropic three-dimensional nite element mo del is prop osed and investigated. Sp ecial attention...

  5. Laser gated viewing : An enabler for Automatic Target Recognition?

    NARCIS (Netherlands)

    Bovenkamp, E.G.P.; Schutte, K.

    2010-01-01

    For many decades attempts to accomplish Automatic Target Recognition have been made using both visual and FLIR camera systems. A recurring problem in these approaches is the segmentation problem, which is the separation between the target and its background. This paper describes an approach to

  6. Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

    Directory of Open Access Journals (Sweden)

    Guangwei Gao

    Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

  7. Incorporating Duration Information in Activity Recognition

    Science.gov (United States)

    Chaurasia, Priyanka; Scotney, Bryan; McClean, Sally; Zhang, Shuai; Nugent, Chris

    Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.

  8. Numerical solution of fluid-structure interaction represented by human vocal folds in airflow

    Directory of Open Access Journals (Sweden)

    Valášek J.

    2016-01-01

    Full Text Available The paper deals with the human vocal folds vibration excited by the fluid flow. The vocal fold is modelled as an elastic body assuming small displacements and therefore linear elasticity theory is used. The viscous incompressible fluid flow is considered. For purpose of numerical solution the arbitrary Lagrangian-Euler method (ALE is used. The whole problem is solved by the finite element method (FEM based solver. Results of numerical experiments with different boundary conditions are presented.

  9. Numerical solution of fluid-structure interaction represented by human vocal folds in airflow

    Science.gov (United States)

    Valášek, J.; Sváček, P.; Horáček, J.

    2016-03-01

    The paper deals with the human vocal folds vibration excited by the fluid flow. The vocal fold is modelled as an elastic body assuming small displacements and therefore linear elasticity theory is used. The viscous incompressible fluid flow is considered. For purpose of numerical solution the arbitrary Lagrangian-Euler method (ALE) is used. The whole problem is solved by the finite element method (FEM) based solver. Results of numerical experiments with different boundary conditions are presented.

  10. Human Activity Recognition from Body Sensor Data using Deep Learning.

    Science.gov (United States)

    Hassan, Mohammad Mehedi; Huda, Shamsul; Uddin, Md Zia; Almogren, Ahmad; Alrubaian, Majed

    2018-04-16

    In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities. In this paper, we address the human activity recognition problem as a classification problem using wearable body sensor data. In particular, we propose to utilize a Deep Belief Network (DBN) model for successful human activity recognition. First, we extract the important initial features from the raw body sensor data. Then, a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) are performed to further process the features and make them more robust to be useful for fast activity recognition. Finally, the DBN is trained by these features. Various experiments were performed on a real-world wearable sensor dataset to verify the effectiveness of the deep learning algorithm. The results show that the proposed DBN outperformed other algorithms and achieves satisfactory activity recognition performance.

  11. Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

    Science.gov (United States)

    Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

    2013-08-01

    Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

  12. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Science.gov (United States)

    2010-01-01

    ...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

  13. Numerical approximations of flow induced vibrations of vocal folds

    Directory of Open Access Journals (Sweden)

    Sváček Petr

    2017-01-01

    Full Text Available The paper focus on mathematical modelling of incompressible fluid flow interacting with vibrations of an elastic vocal fold. The flow in moving domain is modelled by the incompressible Navier-Stokes equations written in the Arbitrary Lagrangian-Eulerian (ALE form. The channel geometry is an approximation of the human glottal region. The flow model is coupled with a simplified structure model. The problem is mathematically described and the resulting fluid-structure interaction problem is discretized by a stabilized finite element method. A strong coupling algorithm is applied for solution of the coupled fluid-structure problem. The choice of boundary conditions is discussed, particularly the choice of different artificial inlet/outlet boundary conditions is described in details. The numerical results are shown.

  14. Numerical approximations of flow induced vibrations of vocal folds

    Science.gov (United States)

    Sváček, Petr

    The paper focus on mathematical modelling of incompressible fluid flow interacting with vibrations of an elastic vocal fold. The flow in moving domain is modelled by the incompressible Navier-Stokes equations written in the Arbitrary Lagrangian-Eulerian (ALE) form. The channel geometry is an approximation of the human glottal region. The flow model is coupled with a simplified structure model. The problem is mathematically described and the resulting fluid-structure interaction problem is discretized by a stabilized finite element method. A strong coupling algorithm is applied for solution of the coupled fluid-structure problem. The choice of boundary conditions is discussed, particularly the choice of different artificial inlet/outlet boundary conditions is described in details. The numerical results are shown.

  15. Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Qi Jia

    2015-03-01

    Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

  16. Threshold models of recognition and the recognition heuristic

    Directory of Open Access Journals (Sweden)

    Edgar Erdfelder

    2011-02-01

    Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

  17. Two Challenges of Correct Validation in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Thomas eNowotny

    2014-09-01

    Full Text Available Supervised pattern recognition is the process of mapping patterns to class labelsthat define their meaning. The core methods for pattern recognitionhave been developed by machine learning experts but due to their broadsuccess an increasing number of non-experts are now employing andrefining them. In this perspective I will discuss the challenge ofcorrect validation of supervised pattern recognition systems, in particular whenemployed by non-experts. To illustrate the problem I will give threeexamples of common errors that I have encountered in the lastyear. Much of this challenge can be addressed by strict procedure invalidation but there are remaining problems of correctlyinterpreting comparative work on exemplary data sets, which I willelucidate on the example of the well-used MNIST data set of handwrittendigits.

  18. TMFoldWeb: a web server for predicting transmembrane protein fold class.

    Science.gov (United States)

    Kozma, Dániel; Tusnády, Gábor E

    2015-09-17

    Here we present TMFoldWeb, the web server implementation of TMFoldRec, a transmembrane protein fold recognition algorithm. TMFoldRec uses statistical potentials and utilizes topology filtering and a gapless threading algorithm. It ranks template structures and selects the most likely candidates and estimates the reliability of the obtained lowest energy model. The statistical potential was developed in a maximum likelihood framework on a representative set of the PDBTM database. According to the benchmark test the performance of TMFoldRec is about 77 % in correctly predicting fold class for a given transmembrane protein sequence. An intuitive web interface has been developed for the recently published TMFoldRec algorithm. The query sequence goes through a pipeline of topology prediction and a systematic sequence to structure alignment (threading). Resulting templates are ordered by energy and reliability values and are colored according to their significance level. Besides the graphical interface, a programmatic access is available as well, via a direct interface for developers or for submitting genome-wide data sets. The TMFoldWeb web server is unique and currently the only web server that is able to predict the fold class of transmembrane proteins while assigning reliability scores for the prediction. This method is prepared for genome-wide analysis with its easy-to-use interface, informative result page and programmatic access. Considering the info-communication evolution in the last few years, the developed web server, as well as the molecule viewer, is responsive and fully compatible with the prevalent tablets and mobile devices.

  19. Star pattern recognition algorithm aided by inertial information

    Science.gov (United States)

    Liu, Bao; Wang, Ke-dong; Zhang, Chao

    2011-08-01

    Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

  20. Quantum Nuclear Extension of Electron Nuclear Dynamics on Folded Effective-Potential Surfaces

    DEFF Research Database (Denmark)

    Hall, B.; Deumens, E.; Ohrn, Y.

    2014-01-01

    A perennial problem in quantum scattering calculations is accurate theoretical treatment of low energy collisions. We propose a method of extracting a folded, nonadiabatic, effective potential energy surface from electron nuclear dynamics (END) trajectories; we then perform nuclear wave packet...

  1. Human recognition at a distance in video

    CERN Document Server

    Bhanu, Bir

    2010-01-01

    Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are

  2. Comparing word and face recognition

    DEFF Research Database (Denmark)

    Robotham, Ro Julia; Starrfelt, Randi

    2017-01-01

    included, as a control, which makes designing experiments all the more challenging. Three main strategies have been used to overcome this problem, each of which has limitations: 1) Compare performances on typical tests of the three stimulus types (e.g., a Face Memory Test, an Object recognition test...... this framework to classify tests and experiments aiming to compare processing across these categories, it becomes apparent that core differences in characteristics (visual and semantic) between the stimuli make the problem of designing comparable tests an insoluble conundrum. By analyzing the experimental...

  3. The problem of automatic identification of concepts

    International Nuclear Information System (INIS)

    Andreewsky, Alexandre

    1975-11-01

    This paper deals with the problem of the automatic recognition of concepts and describes an important language tool, the ''linguistic filter'', which facilitates the construction of statistical algorithms. Certain special filters, of prepositions, conjunctions, negatives, logical implication, compound words, are presented. This is followed by a detailed description of a statistical algorithm allowing recognition of pronoun referents, and finally the problem of the automatic treatment of negatives in French is discussed [fr

  4. View-Invariant Gait Recognition Through Genetic Template Segmentation

    Science.gov (United States)

    Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

    2017-08-01

    Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.

  5. Towards discrete wavelet transform-based human activity recognition

    Science.gov (United States)

    Khare, Manish; Jeon, Moongu

    2017-06-01

    Providing accurate recognition of human activities is a challenging problem for visual surveillance applications. In this paper, we present a simple and efficient algorithm for human activity recognition based on a wavelet transform. We adopt discrete wavelet transform (DWT) coefficients as a feature of human objects to obtain advantages of its multiresolution approach. The proposed method is tested on multiple levels of DWT. Experiments are carried out on different standard action datasets including KTH and i3D Post. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures. The proposed method is found to have better recognition accuracy in comparison to the state-of-the-art methods.

  6. AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    K. Meena

    2013-11-01

    Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

  7. Research of convolutional neural networks for traffic sign recognition

    OpenAIRE

    Stadalnikas, Kasparas

    2017-01-01

    In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

  8. Prevalence of face recognition deficits in middle childhood.

    Science.gov (United States)

    Bennetts, Rachel J; Murray, Ebony; Boyce, Tian; Bate, Sarah

    2017-02-01

    Approximately 2-2.5% of the adult population is believed to show severe difficulties with face recognition, in the absence of any neurological injury-a condition known as developmental prosopagnosia (DP). However, to date no research has attempted to estimate the prevalence of face recognition deficits in children, possibly because there are very few child-friendly, well-validated tests of face recognition. In the current study, we examined face and object recognition in a group of primary school children (aged 5-11 years), to establish whether our tests were suitable for children and to provide an estimate of face recognition difficulties in children. In Experiment 1 (n = 184), children completed a pre-existing test of child face memory, the Cambridge Face Memory Test-Kids (CFMT-K), and a bicycle test with the same format. In Experiment 2 (n = 413), children completed three-alternative forced-choice matching tasks with faces and bicycles. All tests showed good psychometric properties. The face and bicycle tests were well matched for difficulty and showed a similar developmental trajectory. Neither the memory nor the matching tests were suitable to detect impairments in the youngest groups of children, but both tests appear suitable to screen for face recognition problems in middle childhood. In the current sample, 1.2-5.2% of children showed difficulties with face recognition; 1.2-4% showed face-specific difficulties-that is, poor face recognition with typical object recognition abilities. This is somewhat higher than previous adult estimates: It is possible that face matching tests overestimate the prevalence of face recognition difficulties in children; alternatively, some children may "outgrow" face recognition difficulties.

  9. Glass ionomer application for vocal fold augmentation: Histopathological analysis on rabbit vocal fold.

    Science.gov (United States)

    Demirci, Sule; Tuzuner, Arzu; Callıoglu, Elif Ersoy; Yumusak, Nihat; Arslan, Necmi; Baltacı, Bülent

    2016-04-01

    The aim of this study was to investigate the use of glass ionomer cement (GIC) as an injection material for vocal fold augmentation and to evaluate the biocompatibility of the material. Ten adult New Zealand rabbits were used. Under general anesthesia, 0.1-cc GIC was injected to one vocal fold and the augmentation of vocal fold was observed. No injection was applied to the opposite side, which was accepted as the control group. The animals were sacrificed after 3 months and the laryngeal specimens were histopathologically evaluated. The injected and the noninjected control vocal folds were analyzed. The GIC particles were observed in histological sections on the injected side, and no foreign body giant cells, granulomatous inflammation, necrosis, or marked chronic inflammation were detected around the glass ionomer particles. Mild inflammatory reactions were noticed in only two specimens. The noninjected sides of vocal folds were completely normal. The findings of this study suggest that GIC is biocompatible and may be further investigated as an alternative injection material for augmentation of the vocal fold. Further studies are required to examine the viscoelastic properties of GIC and the long-term effects in experimental studies. NA. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  10. Pattern recognition and modelling of earthquake registrations with interactive computer support

    International Nuclear Information System (INIS)

    Manova, Katarina S.

    2004-01-01

    The object of the thesis is Pattern Recognition. Pattern recognition i.e. classification, is applied in many fields: speech recognition, hand printed character recognition, medical analysis, satellite and aerial-photo interpretations, biology, computer vision, information retrieval and so on. In this thesis is studied its applicability in seismology. Signal classification is an area of great importance in a wide variety of applications. This thesis deals with the problem of (automatic) classification of earthquake signals, which are non-stationary signals. Non-stationary signal classification is an area of active research in the signal and image processing community. The goal of the thesis is recognition of earthquake signals according to their epicentral zone. Source classification i.e. recognition is based on transformation of seismograms (earthquake registrations) to images, via time-frequency transformations, and applying image processing and pattern recognition techniques for feature extraction, classification and recognition. The tested data include local earthquakes from seismic regions in Macedonia. By using actual seismic data it is shown that proposed methods provide satisfactory results for classification and recognition.(Author)

  11. Periodic folding of viscous sheets

    Science.gov (United States)

    Ribe, Neil M.

    2003-09-01

    The periodic folding of a sheet of viscous fluid falling upon a rigid surface is a common fluid mechanical instability that occurs in contexts ranging from food processing to geophysics. Asymptotic thin-layer equations for the combined stretching-bending deformation of a two-dimensional sheet are solved numerically to determine the folding frequency as a function of the sheet’s initial thickness, the pouring speed, the height of fall, and the fluid properties. As the buoyancy increases, the system bifurcates from “forced” folding driven kinematically by fluid extrusion to “free” folding in which viscous resistance to bending is balanced by buoyancy. The systematics of the numerically predicted folding frequency are in good agreement with laboratory experiments.

  12. Adaptive Self-Occlusion Behavior Recognition Based on pLSA

    Directory of Open Access Journals (Sweden)

    Hong-bin Tu

    2013-01-01

    Full Text Available Human action recognition is an important area of human action recognition research. Focusing on the problem of self-occlusion in the field of human action recognition, a new adaptive occlusion state behavior recognition approach was presented based on Markov random field and probabilistic Latent Semantic Analysis (pLSA. Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms an occlusion state variable by phase space obtained. Then, we proposed a hierarchical area variety model. Finally, we use the topic model of pLSA to recognize the human behavior. Experiments were performed on the KTH, Weizmann, and Humaneva dataset to test and evaluate the proposed method. The compared experiment results showed that what the proposed method can achieve was more effective than the compared methods.

  13. Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network.

    Science.gov (United States)

    Sun, Xin; Qian, Huinan

    2016-01-01

    Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of these hand-crafted features are low-level image representation, which is easily affected by noise and background. Secondly, the medicine images are very clean without any backgrounds, which makes it difficult to use in practical applications. Therefore, designing high-level image representation for recognition and retrieval in real world medicine images is facing a great challenge. Inspired by the recent progress of deep learning in computer vision, we realize that deep learning methods may provide robust medicine image representation. In this paper, we propose to use the Convolutional Neural Network (CNN) for Chinese herbal medicine image recognition and retrieval. For the recognition problem, we use the softmax loss to optimize the recognition network; then for the retrieval problem, we fine-tune the recognition network by adding a triplet loss to search for the most similar medicine images. To evaluate our method, we construct a public database of herbal medicine images with cluttered backgrounds, which has in total 5523 images with 95 popular Chinese medicine categories. Experimental results show that our method can achieve the average recognition precision of 71% and the average retrieval precision of 53% over all the 95 medicine categories, which are quite promising given the fact that the real world images have multiple pieces of occluded herbal and cluttered backgrounds. Besides, our proposed method achieves the state-of-the-art performance by improving previous studies with a large margin.

  14. Making a diagnosis of different lesions of vocal fold mucosa by contact endoscopy: The first usage in our clinical practice

    Directory of Open Access Journals (Sweden)

    Jovanović Milan B.

    2005-01-01

    Full Text Available During laryngomicroscopy, the superficial layers of vocal fold epithelium can be examined in vivo and in situ by contact endoscopy. Methylene blue is applied initially to stain the epihelial cells of the vocal folds. When in contact with mucosal tissue, this endoscope provides 60 and 150 times magnification and clear visualization of cellular patterns of the superficial epithelial layers. For the first time in our laryngological clinical practice, we confirmed a number of previously established parametars such as regularity and arrangement of the epithelium, nucleus contour, and nucleus-cytoplasm ratio, what all enable recognition and easy evaluation of different clinical conditions such as chronic laryngitis, Reinke.s edema, papiloma dyspiasia or vocal fold carcinoma. The advantage of con- tact endoscopy in vivo and in situ allows for detailed scan and mapping of all cell changes of the whole mucosa surface. All these features definitely classify the contact endoscopy into additional diagnostic methods in laryngology.

  15. Face Recognition Using Local Quantized Patterns and Gabor Filters

    Science.gov (United States)

    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.

  16. Brand recognition in television advertising: The influence of brand presence and brand introduction

    OpenAIRE

    Charlene Gerber; Marlize Terblanche-Smit; Tracey Crommelin

    2014-01-01

    Purpose: To assess the relationship between brand recognition and brand presence and brand introduction. Problem investigated: Brand recognition and recall are established advertising effectiveness measurements to assess brand awareness. Of particular interest is whether encoding of brand information as measured by brand recognition is influenced by brand presence and brand introduction. Design/methodology/approach: A meta-analysis was performed on responses to 25 television advertisem...

  17. Protein folding simulations: from coarse-grained model to all-atom model.

    Science.gov (United States)

    Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

    2009-06-01

    Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL

  18. Protein folding: Over half a century lasting quest. Comment on "There and back again: Two views on the protein folding puzzle" by Alexei V. Finkelstein et al.

    Science.gov (United States)

    Krokhotin, Andrey; Dokholyan, Nikolay V.

    2017-07-01

    Most proteins fold into unique three-dimensional (3D) structures that determine their biological functions, such as catalytic activity or macromolecular binding. Misfolded proteins can pose a threat through aberrant interactions with other proteins leading to a number of diseases including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis [1,2]. What does determine 3D structure of proteins? The first clue to this question came more than fifty years ago when Anfinsen demonstrated that unfolded proteins can spontaneously fold to their native 3D structures [3,4]. Anfinsen's experiments lead to the conclusion that proteins fold to unique native structure corresponding to the stable and kinetically accessible free energy minimum, and protein native structure is solely determined by its amino acid sequence. The question of how exactly proteins find their free energy minimum proved to be a difficult problem. One of the puzzles, initially pointed out by Levinthal, was an inconsistency between observed protein folding times and theoretical estimates. A self-avoiding polymer model of a globular protein of 100-residues length on a cubic lattice can sample at least 1047 states. Based on the assumption that conformational sampling occurs at the highest vibrational mode of proteins (∼picoseconds), predicted folding time by searching among all the possible conformations leads to ∼1027 years (much larger than the age of the universe) [5]. In contrast, observed protein folding time range from microseconds to minutes. Due to tremendous theoretical progress in protein folding field that has been achieved in past decades, the source of this inconsistency is currently understood that is thoroughly described in the review by Finkelstein et al. [6].

  19. Coenzyme Recognition and Gene Regulation by a Flavin Mononucleotide Riboswitch

    Energy Technology Data Exchange (ETDEWEB)

    Serganov, A.; Huang, L; Patel, D

    2009-01-01

    The biosynthesis of several protein cofactors is subject to feedback regulation by riboswitches. Flavin mononucleotide (FMN)-specific riboswitches also known as RFN elements, direct expression of bacterial genes involved in the biosynthesis and transport of riboflavin (vitamin B2) and related compounds. Here we present the crystal structures of the Fusobacterium nucleatum riboswitch bound to FMN, riboflavin and antibiotic roseoflavin. The FMN riboswitch structure, centred on an FMN-bound six-stem junction, does not fold by collinear stacking of adjacent helices, typical for folding of large RNAs. Rather, it adopts a butterfly-like scaffold, stapled together by opposingly directed but nearly identically folded peripheral domains. FMN is positioned asymmetrically within the junctional site and is specifically bound to RNA through interactions with the isoalloxazine ring chromophore and direct and Mg{sup 2+}-mediated contacts with the phosphate moiety. Our structural data, complemented by binding and footprinting experiments, imply a largely pre-folded tertiary RNA architecture and FMN recognition mediated by conformational transitions within the junctional binding pocket. The inherent plasticity of the FMN-binding pocket and the availability of large openings make the riboswitch an attractive target for structure-based design of FMN-like antimicrobial compounds. Our studies also explain the effects of spontaneous and antibiotic-induced deregulatory mutations and provided molecular insights into FMN-based control of gene expression in normal and riboflavin-overproducing bacterial strains.

  20. Two-step interrogation then recognition of DNA binding site by Integration Host Factor: an architectural DNA-bending protein.

    Science.gov (United States)

    Velmurugu, Yogambigai; Vivas, Paula; Connolly, Mitchell; Kuznetsov, Serguei V; Rice, Phoebe A; Ansari, Anjum

    2018-02-28

    The dynamics and mechanism of how site-specific DNA-bending proteins initially interrogate potential binding sites prior to recognition have remained elusive for most systems. Here we present these dynamics for Integration Host factor (IHF), a nucleoid-associated architectural protein, using a μs-resolved T-jump approach. Our studies show two distinct DNA-bending steps during site recognition by IHF. While the faster (∼100 μs) step is unaffected by changes in DNA or protein sequence that alter affinity by >100-fold, the slower (1-10 ms) step is accelerated ∼5-fold when mismatches are introduced at DNA sites that are sharply kinked in the specific complex. The amplitudes of the fast phase increase when the specific complex is destabilized and decrease with increasing [salt], which increases specificity. Taken together, these results indicate that the fast phase is non-specific DNA bending while the slow phase, which responds only to changes in DNA flexibility at the kink sites, is specific DNA kinking during site recognition. Notably, the timescales for the fast phase overlap with one-dimensional diffusion times measured for several proteins on DNA, suggesting that these dynamics reflect partial DNA bending during interrogation of potential binding sites by IHF as it scans DNA.

  1. Brand recognition in television advertising: The influence of brand presence and brand introduction

    Directory of Open Access Journals (Sweden)

    Charlene Gerber

    2014-05-01

    Problem investigated: Brand recognition and recall are established advertising effectiveness measurements to assess brand awareness. Of particular interest is whether encoding of brand information as measured by brand recognition is influenced by brand presence and brand introduction. Design/methodology/approach: A meta-analysis was performed on responses to 25 television advertisements, gathered from 50 000 respondents. Findings: The findings indicated a positive linear relationship between brand presence and brand recognition but a negative linear relationship between brand introduction and brand recognition, whilst brand introduction and brand presence predicted variance in brand recognition. Value of research: The researchers concluded that a brand should be present in an advertisement for about two-thirds of the time for optimum brand recognition.

  2. Swallowing dysfunction in patients with unilateral vocal fold paralysis: aetiology and outcomes.

    Science.gov (United States)

    Ollivere, B; Duce, K; Rowlands, G; Harrison, P; O'Reilly, B J

    2006-01-01

    Although unilateral vocal fold palsy (UVFP) is a common problem, data relating to swallowing dysfunction are sparse. We reviewed the clinical findings (method of presentation, underlying diagnosis and position of the vocal folds) of 30 patients and conducted a follow-up telephone survey. Outcome measures used were direct visualization of fold function, position and compensation. In addition, standardized speech and language assessments for swallowing dysfunction and dysphonia were noted and compared to presentation. Our study indicates that 56 per cent of patients with UVFP have associated dysphagia. Outcome with speech therapy is significant, with 73 per cent showing improvement. These data indicate a significant link between UVFP and swallowing dysfunction. There is a marked therapeutic benefit from voice therapy. Further work is required to evaluate the long-term outcomes and establish the mechanism of swallowing dysfunction in these patients.

  3. Asymmetric hindwing foldings in rove beetles.

    Science.gov (United States)

    Saito, Kazuya; Yamamoto, Shuhei; Maruyama, Munetoshi; Okabe, Yoji

    2014-11-18

    Foldable wings of insects are the ultimate deployable structures and have attracted the interest of aerospace engineering scientists as well as entomologists. Rove beetles are known to fold their wings in the most sophisticated ways that have right-left asymmetric patterns. However, the specific folding process and the reason for this asymmetry remain unclear. This study reveals how these asymmetric patterns emerge as a result of the folding process of rove beetles. A high-speed camera was used to reveal the details of the wing-folding movement. The results show that these characteristic asymmetrical patterns emerge as a result of simultaneous folding of overlapped wings. The revealed folding mechanisms can achieve not only highly compact wing storage but also immediate deployment. In addition, the right and left crease patterns are interchangeable, and thus each wing internalizes two crease patterns and can be folded in two different ways. This two-way folding gives freedom of choice for the folding direction to a rove beetle. The use of asymmetric patterns and the capability of two-way folding are unique features not found in artificial structures. These features have great potential to extend the design possibilities for all deployable structures, from space structures to articles of daily use.

  4. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  5. Quantification of fold growth of frontal antiforms in the Zagros fold and thrust belt (Kurdistan, NE Iraq)

    Science.gov (United States)

    Bretis, Bernhard; Bartl, Nikolaus; Graseman, Bernhard; Lockhart, Duncan

    2010-05-01

    The Zagros fold and thrust belt is a seismically active orogen, where actual kinematic models based on GPS networks suggest a north-south shortening between Arabian and Eurasian in the order of 1.5-2.5 cm/yr. Most of this deformation is partitioned in south-southwest oriented folding and thrusting with northwest-southeast to north-south trending dextral strike slip faults. The Zagros fold and thrust belt is of great economic interest because it has been estimated that this area contains about 15% of the global recoverable hydrocarbons. Whereas the SE parts of the Zagros have been investigated by detailed geological studies, the NW extent being part of the Republic of Iraq have experienced considerably less attention. In this study we combine field work and remote sensing techniques in order to investigate the interaction of erosion and fold growth in the area NE of Erbil (Kurdistan, Iraq). In particular we focus on the interaction of the transient development of drainage patterns along growing antiforms, which directly reflects the kinematics of progressive fold growth. Detailed geomorphological studies of the Bana Bawi-, Permam- and Safeen fold trains show that these anticlines have not developed from subcylindrical embryonic folds but they have merged from different fold segments that joined laterally during fold amplification. This fold segments with length between 5 and 25 km have been detected by mapping ancient and modern river courses that initially cut the nose of growing folds and eventually got defeated leaving behind a wind gap. Fold segments, propagating in different directions force rivers to join resulting in steep gorges, which dissect the merging fold noses. Along rapidly lateral growing folds (e.g. at the SE end of the Bana Bawi Anticline) we observed "curved wind gaps", a new type of abandoned river course, where form of the wind gap mimics a formed nose of a growing antiform. The inherited curved segments of uplifted curved river courses strongly

  6. 9th International Conference on Computer Recognition Systems

    CERN Document Server

    Jackowski, Konrad; Kurzyński, Marek; Woźniak, Michał; Żołnierek, Andrzej

    2016-01-01

    The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.  .

  7. Instruction of pattern recognition by MATLAB practice 1

    International Nuclear Information System (INIS)

    1999-06-01

    This book describes the pattern recognition by MATLAB practice. It includes possibility and limit of AI, introduction of pattern recognition a vector and matrix, basic status and a probability theory, a random variable and probability distribution, statistical decision theory, data-mining, gaussian mixture model, a nerve cell modeling such as Hebb's learning rule, LMS learning rule, genetic algorithm, dynamic programming and DTW, HMN on Markov model and HMM's three problems and solution, introduction of SVM with KKT condition and margin optimum, kernel trick and MATLAB practice.

  8. Structural Mechanisms of Nucleosome Recognition by Linker Histones.

    Science.gov (United States)

    Zhou, Bing-Rui; Jiang, Jiansheng; Feng, Hanqiao; Ghirlando, Rodolfo; Xiao, T Sam; Bai, Yawen

    2015-08-20

    Linker histones bind to the nucleosome and regulate the structure of chromatin and gene expression. Despite more than three decades of effort, the structural basis of nucleosome recognition by linker histones remains elusive. Here, we report the crystal structure of the globular domain of chicken linker histone H5 in complex with the nucleosome at 3.5 Å resolution, which is validated using nuclear magnetic resonance spectroscopy. The globular domain sits on the dyad of the nucleosome and interacts with both DNA linkers. Our structure integrates results from mutation analyses and previous cross-linking and fluorescence recovery after photobleach experiments, and it helps resolve the long debate on structural mechanisms of nucleosome recognition by linker histones. The on-dyad binding mode of the H5 globular domain is different from the recently reported off-dyad binding mode of Drosophila linker histone H1. We demonstrate that linker histones with different binding modes could fold chromatin to form distinct higher-order structures. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. High-performance speech recognition using consistency modeling

    Science.gov (United States)

    Digalakis, Vassilios; Murveit, Hy; Monaco, Peter; Neumeyer, Leo; Sankar, Ananth

    1994-12-01

    The goal of SRI's consistency modeling project is to improve the raw acoustic modeling component of SRI's DECIPHER speech recognition system and develop consistency modeling technology. Consistency modeling aims to reduce the number of improper independence assumptions used in traditional speech recognition algorithms so that the resulting speech recognition hypotheses are more self-consistent and, therefore, more accurate. At the initial stages of this effort, SRI focused on developing the appropriate base technologies for consistency modeling. We first developed the Progressive Search technology that allowed us to perform large-vocabulary continuous speech recognition (LVCSR) experiments. Since its conception and development at SRI, this technique has been adopted by most laboratories, including other ARPA contracting sites, doing research on LVSR. Another goal of the consistency modeling project is to attack difficult modeling problems, when there is a mismatch between the training and testing phases. Such mismatches may include outlier speakers, different microphones and additive noise. We were able to either develop new, or transfer and evaluate existing, technologies that adapted our baseline genonic HMM recognizer to such difficult conditions.

  10. Handwritten Word Recognition Using Multi-view Analysis

    Science.gov (United States)

    de Oliveira, J. J.; de A. Freitas, C. O.; de Carvalho, J. M.; Sabourin, R.

    This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.

  11. Circuit topology of self-interacting chains: implications for folding and unfolding dynamics.

    Science.gov (United States)

    Mugler, Andrew; Tans, Sander J; Mashaghi, Alireza

    2014-11-07

    Understanding the relationship between molecular structure and folding is a central problem in disciplines ranging from biology to polymer physics and DNA origami. Topology can be a powerful tool to address this question. For a folded linear chain, the arrangement of intra-chain contacts is a topological property because rearranging the contacts requires discontinuous deformations. Conversely, the topology is preserved when continuously stretching the chain while maintaining the contact arrangement. Here we investigate how the folding and unfolding of linear chains with binary contacts is guided by the topology of contact arrangements. We formalize the topology by describing the relations between any two contacts in the structure, which for a linear chain can either be in parallel, in series, or crossing each other. We show that even when other determinants of folding rate such as contact order and size are kept constant, this 'circuit' topology determines folding kinetics. In particular, we find that the folding rate increases with the fractions of parallel and crossed relations. Moreover, we show how circuit topology constrains the conformational phase space explored during folding and unfolding: the number of forbidden unfolding transitions is found to increase with the fraction of parallel relations and to decrease with the fraction of series relations. Finally, we find that circuit topology influences whether distinct intermediate states are present, with crossed contacts being the key factor. The approach presented here can be more generally applied to questions on molecular dynamics, evolutionary biology, molecular engineering, and single-molecule biophysics.

  12. COMMERCIAL FUND, RECOGNITION AND ASSESSMENT

    Directory of Open Access Journals (Sweden)

    VIOREL TRIF

    2010-01-01

    Full Text Available The importance of the immaterial investments within companies nowadays urges the specialists in accounting to find the ways to present more in the elements. In their studies researchers face the controversy reinvestments, as an asset in the balance sheet or an expense in the profit or loss account. The main goal of this paper is to analyze the difficulties in commercial fund. In the first part we will analyze various definitions of the problems concerning the commercial fund’s recognition and assessment. The paper also suggests that investments are really social and economic problems.

  13. ZONING DESIGN FOR HAND­WRITTEN NUMERAL RECOGNITION

    NARCIS (Netherlands)

    Lecce Di, V.; Dimauro, G.; Guerriero, A.; Impedovo, S.; Pirlo, G.; Salzo, A.

    2004-01-01

    In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper zoning is considered as the result of an optimisation problem and a new technique is presented for automatic zoning. More precisely, local analysis of feature

  14. RECOGNITION AND VERIFICATION OF TOUCHING HANDWRITTEN NUMERALS

    NARCIS (Netherlands)

    Zhou, J.; Kryzak, A.; Suen, C.Y.

    2004-01-01

    In the field of financial document processing, recognition of touching handwritten numerals has been limited by lack of good benchmarking databases and low reliability of algorithms. This paper addresses the efforts toward solving the two problems. Two databases IRIS-Bell\\\\\\'98 and TNIST are

  15. Are Haar-like Rectangular Features for Biometric Recognition Reducible?

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

  16. Combinatorial pattern discovery approach for the folding trajectory analysis of a beta-hairpin.

    Directory of Open Access Journals (Sweden)

    Laxmi Parida

    2005-06-01

    Full Text Available The study of protein folding mechanisms continues to be one of the most challenging problems in computational biology. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus various reaction coordinates, such as the fraction of native contacts, the radius of gyration, RMSD from the native structure, and so on. In this paper, we present a combinatorial pattern discovery approach toward understanding the global state changes during the folding process. This is a first step toward an unsupervised (and perhaps eventually automated approach toward identification of global states. The approach is based on computing biclusters (or patterned clusters-each cluster is a combination of various reaction coordinates, and its signature pattern facilitates the computation of the Z-score for the cluster. For this discovery process, we present an algorithm of time complexity c in RO((N + nm log n, where N is the size of the output patterns and (n x m is the size of the input with n time frames and m reaction coordinates. To date, this is the best time complexity for this problem. We next apply this to a beta-hairpin folding trajectory and demonstrate that this approach extracts crucial information about protein folding intermediate states and mechanism. We make three observations about the approach: (1 The method recovers states previously obtained by visually analyzing free energy surfaces. (2 It also succeeds in extracting meaningful patterns and structures that had been overlooked in previous works, which provides a better understanding of the folding mechanism of the beta-hairpin. These new patterns also interconnect various states in existing free energy surfaces versus different reaction coordinates. (3 The approach does not require calculating the free energy values, yet it offers an analysis comparable to, and sometimes better than, the methods that use free energy landscapes, thus validating the

  17. Combinatorial Pattern Discovery Approach for the Folding Trajectory Analysis of a beta-Hairpin.

    Directory of Open Access Journals (Sweden)

    2005-06-01

    Full Text Available The study of protein folding mechanisms continues to be one of the most challenging problems in computational biology. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus various reaction coordinates, such as the fraction of native contacts, the radius of gyration, RMSD from the native structure, and so on. In this paper, we present a combinatorial pattern discovery approach toward understanding the global state changes during the folding process. This is a first step toward an unsupervised (and perhaps eventually automated approach toward identification of global states. The approach is based on computing biclusters (or patterned clusters-each cluster is a combination of various reaction coordinates, and its signature pattern facilitates the computation of the Z-score for the cluster. For this discovery process, we present an algorithm of time complexity cinRO((N + nm log n, where N is the size of the output patterns and (n x m is the size of the input with n time frames and m reaction coordinates. To date, this is the best time complexity for this problem. We next apply this to a beta-hairpin folding trajectory and demonstrate that this approach extracts crucial information about protein folding intermediate states and mechanism. We make three observations about the approach: (1 The method recovers states previously obtained by visually analyzing free energy surfaces. (2 It also succeeds in extracting meaningful patterns and structures that had been overlooked in previous works, which provides a better understanding of the folding mechanism of the beta-hairpin. These new patterns also interconnect various states in existing free energy surfaces versus different reaction coordinates. (3 The approach does not require calculating the free energy values, yet it offers an analysis comparable to, and sometimes better than, the methods that use free energy landscapes, thus validating the

  18. Cation-induced folding of alginate-bearing bilayer gels: an unusual example of spontaneous folding along the long axis.

    Science.gov (United States)

    Athas, Jasmin C; Nguyen, Catherine P; Kummar, Shailaa; Raghavan, Srinivasa R

    2018-04-04

    The spontaneous folding of flat gel films into tubes is an interesting example of self-assembly. Typically, a rectangular film folds along its short axis when forming a tube; folding along the long axis has been seen only in rare instances when the film is constrained. Here, we report a case where the same free-swelling gel film folds along either its long or short axis depending on the concentration of a solute. Our gels are sandwiches (bilayers) of two layers: a passive layer of cross-linked N,N'-dimethylyacrylamide (DMAA) and an active layer of cross-linked DMAA that also contains chains of the biopolymer alginate. Multivalent cations like Ca2+ and Cu2+ induce these bilayer gels to fold into tubes. The folding occurs instantly when a flat film of the gel is introduced into a solution of these cations. The likely cause for folding is that the active layer stiffens and shrinks (because the alginate chains in it get cross-linked by the cations) whereas the passive layer is unaffected. The resulting mismatch in swelling degree between the two layers creates internal stresses that drive folding. Cations that are incapable of cross-linking alginate, such as Na+ and Mg2+, do not induce gel folding. Moreover, the striking aspect is the direction of folding. When the Ca2+ concentration is high (100 mM or higher), the gels fold along their long axis, whereas when the Ca2+ concentration is low (40 to 80 mM), the gels fold along their short axis. We hypothesize that the folding axis is dictated by the inhomogeneous nature of alginate-cation cross-linking, i.e., that the edges get cross-linked before the faces of the gel. At high Ca2+ concentration, the stiffer edges constrain the folding; in turn, the gel folds such that the longer edges are deformed less, which explains the folding along the long axis. At low Ca2+ concentration, the edges and the faces of the gel are more similar in their degree of cross-linking; therefore, the gel folds along its short axis. An analogy

  19. Examination of soldier target recognition with direct view optics

    Science.gov (United States)

    Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

    2017-10-01

    Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

  20. Pathways to diagnosis: exploring the experiences of problem recognition and obtaining a dementia diagnosis among Anglo-Canadians.

    Science.gov (United States)

    Leung, Karen K; Finlay, Juli; Silvius, James L; Koehn, Sharon; McCleary, Lynn; Cohen, Carole A; Hum, Susan; Garcia, Linda; Dalziel, William; Emerson, Victor F; Pimlott, Nicholas J G; Persaud, Malini; Kozak, Jean; Drummond, Neil

    2011-07-01

    Increasing evidence suggests that early diagnosis and management of dementia-related symptoms may improve the quality of life for patients and their families. However, individuals may wait from 1-3 years from the onset of symptoms before receiving a diagnosis. The objective of this qualitative study was to explore the perceptions and experiences of problem recognition, and the process of obtaining a diagnosis among individuals with early-stage dementia and their primary carers. From 2006-2009, six Anglo-Canadians with dementia and seven of their carers were recruited from the Alzheimer's Society of Calgary to participate in semi-structured interviews. Using an inductive, thematic approach to the analysis, five major themes were identified: becoming aware of memory problems, attributing meanings to symptoms, initiating help-seeking, acknowledging the severity of cognitive changes and finally obtaining a definitive diagnosis. Individuals with dementia reported noticing memory difficulties earlier than their carers. However, initial symptoms were perceived as ambiguous, and were normalised and attributed to concurrent health problems. The diagnostic process was typically characterised by multiple visits and interactions with health professionals, and a diagnosis was obtained as more severe cognitive deficits emerged. Throughout the diagnostic pathway, carers played dynamic roles. Carers initially served as a source of encouragement to seek help, but they eventually became actively involved over concerns about alternative diagnoses and illness management. A better understanding of the pre-diagnosis period, and the complex interactions between people's beliefs and attributions about symptoms, may elucidate some of the barriers as well as strategies to promote a timelier dementia diagnosis. © 2011 Blackwell Publishing Ltd.

  1. Folding of DsbB in mixed micelles

    DEFF Research Database (Denmark)

    Otzen, Daniel

    2003-01-01

    state and an unfolding intermediate that accumulates only under unfolding conditions at high mole fractions of SDS. The stability of DsbB is around 4.4 kcal/mol in DM, and this is halved upon reduction of the two periplasmic disulfide bonds, and is sensitive to mutagenesis. With the caveat that kinetic...... is sensitive to changes in lipid and detergent composition. As an attempt to overcome this problem, I present a kinetic analysis of the folding of a membrane protein, disulfide bond reducing protein B (DsbB), in a mixed micelle system consisting of varying molar ratios of sodium dodecyl sulfate (SDS...

  2. Employee recognition: a key to motivation.

    Science.gov (United States)

    Magnus, M

    1981-02-01

    Productivity--why it's low and how to enhance it--is on everyone's mind these days. A major component of productivity is employee satisfaction. If an employee is dissatisfied, feels unappreciated or under-compensated, that employee will not perform to the best of his or her ability. How is the personnel administrator to address this pressing problem? One answer that emerges is employee recognition programs. In many cases, properly run recognition programs can boost awareness of the organization, build employee pride, raise morale and, ultimately, increase productivity. As some of our respondents observed, higher salary is not the best answer. While a larger paycheck is always appreciated, everyone's pride is boosted by a public demonstration of appreciation.

  3. Artificial intelligence tools for pattern recognition

    Science.gov (United States)

    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.

  4. Speech Recognition Technology for Disabilities Education

    Science.gov (United States)

    Tang, K. Wendy; Kamoua, Ridha; Sutan, Victor; Farooq, Omer; Eng, Gilbert; Chu, Wei Chern; Hou, Guofeng

    2005-01-01

    Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual…

  5. Spherical images and inextensible curved folding

    Science.gov (United States)

    Seffen, Keith A.

    2018-02-01

    In their study, Duncan and Duncan [Proc. R. Soc. London A 383, 191 (1982), 10.1098/rspa.1982.0126] calculate the shape of an inextensible surface folded in two about a general curve. They find the analytical relationships between pairs of generators linked across the fold curve, the shape of the original path, and the fold angle variation along it. They present two special cases of generator layouts for which the fold angle is uniform or the folded curve remains planar, for simplifying practical folding in sheet-metal processes. We verify their special cases by a graphical treatment according to a method of Gauss. We replace the fold curve by a piecewise linear path, which connects vertices of intersecting pairs of hinge lines. Inspired by the d-cone analysis by Farmer and Calladine [Int. J. Mech. Sci. 47, 509 (2005), 10.1016/j.ijmecsci.2005.02.013], we construct the spherical images for developable folding of successive vertices: the operating conditions of the special cases in Duncan and Duncan are then revealed straightforwardly by the geometric relationships between the images. Our approach may be used to synthesize folding patterns for novel deployable and shape-changing surfaces without need of complex calculation.

  6. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Science.gov (United States)

    2010-01-01

    ...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

  7. Folded diagram theory, time-dependent approach of Johnson and Baranger

    International Nuclear Information System (INIS)

    Johnson, M.B.

    1975-01-01

    The folded diagram expansion of Brandow and extensively developed by Johnson and Baranger is discussed in detail. The time-dependent approach is reviewed through Feynman-Goldstone diagrams to establish the conventions used. The problem of calculating the effective interaction for nuclei beyond 208 Pb is then considered as an example. Finally, examples are given which show how to do the time integrations. (17 figures) (SDF)

  8. Self-similar voiding solutions for a single layered model of folding rocks

    NARCIS (Netherlands)

    Dodwell, T.J.; Peletier, M.A.; Budd, C.J.; Hunt, G.W.

    2011-01-01

    In this paper we derive an obstacle problem with a free boundary to describe the formation of voids at areas of intense geological folding. An elastic layer is forced by overburden pressure against a V-shaped rigid obstacle. Energy minimization leads to representation as a non-linear fourth-order

  9. An application of viola jones method for face recognition for absence process efficiency

    Science.gov (United States)

    Rizki Damanik, Rudolfo; Sitanggang, Delima; Pasaribu, Hendra; Siagian, Hendrik; Gulo, Frisman

    2018-04-01

    Absence was a list of documents that the company used to record the attendance time of each employee. The most common problem in a fingerprint machine is the identification of a slow sensor or a sensor not recognizing a finger. The employees late to work because they get difficulties at fingerprint system, they need about 3 – 5 minutes to absence when the condition of finger is wet or not fit. To overcome this problem, this research tried to utilize facial recognition for attendance process. The method used for facial recognition was Viola Jones. Through the processing phase of the RGB face image was converted into a histogram equalization face image for the next stage of recognition. The result of this research was the absence process could be done less than 1 second with a maximum slope of ± 700 and a distance of 20-200 cm. After implement facial recognition the process of absence is more efficient, just take less 1 minute to absence.

  10. General tensor discriminant analysis and gabor features for gait recognition.

    Science.gov (United States)

    Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

    2007-10-01

    The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine

  11. Deficits in facial emotion recognition indicate behavioral changes and impaired self-awareness after moderate to severe traumatic brain injury.

    Science.gov (United States)

    Spikman, Jacoba M; Milders, Maarten V; Visser-Keizer, Annemarie C; Westerhof-Evers, Herma J; Herben-Dekker, Meike; van der Naalt, Joukje

    2013-01-01

    Traumatic brain injury (TBI) is a leading cause of disability, specifically among younger adults. Behavioral changes are common after moderate to severe TBI and have adverse consequences for social and vocational functioning. It is hypothesized that deficits in social cognition, including facial affect recognition, might underlie these behavioral changes. Measurement of behavioral deficits is complicated, because the rating scales used rely on subjective judgement, often lack specificity and many patients provide unrealistically positive reports of their functioning due to impaired self-awareness. Accordingly, it is important to find performance based tests that allow objective and early identification of these problems. In the present study 51 moderate to severe TBI patients in the sub-acute and chronic stage were assessed with a test for emotion recognition (FEEST) and a questionnaire for behavioral problems (DEX) with a self and proxy rated version. Patients performed worse on the total score and on the negative emotion subscores of the FEEST than a matched group of 31 healthy controls. Patients also exhibited significantly more behavioral problems on both the DEX self and proxy rated version, but proxy ratings revealed more severe problems. No significant correlation was found between FEEST scores and DEX self ratings. However, impaired emotion recognition in the patients, and in particular of Sadness and Anger, was significantly correlated with behavioral problems as rated by proxies and with impaired self-awareness. This is the first study to find these associations, strengthening the proposed recognition of social signals as a condition for adequate social functioning. Hence, deficits in emotion recognition can be conceived as markers for behavioral problems and lack of insight in TBI patients. This finding is also of clinical importance since, unlike behavioral problems, emotion recognition can be objectively measured early after injury, allowing for early

  12. Deficits in facial emotion recognition indicate behavioral changes and impaired self-awareness after moderate to severe traumatic brain injury.

    Directory of Open Access Journals (Sweden)

    Jacoba M Spikman

    Full Text Available Traumatic brain injury (TBI is a leading cause of disability, specifically among younger adults. Behavioral changes are common after moderate to severe TBI and have adverse consequences for social and vocational functioning. It is hypothesized that deficits in social cognition, including facial affect recognition, might underlie these behavioral changes. Measurement of behavioral deficits is complicated, because the rating scales used rely on subjective judgement, often lack specificity and many patients provide unrealistically positive reports of their functioning due to impaired self-awareness. Accordingly, it is important to find performance based tests that allow objective and early identification of these problems. In the present study 51 moderate to severe TBI patients in the sub-acute and chronic stage were assessed with a test for emotion recognition (FEEST and a questionnaire for behavioral problems (DEX with a self and proxy rated version. Patients performed worse on the total score and on the negative emotion subscores of the FEEST than a matched group of 31 healthy controls. Patients also exhibited significantly more behavioral problems on both the DEX self and proxy rated version, but proxy ratings revealed more severe problems. No significant correlation was found between FEEST scores and DEX self ratings. However, impaired emotion recognition in the patients, and in particular of Sadness and Anger, was significantly correlated with behavioral problems as rated by proxies and with impaired self-awareness. This is the first study to find these associations, strengthening the proposed recognition of social signals as a condition for adequate social functioning. Hence, deficits in emotion recognition can be conceived as markers for behavioral problems and lack of insight in TBI patients. This finding is also of clinical importance since, unlike behavioral problems, emotion recognition can be objectively measured early after injury

  13. Evaluating deep learning architectures for Speech Emotion Recognition.

    Science.gov (United States)

    Fayek, Haytham M; Lech, Margaret; Cavedon, Lawrence

    2017-08-01

    Speech Emotion Recognition (SER) can be regarded as a static or dynamic classification problem, which makes SER an excellent test bed for investigating and comparing various deep learning architectures. We describe a frame-based formulation to SER that relies on minimal speech processing and end-to-end deep learning to model intra-utterance dynamics. We use the proposed SER system to empirically explore feed-forward and recurrent neural network architectures and their variants. Experiments conducted illuminate the advantages and limitations of these architectures in paralinguistic speech recognition and emotion recognition in particular. As a result of our exploration, we report state-of-the-art results on the IEMOCAP database for speaker-independent SER and present quantitative and qualitative assessments of the models' performances. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Combining heterogenous features for 3D hand-held object recognition

    Science.gov (United States)

    Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

    2014-10-01

    Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

  15. Transfer learning for bimodal biometrics recognition

    Science.gov (United States)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  16. Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

    NARCIS (Netherlands)

    Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

    2015-01-01

    Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

  17. Identification of a key structural element for protein folding within beta-hairpin turns.

    Science.gov (United States)

    Kim, Jaewon; Brych, Stephen R; Lee, Jihun; Logan, Timothy M; Blaber, Michael

    2003-05-09

    Specific residues in a polypeptide may be key contributors to the stability and foldability of the unique native structure. Identification and prediction of such residues is, therefore, an important area of investigation in solving the protein folding problem. Atypical main-chain conformations can help identify strains within a folded protein, and by inference, positions where unique amino acids may have a naturally high frequency of occurrence due to favorable contributions to stability and folding. Non-Gly residues located near the left-handed alpha-helical region (L-alpha) of the Ramachandran plot are a potential indicator of structural strain. Although many investigators have studied mutations at such positions, no consistent energetic or kinetic contributions to stability or folding have been elucidated. Here we report a study of the effects of Gly, Ala and Asn substitutions found within the L-alpha region at a characteristic position in defined beta-hairpin turns within human acidic fibroblast growth factor, and demonstrate consistent effects upon stability and folding kinetics. The thermodynamic and kinetic data are compared to available data for similar mutations in other proteins, with excellent agreement. The results have identified that Gly at the i+3 position within a subset of beta-hairpin turns is a key contributor towards increasing the rate of folding to the native state of the polypeptide while leaving the rate of unfolding largely unchanged.

  18. Text recognition and correction for automated data collection by mobile devices

    Science.gov (United States)

    Ozarslan, Suleyman; Eren, P. Erhan

    2014-03-01

    Participatory sensing is an approach which allows mobile devices such as mobile phones to be used for data collection, analysis and sharing processes by individuals. Data collection is the first and most important part of a participatory sensing system, but it is time consuming for the participants. In this paper, we discuss automatic data collection approaches for reducing the time required for collection, and increasing the amount of collected data. In this context, we explore automated text recognition on images of store receipts which are captured by mobile phone cameras, and the correction of the recognized text. Accordingly, our first goal is to evaluate the performance of the Optical Character Recognition (OCR) method with respect to data collection from store receipt images. Images captured by mobile phones exhibit some typical problems, and common image processing methods cannot handle some of them. Consequently, the second goal is to address these types of problems through our proposed Knowledge Based Correction (KBC) method used in support of the OCR, and also to evaluate the KBC method with respect to the improvement on the accurate recognition rate. Results of the experiments show that the KBC method improves the accurate data recognition rate noticeably.

  19. Human Activity Recognition Using Hierarchically-Mined Feature Constellations

    NARCIS (Netherlands)

    Oikonomopoulos, A.; Pantic, Maja

    In this paper we address the problem of human activity modelling and recognition by means of a hierarchical representation of mined dense spatiotemporal features. At each level of the hierarchy, the proposed method selects feature constellations that are increasingly discriminative and

  20. The recognition of facial emotion expressions in Parkinson's disease.

    Science.gov (United States)

    Assogna, Francesca; Pontieri, Francesco E; Caltagirone, Carlo; Spalletta, Gianfranco

    2008-11-01

    A limited number of studies in Parkinson's Disease (PD) suggest a disturbance of recognition of facial emotion expressions. In particular, disgust recognition impairment has been reported in unmedicated and medicated PD patients. However, the results are rather inconclusive in the definition of the degree and the selectivity of emotion recognition impairment, and an associated impairment of almost all basic facial emotions in PD is also described. Few studies have investigated the relationship with neuropsychiatric and neuropsychological symptoms with mainly negative results. This inconsistency may be due to many different problems, such as emotion assessment, perception deficit, cognitive impairment, behavioral symptoms, illness severity and antiparkinsonian therapy. Here we review the clinical characteristics and neural structures involved in the recognition of specific facial emotion expressions, and the plausible role of dopamine transmission and dopamine replacement therapy in these processes. It is clear that future studies should be directed to clarify all these issues.

  1. Recent developments in the theory of protein folding: searching for the global energy minimum.

    Science.gov (United States)

    Scheraga, H A

    1996-04-16

    Statistical mechanical theories and computer simulation are being used to gain an understanding of the fundamental features of protein folding. A major obstacle in the computation of protein structures is the multiple-minima problem arising from the existence of many local minima in the multidimensional energy landscape of the protein. This problem has been surmounted for small open-chain and cyclic peptides, and for regular-repeating sequences of models of fibrous proteins. Progress is being made in resolving this problem for globular proteins.

  2. Recognition of knowledge – A step towards optimization of education

    Directory of Open Access Journals (Sweden)

    Vanda Rebolj

    2011-03-01

    In her presentation of the knowledge recognition procedures, the author relies on constructivist theories on knowledge and highlights the importance of the achieved levels of knowledge, paying equal attention to the low levels (skills, higher levels and the highest levels (problem­solving, none of which should be omitted in the assessment and recognition procedures. The author then presents the experience in knowledge recognition gained in the last five years by several colleges providing part­time studies, starting with a course in accounting and proceeding with other programmes. It is essential that knowledge recognition should not be pushed into the domain of experts or become an administrative procedure; it must remain part of the regular teaching procedure and under control of the teacher. This requires implementation of appropriate teacher training. Despite the fact that the recognition procedures developed so far have proved to be valid and have gained on credibility, numerous new research issues are being raised in this field.

  3. Real-Time Multiview Recognition of Human Gestures by Distributed Image Processing

    Directory of Open Access Journals (Sweden)

    Sato Kosuke

    2010-01-01

    Full Text Available Since a gesture involves a dynamic and complex motion, multiview observation and recognition are desirable. For the better representation of gestures, one needs to know, in the first place, from which views a gesture should be observed. Furthermore, it becomes increasingly important how the recognition results are integrated when larger numbers of camera views are considered. To investigate these problems, we propose a framework under which multiview recognition is carried out, and an integration scheme by which the recognition results are integrated online and in realtime. For performance evaluation, we use the ViHASi (Virtual Human Action Silhouette public image database as a benchmark and our Japanese sign language (JSL image database that contains 18 kinds of hand signs. By examining the recognition rates of each gesture for each view, we found gestures that exhibit view dependency and the gestures that do not. Also, we found that the view dependency itself could vary depending on the target gesture sets. By integrating the recognition results of different views, our swarm-based integration provides more robust and better recognition performance than individual fixed-view recognition agents.

  4. Towards The Deep Model : Understanding Visual Recognition Through Computational Models

    OpenAIRE

    Wang, Panqu

    2017-01-01

    Understanding how visual recognition is achieved in the human brain is one of the most fundamental questions in vision research. In this thesis I seek to tackle this problem from a neurocomputational modeling perspective. More specifically, I build machine learning-based models to simulate and explain cognitive phenomena related to human visual recognition, and I improve computational models using brain-inspired principles to excel at computer vision tasks.I first describe how a neurocomputat...

  5. Convolutional neural networks and face recognition task

    Science.gov (United States)

    Sochenkova, A.; Sochenkov, I.; Makovetskii, A.; Vokhmintsev, A.; Melnikov, A.

    2017-09-01

    Computer vision tasks are remaining very important for the last couple of years. One of the most complicated problems in computer vision is face recognition that could be used in security systems to provide safety and to identify person among the others. There is a variety of different approaches to solve this task, but there is still no universal solution that would give adequate results in some cases. Current paper presents following approach. Firstly, we extract an area containing face, then we use Canny edge detector. On the next stage we use convolutional neural networks (CNN) to finally solve face recognition and person identification task.

  6. Automatic anatomy recognition on CT images with pathology

    Science.gov (United States)

    Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

    2016-03-01

    Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

  7. Quantification of Porcine Vocal Fold Geometry.

    Science.gov (United States)

    Stevens, Kimberly A; Thomson, Scott L; Jetté, Marie E; Thibeault, Susan L

    2016-07-01

    The aim of this study was to quantify porcine vocal fold medial surface geometry and three-dimensional geometric distortion induced by freezing the larynx, especially in the region of the vocal folds. The medial surface geometries of five excised porcine larynges were quantified and reported. Five porcine larynges were imaged in a micro-CT scanner, frozen, and rescanned. Segmentations and three-dimensional reconstructions were used to quantify and characterize geometric features. Comparisons were made with geometry data previously obtained using canine and human vocal folds as well as geometries of selected synthetic vocal fold models. Freezing induced an overall expansion of approximately 5% in the transverse plane and comparable levels of nonuniform distortion in sagittal and coronal planes. The medial surface of the porcine vocal folds was found to compare reasonably well with other geometries, although the compared geometries exhibited a notable discrepancy with one set of published human female vocal fold geometry. Porcine vocal folds are qualitatively geometrically similar to data available for canine and human vocal folds, as well as commonly used models. Freezing of tissue in the larynx causes distortion of around 5%. The data can provide direction in estimating uncertainty due to bulk distortion of tissue caused by freezing, as well as quantitative geometric data that can be directly used in developing vocal fold models. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  8. Graph-representation of oxidative folding pathways

    Directory of Open Access Journals (Sweden)

    Kaján László

    2005-01-01

    Full Text Available Abstract Background The process of oxidative folding combines the formation of native disulfide bond with conformational folding resulting in the native three-dimensional fold. Oxidative folding pathways can be described in terms of disulfide intermediate species (DIS which can also be isolated and characterized. Each DIS corresponds to a family of folding states (conformations that the given DIS can adopt in three dimensions. Results The oxidative folding space can be represented as a network of DIS states interconnected by disulfide interchange reactions that can either create/abolish or rearrange disulfide bridges. We propose a simple 3D representation wherein the states having the same number of disulfide bridges are placed on separate planes. In this representation, the shuffling transitions are within the planes, and the redox edges connect adjacent planes. In a number of experimentally studied cases (bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor, the observed intermediates appear as part of contiguous oxidative folding pathways. Conclusions Such networks can be used to visualize folding pathways in terms of the experimentally observed intermediates. A simple visualization template written for the Tulip package http://www.tulip-software.org/ can be obtained from V.A.

  9. Robust Peak Recognition in Intracranial Pressure Signals

    Directory of Open Access Journals (Sweden)

    Bergsneider Marvin

    2010-10-01

    Full Text Available Abstract Background The waveform morphology of intracranial pressure pulses (ICP is an essential indicator for monitoring, and forecasting critical intracranial and cerebrovascular pathophysiological variations. While current ICP pulse analysis frameworks offer satisfying results on most of the pulses, we observed that the performance of several of them deteriorates significantly on abnormal, or simply more challenging pulses. Methods This paper provides two contributions to this problem. First, it introduces MOCAIP++, a generic ICP pulse processing framework that generalizes MOCAIP (Morphological Clustering and Analysis of ICP Pulse. Its strength is to integrate several peak recognition methods to describe ICP morphology, and to exploit different ICP features to improve peak recognition. Second, it investigates the effect of incorporating, automatically identified, challenging pulses into the training set of peak recognition models. Results Experiments on a large dataset of ICP signals, as well as on a representative collection of sampled challenging ICP pulses, demonstrate that both contributions are complementary and significantly improve peak recognition performance in clinical conditions. Conclusion The proposed framework allows to extract more reliable statistics about the ICP waveform morphology on challenging pulses to investigate the predictive power of these pulses on the condition of the patient.

  10. Combining Illumination Normalization Methods for Better Face Recognition

    NARCIS (Netherlands)

    Boom, B.J.; Tao, Q.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2009-01-01

    Face Recognition under uncontrolled illumination conditions is partly an unsolved problem. There are two categories of illumination normalization methods. The first category performs a local preprocessing, where they correct a pixel value based on a local neighborhood in the images. The second

  11. A survey on vision-based human action recognition

    NARCIS (Netherlands)

    Poppe, Ronald Walter

    Vision-based human action recognition is the process of labeling image sequences with action labels. Robust solutions to this problem have applications in domains such as visual surveillance, video retrieval and human–computer interaction. The task is challenging due to variations in motion

  12. An improved Four-Russians method and sparsified Four-Russians algorithm for RNA folding.

    Science.gov (United States)

    Frid, Yelena; Gusfield, Dan

    2016-01-01

    The basic RNA secondary structure prediction problem or single sequence folding problem (SSF) was solved 35 years ago by a now well-known [Formula: see text]-time dynamic programming method. Recently three methodologies-Valiant, Four-Russians, and Sparsification-have been applied to speedup RNA secondary structure prediction. The sparsification method exploits two properties of the input: the number of subsequence Z with the endpoints belonging to the optimal folding set and the maximum number base-pairs L. These sparsity properties satisfy [Formula: see text] and [Formula: see text], and the method reduces the algorithmic running time to O(LZ). While the Four-Russians method utilizes tabling partial results. In this paper, we explore three different algorithmic speedups. We first expand the reformulate the single sequence folding Four-Russians [Formula: see text]-time algorithm, to utilize an on-demand lookup table. Second, we create a framework that combines the fastest Sparsification and new fastest on-demand Four-Russians methods. This combined method has worst-case running time of [Formula: see text], where [Formula: see text] and [Formula: see text]. Third we update the Four-Russians formulation to achieve an on-demand [Formula: see text]-time parallel algorithm. This then leads to an asymptotic speedup of [Formula: see text] where [Formula: see text] and [Formula: see text] the number of subsequence with the endpoint j belonging to the optimal folding set. The on-demand formulation not only removes all extraneous computation and allows us to incorporate more realistic scoring schemes, but leads us to take advantage of the sparsity properties. Through asymptotic analysis and empirical testing on the base-pair maximization variant and a more biologically informative scoring scheme, we show that this Sparse Four-Russians framework is able to achieve a speedup on every problem instance, that is asymptotically never worse, and empirically better than achieved by

  13. Understanding ensemble protein folding at atomic detail

    International Nuclear Information System (INIS)

    Wallin, Stefan; Shakhnovich, Eugene I

    2008-01-01

    Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

  14. Writer and writing-style classification in the recognition of online handwriting

    NARCIS (Netherlands)

    Schomaker, Lambertus; Abbink, Gerben; Selen, Sjoerd

    1994-01-01

    One of the problems in the automatic recognition of cursive and mixed-cursive handwriting is the large variation of handwriting styles in a population. Automatic detection of the generic handwriting style, or identification of the writer could be useful to counteract this problem. The starting point

  15. Vocal fold injection medialization laryngoplasty.

    Science.gov (United States)

    Modi, Vikash K

    2012-01-01

    Unilateral vocal fold paralysis (UVFP) can cause glottic insufficiency that can result in hoarseness, chronic cough, dysphagia, and/or aspiration. In rare circumstances, UVFP can cause airway obstruction necessitating a tracheostomy. The treatment options for UVFP include observation, speech therapy, vocal fold injection medialization laryngoplasty, thyroplasty, and laryngeal reinnervation. In this chapter, the author will discuss the technique of vocal fold injection for medialization of a UVFP. Copyright © 2012 S. Karger AG, Basel.

  16. Intelligent Facial Recognition Systems: Technology advancements for security applications

    Energy Technology Data Exchange (ETDEWEB)

    Beer, C.L.

    1993-07-01

    Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

  17. Optimal pattern synthesis for speech recognition based on principal component analysis

    Science.gov (United States)

    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.

  18. Functional results after external vocal fold medialization thyroplasty with the titanium vocal fold medialization implant.

    Science.gov (United States)

    Schneider, Berit; Denk, Doris-Maria; Bigenzahn, Wolfgang

    2003-04-01

    A persistent insufficiency of glottal closure is mostly a consequence of a unilateral vocal fold movement impairment. It can also be caused by vocal fold atrophy or scarring processes with regular bilateral respiratory vocal fold function. Because of consequential voice, breathing, and swallowing impairments, a functional surgical treatment is required. The goal of the study was to outline the functional results after medialization thyroplasty with the titanium vocal fold medialization implant according to Friedrich. In the period of 1999 to 2001, an external vocal fold medialization using the titanium implant was performed on 28 patients (12 women and 16 men). The patients were in the age range of 19 to 84 years. Twenty-two patients had a paralysis of the left-side vocal fold, and six patients, of the right-side vocal fold. Detailed functional examinations were executed on all patients before and after the surgery: perceptive voice sound analysis according to the "roughness, breathiness, and hoarseness" method, judgment of the s/z ratio and voice dysfunction index, voice range profile measurements, videostroboscopy, and pulmonary function tests. In case of dysphagia/aspiration, videofluoroscopy of swallowing was also performed. The respective data were statistically analyzed (paired t test, Wilcoxon-test). All patients reported on improvement of voice, swallowing, and breathing functions postoperatively. Videostroboscopy revealed an almost complete glottal closure after surgery in all of the patients. All voice-related parameters showed a significant improvement. An increase of the laryngeal resistance by the medialization procedure could be excluded by analysis of the pulmonary function test. The results confirm the external medialization of the vocal folds as an adequate method in the therapy of voice, swallowing, and breathing impairment attributable to an insufficient glottal closure. The titanium implant offers, apart from good tissue tolerability, the

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

    Science.gov (United States)

    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.

  20. New forms of conflict resolution: transformation, empowerment and recognition

    Directory of Open Access Journals (Sweden)

    Vicent Martínez Guzmán

    2006-04-01

    Full Text Available This paper uses the scientific field of Conflict Studies, within the framework of Peace Research. It is based on a philosophic conception of the “human condition” and is guided by the notions of empowerment and recognition as tools suitable for the pacific transformation of conflicts. It also looks at the relation of the doctrine of recognition with the problem of inequality and with a political philosophy of justice. It maintains that one cannot separate policies of recognition, more closely linked to identity and culture, from policies of justice, more attent to the pacific transformation of human inequalities, poverty, indigence, marginalization and exclusion. As an example of this proposal, it uses the most recent report of the United Nations Human Development Program.

  1. Preliminary Analysis of Automatic Speech Recognition and Synthesis Technology.

    Science.gov (United States)

    1983-05-01

    ANDELES CA 0 SHDAP ET AL MAY 93 UNCISSIFED UCG -020-8 MDA04-8’-C-415F/ 17/2 N mE = h IEEE 11111 10’ ~ 2.0 11-41 & 11111I25IID MICROCOPY RESOLUTION TEST...speech. Private industry, which sees a major market for improved speech recognition systems, is attempting to solve the problems involved in...manufacturer is able to market such a recognition system. A second requirement for the spotting of keywords in distress signals concerns the need for a

  2. In-the-wild facial expression recognition in extreme poses

    Science.gov (United States)

    Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

    2018-04-01

    In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

  3. Intelligent fault recognition strategy based on adaptive optimized multiple centers

    Science.gov (United States)

    Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

    2018-06-01

    For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

  4. Pattern recognition approach to nondestructive evaluation of materials

    International Nuclear Information System (INIS)

    Chen, C.H.

    1987-01-01

    In this paper, a pattern recognition approach to the ultrasonic nondestructive evaluation of materials is examined. Emphasis is placed on identifying effective features from time and frequency domains, correlation functions and impulse responses to classify aluminum plate specimens into three major defect geometry categories: flat, angular cut and circular hole defects. A multi-stage classification procedure is developed which can further determine the angles and sizes for defect characterization and classification. The research clearly demonstrates that the pattern recognition approach can significantly improve the nondestructive material evaluation capability of the ultrasonic methods without resorting to the solution of highly complex mathematical inverse problems

  5. A comparison of RNA folding measures

    Directory of Open Access Journals (Sweden)

    Gardner Paul P

    2005-10-01

    Full Text Available Abstract Background In the last few decades there has been a great deal of discussion concerning whether or not noncoding RNA sequences (ncRNAs fold in a more well-defined manner than random sequences. In this paper, we investigate several existing measures for how well an RNA sequence folds, and compare the behaviour of these measures over a large range of Rfam ncRNA families. Such measures can be useful in, for example, identifying novel ncRNAs, and indicating the presence of alternate RNA foldings. Results Our analysis shows that ncRNAs, but not mRNAs, in general have lower minimal free energy (MFE than random sequences with the same dinucleotide frequency. Moreover, even when the MFE is significant, many ncRNAs appear to not have a unique fold, but rather several alternative folds, at least when folded in silico. Furthermore, we find that the six investigated measures are correlated to varying degrees. Conclusion Due to the correlations between the different measures we find that it is sufficient to use only two of them in RNA folding studies, one to test if the sequence in question has lower energy than a random sequence with the same dinucleotide frequency (the Z-score and the other to see if the sequence has a unique fold (the average base-pair distance, D.

  6. Facial emotion recognition in paranoid schizophrenia and autism spectrum disorder.

    Science.gov (United States)

    Sachse, Michael; Schlitt, Sabine; Hainz, Daniela; Ciaramidaro, Angela; Walter, Henrik; Poustka, Fritz; Bölte, Sven; Freitag, Christine M

    2014-11-01

    Schizophrenia (SZ) and autism spectrum disorder (ASD) share deficits in emotion processing. In order to identify convergent and divergent mechanisms, we investigated facial emotion recognition in SZ, high-functioning ASD (HFASD), and typically developed controls (TD). Different degrees of task difficulty and emotion complexity (face, eyes; basic emotions, complex emotions) were used. Two Benton tests were implemented in order to elicit potentially confounding visuo-perceptual functioning and facial processing. Nineteen participants with paranoid SZ, 22 with HFASD and 20 TD were included, aged between 14 and 33 years. Individuals with SZ were comparable to TD in all obtained emotion recognition measures, but showed reduced basic visuo-perceptual abilities. The HFASD group was impaired in the recognition of basic and complex emotions compared to both, SZ and TD. When facial identity recognition was adjusted for, group differences remained for the recognition of complex emotions only. Our results suggest that there is a SZ subgroup with predominantly paranoid symptoms that does not show problems in face processing and emotion recognition, but visuo-perceptual impairments. They also confirm the notion of a general facial and emotion recognition deficit in HFASD. No shared emotion recognition deficit was found for paranoid SZ and HFASD, emphasizing the differential cognitive underpinnings of both disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Activity Recognition Using A Combination of Category Components And Local Models for Video Surveillance

    OpenAIRE

    Lin, Weiyao; Sun, Ming-Ting; Poovendran, Radha; Zhang, Zhengyou

    2015-01-01

    This paper presents a novel approach for automatic recognition of human activities for video surveillance applications. We propose to represent an activity by a combination of category components, and demonstrate that this approach offers flexibility to add new activities to the system and an ability to deal with the problem of building models for activities lacking training data. For improving the recognition accuracy, a Confident-Frame- based Recognition algorithm is also proposed, where th...

  8. Repairing the vibratory vocal fold.

    Science.gov (United States)

    Long, Jennifer L

    2018-01-01

    A vibratory vocal fold replacement would introduce a new treatment paradigm for structural vocal fold diseases such as scarring and lamina propria loss. This work implants a tissue-engineered replacement for vocal fold lamina propria and epithelium in rabbits and compares histology and function to injured controls and orthotopic transplants. Hypotheses were that the cell-based implant would engraft and control the wound response, reducing fibrosis and restoring vibration. Translational research. Rabbit adipose-derived mesenchymal stem cells (ASC) were embedded within a three-dimensional fibrin gel, forming the cell-based outer vocal fold replacement (COVR). Sixteen rabbits underwent unilateral resection of vocal fold epithelium and lamina propria, as well as reconstruction with one of three treatments: fibrin glue alone with healing by secondary intention, replantation of autologous resected vocal fold cover, or COVR implantation. After 4 weeks, larynges were examined histologically and with phonation. Fifteen rabbits survived. All tissues incorporated well after implantation. After 1 month, both graft types improved histology and vibration relative to injured controls. Extracellular matrix (ECM) of the replanted mucosa was disrupted, and ECM of the COVR implants remained immature. Immune reaction was evident when male cells were implanted into female rabbits. Best histologic and short-term vibratory outcomes were achieved with COVR implants containing male cells implanted into male rabbits. Vocal fold cover replacement with a stem cell-based tissue-engineered construct is feasible and beneficial in acute rabbit implantation. Wound-modifying behavior of the COVR implant is judged to be an important factor in preventing fibrosis. NA. Laryngoscope, 128:153-159, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

  9. Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

    Science.gov (United States)

    Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

    2017-10-12

    Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

  10. Introduction and Overview of the Vicens-Reddy Speech Recognition System.

    Science.gov (United States)

    Kameny, Iris; Ritea, H.

    The Vicens-Reddy System is unique in the sense that it approaches the problem of speech recognition as a whole, rather than treating particular aspects of the problems as in previous attempts. For example, where earlier systems treated only segmentation of speech into phoneme groups, or detected phonemes in a given context, the Vicens-Reddy System…

  11. Leveraging Automatic Speech Recognition Errors to Detect Challenging Speech Segments in TED Talks

    Science.gov (United States)

    Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya

    2016-01-01

    This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…

  12. Chinese character recognition based on Gabor feature extraction and CNN

    Science.gov (United States)

    Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

    2018-03-01

    As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

  13. An adaptive deep Q-learning strategy for handwritten digit recognition.

    Science.gov (United States)

    Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

    2018-02-22

    Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Kinetic partitioning mechanism of HDV ribozyme folding

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Jiawen; Gong, Sha; Wang, Yujie; Zhang, Wenbing, E-mail: wbzhang@whu.edu.cn [Department of Physics, Wuhan University, Wuhan, Hubei 430072 (China)

    2014-01-14

    RNA folding kinetics is directly tied to RNA biological functions. We introduce here a new approach for predicting the folding kinetics of RNA secondary structure with pseudoknots. This approach is based on our previous established helix-based method for predicting the folding kinetics of RNA secondary structure. In this approach, the transition rates for an elementary step: (1) formation, (2) disruption of a helix stem, and (3) helix formation with concomitant partial melting of an incompatible helix, are calculated with the free energy landscape. The folding kinetics of the Hepatitis delta virus (HDV) ribozyme and the mutated sequences are studied with this method. The folding pathways are identified by recursive searching the states with high net flux-in(out) population starting from the native state. The theory results are in good agreement with that of the experiments. The results indicate that the bi-phasic folding kinetics for the wt HDV sequence is ascribed to the kinetic partitioning mechanism: Part of the population will quickly fold to the native state along the fast pathway, while another part of the population will fold along the slow pathway, in which the population is trapped in a non-native state. Single mutation not only changes the folding rate but also the folding pathway.

  15. Recognition of upper airway and surrounding structures at MRI in pediatric PCOS and OSAS

    Science.gov (United States)

    Tong, Yubing; Udupa, J. K.; Odhner, D.; Sin, Sanghun; Arens, Raanan

    2013-03-01

    Obstructive Sleep Apnea Syndrome (OSAS) is common in obese children with risk being 4.5 fold compared to normal control subjects. Polycystic Ovary Syndrome (PCOS) has recently been shown to be associated with OSAS that may further lead to significant cardiovascular and neuro-cognitive deficits. We are investigating image-based biomarkers to understand the architectural and dynamic changes in the upper airway and the surrounding hard and soft tissue structures via MRI in obese teenage children to study OSAS. At the previous SPIE conferences, we presented methods underlying Fuzzy Object Models (FOMs) for Automatic Anatomy Recognition (AAR) based on CT images of the thorax and the abdomen. The purpose of this paper is to demonstrate that the AAR approach is applicable to a different body region and image modality combination, namely in the study of upper airway structures via MRI. FOMs were built hierarchically, the smaller sub-objects forming the offspring of larger parent objects. FOMs encode the uncertainty and variability present in the form and relationships among the objects over a study population. Totally 11 basic objects (17 including composite) were modeled. Automatic recognition for the best pose of FOMs in a given image was implemented by using four methods - a one-shot method that does not require search, another three searching methods that include Fisher Linear Discriminate (FLD), a b-scale energy optimization strategy, and optimum threshold recognition method. In all, 30 multi-fold cross validation experiments based on 15 patient MRI data sets were carried out to assess the accuracy of recognition. The results indicate that the objects can be recognized with an average location error of less than 5 mm or 2-3 voxels. Then the iterative relative fuzzy connectedness (IRFC) algorithm was adopted for delineation of the target organs based on the recognized results. The delineation results showed an overall FP and TP volume fraction of 0.02 and 0.93.

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

    Science.gov (United States)

    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.

  17. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-01-01

    Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

  18. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2018-04-01

    Full Text Available Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD method for an iris recognition system (iPAD using a near infrared light (NIR camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED. Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM. Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

  19. Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

    Science.gov (United States)

    Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

    2018-04-24

    Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

  20. Self-folding origami at any energy scale

    Science.gov (United States)

    Pinson, Matthew B.; Stern, Menachem; Carruthers Ferrero, Alexandra; Witten, Thomas A.; Chen, Elizabeth; Murugan, Arvind

    2017-05-01

    Programmable stiff sheets with a single low-energy folding motion have been sought in fields ranging from the ancient art of origami to modern meta-materials research. Despite such attention, only two extreme classes of crease patterns are usually studied; special Miura-Ori-based zero-energy patterns, in which crease folding requires no sheet bending, and random patterns with high-energy folding, in which the sheet bends as much as creases fold. We present a physical approach that allows systematic exploration of the entire space of crease patterns as a function of the folding energy. Consequently, we uncover statistical results in origami, finding the entropy of crease patterns of given folding energy. Notably, we identify three classes of Mountain-Valley choices that have widely varying `typical' folding energies. Our work opens up a wealth of experimentally relevant self-folding origami designs not reliant on Miura-Ori, the Kawasaki condition or any special symmetry in space.

  1. A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

    Directory of Open Access Journals (Sweden)

    Chenchen Huang

    2014-01-01

    Full Text Available Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.

  2. Energetic frustrations in protein folding at residue resolution: a homologous simulation study of Im9 proteins.

    Directory of Open Access Journals (Sweden)

    Yunxiang Sun

    Full Text Available Energetic frustration is becoming an important topic for understanding the mechanisms of protein folding, which is a long-standing big biological problem usually investigated by the free energy landscape theory. Despite the significant advances in probing the effects of folding frustrations on the overall features of protein folding pathways and folding intermediates, detailed characterizations of folding frustrations at an atomic or residue level are still lacking. In addition, how and to what extent folding frustrations interact with protein topology in determining folding mechanisms remains unclear. In this paper, we tried to understand energetic frustrations in the context of protein topology structures or native-contact networks by comparing the energetic frustrations of five homologous Im9 alpha-helix proteins that share very similar topology structures but have a single hydrophilic-to-hydrophobic mutual mutation. The folding simulations were performed using a coarse-grained Gō-like model, while non-native hydrophobic interactions were introduced as energetic frustrations using a Lennard-Jones potential function. Energetic frustrations were then examined at residue level based on φ-value analyses of the transition state ensemble structures and mapped back to native-contact networks. Our calculations show that energetic frustrations have highly heterogeneous influences on the folding of the four helices of the examined structures depending on the local environment of the frustration centers. Also, the closer the introduced frustration is to the center of the native-contact network, the larger the changes in the protein folding. Our findings add a new dimension to the understanding of protein folding the topology determination in that energetic frustrations works closely with native-contact networks to affect the protein folding.

  3. CATHEDRAL: a fast and effective algorithm to predict folds and domain boundaries from multidomain protein structures.

    Directory of Open Access Journals (Sweden)

    Oliver C Redfern

    2007-11-01

    Full Text Available We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure-based method (using graph theory to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these

  4. Anatomy and Histology of an Epicanthal Fold.

    Science.gov (United States)

    Park, Jae Woo; Hwang, Kun

    2016-06-01

    The aim of this study is to elucidate the precise anatomical and histological detail of the epicanthal fold.Thirty-two hemifaces of 16 Korean adult cadavers were used in this study (30 hemifaces with an epicanthal fold, 2 without an epicanthal fold). In 2 patients who had an epicanthoplasty, the epicanthal folds were sampled.In a dissection, the periorbital skin and subcutaneous tissues were removed and the epicanthal fold was observed in relation to each part of the orbicularis oculi muscle. Specimens including the epicanthal fold were embeddedin in paraffin, sectioned at 10 um, and stained with Hematoxylin-Eosin. The horizontal section in the level of the paplebral fissure was made and the prepared slides were observed under a light microscope.In the specimens without an epicanthal fold, no connection between the upper preseptal muscle and the lower preseptal muscle was found. In the specimens with an epicanthal fold, a connection of the upper preseptal muscle to the lower preseptal muscle was observed. It was present in all 15 hemifaces (100%). There was no connection between the pretarsal muscles. In a horizontal section, the epicanthal fold was composed of 3 compartments: an outer skin lining, a core structure, and an innerskin lining. The core structure was mainly composed of muscular fibers and fibrotic tissue and they were intermingled.Surgeons should be aware of the anatomical details of an epicanthal fold. In removing or reconstructing an epicanthal fold, the fibromuscular core band should also be removed or reconstructed.

  5. Social emotion recognition, social functioning, and attempted suicide in late-life depression.

    Science.gov (United States)

    Szanto, Katalin; Dombrovski, Alexandre Y; Sahakian, Barbara J; Mulsant, Benoit H; Houck, Patricia R; Reynolds, Charles F; Clark, Luke

    2012-03-01

    : Lack of feeling connected and poor social problem solving have been described in suicide attempters. However, cognitive substrates of this apparent social impairment in suicide attempters remain unknown. One possible deficit, the inability to recognize others' complex emotional states has been observed not only in disorders characterized by prominent social deficits (autism-spectrum disorders and frontotemporal dementia) but also in depression and normal aging. This study assessed the relationship between social emotion recognition, problem solving, social functioning, and attempted suicide in late-life depression. : There were 90 participants: 24 older depressed suicide attempters, 38 nonsuicidal depressed elders, and 28 comparison subjects with no psychiatric history. We compared performance on the Reading the Mind in the Eyes test and measures of social networks, social support, social problem solving, and chronic interpersonal difficulties in these three groups. : Suicide attempters committed significantly more errors in social emotion recognition and showed poorer global cognitive performance than elders with no psychiatric history. Attempters had restricted social networks: they were less likely to talk to their children, had fewer close friends, and did not engage in volunteer activities, compared to nonsuicidal depressed elders and those with no psychiatric history. They also reported a pattern of struggle against others and hostility in relationships, felt a lack of social support, perceived social problems as impossible to resolve, and displayed a careless/impulsive approach to problems. : Suicide attempts in depressed elders were associated with poor social problem solving, constricted social networks, and disruptive interpersonal relationships. Impaired social emotion recognition in the suicide attempter group was related.

  6. The review on tessellation origami inspired folded structure

    Science.gov (United States)

    Chu, Chai Chen; Keong, Choong Kok

    2017-10-01

    Existence of folds enhances the load carrying capacity of a folded structure which makes it suitable to be used for application where large open space is required such as large span roof structures and façade. Folded structure is closely related to origami especially the tessellation origami. Tessellation origami provides a folded configuration with facetted surface as a result from repeated folding pattern. Besides that, tessellation origami has flexible folding mechanism that produced a variety of 3-dimensional folded configurations. Despite the direct relationship between fold in origami and folded structure, the idea of origami inspired folded structure is not properly reviewed in the relevant engineering field. Hence, this paper aims to present the current studies from related discipline which has direct relation with application of tessellation origami in folded structure. First, tessellation origami is properly introduced and defined. Then, the review covers the topic on the origami tessellation design suitable for folded structure, its modeling and simulation method, and existing studies and applications of origami as folded structure is presented. The paper also includes the discussion on the current issues related to each topic.

  7. Enhanced iris recognition method based on multi-unit iris images

    Science.gov (United States)

    Shin, Kwang Yong; Kim, Yeong Gon; Park, Kang Ryoung

    2013-04-01

    For the purpose of biometric person identification, iris recognition uses the unique characteristics of the patterns of the iris; that is, the eye region between the pupil and the sclera. When obtaining an iris image, the iris's image is frequently rotated because of the user's head roll toward the left or right shoulder. As the rotation of the iris image leads to circular shifting of the iris features, the accuracy of iris recognition is degraded. To solve this problem, conventional iris recognition methods use shifting of the iris feature codes to perform the matching. However, this increases the computational complexity and level of false acceptance error. To solve these problems, we propose a novel iris recognition method based on multi-unit iris images. Our method is novel in the following five ways compared with previous methods. First, to detect both eyes, we use Adaboost and a rapid eye detector (RED) based on the iris shape feature and integral imaging. Both eyes are detected using RED in the approximate candidate region that consists of the binocular region, which is determined by the Adaboost detector. Second, we classify the detected eyes into the left and right eyes, because the iris patterns in the left and right eyes in the same person are different, and they are therefore considered as different classes. We can improve the accuracy of iris recognition using this pre-classification of the left and right eyes. Third, by measuring the angle of head roll using the two center positions of the left and right pupils, detected by two circular edge detectors, we obtain the information of the iris rotation angle. Fourth, in order to reduce the error and processing time of iris recognition, adaptive bit-shifting based on the measured iris rotation angle is used in feature matching. Fifth, the recognition accuracy is enhanced by the score fusion of the left and right irises. Experimental results on the iris open database of low-resolution images showed that the

  8. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments.

    Science.gov (United States)

    Baldominos, Alejandro; Saez, Yago; Isasi, Pedro

    2018-04-23

    Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

  9. Toward retail product recognition on grocery shelves

    Science.gov (United States)

    Varol, Gül; Kuzu, Rıdvan S.

    2015-03-01

    This paper addresses the problem of retail product recognition on grocery shelf images. We present a technique for accomplishing this task with a low time complexity. We decompose the problem into detection and recognition. The former is achieved by a generic product detection module which is trained on a specific class of products (e.g. tobacco packages). Cascade object detection framework of Viola and Jones [1] is used for this purpose. We further make use of Support Vector Machines (SVMs) to recognize the brand inside each detected region. We extract both shape and color information; and apply feature-level fusion from two separate descriptors computed with the bag of words approach. Furthermore, we introduce a dataset (available on request) that we have collected for similar research purposes. Results are presented on this dataset of more than 5,000 images consisting of 10 tobacco brands. We show that satisfactory detection and classification can be achieved on devices with cheap computational power. Potential applications of the proposed approach include planogram compliance control, inventory management and assisting visually impaired people during shopping.

  10. Vocal Fold Vibratory Changes Following Surgical Intervention.

    Science.gov (United States)

    Chen, Wenli; Woo, Peak; Murry, Thomas

    2016-03-01

    High-speed videoendoscopy (HSV) captures direct cycle-to-cycle visualization of vocal fold movement in real time. This ultrafast recording rate is capable of visualizing the vibratory motion of the vocal folds in severely disordered phonation and provides a direct method for examining vibratory changes after vocal fold surgery. The purpose of this study was to examine the vibratory motion before and after surgical intervention. HSV was captured from two subjects with identifiable midvocal fold benign lesions and six subjects with highly aperiodic vocal fold vibration before and after phonosurgery. Digital kymography (DKG) was used to extract high-speed kymographic vocal fold images sampled at the midmembranous, anterior 1/3, and posterior 1/3 region. Spectral analysis was subsequently applied to the DKG to quantify the cycle-to-cycle movements of the left and the right vocal fold, expressed as a spectrum. Before intervention, the vibratory spectrum consisted of decreased and flat-like spectral peaks with robust power asymmetry. After intervention, increases in spectral power and decreases in power symmetry were noted. Spectral power increases were most remarkable in the midmembranous region of the vocal fold. Surgical modification resulted in improved lateral excursion of the vocal folds, vibratory function, and perceptual measures of Voice Handicap Index-10. These changes in vibratory behavior trended toward normal vocal fold vibration. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  11. Current trends in small vocabulary speech recognition for equipment control

    Science.gov (United States)

    Doukas, Nikolaos; Bardis, Nikolaos G.

    2017-09-01

    Speech recognition systems allow human - machine communication to acquire an intuitive nature that approaches the simplicity of inter - human communication. Small vocabulary speech recognition is a subset of the overall speech recognition problem, where only a small number of words need to be recognized. Speaker independent small vocabulary recognition can find significant applications in field equipment used by military personnel. Such equipment may typically be controlled by a small number of commands that need to be given quickly and accurately, under conditions where delicate manual operations are difficult to achieve. This type of application could hence significantly benefit by the use of robust voice operated control components, as they would facilitate the interaction with their users and render it much more reliable in times of crisis. This paper presents current challenges involved in attaining efficient and robust small vocabulary speech recognition. These challenges concern feature selection, classification techniques, speaker diversity and noise effects. A state machine approach is presented that facilitates the voice guidance of different equipment in a variety of situations.

  12. Surface imprinted beads for the recognition of human serum albumin.

    Science.gov (United States)

    Bonini, Francesca; Piletsky, Sergey; Turner, Anthony P F; Speghini, Adolfo; Bossi, Alessandra

    2007-04-15

    The synthesis of poly-aminophenylboronic acid (ABPA) imprinted beads for the recognition of the protein human serum albumin (HSA) is reported. In order to create homogeneous recognition sites, covalent immobilisation of the template HSA was exploited. The resulting imprinted beads were selective for HSA. The indirect imprinting factor (IF) calculated from supernatant was 1.6 and the direct IF, evaluated from the protein recovered from the beads, was 1.9. The binding capacity was 1.4 mg/g, which is comparable to commercially available affinity materials. The specificity of the HSA recognition was evaluated with competitive experiments, indicating a molar ratio 4.5/1 of competitor was necessary to displace half of the bound HSA. The recognition and binding of the imprinted beads was also tested with a complex sample, human serum and targeted removal of HSA without a loss of the other protein components was demonstrated. The easy preparation protocol of derivatised beads and a good protein recognition properties make the approach an attractive solution to analytical and bio-analytical problems in the field of biotechnology.

  13. Arguments Against a Configural Processing Account of Familiar Face Recognition.

    Science.gov (United States)

    Burton, A Mike; Schweinberger, Stefan R; Jenkins, Rob; Kaufmann, Jürgen M

    2015-07-01

    Face recognition is a remarkable human ability, which underlies a great deal of people's social behavior. Individuals can recognize family members, friends, and acquaintances over a very large range of conditions, and yet the processes by which they do this remain poorly understood, despite decades of research. Although a detailed understanding remains elusive, face recognition is widely thought to rely on configural processing, specifically an analysis of spatial relations between facial features (so-called second-order configurations). In this article, we challenge this traditional view, raising four problems: (1) configural theories are underspecified; (2) large configural changes leave recognition unharmed; (3) recognition is harmed by nonconfigural changes; and (4) in separate analyses of face shape and face texture, identification tends to be dominated by texture. We review evidence from a variety of sources and suggest that failure to acknowledge the impact of familiarity on facial representations may have led to an overgeneralization of the configural account. We argue instead that second-order configural information is remarkably unimportant for familiar face recognition. © The Author(s) 2015.

  14. Simulation Analysis on Driving Behavior during Traffic Sign Recognition

    Directory of Open Access Journals (Sweden)

    Lishan Sun

    2011-05-01

    Full Text Available The traffic signs transfer trip information to drivers through vectors like words, graphs and numbers. Traffic sign with excessive information often makes the drivers have no time to read and understand, leading to risky driving. It is still a problem of how to clarify the relationship between traffic sign recognition and risky driving behavior. This paper presents a study that is reflective of such an effort. Twenty volunteers participated in the dynamic visual recognition experiment in driving simulator, and the data of several key indicators are obtained, including visual cognition time, vehicle acceleration and the offset distance from middle lane, etc. Correlations between each indicator above are discussed in terms of risky driving. Research findings directly show that drivers' behavior changes a lot during their traffic sign recognition.

  15. Pattern recognition in molecular dynamics. [FORTRAN

    Energy Technology Data Exchange (ETDEWEB)

    Zurek, W H; Schieve, W C [Texas Univ., Austin (USA)

    1977-07-01

    An algorithm for the recognition of the formation of bound molecular states in the computer simulation of a dilute gas is presented. Applications to various related problems in physics and chemistry are pointed out. Data structure and decision processes are described. Performance of the FORTRAN program based on the algorithm in cooperation with the molecular dynamics program is described and the results are presented.

  16. Optical Pattern Recognition

    Science.gov (United States)

    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.

  17. A new selective developmental deficit: Impaired object recognition with normal face recognition.

    Science.gov (United States)

    Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

    2011-05-01

    Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

  18. Folding of non-Euclidean curved shells

    Science.gov (United States)

    Bende, Nakul; Evans, Arthur; Innes-Gold, Sarah; Marin, Luis; Cohen, Itai; Santangelo, Christian; Hayward, Ryan

    2015-03-01

    Origami-based folding of 2D sheets has been of recent interest for a variety of applications ranging from deployable structures to self-folding robots. Though folding of planar sheets follows well-established principles, folding of curved shells involves an added level of complexity due to the inherent influence of curvature on mechanics. In this study, we use principles from differential geometry and thin shell mechanics to establish fundamental rules that govern folding of prototypical creased shells. In particular, we show how the normal curvature of a crease line controls whether the deformation is smooth or discontinuous, and investigate the influence of shell thickness and boundary conditions. We show that snap-folding of shells provides a route to rapid actuation on time-scales dictated by the speed of sound. The simple geometric design principles developed can be applied at any length-scale, offering potential for bio-inspired soft actuators for tunable optics, microfluidics, and robotics. This work was funded by the National Science Foundation through EFRI ODISSEI-1240441 with additional support to S.I.-G. through the UMass MRSEC DMR-0820506 REU program.

  19. Spin-image surface matching based target recognition in laser radar range imagery

    International Nuclear Information System (INIS)

    Li, Wang; Jian-Feng, Sun; Qi, Wang

    2010-01-01

    We explore the problem of in-plane rotation-invariance existing in the vertical detection of laser radar (Ladar) using the algorithm of spin-image surface matching. The method used to recognize the target in the range imagery of Ladar is time-consuming, owing to its complicated procedure, which violates the requirement of real-time target recognition in practical applications. To simplify the troublesome procedures, we improve the spin-image algorithm by introducing a statistical correlated coefficient into target recognition in range imagery of Ladar. The system performance is demonstrated on sixteen simulated noise range images with targets rotated through an arbitrary angle in plane. A high efficiency and an acceptable recognition rate obtained herein testify the validity of the improved algorithm for practical applications. The proposed algorithm not only solves the problem of in-plane rotation-invariance rationally, but also meets the real-time requirement. This paper ends with a comparison of the proposed method and the previous one. (classical areas of phenomenology)

  20. Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Shieh

    2014-01-01

    Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

  1. Overview of radar intra-pulse modulation recognition

    Science.gov (United States)

    Zang, Hanlin; Li, Yanling

    2018-05-01

    This paper introduces the current radar intra-pulse modulation method, describes the status quo and development direction of the intentional modulation and unintentional modulation in the pulse, and summarizes the existing problems and prospects for the future. Looking forward to the future, and providing a reference direction for the research on radar signal recognition in the next step.

  2. Synovial folds in equine articular process joints

    DEFF Research Database (Denmark)

    Thomsen, Line Nymann; Berg, Lise Charlotte; Markussen, Bo

    2013-01-01

    Cervical synovial folds have been suggested as a potential cause of neck pain in humans. Little is known about the extent and characteristics of cervical synovial folds in horses.......Cervical synovial folds have been suggested as a potential cause of neck pain in humans. Little is known about the extent and characteristics of cervical synovial folds in horses....

  3. Inertial Sensor-Based Gait Recognition: A Review

    Science.gov (United States)

    Sprager, Sebastijan; Juric, Matjaz B.

    2015-01-01

    With the recent development of microelectromechanical systems (MEMS), inertial sensors have become widely used in the research of wearable gait analysis due to several factors, such as being easy-to-use and low-cost. Considering the fact that each individual has a unique way of walking, inertial sensors can be applied to the problem of gait recognition where assessed gait can be interpreted as a biometric trait. Thus, inertial sensor-based gait recognition has a great potential to play an important role in many security-related applications. Since inertial sensors are included in smart devices that are nowadays present at every step, inertial sensor-based gait recognition has become very attractive and emerging field of research that has provided many interesting discoveries recently. This paper provides a thorough and systematic review of current state-of-the-art in this field of research. Review procedure has revealed that the latest advanced inertial sensor-based gait recognition approaches are able to sufficiently recognise the users when relying on inertial data obtained during gait by single commercially available smart device in controlled circumstances, including fixed placement and small variations in gait. Furthermore, these approaches have also revealed considerable breakthrough by realistic use in uncontrolled circumstances, showing great potential for their further development and wide applicability. PMID:26340634

  4. FaceIt: face recognition from static and live video for law enforcement

    Science.gov (United States)

    Atick, Joseph J.; Griffin, Paul M.; Redlich, A. N.

    1997-01-01

    Recent advances in image and pattern recognition technology- -especially face recognition--are leading to the development of a new generation of information systems of great value to the law enforcement community. With these systems it is now possible to pool and manage vast amounts of biometric intelligence such as face and finger print records and conduct computerized searches on them. We review one of the enabling technologies underlying these systems: the FaceIt face recognition engine; and discuss three applications that illustrate its benefits as a problem-solving technology and an efficient and cost effective investigative tool.

  5. Exemplar-based Parametric Hidden Markov Models for Recognition and Synthesis of Movements

    DEFF Research Database (Denmark)

    Herzog, Dennis; Krüger, Volker; Grest, Daniel

    2007-01-01

    A common problem in movement recognition is the recognition of movements of a particular type. E.g. pointing movements are of a particular type but differ in terms of the pointing direction. Arm movements with the goal of reaching out and grasping an object are of a particular type but differ...... are carried out through locally linear interpolation of the exemplar movements. Experiments are performed with pointing and grasping movements. Synthesis is done based on the object position as parameterization. In case of the recognition, the coordinates of the grasped or pointed at object are recovered. Our...

  6. Facing the Problem: Impaired Emotion Recognition During Multimodal Social Information Processing in Borderline Personality Disorder.

    Science.gov (United States)

    Niedtfeld, Inga; Defiebre, Nadine; Regenbogen, Christina; Mier, Daniela; Fenske, Sabrina; Kirsch, Peter; Lis, Stefanie; Schmahl, Christian

    2017-04-01

    Previous research has revealed alterations and deficits in facial emotion recognition in patients with borderline personality disorder (BPD). During interpersonal communication in daily life, social signals such as speech content, variation in prosody, and facial expression need to be considered simultaneously. We hypothesized that deficits in higher level integration of social stimuli contribute to difficulties in emotion recognition in BPD, and heightened arousal might explain this effect. Thirty-one patients with BPD and thirty-one healthy controls were asked to identify emotions in short video clips, which were designed to represent different combinations of the three communication channels: facial expression, speech content, and prosody. Skin conductance was recorded as a measure of sympathetic arousal, while controlling for state dissociation. Patients with BPD showed lower mean accuracy scores than healthy control subjects in all conditions comprising emotional facial expressions. This was true for the condition with facial expression only, and for the combination of all three communication channels. Electrodermal responses were enhanced in BPD only in response to auditory stimuli. In line with the major body of facial emotion recognition studies, we conclude that deficits in the interpretation of facial expressions lead to the difficulties observed in multimodal emotion processing in BPD.

  7. Optical character recognition of handwritten Arabic using hidden Markov models

    Science.gov (United States)

    Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

    2011-04-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

  8. Dynamics of Folds in the Plane

    Science.gov (United States)

    Krylov, Nikolai A.; Rogers, Edwin L.

    2011-01-01

    Take a strip of paper and fold a crease intersecting the long edges, creating two angles. Choose one edge and consider the angle with the crease. Fold the opposite edge along the crease, creating a new crease that bisects the angle. Fold again, this time using the newly created crease and the initial edge, creating a new angle along the chosen…

  9. Development of a device for real-time light-guided vocal fold injection: A preliminary report.

    Science.gov (United States)

    Cha, Wonjae; Ro, Jung Hoon; Wang, Soo-Geun; Jang, Jeon Yeob; Cho, Jae Keun; Kim, Geun-Hyo; Lee, Yeon Woo

    2016-04-01

    Vocal fold injection is a minimally invasive technique for various vocal fold pathologies. The shortcomings of the cricothyroid (CT) membrane approach are mainly related to invisibility of the injection needle. If localization of the needle tip can be improved during vocal fold injection with the CT approach, the current problems of the technique can be overcome. We have conceptualized real-time light-guided vocal fold injection that enables simultaneous injection under precise localization. In this study, we developed a device for real-time light-guided vocal fold injection and applied it in excised canine larynx. Animal model. A single optic fiber was inserted in an unmodified 25-gauge needle. A designated connector for the device was attached to the needle, the optic fiber, and the syringe. A laser diode module was used as the light source. An ex vivo canine larynx model was used to validate the device. The location of the needle tip was accurately indicated, and the depth from the mucosa could be estimated according to the brightness and size of the red light. The needle was inserted and could be localized in the canine vocal fold by the light of the device. Precise injection at the intended location was easily performed with no manipulation of the device or the needle. Real-time light-guided vocal fold injection might be a feasible and promising technique for treatment of vocal fold pathology. It is expected that this technique can improve the precision of vocal fold injection and expand its indication in laryngology. NA. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  10. Teaching computers to fold proteins

    DEFF Research Database (Denmark)

    Winther, Ole; Krogh, Anders Stærmose

    2004-01-01

    A new general algorithm for optimization of potential functions for protein folding is introduced. It is based upon gradient optimization of the thermodynamic stability of native folds of a training set of proteins with known structure. The iterative update rule contains two thermodynamic averages...

  11. Origami-Inspired Folding of Thick, Rigid Panels

    Science.gov (United States)

    Trease, Brian P.; Thomson, Mark W.; Sigel, Deborah A.; Walkemeyer, Phillip E.; Zirbel, Shannon; Howell, Larry; Lang, Robert

    2014-01-01

    To achieve power of 250 kW or greater, a large compression ratio of stowed-to-deployed area is needed. Origami folding patterns were used to inspire the folding of a solar array to achieve synchronous deployment; however, origami models are generally created for near-zero-thickness material. Panel thickness is one of the main challenges of origami-inspired design. Three origami-inspired folding techniques (flasher, square twist, and map fold) were created with rigid panels and hinges. Hinge components are added to the model to enable folding of thick, rigid materials. Origami models are created assuming zero (or near zero) thickness. When a material with finite thickness is used, the panels are required to bend around an increasingly thick fold as they move away from the center of the model. The two approaches for dealing with material thickness are to use membrane hinges to connect the panels, or to add panel hinges, or hinges of the same thickness, at an appropriate width to enable folding.

  12. Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.

    Science.gov (United States)

    Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

    2017-06-06

    Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.

  13. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    Science.gov (United States)

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  14. Recognition in Programmes for Children with Special Needs

    Directory of Open Access Journals (Sweden)

    Marjeta Šmid

    2016-09-01

    Full Text Available The purpose of this article is to examine the factors that affect the inclusion of pupils in programmes for children with special needs from the perspective of the theory of recognition. The concept of recognition, which includes three aspects of social justice (economic, cultural and political, argues that the institutional arrangements that prevent ‘parity of participation’ in the school social life of the children with special needs are affected not only by economic distribution but also by the patterns of cultural values. A review of the literature shows that the arrangements of education of children with special needs are influenced primarily by the patterns of cultural values of capability and inferiority, as well as stereotypical images of children with special needs. Due to the significant emphasis on learning skills for academic knowledge and grades, less attention is dedicated to factors of recognition and representational character, making it impossible to improve some meaningful elements of inclusion. Any participation of pupils in activities, the voices of the children, visibility of the children due to achievements and the problems of arbitrariness in determining boundaries between programmes are some such elements. Moreover, aided by theories, the actions that could contribute to better inclusion are reviewed. An effective approach to changes would be the creation of transformative conditions for the recognition and balancing of redistribution, recognition, and representation.

  15. Vocal fold hemorrhage: factors predicting recurrence.

    Science.gov (United States)

    Lennon, Christen J; Murry, Thomas; Sulica, Lucian

    2014-01-01

    Vocal fold hemorrhage is an acute phonotraumatic injury treated with voice rest; recurrence is a generally accepted indication for surgical intervention. This study aims to identify factors predictive of recurrence based on outcomes of a large clinical series. Retrospective cohort. Retrospective review of cases of vocal fold hemorrhage presenting to a university laryngology service. Demographic information was compiled. Videostroboscopic exams were evaluated for hemorrhage extent, presence of varix, mucosal lesion, and/or vocal fold paresis. Vocal fold hemorrhage recurrence was the main outcome measure. Follow-up telephone survey was used to complement clinical data. Forty-seven instances of vocal fold hemorrhage were evaluated (25M:22F; 32 professional voice users). Twelve of the 47 (26%) patients experienced recurrence. Only the presence of varix demonstrated significant association with recurrence (P = 0.0089) on multivariate logistic regression. Vocal fold hemorrhage recurred in approximately 26% of patients. Varix was a predictor of recurrence, with 48% of those with varix experiencing recurrence. Monitoring, behavioral management and/or surgical intervention may be indicated to treat patients with such characteristics. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

  16. Geometric U-folds in four dimensions

    Science.gov (United States)

    Lazaroiu, C. I.; Shahbazi, C. S.

    2018-01-01

    We describe a general construction of geometric U-folds compatible with a non-trivial extension of the global formulation of four-dimensional extended supergravity on a differentiable spin manifold. The topology of geometric U-folds depends on certain flat fiber bundles which encode how supergravity fields are globally glued together. We show that smooth non-trivial U-folds of this type can exist only in theories where both the scalar and space-time manifolds have non-trivial fundamental group and in addition the scalar map of the solution is homotopically non-trivial. Consistency with string theory requires smooth geometric U-folds to be glued using subgroups of the effective discrete U-duality group, implying that the fundamental group of the scalar manifold of such solutions must be a subgroup of the latter. We construct simple examples of geometric U-folds in a generalization of the axion-dilaton model of \

  17. Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

    Directory of Open Access Journals (Sweden)

    Min Peng

    2017-10-01

    Full Text Available Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

  18. Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

    Science.gov (United States)

    Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

    2017-01-01

    Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

  19. Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

    Science.gov (United States)

    Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

    2017-01-01

    Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

  20. Robust Face Recognition Via Gabor Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Hao Yu-Juan

    2016-01-01

    Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.

  1. Self-folding graphene-polymer bilayers

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Tao [Institute of Microelectronics, Tsinghua University, Beijing 100084 (China); Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Yoon, ChangKyu [Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Jin, Qianru [Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Li, Mingen [Department of Physics, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Liu, Zewen [Institute of Microelectronics, Tsinghua University, Beijing 100084 (China); Gracias, David H., E-mail: dgracias@jhu.edu [Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States)

    2015-05-18

    In order to incorporate the extraordinary intrinsic thermal, electrical, mechanical, and optical properties of graphene with three dimensional (3D) flexible substrates, we introduce a solvent-driven self-folding approach using graphene-polymer bilayers. A polymer (SU-8) film was spin coated atop chemically vapor deposited graphene films on wafer substrates and graphene-polymer bilayers were patterned with or without metal electrodes using photolithography, thin film deposition, and etching. After patterning, the bilayers were released from the substrates and they self-folded to form fully integrated, curved, and folded structures. In contrast to planar graphene sensors on rigid substrates, we assembled curved and folded sensors that are flexible and they feature smaller form factors due to their 3D geometry and large surface areas due to their multiple rolled architectures. We believe that this approach could be used to assemble a range of high performance 3D electronic and optical devices of relevance to sensing, diagnostics, wearables, and energy harvesting.

  2. Pattern recognition in high energy physics

    International Nuclear Information System (INIS)

    Tenner, A.G.

    1980-01-01

    In high energy physics experiments tracks of elementary particles are recorded by different types of equipment. Coordinates of points of these tracks have to be measured for the geometrical reconstruction and the further analysis of the observed events. Pattern recognition methods may facilitate the detection of tracks or whole events and the separation of relevant from non-relevant information. They may also serve for the automation of measurement. Generally, all work is done by digital computation. In a bubble chamber tracks appear as strings of vapour bubbles that can be recorded photographically. Two methods of pattern recognition are discussed. The flying spot digitizer encodes the pattern on the photograph into point coordinates in the memory of a computer. The computer carries out the pattern recognition procedure entirely on the basis of the stored information. Cathode ray instruments scan the photograph by means of a computer steered optical device. Data acquisition from the film is performed in a feedback loop of the computation. In electronic experimental equipment tracks are defined by the spacial distribution of hits of counters (wire counters, scintillation counters, spark chambers). Pattern recognition is generally performed in various stages both by on-line and off-line equipment. Problems in the data handling arise both from the great abundance of data and from the time limits imposed on the on-line computation by high measuring rates. The on-line computation is carried out by hardwired logic, small computers, and to an increasing extent by microprocessors. (Auth.)

  3. Narrowing the gap between automatic and human word recognition

    NARCIS (Netherlands)

    Scharenborg, O.E.

    2005-01-01

    In everyday life, speech is all around us, on the radio, television, and in human-human interaction. We are continually confronted with novel utterances, and usually we have no problem recognising and understanding them. Several research fields investigate the speech recognition process. This thesis

  4. How old is your fold?

    NARCIS (Netherlands)

    Winstanley, Henry F.; Abeln, Sanne; Deane, Charlotte M.

    Motivation: At present there exists no age estimate for the different protein structures found in nature. It has become clear from occurrence studies that different folds arose at different points in evolutionary time. An estimation of the age of different folds would be a starting point for many

  5. Speech Recognition

    Directory of Open Access Journals (Sweden)

    Adrian Morariu

    2009-01-01

    Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

  6. SAR Target Recognition via Local Sparse Representation of Multi-Manifold Regularized Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Meiting Yu

    2018-02-01

    Full Text Available The extraction of a valuable set of features and the design of a discriminative classifier are crucial for target recognition in SAR image. Although various features and classifiers have been proposed over the years, target recognition under extended operating conditions (EOCs is still a challenging problem, e.g., target with configuration variation, different capture orientations, and articulation. To address these problems, this paper presents a new strategy for target recognition. We first propose a low-dimensional representation model via incorporating multi-manifold regularization term into the low-rank matrix factorization framework. Two rules, pairwise similarity and local linearity, are employed for constructing multiple manifold regularization. By alternately optimizing the matrix factorization and manifold selection, the feature representation model can not only acquire the optimal low-rank approximation of original samples, but also capture the intrinsic manifold structure information. Then, to take full advantage of the local structure property of features and further improve the discriminative ability, local sparse representation is proposed for classification. Finally, extensive experiments on moving and stationary target acquisition and recognition (MSTAR database demonstrate the effectiveness of the proposed strategy, including target recognition under EOCs, as well as the capability of small training size.

  7. Finger vein recognition based on convolutional neural network

    Directory of Open Access Journals (Sweden)

    Meng Gesi

    2017-01-01

    Full Text Available Biometric Authentication Technology has been widely used in this information age. As one of the most important technology of authentication, finger vein recognition attracts our attention because of its high security, reliable accuracy and excellent performance. However, the current finger vein recognition system is difficult to be applied widely because its complicated image pre-processing and not representative feature vectors. To solve this problem, a finger vein recognition method based on the convolution neural network (CNN is proposed in the paper. The image samples are directly input into the CNN model to extract its feature vector so that we can make authentication by comparing the Euclidean distance between these vectors. Finally, the Deep Learning Framework Caffe is adopted to verify this method. The result shows that there are great improvements in both speed and accuracy rate compared to the previous research. And the model has nice robustness in illumination and rotation.

  8. Tracking and recognition face in videos with incremental local sparse representation model

    Science.gov (United States)

    Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

    2013-10-01

    This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

  9. Mfold web server for nucleic acid folding and hybridization prediction.

    Science.gov (United States)

    Zuker, Michael

    2003-07-01

    The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.

  10. Down image recognition based on deep convolutional neural network

    Directory of Open Access Journals (Sweden)

    Wenzhu Yang

    2018-06-01

    Full Text Available Since of the scale and the various shapes of down in the image, it is difficult for traditional image recognition method to correctly recognize the type of down image and get the required recognition accuracy, even for the Traditional Convolutional Neural Network (TCNN. To deal with the above problems, a Deep Convolutional Neural Network (DCNN for down image classification is constructed, and a new weight initialization method is proposed. Firstly, the salient regions of a down image were cut from the image using the visual saliency model. Then, these salient regions of the image were used to train a sparse autoencoder and get a collection of convolutional filters, which accord with the statistical characteristics of dataset. At last, a DCNN with Inception module and its variants was constructed. To improve the recognition accuracy, the depth of the network is deepened. The experiment results indicate that the constructed DCNN increases the recognition accuracy by 2.7% compared to TCNN, when recognizing the down in the images. The convergence rate of the proposed DCNN with the new weight initialization method is improved by 25.5% compared to TCNN. Keywords: Deep convolutional neural network, Weight initialization, Sparse autoencoder, Visual saliency model, Image recognition

  11. Pseudomonas Evades Immune Recognition of Flagellin in Both Mammals and Plants

    Science.gov (United States)

    Bardoel, Bart W.; van der Ent, Sjoerd; Pel, Michiel J. C.; Tommassen, Jan; Pieterse, Corné M. J.; van Kessel, Kok P. M.; van Strijp, Jos A. G.

    2011-01-01

    The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5) in mammals and flagellin-sensitive 2 (FLS2) in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR) antagonists, we screened bacterial supernatants and identified alkaline protease (AprA) of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility) and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition) in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants. PMID:21901099

  12. Muscular anatomy of the human ventricular folds.

    Science.gov (United States)

    Moon, Jerald; Alipour, Fariborz

    2013-09-01

    Our purpose in this study was to better understand the muscular anatomy of the ventricular folds in order to help improve biomechanical modeling of phonation and to better understand the role of these muscles during phonatory and nonphonatory tasks. Four human larynges were decalcified, sectioned coronally from posterior to anterior by a CryoJane tape transfer system, and stained with Masson's trichrome. The total and relative areas of muscles observed in each section were calculated and used for characterizing the muscle distribution within the ventricular folds. The ventricular folds contained anteriorly coursing thyroarytenoid and ventricularis muscle fibers that were in the lower half of the ventricular fold posteriorly, and some ventricularis muscle was evident in the upper and lateral portions of the fold more anteriorly. Very little muscle tissue was observed in the medial half of the fold, and the anterior half of the ventricular fold was largely devoid of any muscle tissue. All 4 larynges contained muscle bundles that coursed superiorly and medially through the upper half of the fold, toward the lateral margin of the epiglottis. Although variability of expression was evident, a well-defined thyroarytenoid muscle was readily apparent lateral to the arytenoid cartilage in all specimens.

  13. Neural network application to the neutral meson recognition

    International Nuclear Information System (INIS)

    Lefevre, F.; Delagrange, H.; Merrouch, R.; Ostendorf, R.; Schutz, Y.; Matulewicz, T.

    1991-01-01

    The combinatorial background produced by high photon multiplicities expected in TAPS experiments causes problems in precise meson recognition. We use neural networks to reduce this background. First we give a description of this technique, hereafter the first results obtained by applying this method to simulated events and future perspective will be discussed [fr

  14. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

    Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...

  15. Exact folded-band chaotic oscillator.

    Science.gov (United States)

    Corron, Ned J; Blakely, Jonathan N

    2012-06-01

    An exactly solvable chaotic oscillator with folded-band dynamics is shown. The oscillator is a hybrid dynamical system containing a linear ordinary differential equation and a nonlinear switching condition. Bounded oscillations are provably chaotic, and successive waveform maxima yield a one-dimensional piecewise-linear return map with segments of both positive and negative slopes. Continuous-time dynamics exhibit a folded-band topology similar to Rössler's oscillator. An exact solution is written as a linear convolution of a fixed basis pulse and a discrete binary sequence, from which an equivalent symbolic dynamics is obtained. The folded-band topology is shown to be dependent on the symbol grammar.

  16. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Baldominos

    2018-04-01

    Full Text Available Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

  17. Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

    Science.gov (United States)

    2018-01-01

    Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures. PMID:29690587

  18. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  19. Tensor manifold-based extreme learning machine for 2.5-D face recognition

    Science.gov (United States)

    Chong, Lee Ying; Ong, Thian Song; Teoh, Andrew Beng Jin

    2018-01-01

    We explore the use of the Gabor regional covariance matrix (GRCM), a flexible matrix-based descriptor that embeds the Gabor features in the covariance matrix, as a 2.5-D facial descriptor and an effective means of feature fusion for 2.5-D face recognition problems. Despite its promise, matching is not a trivial problem for GRCM since it is a special instance of a symmetric positive definite (SPD) matrix that resides in non-Euclidean space as a tensor manifold. This implies that GRCM is incompatible with the existing vector-based classifiers and distance matchers. Therefore, we bridge the gap of the GRCM and extreme learning machine (ELM), a vector-based classifier for the 2.5-D face recognition problem. We put forward a tensor manifold-compliant ELM and its two variants by embedding the SPD matrix randomly into reproducing kernel Hilbert space (RKHS) via tensor kernel functions. To preserve the pair-wise distance of the embedded data, we orthogonalize the random-embedded SPD matrix. Hence, classification can be done using a simple ridge regressor, an integrated component of ELM, on the random orthogonal RKHS. Experimental results show that our proposed method is able to improve the recognition performance and further enhance the computational efficiency.

  20. Solving the rectangular assignment problem and applications

    NARCIS (Netherlands)

    Bijsterbosch, J.; Volgenant, A.

    2010-01-01

    The rectangular assignment problem is a generalization of the linear assignment problem (LAP): one wants to assign a number of persons to a smaller number of jobs, minimizing the total corresponding costs. Applications are, e.g., in the fields of object recognition and scheduling. Further, we show

  1. Vocal fold paresis - a debilitating and underdiagnosed condition.

    Science.gov (United States)

    Harris, G; O'Meara, C; Pemberton, C; Rough, J; Darveniza, P; Tisch, S; Cole, I

    2017-07-01

    To review the clinical signs of vocal fold paresis on laryngeal videostroboscopy, to quantify its impact on patients' quality of life and to confirm the benefit of laryngeal electromyography in its diagnosis. Twenty-nine vocal fold paresis patients were referred for laryngeal electromyography. Voice Handicap Index 10 results were compared to 43 patients diagnosed with vocal fold paralysis. Laryngeal videostroboscopy analysis was conducted to determine side of paresis. Blinded laryngeal electromyography confirmed vocal fold paresis in 92.6 per cent of cases, with vocal fold lag being the most common diagnostic sign. The laryngology team accurately predicted side of paresis in 76 per cent of cases. Total Voice Handicap Index 10 responses were not significantly different between vocal fold paralysis and vocal fold paresis groups (26.08 ± 0.21 and 22.93 ± 0.17, respectively). Vocal fold paresis has a significant impact on quality of life. This study shows that laryngeal electromyography is an important diagnostic tool. Patients with persisting dysphonia and apparently normal vocal fold movement, who fail to respond to appropriate speech therapy, should be investigated for a diagnosis of vocal fold paresis.

  2. Some physical approaches to protein folding

    Science.gov (United States)

    Bascle, J.; Garel, T.; Orland, H.

    1993-02-01

    To understand how a protein folds is a problem which has important biological implications. In this article, we would like to present a physics-oriented point of view, which is twofold. First of all, we introduce simple statistical mechanics models which display, in the thermodynamic limit, folding and related transitions. These models can be divided into (i) crude spin glass-like models (with their Mattis analogs), where one may look for possible correlations between the chain self-interactions and the folded structure, (ii) glass-like models, where one emphasizes the geometrical competition between one- or two-dimensional local order (mimicking α helix or β sheet structures), and the requirement of global compactness. Both models are too simple to predict the spatial organization of a realistic protein, but are useful for the physicist and should have some feedback in other glassy systems (glasses, collapsed polymers .... ). These remarks lead us to the second physical approach, namely a new Monte-Carlo method, where one grows the protein atom-by-atom (or residue-by-residue), using a standard form (CHARMM .... ) for the total energy. A detailed comparison with other Monte-Carlo schemes, or Molecular Dynamics calculations, is then possible; we will sketch such a comparison for poly-alanines. Our twofold approach illustrates some of the difficulties one encounters in the protein folding problem, in particular those associated with the existence of a large number of metastable states. Le repliement des protéines est un problème qui a de nombreuses implications biologiques. Dans cet article, nous présentons, de deux façons différentes, un point de vue de physicien. Nous introduisons tout d'abord des modèles simples de mécanique statistique qui exhibent, à la limite thermodynamique, des transitions de repliement. Ces modèles peuvent être divisés en (i) verres de spin (éventuellement à la Mattis), où l'on peut chercher des corrélations entre les

  3. Application of deep convolutional neural networks for ocean front recognition

    Science.gov (United States)

    Lima, Estanislau; Sun, Xin; Yang, Yuting; Dong, Junyu

    2017-10-01

    Ocean fronts have been a subject of study for many years, a variety of methods and algorithms have been proposed to address the problem of ocean fronts. However, all these existing ocean front recognition methods are built upon human expertise in defining the front based on subjective thresholds of relevant physical variables. This paper proposes a deep learning approach for ocean front recognition that is able to automatically recognize the front. We first investigated four existing deep architectures, i.e., AlexNet, CaffeNet, GoogLeNet, and VGGNet, for the ocean front recognition task using remote sensing (RS) data. We then propose a deep network with fewer layers compared to existing architecture for the front recognition task. This network has a total of five learnable layers. In addition, we extended the proposed network to recognize and classify the front into strong and weak ones. We evaluated and analyzed the proposed network with two strategies of exploiting the deep model: full-training and fine-tuning. Experiments are conducted on three different RS image datasets, which have different properties. Experimental results show that our model can produce accurate recognition results.

  4. Fine-grained vehicle type recognition based on deep convolution neural networks

    Directory of Open Access Journals (Sweden)

    Hongcai CHEN

    2017-12-01

    Full Text Available Public security and traffic department put forward higher requirements for real-time performance and accuracy of vehicle type recognition in complex traffic scenes. Aiming at the problems of great plice forces occupation, low retrieval efficiency, and lacking of intelligence for dealing with false license, fake plate vehicles and vehicles without plates, this paper proposes a vehicle type fine-grained recognition method based GoogleNet deep convolution neural networks. The filter size and numbers of convolution neural network are designed, the activation function and vehicle type classifier are optimally selected, and a new network framework is constructed for vehicle type fine-grained recognition. The experimental results show that the proposed method has 97% accuracy for vehicle type fine-grained recognition and has greater improvement than the original GoogleNet model. Moreover, the new model effectively reduces the number of training parameters, and saves computer memory. Fine-grained vehicle type recognition can be used in intelligent traffic management area, and has important theoretical research value and practical significance.

  5. View-invariant gait recognition method by three-dimensional convolutional neural network

    Science.gov (United States)

    Xing, Weiwei; Li, Ying; Zhang, Shunli

    2018-01-01

    Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

  6. Adaptive Origami for Efficiently Folded Structures

    Science.gov (United States)

    2016-02-01

    heating. Although a large fold angle at a high temperature is desirable in order to extrapolate the origami geometry toward closure, more emphasis is...AFRL-RQ-WP-TR-2016-0020 ADAPTIVE ORIGAMI FOR EFFICIENTLY FOLDED STRUCTURES James J. Joo and Greg Reich Design and Analysis Branch... ORIGAMI FOR EFFICIENTLY FOLDED STRUCTURES 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) James J

  7. Vocal fold paralysis secondary to phonotrauma.

    Science.gov (United States)

    Klein, Travis A L; Gaziano, Joy E; Ridley, Marion B

    2014-01-01

    A unique case of acute onset vocal fold paralysis secondary to phonotrauma is presented. The cause was forceful vocalization by a drill instructor on a firearm range. Imaging studies revealed extensive intralaryngeal and retropharyngeal hemorrhage. Laryngoscopy showed a complete left vocal fold paralysis. Relative voice rest was recommended, and the patient regained normal vocal fold mobility and function after approximately 12 weeks. Copyright © 2014 The Voice Foundation. All rights reserved.

  8. 100-fold but not 50-fold dystrophin overexpression aggravates electrocardiographic defects in the mdx model of Duchenne muscular dystrophy

    Directory of Open Access Journals (Sweden)

    Yongping Yue

    2016-01-01

    Full Text Available Dystrophin gene replacement holds the promise of treating Duchenne muscular dystrophy. Supraphysiological expression is a concern for all gene therapy studies. In the case of Duchenne muscular dystrophy, Chamberlain and colleagues found that 50-fold overexpression did not cause deleterious side effect in skeletal muscle. To determine whether excessive dystrophin expression in the heart is safe, we studied two lines of transgenic mdx mice that selectively expressed a therapeutic minidystrophin gene in the heart at 50-fold and 100-fold of the normal levels. In the line with 50-fold overexpression, minidystrophin showed sarcolemmal localization and electrocardiogram abnormalities were corrected. However, in the line with 100-fold overexpression, we not only detected sarcolemmal minidystrophin expression but also observed accumulation of minidystrophin vesicles in the sarcoplasm. Excessive minidystrophin expression did not correct tachycardia, a characteristic feature of Duchenne muscular dystrophy. Importantly, several electrocardiogram parameters (QT interval, QRS duration and the cardiomyopathy index became worse than that of mdx mice. Our data suggests that the mouse heart can tolerate 50-fold minidystrophin overexpression, but 100-fold overexpression leads to cardiac toxicity.

  9. Sarcoidosis Presenting as Bilateral Vocal Fold Immobility.

    Science.gov (United States)

    Hintze, Justin M; Gnagi, Sharon H; Lott, David G

    2018-05-01

    Bilateral true vocal fold paralysis is rarely attributable to inflammatory diseases. Sarcoidosis is a rare but important etiology of bilateral true vocal fold paralysis by compressive lymphadenopathy, granulomatous infiltration, and neural involvement. We describe the first reported case of sarcoidosis presenting as bilateral vocal fold immobility caused by direct fixation by granulomatous infiltration severe enough to necessitate tracheostomy insertion. In addition, we discuss the presentation, the pathophysiology, and the treatment of this disease with a review of the literature of previously reported cases of sarcoidosis-related vocal fold immobility. Sarcoidosis should therefore be an important consideration for the otolaryngologist's differential diagnosis of true vocal fold immobility. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  10. Cofactor-binding sites in proteins of deviating sequence: comparative analysis and clustering in torsion angle, cavity, and fold space.

    Science.gov (United States)

    Stegemann, Björn; Klebe, Gerhard

    2012-02-01

    Small molecules are recognized in protein-binding pockets through surface-exposed physicochemical properties. To optimize binding, they have to adopt a conformation corresponding to a local energy minimum within the formed protein-ligand complex. However, their conformational flexibility makes them competent to bind not only to homologous proteins of the same family but also to proteins of remote similarity with respect to the shape of the binding pockets and folding pattern. Considering drug action, such observations can give rise to unexpected and undesired cross reactivity. In this study, datasets of six different cofactors (ADP, ATP, NAD(P)(H), FAD, and acetyl CoA, sharing an adenosine diphosphate moiety as common substructure), observed in multiple crystal structures of protein-cofactor complexes exhibiting sequence identity below 25%, have been analyzed for the conformational properties of the bound ligands, the distribution of physicochemical properties in the accommodating protein-binding pockets, and the local folding patterns next to the cofactor-binding site. State-of-the-art clustering techniques have been applied to group the different protein-cofactor complexes in the different spaces. Interestingly, clustering in cavity (Cavbase) and fold space (DALI) reveals virtually the same data structuring. Remarkable relationships can be found among the different spaces. They provide information on how conformations are conserved across the host proteins and which distinct local cavity and fold motifs recognize the different portions of the cofactors. In those cases, where different cofactors are found to be accommodated in a similar fashion to the same fold motifs, only a commonly shared substructure of the cofactors is used for the recognition process. Copyright © 2011 Wiley Periodicals, Inc.

  11. USING CONVOLUTIONAL NEURAL NETWORKS FOR LICENSE PLATES RECOGNITION. ADVANTAGES AND DISADVANTAGES IN COMPARISON WITH TEMPLATE-BASED METHOD

    OpenAIRE

    Mikhalevich Y. S.; Tkachenko V. V.

    2016-01-01

    Car license plates recognition problem is one of the typical tasks of computer vision. Video surveillance software usually provides license plates recognition function. Meanwhile, there are many approaches to solve this problem, where template-based methods are the most common. Such methods providing predictable and short enough execution time, and little percent of mistakes. However, such methods are far less effective in case there is a need to recognize car’s license plate, which may be lo...

  12. Pose-invariant face recognition using Markov random fields.

    Science.gov (United States)

    Ho, Huy Tho; Chellappa, Rama

    2013-04-01

    One of the key challenges for current face recognition techniques is how to handle pose variations between the probe and gallery face images. In this paper, we present a method for reconstructing the virtual frontal view from a given nonfrontal face image using Markov random fields (MRFs) and an efficient variant of the belief propagation algorithm. In the proposed approach, the input face image is divided into a grid of overlapping patches, and a globally optimal set of local warps is estimated to synthesize the patches at the frontal view. A set of possible warps for each patch is obtained by aligning it with images from a training database of frontal faces. The alignments are performed efficiently in the Fourier domain using an extension of the Lucas-Kanade algorithm that can handle illumination variations. The problem of finding the optimal warps is then formulated as a discrete labeling problem using an MRF. The reconstructed frontal face image can then be used with any face recognition technique. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, we also present an algorithm for classifying whether a given face image is at a frontal or nonfrontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach.

  13. Multi-crease Self-folding by Global Heating.

    Science.gov (United States)

    Miyashita, Shuhei; Onal, Cagdas D; Rus, Daniela

    2015-01-01

    This study demonstrates a new approach to autonomous folding for the body of a 3D robot from a 2D sheet, using heat. We approach this challenge by folding a 0.27-mm sheetlike material into a structure. We utilize the thermal deformation of a contractive sheet sandwiched by rigid structural layers. During this baking process, the heat applied on the entire sheet induces contraction of the contracting layer and thus forms an instructed bend in the sheet. To attain the targeted folding angles, the V-fold spans method is used. The targeted angle θout can be kinematically encoded into crease geometry. The realization of this angle in the folded structure can be approximately controlled by a contraction angle θin. The process is non-reversible, is reliable, and is relatively fast. Our method can be applied simultaneously to all the folds in multi-crease origami structures. We demonstrate the use of this method to create a lightweight mobile robot.

  14. The active blind spot camera: hard real-time recognition of moving objects from a moving camera

    OpenAIRE

    Van Beeck, Kristof; Goedemé, Toon; Tuytelaars, Tinne

    2014-01-01

    This PhD research focuses on visual object recognition under specific demanding conditions. The object to be recognized as well as the camera move, and the time available for the recognition task is extremely short. This generic problem is applied here on a specific problem: the active blind spot camera. Statistics show a large number of accidents with trucks are related to the so-called blind spot, the area around the vehicle in which vulnerable road users are hard to perceive by the truck d...

  15. Re-thinking employee recognition: understanding employee experiences of recognition

    OpenAIRE

    Smith, Charlotte

    2013-01-01

    Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

  16. Experiments on Automatic Recognition of Nonnative Arabic Speech

    Directory of Open Access Journals (Sweden)

    Douglas O'Shaughnessy

    2008-05-01

    Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

  17. Experiments on Automatic Recognition of Nonnative Arabic Speech

    Directory of Open Access Journals (Sweden)

    Selouani Sid-Ahmed

    2008-01-01

    Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

  18. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2012-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions

  19. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2011-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

  20. [Clinical analysis of vocal fold firbrous mass].

    Science.gov (United States)

    Chen, Hao; Sun, Jing Wu; Wan, Guang Lun; Hu, Yan Ming

    2018-03-01

    To explore the character of laryngoscopy finding, voice, and therapy of vocal fold fibrous mass. Clinical data, morphology, voice character, surgery and pathology of 15 cases with vocal fold fibrous mass were analyzed. The morbidity of vocal fold fibrous mass might be related to overuse of voice and laryngopharyngeal reflex. Laryngoscopy revealed shuttle line appearance, smoothness and decreased mucosal wave of vocal fold. These patients were invalid for voice training and might be improved by surgery, but recovery is slow. The morbidity of vocal fold fibrous mass might be related to overuse of voice and laryngopharyngeal reflex. Conservative treatment is ineffective for this disease, and surgery might improve. Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.

  1. Face recognition using elastic grid matching through photoshop: A new approach

    Directory of Open Access Journals (Sweden)

    Manavpreet Kaur

    2015-12-01

    Full Text Available Computing grids propose to be a very efficacious, economic and ascendable way of image identification. In this paper, we propose a grid based face recognition overture employing a general template matching method to solve the timeconsuming face recognition problem. A new approach has been employed in which the grid was prepared for a specific individual over his photograph using Adobe Photoshop CS5 software. The background was later removed and the grid prepared by merging layers was used as a template for image matching or comparison. This overture is computationally efficient, has high recognition rates and is able to identify a person with minimal efforts and in short time even from photographs taken at different magnifications and from different distances.

  2. Static sign language recognition using 1D descriptors and neural networks

    Science.gov (United States)

    Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César

    2012-10-01

    A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.

  3. The use of the operand-recognition paradigm for the study of mental addition in older adults.

    Science.gov (United States)

    Thevenot, Catherine; Castel, Caroline; Danjon, Juliette; Fanget, Muriel; Fayol, Michel

    2013-01-01

    Determining how individuals solve arithmetic problems is crucial for our understanding of human cognitive architecture. Elderly adults are supposed to use memory retrieval more often than younger ones. However, they might backup their retrieval by reconstructive strategies. In order to investigate this issue, we used the operand-recognition paradigm, which capitalizes on the fact that algorithmic procedures degrade the memory traces of the operands. Twenty-three older adults (M = 70.4) and 23 younger adults (M = 20.0) solved easy, difficult, and medium-difficulty addition and comparison problems and were then presented with a recognition task of the operands. When one-digit numbers with sums larger than 10 were involved (medium-difficulty problem), it was more difficult for younger adults to recognize the operands after addition than comparison. In contrast, in older adults, recognition times of the operands were the same after addition and comparison. Older adults, in contrast with younger adults, are able to retrieve the results of addition problems of medium difficulty. Contrary to what was suggested, older participants do not seem to resort to backup strategies for such problems. Finally, older adults' reliance on the more efficient retrieval strategy allowed them to catch up to younger adults in terms of solution times.

  4. Human action recognition based on estimated weak poses

    Science.gov (United States)

    Gong, Wenjuan; Gonzàlez, Jordi; Roca, Francesc Xavier

    2012-12-01

    We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.

  5. Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

    Science.gov (United States)

    Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

    2017-07-01

    According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

  6. Adaptive local learning in sampling based motion planning for protein folding.

    Science.gov (United States)

    Ekenna, Chinwe; Thomas, Shawna; Amato, Nancy M

    2016-08-01

    Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods and variants contain several phases (i.e., sampling, connection, and path extraction). Most of the time is spent in the connection phase and selecting which variant to employ is a difficult task. Global machine learning has been applied to the connection phase but is inefficient in situations with varying topology, such as those typical of folding landscapes. We develop a local learning algorithm that exploits the past performance of methods within the neighborhood of the current connection attempts as a basis for learning. It is sensitive not only to different types of landscapes but also to differing regions in the landscape itself, removing the need to explicitly partition the landscape. We perform experiments on 23 proteins of varying secondary structure makeup with 52-114 residues. We compare the success rate when using our methods and other methods. We demonstrate a clear need for learning (i.e., only learning methods were able to validate against all available experimental data) and show that local learning is superior to global learning producing, in many cases, significantly higher quality results than the other methods. We present an algorithm that uses local learning to select appropriate connection methods in the context of roadmap construction for protein folding. Our method removes the burden of deciding which method to use, leverages the strengths of the individual input methods, and it is extendable to include other future connection methods.

  7. A multi-view face recognition system based on cascade face detector and improved Dlib

    Science.gov (United States)

    Zhou, Hongjun; Chen, Pei; Shen, Wei

    2018-03-01

    In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

  8. Object Recognition System-on-Chip Using the Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Houzet Dominique

    2005-01-01

    Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

  9. Factors that affect coseismic folds in an overburden layer

    Science.gov (United States)

    Zeng, Shaogang; Cai, Yongen

    2018-03-01

    Coseismic folds induced by blind thrust faults have been observed in many earthquake zones, and they have received widespread attention from geologists and geophysicists. Numerous studies have been conducted regarding fold kinematics; however, few have studied fold dynamics quantitatively. In this paper, we establish a conceptual model with a thrust fault zone and tectonic stress load to study the factors that affect coseismic folds and their formation mechanisms using the finite element method. The numerical results show that the fault dip angle is a key factor that controls folding. The greater the dip angle is, the steeper the fold slope. The second most important factor is the overburden thickness. The thicker the overburden is, the more gradual the fold. In this case, folds are difficult to identify in field surveys. Therefore, if a fold can be easily identified with the naked eye, the overburden is likely shallow. The least important factors are the mechanical parameters of the overburden. The larger the Young's modulus of the overburden is, the smaller the displacement of the fold and the fold slope. Strong horizontal compression and vertical extension in the overburden near the fault zone are the main mechanisms that form coseismic folds.

  10. Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

    CERN Document Server

    Melin, Patricia

    2012-01-01

    This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

  11. Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

    Science.gov (United States)

    Spirkovska, Lilly; Reid, Max B.

    1994-01-01

    A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

  12. Computing with Connections in Visual Recognition of Origami Objects.

    Science.gov (United States)

    Sabbah, Daniel

    1985-01-01

    Summarizes an initial foray in tackling artificial intelligence problems using a connectionist approach. The task chosen is visual recognition of Origami objects, and the questions answered are how to construct a connectionist network to represent and recognize projected Origami line drawings and the advantages such an approach would have. (30…

  13. Domain Adversarial for Acoustic Emotion Recognition

    OpenAIRE

    Abdelwahab, Mohammed; Busso, Carlos

    2018-01-01

    The performance of speech emotion recognition is affected by the differences in data distributions between train (source domain) and test (target domain) sets used to build and evaluate the models. This is a common problem, as multiple studies have shown that the performance of emotional classifiers drop when they are exposed to data that does not match the distribution used to build the emotion classifiers. The difference in data distributions becomes very clear when the training and testing...

  14. Physics of protein folding

    Science.gov (United States)

    Finkelstein, A. V.; Galzitskaya, O. V.

    2004-04-01

    Protein physics is grounded on three fundamental experimental facts: protein, this long heteropolymer, has a well defined compact three-dimensional structure; this structure can spontaneously arise from the unfolded protein chain in appropriate environment; and this structure is separated from the unfolded state of the chain by the “all-or-none” phase transition, which ensures robustness of protein structure and therefore of its action. The aim of this review is to consider modern understanding of physical principles of self-organization of protein structures and to overview such important features of this process, as finding out the unique protein structure among zillions alternatives, nucleation of the folding process and metastable folding intermediates. Towards this end we will consider the main experimental facts and simple, mostly phenomenological theoretical models. We will concentrate on relatively small (single-domain) water-soluble globular proteins (whose structure and especially folding are much better studied and understood than those of large or membrane and fibrous proteins) and consider kinetic and structural aspects of transition of initially unfolded protein chains into their final solid (“native”) 3D structures.

  15. Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

    OpenAIRE

    Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

    2016-01-01

    A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

  16. Individual discriminative face recognition models based on subsets of features

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

    2007-01-01

    The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

  17. Knowledge fusion: An approach to time series model selection followed by pattern recognition

    International Nuclear Information System (INIS)

    Bleasdale, S.A.; Burr, T.L.; Scovel, J.C.; Strittmatter, R.B.

    1996-03-01

    This report describes work done during FY 95 that was sponsored by the Department of Energy, Office of Nonproliferation and National Security, Knowledge Fusion Project. The project team selected satellite sensor data to use as the one main example for the application of its analysis algorithms. The specific sensor-fusion problem has many generic features, which make it a worthwhile problem to attempt to solve in a general way. The generic problem is to recognize events of interest from multiple time series that define a possibly noisy background. By implementing a suite of time series modeling and forecasting methods and using well-chosen alarm criteria, we reduce the number of false alarms. We then further reduce the number of false alarms by analyzing all suspicious sections of data, as judged by the alarm criteria, with pattern recognition methods. An accompanying report (Ref 1) describes the implementation and application of this 2-step process for separating events from unusual background and applies a suite of forecasting methods followed by a suite of pattern recognition methods. This report goes into more detail about one of the forecasting methods and one of the pattern recognition methods and is applied to the same kind of satellite-sensor data that is described in Ref. 1

  18. Selection of G-quadruplex folding topology with LNA-modified human telomeric sequences in K+ solution

    DEFF Research Database (Denmark)

    Pradhan, Devranjan; Hansen, Lykke H; Vester, Birte

    2011-01-01

    G-rich nucleic acid oligomers can form G-quadruplexes built by G-tetrads stacked upon each other. Depending on the nucleotide sequence, G-quadruplexes fold mainly with two topologies: parallel, in which all G-tracts are oriented parallel to each other, or antiparallel, in which one or more G......-tracts are oriented antiparallel to the other G-tracts. In the former topology, all glycosidic bond angles conform to anti conformations, while in the latter topology they adopt both syn and anti conformations. It is of interest to understand the molecular forces that govern G-quadruplex folding. Here, we approach...... this problem by examining the impact of LNA (locked nucleic acid) modifications on the folding topology of the dimeric model system of the human telomere sequence. In solution, this DNA G-quadruplex forms a mixture of G-quadruplexes with antiparallel and parallel topologies. Using CD and NMR spectroscopies, we...

  19. Unfolding a Problem

    Science.gov (United States)

    Currier, Sarah Cox

    2015-01-01

    In this article, Sarah Currier, a math specialist at Elizabeth Hall International School in Minnesota, describes how she used origami in a deliberate manner to teach content. She shares how she uses paper folding to teach mathematical concepts, reinforce vocabulary, and as a problem-solving model. She also offers ideas for using origami in other…

  20. A Review of Human Activity Recognition Methods

    Directory of Open Access Journals (Sweden)

    Michalis eVrigkas

    2015-11-01

    Full Text Available Recognizing human activities from video sequences or still images is a challenging task due to problems such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance. Many applications, including video surveillance systems, human-computer interaction, and robotics for human behavior characterization, require a multiple activity recognition system. In this work, we provide a detailed review of recent and state-of-the-art research advances in the field of human activity classification. We propose a categorization of human activity methodologies and discuss their advantages and limitations. In particular, we divide human activity classification methods into two large categories according to whether they use data from different modalities or not. Then, each of these categories is further analyzed into sub-categories, which reflect how they model human activities and what type of activities they are interested in. Moreover, we provide a comprehensive analysis of the existing, publicly available human activity classification datasets and examine the requirements for an ideal human activity recognition dataset. Finally, we report the characteristics of future research directions and present some open issues on human activity recognition.

  1. Multimodal approaches for emotion recognition: a survey

    Science.gov (United States)

    Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

    2005-01-01

    Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

  2. In vivo measurement of vocal fold surface resistance.

    Science.gov (United States)

    Mizuta, Masanobu; Kurita, Takashi; Dillon, Neal P; Kimball, Emily E; Garrett, C Gaelyn; Sivasankar, M Preeti; Webster, Robert J; Rousseau, Bernard

    2017-10-01

    A custom-designed probe was developed to measure vocal fold surface resistance in vivo. The purpose of this study was to demonstrate proof of concept of using vocal fold surface resistance as a proxy of functional tissue integrity after acute phonotrauma using an animal model. Prospective animal study. New Zealand White breeder rabbits received 120 minutes of airflow without vocal fold approximation (control) or 120 minutes of raised intensity phonation (experimental). The probe was inserted via laryngoscope and placed on the left vocal fold under endoscopic visualization. Vocal fold surface resistance of the middle one-third of the vocal fold was measured after 0 (baseline), 60, and 120 minutes of phonation. After the phonation procedure, the larynx was harvested and prepared for transmission electron microscopy. In the control group, vocal fold surface resistance values remained stable across time points. In the experimental group, surface resistance (X% ± Y% relative to baseline) was significantly decreased after 120 minutes of raised intensity phonation. This was associated with structural changes using transmission electron microscopy, which revealed damage to the vocal fold epithelium after phonotrauma, including disruption of the epithelium and basement membrane, dilated paracellular spaces, and alterations to epithelial microprojections. In contrast, control vocal fold specimens showed well-preserved stratified squamous epithelia. These data demonstrate the feasibility of measuring vocal fold surface resistance in vivo as a means of evaluating functional vocal fold epithelial barrier integrity. Device prototypes are in development for additional testing, validation, and for clinical applications in laryngology. NA Laryngoscope, 127:E364-E370, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

  3. Pseudomonas evades immune recognition of flagellin in both mammals and plants.

    Directory of Open Access Journals (Sweden)

    Bart W Bardoel

    2011-08-01

    Full Text Available The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5 in mammals and flagellin-sensitive 2 (FLS2 in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR antagonists, we screened bacterial supernatants and identified alkaline protease (AprA of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants.

  4. Event Recognition Based on Deep Learning in Chinese Texts.

    Directory of Open Access Journals (Sweden)

    Yajun Zhang

    Full Text Available Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM. Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN, then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

  5. Event Recognition Based on Deep Learning in Chinese Texts.

    Science.gov (United States)

    Zhang, Yajun; Liu, Zongtian; Zhou, Wen

    2016-01-01

    Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

  6. Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

    Science.gov (United States)

    Yin, Xi; Liu, Xiaoming

    2018-02-01

    This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.

  7. Fold and Fit: Space Conserving Shape Editing

    KAUST Repository

    Ibrahim, Mohamed

    2017-09-01

    We present a framework that folds man-made objects in a structure-aware manner for space-conserving storage and transportation. Given a segmented 3D mesh of a man-made object, our framework jointly optimizes for joint locations, the folding order, and folding angles for each part of the model, enabling it to transform into a spatially efficient configuration while keeping its original functionality as intact as possible. That is, if a model is supposed to withstand several forces in its initial state to serve its functionality, our framework places the joints between the parts of the model such that the model can withstand forces with magnitudes that are comparable to the magnitudes applied on the unedited model. Furthermore, if the folded shape is not compact, our framework proposes further segmentation of the model to improve its compactness in its folded state.

  8. Two-dimensional shape recognition using oriented-polar representation

    Science.gov (United States)

    Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li

    1997-10-01

    To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.

  9. Semantic and visual determinants of face recognition in a prosopagnosic patient.

    Science.gov (United States)

    Dixon, M J; Bub, D N; Arguin, M

    1998-05-01

    Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

  10. Self-folding miniature elastic electric devices

    International Nuclear Information System (INIS)

    Miyashita, Shuhei; Meeker, Laura; Rus, Daniela; Tolley, Michael T; Wood, Robert J

    2014-01-01

    Printing functional materials represents a considerable impact on the access to manufacturing technology. In this paper we present a methodology and validation of print-and-self-fold miniature electric devices. Polyvinyl chloride laminated sheets based on metalized polyester film show reliable self-folding processes under a heat application, and it configures 3D electric devices. We exemplify this technique by fabricating fundamental electric devices, namely a resistor, capacitor, and inductor. Namely, we show the development of a self-folded stretchable resistor, variable resistor, capacitive strain sensor, and an actuation mechanism consisting of a folded contractible solenoid coil. Because of their pre-defined kinematic design, these devices feature elasticity, making them suitable as sensors and actuators in flexible circuits. Finally, an RLC circuit obtained from the integration of developed devices is demonstrated, in which the coil based actuator is controlled by reading a capacitive strain sensor. (paper)

  11. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  12. Extended Target Recognition in Cognitive Radar Networks

    Directory of Open Access Journals (Sweden)

    Xiqin Wang

    2010-11-01

    Full Text Available We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR based sequential hypothesis testing (SHT framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS. Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

  13. EEG source imaging assists decoding in a face recognition task

    DEFF Research Database (Denmark)

    Andersen, Rasmus S.; Eliasen, Anders U.; Pedersen, Nicolai

    2017-01-01

    of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source...

  14. Improving entrepreneurial opportunity recognition through web content analytics

    Science.gov (United States)

    Bakar, Muhamad Shahbani Abu; Azmi, Azwiyati

    2017-10-01

    The ability to recognize and develop an opportunity into a venture defines an entrepreneur. Research in opportunity recognition has been robust and focuses more on explaining the processes involved in opportunity recognition. Factors such as prior knowledge, cognitive and creative capabilities are shown to affect opportunity recognition in entrepreneurs. Prior knowledge in areas such as customer problems, ways to serve the market, and technology has been shows in various studies to be a factor that facilitates entrepreneurs to identify and recognize opportunities. Findings from research also shows that experienced entrepreneurs search and scan for information to discover opportunities. Searching and scanning for information has also been shown to help novice entrepreneurs who lack prior knowledge to narrow this gap and enable them to better identify and recognize opportunities. There is less focus in research on finding empirically proven techniques and methods to develop and enhance opportunity recognition in student entrepreneurs. This is important as the country pushes for more graduate entrepreneurs that can drive the economy. This paper aims to discuss Opportunity Recognition Support System (ORSS), an information support system to help especially student entrepreneurs in identifying and recognizing business opportunities. The ORSS aims to provide the necessary knowledge to student entrepreneurs to be able to better identify and recognize opportunities. Applying design research, theories in opportunity recognition are applied to identify the requirements for the support system and the requirements in turn dictate the design of the support system. The paper proposes the use of web content mining and analytics as two core components and techniques for the support system. Web content mining can mine the vast knowledge repositories available on the internet and analytics can provide entrepreneurs with further insights into the information needed to recognize

  15. A multimodal approach to emotion recognition ability in autism spectrum disorders

    NARCIS (Netherlands)

    Jones, C.R.G.; Pickles, A.; Falcaro, M.; Marsden, A.J.S.; Happé, F.; Scott, S.K.; Sauter, D.; Tregay, J.; Phillips, R.J.; Baird, G.; Simonoff, E.; Charman, T.

    2011-01-01

    Background:  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,

  16. Microvascular lesions of the true vocal fold.

    Science.gov (United States)

    Postma, G N; Courey, M S; Ossoff, R H

    1998-06-01

    Microvascular lesions, also called varices or capillary ectasias, in contrast to vocal fold polyps with telangiectatic vessels, are relatively small lesions arising from the microcirculation of the vocal fold. Varices are most commonly seen in female professional vocalists and may be secondary to repetitive trauma, hormonal variations, or repeated inflammation. Microvascular lesions may either be asymptomatic or cause frank dysphonia by interrupting the normal vibratory pattern, mass, or closure of the vocal folds. They may also lead to vocal fold hemorrhage, scarring, or polyp formation. Laryngovideostroboscopy is the key in determining the functional significance of vocal fold varices. Management of patients with a varix includes medical therapy, speech therapy, and occasionally surgical vaporization. Indications for surgery are recurrent hemorrhage, enlargement of the varix, development of a mass in conjunction with the varix or hemorrhage, and unacceptable dysphonia after maximal medical and speech therapy due to a functionally significant varix.

  17. Approaching climate-adaptive facades with foldings

    DEFF Research Database (Denmark)

    Sack-Nielsen, Torsten

    2014-01-01

    envelopes based on folding principles such as origami. Three major aspects cover the project’s interest in this topic: Shape, kinetics and the application of new multi-functional materials form the interdisciplinary framework of this research. Shape// Initially small paper sketch models demonstrate folding...

  18. Folded Plate Structures as Building Envelopes

    DEFF Research Database (Denmark)

    Falk, Andreas; Buelow, Peter von; Kirkegaard, Poul Henning

    2012-01-01

    This paper treats applications of cross-laminated timber (CLT) in structural systems for folded façade solutions. Previous work on CLT-based systems for folded roofs has shown a widening range of structural possibilities to develop timber-based shells. Geometric and material properties play...... CLT-based systems, which are studied and analysed by using a combination of digital tools for structural and environmental design and analysis. The results show gainful, rational properties of folded systems and beneficial effects from an integration of architectural and environmental performance...... criteria in the design of CLT-based façades....

  19. Mechanical Models of Fault-Related Folding

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, A. M.

    2003-01-09

    The subject of the proposed research is fault-related folding and ground deformation. The results are relevant to oil-producing structures throughout the world, to understanding of damage that has been observed along and near earthquake ruptures, and to earthquake-producing structures in California and other tectonically-active areas. The objectives of the proposed research were to provide both a unified, mechanical infrastructure for studies of fault-related foldings and to present the results in computer programs that have graphical users interfaces (GUIs) so that structural geologists and geophysicists can model a wide variety of fault-related folds (FaRFs).

  20. Support vector machine-based facial-expression recognition method combining shape and appearance

    Science.gov (United States)

    Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

    2010-11-01

    Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

  1. Bifurcation of self-folded polygonal bilayers

    Science.gov (United States)

    Abdullah, Arif M.; Braun, Paul V.; Hsia, K. Jimmy

    2017-09-01

    Motivated by the self-assembly of natural systems, researchers have investigated the stimulus-responsive curving of thin-shell structures, which is also known as self-folding. Self-folding strategies not only offer possibilities to realize complicated shapes but also promise actuation at small length scales. Biaxial mismatch strain driven self-folding bilayers demonstrate bifurcation of equilibrium shapes (from quasi-axisymmetric doubly curved to approximately singly curved) during their stimulus-responsive morphing behavior. Being a structurally instable, bifurcation could be used to tune the self-folding behavior, and hence, a detailed understanding of this phenomenon is appealing from both fundamental and practical perspectives. In this work, we investigated the bifurcation behavior of self-folding bilayer polygons. For the mechanistic understanding, we developed finite element models of planar bilayers (consisting of a stimulus-responsive and a passive layer of material) that transform into 3D curved configurations. Our experiments with cross-linked Polydimethylsiloxane samples that change shapes in organic solvents confirmed our model predictions. Finally, we explored a design scheme to generate gripper-like architectures by avoiding the bifurcation of stimulus-responsive bilayers. Our research contributes to the broad field of self-assembly as the findings could motivate functional devices across multiple disciplines such as robotics, artificial muscles, therapeutic cargos, and reconfigurable biomedical devices.

  2. Action recognition using mined hierarchical compound features.

    Science.gov (United States)

    Gilbert, Andrew; Illingworth, John; Bowden, Richard

    2011-05-01

    The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical

  3. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  4. Coarsely resolved topography along protein folding pathways

    Science.gov (United States)

    Fernández, Ariel; Kostov, Konstantin S.; Berry, R. Stephen

    2000-03-01

    The kinetic data from the coarse representation of polypeptide torsional dynamics described in the preceding paper [Fernandez and Berry, J. Chem. Phys. 112, 5212 (2000), preceding paper] is inverted by using detailed balance to obtain a topographic description of the potential-energy surface (PES) along the dominant folding pathway of the bovine pancreatic trypsin inhibitor (BPTI). The topography is represented as a sequence of minima and effective saddle points. The dominant folding pathway displays an overall monotonic decrease in energy with a large number of staircaselike steps, a clear signature of a good structure-seeker. The diversity and availability of alternative folding pathways is analyzed in terms of the Shannon entropy σ(t) associated with the time-dependent probability distribution over the kinetic ensemble of contact patterns. Several stages in the folding process are evident. Initially misfolded states form and dismantle revealing no definite pattern in the topography and exhibiting high Shannon entropy. Passage down a sequence of staircase steps then leads to the formation of a nativelike intermediate, for which σ(t) is much lower and fairly constant. Finally, the structure of the intermediate is refined to produce the native state of BPTI. We also examine how different levels of tolerance to mismatches of side chain contacts influence the folding kinetics, the topography of the dominant folding pathway, and the Shannon entropy. This analysis yields upper and lower bounds of the frustration tolerance required for the expeditious and robust folding of BPTI.

  5. Single injection of basic fibroblast growth factor to treat severe vocal fold lesions and vocal fold paralysis.

    Science.gov (United States)

    Kanazawa, Takeharu; Komazawa, Daigo; Indo, Kanako; Akagi, Yusuke; Lee, Yogaku; Nakamura, Kazuhiro; Matsushima, Koji; Kunieda, Chikako; Misawa, Kiyoshi; Nishino, Hiroshi; Watanabe, Yusuke

    2015-10-01

    Severe vocal fold lesions such as vocal fold sulcus, scars, and atrophy induce a communication disorder due to severe hoarseness, but a treatment has not been established. Basic fibroblast growth factor (bFGF) therapies by either four-time repeated local injections or regenerative surgery for vocal fold scar and sulcus have previously been reported, and favorable outcomes have been observed. In this study, we modified bFGF therapy using a single of bFGF injection, which may potentially be used in office procedures. Retrospective chart review. Five cases of vocal fold sulcus, six cases of scars, seven cases of paralysis, and 17 cases of atrophy were treated by a local injection of bFGF. The injection regimen involved injecting 50 µg of bFGF dissolved in 0.5 mL saline only once into the superficial lamina propria using a 23-gauge injection needle. Two months to 3 months after the injection, phonological outcomes were evaluated. The maximum phonation time (MPT), mean airflow rate, pitch range, speech fundamental frequency, jitter, and voice handicap index improved significantly after the bFGF injection. Furthermore, improvement in the MPT was significantly greater in patients with (in increasing order) vocal fold atrophy, scar, and paralysis. The improvement in the MPT among all patients was significantly correlated with age; the MPT improved more greatly in younger patients. Regenerative treatments by bFGF injection—even a single injection—effectively improve vocal function in vocal fold lesions. 4 © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  6. A comparison of RNA folding measures

    DEFF Research Database (Denmark)

    Freyhult, E.; Gardner, P. P.; Moulton, V.

    2005-01-01

    the behaviour of these measures over a large range of Rfam ncRNA families. Such measures can be useful in, for example, identifying novel ncRNAs, and indicating the presence of alternate RNA foldings. Results Our analysis shows that ncRNAs, but not mRNAs, in general have lower minimal free energy (MFE) than....... Conclusion Due to the correlations between the different measures we find that it is sufficient to use only two of them in RNA folding studies, one to test if the sequence in question has lower energy than a random sequence with the same dinucleotide frequency (the Z-score) and the other to see......Background In the last few decades there has been a great deal of discussion concerning whether or not noncoding RNA sequences (ncRNAs) fold in a more well-defined manner than random sequences. In this paper, we investigate several existing measures for how well an RNA sequence folds, and compare...

  7. Human Wearable Attribute Recognition Using Probability-Map-Based Decomposition of Thermal Infrared Images

    OpenAIRE

    KRESNARAMAN, Brahmastro; KAWANISHI, Yasutomo; DEGUCHI, Daisuke; TAKAHASHI, Tomokazu; MEKADA, Yoshito; IDE, Ichiro; MURASE, Hiroshi

    2017-01-01

    This paper addresses the attribute recognition problem, a field of research that is dominated by studies in the visible spectrum. Only a few works are available in the thermal spectrum, which is fundamentally different from the visible one. This research performs recognition specifically on wearable attributes, such as glasses and masks. Usually these attributes are relatively small in size when compared with the human body, on top of a large intra-class variation of the human body itself, th...

  8. Study on road sign recognition in LabVIEW

    Science.gov (United States)

    Panoiu, M.; Rat, C. L.; Panoiu, C.

    2016-02-01

    Road and traffic sign identification is a field of study that can be used to aid the development of in-car advisory systems. It uses computer vision and artificial intelligence to extract the road signs from outdoor images acquired by a camera in uncontrolled lighting conditions where they may be occluded by other objects, or may suffer from problems such as color fading, disorientation, variations in shape and size, etc. An automatic means of identifying traffic signs, in these conditions, can make a significant contribution to develop an Intelligent Transport Systems (ITS) that continuously monitors the driver, the vehicle, and the road. Road and traffic signs are characterized by a number of features which make them recognizable from the environment. Road signs are located in standard positions and have standard shapes, standard colors, and known pictograms. These characteristics make them suitable for image identification. Traffic sign identification covers two problems: traffic sign detection and traffic sign recognition. Traffic sign detection is meant for the accurate localization of traffic signs in the image space, while traffic sign recognition handles the labeling of such detections into specific traffic sign types or subcategories [1].

  9. Discriminant WSRC for Large-Scale Plant Species Recognition

    Directory of Open Access Journals (Sweden)

    Shanwen Zhang

    2017-01-01

    Full Text Available In sparse representation based classification (SRC and weighted SRC (WSRC, it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.

  10. Evaluation of automatic face recognition for automatic border control on actual data recorded of travellers at Schiphol Airport

    NARCIS (Netherlands)

    Spreeuwers, Lieuwe Jan; Hendrikse, A.J.; Gerritsen, K.J.; Brömme, A.; Busch, C.

    2012-01-01

    Automatic border control at airports using automated facial recognition for checking the passport is becoming more and more common. A problem is that it is not clear how reliable these automatic gates are. Very few independent studies exist that assess the reliability of automated facial recognition

  11. ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering

    Science.gov (United States)

    Ren, Xiang; El-Kishky, Ahmed; Wang, Chi; Tao, Fangbo; Voss, Clare R.; Ji, Heng; Han, Jiawei

    2015-01-01

    Entity recognition is an important but challenging research problem. In reality, many text collections are from specific, dynamic, or emerging domains, which poses significant new challenges for entity recognition with increase in name ambiguity and context sparsity, requiring entity detection without domain restriction. In this paper, we investigate entity recognition (ER) with distant-supervision and propose a novel relation phrase-based ER framework, called ClusType, that runs data-driven phrase mining to generate entity mention candidates and relation phrases, and enforces the principle that relation phrases should be softly clustered when propagating type information between their argument entities. Then we predict the type of each entity mention based on the type signatures of its co-occurring relation phrases and the type indicators of its surface name, as computed over the corpus. Specifically, we formulate a joint optimization problem for two tasks, type propagation with relation phrases and multi-view relation phrase clustering. Our experiments on multiple genres—news, Yelp reviews and tweets—demonstrate the effectiveness and robustness of ClusType, with an average of 37% improvement in F1 score over the best compared method. PMID:26705503

  12. The Ventricular-Fold Dynamics in Human Phonation

    OpenAIRE

    Bailly , Lucie; Henrich Bernardoni , Nathalie; Müller , Frank; Rohlfs , Anna-Katharina; Hess , Markus

    2014-01-01

    International audience; Purpose: In this study, the authors aimed (a) to provide a classification of the ventricular-fold dynamics during voicing, (b) to study the aerodynamic impact of these motions on vocal-fold vibrations, and (c) to assess whether ventricularfold oscillations could be sustained by aerodynamic coupling with the vocal folds. Method: A 72-sample database of vocal gestures accompanying different acoustical events comprised highspeed cinematographic, audio, and electroglottogr...

  13. Single-Chain Folding of Synthetic Polymers: A Critical Update.

    Science.gov (United States)

    Altintas, Ozcan; Barner-Kowollik, Christopher

    2015-11-23

    The current contribution serves as a critical update to a previous feature article from us (Macromol. Rapid Commun. 2012, 33, 958-971), and highlights the latest advances in the preparation of single chain polymeric nanoparticles and initial-yet promising-attempts towards mimicking the structure of natural biomacromolecules via single-chain folding of well-defined linear polymers via so-called single chain selective point folding and repeat unit folding. The contribution covers selected examples from the literature published up to ca. September 2015. Our aim is not to provide an exhaustive review but rather highlight a selection of new and exciting examples for single-chain folding based on advanced macromolecular precision chemistry. Initially, the discussion focuses on the synthesis and characterization of single-chain folded structures via selective point folding. The second part of the feature article addresses the folding of well-defined single-chain polymers by means of repeat unit folding. The current state of the art in the field of single-chain folding indicates that repeat unit folding-driven nanoparticle preparation is well-advanced, while initial encouraging steps towards building selective point folding systems have been taken. In addition, a summary of the-in our view-open key questions is provided that may guide future biomimetic design efforts. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Ring recognition in the CBM RICH detector

    International Nuclear Information System (INIS)

    Lebedev, S.; Ososkov, G.; Hoehne, C.

    2007-01-01

    Two algorithms of ring recognition, a standalone ring finder (using only RICH information) and an algorithm based on the information from vertex tracks are described. The fake ring problem and its solution using a set of two-dimensional cuts or an artificial neural network are discussed. Results of a comparative study are given. All developed algorithms were tested on large statistics of simulated events and were then included into the CBM framework for common use

  15. Adipose-Derived Mesenchymal Stem Cells in the Regeneration of Vocal Folds: A Study on a Chronic Vocal Fold Scar

    Directory of Open Access Journals (Sweden)

    Angelou Valerie

    2016-01-01

    Full Text Available Background. The aim of the study was to assess the histological effects of autologous infusion of adipose-derived stem cells (ADSC on a chronic vocal fold scar in a rabbit model as compared to an untreated scar as well as in injection of hyaluronic acid. Study Design. Animal experiment. Method. We used 74 New Zealand rabbits. Sixteen of them were used as control/normal group. We created a bilateral vocal fold wound in the remaining 58 rabbits. After 18 months we separated our population into three groups. The first group served as control/scarred group. The second one was injected with hyaluronic acid in the vocal folds, and the third received an autologous adipose-derived stem cell infusion in the scarred vocal folds (ADSC group. We measured the variation of thickness of the lamina propria of the vocal folds and analyzed histopathologic changes in each group after three months. Results. The thickness of the lamina propria was significantly reduced in the group that received the ADSC injection, as compared to the normal/scarred group. The collagen deposition, the hyaluronic acid, the elastin levels, and the organization of elastic fibers tend to return to normal after the injection of ADSC. Conclusions. Autologous injection of adipose-derived stem cells on a vocal fold chronic scar enhanced the healing of the vocal folds and the reduction of the scar tissue, even when compared to other treatments.

  16. Adipose-Derived Mesenchymal Stem Cells in the Regeneration of Vocal Folds: A Study on a Chronic Vocal Fold Scar

    Science.gov (United States)

    Vassiliki, Kalodimou; Irini, Messini; Nikolaos, Psychalakis; Karampela, Eleftheria; Apostolos, Papalois

    2016-01-01

    Background. The aim of the study was to assess the histological effects of autologous infusion of adipose-derived stem cells (ADSC) on a chronic vocal fold scar in a rabbit model as compared to an untreated scar as well as in injection of hyaluronic acid. Study Design. Animal experiment. Method. We used 74 New Zealand rabbits. Sixteen of them were used as control/normal group. We created a bilateral vocal fold wound in the remaining 58 rabbits. After 18 months we separated our population into three groups. The first group served as control/scarred group. The second one was injected with hyaluronic acid in the vocal folds, and the third received an autologous adipose-derived stem cell infusion in the scarred vocal folds (ADSC group). We measured the variation of thickness of the lamina propria of the vocal folds and analyzed histopathologic changes in each group after three months. Results. The thickness of the lamina propria was significantly reduced in the group that received the ADSC injection, as compared to the normal/scarred group. The collagen deposition, the hyaluronic acid, the elastin levels, and the organization of elastic fibers tend to return to normal after the injection of ADSC. Conclusions. Autologous injection of adipose-derived stem cells on a vocal fold chronic scar enhanced the healing of the vocal folds and the reduction of the scar tissue, even when compared to other treatments. PMID:26933440

  17. Community recognition and beliefs about anorexia nervosa and its treatment.

    Science.gov (United States)

    Darby, Anita M; Hay, Phillipa J; Mond, Jonathan M; Quirk, Frances

    2012-01-01

    Mental Health Literacy (MHL), namely recognition, and beliefs about treatment concerning Anorexia Nervosa (AN) were examined in a community sample of male and female (n = 983) aged 15-94 years. A vignette describing a women suffering from the symptoms of AN was presented, followed by a respondent-based structured interview concerning recognition of the problem and treatment beliefs. The majority of participants could identify the problem as that of an eating disorder, although only 16.1% could specifically identify it as AN. Many also believed the problem was primarily one of low self-esteem (32.5%). General practitioners and psychiatrists or psychologists were considered the most helpful treatment providers, while obtaining information about the problem and available services, followed by family therapy, were considered the most helpful treatments. Less than one-third of participants believed complete recovery was possible. Better AN MHL was found in younger, higher educated, and metropolitan domiciled females. This study offers encouraging results in regard to AN MHL. In particular, there was moderate regard for the use of mental health specialists in the treatment of the disorder. However, there appears to be a misconception that AN is largely the manifestation of low self-esteem and confusion concerning the distinction between AN and bulimia nervosa. AN MHL was poorer in males and those with higher social and health disadvantage. Copyright © 2010 Wiley Periodicals, Inc.

  18. Face recognition based on two-dimensional discriminant sparse preserving projection

    Science.gov (United States)

    Zhang, Dawei; Zhu, Shanan

    2018-04-01

    In this paper, a supervised dimensionality reduction algorithm named two-dimensional discriminant sparse preserving projection (2DDSPP) is proposed for face recognition. In order to accurately model manifold structure of data, 2DDSPP constructs within-class affinity graph and between-class affinity graph by the constrained least squares (LS) and l1 norm minimization problem, respectively. Based on directly operating on image matrix, 2DDSPP integrates graph embedding (GE) with Fisher criterion. The obtained projection subspace preserves within-class neighborhood geometry structure of samples, while keeping away samples from different classes. The experimental results on the PIE and AR face databases show that 2DDSPP can achieve better recognition performance.

  19. Effect of Vocal Fold Medialization on Dysphagia in Patients with Unilateral Vocal Fold Immobility.

    Science.gov (United States)

    Cates, Daniel J; Venkatesan, Naren N; Strong, Brandon; Kuhn, Maggie A; Belafsky, Peter C

    2016-09-01

    The effect of vocal fold medialization (VFM) on vocal improvement in persons with unilateral vocal fold immobility (UVFI) is well established. The effect of VFM on the symptom of dysphagia is uncertain. The purpose of this study is to evaluate dysphagia symptoms in patients with UVFI pre- and post-VFM. Case series with chart review. Academic tertiary care medical center. The charts of 44 persons with UVFI who underwent VFM between June 1, 2013, and December 31, 2014, were abstracted from a prospectively maintained database at the University of California, Davis, Voice and Swallowing Center. Patient demographics, indications, and type of surgical procedure were recorded. Self-reported swallowing impairment was assessed with the validated 10-item Eating Assessment Tool (EAT-10) before and after surgery. A paired samples t test was used to compare pre- and postmedialization EAT-10 scores. Forty-four patients met criteria and underwent either vocal fold injection (73%) or thyroplasty (27%). Etiologies of vocal fold paralysis were iatrogenic (55%), idiopathic (29%), benign or malignant neoplastic (9%), traumatic (5%), or related to the late effects of radiation (2%). EAT-10 (mean ± SD) scores improved from 12.2 ± 11.1 to 7.7 ± 7.2 after medialization (P dysphagia and report significant improvement in swallowing symptoms following VFM. The symptomatic improvement appears to be durable over time. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

  20. Word-level recognition of multifont Arabic text using a feature vector matching approach

    Science.gov (United States)

    Erlandson, Erik J.; Trenkle, John M.; Vogt, Robert C., III

    1996-03-01

    Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. An alternative approach is to recognize text imagery at the word level, without analyzing individual characters. This approach avoids the problem of individual character segmentation, and can overcome local errors in character recognition. A word-level recognition system for machine-printed Arabic text has been implemented. Arabic is a script language, and is therefore difficult to segment at the character level. Character segmentation has been avoided by recognizing text imagery of complete words. The Arabic recognition system computes a vector of image-morphological features on a query word image. This vector is matched against a precomputed database of vectors from a lexicon of Arabic words. Vectors from the database with the highest match score are returned as hypotheses for the unknown image. Several feature vectors may be stored for each word in the database. Database feature vectors generated using multiple fonts and noise models allow the system to be tuned to its input stream. Used in conjunction with database pruning techniques, this Arabic recognition system has obtained promising word recognition rates on low-quality multifont text imagery.

  1. Nomenclature proposal to describe vocal fold motion impairment

    NARCIS (Netherlands)

    Rosen, Clark A.; Mau, Ted; Remacle, Marc; Hess, Markus; Eckel, Hans E.; Young, VyVy N.; Hantzakos, Anastasios; Yung, Katherine C.; Dikkers, Frederik G.

    2016-01-01

    The terms used to describe vocal fold motion impairment are confusing and not standardized. This results in a failure to communicate accurately and to major limitations of interpreting research studies involving vocal fold impairment. We propose standard nomenclature for reporting vocal fold

  2. Nomenclature proposal to describe vocal fold motion impairment

    NARCIS (Netherlands)

    Rosen, Clark A.; Mau, Ted; Remacle, Marc; Hess, Markus; Eckel, Hans E.; Young, VyVy N.; Hantzakos, Anastasios; Yung, Katherine C.; Dikkers, Frederik G.

    The terms used to describe vocal fold motion impairment are confusing and not standardized. This results in a failure to communicate accurately and to major limitations of interpreting research studies involving vocal fold impairment. We propose standard nomenclature for reporting vocal fold

  3. Curved Folded Plate Timber Structures

    OpenAIRE

    Buri, Hans Ulrich; Stotz, Ivo; Weinand, Yves

    2011-01-01

    This work investigates the development of a Curved Origami Prototype made with timber panels. In the last fifteen years the timber industry has developed new, large size, timber panels. Composition and dimensions of these panels and the possibility of milling them with Computer Numerical Controlled machines shows great potential for folded plate structures. To generate the form of these structures we were inspired by Origami, the Japanese art of paper folding. Common paper tessellations are c...

  4. Dysphonia and vocal fold telangiectasia in hereditary hemorrhagic telangiectasia.

    Science.gov (United States)

    Chang, Joseph; Yung, Katherine C

    2014-11-01

    This case report is the first documentation of dysphonia and vocal fold telangiectasia as a complication of hereditary hemorrhagic telangiectasia (HHT). Case report of a 40-year-old man with HHT presenting with 2 years of worsening hoarseness. Hoarseness corresponded with a period of anticoagulation. Endoscopy revealed vocal fold scarring, vocal fold telangiectasias, and plica ventricular is suggestive of previous submucosal vocal fold hemorrhage and subsequent counterproductive compensation with ventricular phonation. Hereditary hemorrhagic telangiectasia may present as dysphonia with vocal fold telangiectasias and place patients at risk of vocal fold hemorrhage. © The Author(s) 2014.

  5. Neurocomputing methods for pattern recognition in nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Gyulassy, M.; Dong, D.; Harlander, M. [Lawrence Berkeley Lab., CA (United States)

    1991-12-31

    We review recent progress on the development and applications of novel neurocomputing techniques for pattern recognition problems of relevance to RHIC experiments. The Elastic Tracking algorithm is shown to achieve sub-pad two track resolution without preprocessing. A high pass neural filter is developed for jet analysis and singular deconvolution methods are shown to recover the primordial jet distribution to a surprising high degree of accuracy.

  6. Pattern recognition as a method of data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Caputo, M.

    1978-11-15

    The method of pattern recognition has been used in biological and social sciences and has been recently introduced for the solution of geological and geophysical problems such as oil and ore prospecting and seismological prediction. The method is briefly illustrated by an application to earthquake prediction in Italy in which topographic and geologic maps are used in conjunction with earthquake catalogs. 3 figures, 1 table.

  7. Accurately controlled sequential self-folding structures by polystyrene film

    Science.gov (United States)

    Deng, Dongping; Yang, Yang; Chen, Yong; Lan, Xing; Tice, Jesse

    2017-08-01

    Four-dimensional (4D) printing overcomes the traditional fabrication limitations by designing heterogeneous materials to enable the printed structures evolve over time (the fourth dimension) under external stimuli. Here, we present a simple 4D printing of self-folding structures that can be sequentially and accurately folded. When heated above their glass transition temperature pre-strained polystyrene films shrink along the XY plane. In our process silver ink traces printed on the film are used to provide heat stimuli by conducting current to trigger the self-folding behavior. The parameters affecting the folding process are studied and discussed. Sequential folding and accurately controlled folding angles are achieved by using printed ink traces and angle lock design. Theoretical analyses are done to guide the design of the folding processes. Programmable structures such as a lock and a three-dimensional antenna are achieved to test the feasibility and potential applications of this method. These self-folding structures change their shapes after fabrication under controlled stimuli (electric current) and have potential applications in the fields of electronics, consumer devices, and robotics. Our design and fabrication method provides an easy way by using silver ink printed on polystyrene films to 4D print self-folding structures for electrically induced sequential folding with angular control.

  8. Action recognition in depth video from RGB perspective: A knowledge transfer manner

    Science.gov (United States)

    Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

    2018-03-01

    Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

  9. A hydrogel actuator with flexible folding deformation and shape programming via using sodium carboxymethyl cellulose and acrylic acid.

    Science.gov (United States)

    Wu, Shuiping; Yu, Feng; Dong, Hua; Cao, Xiaodong

    2017-10-01

    Hydrogel actuator is an intelligent material, which can work as artificial muscle. However, most present hydrogel actuators, due to the inferior mechanical property and uncontrolled folding property, have always resulted in slipping off or the failure of grasping an object with specific shape and required weight. In order to solve this problem, here a tough hydrogel actuator with programmable folding deformation has been prepared by combining the "selective implanting method" and "ionic coordination". The shape and folding angle (from 0 to 180 o ) of hydrogel actuator can be precisely controlled by altering the location and size of the implanting parts that seems like the joints of finger. The ionic coordination is not only the force to trigger the folding of hydrogel, but also utilized to reinforce the mechanical property. We believed the superior mechanical and shape-programmable property can endow the hydrogel actuator with great application prospect in soft machine. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Apply lightweight recognition algorithms in optical music recognition

    Science.gov (United States)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  11. Is voice therapy effective for the treatment of dysphonic patients with benign vocal fold lesions?

    Science.gov (United States)

    Ogawa, Makoto; Inohara, Hidenori

    2017-08-22

    To update our knowledge regarding the effectiveness of voice therapy for the treatment of vocal disturbance associated with benign vocal fold lesions, including vocal polyps, nodules and cysts, and for determining the utility of voice therapy in treating organic voice disorders, while highlighting problems for the future development of this clinical field. We conducted a review of the most recent literature on the therapeutic effects of voice therapy, vocal hygiene education or direct vocal training on vocal quality, the lesion appearance and discomfort felt by patients due to the clinical entity of benign vocal fold mass lesions. Although voice therapy is principally indicated for the treatment of functional dysphonia without any organic abnormalities in the vocal folds, a number of clinicians have attempted to perform voice therapy even in dysphonic patients with benign mass lesions in the vocal folds. The two major possible reasons for the effectiveness of voice therapy on vocal disturbance associated with benign vocal fold lesions are hypothesized to be the regression of lesions and the correction of excessive/inappropriate muscle contraction of the phonatory organs. According to the current literature, a substantial proportion of vocal polyps certainly tend to shrink after voice therapy, but whether or not the regression results from voice therapy, vocal hygiene education or a natural cure is unclear at present due to the lack of controlled studies comparing two groups with and without interventions. Regarding vocal nodules, no studies have investigated the effectiveness of voice therapy using proper experimental methodology. Vocal cysts are difficult to cure by voice therapy without surgical excision according to previous studies. Evidences remains insufficient to support the use of voice therapy against benign vocal fold lesions. Evidences at present is therefore still insufficient to support the use of voice therapy for the treatment of benign vocal fold

  12. Compressed sensing method for human activity recognition using tri-axis accelerometer on mobile phone

    Institute of Scientific and Technical Information of China (English)

    Song Hui; Wang Zhongmin

    2017-01-01

    The diversity in the phone placements of different mobile users' dailylife increases the difficulty of recognizing human activities by using mobile phone accelerometer data.To solve this problem,a compressed sensing method to recognize human activities that is based on compressed sensing theory and utilizes both raw mobile phone accelerometer data and phone placement information is proposed.First,an over-complete dictionary matrix is constructed using sufficient raw tri-axis acceleration data labeled with phone placement information.Then,the sparse coefficient is evaluated for the samples that need to be tested by resolving L1 minimization.Finally,residual values are calculated and the minimum value is selected as the indicator to obtain the recognition results.Experimental results show that this method can achieve a recognition accuracy reaching 89.86%,which is higher than that of a recognition method that does not adopt the phone placement information for the recognition process.The recognition accuracy of the proposed method is effective and satisfactory.

  13. Improving decoy databases for protein folding algorithms

    KAUST Repository

    Lindsey, Aaron

    2014-01-01

    Copyright © 2014 ACM. Predicting protein structures and simulating protein folding are two of the most important problems in computational biology today. Simulation methods rely on a scoring function to distinguish the native structure (the most energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing redundant structures. We test our approach on 17 different decoy databases of varying size and type and show significant improvement across a variety of metrics. We also test our improved databases on a popular modern scoring function and show that they contain a greater number of native-like structures than the original databases, thereby producing a more rigorous database for testing scoring functions.

  14. Structural pattern recognition methods based on string comparison for fusion databases

    International Nuclear Information System (INIS)

    Dormido-Canto, S.; Farias, G.; Dormido, R.; Vega, J.; Sanchez, J.; Duro, N.; Vargas, H.; Ratta, G.; Pereira, A.; Portas, A.

    2008-01-01

    Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed

  15. Structural pattern recognition methods based on string comparison for fusion databases

    Energy Technology Data Exchange (ETDEWEB)

    Dormido-Canto, S. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain)], E-mail: sebas@dia.uned.es; Farias, G.; Dormido, R. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain); Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Ratta, G.; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain)

    2008-04-15

    Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed.

  16. Unraveling metamaterial properties in zigzag-base folded sheets.

    Science.gov (United States)

    Eidini, Maryam; Paulino, Glaucio H

    2015-09-01

    Creating complex spatial objects from a flat sheet of material using origami folding techniques has attracted attention in science and engineering. In the present work, we use the geometric properties of partially folded zigzag strips to better describe the kinematics of known zigzag/herringbone-base folded sheet metamaterials such as Miura-ori. Inspired by the kinematics of a one-degree of freedom zigzag strip, we introduce a class of cellular folded mechanical metamaterials comprising different scales of zigzag strips. This class of patterns combines origami folding techniques with kirigami. Using analytical and numerical models, we study the key mechanical properties of the folded materials. We show that our class of patterns, by expanding on the design space of Miura-ori, is appropriate for a wide range of applications from mechanical metamaterials to deployable structures at small and large scales. We further show that, depending on the geometry, these materials exhibit either negative or positive in-plane Poisson's ratios. By introducing a class of zigzag-base materials in the current study, we unify the concept of in-plane Poisson's ratio for similar materials in the literature and extend it to the class of zigzag-base folded sheet materials.

  17. Parametric HMMs for Movement Recognition and Synthesis

    DEFF Research Database (Denmark)

    Herzog, Dennis; Krüger, Volker

    2009-01-01

    , we develop an exemplar-based parametric hidden Markov model (PHMM) that allows to represent movements of a particular type. Since we use model interpolation to reduce the necessary amount of training data, we had to develop a method to setup local models in a synchronized way. In our experiments we......A common problem in human movement recognition is the recognition of movements of a particular type (semantic). E.g., grasping movements have a particular semantic (grasping) but the actual movements usually have very different appearances due to, e.g., different grasping directions. In this paper...... to recover the movement type, and, e.g., the object position a human is pointing at. Our experiments show the flexibility of the PHMMs in terms of the amount of training data and its robustness in terms of noisy observation data. In addition, we compare our PHMM to an other kind of PHMM, which has been...

  18. Action Recognition Using Discriminative Structured Trajectory Groups

    KAUST Repository

    Atmosukarto, Indriyati

    2015-01-06

    In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.

  19. Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

    Science.gov (United States)

    Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

    2017-04-15

    Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain

  20. Binary pattern flavored feature extractors for Facial Expression Recognition: An overview

    DEFF Research Database (Denmark)

    Kristensen, Rasmus Lyngby; Tan, Zheng-Hua; Ma, Zhanyu

    2015-01-01

    This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression Recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER...