EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation

PubMed Central

Amidi, Afshine; Megalooikonomou, Vasileios; Paragios, Nikos

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet. PMID:29740518

EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation.

PubMed

Amidi, Afshine; Amidi, Shervine; Vlachakis, Dimitrios; Megalooikonomou, Vasileios; Paragios, Nikos; Zacharaki, Evangelia I

2018-01-01

During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems. The size of the Protein Data Bank (PDB) has increased more than 15-fold since 1999, which enabled the expansion of models that aim at predicting enzymatic function via their amino acid composition. Amino acid sequence, however, is less conserved in nature than protein structure and therefore considered a less reliable predictor of protein function. This paper presents EnzyNet, a novel 3D convolutional neural networks classifier that predicts the Enzyme Commission number of enzymes based only on their voxel-based spatial structure. The spatial distribution of biochemical properties was also examined as complementary information. The two-layer architecture was investigated on a large dataset of 63,558 enzymes from the PDB and achieved an accuracy of 78.4% by exploiting only the binary representation of the protein shape. Code and datasets are available at https://github.com/shervinea/enzynet.

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

Mapping Hydrophobicity on the Protein Molecular Surface at Atom-Level Resolution

PubMed Central

Nicolau Jr., Dan V.; Paszek, Ewa; Fulga, Florin; Nicolau, Dan V.

2014-01-01

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 Å, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced “leopard skin”-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism. PMID:25462574

Promoting Student Development of Models and Scientific Inquiry Skills in Acid-Base Chemistry: An Important Skill Development in Preparation for AP Chemistry

ERIC Educational Resources Information Center

Hale-Hanes, Cara

2015-01-01

In this study, two groups of 11th grade chemistry students (n = 210) performed a sequence of hands-on and virtual laboratories that were progressively more inquiry-based. One-half of the students did the laboratory sequence with the addition of a teacher-led discussion connecting student data to student-generated visual representations of…

SA-Search: a web tool for protein structure mining based on a Structural Alphabet

PubMed Central

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-01-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search. PMID:15215446

SA-Search: a web tool for protein structure mining based on a Structural Alphabet.

PubMed

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-07-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search.

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

WebLogo

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

Crooks, Gavin E.

WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible. Sequesnce logos are a graphical representation of an amino acid or nucleic acid multiple sequence alignment developed by Tom Schneider and Mike Stephens. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. In general, a sequence logo provides a richermore » and more precise description of, for example, a binding site, than would a consensus sequence.« less

Representation mutations from standard genetic codes

NASA Astrophysics Data System (ADS)

Aisah, I.; Suyudi, M.; Carnia, E.; Suhendi; Supriatna, A. K.

2018-03-01

Graph is widely used in everyday life especially to describe model problem and describe it concretely and clearly. In addition graph is also used to facilitate solve various kinds of problems that are difficult to be solved by calculation. In Biology, graph can be used to describe the process of protein synthesis in DNA. Protein has an important role for DNA (deoxyribonucleic acid) or RNA (ribonucleic acid). Proteins are composed of amino acids. In this study, amino acids are related to genetics, especially the genetic code. The genetic code is also known as the triplet or codon code which is a three-letter arrangement of DNA nitrogen base. The bases are adenine (A), thymine (T), guanine (G) and cytosine (C). While on RNA thymine (T) is replaced with Urasil (U). The set of all Nitrogen bases in RNA is denoted by N = {C U, A, G}. This codon works at the time of protein synthesis inside the cell. This codon also encodes the stop signal as a sign of the stop of protein synthesis process. This paper will examine the process of protein synthesis through mathematical studies and present it in three-dimensional space or graph. The study begins by analysing the set of all codons denoted by NNN such that to obtain geometric representations. At this stage there is a matching between the sets of all nitrogen bases N with Z 2 × Z 2; C=(\\overline{0},\\overline{0}),{{U}}=(\\overline{0},\\overline{1}),{{A}}=(\\overline{1},\\overline{0}),{{G}}=(\\overline{1},\\overline{1}). By matching the algebraic structure will be obtained such as group, group Klein-4,Quotien group etc. With the help of Geogebra software, the set of all codons denoted by NNN can be presented in a three-dimensional space as a multicube NNN and also can be represented as a graph, so that can easily see relationship between the codon.

Relationship of students' conceptual representations and problem-solving abilities in acid-base chemistry

NASA Astrophysics Data System (ADS)

Powers, Angela R.

2000-10-01

This study explored the relationship between secondary chemistry students' conceptual representations of acid-base chemistry, as shown in student-constructed concept maps, and their ability to solve acid-base problems, represented by their score on an 18-item paper and pencil test, the Acid-Base Concept Assessment (ABCA). The ABCA, consisting of both multiple-choice and short-answer items, was originally designed using a question-type by subtopic matrix, validated by a panel of experts, and refined through pilot studies and factor analysis to create the final instrument. The concept map task included a short introduction to concept mapping, a prototype concept map, a practice concept-mapping activity, and the instructions for the acid-base concept map task. The instruments were administered to chemistry students at two high schools; 108 subjects completed both instruments for this study. Factor analysis of ABCA results indicated that the test was unifactorial for these students, despite the intention to create an instrument with multiple "question-type" scales. Concept maps were scored both holistically and by counting valid concepts. The two approaches were highly correlated (r = 0.75). The correlation between ABCA score and concept-map score was 0.29 for holistically-scored concept maps and 0.33 for counted-concept maps. Although both correlations were significant, they accounted for only 8.8 and 10.2% of variance in ABCA scores, respectively. However, when the reliability of the instruments used is considered, more than 20% of the variance in ABCA scores may be explained by concept map scores. MANOVAs for ABCA and concept map scores by instructor, student gender, and year in school showed significant differences for both holistic and counted concept-map scores. Discriminant analysis revealed that the source of these differences was the instruction variable. Significant differences between classes receiving different instruction were found in the frequency of concepts listed by students for 9 of 10 concepts evaluated. Mean ABCA scores did not differ significantly between the two instruction groups. The results of this study failed to provide evidence of conceptual distinctions among different "types" of problem-solving items. The results suggested that several factors influence success in chemistry problem solving, including concept knowledge and organization. Further research into the nature of chemistry problems and problem solving is recommended.

modlAMP: Python for antimicrobial peptides.

PubMed

Müller, Alex T; Gabernet, Gisela; Hiss, Jan A; Schneider, Gisbert

2017-09-01

We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled datasets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra. The modlAMP Python package is available under the BSD license from URL http://doi.org/10.5905/ethz-1007-72 or via pip from the Python Package Index (PyPI). gisbert.schneider@pharma.ethz.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing; Yan, Gui-Ying

2016-12-23

Protein-protein interactions (PPIs) are essential to most biological processes. Since bioscience has entered into the era of genome and proteome, there is a growing demand for the knowledge about PPI network. High-throughput biological technologies can be used to identify new PPIs, but they are expensive, time-consuming, and tedious. Therefore, computational methods for predicting PPIs have an important role. For the past years, an increasing number of computational methods such as protein structure-based approaches have been proposed for predicting PPIs. The major limitation in principle of these methods lies in the prior information of the protein to infer PPIs. Therefore, it is of much significance to develop computational methods which only use the information of protein amino acids sequence. Here, we report a highly efficient approach for predicting PPIs. The main improvements come from the use of a novel protein sequence representation by combining continuous wavelet descriptor and Chou's pseudo amino acid composition (PseAAC), and from adopting weighted sparse representation based classifier (WSRC). This method, cross-validated on the PPIs datasets of Saccharomyces cerevisiae, Human and H. pylori, achieves an excellent results with accuracies as high as 92.50%, 95.54% and 84.28% respectively, significantly better than previously proposed methods. Extensive experiments are performed to compare the proposed method with state-of-the-art Support Vector Machine (SVM) classifier. The outstanding results yield by our model that the proposed feature extraction method combing two kinds of descriptors have strong expression ability and are expected to provide comprehensive and effective information for machine learning-based classification models. In addition, the prediction performance in the comparison experiments shows the well cooperation between the combined feature and WSRC. Thus, the proposed method is a very efficient method to predict PPIs and may be a useful supplementary tool for future proteomics studies.

An integrated, structure- and energy-based view of the genetic code.

PubMed

Grosjean, Henri; Westhof, Eric

2016-09-30

The principles of mRNA decoding are conserved among all extant life forms. We present an integrative view of all the interaction networks between mRNA, tRNA and rRNA: the intrinsic stability of codon-anticodon duplex, the conformation of the anticodon hairpin, the presence of modified nucleotides, the occurrence of non-Watson-Crick pairs in the codon-anticodon helix and the interactions with bases of rRNA at the A-site decoding site. We derive a more information-rich, alternative representation of the genetic code, that is circular with an unsymmetrical distribution of codons leading to a clear segregation between GC-rich 4-codon boxes and AU-rich 2:2-codon and 3:1-codon boxes. All tRNA sequence variations can be visualized, within an internal structural and energy framework, for each organism, and each anticodon of the sense codons. The multiplicity and complexity of nucleotide modifications at positions 34 and 37 of the anticodon loop segregate meaningfully, and correlate well with the necessity to stabilize AU-rich codon-anticodon pairs and to avoid miscoding in split codon boxes. The evolution and expansion of the genetic code is viewed as being originally based on GC content with progressive introduction of A/U together with tRNA modifications. The representation we present should help the engineering of the genetic code to include non-natural amino acids. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Responses of primate taste cortex neurons to the astringent tastant tannic acid.

PubMed

Critchley, H D; Rolls, E T

1996-04-01

In order to advance knowledge of the neural control of feeding, we investigated the cortical representation of the taste of tannic acid, which produces the taste of astringency. It is a dietary component of biological importance particularly to arboreal primates. Recordings were made from 74 taste responsive neurons in the orbitofrontal cortex. Single neurons were found that were tuned to respond to 0.001 M tannic acid, and represented a subpopulation of neurons that was distinct from neurons responsive to the tastes of glucose (sweet), NaCl (salty), HCl (sour), quinine (bitter) and monosodium glutamate (umami). In addition, across the population of 74 neurons, tannic acid was as well represented as the tastes of NaCl, HCl quinine or monosodium glutamate. Multidimensional scaling analysis of the neuronal responses to the tastants indicates that tannic acid lies outside the boundaries of the four conventional taste qualities (sweet, sour, bitter and salty). Taken together these data indicate that the astringent taste of tannic acid should be considered as a taste quality, which receives a separate representation from sweet, salt, bitter and sour in the primate cortical taste areas.

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

PubMed Central

Zhang, Long; Jia, Lianyin; Ren, Yazhou

2017-01-01

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study. PMID:29117139

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.

PubMed

Wang, Jun; Zhang, Long; Jia, Lianyin; Ren, Yazhou; Yu, Guoxian

2017-11-08

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae , DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

Acidity field of soils as ion-exchange systems and the diagnostics of genetic soil horizons

NASA Astrophysics Data System (ADS)

Kokotov, Yu. A.; Sukhacheva, E. Yu.; Aparin, B. F.

2014-12-01

For the comprehensive description of the acidity of a two-phase ion-exchange system, we should analyze two curves of the ionite titration by a strong base in water and salt solutions and find the quantitative relationships between the corresponding pH characteristics. An idea of the three-dimensional field of acidity of ion-exchange systems (the phase space of the soil acidity characteristics) and its three two-dimensional projections is suggested. For soils, three interrelated characteristics—the pH values of the salt and water extracts and the degree of base saturation—can serve as spatial coordinates for the acidity field. Representation of factual data in this field makes it possible to compare and analyze the acidity characteristics of different soils and soil horizons and to determine their specific features. Differentiation of the field into separate volumes allows one to present the data in a discrete form. We have studied the distribution patterns of the groups of soil horizons from Leningrad oblast and other regions of northwestern Russia in the acidity field. The studied samples are grouped in different partially overlapping areas of the projections of the acidity field. The results of this grouping attest to the correctness of the modern classification of Russian soils. A notion of the characteristic soil area in the acidity field is suggested; it can be applied to all the soils with a leaching soil water regime.

Analysis of 2H-Evaporator Acid Cleaning Samples

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

Hay, M.; Diprete, D.; Edwards, T.

The 2H-Evaporator acid cleaning solution samples were analyzed by SRNL to determine a composition for the scale present in the evaporator before recent acid cleaning. Composite samples were formed from the solution samples from the two acid cleaning cycles. The solution composition was converted to a weight percent scale solids basis under an assumed chemical composition. The scale composition produced from the acid cleaning solution samples indicates a concentration of 6.85 wt% uranium. An upper bound, onesided 95% confidence interval on the weight percent uranium value may be given as 6.9 wt% + 1.645 × 0.596 wt% = 7.9 wt%.more » The comparison of the composition from the current acid cleaning solutions with the composition of recent scale samples along with the thermodynamic modeling results provides reasonable assurance that the sample results provide a good representation of the overall scale composition in the evaporator prior to acid cleaning. The small amount of scale solids dissolved in the 1.5 M nitric acid during the evaporator cleaning process likely produced only a small amount of precipitation based on modeling results and the visual appearance of the samples.« less

A Thermochemical Kinetic-Based Study of Ignition Delays for 2-Azidoethanamine-Red Fuming Nitric Acid Systems: 2-Azido-N-Methylethanamine (MMAZ) Vs. 2-Azido-N,N-Dimethylethanamine (DMAZ)

DTIC Science & Technology

2014-01-01

ABSTRACT UU 18. NUMBER OF PAGES 68 19a. NAME OF RESPONSIBLE PERSON Chiung-Chu Chen a. REPORT Unclassified b. ABSTRACT Unclassified c ...Abstraction Reactions 33 Appendix C . Geometric Representations, Normal Mode Frequencies, and Moments of Inertia for Molecular Structures Involved in...from MMAZ and DMAZ by NO2 are also shown. ....................13 Figure 6. Potential energy diagram for the C •H2NHCH2CH2N3 + NO2 system: G4-based

Emphasizing Multiple Levels of Representation to Enhance Students' Understandings of the Changes Occurring during Chemical Reactions

ERIC Educational Resources Information Center

Chandrasegaran, A. L.; Treagust, David F.; Mocerino, Mauro

2009-01-01

An alternative program of instruction was implemented with 33 high-achieving Grade 9 students (15-16 years old) in Singapore that overtly focused on the use of macroscopic, submicroscopic, and symbolic representations to describe and explain the changes that occurred during the burning of metals, reactions of dilute acids, ionic precipitations,…

Optimization of a Nucleic Acids united-RESidue 2-Point model (NARES-2P) with a maximum-likelihood approach

NASA Astrophysics Data System (ADS)

He, Yi; Liwo, Adam; Scheraga, Harold A.

2015-12-01

Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.

Using the concept of pseudo amino acid composition to predict resistance gene against Xanthomonas oryzae pv. oryzae in rice: an approach from chaos games representation.

PubMed

Jingbo, Xia; Silan, Zhang; Feng, Shi; Huijuan, Xiong; Xuehai, Hu; Xiaohui, Niu; Zhi, Li

2011-09-07

To evaluate the possibility of an unknown protein to be a resistant gene against Xanthomonas oryzae pv. oryzae, a different mode of pseudo amino acid composition (PseAAC) is proposed to formulate the protein samples by integrating the amino acid composition, as well as the Chaos games representation (CGR) method. Some numerical comparisons of triangle, quadrangle and 12-vertex polygon CGR are carried to evaluate the efficiency of using these fractal figures in classifiers. The numerical results show that among the three polygon methods, triangle method owns a good fractal visualization and performs the best in the classifier construction. By using triangle + 12-vertex polygon CGR as the mathematical feature, the classifier achieves 98.13% in Jackknife test and MCC achieves 0.8462. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mathematical Representation Ability by Using Project Based Learning on the Topic of Statistics

NASA Astrophysics Data System (ADS)

Widakdo, W. A.

2017-09-01

Seeing the importance of the role of mathematics in everyday life, mastery of the subject areas of mathematics is a must. Representation ability is one of the fundamental ability that used in mathematics to make connection between abstract idea with logical thinking to understanding mathematics. Researcher see the lack of mathematical representation and try to find alternative solution to dolve it by using project based learning. This research use literature study from some books and articles in journals to see the importance of mathematical representation abiliy in mathemtics learning and how project based learning able to increase this mathematical representation ability on the topic of Statistics. The indicators for mathematical representation ability in this research classifies namely visual representation (picture, diagram, graph, or table); symbolize representation (mathematical statement. Mathematical notation, numerical/algebra symbol) and verbal representation (written text). This article explain about why project based learning able to influence student’s mathematical representation by using some theories in cognitive psychology, also showing the example of project based learning that able to use in teaching statistics, one of mathematics topic that very useful to analyze data.

Small molecule annotation for the Protein Data Bank

PubMed Central

Sen, Sanchayita; Young, Jasmine; Berrisford, John M.; Chen, Minyu; Conroy, Matthew J.; Dutta, Shuchismita; Di Costanzo, Luigi; Gao, Guanghua; Ghosh, Sutapa; Hudson, Brian P.; Igarashi, Reiko; Kengaku, Yumiko; Liang, Yuhe; Peisach, Ezra; Persikova, Irina; Mukhopadhyay, Abhik; Narayanan, Buvaneswari Coimbatore; Sahni, Gaurav; Sato, Junko; Sekharan, Monica; Shao, Chenghua; Tan, Lihua; Zhuravleva, Marina A.

2014-01-01

The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100 000 structures contain more than 20 000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors. PMID:25425036

Small molecule annotation for the Protein Data Bank.

PubMed

Sen, Sanchayita; Young, Jasmine; Berrisford, John M; Chen, Minyu; Conroy, Matthew J; Dutta, Shuchismita; Di Costanzo, Luigi; Gao, Guanghua; Ghosh, Sutapa; Hudson, Brian P; Igarashi, Reiko; Kengaku, Yumiko; Liang, Yuhe; Peisach, Ezra; Persikova, Irina; Mukhopadhyay, Abhik; Narayanan, Buvaneswari Coimbatore; Sahni, Gaurav; Sato, Junko; Sekharan, Monica; Shao, Chenghua; Tan, Lihua; Zhuravleva, Marina A

2014-01-01

The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100,000 structures contain more than 20,000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors. © The Author(s) 2014. Published by Oxford University Press.

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E.

2014-01-01

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand the structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as means to sample conformational space for a better understanding of the relevance of a given model. From this discussion, the major limitations with modeling, in general, were highlighted. These are the difficult issues in sampling conformational space effectively—the multiple minima or conformational sampling problems—and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These are discussed in detail in this unit. PMID:18428877

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

Phage display peptide libraries: deviations from randomness and correctives

PubMed Central

Ryvkin, Arie; Ashkenazy, Haim; Weiss-Ottolenghi, Yael; Piller, Chen; Pupko, Tal; Gershoni, Jonathan M

2018-01-01

Abstract Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications. PMID:29420788

Optimized scalar promotion with load and splat SIMD instructions

DOEpatents

Eichenberger, Alexander E; Gschwind, Michael K; Gunnels, John A

2013-10-29

Mechanisms for optimizing scalar code executed on a single instruction multiple data (SIMD) engine are provided. Placement of vector operation-splat operations may be determined based on an identification of scalar and SIMD operations in an original code representation. The original code representation may be modified to insert the vector operation-splat operations based on the determined placement of vector operation-splat operations to generate a first modified code representation. Placement of separate splat operations may be determined based on identification of scalar and SIMD operations in the first modified code representation. The first modified code representation may be modified to insert or delete separate splat operations based on the determined placement of the separate splat operations to generate a second modified code representation. SIMD code may be output based on the second modified code representation for execution by the SIMD engine.

Optimized scalar promotion with load and splat SIMD instructions

DOEpatents

Eichenberger, Alexandre E [Chappaqua, NY; Gschwind, Michael K [Chappaqua, NY; Gunnels, John A [Yorktown Heights, NY

2012-08-28

Mechanisms for optimizing scalar code executed on a single instruction multiple data (SIMD) engine are provided. Placement of vector operation-splat operations may be determined based on an identification of scalar and SIMD operations in an original code representation. The original code representation may be modified to insert the vector operation-splat operations based on the determined placement of vector operation-splat operations to generate a first modified code representation. Placement of separate splat operations may be determined based on identification of scalar and SIMD operations in the first modified code representation. The first modified code representation may be modified to insert or delete separate splat operations based on the determined placement of the separate splat operations to generate a second modified code representation. SIMD code may be output based on the second modified code representation for execution by the SIMD engine.

Building Hierarchical Representations for Oracle Character and Sketch Recognition.

PubMed

Jun Guo; Changhu Wang; Roman-Rangel, Edgar; Hongyang Chao; Yong Rui

2016-01-01

In this paper, we study oracle character recognition and general sketch recognition. First, a data set of oracle characters, which are the oldest hieroglyphs in China yet remain a part of modern Chinese characters, is collected for analysis. Second, typical visual representations in shape- and sketch-related works are evaluated. We analyze the problems suffered when addressing these representations and determine several representation design criteria. Based on the analysis, we propose a novel hierarchical representation that combines a Gabor-related low-level representation and a sparse-encoder-related mid-level representation. Extensive experiments show the effectiveness of the proposed representation in both oracle character recognition and general sketch recognition. The proposed representation is also complementary to convolutional neural network (CNN)-based models. We introduce a solution to combine the proposed representation with CNN-based models, and achieve better performances over both approaches. This solution has beaten humans at recognizing general sketches.

Volta-Based Cells Materials Chemical Multiple Representation to Improve Ability of Student Representation

NASA Astrophysics Data System (ADS)

Helsy, I.; Maryamah; Farida, I.; Ramdhani, M. A.

2017-09-01

This study aimed to describe the application of teaching materials, analyze the increase in the ability of students to connect the three levels of representation and student responses after application of multiple representations based teaching materials chemistry. The method used quasi one-group pretest-posttest design to 71 students. The results showed the application of teaching materials carried 88% with very good category. A significant increase ability to connect the three levels of representation of students after the application of multiple representations based teaching materials chemistry with t-value > t-crit (11.402 > 1.991). Recapitulation N-gain pretest and posttest showed relatively similar for all groups is 0.6 criterion being achievement. Students gave a positive response to the application of multiple representations based teaching materials chemistry. Students agree teaching materials used in teaching chemistry (88%), and agrees teaching materials to provide convenience in connecting the three levels of representation (95%).

Flux-Based Finite Volume representations for general thermal problems

NASA Technical Reports Server (NTRS)

Mohan, Ram V.; Tamma, Kumar K.

1993-01-01

Flux-Based Finite Volume (FV) element representations for general thermal problems are given in conjunction with a generalized trapezoidal gamma-T family of algorithms, formulated following the spirit of what we term as the Lax-Wendroff based FV formulations. The new flux-based representations introduced offer an improved physical interpretation of the problem along with computationally convenient and attractive features. The space and time discretization emanate from a conservation form of the governing equation for thermal problems, and in conjunction with the flux-based element representations give rise to a physically improved and locally conservative numerical formulations. The present representations seek to involve improved locally conservative properties, improved physical representations and computational features; these are based on a 2D, bilinear FV element and can be extended for other cases. Time discretization based on a gamma-T family of algorithms in the spirit of a Lax-Wendroff based FV formulations are employed. Numerical examples involving linear/nonlinear steady and transient situations are shown to demonstrate the applicability of the present representations for thermal analysis situations.

Modelling of the acid-base properties of natural and synthetic adsorbent materials used for heavy metal removal from aqueous solutions.

PubMed

Pagnanelli, Francesca; Vegliò, Francesco; Toro, Luigi

2004-02-01

In this paper a comparison about kinetic behaviour, acid-base properties and copper removal capacities was carried out between two different adsorbent materials used for heavy metal removal from aqueous solutions: an aminodiacetic chelating resin as commercial product (Lewatit TP207) and a lyophilised bacterial biomass of Sphaerotilus natans. The acid-base properties of a S. natans cell suspension were well described by simplified mechanistic models without electrostatic corrections considering two kinds of weakly acidic active sites. In particular the introduction of two-peak distribution function for the proton affinity constants allows a better representation of the experimental data reproducing the site heterogeneity. A priori knowledge about resin functional groups (aminodiacetic groups) is the base for preliminary simulations of titration curve assuming a Donnan gel structure for the resin phase considered as a concentrated aqueous solution of aminodiacetic acid (ADA). Departures from experimental and simulated data can be interpreted by considering the heterogeneity of the functional groups and the effect of ionic concentration in the resin phase. Two-site continuous model describes adequately the experimental data. Moreover the values of apparent protonation constants (as adjustable parameters found by non-linear regression) are very near to the apparent constants evaluated by a Donnan model assuming the intrinsic constants in resin phase equal to the equilibrium constants in aqueous solution of ADA and considering the amphoteric nature of active sites for the evaluation of counter-ion concentration in the resin phase. Copper removal outlined the strong affinity of the active groups of the resin for this ion in solution compared to the S. natans biomass according to the complexation constants between aminodiacetic and mono-carboxylic groups and copper ions.

Spatiotemporal dynamics of similarity-based neural representations of facial identity.

PubMed

Vida, Mark D; Nestor, Adrian; Plaut, David C; Behrmann, Marlene

2017-01-10

Humans' remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level "image-based" and higher level "identity-based" model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise.

Designing electronic module based on learning content development system in fostering students’ multi representation skills

NASA Astrophysics Data System (ADS)

Resita, I.; Ertikanto, C.

2018-05-01

This study aims to develop electronic module design based on Learning Content Development System (LCDS) to foster students’ multi representation skills in physics subject material. This study uses research and development method to the product design. This study involves 90 students and 6 physics teachers who were randomly chosen from 3 different Senior High Schools in Lampung Province. The data were collected by using questionnaires and analyzed by using quantitative descriptive method. Based on the data, 95% of the students only use one form of representation in solving physics problems. Representation which is tend to be used by students is symbolic representation. Students are considered to understand the concept of physics if they are able to change from one form to the other forms of representation. Product design of LCDS-based electronic module presents text, image, symbolic, video, and animation representation.

Physiologically based pharmacokinetic modeling of dibromoacetic acid in F344 rats

PubMed Central

Matthews, Jessica L.; Schultz, Irvin R.; Easterling, Michael R.; Melnick, Ronald L.

2010-01-01

A novel physiologically based pharmacokinetic (PBPK) model structure, which includes submodels for the common metabolites (glyoxylate (GXA) and oxalate (OXA)) that may be involved in the toxicity or carcinogenicity of dibromoacetic acid (DBA), has been developed. Particular attention is paid to the representation of hepatic metabolism, which is the primary elimination mechanism. DBA-induced suicide inhibition is modeled by irreversible covalent binding of the intermediate metabolite α-halocarboxymethylglutathione (αH1) to the glutathione-S-transferase zeta (GSTzeta) enzyme. We also present data illustrating the presence of a secondary non-GSTzeta metabolic pathway for DBA, but not dichloroacetic acid (DCA), that produces GXA. The model is calibrated with plasma and urine concentration data from DBA exposures in female F344 rats through intravenous (IV), oral gavage, and drinking water routes. Sensitivity analysis is performed to confirm identifiability of estimated parameters. Finally, model validation is performed with data sets not used during calibration. Given the structural similarity of dihaloacetates (DHAs), we hypothesize that the PBPK model presented here has the capacity to describe the kinetics of any member or mixture of members of this class in any species with the alteration of chemical- and species-specific parameters. PMID:20045428

Physiologically based pharmacokinetic modeling of dibromoacetic acid in F344 rats

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

Matthews, Jessica L., E-mail: Jessica_Matthews@sra.co; Schultz, Irvin R., E-mail: irv.schultz@pnl.go; Easterling, Michael R., E-mail: Michael_Easterling@sra.co

A novel physiologically based pharmacokinetic (PBPK) model structure, which includes submodels for the common metabolites (glyoxylate (GXA) and oxalate (OXA)) that may be involved in the toxicity or carcinogenicity of dibromoacetic acid (DBA), has been developed. Particular attention is paid to the representation of hepatic metabolism, which is the primary elimination mechanism. DBA-induced suicide inhibition is modeled by irreversible covalent binding of the intermediate metabolite alpha-halocarboxymethylglutathione (alphaH1) to the glutathione-S-transferase zeta (GSTzeta) enzyme. We also present data illustrating the presence of a secondary non-GSTzeta metabolic pathway for DBA, but not dichloroacetic acid (DCA), that produces GXA. The model is calibratedmore » with plasma and urine concentration data from DBA exposures in female F344 rats through intravenous (IV), oral gavage, and drinking water routes. Sensitivity analysis is performed to confirm identifiability of estimated parameters. Finally, model validation is performed with data sets not used during calibration. Given the structural similarity of dihaloacetates (DHAs), we hypothesize that the PBPK model presented here has the capacity to describe the kinetics of any member or mixture of members of this class in any species with the alteration of chemical-and species-specific parameters.« less

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

Motor memory is encoded as a gain-field combination of intrinsic and extrinsic action representations.

PubMed

Brayanov, Jordan B; Press, Daniel Z; Smith, Maurice A

2012-10-24

Actions can be planned in either an intrinsic (body-based) reference frame or an extrinsic (world-based) frame, and understanding how the internal representations associated with these frames contribute to the learning of motor actions is a key issue in motor control. We studied the internal representation of this learning in human subjects by analyzing generalization patterns across an array of different movement directions and workspaces after training a visuomotor rotation in a single movement direction in one workspace. This provided a dense sampling of the generalization function across intrinsic and extrinsic reference frames, which allowed us to dissociate intrinsic and extrinsic representations and determine the manner in which they contributed to the motor memory for a trained action. A first experiment showed that the generalization pattern reflected a memory that was intermediate between intrinsic and extrinsic representations. A second experiment showed that this intermediate representation could not arise from separate intrinsic and extrinsic learning. Instead, we find that the representation of learning is based on a gain-field combination of local representations in intrinsic and extrinsic coordinates. This gain-field representation generalizes between actions by effectively computing similarity based on the (Mahalanobis) distance across intrinsic and extrinsic coordinates and is in line with neural recordings showing mixed intrinsic-extrinsic representations in motor and parietal cortices.

CHARMM-GUI PDB manipulator for advanced modeling and simulations of proteins containing nonstandard residues.

PubMed

Jo, Sunhwan; Cheng, Xi; Islam, Shahidul M; Huang, Lei; Rui, Huan; Zhu, Allen; Lee, Hui Sun; Qi, Yifei; Han, Wei; Vanommeslaeghe, Kenno; MacKerell, Alexander D; Roux, Benoît; Im, Wonpil

2014-01-01

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface to prepare molecular simulation systems and input files to facilitate the usage of common and advanced simulation techniques. Since it is originally developed in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to setup a broad range of simulations including free energy calculation and large-scale coarse-grained representation. Here, we describe functionalities that have recently been integrated into CHARMM-GUI PDB Manipulator, such as ligand force field generation, incorporation of methanethiosulfonate spin labels and chemical modifiers, and substitution of amino acids with unnatural amino acids. These new features are expected to be useful in advanced biomolecular modeling and simulation of proteins. © 2014 Elsevier Inc. All rights reserved.

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

PubMed

Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2012-05-10

RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM)-based representation (PSSMSeq) outperform those that use an amino acid identity based representation (IDSeq) or a smoothed PSSM (SmoPSSMSeq); (ii) Structure-based classifiers that use smoothed PSSM representation (SmoPSSMStr) outperform those that use PSSM (PSSMStr) as well as sequence identity based representation (IDStr). PSSMSeq classifiers, when tested on an independent test set of 44 proteins, achieve performance that is comparable to that of three state-of-the-art structure-based predictors (including those that exploit geometric features) in terms of Matthews Correlation Coefficient (MCC), although the structure-based methods achieve substantially higher Specificity (albeit at the expense of Sensitivity) compared to sequence-based methods. We also find that the expected performance of the classifiers on a residue level can be markedly different from that on a protein level. Our experiments show that the classifiers trained on three different non-redundant protein-RNA interface datasets achieve comparable cross-validation performance. However, we find that the results are significantly affected by differences in the distance threshold used to define interface residues. Our results demonstrate that protein-RNA interface residue predictors that use a PSSM-based encoding of sequence windows outperform classifiers that use other encodings of sequence windows. While structure-based methods that exploit geometric features can yield significant increases in the Specificity of protein-RNA interface residue predictions, such increases are offset by decreases in Sensitivity. These results underscore the importance of comparing alternative methods using rigorous statistical procedures, multiple performance measures, and datasets that are constructed based on several alternative definitions of interface residues and redundancy cutoffs as well as including evaluations on independent test sets into the comparisons.

Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

ERIC Educational Resources Information Center

Yung, Hsin I.; Paas, Fred

2015-01-01

Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

Effects and limitations of a nucleobase-driven backmapping procedure for nucleic acids using steered molecular dynamics.

PubMed

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-03-29

Coarse-grained models can be of great help to address the problem of structure prediction in nucleic acids. On one hand they can make the prediction more efficient, while on the other hand they can also help to identify the essential degrees of freedom and interactions for the description of a number of structures. With the aim to provide an all-atom representation in an explicit solvent to the predictions of our SPlit and conQueR (SPQR) coarse-grained model of RNA, we recently introduced a backmapping procedure which enforces the predicted structure into an atomistic one by means of steered molecular dynamics. These simulations minimize the ERMSD, a particular metric which deals exclusively with the relative arrangement of nucleobases, between the atomistic representation and the target structure. In this paper, we explore the effects of this approach on the resulting interaction networks and backbone conformations by applying it on a set of fragments using as a target their native structure. We find that the geometry of the target structures can be reliably recovered, with limitations in the regions with unpaired bases such as bulges. In addition, we observe that the folding pathway can also change depending on the parameters used in the definition of the ERMSD and the use of other metrics such as the RMSD. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-representation based on scientific investigation for enhancing students’ representation skills

NASA Astrophysics Data System (ADS)

Siswanto, J.; Susantini, E.; Jatmiko, B.

2018-03-01

This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.

Space-time modeling using environmental constraints in a mobile robot system

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1990-01-01

Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.

Compositional and phase relations among rare earth element minerals

NASA Technical Reports Server (NTRS)

Burt, D. M.

1989-01-01

A review is presented that mainly treats minerals in which the rare-earth elements are essential constituents, e.g., bastnaesite, monazite, xenotime, aeschynite, allanite. The chemical mechanisms and limits of REE substitution in some rock-forming minerals (zircon, apatite, titanite, garnet) are also derived. Vector representation of complex coupled substitutions in selected REE-bearing minerals is examined and some comments on REE-partitioning between minerals as related to acid-based tendencies and mineral stabilities are presented. As the same or analogous coupled substitutions involving the REE occur in a wide variety of mineral structures, they are discussed together.

Part-based deep representation for product tagging and search

NASA Astrophysics Data System (ADS)

Chen, Keqing

2017-06-01

Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

Effects of Finger Counting on Numerical Development – The Opposing Views of Neurocognition and Mathematics Education

PubMed Central

Moeller, Korbinian; Martignon, Laura; Wessolowski, Silvia; Engel, Joachim; Nuerk, Hans-Christoph

2011-01-01

Children typically learn basic numerical and arithmetic principles using finger-based representations. However, whether or not reliance on finger-based representations is beneficial or detrimental is the subject of an ongoing debate between researchers in neurocognition and mathematics education. From the neurocognitive perspective, finger counting provides multisensory input, which conveys both cardinal and ordinal aspects of numbers. Recent data indicate that children with good finger-based numerical representations show better arithmetic skills and that training finger gnosis, or “finger sense,” enhances mathematical skills. Therefore neurocognitive researchers conclude that elaborate finger-based numerical representations are beneficial for later numerical development. However, research in mathematics education recommends fostering mentally based numerical representations so as to induce children to abandon finger counting. More precisely, mathematics education recommends first using finger counting, then concrete structured representations and, finally, mental representations of numbers to perform numerical operations. Taken together, these results reveal an important debate between neurocognitive and mathematics education research concerning the benefits and detriments of finger-based strategies for numerical development. In the present review, the rationale of both lines of evidence will be discussed. PMID:22144969

Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course.

PubMed

Jaswal, Sheila S; O'Hara, Patricia B; Williamson, Patrick L; Springer, Amy L

2013-01-01

Because understanding the structure of biological macromolecules is critical to understanding their function, students of biochemistry should become familiar not only with viewing, but also with generating and manipulating structural representations. We report a strategy from a one-semester undergraduate biochemistry course to integrate use of structural representation tools into both laboratory and homework activities. First, early in the course we introduce the use of readily available open-source software for visualizing protein structure, coincident with modules on amino acid and peptide bond properties. Second, we use these same software tools in lectures and incorporate images and other structure representations in homework tasks. Third, we require a capstone project in which teams of students examine a protein-nucleic acid complex and then use the software tools to illustrate for their classmates the salient features of the structure, relating how the structure helps explain biological function. To ensure engagement with a range of software and database features, we generated a detailed template file that can be used to explore any structure, and that guides students through specific applications of many of the software tools. In presentations, students demonstrate that they are successfully interpreting structural information, and using representations to illustrate particular points relevant to function. Thus, over the semester students integrate information about structural features of biological macromolecules into the larger discussion of the chemical basis of function. Together these assignments provide an accessible introduction to structural representation tools, allowing students to add these methods to their biochemical toolboxes early in their scientific development. © 2013 by The International Union of Biochemistry and Molecular Biology.

Motor Memory Is Encoded as a Gain-Field Combination of Intrinsic and Extrinsic Action Representations

PubMed Central

Brayanov, Jordan B.; Press, Daniel Z.; Smith, Maurice A.

2013-01-01

Actions can be planned in either an intrinsic (body-based) reference frame or an extrinsic (world-based) frame, and understanding how the internal representations associated with these frames contribute to the learning of motor actions is a key issue in motor control. We studied the internal representation of this learning in human subjects by analyzing generalization patterns across an array of different movement directions and workspaces after training a visuomotor rotation in a single movement direction in one workspace. This provided a dense sampling of the generalization function across intrinsic and extrinsic reference frames, which allowed us to dissociate intrinsic and extrinsic representations and determine the manner in which they contributed to the motor memory for a trained action. A first experiment showed that the generalization pattern reflected a memory that was intermediate between intrinsic and extrinsic representations. A second experiment showed that this intermediate representation could not arise from separate intrinsic and extrinsic learning. Instead, we find that the representation of learning is based on a gain-field combination of local representations in intrinsic and extrinsic coordinates. This gain-field representation generalizes between actions by effectively computing similarity based on the (Mahalanobis) distance across intrinsic and extrinsic coordinates and is in line with neural recordings showing mixed intrinsic-extrinsic representations in motor and parietal cortices. PMID:23100418

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid

PubMed Central

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php PMID:26896846

Elementary School Students' Perceptions of Technology in their Pictorial Representations

ERIC Educational Resources Information Center

Eristi, Suzan Duygu; Kurt, Adile Askim

2011-01-01

The current study aimed to reveal elementary school students' perceptions of technology through their pictorial representations and their written expressions based on their pictorial representations. Content analysis based on the qualitative research method along with art-based inquiry was applied. The "coding system for the concepts revealed…

Inherited Representations are Read in Development

PubMed Central

Shea, Nicholas

2013-01-01

Recent theoretical work has identified a tightly constrained sense in which genes carry representational content. Representational properties of the genome are founded in the transmission of DNA over phylogenetic time and its role in natural selection. However, genetic representation is not just relevant to questions of selection and evolution. This article goes beyond existing treatments and argues for the heterodox view that information generated by a process of selection over phylogenetic time can be read in ontogenetic time, in the course of individual development. Recent results in evolutionary biology, drawn both from modelling work, and from experimental and observational data, support a role for genetic representation in explaining individual ontogeny: both genetic representations and environmental information are read by the mechanisms of development, in an individual, so as to lead to adaptive phenotypes. Furthermore, in some cases there appears to have been selection between individuals that rely to different degrees on the two sources of information. Thus, the theory of representation in inheritance systems like the genome is much more than just a coherent reconstruction of information talk in biology. Genetic representation is a property with considerable explanatory utility. 1 Introduction2 Inherited Representations3 Reading Genetic Representations   3.1 Do genes carry correlational information?4 Selection Between Genetic and Environmental Information   4.1 Modelling  4.2 Empirical applications  4.3 Maternal effects5 Genetic Representation and the Genome   5.1 Information capacity of organisms' genomes  5.2 Many amino acids, few nucleotides  5.3 A function of sex6 Explaining Further Aspects of Development   6.1 Canalization against environmental variation  6.2 An informational function for the nuclear membrane?7 Conclusion PMID:23526835

Students' Representational Fluency at University: A Cross-Sectional Measure of How Multiple Representations Are Used by Physics Students Using the Representational Fluency Survey

ERIC Educational Resources Information Center

Hill, Matthew; Sharma, Manjula Devi

2015-01-01

To succeed within scientific disciplines, using representations, including those based on words, graphs, equations, and diagrams, is important. Research indicates that the use of discipline specific representations (sometimes referred to as expert generated representations), as well as multi-representational use, is critical for problem solving…

Object-based benefits without object-based representations.

PubMed

Fougnie, Daryl; Cormiea, Sarah M; Alvarez, George A

2013-08-01

Influential theories of visual working memory have proposed that the basic units of memory are integrated object representations. Key support for this proposal is provided by the same object benefit: It is easier to remember multiple features of a single object than the same set of features distributed across multiple objects. Here, we replicate the object benefit but demonstrate that features are not stored as single, integrated representations. Specifically, participants could remember 10 features better when arranged in 5 objects compared to 10 objects, yet memory for one object feature was largely independent of memory for the other object feature. These results rule out the possibility that integrated representations drive the object benefit and require a revision of the concept of object-based memory representations. We propose that working memory is object-based in regard to the factors that enhance performance but feature based in regard to the level of representational failure. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Improving the Representational Strategies of Children in a Music-Listening and Playing Task: An Intervention-Based Study

ERIC Educational Resources Information Center

Gil, Vicent; Reybrouck, Mark; Tejada, Jesús; Verschaffel, Lieven

2015-01-01

This intervention-based study focuses on the relation between music and its graphic representation from a meta-representational point of view. It aims to determine whether middle school students show an increase in meta-representational competence (MRC) after an educational intervention. Three classes of 11 to 14-year-old students participated in…

Spatiotemporal dynamics of similarity-based neural representations of facial identity

PubMed Central

Vida, Mark D.; Nestor, Adrian; Plaut, David C.; Behrmann, Marlene

2017-01-01

Humans’ remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level “image-based” and higher level “identity-based” model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise. PMID:28028220

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Toward the establishment of standardized in vitro tests for lipid-based formulations, part 6: effects of varying pancreatin and calcium levels.

PubMed

Sassene, Philip; Kleberg, Karen; Williams, Hywel D; Bakala-N'Goma, Jean-Claude; Carrière, Frédéric; Calderone, Marilyn; Jannin, Vincent; Igonin, Annabel; Partheil, Anette; Marchaud, Delphine; Jule, Eduardo; Vertommen, Jan; Maio, Mario; Blundell, Ross; Benameur, Hassan; Porter, Christopher J H; Pouton, Colin W; Müllertz, Anette

2014-11-01

The impact of pancreatin and calcium addition on a wide array of lipid-based formulations (LBFs) during in vitro lipolysis, with regard to digestion rates and distribution of the model drug danazol, was investigated. Pancreatin primarily affected the extent of digestion, leaving drug distribution somewhat unaffected. Calcium only affected the extent of digestion slightly but had a major influence on drug distribution, with more drug precipitating at higher calcium levels. This is likely to be caused by a combination of removal of lipolysis products from solution by the formation of calcium soaps and calcium precipitating with bile acids, events known to reduce the solubilizing capacity of LBFs dispersed in biorelevant media. Further, during the digestion of hydrophilic LBFs, like IIIA-LC, the un-ionized-ionized ratio of free fatty acids (FFA) remained unchanged at physiological calcium levels. This makes the titration curves at pH 6.5 representable for digestion. However, caution should be taken when interpreting lipolysis curves of lipophilic LBFs, like I-LC, at pH 6.5, at physiological levels of calcium (1.4 mM); un-ionized-ionized ratio of FFA might change during digestion, rendering the lipolysis curve at pH 6.5 non-representable for the total digestion. The ratio of un-ionized-ionized FFAs can be maintained during digestion by applying non-physiological levels of calcium, resulting in a modified drug distribution with increased drug precipitation. However, as the main objective of the in vitro digestion model is to evaluate drug distribution, which is believed to have an impact on bioavailability in vivo, a physiological level (1.4 mM) of calcium is preferred.

Suitability of Commercial Transport Media for Biological Pathogens under Nonideal Conditions

PubMed Central

Hubbard, Kyle; Pellar, Gregory; Emanuel, Peter

2011-01-01

There is extensive data to support the use of commercial transport media as a stabilizer for known clinical samples; however, there is little information to support their use outside of controlled conditions specified by the manufacturer. Furthermore, there is no data to determine the suitability of said media for biological pathogens, specifically those of interest to the US military. This study evaluates commercial off-the-shelf (COTS) transport media based on sample recovery, viability, and quality of nucleic acids and peptides for nonpathogenic strains of Bacillus anthracis, Yersinia pestis, and Venezuelan equine encephalitis virus, in addition to ricin toxin. Samples were stored in COTS, PBST, or no media at various temperatures over an extended test period. The results demonstrate that COTS media, although sufficient for the preservation of nucleic acid and proteinaceous material, are not capable of maintaining an accurate representation of biothreat agents at the time of collection. PMID:22121364

Optimization of digital designs

NASA Technical Reports Server (NTRS)

Miles, Lowell H. (Inventor); Whitaker, Sterling R. (Inventor)

2009-01-01

An application specific integrated circuit is optimized by translating a first representation of its digital design to a second representation. The second representation includes multiple syntactic expressions that admit a representation of a higher-order function of base Boolean values. The syntactic expressions are manipulated to form a third representation of the digital design.

Subject and Citation Indexing. Part I: The Clustering Structure of Composite Representations in the Cystic Fibrosis Document Collection. Part II: The Optimal, Cluster-Based Retrieval Performance of Composite Representations.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1991-01-01

Two articles discuss the clustering of composite representations in the Cystic Fibrosis Document Collection from the National Library of Medicine's MEDLINE file. Clustering is evaluated as a function of the exhaustivity of composite representations based on Medical Subject Headings (MeSH) and citation indexes, and evaluation of retrieval…

A Review on Human Activity Recognition Using Vision-Based Method.

PubMed

Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.

The interplay of representations and patterns of classroom discourse in science teaching sequences

NASA Astrophysics Data System (ADS)

Tang, Kok-Sing

2016-09-01

The purpose of this study is to examines the relationship between the communicative approach of classroom talk and the modes of representations used by science teachers. Based on video data from two physics classrooms in Singapore, a recurring pattern in the relationship was observed as the teaching sequence of a lesson unfolded. It was found that as the mode of representation shifted from enactive (action based) to iconic (image based) to symbolic (language based), there was a concurrent and coordinated shift in the classroom communicative approach from interactive-dialogic to interactive-authoritative to non-interactive-authoritative. Specifically, the shift from enactive to iconic to symbolic representations occurred mainly within the interactive-dialogic approach while the shift towards the interactive-authoritative and non-interactive-authoritative approaches occurred when symbolic modes of representation were used. This concurrent and coordinated shift has implications on how we conceive the use of representations in conjunction with the co-occurring classroom discourse, both theoretically and pedagogically.

A Review on Human Activity Recognition Using Vision-Based Method

PubMed Central

Nie, Jie

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. PMID:29065585

Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space

PubMed Central

2014-01-01

Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993

Analysis of DNA Sequences by An Optical Time-Integrating Correlator: Proof-Of-Concept Experiments.

DTIC Science & Technology

1992-05-01

TABLES xv LIST OF ABBREVIATIONS xvii 1.0 INTRODUCTION 1 2.0 DNA ANALYSIS STRATEGY 4 2.1 Representation of DNA Bases 4 2.2 DNA Analysis Strategy 6 3.0...Zehnder architecture. 3 Figure 3: Short representations of the DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 5... DNA bases where each base is represented by 7-bits long pseudorandom sequences. 4 Table 2: Long representations of the DNA bases with 255-bits maximum

Integrating conventional and inverse representation for face recognition.

PubMed

Xu, Yong; Li, Xuelong; Yang, Jian; Lai, Zhihui; Zhang, David

2014-10-01

Representation-based classification methods are all constructed on the basis of the conventional representation, which first expresses the test sample as a linear combination of the training samples and then exploits the deviation between the test sample and the expression result of every class to perform classification. However, this deviation does not always well reflect the difference between the test sample and each class. With this paper, we propose a novel representation-based classification method for face recognition. This method integrates conventional and the inverse representation-based classification for better recognizing the face. It first produces conventional representation of the test sample, i.e., uses a linear combination of the training samples to represent the test sample. Then it obtains the inverse representation, i.e., provides an approximation representation of each training sample of a subject by exploiting the test sample and training samples of the other subjects. Finally, the proposed method exploits the conventional and inverse representation to generate two kinds of scores of the test sample with respect to each class and combines them to recognize the face. The paper shows the theoretical foundation and rationale of the proposed method. Moreover, this paper for the first time shows that a basic nature of the human face, i.e., the symmetry of the face can be exploited to generate new training and test samples. As these new samples really reflect some possible appearance of the face, the use of them will enable us to obtain higher accuracy. The experiments show that the proposed conventional and inverse representation-based linear regression classification (CIRLRC), an improvement to linear regression classification (LRC), can obtain very high accuracy and greatly outperforms the naive LRC and other state-of-the-art conventional representation based face recognition methods. The accuracy of CIRLRC can be 10% greater than that of LRC.

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes.

PubMed

Chou, Kuo-Chen

2005-01-01

With protein sequences entering into databanks at an explosive pace, the early determination of the family or subfamily class for a newly found enzyme molecule becomes important because this is directly related to the detailed information about which specific target it acts on, as well as to its catalytic process and biological function. Unfortunately, it is both time-consuming and costly to do so by experiments alone. In a previous study, the covariant-discriminant algorithm was introduced to identify the 16 subfamily classes of oxidoreductases. Although the results were quite encouraging, the entire prediction process was based on the amino acid composition alone without including any sequence-order information. Therefore, it is worthy of further investigation. To incorporate the sequence-order effects into the predictor, the 'amphiphilic pseudo amino acid composition' is introduced to represent the statistical sample of a protein. The novel representation contains 20 + 2lambda discrete numbers: the first 20 numbers are the components of the conventional amino acid composition; the next 2lambda numbers are a set of correlation factors that reflect different hydrophobicity and hydrophilicity distribution patterns along a protein chain. Based on such a concept and formulation scheme, a new predictor is developed. It is shown by the self-consistency test, jackknife test and independent dataset tests that the success rates obtained by the new predictor are all significantly higher than those by the previous predictors. The significant enhancement in success rates also implies that the distribution of hydrophobicity and hydrophilicity of the amino acid residues along a protein chain plays a very important role to its structure and function.

Tactile mental body parts representation in obesity.

PubMed

Scarpina, Federica; Castelnuovo, Gianluca; Molinari, Enrico

2014-12-30

Obese people׳s distortions in visually-based mental body-parts representations have been reported in previous studies, but other sensory modalities have largely been neglected. In the present study, we investigated possible differences in tactilely-based body-parts representation between an obese and a healthy-weight group; additionally we explore the possible relationship between the tactile- and the visually-based body representation. Participants were asked to estimate the distance between two tactile stimuli that were simultaneously administered on the arm or on the abdomen, in the absence of visual input. The visually-based body-parts representation was investigated by a visual imagery method in which subjects were instructed to compare the horizontal extension of body part pairs. According to the results, the obese participants overestimated the size of the tactilely-perceived distances more than the healthy-weight group when the arm, and not the abdomen, was stimulated. Moreover, they reported a lower level of accuracy than did the healthy-weight group when estimating horizontal distances relative to their bodies, confirming an inappropriate visually-based mental body representation. Our results imply that body representation disturbance in obese people is not limited to the visual mental domain, but it spreads to the tactilely perceived distances. The inaccuracy was not a generalized tendency but was body-part related. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

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

Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig

2006-10-01

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a modelmore » is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.« less

cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches.

PubMed

Martin-Herranz, Daniel E; Ribeiro, António J M; Krueger, Felix; Thornton, Janet M; Reik, Wolf; Stubbs, Thomas M

2017-11-16

DNA methylation is an important epigenetic modification in many species that is critical for development, and implicated in ageing and many complex diseases, such as cancer. Many cost-effective genome-wide analyses of DNA modifications rely on restriction enzymes capable of digesting genomic DNA at defined sequence motifs. There are hundreds of restriction enzyme families but few are used to date, because no tool is available for the systematic evaluation of restriction enzyme combinations that can enrich for certain sites of interest in a genome. Herein, we present customised Reduced Representation Bisulfite Sequencing (cuRRBS), a novel and easy-to-use computational method that solves this problem. By computing the optimal enzymatic digestions and size selection steps required, cuRRBS generalises the traditional MspI-based Reduced Representation Bisulfite Sequencing (RRBS) protocol to all restriction enzyme combinations. In addition, cuRRBS estimates the fold-reduction in sequencing costs and provides a robustness value for the personalised RRBS protocol, allowing users to tailor the protocol to their experimental needs. Moreover, we show in silico that cuRRBS-defined restriction enzymes consistently out-perform MspI digestion in many biological systems, considering both CpG and CHG contexts. Finally, we have validated the accuracy of cuRRBS predictions for single and double enzyme digestions using two independent experimental datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Geographic Comparison of Women in Academic Obstetrics and Gynecology Department-Based Leadership Roles.

PubMed

Ricciotti, Hope A; Dodge, Laura E; Aluko, Ashley; Hofler, Lisa G; Hacker, Michele R

2017-10-01

To describe and compare geographic representation of women in obstetrics and gynecology department-based leadership roles across American Congress of Obstetricians and Gynecologists (ACOG) districts and U.S. Census Bureau regions while accounting for the proportion of women practicing in each area. We conducted a cross-sectional observational study. To more meaningfully quantify representation of women as leaders in ACOG districts and U.S. Census Bureau regions, we calculated representation ratios-the proportion of department-based leaders who were women divided by the proportion of obstetrician-gynecologists who were women. A ratio of 1.0 indicates proportionate representation and less than 1.0 indicates underrepresentation. We calculated 95% CIs to compare representation of women in leadership roles across geographic areas. The gender of major department-based leaders (chair, vice chair, division director) and educational leaders (fellowship, residency, associate residency, medical student clerkship director) was determined from websites. The proportion of department chairs who were women was highest in the West and lowest in the South Census Bureau regions. Representation ratios for women in major department-based leadership roles demonstrated underrepresentation relative to the practicing base nationally and in all four regions. Although women were underrepresented in major department-based leadership throughout the country, there was significantly higher women's representation in major department-based leadership roles in the West (ratio 0.82, 95% CI 0.68-0.99) compared with the Northeast (ratio 0.50, 95% CI 0.42-0.59) and the South (ratio 0.45, 95% CI 0.36-0.57). Similarly, in the division director role, the West (ratio 0.85, 95% CI 0.68-1.1) had significantly higher representation of women compared with the Northeast (ratio 0.50, 95% CI 0.40-0.62). Nationally, women were underrepresented as fellowship directors, proportionately represented as residency program directors, and overrepresented as medical student clerkship directors. Representation ratios of women in major department-based leadership roles, which account for the proportion of women practicing in each geographic area, suggest that women were more likely to advance to the department-based leadership roles of chair, vice chair, or division director in the western United States.

Translating between Representations in a Social Context: A Study of Undergraduate Science Students' Representational Fluency

ERIC Educational Resources Information Center

Nichols, Kim; Ranasinghe, Muditha; Hanan, Jim

2013-01-01

Interacting with and translating across multiple representations is an essential characteristic of expertise and representational fluency. In this study, we explored the effect of interacting with and translating between representations in a computer simulation or in a paper-based assignment on scientific accuracy of undergraduate science…

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Statistical representation of multiphase flow

NASA Astrophysics Data System (ADS)

Subramaniam

2000-11-01

The relationship between two common statistical representations of multiphase flow, namely, the single--point Eulerian statistical representation of two--phase flow (D. A. Drew, Ann. Rev. Fluid Mech. (15), 1983), and the Lagrangian statistical representation of a spray using the dropet distribution function (F. A. Williams, Phys. Fluids 1 (6), 1958) is established for spherical dispersed--phase elements. This relationship is based on recent work which relates the droplet distribution function to single--droplet pdfs starting from a Liouville description of a spray (Subramaniam, Phys. Fluids 10 (12), 2000). The Eulerian representation, which is based on a random--field model of the flow, is shown to contain different statistical information from the Lagrangian representation, which is based on a point--process model. The two descriptions are shown to be simply related for spherical, monodisperse elements in statistically homogeneous two--phase flow, whereas such a simple relationship is precluded by the inclusion of polydispersity and statistical inhomogeneity. The common origin of these two representations is traced to a more fundamental statistical representation of a multiphase flow, whose concepts derive from a theory for dense sprays recently proposed by Edwards (Atomization and Sprays 10 (3--5), 2000). The issue of what constitutes a minimally complete statistical representation of a multiphase flow is resolved.

The Influence of Recollection and Familiarity in the Formation and Updating of Associative Representations

ERIC Educational Resources Information Center

Ozubko, Jason D.; Moscovitch, Morris; Winocur, Gordon

2017-01-01

Prior representations affect future learning. Little is known, however, about the effects of recollective or familiarity-based representations on such learning. We investigate the ability to reuse or reassociate elements from recollection- and familiarity-based associations to form new associations. Past neuropsychological research suggests that…

iMODS: internal coordinates normal mode analysis server.

PubMed

López-Blanco, José Ramón; Aliaga, José I; Quintana-Ortí, Enrique S; Chacón, Pablo

2014-07-01

Normal mode analysis (NMA) in internal (dihedral) coordinates naturally reproduces the collective functional motions of biological macromolecules. iMODS facilitates the exploration of such modes and generates feasible transition pathways between two homologous structures, even with large macromolecules. The distinctive internal coordinate formulation improves the efficiency of NMA and extends its applicability while implicitly maintaining stereochemistry. Vibrational analysis, motion animations and morphing trajectories can be easily carried out at different resolution scales almost interactively. The server is versatile; non-specialists can rapidly characterize potential conformational changes, whereas advanced users can customize the model resolution with multiple coarse-grained atomic representations and elastic network potentials. iMODS supports advanced visualization capabilities for illustrating collective motions, including an improved affine-model-based arrow representation of domain dynamics. The generated all-heavy-atoms conformations can be used to introduce flexibility for more advanced modeling or sampling strategies. The server is free and open to all users with no login requirement at http://imods.chaconlab.org. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

PaLaCe: A Coarse-Grain Protein Model for Studying Mechanical Properties.

PubMed

Pasi, Marco; Lavery, Richard; Ceres, Nicoletta

2013-01-08

We present a coarse-grain protein model PaLaCe (Pasi-Lavery-Ceres) that has been developed principally to allow fast computational studies of protein mechanics and to clarify the links between mechanics and function. PaLaCe uses a two-tier protein representation with one to three pseudoatoms representing each amino acid for the main nonbonded interactions, combined with atomic-scale peptide groups and some side chain atoms to allow the explicit representation of backbone hydrogen bonds and to simplify the treatment of bonded interactions. The PaLaCe force field is composed of physics-based terms, parametrized using Boltzmann inversion of conformational probability distributions derived from a protein structure data set, and iteratively refined to reproduce the experimental distributions. PaLaCe has been implemented in the MMTK simulation package and can be used for energy minimization, normal mode calculations, and molecular or stochastic dynamics. We present simulations with PaLaCe that test its ability to maintain stable structures for folded proteins, reproduce their dynamic fluctuations, and correctly model large-scale, force-induced conformational changes.

Phenylalanine ab initio models for the simulation of skin natural moisturizing factor

NASA Astrophysics Data System (ADS)

Carvalho, B. G.; Raniero, L. J.; Martin, A. A.; Favero, P. P.

2013-04-01

In this study, we evaluated models that can be used to simulate amino acids in biological environments via density functional theory (DFT). The goal was to obtain realistic representations that combine computational economy and result quality when compared to experimental data. We increased the complexity of the models by using a model of an amino acid in a vacuum, followed by a water-solvated amino acid model. To consider pH variation, we simulated zwitterionic and nonionic amino acid configurations. The amino acid chosen for testing was phenylalanine, an aromatic amino acid present in high concentrations in the natural moisturizing factor of skin that plays a fundamental role in ultraviolet protection and vitiligo disease. To validate the models, vibrational modes and electronic properties were calculated and compared to experimental results.

Origins of Secure Base Script Knowledge and the Developmental Construction of Attachment Representations

PubMed Central

Waters, Theodore E. A.; Ruiz, Sarah K.; Roisman, Glenn I.

2016-01-01

Increasing evidence suggests that attachment representations take at least two forms—a secure base script and an autobiographical narrative of childhood caregiving experiences. This study presents data from the first 26 years of the Minnesota Longitudinal Study of Risk and Adaptation (N = 169), examining the developmental origins of secure base script knowledge in a high-risk sample, and testing alternative models of the developmental sequencing of the construction of attachment representations. Results demonstrated that secure base script knowledge was predicted by observations of maternal sensitivity across childhood and adolescence. Further, findings suggest that the construction of a secure base script supports the development of a coherent autobiographical representation of childhood attachment experiences with primary caregivers by early adulthood. PMID:27302650

Correlational Neural Networks.

PubMed

Chandar, Sarath; Khapra, Mitesh M; Larochelle, Hugo; Ravindran, Balaraman

2016-02-01

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

PubMed

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-02-28

We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

The DTW-based representation space for seismic pattern classification

NASA Astrophysics Data System (ADS)

Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario

2015-12-01

Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Representations of the language recognition problem for a theorem prover

NASA Technical Reports Server (NTRS)

Minker, J.; Vanderbrug, G. J.

1972-01-01

Two representations of the language recognition problem for a theorem prover in first order logic are presented and contrasted. One of the representations is based on the familiar method of generating sentential forms of the language, and the other is based on the Cocke parsing algorithm. An augmented theorem prover is described which permits recognition of recursive languages. The state-transformation method developed by Cordell Green to construct problem solutions in resolution-based systems can be used to obtain the parse tree. In particular, the end-order traversal of the parse tree is derived in one of the representations. An inference system, termed the cycle inference system, is defined which makes it possible for the theorem prover to model the method on which the representation is based. The general applicability of the cycle inference system to state space problems is discussed. Given an unsatisfiable set S, where each clause has at most one positive literal, it is shown that there exists an input proof. The clauses for the two representations satisfy these conditions, as do many state space problems.

Multi-layer sparse representation for weighted LBP-patches based facial expression recognition.

PubMed

Jia, Qi; Gao, Xinkai; Guo, He; Luo, Zhongxuan; Wang, Yi

2015-03-19

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.

Knowledge-based vision and simple visual machines.

PubMed Central

Cliff, D; Noble, J

1997-01-01

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong. PMID:9304684

Towards improving phenotype representation in OWL

PubMed Central

2012-01-01

Background Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected entities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies. Methods We analyze formalizations of complex phenotype descriptions in the Web Ontology Language (OWL) that are based on the EQ model, identify several representational challenges and analyze potential solutions to address these challenges. Results In particular, we suggest a novel, role-based approach to represent relational qualities such as concentration of iron in spleen, discuss its ontological foundation in the General Formal Ontology (GFO) and evaluate its representation in OWL and the benefits it can bring to the representation of phenotype annotations. Conclusion Our analysis of OWL-based representations of phenotypes can contribute to improving consistency and expressiveness of formal phenotype descriptions. PMID:23046625

Analysis of DNA Sequences by an Optical ime-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0 STRATEGY FOR COARSE...1)-correlation peak formed by the AxB term and (2)-pedestal formed by the A + B terms. 7 Figure 4: Short representations of the DNA bases where each...linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits long pseudorandom

Squeezing, Striking, and Vocalizing: Is Number Representation Fundamentally Spatial?

ERIC Educational Resources Information Center

Nunez, Rafael; Doan, D.; Nikoulina, Anastasia

2011-01-01

Numbers are fundamental entities in mathematics, but their cognitive bases are unclear. Abundant research points to linear space as a natural grounding for number representation. But, is number representation fundamentally spatial? We disentangle number representation from standard number-to-line reporting methods, and compare numerical…

Venturing into Unknown Territory: Using Aesthetic Representations to Understand Reading Comprehension

ERIC Educational Resources Information Center

Cuero, Kimberley K.; Bonner, Jennifer; Smith, Brittaney; Schwartz, Michelle; Touchstone, Rose; Vela, Yvonne

2008-01-01

Based on Elliot Eisner's notions of multiple forms of representation and Rosenblatt's aesthetic/efferent responses to reading, a teacher educator/researcher had her undergraduate students explore their connections, using aesthetic representations, to a course entitled "Reading Comprehension". Each aesthetic representation revealed the complexities…

QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

PubMed

Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

Shared Representations in Language Processing and Verbal Short-Term Memory: The Case of Grammatical Gender

ERIC Educational Resources Information Center

Schweppe, Judith; Rummer, Ralf

2007-01-01

The general idea of language-based accounts of short-term memory is that retention of linguistic materials is based on representations within the language processing system. In the present sentence recall study, we address the question whether the assumption of shared representations holds for morphosyntactic information (here: grammatical gender…

Students and Teacher Academic Evaluation Perceptions: Methodology to Construct a Representation Based on Actionable Knowledge Discovery Framework

ERIC Educational Resources Information Center

Molina, Otilia Alejandro; Ratté, Sylvie

2017-01-01

This research introduces a method to construct a unified representation of teachers and students perspectives based on the actionable knowledge discovery (AKD) and delivery framework. The representation is constructed using two models: one obtained from student evaluations and the other obtained from teachers' reflections about their teaching…

Representational Tools in Computer-Supported Collaborative Argumentation-Based Learning: How Dyads Work with Constructed and Inspected Argumentative Diagrams

ERIC Educational Resources Information Center

van Amelsvoort, Marije; Andriessen, Jerry; Kanselaar, Gellof

2007-01-01

This article investigates the conditions under which diagrammatic representations support collaborative argumentation-based learning in a computer environment. Thirty dyads of 15- to 18-year-old students participated in a writing task consisting of 3 phases. Students prepared by constructing a representation (text or diagram) individually. Then…

Preexisting semantic representation improves working memory performance in the visuospatial domain.

PubMed

Rudner, Mary; Orfanidou, Eleni; Cardin, Velia; Capek, Cheryl M; Woll, Bencie; Rönnberg, Jerker

2016-05-01

Working memory (WM) for spoken language improves when the to-be-remembered items correspond to preexisting representations in long-term memory. We investigated whether this effect generalizes to the visuospatial domain by administering a visual n-back WM task to deaf signers and hearing signers, as well as to hearing nonsigners. Four different kinds of stimuli were presented: British Sign Language (BSL; familiar to the signers), Swedish Sign Language (SSL; unfamiliar), nonsigns, and nonlinguistic manual actions. The hearing signers performed better with BSL than with SSL, demonstrating a facilitatory effect of preexisting semantic representation. The deaf signers also performed better with BSL than with SSL, but only when WM load was high. No effect of preexisting phonological representation was detected. The deaf signers performed better than the hearing nonsigners with all sign-based materials, but this effect did not generalize to nonlinguistic manual actions. We argue that deaf signers, who are highly reliant on visual information for communication, develop expertise in processing sign-based items, even when those items do not have preexisting semantic or phonological representations. Preexisting semantic representation, however, enhances the quality of the gesture-based representations temporarily maintained in WM by this group, thereby releasing WM resources to deal with increased load. Hearing signers, on the other hand, may make strategic use of their speech-based representations for mnemonic purposes. The overall pattern of results is in line with flexible-resource models of WM.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid.

PubMed

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php. © The Author(s) 2016. Published by Oxford University Press.

Fast and accurate grid representations for atom-based docking with partner flexibility.

PubMed

de Vries, Sjoerd J; Zacharias, Martin

2017-06-30

Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Intersection of argumentation and the use of multiple representations in the context of socioscientific issues

NASA Astrophysics Data System (ADS)

Namdar, Bahadir; Shen, Ji

2016-05-01

Using multiple representations and argumentation are two fundamental processes in science. With the advancements of information communication technologies, these two processes are blended more so than ever before. However, little is known about how these two processes interact with each other in student learning. Hence, we conducted a design-based study in order to distill the relationship between these two processes. Specifically, we designed a learning unit on nuclear energy and implemented it with a group of preservice middle school teachers. The participants used a web-based knowledge organization platform that incorporated three representational modes: textual, concept map, and pictorial. The participants organized their knowledge on nuclear energy by searching, sorting, clustering information through the use of these representational modes and argued about the nuclear energy issue. We found that the use of multiple representations and argumentation interacted with each other in a complex way. Based on our findings, we argue that the complexity can be unfolded in two aspects: (a) the use of multiple representations mediates argumentation in different forms and for different purposes; (b) the type of argumentation that leads to refinement of the use of multiple representations is often non-mediated and drawn from personal experience.

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

PubMed Central

Mack, Michael L.; Love, Bradley C.; Preston, Alison R.

2016-01-01

Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal. PMID:27803320

An analysis of science content and representations in introductory college physics textbooks and multimodal learning resources

NASA Astrophysics Data System (ADS)

Donnelly, Suzanne M.

This study features a comparative descriptive analysis of the physics content and representations surrounding the first law of thermodynamics as presented in four widely used introductory college physics textbooks representing each of four physics textbook categories (calculus-based, algebra/trigonometry-based, conceptual, and technical/applied). Introducing and employing a newly developed theoretical framework, multimodal generative learning theory (MGLT), an analysis of the multimodal characteristics of textbook and multimedia representations of physics principles was conducted. The modal affordances of textbook representations were identified, characterized, and compared across the four physics textbook categories in the context of their support of problem-solving. Keywords: college science, science textbooks, multimodal learning theory, thermodynamics, representations

A novel knowledge-based system for interpreting complex engineering drawings: theory, representation, and implementation.

PubMed

Lu, Tong; Tai, Chiew-Lan; Yang, Huafei; Cai, Shijie

2009-08-01

We present a novel knowledge-based system to automatically convert real-life engineering drawings to content-oriented high-level descriptions. The proposed method essentially turns the complex interpretation process into two parts: knowledge representation and knowledge-based interpretation. We propose a new hierarchical descriptor-based knowledge representation method to organize the various types of engineering objects and their complex high-level relations. The descriptors are defined using an Extended Backus Naur Form (EBNF), facilitating modification and maintenance. When interpreting a set of related engineering drawings, the knowledge-based interpretation system first constructs an EBNF-tree from the knowledge representation file, then searches for potential engineering objects guided by a depth-first order of the nodes in the EBNF-tree. Experimental results and comparisons with other interpretation systems demonstrate that our knowledge-based system is accurate and robust for high-level interpretation of complex real-life engineering projects.

Secure Base Narrative Representations and Intimate Partner Violence: A Dyadic Perspective

PubMed Central

Karakurt, Gunnur; Silver, Kristin E.; Keiley, Margaret K.

2015-01-01

This study aimed to understand the relationship between secure base phenomena and dating violence among couples. Within a relationship, a secure base can be defined as a balancing act of proximity-seeking and exploration at various times and contexts with the assurance of a caregiver’s availability and responsiveness in emotionally distressing situations. Participants were 87 heterosexual couples. The Actor-Partner Interdependence Model was used to examine the relationship between each partner’s scores on secure base representational knowledge and intimate partner violence. Findings demonstrated that women’s secure base representational knowledge had a significant direct negative effect on the victimization of both men and women, while men’s secure base representational knowledge did not have any significant partner or actor effects. Therefore, findings suggest that women with insecure attachments may be more vulnerable to being both the victims and the perpetrators of PMID:27445432

Origins of Secure Base Script Knowledge and the Developmental Construction of Attachment Representations.

PubMed

Waters, Theodore E A; Ruiz, Sarah K; Roisman, Glenn I

2017-01-01

Increasing evidence suggests that attachment representations take at least two forms: a secure base script and an autobiographical narrative of childhood caregiving experiences. This study presents data from the first 26 years of the Minnesota Longitudinal Study of Risk and Adaptation (N = 169), examining the developmental origins of secure base script knowledge in a high-risk sample and testing alternative models of the developmental sequencing of the construction of attachment representations. Results demonstrated that secure base script knowledge was predicted by observations of maternal sensitivity across childhood and adolescence. Furthermore, findings suggest that the construction of a secure base script supports the development of a coherent autobiographical representation of childhood attachment experiences with primary caregivers by early adulthood. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Texture-Based Correspondence Display

NASA Technical Reports Server (NTRS)

Gerald-Yamasaki, Michael

2004-01-01

Texture-based correspondence display is a methodology to display corresponding data elements in visual representations of complex multidimensional, multivariate data. Texture is utilized as a persistent medium to contain a visual representation model and as a means to create multiple renditions of data where color is used to identify correspondence. Corresponding data elements are displayed over a variety of visual metaphors in a normal rendering process without adding extraneous linking metadata creation and maintenance. The effectiveness of visual representation for understanding data is extended to the expression of the visual representation model in texture.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Medical Image Fusion Based on Feature Extraction and Sparse Representation

PubMed Central

Wei, Gao; Zongxi, Song

2017-01-01

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

Neural Representation. A Survey-Based Analysis of the Notion

PubMed Central

Vilarroya, Oscar

2017-01-01

The word representation (as in “neural representation”), and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA) research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature. PMID:28900406

Argumentation-Based Collaborative Inquiry in Science through Representational Work: Impact on Primary Students' Representational Fluency

ERIC Educational Resources Information Center

Nichols, Kim; Gillies, Robyn; Hedberg, John

2016-01-01

This study explored the impact of argumentation-promoting collaborative inquiry and representational work in science on primary students' representational fluency. Two hundred sixty-six year 6 students received instruction on natural disasters with a focus on collaborative inquiry. Students in the Comparison condition received only this…

Student Thinking Processes While Constructing Graphic Representations of Textbook Content: What Insights Do Think-Alouds Provide?

ERIC Educational Resources Information Center

Scott, D. Beth; Dreher, Mariam Jean

2016-01-01

This study examined the thinking processes students engage in while constructing graphic representations of textbook content. Twenty-eight students who either used graphic representations in a routine manner during social studies instruction or learned to construct graphic representations based on the rhetorical patterns used to organize textbook…

Force Concept Inventory-Based Multiple-Choice Test for Investigating Students' Representational Consistency

ERIC Educational Resources Information Center

Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

2010-01-01

This study investigates students' ability to interpret multiple representations consistently (i.e., representational consistency) in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI), which makes use of nine items from the 1995 version of the Force Concept Inventory…

The Proteus Effect: The Effect of Transformed Self-Representation on Behavior

ERIC Educational Resources Information Center

Yee, Nick; Bailenson, Jeremy

2007-01-01

Virtual environments, such as online games and web-based chat rooms, increasingly allow us to alter our digital self-representations dramatically and easily. But as we change our self-representations, do our self-representations change our behavior in turn? In 2 experimental studies, we explore the hypothesis that an individual's behavior conforms…

Computational modelling of genome-scale metabolic networks and its application to CHO cell cultures.

PubMed

Rejc, Živa; Magdevska, Lidija; Tršelič, Tilen; Osolin, Timotej; Vodopivec, Rok; Mraz, Jakob; Pavliha, Eva; Zimic, Nikolaj; Cvitanović, Tanja; Rozman, Damjana; Moškon, Miha; Mraz, Miha

2017-09-01

Genome-scale metabolic models (GEMs) have become increasingly important in recent years. Currently, GEMs are the most accurate in silico representation of the genotype-phenotype link. They allow us to study complex networks from the systems perspective. Their application may drastically reduce the amount of experimental and clinical work, improve diagnostic tools and increase our understanding of complex biological phenomena. GEMs have also demonstrated high potential for the optimisation of bio-based production of recombinant proteins. Herein, we review the basic concepts, methods, resources and software tools used for the reconstruction and application of GEMs. We overview the evolution of the modelling efforts devoted to the metabolism of Chinese Hamster Ovary (CHO) cells. We present a case study on CHO cell metabolism under different amino acid depletions. This leads us to the identification of the most influential as well as essential amino acids in selected CHO cell lines. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using distances between Top-n-gram and residue pairs for protein remote homology detection.

PubMed

Liu, Bin; Xu, Jinghao; Zou, Quan; Xu, Ruifeng; Wang, Xiaolong; Chen, Qingcai

2014-01-01

Protein remote homology detection is one of the central problems in bioinformatics, which is important for both basic research and practical application. Currently, discriminative methods based on Support Vector Machines (SVMs) achieve the state-of-the-art performance. Exploring feature vectors incorporating the position information of amino acids or other protein building blocks is a key step to improve the performance of the SVM-based methods. Two new methods for protein remote homology detection were proposed, called SVM-DR and SVM-DT. SVM-DR is a sequence-based method, in which the feature vector representation for protein is based on the distances between residue pairs. SVM-DT is a profile-based method, which considers the distances between Top-n-gram pairs. Top-n-gram can be viewed as a profile-based building block of proteins, which is calculated from the frequency profiles. These two methods are position dependent approaches incorporating the sequence-order information of protein sequences. Various experiments were conducted on a benchmark dataset containing 54 families and 23 superfamilies. Experimental results showed that these two new methods are very promising. Compared with the position independent methods, the performance improvement is obvious. Furthermore, the proposed methods can also provide useful insights for studying the features of protein families. The better performance of the proposed methods demonstrates that the position dependant approaches are efficient for protein remote homology detection. Another advantage of our methods arises from the explicit feature space representation, which can be used to analyze the characteristic features of protein families. The source code of SVM-DT and SVM-DR is available at http://bioinformatics.hitsz.edu.cn/DistanceSVM/index.jsp.

Mental representation and motor imagery training

PubMed Central

Schack, Thomas; Essig, Kai; Frank, Cornelia; Koester, Dirk

2014-01-01

Research in sports, dance and rehabilitation has shown that basic action concepts (BACs) are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, the structural dimensional analysis of mental representation (SDA-M), to assess action-relevant representational structures that reflect the organization of BACs. The SDA-M reveals a strong relationship between cognitive representation and performance if complex actions are performed. We show how the SDA-M can improve motor imagery training and how it contributes to our understanding of coaching processes. The SDA-M capitalizes on the objective measurement of individual mental movement representations before training and the integration of these results into the motor imagery training. Such motor imagery training based on mental representations (MTMR) has been applied successfully in professional sports such as golf, volleyball, gymnastics, windsurfing, and recently in the rehabilitation of patients who have suffered a stroke. PMID:24904368

A Comparison of Reasoning Processes in a Collaborative Modelling Environment: Learning about genetics problems using virtual chat

NASA Astrophysics Data System (ADS)

Pata, Kai; Sarapuu, Tago

2006-09-01

This study investigated the possible activation of different types of model-based reasoning processes in two learning settings, and the influence of various terms of reasoning on the learners’ problem representation development. Changes in 53 students’ problem representations about genetic issue were analysed while they worked with different modelling tools in a synchronous network-based environment. The discussion log-files were used for the “microgenetic” analysis of reasoning types. For studying the stages of students’ problem representation development, individual pre-essays and post-essays and their utterances during two reasoning phases were used. An approach for mapping problem representations was developed. Characterizing the elements of mental models and their reasoning level enabled the description of five hierarchical categories of problem representations. Learning in exploratory and experimental settings was registered as the shift towards more complex stages of problem representations in genetics. The effect of different types of reasoning could be observed as the divergent development of problem representations within hierarchical categories.

Understanding Deep Representations Learned in Modeling Users Likes.

PubMed

Guntuku, Sharath Chandra; Zhou, Joey Tianyi; Roy, Sujoy; Lin, Weisi; Tsang, Ivor W

2016-08-01

Automatically understanding and discriminating different users' liking for an image is a challenging problem. This is because the relationship between image features (even semantic ones extracted by existing tools, viz., faces, objects, and so on) and users' likes is non-linear, influenced by several subtle factors. This paper presents a deep bi-modal knowledge representation of images based on their visual content and associated tags (text). A mapping step between the different levels of visual and textual representations allows for the transfer of semantic knowledge between the two modalities. Feature selection is applied before learning deep representation to identify the important features for a user to like an image. The proposed representation is shown to be effective in discriminating users based on images they like and also in recommending images that a given user likes, outperforming the state-of-the-art feature representations by  ∼ 15 %-20%. Beyond this test-set performance, an attempt is made to qualitatively understand the representations learned by the deep architecture used to model user likes.

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs

PubMed Central

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-01-01

Abstract We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\mathcal {E}$\\end{document}SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base–phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation. PMID:29272539

Multiple Domains of Parental Secure Base Support During Childhood and Adolescence Contribute to Adolescents’ Representations of Attachment as a Secure Base Script

PubMed Central

Vaughn, Brian E.; Waters, Theodore E. A.; Steele, Ryan D.; Roisman, Glenn I.; Bost, Kelly K.; Truitt, Warren; Waters, Harriet S.; Booth-LaForce, Cathryn

2016-01-01

Although attachment theory claims that early attachment representations reflecting the quality of the child’s “lived experiences” are maintained across developmental transitions, evidence that has emerged over the last decade suggests that the association between early relationship quality and adolescents’ attachment representations is fairly modest in magnitude. We used aspects of parenting beyond sensitivity over childhood and adolescence and early security to predict adolescents’ scripted attachment representations. At age 18 years, 673 participants from the NICHD Study of Early Child Care and Youth Development (SECCYD) completed the Attachment Script Assessment (ASA) from which we derived an assessment of secure base script knowledge. Measures of secure base support from childhood through age 15 years (e.g., parental monitoring of child activity, father presence in the home) were selected as predictors and accounted for an additional 8% of the variance in secure base script knowledge scores above and beyond direct observations of sensitivity and early attachment status alone, suggesting that adolescents’ scripted attachment representations reflect multiple domains of parenting. Cognitive and demographic variables also significantly increased predicted variance in secure base script knowledge by 2% each. PMID:27032953

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning

PubMed Central

Dann, Benjamin

2016-01-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity. PMID:27814352

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.

PubMed

Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

2016-11-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.

Learning-Dependent Plasticity of the Barrel Cortex Is Impaired by Restricting GABA-Ergic Transmission.

PubMed

Posluszny, Anna; Liguz-Lecznar, Monika; Turzynska, Danuta; Zakrzewska, Renata; Bielecki, Maksymilian; Kossut, Malgorzata

2015-01-01

Experience-induced plastic changes in the cerebral cortex are accompanied by alterations in excitatory and inhibitory transmission. Increased excitatory drive, necessary for plasticity, precedes the occurrence of plastic change, while decreased inhibitory signaling often facilitates plasticity. However, an increase of inhibitory interactions was noted in some instances of experience-dependent changes. We previously reported an increase in the number of inhibitory markers in the barrel cortex of mice after fear conditioning engaging vibrissae, observed concurrently with enlargement of the cortical representational area of the row of vibrissae receiving conditioned stimulus (CS). We also observed that an increase of GABA level accompanied the conditioning. Here, to find whether unaltered GABAergic signaling is necessary for learning-dependent rewiring in the murine barrel cortex, we locally decreased GABA production in the barrel cortex or reduced transmission through GABAA receptors (GABAARs) at the time of the conditioning. Injections of 3-mercaptopropionic acid (3-MPA), an inhibitor of glutamic acid decarboxylase (GAD), into the barrel cortex prevented learning-induced enlargement of the conditioned vibrissae representation. A similar effect was observed after injection of gabazine, an antagonist of GABAARs. At the behavioral level, consistent conditioned response (cessation of head movements in response to CS) was impaired. These results show that appropriate functioning of the GABAergic system is required for both manifestation of functional cortical representation plasticity and for the development of a conditioned response.

Comparison of the SAWNUC model with CLOUD measurements of sulphuric acid-water nucleation.

PubMed

Ehrhart, Sebastian; Ickes, Luisa; Almeida, Joao; Amorim, Antonio; Barmet, Peter; Bianchi, Federico; Dommen, Josef; Dunne, Eimear M; Duplissy, Jonathan; Franchin, Alessandro; Kangasluoma, Juha; Kirkby, Jasper; Kürten, Andreas; Kupc, Agnieszka; Lehtipalo, Katrianne; Nieminen, Tuomo; Riccobono, Francesco; Rondo, Linda; Schobesberger, Siegfried; Steiner, Gerhard; Tomé, António; Wimmer, Daniela; Baltensperger, Urs; Wagner, Paul E; Curtius, Joachim

2016-10-27

Binary nucleation of sulphuric acid-water particles is expected to be an important process in the free troposphere at low temperatures. SAWNUC (Sulphuric Acid Water Nucleation) is a model of binary nucleation that is based on laboratory measurements of the binding energies of sulphuric acid and water in charged and neutral clusters. Predictions of SAWNUC are compared for the first time comprehensively with experimental binary nucleation data from the CLOUD chamber at European Organization for Nuclear Research. The experimental measurements span a temperature range of 208-292 K, sulphuric acid concentrations from 1·10 6 to 1·10 9  cm -3 , and distinguish between ion-induced and neutral nucleation. Good agreement, within a factor of 5, is found between the experimental and modeled formation rates for ion-induced nucleation at 278 K and below and for neutral nucleation at 208 and 223 K. Differences at warm temperatures are attributed to ammonia contamination which was indicated by the presence of ammonia-sulphuric acid clusters, detected by an Atmospheric Pressure Interface Time of Flight (APi-TOF) mass spectrometer. APi-TOF measurements of the sulphuric acid ion cluster distributions ( (H2SO4)i·HSO4- with i = 0, 1, ..., 10) show qualitative agreement with the SAWNUC ion cluster distributions. Remaining differences between the measured and modeled distributions are most likely due to fragmentation in the APi-TOF. The CLOUD results are in good agreement with previously measured cluster binding energies and show the SAWNUC model to be a good representation of ion-induced and neutral binary nucleation of sulphuric acid-water clusters in the middle and upper troposphere.

Identities of almost Stable Group Representations

NASA Astrophysics Data System (ADS)

Vovsi, S. M.; Khung Shon, Nguen

1988-02-01

It is proved that almost stable group representations over a field have a finite basis of identities. Moreover, a variety generated by an arbitrary almost stable representation is Specht and all of its subvarieties have a finite uniformly bounded basis rank. In particular, the identities of an arbitrary representation of a finite group are finitely based.Bibliography: 17 titles.

Perceptual and Symbolic Representations as a Starting Point of the Acquisition of the Derivative

ERIC Educational Resources Information Center

Hahkioniemi, Markus

2004-01-01

In this paper we study how a student begins to acquire the concept of the derivative, what kind of representations he acquires and how he connects these representations. A teaching period, in which different perceptual and symbolic representation were emphasized, was carried out and task based interviews conducted to five students. The students…

The Binary Representation of Rational Numbers.

ERIC Educational Resources Information Center

Schmalz, Rosemary

1987-01-01

Presented are the mathematical explanation of the algorithm for representing rational numbers in base two, paper-and-pencil methods for producing the representation, some patterns in these representations, and pseudocode for computer programs to explore these patterns. (MNS)

GraDit: graph-based data repair algorithm for multiple data edits rule violations

NASA Astrophysics Data System (ADS)

Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

2018-03-01

Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

Formal Representations of Eligibility Criteria: A Literature Review

PubMed Central

Weng, Chunhua; Tu, Samson W.; Sim, Ida; Richesson, Rachel

2010-01-01

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria. PMID:20034594

Statistically optimal perception and learning: from behavior to neural representations

PubMed Central

Fiser, József; Berkes, Pietro; Orbán, Gergő; Lengyel, Máté

2010-01-01

Human perception has recently been characterized as statistical inference based on noisy and ambiguous sensory inputs. Moreover, suitable neural representations of uncertainty have been identified that could underlie such probabilistic computations. In this review, we argue that learning an internal model of the sensory environment is another key aspect of the same statistical inference procedure and thus perception and learning need to be treated jointly. We review evidence for statistically optimal learning in humans and animals, and reevaluate possible neural representations of uncertainty based on their potential to support statistically optimal learning. We propose that spontaneous activity can have a functional role in such representations leading to a new, sampling-based, framework of how the cortex represents information and uncertainty. PMID:20153683

Representing sentence information

NASA Astrophysics Data System (ADS)

Perkins, Walton A., III

1991-03-01

This paper describes a computer-oriented representation for sentence information. Whereas many Artificial Intelligence (AI) natural language systems start with a syntactic parse of a sentence into the linguist's components: noun, verb, adjective, preposition, etc., we argue that it is better to parse the input sentence into 'meaning' components: attribute, attribute value, object class, object instance, and relation. AI systems need a representation that will allow rapid storage and retrieval of information and convenient reasoning with that information. The attribute-of-object representation has proven useful for handling information in relational databases (which are well known for their efficiency in storage and retrieval) and for reasoning in knowledge- based systems. On the other hand, the linguist's syntactic representation of the works in sentences has not been shown to be useful for information handling and reasoning. We think it is an unnecessary and misleading intermediate form. Our sentence representation is semantic based in terms of attribute, attribute value, object class, object instance, and relation. Every sentence is segmented into one or more components with the form: 'attribute' of 'object' 'relation' 'attribute value'. Using only one format for all information gives the system simplicity and good performance as a RISC architecture does for hardware. The attribute-of-object representation is not new; it is used extensively in relational databases and knowledge-based systems. However, we will show that it can be used as a meaning representation for natural language sentences with minor extensions. In this paper we describe how a computer system can parse English sentences into this representation and generate English sentences from this representation. Much of this has been tested with computer implementation.

A knowledge base of the chemical compounds of intermediary metabolism.

PubMed

Karp, P D

1992-08-01

This paper describes a publicly available knowledge base of the chemical compounds involved in intermediary metabolism. We consider the motivations for constructing a knowledge base of metabolic compounds, the methodology by which it was constructed, and the information that it currently contains. Currently the knowledge base describes 981 compounds, listing for each: synonyms for its name, a systematic name, CAS registry number, chemical formula, molecular weight, chemical structure and two-dimensional display coordinates for the structure. The Compound Knowledge Base (CompoundKB) illustrates several methodological principles that should guide the development of biological knowledge bases. I argue that biological datasets should be made available in multiple representations to increase their accessibility to end users, and I present multiple representations of the CompoundKB (knowledge base, relational data base and ASN. 1 representations). I also analyze the general characteristics of these representations to provide an understanding of their relative advantages and disadvantages. Another principle is that the error rate of biological data bases should be estimated and documented-this analysis is performed for the CompoundKB.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Reliability in the location of hindlimb motor representations in Fischer-344 rats: laboratory investigation.

PubMed

Frost, Shawn B; Iliakova, Maria; Dunham, Caleb; Barbay, Scott; Arnold, Paul; Nudo, Randolph J

2013-08-01

The purpose of the present study was to determine the feasibility of using a common laboratory rat strain for reliably locating cortical motor representations of the hindlimb. Intracortical microstimulation techniques were used to derive detailed maps of the hindlimb motor representations in 6 adult Fischer-344 rats. The organization of the hindlimb movement representation, while variable across individual rats in topographic detail, displayed several commonalities. The hindlimb representation was positioned posterior to the forelimb motor representation and posterolateral to the motor trunk representation. The areal extent of the hindlimb representation across the cortical surface averaged 2.00 ± 0.50 mm(2). Superimposing individual maps revealed an overlapping area measuring 0.35 mm(2), indicating that the location of the hindlimb representation can be predicted reliably based on stereotactic coordinates. Across the sample of rats, the hindlimb representation was found 1.25-3.75 mm posterior to the bregma, with an average center location approximately 2.6 mm posterior to the bregma. Likewise, the hindlimb representation was found 1-3.25 mm lateral to the midline, with an average center location approximately 2 mm lateral to the midline. The location of the cortical hindlimb motor representation in Fischer-344 rats can be reliably located based on its stereotactic position posterior to the bregma and lateral to the longitudinal skull suture at midline. The ability to accurately predict the cortical localization of functional hindlimb territories in a rodent model is important, as such animal models are being increasingly used in the development of brain-computer interfaces for restoration of function after spinal cord injury.

Reliability in the Location of Hindlimb Motor Representations in Fischer-344 Rats

PubMed Central

Frost, Shawn B.; Iliakova, Maria; Dunham, Caleb; Barbay, Scott; Arnold, Paul; Nudo, Randolph J.

2014-01-01

Object The purpose of the present study was to determine the feasibility of using a common laboratory rat strain for locating cortical motor representations of the hindlimb reliably. Methods Intracortical Microstimulation (ICMS) techniques were used to derive detailed maps of the hindlimb motor representations in six adult Fischer-344 rats. Results The organization of the hindlimb movement representation, while variable across individuals in topographic detail, displayed several commonalities. The hindlimb representation was positioned posterior to the forelimb motor representation and postero-lateral to the motor trunk representation. The areal extent of the hindlimb representation across the cortical surface averaged 2.00 +/− 0.50 mm2. Superimposing individual maps revealed an overlapping area measuring 0.35 mm2, indicating that the location of the hindlimb representation can be predicted reliably based on stereotactic coordinates. Across the sample of rats, the hindlimb representation was found 1.25–3.75 mm posterior to Bregma, with an average center location ~ 2.6 mm posterior to Bregma. Likewise, the hindlimb representation was found 1–3.25 mm lateral to the midline, with an average center location ~ 2 mm lateral to midline. Conclusions The location of the cortical hindlimb motor representation in Fischer-344 rats can be reliably located based on its stereotactic position posterior to Bregma and lateral to the longitudinal skull suture at midline. The ability to accurately predict the cortical localization of functional hindlimb territories in a rodent model is important, as such animal models are being used increasingly in the development of brain-computer interfaces for restoration of function after spinal cord injury. PMID:23725395

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

NASA Astrophysics Data System (ADS)

Sowanto; Kusumah, Y. S.

2018-05-01

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

Dependency-based Siamese long short-term memory network for learning sentence representations

PubMed Central

Zhu, Wenhao; Ni, Jianyue; Wei, Baogang; Lu, Zhiguo

2018-01-01

Textual representations play an important role in the field of natural language processing (NLP). The efficiency of NLP tasks, such as text comprehension and information extraction, can be significantly improved with proper textual representations. As neural networks are gradually applied to learn the representation of words and phrases, fairly efficient models of learning short text representations have been developed, such as the continuous bag of words (CBOW) and skip-gram models, and they have been extensively employed in a variety of NLP tasks. Because of the complex structure generated by the longer text lengths, such as sentences, algorithms appropriate for learning short textual representations are not applicable for learning long textual representations. One method of learning long textual representations is the Long Short-Term Memory (LSTM) network, which is suitable for processing sequences. However, the standard LSTM does not adequately address the primary sentence structure (subject, predicate and object), which is an important factor for producing appropriate sentence representations. To resolve this issue, this paper proposes the dependency-based LSTM model (D-LSTM). The D-LSTM divides a sentence representation into two parts: a basic component and a supporting component. The D-LSTM uses a pre-trained dependency parser to obtain the primary sentence information and generate supporting components, and it also uses a standard LSTM model to generate the basic sentence components. A weight factor that can adjust the ratio of the basic and supporting components in a sentence is introduced to generate the sentence representation. Compared with the representation learned by the standard LSTM, the sentence representation learned by the D-LSTM contains a greater amount of useful information. The experimental results show that the D-LSTM is superior to the standard LSTM for sentences involving compositional knowledge (SICK) data. PMID:29513748

Strength of object representation: its key role in object-based attention for determining the competition result between Gestalt and top-down objects.

PubMed

Zhao, Jingjing; Wang, Yonghui; Liu, Donglai; Zhao, Liang; Liu, Peng

2015-10-01

It was found in previous studies that two types of objects (rectangles formed according to the Gestalt principle and Chinese words formed in a top-down fashion) can both induce an object-based effect. The aim of the present study was to investigate how the strength of an object representation affects the result of the competition between these two types of objects based on research carried out by Liu, Wang and Zhou [(2011) Acta Psychologica, 138(3), 397-404]. In Experiment 1, the rectangles were filled with two different colors to increase the strength of Gestalt object representation, and we found that the object effect changed significantly for the different stimulus types. Experiment 2 used Chinese words with various familiarities to manipulate the strength of the top-down object representation. As a result, the object-based effect induced by rectangles was observed only when the Chinese word familiarity was low. These results suggest that the strength of object representation determines the result of competition between different types of objects.

Secure base representations in middle childhood across two Western cultures: Associations with parental attachment representations and maternal reports of behavior problems.

PubMed

Waters, Theodore E A; Bosmans, Guy; Vandevivere, Eva; Dujardin, Adinda; Waters, Harriet S

2015-08-01

Recent work examining the content and organization of attachment representations suggests that 1 way in which we represent the attachment relationship is in the form of a cognitive script. This work has largely focused on early childhood or adolescence/adulthood, leaving a large gap in our understanding of script-like attachment representations in the middle childhood period. We present 2 studies and provide 3 critical pieces of evidence regarding the presence of a script-like representation of the attachment relationship in middle childhood. We present evidence that a middle childhood attachment script assessment tapped a stable underlying script using samples drawn from 2 western cultures, the United States (Study 1) and Belgium (Study 2). We also found evidence suggestive of the intergenerational transmission of secure base script knowledge (Study 1) and relations between secure base script knowledge and symptoms of psychopathology in middle childhood (Study 2). The results from this investigation represent an important downward extension of the secure base script construct. (c) 2015 APA, all rights reserved).

Secure Base Representations in Middle Childhood Across Two Western Cultures: Associations with Parental Attachment Representations and Maternal Reports of Behavior Problems

PubMed Central

Waters, Theodore E. A.; Bosmans, Guy; Vandevivere, Eva; Dujardin, Adinda; Waters, Harriet S.

2015-01-01

Recent work examining the content and organization of attachment representations suggests that one way in which we represent the attachment relationship is in the form of a cognitive script. That said, this work has largely focused on early childhood or adolescence/adulthood, leaving a large gap in our understanding of script-like attachment representations in the middle childhood period. We present two studies and provide three critical pieces of evidence regarding the presence of a script-like representation of the attachment relationship in middle childhood. We present evidence that a middle childhood attachment script assessment tapped a stable underlying script using samples drawn from two western cultures, the United States (Study 1) and Belgium (Study 2). We also found evidence suggestive of the intergenerational transmission of secure base script knowledge (Study 1) and relations between secure base script knowledge and symptoms of psychopathology in middle childhood (Study 2). The results from this investigation represent an important downward extension of the secure base script construct. PMID:26147774

The Effects of Scaffolded Simulation-Based Inquiry Learning on Fifth-Graders' Representations of the Greenhouse Effect

NASA Astrophysics Data System (ADS)

Kukkonen, Jari Ensio; Kärkkäinen, Sirpa; Dillon, Patrick; Keinonen, Tuula

2014-02-01

Research has demonstrated that simulation-based inquiry learning has significant advantages for learning outcomes when properly scaffolded. For successful learning in science with simulation-based inquiry, one needs to ascertain levels of background knowledge so as to support learners in making, evaluating and modifying hypotheses, conducting experiments and interpreting data, and to regulate the learning process. This case study examines the influence of scaffolded simulation-based inquiry learning on fifth-graders' (n = 21) models of the greenhouse effect. The pupils were asked to make annotated drawings about the greenhouse effect both before and after scaffolding through simulation-based instructional interventions. The data were analysed qualitatively to investigate the impact of the interventions on the representations that pupils used in their descriptions of the greenhouse effect. It was found that scaffolded simulation-based inquiry learning noticeably enriched the concepts pupils used in their representations leading to better understanding of the phenomenon. In many cases, the fifth graders produced quite sophisticated representations.

Impossibility Theorem in Proportional Representation Problem

NASA Astrophysics Data System (ADS)

Karpov, Alexander

2010-09-01

The study examines general axiomatics of Balinski and Young and analyzes existed proportional representation methods using this approach. The second part of the paper provides new axiomatics based on rational choice models. New system of axioms is applied to study known proportional representation systems. It is shown that there is no proportional representation method satisfying a minimal set of the axioms (monotonicity and neutrality).

Research in Knowledge Representation for Natural Language Understanding

DTIC Science & Technology

1980-11-01

artificial intelligence, natural language understanding , parsing, syntax, semantics, speaker meaning, knowledge representation, semantic networks...TinB PAGE map M W006 1Report No. 4513 L RESEARCH IN KNOWLEDGE REPRESENTATION FOR NATURAL LANGUAGE UNDERSTANDING Annual Report 1 September 1979 to 31... understanding , knowledge representation, and knowledge based inference. The work that we have been doing falls into three classes, successively motivated by

Semiclassical initial value representation for the quantum propagator in the Heisenberg interaction representation

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

Petersen, Jakob; Pollak, Eli, E-mail: eli.pollak@weizmann.ac.il

2015-12-14

One of the challenges facing on-the-fly ab initio semiclassical time evolution is the large expense needed to converge the computation. In this paper, we suggest that a significant saving in computational effort may be achieved by employing a semiclassical initial value representation (SCIVR) of the quantum propagator based on the Heisenberg interaction representation. We formulate and test numerically a modification and simplification of the previous semiclassical interaction representation of Shao and Makri [J. Chem. Phys. 113, 3681 (2000)]. The formulation is based on the wavefunction form of the semiclassical propagation instead of the operator form, and so is simpler andmore » cheaper to implement. The semiclassical interaction representation has the advantage that the phase and prefactor vary relatively slowly as compared to the “standard” SCIVR methods. This improves its convergence properties significantly. Using a one-dimensional model system, the approximation is compared with Herman-Kluk’s frozen Gaussian and Heller’s thawed Gaussian approximations. The convergence properties of the interaction representation approach are shown to be favorable and indicate that the interaction representation is a viable way of incorporating on-the-fly force field information within a semiclassical framework.« less

Neural representations of magnitude for natural and rational numbers.

PubMed

DeWolf, Melissa; Chiang, Jeffrey N; Bassok, Miriam; Holyoak, Keith J; Monti, Martin M

2016-11-01

Humans have developed multiple symbolic representations for numbers, including natural numbers (positive integers) as well as rational numbers (both fractions and decimals). Despite a considerable body of behavioral and neuroimaging research, it is currently unknown whether different notations map onto a single, fully abstract, magnitude code, or whether separate representations exist for specific number types (e.g., natural versus rational) or number representations (e.g., base-10 versus fractions). We address this question by comparing brain metabolic response during a magnitude comparison task involving (on different trials) integers, decimals, and fractions. Univariate and multivariate analyses revealed that the strength and pattern of activation for fractions differed systematically, within the intraparietal sulcus, from that of both decimals and integers, while the latter two number representations appeared virtually indistinguishable. These results demonstrate that the two major notations formats for rational numbers, fractions and decimals, evoke distinct neural representations of magnitude, with decimals representations being more closely linked to those of integers than to those of magnitude-equivalent fractions. Our findings thus suggest that number representation (base-10 versus fractions) is an important organizational principle for the neural substrate underlying mathematical cognition. Copyright © 2016 Elsevier Inc. All rights reserved.

New instantaneous frequency estimation method based on the use of image processing techniques

NASA Astrophysics Data System (ADS)

Borda, Monica; Nafornita, Ioan; Isar, Alexandru

2003-05-01

The aim of this paper is to present a new method for the estimation of the instantaneous frequency of a frequency modulated signal, corrupted by additive noise. This method represents an example of fusion of two theories: the time-frequency representations and the mathematical morphology. Any time-frequency representation of a useful signal is concentrated around its instantaneous frequency law and realizes the diffusion of the noise that perturbs the useful signal in the time - frequency plane. In this paper a new time-frequency representation, useful for the estimation of the instantaneous frequency, is proposed. This time-frequency representation is the product of two others time-frequency representations: the Wigner - Ville time-frequency representation and a new one obtained by filtering with a hard thresholding filter the Gabor representation of the signal to be processed. Using the image of this new time-frequency representation the instantaneous frequency of the useful signal can be extracted with the aid of some mathematical morphology operators: the conversion in binary form, the dilation and the skeleton. The simulations of the proposed method have proved its qualities. It is better than other estimation methods, like those based on the use of adaptive notch filters.

Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations.

PubMed

Cao, Houwei; Savran, Arman; Verma, Ragini; Nenkova, Ani

2015-01-01

In this article we investigate what representations of acoustics and word usage are most suitable for predicting dimensions of affect|AROUSAL, VALANCE, POWER and EXPECTANCY|in spontaneous interactions. Our experiments are based on the AVEC 2012 challenge dataset. For lexical representations, we compare corpus-independent features based on psychological word norms of emotional dimensions, as well as corpus-dependent representations. We find that corpus-dependent bag of words approach with mutual information between word and emotion dimensions is by far the best representation. For the analysis of acoustics, we zero in on the question of granularity. We confirm on our corpus that utterance-level features are more predictive than word-level features. Further, we study more detailed representations in which the utterance is divided into regions of interest (ROI), each with separate representation. We introduce two ROI representations, which significantly outperform less informed approaches. In addition we show that acoustic models of emotion can be improved considerably by taking into account annotator agreement and training the model on smaller but reliable dataset. Finally we discuss the potential for improving prediction by combining the lexical and acoustic modalities. Simple fusion methods do not lead to consistent improvements over lexical classifiers alone but improve over acoustic models.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

NetWeaver for EMDS user guide (version 1.1): a knowledge base development system.

Treesearch

Keith M. Reynolds

1999-01-01

The guide describes use of the NetWeaver knowledge base development system. Knowledge representation in NetWeaver is based on object-oriented fuzzy-logic networks that offer several significant advantages over the more traditional rulebased representation. Compared to rule-based knowledge bases, NetWeaver knowledge bases are easier to build, test, and maintain because...

A path-oriented matrix-based knowledge representation system

NASA Technical Reports Server (NTRS)

Feyock, Stefan; Karamouzis, Stamos T.

1993-01-01

Experience has shown that designing a good representation is often the key to turning hard problems into simple ones. Most AI (Artificial Intelligence) search/representation techniques are oriented toward an infinite domain of objects and arbitrary relations among them. In reality much of what needs to be represented in AI can be expressed using a finite domain and unary or binary predicates. Well-known vector- and matrix-based representations can efficiently represent finite domains and unary/binary predicates, and allow effective extraction of path information by generalized transitive closure/path matrix computations. In order to avoid space limitations a set of abstract sparse matrix data types was developed along with a set of operations on them. This representation forms the basis of an intelligent information system for representing and manipulating relational data.

Inequivalent coherent state representations in group field theory

NASA Astrophysics Data System (ADS)

Kegeles, Alexander; Oriti, Daniele; Tomlin, Casey

2018-06-01

In this paper we propose an algebraic formulation of group field theory and consider non-Fock representations based on coherent states. We show that we can construct representations with an infinite number of degrees of freedom on compact manifolds. We also show that these representations break translation symmetry. Since such representations can be regarded as quantum gravitational systems with an infinite number of fundamental pre-geometric building blocks, they may be more suitable for the description of effective geometrical phases of the theory.

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2000-08-08

A method and apparatus for modeling interactions between bodies. The method comprises representing two bodies undergoing translations and rotations by two hierarchical swept volume representations. Interactions such as nearest approach and collision can be modeled based on the swept body representations. The present invention can serve as a practical tool in motion planning, CAD systems, simulation systems, safety analysis, and applications that require modeling time-based interactions. A body can be represented in the present invention by a union of convex polygons and convex polyhedra. As used generally herein, polyhedron includes polygon, and polyhedra includes polygons. The body undergoing translation can be represented by a swept body representation, where the swept body representation comprises a hierarchical bounding volume representation whose leaves each contain a representation of the region swept by a section of the body during the translation, and where the union of the regions is a superset of the region swept by the surface of the body during translation. Interactions between two bodies thus represented can be modeled by modeling interactions between the convex hulls of the finite sets of discrete points in the swept body representations.

Developing young adults' representational competence through infographic-based science news reporting

NASA Astrophysics Data System (ADS)

Gebre, Engida H.; Polman, Joseph L.

2016-12-01

This study presents descriptive analysis of young adults' use of multiple representations in the context of science news reporting. Across one semester, 71 high school students, in a socioeconomically diverse suburban secondary school in Midwestern United States, participated in activities of researching science topics of their choice and producing infographic-based science news for possible online publication. An external editor reviewed their draft infographics and provided comments for subsequent revision. Students also provided peer feedback to the draft version of infographics using an online commentary tool. We analysed the nature of representations students used as well as the comments from peer and the editor feedback. Results showed both students' capabilities and challenges in learning with representations in this context. Students frequently rely on using certain kinds of representations that are depictive in nature, and supporting their progress towards using more abstract representations requires special attention and identifying learning gaps. Results also showed that students were able to determine representational adequacy in the context of providing peer feedback. The study has implication for research and instruction using infographics as expressive tools to support learning.

Towards a standardised representation of a knowledge base for adverse drug event prevention.

PubMed

Koutkias, Vassilis; Lazou, Katerina; de Clercq, Paul; Maglaveras, Nicos

2011-01-01

Knowledge representation is an important part of knowledge engineering activities that is crucial for enabling knowledge sharing and reuse. In this regard, standardised formalisms and technologies play a significant role. Especially for the medical domain, where knowledge may be tacit, not articulated and highly diverse, the development and adoption of standardised knowledge representations is highly challenging and of outmost importance to achieve knowledge interoperability. To this end, this paper presents a research effort towards the standardised representation of a Knowledge Base (KB) encapsulating rule-based signals and procedures for Adverse Drug Event (ADE) prevention. The KB constitutes an integral part of Clinical Decision Support Systems (CDSSs) to be used at the point of care. The paper highlights the requirements at the domain of discourse with respect to knowledge representation, according to which GELLO (an HL7 and ANSI standard) has been adopted. Results of our prototype implementation are presented along with the advantages and the limitations introduced by the employed approach.

A Subdivision-Based Representation for Vector Image Editing.

PubMed

Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

2012-11-01

Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.

Implicit kernel sparse shape representation: a sparse-neighbors-based objection segmentation framework.

PubMed

Yao, Jincao; Yu, Huimin; Hu, Roland

2017-01-01

This paper introduces a new implicit-kernel-sparse-shape-representation-based object segmentation framework. Given an input object whose shape is similar to some of the elements in the training set, the proposed model can automatically find a cluster of implicit kernel sparse neighbors to approximately represent the input shape and guide the segmentation. A distance-constrained probabilistic definition together with a dualization energy term is developed to connect high-level shape representation and low-level image information. We theoretically prove that our model not only derives from two projected convex sets but is also equivalent to a sparse-reconstruction-error-based representation in the Hilbert space. Finally, a "wake-sleep"-based segmentation framework is applied to drive the evolutionary curve to recover the original shape of the object. We test our model on two public datasets. Numerical experiments on both synthetic images and real applications show the superior capabilities of the proposed framework.

Color Sparse Representations for Image Processing: Review, Models, and Prospects.

PubMed

Barthélemy, Quentin; Larue, Anthony; Mars, Jérôme I

2015-11-01

Sparse representations have been extended to deal with color images composed of three channels. A review of dictionary-learning-based sparse representations for color images is made here, detailing the differences between the models, and comparing their results on the real and simulated data. These models are considered in a unifying framework that is based on the degrees of freedom of the linear filtering/transformation of the color channels. Moreover, this allows it to be shown that the scalar quaternionic linear model is equivalent to constrained matrix-based color filtering, which highlights the filtering implicitly applied through this model. Based on this reformulation, the new color filtering model is introduced, using unconstrained filters. In this model, spatial morphologies of color images are encoded by atoms, and colors are encoded by color filters. Color variability is no longer captured in increasing the dictionary size, but with color filters, this gives an efficient color representation.

Characterizing Interaction with Visual Mathematical Representations

ERIC Educational Resources Information Center

Sedig, Kamran; Sumner, Mark

2006-01-01

This paper presents a characterization of computer-based interactions by which learners can explore and investigate visual mathematical representations (VMRs). VMRs (e.g., geometric structures, graphs, and diagrams) refer to graphical representations that visually encode properties and relationships of mathematical structures and concepts.…

A Nakanishi-based model illustrating the covariant extension of the pion GPD overlap representation and its ambiguities

NASA Astrophysics Data System (ADS)

Chouika, N.; Mezrag, C.; Moutarde, H.; Rodríguez-Quintero, J.

2018-05-01

A systematic approach for the model building of Generalized Parton Distributions (GPDs), based on their overlap representation within the DGLAP kinematic region and a further covariant extension to the ERBL one, is applied to the valence-quark pion's case, using light-front wave functions inspired by the Nakanishi representation of the pion Bethe-Salpeter amplitudes (BSA). This simple but fruitful pion GPD model illustrates the general model building technique and, in addition, allows for the ambiguities related to the covariant extension, grounded on the Double Distribution (DD) representation, to be constrained by requiring a soft-pion theorem to be properly observed.

Improving students’ mathematical representational ability through RME-based progressive mathematization

NASA Astrophysics Data System (ADS)

Warsito; Darhim; Herman, T.

2018-01-01

This study aims to determine the differences in the improving of mathematical representation ability based on progressive mathematization with realistic mathematics education (PMR-MP) with conventional learning approach (PB). The method of research is quasi-experiments with non-equivalent control group designs. The study population is all students of class VIII SMPN 2 Tangerang consisting of 6 classes, while the sample was taken two classes with purposive sampling technique. The experimental class is treated with PMR-MP while the control class is treated with PB. The instruments used are test of mathematical representation ability. Data analysis was done by t-test, ANOVA test, post hoc test, and descriptive analysis. The result of analysis can be concluded that: 1) there are differences of mathematical representation ability improvement between students treated by PMR-MP and PB, 2) no interaction between learning approach (PMR-MP, PB) and prior mathematics knowledge (PAM) to improve students’ mathematical representation; 3) Students’ mathematical representation improvement in the level of higher PAM is better than medium, and low PAM students. Thus, based on the process of mathematization, it is very important when the learning direction of PMR-MP emphasizes on the process of building mathematics through a mathematical model.

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

Online fingerprint verification.

PubMed

Upendra, K; Singh, S; Kumar, V; Verma, H K

2007-01-01

As organizations search for more secure authentication methods for user access, e-commerce, and other security applications, biometrics is gaining increasing attention. With an increasing emphasis on the emerging automatic personal identification applications, fingerprint based identification is becoming more popular. The most widely used fingerprint representation is the minutiae based representation. The main drawback with this representation is that it does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Also, it is difficult quickly to match two fingerprint images containing different number of unregistered minutiae points. In this study filter bank based representation, which eliminates these weakness, is implemented and the overall performance of the developed system is tested. The results have shown that this system can be used effectively for secure online verification applications.

Secure Base Representations in Middle Childhood across Two Western Cultures: Associations with Parental Attachment Representations and Maternal Reports of Behavior Problems

ERIC Educational Resources Information Center

Waters, Theodore E. A.; Bosmans, Guy; Vandevivere, Eva; Dujardin, Adinda; Waters, Harriet S.

2015-01-01

Recent work examining the content and organization of attachment representations suggests that 1 way in which we represent the attachment relationship is in the form of a cognitive script. This work has largely focused on early childhood or adolescence/adulthood, leaving a large gap in our understanding of script-like attachment representations in…

A critical review of the allocentric spatial representation and its neural underpinnings: toward a network-based perspective

PubMed Central

Ekstrom, Arne D.; Arnold, Aiden E. G. F.; Iaria, Giuseppe

2014-01-01

While the widely studied allocentric spatial representation holds a special status in neuroscience research, its exact nature and neural underpinnings continue to be the topic of debate, particularly in humans. Here, based on a review of human behavioral research, we argue that allocentric representations do not provide the kind of map-like, metric representation one might expect based on past theoretical work. Instead, we suggest that almost all tasks used in past studies involve a combination of egocentric and allocentric representation, complicating both the investigation of the cognitive basis of an allocentric representation and the task of identifying a brain region specifically dedicated to it. Indeed, as we discuss in detail, past studies suggest numerous brain regions important to allocentric spatial memory in addition to the hippocampus, including parahippocampal, retrosplenial, and prefrontal cortices. We thus argue that although allocentric computations will often require the hippocampus, particularly those involving extracting details across temporally specific routes, the hippocampus is not necessary for all allocentric computations. We instead suggest that a non-aggregate network process involving multiple interacting brain areas, including hippocampus and extra-hippocampal areas such as parahippocampal, retrosplenial, prefrontal, and parietal cortices, better characterizes the neural basis of spatial representation during navigation. According to this model, an allocentric representation does not emerge from the computations of a single brain region (i.e., hippocampus) nor is it readily decomposable into additive computations performed by separate brain regions. Instead, an allocentric representation emerges from computations partially shared across numerous interacting brain regions. We discuss our non-aggregate network model in light of existing data and provide several key predictions for future experiments. PMID:25346679

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

PubMed

Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

2018-05-01

Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Neurons.

PubMed

Edwards, Jonathan C W

2016-01-01

It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with the issue of meaning, interpretation, or significance (semantic content). It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as a representation it must provide an input to a 'consumer' in the street. The arguments presented draw on two principles - the neuron doctrine and the need for a venue for 'presentation' or 'reception' of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include 'null' elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right - some form of atomic propositional significance - since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming 'scenarios' comprising a molecular combination of 'premises' from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to 'occurrent' representations based on current neural activity.) The concept of representations-as-input emphasizes the need for an internal 'consumer' of a representation and the dependence of meaning on the co-relationships involved in an input interaction between signals and consumer. The acceptance of this necessity provides a basis for resolving the problem that representations appear both as distributed (representation-as-origin) and as local (representation-as-input). The key implications are that representations in the brain are massively multiple both in series and in parallel, and that individual cells play specific semantic roles. These roles are discussed in relation to traditional concepts of 'gnostic' cell types.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Neurons

PubMed Central

Edwards, Jonathan C. W.

2016-01-01

It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with the issue of meaning, interpretation, or significance (semantic content). It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as a representation it must provide an input to a ‘consumer’ in the street. The arguments presented draw on two principles – the neuron doctrine and the need for a venue for ‘presentation’ or ‘reception’ of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include ‘null’ elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right – some form of atomic propositional significance – since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming ‘scenarios’ comprising a molecular combination of ‘premises’ from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to ‘occurrent’ representations based on current neural activity.) The concept of representations-as-input emphasizes the need for an internal ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an input interaction between signals and consumer. The acceptance of this necessity provides a basis for resolving the problem that representations appear both as distributed (representation-as-origin) and as local (representation-as-input). The key implications are that representations in the brain are massively multiple both in series and in parallel, and that individual cells play specific semantic roles. These roles are discussed in relation to traditional concepts of ‘gnostic’ cell types. PMID:27746760

Classification of forensic autopsy reports through conceptual graph-based document representation model.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2018-06-01

Text categorization has been used extensively in recent years to classify plain-text clinical reports. This study employs text categorization techniques for the classification of open narrative forensic autopsy reports. One of the key steps in text classification is document representation. In document representation, a clinical report is transformed into a format that is suitable for classification. The traditional document representation technique for text categorization is the bag-of-words (BoW) technique. In this study, the traditional BoW technique is ineffective in classifying forensic autopsy reports because it merely extracts frequent but discriminative features from clinical reports. Moreover, this technique fails to capture word inversion, as well as word-level synonymy and polysemy, when classifying autopsy reports. Hence, the BoW technique suffers from low accuracy and low robustness unless it is improved with contextual and application-specific information. To overcome the aforementioned limitations of the BoW technique, this research aims to develop an effective conceptual graph-based document representation (CGDR) technique to classify 1500 forensic autopsy reports from four (4) manners of death (MoD) and sixteen (16) causes of death (CoD). Term-based and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) based conceptual features were extracted and represented through graphs. These features were then used to train a two-level text classifier. The first level classifier was responsible for predicting MoD. In addition, the second level classifier was responsible for predicting CoD using the proposed conceptual graph-based document representation technique. To demonstrate the significance of the proposed technique, its results were compared with those of six (6) state-of-the-art document representation techniques. Lastly, this study compared the effects of one-level classification and two-level classification on the experimental results. The experimental results indicated that the CGDR technique achieved 12% to 15% improvement in accuracy compared with fully automated document representation baseline techniques. Moreover, two-level classification obtained better results compared with one-level classification. The promising results of the proposed conceptual graph-based document representation technique suggest that pathologists can adopt the proposed system as their basis for second opinion, thereby supporting them in effectively determining CoD. Copyright © 2018 Elsevier Inc. All rights reserved.

Translation between representation languages

NASA Technical Reports Server (NTRS)

Vanbaalen, Jeffrey

1994-01-01

A capability for translating between representation languages is critical for effective knowledge base reuse. A translation technology for knowledge representation languages based on the use of an interlingua for communicating knowledge is described. The interlingua-based translation process consists of three major steps: translation from the source language into a subset of the interlingua, translation between subsets of the interlingua, and translation from a subset of the interlingua into the target language. The first translation step into the interlingua can typically be specified in the form of a grammar that describes how each top-level form in the source language translates into the interlingua. In cases where the source language does not have a declarative semantics, such a grammar is also a specification of a declarative semantics for the language. A methodology for building translators that is currently under development is described. A 'translator shell' based on this methodology is also under development. The shell has been used to build translators for multiple representation languages and those translators have successfully translated nontrivial knowledge bases.

Phonological Representations in Children with SLI

ERIC Educational Resources Information Center

Claessen, Mary; Leitao, Suze

2012-01-01

It has been hypothesized that children with specific language impairment (SLI) have difficulty processing sound-based information, including storing and accessing phonological representations in the lexicon. Tasks are emerging in the literature that provide a measure of the quality of stored phonological representations, without requiring a verbal…

Investigating Trigonometric Representations in the Transition to College Mathematics

ERIC Educational Resources Information Center

Byers, Patricia

2010-01-01

This Ontario-based qualitative study examined secondary school and college textbooks' treatment of trigonometric representations in order to identify potential sources of student difficulties in the transition from secondary school to college mathematics. Analysis of networks, comprised of trigonometric representations, identified numerous issues…

Heterotrophic Archaea Contribute to Carbon Cycling in Low-pH, Suboxic Biofilm Communities

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

Justice, Nicholas B; Pan, Chongle; Mueller, Ryan

Archaea are widely distributed and yet are most often not the most abundant members of microbial communities. Here, we document a transition from Bacteria- to Archaea-dominated communities in microbial biofilms sampled from the Richmond Mine acid mine drainage (AMD) system (pH 1.0,38 C) and in laboratory-cultivated biofilms. This transition occurs when chemoautotrophic microbial communities that develop at the air-solution interface sink to the sediment-solution interface and degrade under microaerobic and anaerobic conditions. The archaea identified in these sunken biofilms are from the class Thermoplasmata, and in some cases, the highly divergent ARMAN nanoarchaeal lineage. In several of the sunken biofilms,more » nanoarchaea comprise 10 to 25% of the community, based on fluorescent in situ hybridization and metagenomic analyses. Comparative community proteomic analyses show a persistence of bacterial proteins in sunken biofilms, but there is clear evidence for amino acid modifications due to acid hydrolysis. Given the low representation of bacterial cells in sunken biofilms based on microscopy, we infer that hydrolysis reflects proteins derived from lysed cells. For archaea, we detected 2,400 distinct proteins, including a subset involved in proteolysis and peptide uptake. Laboratory cultivation experiments using complex carbon substrates demonstrated anaerobic enrichment of Ferroplasma and Aplasma coupled to the reduction of ferric iron. These findings indicate dominance of acidophilic archaea in degrading biofilms and suggest that they play roles in anaerobic nutrient cycling at low pH.« less

NeEMO: a method using residue interaction networks to improve prediction of protein stability upon mutation.

PubMed

Giollo, Manuel; Martin, Alberto J M; Walsh, Ian; Ferrari, Carlo; Tosatto, Silvio C E

2014-01-01

The rapid growth of un-annotated missense variants poses challenges requiring novel strategies for their interpretation. From the thermodynamic point of view, amino acid changes can lead to a change in the internal energy of a protein and induce structural rearrangements. This is of great relevance for the study of diseases and protein design, justifying the development of prediction methods for variant-induced stability changes. Here we propose NeEMO, a tool for the evaluation of stability changes using an effective representation of proteins based on residue interaction networks (RINs). RINs are used to extract useful features describing interactions of the mutant amino acid with its structural environment. Benchmarking shows NeEMO to be very effective, allowing reliable predictions in different parts of the protein such as β-strands and buried residues. Validation on a previously published independent dataset shows that NeEMO has a Pearson correlation coefficient of 0.77 and a standard error of 1 Kcal/mol, outperforming nine recent methods. The NeEMO web server can be freely accessed from URL: http://protein.bio.unipd.it/neemo/. NeEMO offers an innovative and reliable tool for the annotation of amino acid changes. A key contribution are RINs, which can be used for modeling proteins and their interactions effectively. Interestingly, the approach is very general, and can motivate the development of a new family of RIN-based protein structure analyzers. NeEMO may suggest innovative strategies for bioinformatics tools beyond protein stability prediction.

Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences.

PubMed

Lentes, K U; Mathieu, E; Bischoff, R; Rasmussen, U B; Pavirani, A

1993-01-01

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%, since maximization of a homology score does not take into account any structural information. A new technique called Hydrophobic Cluster Analysis (HCA) has been developed by Lemesle-Varloot et al. (Biochimie 72, 555-574), 1990). This consists of comparing several sequences simultaneously and combining homology detection with secondary structure analysis. HCA is primarily based on the detection and comparison of structural segments constituting the hydrophobic core of globular protein domains, with or without transmembrane domains. We have applied HCA to the analysis of different families of G-protein coupled receptors, such as catecholamine receptors as well as peptide hormone receptors. Utilizing HCA the thrombin receptor, a new and as yet unique member of the family of G-protein coupled receptors, can be clearly classified as being closely related to the family of neuropeptide receptors rather than to the catecholamine receptors for which the shape of the hydrophobic clusters and the length of their third cytoplasmic loop are very different. Furthermore, the potential of HCA to predict relationships between new putative and already characterized members of this family of receptors will be presented.

Revising the Representation of Fatty Acid, Glycerolipid, and Glycerophospholipid Metabolism in the Consensus Model of Yeast Metabolism

PubMed Central

Aung, Hnin W.; Henry, Susan A.

2013-01-01

Abstract Genome-scale metabolic models are built using information from an organism's annotated genome and, correspondingly, information on reactions catalyzed by the set of metabolic enzymes encoded by the genome. These models have been successfully applied to guide metabolic engineering to increase production of metabolites of industrial interest. Congruity between simulated and experimental metabolic behavior is influenced by the accuracy of the representation of the metabolic network in the model. In the interest of applying the consensus model of Saccharomyces cerevisiae metabolism for increased productivity of triglycerides, we manually evaluated the representation of fatty acid, glycerophospholipid, and glycerolipid metabolism in the consensus model (Yeast v6.0). These areas of metabolism were chosen due to their tightly interconnected nature to triglyceride synthesis. Manual curation was facilitated by custom MATLAB functions that return information contained in the model for reactions associated with genes and metabolites within the stated areas of metabolism. Through manual curation, we have identified inconsistencies between information contained in the model and literature knowledge. These inconsistencies include incorrect gene-reaction associations, improper definition of substrates/products in reactions, inappropriate assignments of reaction directionality, nonfunctional β-oxidation pathways, and missing reactions relevant to the synthesis and degradation of triglycerides. Suggestions to amend these inconsistencies in the Yeast v6.0 model can be implemented through a MATLAB script provided in the Supplementary Materials, Supplementary Data S1 (Supplementary Data are available online at www.liebertpub.com/ind). PMID:24678285

Differential representation of liver proteins in obese human subjects suggests novel biomarkers and promising targets for drug development in obesity.

PubMed

Caira, Simonetta; Iannelli, Antonio; Sciarrillo, Rosaria; Picariello, Gianluca; Renzone, Giovanni; Scaloni, Andrea; Addeo, Pietro

2017-12-01

The proteome of liver biopsies from human obese (O) subjects has been compared to those of nonobese (NO) subjects using two-dimensional gel electrophoresis (2-DE). Differentially represented proteins were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based peptide mass fingerprinting (PMF) and nanoflow-liquid chromatography coupled to electrospray-tandem mass spectrometry (nLC-ESI-MS/MS). Overall, 61 gene products common to all of the liver biopsies were identified within 65 spots, among which 25 ones were differently represented between O and NO subjects. In particular, over-representation of short-chain acyl-CoA dehydrogenase, Δ(3,5)-Δ(2,4)dienoyl-CoA isomerase, acetyl-CoA acetyltransferase, glyoxylate reductase/hydroxypyruvate reductase, fructose-biphosphate aldolase B, peroxiredoxin I, protein DJ-1, catalase, α- and β-hemoglobin subunits, 3-mercaptopyruvate S-transferase, calreticulin, aminoacylase 1, phenazine biosynthesis-like domain-containing protein and a form of fatty acid-binding protein, together with downrepresentation of glutamate dehydrogenase, glutathione S-transferase A1, S-adenosylmethionine synthase 1A and a form of apolipoprotein A-I, was associated with the obesity condition. Some of these metabolic enzymes and antioxidant proteins have already been identified as putative diagnostic markers of liver dysfunction in animal models of steatosis or obesity, suggesting additional investigations on their role in these syndromes. Their differential representation in human liver was suggestive of their consideration as obesity human biomarkers and for the development of novel antiobesity drugs.

Sparsity-Based Representation for Classification Algorithms and Comparison Results for Transient Acoustic Signals

DTIC Science & Technology

2016-05-01

large but correlated noise and signal interference (i.e., low -rank interference). Another contribution is the implementation of deep learning...representation, low rank, deep learning 52 Tung-Duong Tran-Luu 301-394-3082Unclassified Unclassified Unclassified UU ii Approved for public release; distribution...Classification of Acoustic Transients 6 3.2 Joint Sparse Representation with Low -Rank Interference 7 3.3 Simultaneous Group-and-Joint Sparse Representation

Vector-Based Ground Surface and Object Representation Using Cameras

DTIC Science & Technology

2009-12-01

representations and it is a digital data structure used for the representation of a ground surface in geographical information systems ( GIS ). Figure...Vision API library, and the OpenCV library. Also, the Posix thread library was utilized to quickly capture the source images from cameras. Both

Effects of Abstract and Concrete Simulation Elements on Science Learning

ERIC Educational Resources Information Center

Jaakkola, T.; Veermans, K.

2015-01-01

Contemporary evidence on the effectiveness of concrete and abstract representations in science education is based solely on studies conducted in college context. There it has been found that learning with abstract representations produces predominantly better outcomes than learning with concrete representations and combining the representations…

Representational Approach: A Conceptual Framework to Guide Patient Education Research and Practice.

PubMed

Arida, Janet A; Sherwood, Paula R; Flannery, Marie; Donovan, Heidi S

2016-11-01

Illness representations are cognitive structures that individuals rely on to understand and explain their illnesses and associated symptoms. The Representational Approach (RA) to patient education offers a theoretically based, clinically useful model that can support oncology nurses to develop a shared understanding of patients' illness representations to collaboratively develop highly personalized plans for symptom management and other important self-management behaviors. This article discusses theoretical underpinnings, practical applications, challenges, and future directions for incorporating illness representations and the RA in clinical and research endeavors.

Modified signed-digit arithmetic based on redundant bit representation.

PubMed

Huang, H; Itoh, M; Yatagai, T

1994-09-10

Fully parallel modified signed-digit arithmetic operations are realized based on redundant bit representation of the digits proposed. A new truth-table minimizing technique is presented based on redundant-bitrepresentation coding. It is shown that only 34 minterms are enough for implementing one-step modified signed-digit addition and subtraction with this new representation. Two optical implementation schemes, correlation and matrix multiplication, are described. Experimental demonstrations of the correlation architecture are presented. Both architectures use fixed minterm masks for arbitrary-length operands, taking full advantage of the parallelism of the modified signed-digit number system and optics.

Text categorization of biomedical data sets using graph kernels and a controlled vocabulary.

PubMed

Bleik, Said; Mishra, Meenakshi; Huan, Jun; Song, Min

2013-01-01

Recently, graph representations of text have been showing improved performance over conventional bag-of-words representations in text categorization applications. In this paper, we present a graph-based representation for biomedical articles and use graph kernels to classify those articles into high-level categories. In our representation, common biomedical concepts and semantic relationships are identified with the help of an existing ontology and are used to build a rich graph structure that provides a consistent feature set and preserves additional semantic information that could improve a classifier's performance. We attempt to classify the graphs using both a set-based graph kernel that is capable of dealing with the disconnected nature of the graphs and a simple linear kernel. Finally, we report the results comparing the classification performance of the kernel classifiers to common text-based classifiers.

Maximum entropy perception-action space: a Bayesian model of eye movement selection

NASA Astrophysics Data System (ADS)

Colas, Francis; Bessière, Pierre; Girard, Benoît

2011-03-01

In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps predict the eye movements of subjects recorded in a psychophysics experiment. Finally, based on experimental data, we postulate that the complex logarithmic mapping has a functional relevance, as the density of objects in this space in more uniform than expected. This may indicate that the representation space and control strategies are such that the object density is of maximum entropy.

Harnessing Computational Biology for Exact Linear B-Cell Epitope Prediction: A Novel Amino Acid Composition-Based Feature Descriptor.

PubMed

Saravanan, Vijayakumar; Gautham, Namasivayam

2015-10-01

Proteins embody epitopes that serve as their antigenic determinants. Epitopes occupy a central place in integrative biology, not to mention as targets for novel vaccine, pharmaceutical, and systems diagnostics development. The presence of T-cell and B-cell epitopes has been extensively studied due to their potential in synthetic vaccine design. However, reliable prediction of linear B-cell epitope remains a formidable challenge. Earlier studies have reported discrepancy in amino acid composition between the epitopes and non-epitopes. Hence, this study proposed and developed a novel amino acid composition-based feature descriptor, Dipeptide Deviation from Expected Mean (DDE), to distinguish the linear B-cell epitopes from non-epitopes effectively. In this study, for the first time, only exact linear B-cell epitopes and non-epitopes have been utilized for developing the prediction method, unlike the use of epitope-containing regions in earlier reports. To evaluate the performance of the DDE feature vector, models have been developed with two widely used machine-learning techniques Support Vector Machine and AdaBoost-Random Forest. Five-fold cross-validation performance of the proposed method with error-free dataset and dataset from other studies achieved an overall accuracy between nearly 61% and 73%, with balance between sensitivity and specificity metrics. Performance of the DDE feature vector was better (with accuracy difference of about 2% to 12%), in comparison to other amino acid-derived features on different datasets. This study reflects the efficiency of the DDE feature vector in enhancing the linear B-cell epitope prediction performance, compared to other feature representations. The proposed method is made as a stand-alone tool available freely for researchers, particularly for those interested in vaccine design and novel molecular target development for systems therapeutics and diagnostics: https://github.com/brsaran/LBEEP.

Multilayered nonuniform sampling for three-dimensional scene representation

NASA Astrophysics Data System (ADS)

Lin, Huei-Yung; Xiao, Yu-Hua; Chen, Bo-Ren

2015-09-01

The representation of a three-dimensional (3-D) scene is essential in multiview imaging technologies. We present a unified geometry and texture representation based on global resampling of the scene. A layered data map representation with a distance-dependent nonuniform sampling strategy is proposed. It is capable of increasing the details of the 3-D structure locally and is compact in size. The 3-D point cloud obtained from the multilayered data map is used for view rendering. For any given viewpoint, image synthesis with different levels of detail is carried out using the quadtree-based nonuniformly sampled 3-D data points. Experimental results are presented using the 3-D models of reconstructed real objects.

Incorporating Feature-Based Annotations into Automatically Generated Knowledge Representations

NASA Astrophysics Data System (ADS)

Lumb, L. I.; Lederman, J. I.; Aldridge, K. D.

2006-12-01

Earth Science Markup Language (ESML) is efficient and effective in representing scientific data in an XML- based formalism. However, features of the data being represented are not accounted for in ESML. Such features might derive from events (e.g., a gap in data collection due to instrument servicing), identifications (e.g., a scientifically interesting area/volume in an image), or some other source. In order to account for features in an ESML context, we consider them from the perspective of annotation, i.e., the addition of information to existing documents without changing the originals. Although it is possible to extend ESML to incorporate feature-based annotations internally (e.g., by extending the XML schema for ESML), there are a number of complicating factors that we identify. Rather than pursuing the ESML-extension approach, we focus on an external representation for feature-based annotations via XML Pointer Language (XPointer). In previous work (Lumb &Aldridge, HPCS 2006, IEEE, doi:10.1109/HPCS.2006.26), we have shown that it is possible to extract relationships from ESML-based representations, and capture the results in the Resource Description Format (RDF). Thus we explore and report on this same requirement for XPointer-based annotations of ESML representations. As in our past efforts, the Global Geodynamics Project (GGP) allows us to illustrate with a real-world example this approach for introducing annotations into automatically generated knowledge representations.

Visual saliency detection based on in-depth analysis of sparse representation

NASA Astrophysics Data System (ADS)

Wang, Xin; Shen, Siqiu; Ning, Chen

2018-03-01

Visual saliency detection has been receiving great attention in recent years since it can facilitate a wide range of applications in computer vision. A variety of saliency models have been proposed based on different assumptions within which saliency detection via sparse representation is one of the newly arisen approaches. However, most existing sparse representation-based saliency detection methods utilize partial characteristics of sparse representation, lacking of in-depth analysis. Thus, they may have limited detection performance. Motivated by this, this paper proposes an algorithm for detecting visual saliency based on in-depth analysis of sparse representation. A number of discriminative dictionaries are first learned with randomly sampled image patches by means of inner product-based dictionary atom classification. Then, the input image is partitioned into many image patches, and these patches are classified into salient and nonsalient ones based on the in-depth analysis of sparse coding coefficients. Afterward, sparse reconstruction errors are calculated for the salient and nonsalient patch sets. By investigating the sparse reconstruction errors, the most salient atoms, which tend to be from the most salient region, are screened out and taken away from the discriminative dictionaries. Finally, an effective method is exploited for saliency map generation with the reduced dictionaries. Comprehensive evaluations on publicly available datasets and comparisons with some state-of-the-art approaches demonstrate the effectiveness of the proposed algorithm.

Basic-Level and Superordinate-like Categorical Representations in Early Infancy.

ERIC Educational Resources Information Center

Behl-Chadha, Gundeep

1996-01-01

Examined three- to four-month-old infants' ability to form perceptually based categorical representation in the domains of natural kinds and artifacts. By showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, findings underscored the…

Interactivity of Visual Mathematical Representations: Factors Affecting Learning and Cognitive Processes

ERIC Educational Resources Information Center

Sedig, Kamran; Liang, Hai-Ning

2006-01-01

Computer-based mathematical cognitive tools (MCTs) are a category of external aids intended to support and enhance learning and cognitive processes of learners. MCTs often contain interactive visual mathematical representations (VMRs), where VMRs are graphical representations that encode properties and relationships of mathematical concepts. In…

Impact of the Second Semester University Modeling Instruction Course on Students' Representation Choices

ERIC Educational Resources Information Center

McPadden, Daryl; Brewe, Eric

2017-01-01

Representation use is a critical skill for learning, problem solving, and communicating in science, especially in physics where multiple representations often scaffold the understanding of a phenomenon. University Modeling Instruction, which is an active-learning, research-based introductory physics curriculum centered on students' use of…

Interleaved Practice with Multiple Representations: Analyses with Knowledge Tracing Based Techniques

ERIC Educational Resources Information Center

Rau, Martina A.; Pardos, Zachary A.

2012-01-01

The goal of this paper is to use Knowledge Tracing to augment the results obtained from an experiment that investigated the effects of practice schedules using an intelligent tutoring system for fractions. Specifically, this experiment compared different practice schedules of multiple representations of fractions: representations were presented to…

Exploring the Structure of Spatial Representations

PubMed Central

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

Knowledge Representation and Ontologies

NASA Astrophysics Data System (ADS)

Grimm, Stephan

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

Rankings of Economics Faculties and Representation on Editorial Boards of Top Journals.

ERIC Educational Resources Information Center

Gibbons, Jean D.; Fish, Mary

1991-01-01

Presents rankings of U.S., university, economics departments. Explains the rankings are based upon representation of the departments on the editorial boards of leading economics journals. Reports that results are similar to rankings based upon other criteria. (DK)

Representation and matching of knowledge to design digital systems

NASA Technical Reports Server (NTRS)

Jones, J. U.; Shiva, S. G.

1988-01-01

A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described.

Self-other disturbance in borderline personality disorder: Neural, self-report, and performance-based evidence.

PubMed

Beeney, Joseph E; Hallquist, Michael N; Ellison, William D; Levy, Kenneth N

2016-01-01

Individuals with borderline personality disorder (BPD) display an impoverished sense of self and representations of self and others that shift between positive and negative poles. However, little research has investigated the nature of representational disturbance in BPD. The present study takes a multimodal approach. A card sort task was used to investigate complexity, integration, and valence of self-representation in BPD. Impairment in maintenance of self and other representations was assessed using a personality representational maintenance task. Finally, functional MRI (fMRI) was used to assess whether individuals with BPD show neural abnormalities related specifically to the self and what brain areas may be related to poor representational maintenance. Individuals with BPD sorted self-aspects suggesting more complexity of self-representation, but also less integration and more negative valence overall. On the representational maintenance task, individuals with BPD showed less consistency in their representations of self and others over the 3-hr period, but only for abstract, personality-based representations. Performance on this measure mediated between-groups brain activation in several areas supporting social cognition. We found no evidence for social-cognitive disturbance specific to the self. Additionally, the BPD group showed main effects, insensitive to condition, of hyperactivation in the medial prefrontal cortex, temporal parietal junction, several regions of the frontal pole, the precuneus and middle temporal gyrus, all areas crucial social cognition. In contrast, controls evidenced greater activation in visual, sensory, motor, and mirror neuron regions. These findings are discussed in relation to research regarding hypermentalization and the overlap between self- and other-disturbance. (c) 2016 APA, all rights reserved).

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Design of multiple representations e-learning resources based on a contextual approach for the basic physics course

NASA Astrophysics Data System (ADS)

Bakri, F.; Muliyati, D.

2018-05-01

This research aims to design e-learning resources with multiple representations based on a contextual approach for the Basic Physics Course. The research uses the research and development methods accordance Dick & Carey strategy. The development carried out in the digital laboratory of Physics Education Department, Mathematics and Science Faculty, Universitas Negeri Jakarta. The result of the process of product development with Dick & Carey strategy, have produced e-learning design of the Basic Physics Course is presented in multiple representations in contextual learning syntax. The appropriate of representation used in the design of learning basic physics include: concept map, video, figures, data tables of experiment results, charts of data tables, the verbal explanations, mathematical equations, problem and solutions example, and exercise. Multiple representations are presented in the form of contextual learning by stages: relating, experiencing, applying, transferring, and cooperating.

Vietnamese Document Representation and Classification

NASA Astrophysics Data System (ADS)

Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

Mental Representations Formed From Educational Website Formats

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

Elizabeth T. Cady; Kimberly R. Raddatz; Tuan Q. Tran

2006-10-01

The increasing popularity of web-based distance education places high demand on distance educators to format web pages to facilitate learning. However, limited guidelines exist regarding appropriate writing styles for web-based distance education. This study investigated the effect of four different writing styles on reader’s mental representation of hypertext. Participants studied hypertext written in one of four web-writing styles (e.g., concise, scannable, objective, and combined) and were then administered a cued association task intended to measure their mental representations of the hypertext. It is hypothesized that the scannable and combined styles will bias readers to scan rather than elaborately read, whichmore » may result in less dense mental representations (as identified through Pathfinder analysis) relative to the objective and concise writing styles. Further, the use of more descriptors in the objective writing style will lead to better integration of ideas and more dense mental representations than the concise writing style.« less

A simplified formalism of the algebra of partially transposed permutation operators with applications

NASA Astrophysics Data System (ADS)

Mozrzymas, Marek; Studziński, Michał; Horodecki, Michał

2018-03-01

Herein we continue the study of the representation theory of the algebra of permutation operators acting on the n -fold tensor product space, partially transposed on the last subsystem. We develop the concept of partially reduced irreducible representations, which allows us to significantly simplify previously proved theorems and, most importantly, derive new results for irreducible representations of the mentioned algebra. In our analysis we are able to reduce the complexity of the central expressions by getting rid of sums over all permutations from the symmetric group, obtaining equations which are much more handy in practical applications. We also find relatively simple matrix representations for the generators of the underlying algebra. The obtained simplifications and developments are applied to derive the characteristics of a deterministic port-based teleportation scheme written purely in terms of irreducible representations of the studied algebra. We solve an eigenproblem for the generators of the algebra, which is the first step towards a hybrid port-based teleportation scheme and gives us new proofs of the asymptotic behaviour of teleportation fidelity. We also show a connection between the density operator characterising port-based teleportation and a particular matrix composed of an irreducible representation of the symmetric group, which encodes properties of the investigated algebra.

Formal ontologies in biomedical knowledge representation.

PubMed

Schulz, S; Jansen, L

2013-01-01

Medical decision support and other intelligent applications in the life sciences depend on increasing amounts of digital information. Knowledge bases as well as formal ontologies are being used to organize biomedical knowledge and data. However, these two kinds of artefacts are not always clearly distinguished. Whereas the popular RDF(S) standard provides an intuitive triple-based representation, it is semantically weak. Description logics based ontology languages like OWL-DL carry a clear-cut semantics, but they are computationally expensive, and they are often misinterpreted to encode all kinds of statements, including those which are not ontological. We distinguish four kinds of statements needed to comprehensively represent domain knowledge: universal statements, terminological statements, statements about particulars and contingent statements. We argue that the task of formal ontologies is solely to represent universal statements, while the non-ontological kinds of statements can nevertheless be connected with ontological representations. To illustrate these four types of representations, we use a running example from parasitology. We finally formulate recommendations for semantically adequate ontologies that can efficiently be used as a stable framework for more context-dependent biomedical knowledge representation and reasoning applications like clinical decision support systems.

Implementation of a frame-based representation in CLIPS

NASA Technical Reports Server (NTRS)

Assal, Hisham; Myers, Leonard

1990-01-01

Knowledge representation is one of the major concerns in expert systems. The representation of domain-specific knowledge should agree with the nature of the domain entities and their use in the real world. For example, architectural applications deal with objects and entities such as spaces, walls, and windows. A natural way of representing these architectural entities is provided by frames. This research explores the potential of using the expert system shell CLIPS, developed by NASA, to implement a frame-based representation that can accommodate architectural knowledge. These frames are similar but quite different from the 'template' construct in version 4.3 of CLIPS. Templates support only the grouping of related information and the assignment of default values to template fields. In addition to these features frames provide other capabilities including definition of classes, inheritance between classes and subclasses, relation of objects of different classes with 'has-a', association of methods (demons) of different types (standard and user-defined) to fields (slots), and creation of new fields at run-time. This frame-based representation is implemented completely in CLIPS. No change to the source code is necessary.

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

2016-11-01

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.

The interfacial pH of acidic degradable polymeric biomaterials and its effects on osteoblast behavior.

PubMed

Ruan, Changshun; Hu, Nan; Ma, Yufei; Li, Yuxiao; Liu, Juan; Zhang, Xinzhou; Pan, Haobo

2017-07-28

A weak alkaline environment is established to facilitate the growth of osteoblasts. Unfortunately, this is inconsistent with the application of biodegradable polymer in bone regeneration, as the degradation products are usually acidic. In this study, the variation of the interfacial pH of poly (D, L-lactide) and piperazine-based polyurethane ureas (P-PUUs), as the representations of acidic degradable materials, and the behavior of osteoblasts on these substrates with tunable interfacial pH were investigated in vitro. These results revealed that the release of degraded products caused a rapid decrease in the interfacial pH, and this could be relieved by the introduction of alkaline segments. On the contrary, when culturing with osteoblasts, the variation of the interfacial pH revealed an upward tendency, indicating that cell could construct the microenvironment by secreting cellular metabolites to satisfy its own survival. In addition, the behavior of osteoblasts on substrates exhibited that P-PUUs with the most PP units were better for cell growth and osteogenic differentiation of cells. This is due to the hydrophilic surface and the moderate N% in P-PUUs, key factors in the promotion of the early stages of cellular responses, and the interfacial pH contributing to the enhanced effect on osteogenic differentiation.

Classifying Membrane Proteins in the Proteome by Using Artificial Neural Networks Based on the Preferential Parameters of Amino Acids

NASA Astrophysics Data System (ADS)

Bose, Subrata K.; Browne, Antony; Kazemian, Hassan; White, Kenneth

Membrane proteins (MPs) are large set of biological macromolecules that play a fundamental role in physiology and pathophysiology for survival. From a pharma-economical perspective, though it is the fact that MPs constitute ˜75% of possible targets for novel drugs but MPs are one of the most understudied groups of proteins in biochemical research. This is mainly because of the technical difficulties of obtaining structural information about trans-membrane regions (these are small sequences that crossways the bilayer lipid membrane). It is quite useful to predict the location of transmembrane segments down the sequence, since these are the elementary structural building blocks defining their topology. There have been several attempts over the last 20 years to develop tools for predicting membrane-spanning regions but current tools are far away from achieving a considerable reliability in prediction. This study aims to exploit the knowledge and current understanding in the field of artificial neural networks (ANNs) in particular data representation through the development of a system to identify and predict membrane-spanning regions by analysing primary amino acids sequence. In this paper we present a novel neural network (NNs) architecture and algorithms for predicting membrane spanning regions from primary amino acids sequences by using their preference parameters.

Multi-voxel patterns of visual category representation during episodic encoding are predictive of subsequent memory

PubMed Central

Kuhl, Brice A.; Rissman, Jesse; Wagner, Anthony D.

2012-01-01

Successful encoding of episodic memories is thought to depend on contributions from prefrontal and temporal lobe structures. Neural processes that contribute to successful encoding have been extensively explored through univariate analyses of neuroimaging data that compare mean activity levels elicited during the encoding of events that are subsequently remembered vs. those subsequently forgotten. Here, we applied pattern classification to fMRI data to assess the degree to which distributed patterns of activity within prefrontal and temporal lobe structures elicited during the encoding of word-image pairs were diagnostic of the visual category (Face or Scene) of the encoded image. We then assessed whether representation of category information was predictive of subsequent memory. Classification analyses indicated that temporal lobe structures contained information robustly diagnostic of visual category. Information in prefrontal cortex was less diagnostic of visual category, but was nonetheless associated with highly reliable classifier-based evidence for category representation. Critically, trials associated with greater classifier-based estimates of category representation in temporal and prefrontal regions were associated with a higher probability of subsequent remembering. Finally, consideration of trial-by-trial variance in classifier-based measures of category representation revealed positive correlations between prefrontal and temporal lobe representations, with the strength of these correlations varying as a function of the category of image being encoded. Together, these results indicate that multi-voxel representations of encoded information can provide unique insights into how visual experiences are transformed into episodic memories. PMID:21925190

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

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

PubMed Central

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

2007-01-01

Background 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. Results 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 . 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 significantly improves on the standard one-vs-all method for both the superfamily and fold prediction in the remote homology setting and on the fold recognition problem. Moreover, our code weight learning algorithm strongly outperforms nearest-neighbor methods based on PSI-BLAST in terms of prediction accuracy on every structure classification problem we consider. Conclusion By combining state-of-the-art SVM kernel methods with a novel multi-class algorithm, the SVM-Fold system delivers efficient and accurate protein fold and superfamily recognition. PMID:17570145

Bag of Lines (BoL) for Improved Aerial Scene Representation

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

Sridharan, Harini; Cheriyadat, Anil M.

2014-09-22

Feature representation is a key step in automated visual content interpretation. In this letter, we present a robust feature representation technique, referred to as bag of lines (BoL), for high-resolution aerial scenes. The proposed technique involves extracting and compactly representing low-level line primitives from the scene. The compact scene representation is generated by counting the different types of lines representing various linear structures in the scene. Through extensive experiments, we show that the proposed scene representation is invariant to scale changes and scene conditions and can discriminate urban scene categories accurately. We compare the BoL representation with the popular scalemore » invariant feature transform (SIFT) and Gabor wavelets for their classification and clustering performance on an aerial scene database consisting of images acquired by sensors with different spatial resolutions. The proposed BoL representation outperforms the SIFT- and Gabor-based representations.« less

Rubber airplane: Constraint-based component-modeling for knowledge representation in computer-aided conceptual design

NASA Technical Reports Server (NTRS)

Kolb, Mark A.

1990-01-01

Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.

Family cumulative risk and at-risk kindergarteners' social competence: the mediating role of parent representations of the attachment relationship.

PubMed

Sparks, Lauren A; Trentacosta, Christopher J; Owusu, Erika; McLear, Caitlin; Smith-Darden, Joanne

2018-08-01

Secure attachment relationships have been linked to social competence in at-risk children. In the current study, we examined the role of parent secure base scripts in predicting at-risk kindergarteners' social competence. Parent representations of secure attachment were hypothesized to mediate the relationship between lower family cumulative risk and children's social competence. Participants included 106 kindergarteners and their primary caregivers recruited from three urban charter schools serving low-income families as a part of a longitudinal study. Lower levels of cumulative risk predicted greater secure attachment representations in parents, and scores on the secure base script assessment predicted children's social competence. An indirect relationship between lower cumulative risk and kindergarteners' social competence via parent secure base script scores was also supported. Parent script-based representations of the attachment relationship appear to be an important link between lower levels of cumulative risk and low-income kindergarteners' social competence. Implications of these findings for future interventions are discussed.

A comparison of certain extracting agents for extraction of adenosine triphosphate (ATP) from microorganisms for use in the firefly luciferase ATP assay

NASA Technical Reports Server (NTRS)

Knust, E. A.; Chappelle, E. W.; Picciolo, G. L.

1975-01-01

Firefly luciferase ATP assay is used in clinical and industrial applications, such as determination of urinary infection levels, microbial susceptibility testing, and monitoring of yeast levels in beverages. Three categories of extractants were investigated for their extracting efficiency. They were ionizing organic solvents, nonionizing organic solvents, and inorganic acids. Dimethylsulfoxide and formamide represented the ionizing organic solvents, while n-butanol, chloroform, ethanol, acetone, and methylene chloride were used for the nonionizing organic solvents. Nitric acid and perchloric acid were chosen for the inorganic acids category. Pathogens were tested with each solvent. They included: Saccharomyces carlsbergensis, E. coli, Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter species, Proteus mirabilis, Proteus vulgaris, Staphylococcus epidermidis, Streptococcus faecalis, Pseudomonas aeruginosa, and Candida albicans. These results are shown in graphic representations.

Jaccard distance based weighted sparse representation for coarse-to-fine plant species recognition.

PubMed

Zhang, Shanwen; Wu, Xiaowei; You, Zhuhong

2017-01-01

Leaf based plant species recognition plays an important role in ecological protection, however its application to large and modern leaf databases has been a long-standing obstacle due to the computational cost and feasibility. Recognizing such limitations, we propose a Jaccard distance based sparse representation (JDSR) method which adopts a two-stage, coarse to fine strategy for plant species recognition. In the first stage, we use the Jaccard distance between the test sample and each training sample to coarsely determine the candidate classes of the test sample. The second stage includes a Jaccard distance based weighted sparse representation based classification(WSRC), which aims to approximately represent the test sample in the training space, and classify it by the approximation residuals. Since the training model of our JDSR method involves much fewer but more informative representatives, this method is expected to overcome the limitation of high computational and memory costs in traditional sparse representation based classification. Comparative experimental results on a public leaf image database demonstrate that the proposed method outperforms other existing feature extraction and SRC based plant recognition methods in terms of both accuracy and computational speed.

Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

PubMed Central

Serrano, Miguel Ángel; Gómez-Romero, Juan; Patricio, Miguel Ángel; García, Jesús; Molina, José Manuel

2012-01-01

Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI) environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors' knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP) application for the elaboration of live market researches.

First-Principles pH Theory

NASA Astrophysics Data System (ADS)

Kim, Yong-Hyun; Zhang, S. B.

2006-03-01

Despite being one of the most important macroscopic measures and a long history even before the quantum mechanics, the concept of pH has rarely been mentioned in microscopic theories, nor being incorporated computationally into first-principles theory of aqueous solutions. Here, we formulate a theory for the pH dependence of solution formation energy by introducing the proton chemical potential as the microscopic counterpart of pH in atomistic solution models. Within the theory, the general acid-base chemistry can be cast in a simple pictorial representation. We adopt density-functional molecular dynamics to demonstrate the usefulness of the method by studying a number of solution systems including water, small solute molecules such as NH3 and HCOOH, and more complex amino acids with several functional groups. For pure water, we calculated the auto- ionization constant to be 13.2 with a 95 % accuracy. For other solutes, the calculated dissociation constants, i.e., the so- called pKa, are also in reasonable agreement with experiments. Our first-principles pH theory can be readily applied to broad solution chemistry problems such as redox reactions.

Hypergravity exposure decreases gamma-aminobutyric acid immunoreactivity in axon terminals contacting pyramidal cells in the rat somatosensory cortex: a quantitative immunocytochemical image analysis

NASA Technical Reports Server (NTRS)

D'Amelio, F.; Wu, L. C.; Fox, R. A.; Daunton, N. G.; Corcoran, M. L.; Polyakov, I.

1998-01-01

Quantitative evaluation of gamma-aminobutyric acid immunoreactivity (GABA-IR) in the hindlimb representation of the rat somatosensory cortex after 14 days of exposure to hypergravity (hyper-G) was conducted by using computer-assisted image processing. The area of GABA-IR axosomatic terminals apposed to pyramidal cells of cortical layer V was reduced in rats exposed to hyper-G compared with control rats, which were exposed either to rotation alone or to vivarium conditions. Based on previous immunocytochemical and behavioral studies, we suggest that this reduction is due to changes in sensory feedback information from muscle receptors. Consequently, priorities for muscle recruitment are altered at the cortical level, and a new pattern of muscle activity is thus generated. It is proposed that the reduction observed in GABA-IR of the terminal area around pyramidal neurons is the immunocytochemical expression of changes in the activity of GABAergic cells that participate in reprogramming motor outputs to achieve effective movement control in response to alterations in the afferent information.

Visualising substrate-fingermark interactions: Solid-state NMR spectroscopy of amino acid reagent development on cellulose substrates.

PubMed

Spindler, Xanthe; Shimmon, Ronald; Roux, Claude; Lennard, Chris

2015-05-01

Most spectroscopic studies of the reaction products formed by ninhydrin, 1,2-indanedione-zinc (Ind-Zn) and 1,8-diazafluoren-9-one (DFO) when reacted with amino acids or latent fingermarks on paper substrates are focused on visible absorption or luminescence spectroscopy. In addition, structural elucidation studies are typically limited to solution-based mass spectrometry or liquid nuclear magnetic resonance (NMR) spectroscopy, which does not provide an accurate representation of the fingermark development process on common paper substrates. The research presented in this article demonstrates that solid-state carbon-13 magic angle spinning NMR ((13)C-MAS-NMR) is a technique that can not only be utilised for structural studies of fingermark enhancement reagents, but is a promising technique for characterising the effect of paper chemistry on fingermark deposition and enhancement. The latter opens up a research area that has been under-explored to date but has the potential to improve our understanding of how fingermark secretions and enhancement reagents interact with paper substrates. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Kernel analysis of partial least squares (PLS) regression models.

PubMed

Shinzawa, Hideyuki; Ritthiruangdej, Pitiporn; Ozaki, Yukihiro

2011-05-01

An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA). Thus, it becomes possible to establish the proper interpretation of the scores. A PLS model for the total nitrogen (TN) content in multiple Thai fish sauces is built with a set of near-infrared (NIR) transmittance spectra of the fish sauce samples. The kernel analysis of the scores effectively reveals that the variation of the spectral feature induced by the change in protein content is substantially associated with the total water content and the protein hydration. Kernel analysis is also carried out on a set of time-dependent infrared (IR) spectra representing transient evaporation of ethanol from a binary mixture solution of ethanol and oleic acid. A PLS model to predict the elapsed time is built with the IR spectra and the kernel matrix is derived from the scores. The detailed analysis of the kernel matrix provides penetrating insight into the interaction between the ethanol and the oleic acid.

[Visual representation of natural scenes in flicker changes].

PubMed

Nakashima, Ryoichi; Yokosawa, Kazuhiko

2010-08-01

Coherence theory in scene perception (Rensink, 2002) assumes the retention of volatile object representations on which attention is not focused. On the other hand, visual memory theory in scene perception (Hollingworth & Henderson, 2002) assumes that robust object representations are retained. In this study, we hypothesized that the difference between these two theories is derived from the difference of the experimental tasks that they are based on. In order to verify this hypothesis, we examined the properties of visual representation by using a change detection and memory task in a flicker paradigm. We measured the representations when participants were instructed to search for a change in a scene, and compared them with the intentional memory representations. The visual representations were retained in visual long-term memory even in the flicker paradigm, and were as robust as the intentional memory representations. However, the results indicate that the representations are unavailable for explicitly localizing a scene change, but are available for answering the recognition test. This suggests that coherence theory and visual memory theory are compatible.

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

Operator assistant systems - An experimental approach using a telerobotics application

NASA Technical Reports Server (NTRS)

Boy, Guy A.; Mathe, Nathalie

1993-01-01

This article presents a knowledge-based system methodology for developing operator assistant (OA) systems in dynamic and interactive environments. This is a problem both of training and design, which is the subject of this article. Design includes both design of the system to be controlled and design of procedures for operating this system. A specific knowledge representation is proposed for representing the corresponding system and operational knowledge. This representation is based on the situation recognition and analytical reasoning paradigm. It tries to make explicit common factors involved in both human and machine intelligence, including perception and reasoning. An OA system based on this representation has been developed for space telerobotics. Simulations have been carried out with astronauts and the resulting protocols have been analyzed. Results show the relevance of the approach and have been used for improving the knowledge representation and the OA architecture.

Communication: Multiple-property-based diabatization for open-shell van der Waals molecules

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

Karman, Tijs; Avoird, Ad van der; Groenenboom, Gerrit C., E-mail: gerritg@theochem.ru.nl

2016-03-28

We derive a new multiple-property-based diabatization algorithm. The transformation between adiabatic and diabatic representations is determined by requiring a set of properties in both representations to be related by a similarity transformation. This set of properties is determined in the adiabatic representation by rigorous electronic structure calculations. In the diabatic representation, the same properties are determined using model diabatic states defined as products of undistorted monomer wave functions. This diabatic model is generally applicable to van der Waals molecules in arbitrary electronic states. Application to locating seams of conical intersections and collisional transfer of electronic excitation energy is demonstrated formore » O{sub 2} − O{sub 2} in low-lying excited states. Property-based diabatization for this test system included all components of the electric quadrupole tensor, orbital angular momentum, and spin-orbit coupling.« less

Exploiting salient semantic analysis for information retrieval

NASA Astrophysics Data System (ADS)

Luo, Jing; Meng, Bo; Quan, Changqin; Tu, Xinhui

2016-11-01

Recently, many Wikipedia-based methods have been proposed to improve the performance of different natural language processing (NLP) tasks, such as semantic relatedness computation, text classification and information retrieval. Among these methods, salient semantic analysis (SSA) has been proven to be an effective way to generate conceptual representation for words or documents. However, its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use SSA to improve the information retrieval performance, and propose a SSA-based retrieval method under the language model framework. First, SSA model is adopted to build conceptual representations for documents and queries. Then, these conceptual representations and the bag-of-words (BOW) representations can be used in combination to estimate the language models of queries and documents. The proposed method is evaluated on several standard text retrieval conference (TREC) collections. Experiment results on standard TREC collections show the proposed models consistently outperform the existing Wikipedia-based retrieval methods.

Orienting Attention to Sound Object Representations Attenuates Change Deafness

ERIC Educational Resources Information Center

Backer, Kristina C.; Alain, Claude

2012-01-01

According to the object-based account of attention, multiple objects coexist in short-term memory (STM), and we can selectively attend to a particular object of interest. Although there is evidence that attention can be directed to visual object representations, the assumption that attention can be oriented to sound object representations has yet…

Gender Difference in the Use of Thought Representation--A Corpus-Based Study

ERIC Educational Resources Information Center

Riissanen, Anne; Watson, Greg

2014-01-01

This study (Note 1) investigates potential differences in language use between genders, by applying a modified model of thought representation. Our hypothesis is that women use more direct forms of thought representation than men in modern spoken British English. Women are said to favour "private speech" that creates intimacy and…

Age-Related Declines in the Fidelity of Newly Acquired Category Representations

ERIC Educational Resources Information Center

Davis, Tyler; Love, Bradley C.; Maddox, W. Todd

2012-01-01

We present a theory suggesting that the ability to build category representations that reflect the nuances of category structures in the environment depends upon clustering mechanisms instantiated in an MTL-PFC-based circuit. Because function in this circuit declines with age, we predict that the ability to build category representations will be…

Classification of Chemical Substances Using Particulate Representations of Matter: An Analysis of Student Thinking

ERIC Educational Resources Information Center

Stains, Marilyne; Talanquer, Vicente

2007-01-01

We applied a mixed-method research design to investigate the patterns of reasoning used by novice undergraduate chemistry students to classify chemical substances as elements, compounds, or mixtures based on their particulate representations. We were interested in the identification of the representational features that students use to build a…

The Use of Digitized Images in Developing Software for Young Children.

ERIC Educational Resources Information Center

Wright, June L.

1992-01-01

Parents and children interacted with computer-based representations of a park, one with animated picture graphics and one with digitized full motion video. Children who interacted with the digitized representation replayed the program more and showed a stronger cognitive focus on the representation than did the other children. (LB)

Research-Based Worksheets on Using Multiple Representations in Science Classrooms

ERIC Educational Resources Information Center

Hill, Matthew; Sharma, Manjula

2015-01-01

The ability to represent the world like a scientist is difficult to teach; it is more than simply knowing the representations (e.g., graphs, words, equations and diagrams). For meaningful science learning to take place, consideration needs to be given to explicitly integrating representations into instructional methods, linked to the content, and…

Teaching Equivalent Fractions to Secondary Students with Disabilities via the Virtual-Representational-Abstract Instructional Sequence

ERIC Educational Resources Information Center

Bouck, Emily C.; Bassette, Laura; Shurr, Jordan; Park, Jiyoon; Kerr, Jackie; Whorley, Abbie

2017-01-01

Fractions are an important mathematical concept; however, fractions are also a struggle for many students with disabilities. This study explored a new framework adapted from the evidence-based concrete-representational-abstract framework: the virtual-representational-abstract (VRA) framework. The VRA framework involves teaching students to solve…

Using Theory of Mind to Promote Conceptual Change in Science

ERIC Educational Resources Information Center

Kyriakopoulou, Natassa; Vosniadou, Stella

2014-01-01

We argue that learning science requires children to move from perceptually based representations to more abstract conceptual representations and to understand that appearance may sometimes deceive us and that the same phenomenon in the world can have more than one representation when seen from different perspectives. We also argue that the…

The Changing Role of Students' Representation in Poland: An Historical Appraisal

ERIC Educational Resources Information Center

Antonowicz, Dominik; Pinheiro, Rómulo; Smuzewska, Marcelina

2014-01-01

Student representation in Poland has a relatively short but turbulent history. This article offers an historical appraisal of the development of student representation at the national level in the context of rapid and deep structural changes in Polish higher education. Based on a desktop analysis of official documentation, legislation, ideological…

Representation learning via Dual-Autoencoder for recommendation.

PubMed

Zhuang, Fuzhen; Zhang, Zhiqiang; Qian, Mingda; Shi, Chuan; Xie, Xing; He, Qing

2017-06-01

Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e.g., social relationships of users and items' attributions, to improve the recommendation performance under the matrix factorization framework. However, matrix factorization methods may not make full use of the limited information from rating or check-in matrices, and achieve unsatisfying results. Recently, deep learning has proven able to learn good representation in natural language processing, image classification, and so on. Along this line, we propose a new representation learning framework called Recommendation via Dual-Autoencoder (ReDa). In this framework, we simultaneously learn the new hidden representations of users and items using autoencoders, and minimize the deviations of training data by the learnt representations of users and items. Based on this framework, we develop a gradient descent method to learn hidden representations. Extensive experiments conducted on several real-world data sets demonstrate the effectiveness of our proposed method compared with state-of-the-art matrix factorization based methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

NASA Astrophysics Data System (ADS)

Yanti, Y. R.; Amin, S. M.; Sulaiman, R.

2018-01-01

This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.

Decoding the dynamic representation of musical pitch from human brain activity.

PubMed

Sankaran, N; Thompson, W F; Carlile, S; Carlson, T A

2018-01-16

In music, the perception of pitch is governed largely by its tonal function given the preceding harmonic structure of the music. While behavioral research has advanced our understanding of the perceptual representation of musical pitch, relatively little is known about its representational structure in the brain. Using Magnetoencephalography (MEG), we recorded evoked neural responses to different tones presented within a tonal context. Multivariate Pattern Analysis (MVPA) was applied to "decode" the stimulus that listeners heard based on the underlying neural activity. We then characterized the structure of the brain's representation using decoding accuracy as a proxy for representational distance, and compared this structure to several well established perceptual and acoustic models. The observed neural representation was best accounted for by a model based on the Standard Tonal Hierarchy, whereby differences in the neural encoding of musical pitches correspond to their differences in perceived stability. By confirming that perceptual differences honor those in the underlying neuronal population coding, our results provide a crucial link in understanding the cognitive foundations of musical pitch across psychological and neural domains.

The Digital electronic Guideline Library (DeGeL): a hybrid framework for representation and use of clinical guidelines.

PubMed

Shahar, Yuval; Young, Ohad; Shalom, Erez; Mayaffit, Alon; Moskovitch, Robert; Hessing, Alon; Galperin, Maya

2004-01-01

We propose to present a poster (and potentially also a demonstration of the implemented system) summarizing the current state of our work on a hybrid, multiple-format representation of clinical guidelines that facilitates conversion of guidelines from free text to a formal representation. We describe a distributed Web-based architecture (DeGeL) and a set of tools using the hybrid representation. The tools enable performing tasks such as guideline specification, semantic markup, search, retrieval, visualization, eligibility determination, runtime application and retrospective quality assessment. The representation includes four parallel formats: Free text (one or more original sources); semistructured text (labeled by the target guideline-ontology semantic labels); semiformal text (which includes some control specification); and a formal, machine-executable representation. The specification, indexing, search, retrieval, and browsing tools are essentially independent of the ontology chosen for guideline representation, but editing the semi-formal and formal formats requires ontology-specific tools, which we have developed in the case of the Asbru guideline-specification language. The four formats support increasingly sophisticated computational tasks. The hybrid guidelines are stored in a Web-based library. All tools, such as for runtime guideline application or retrospective quality assessment, are designed to operate on all representations. We demonstrate the hybrid framework by providing examples from the semantic markup and search tools.

Drug related webpages classification using images and text information based on multi-kernel learning

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Xiao, Liping; Zheng, Wenjuan

2015-12-01

In this paper, multi-kernel learning(MKL) is used for drug-related webpages classification. First, body text and image-label text are extracted through HTML parsing, and valid images are chosen by the FOCARSS algorithm. Second, text based BOW model is used to generate text representation, and image-based BOW model is used to generate images representation. Last, text and images representation are fused with a few methods. Experimental results demonstrate that the classification accuracy of MKL is higher than those of all other fusion methods in decision level and feature level, and much higher than the accuracy of single-modal classification.

Single-chain-in-mean-field simulations of weak polyelectrolyte brushes

NASA Astrophysics Data System (ADS)

Léonforte, F.; Welling, U.; Müller, M.

2016-12-01

Structural properties of brushes which are composed of weak acidic and basic polyelectrolytes are studied in the framework of a particle-based approach that implicitly accounts for the solvent quality. Using a semi-grandcanonical partition function in the framework of the Single-Chain-in-Mean-Field (SCMF) algorithm, the weak polyelectrolyte is conceived as a supramolecular mixture of polymers in different dissociation states, which are explicitly treated in the partition function and sampled by the SCMF procedure. One obtains a local expression for the equilibrium acid-base reaction responsible for the regulation of the charged groups that is also incorporated to the SCMF sampling. Coupled to a simultaneous treatment of the electrostatics, the approach is shown to capture the main features of weak polyelectrolyte brushes as a function of the bulk pH in the solution, the salt concentration, and the grafting density. Results are compared to experimental and theoretical works from the literature using coarse-grained representations of poly(acrylic acid) (PAA) and poly(2-vinyl pyridine) (P2VP) polymer-based brushes. As the Born self-energy of ions can be straightforwardly included in the numerical approach, we also study its effect on the local charge regulation mechanism of the brush. We find that its effect becomes significant when the brush is dense and exposed to high salt concentrations. The numerical methodology is then applied (1) to the study of the kinetics of collapse/swelling of a P2VP brush and (2) to the ability of an applied voltage to induce collapse/swelling of a PAA brush in a pH range close to the pKa value of the polymer.

Taking representation seriously: rethinking bioethics through Clint Eastwood's Million Dollar Baby.

PubMed

Braswell, Harold

2011-06-01

In this article, I propose a new model for understanding the function of representation in bioethics. Bioethicists have traditionally judged representations according to a mimetic paradigm, in which representations of bioethical dilemmas are assessed based on their correspondence to the "reality" of bioethics itself. In this article, I argue that this mimetic paradigm obscures the interaction between representation and reality and diverts bioethicists from analyzing the tensions in the representational object itself. I propose an anti-mimetic model of representation that is attuned to how representations can both maintain and potentially subvert dominant conceptions of bioethics. I illustrate this model through a case study of Clint Eastwood's film Million Dollar Baby. By focusing attention on the film's lack of adherence bioethical procedures and medical science, critics missed how an analysis of its representational logic provides a means of reimagining both bioethics and medical practice. In my conclusion, I build off this case study to assess how an incorporation of representational studies can deepen-and be deepened by-recent calls for interdisciplinarity in bioethics.

Supporting Representational Competence in High School Biology with Computer-Based Biomolecular Visualizations

ERIC Educational Resources Information Center

Wilder, Anna; Brinkerhoff, Jonathan

2007-01-01

This study assessed the effectiveness of computer-based biomolecular visualization activities on the development of high school biology students' representational competence as a means of understanding and visualizing protein structure/function relationships. Also assessed were students' attitudes toward these activities. Sixty-nine students…

Phonology, reading, and Chomsky and Halle's optimal orthography.

PubMed

Steinberg, D D

1973-09-01

Chomsky and Halle claim that an orthography based on their underlying phonological representations (UPR) of lexical items would be optimal for English. This paper challenges three of C & H's basic phonological assumptions, that their vowel shift rule is valid, that the UPR is the only sound representation to be listed in the lexicon, and that derived words do not appear as wholes in the lexicon. A less abstract phonological representation level based on the conscious perceptions of speakers, the surface phonemic (SPR), is proposed. An SPR-based orthography has advantages which a UPR-based orthography would not: it is easy to learn and teach, it can be learned at an early age, and it permits rapid detection of rhyme. It is concluded that an orthography based on SPRs, and not UPRs, would be optimal.

PREDICT: Pattern Representation and Evaluation of Data Through Integration, Correlation and Transformation

DTIC Science & Technology

2015-02-01

SB, Helbok R, et al. Cerebral perfusion pressure thresholds for brain tissue hypoxia and metabolic crisis after poor-grade subarachnoid hemorrhage...for future work. ALARMSMONITORINGDETAILED STATUS HOME Dove, J Doe, Joe Johnson, P. Myers, S Palli, H.Doe, E WBC Platelet Creatinine Lactic Acid AST

Perceiving fingers in single-digit arithmetic problems.

PubMed

Berteletti, Ilaria; Booth, James R

2015-01-01

In this study, we investigate in children the neural underpinnings of finger representation and finger movement involved in single-digit arithmetic problems. Evidence suggests that finger representation and finger-based strategies play an important role in learning and understanding arithmetic. Because different operations rely on different networks, we compared activation for subtraction and multiplication problems in independently localized finger somatosensory and motor areas and tested whether activation was related to skill. Brain activations from children between 8 and 13 years of age revealed that only subtraction problems significantly activated finger motor areas, suggesting reliance on finger-based strategies. In addition, larger subtraction problems yielded greater somatosensory activation than smaller problems, suggesting a greater reliance on finger representation for larger numerical values. Interestingly, better performance in subtraction problems was associated with lower activation in the finger somatosensory area. Our results support the importance of fine-grained finger representation in arithmetical skill and are the first neurological evidence for a functional role of the somatosensory finger area in proficient arithmetical problem solving, in particular for those problems requiring quantity manipulation. From an educational perspective, these results encourage investigating whether different finger-based strategies facilitate arithmetical understanding and encourage educational practices aiming at integrating finger representation and finger-based strategies as a tool for instilling stronger numerical sense.

Perceiving fingers in single-digit arithmetic problems

PubMed Central

Berteletti, Ilaria; Booth, James R.

2015-01-01

In this study, we investigate in children the neural underpinnings of finger representation and finger movement involved in single-digit arithmetic problems. Evidence suggests that finger representation and finger-based strategies play an important role in learning and understanding arithmetic. Because different operations rely on different networks, we compared activation for subtraction and multiplication problems in independently localized finger somatosensory and motor areas and tested whether activation was related to skill. Brain activations from children between 8 and 13 years of age revealed that only subtraction problems significantly activated finger motor areas, suggesting reliance on finger-based strategies. In addition, larger subtraction problems yielded greater somatosensory activation than smaller problems, suggesting a greater reliance on finger representation for larger numerical values. Interestingly, better performance in subtraction problems was associated with lower activation in the finger somatosensory area. Our results support the importance of fine-grained finger representation in arithmetical skill and are the first neurological evidence for a functional role of the somatosensory finger area in proficient arithmetical problem solving, in particular for those problems requiring quantity manipulation. From an educational perspective, these results encourage investigating whether different finger-based strategies facilitate arithmetical understanding and encourage educational practices aiming at integrating finger representation and finger-based strategies as a tool for instilling stronger numerical sense. PMID:25852582

Locality constrained joint dynamic sparse representation for local matching based face recognition.

PubMed

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

COM3/369: Knowledge-based Information Systems: A new approach for the representation and retrieval of medical information

PubMed Central

Mann, G; Birkmann, C; Schmidt, T; Schaeffler, V

1999-01-01

Introduction Present solutions for the representation and retrieval of medical information from online sources are not very satisfying. Either the retrieval process lacks of precision and completeness the representation does not support the update and maintenance of the represented information. Most efforts are currently put into improving the combination of search engines and HTML based documents. However, due to the current shortcomings of methods for natural language understanding there are clear limitations to this approach. Furthermore, this approach does not solve the maintenance problem. At least medical information exceeding a certain complexity seems to afford approaches that rely on structured knowledge representation and corresponding retrieval mechanisms. Methods Knowledge-based information systems are based on the following fundamental ideas. The representation of information is based on ontologies that define the structure of the domain's concepts and their relations. Views on domain models are defined and represented as retrieval schemata. Retrieval schemata can be interpreted as canonical query types focussing on specific aspects of the provided information (e.g. diagnosis or therapy centred views). Based on these retrieval schemata it can be decided which parts of the information in the domain model must be represented explicitly and formalised to support the retrieval process. As representation language propositional logic is used. All other information can be represented in a structured but informal way using text, images etc. Layout schemata are used to assign layout information to retrieved domain concepts. Depending on the target environment HTML or XML can be used. Results Based on this approach two knowledge-based information systems have been developed. The 'Ophthalmologic Knowledge-based Information System for Diabetic Retinopathy' (OKIS-DR) provides information on diagnoses, findings, examinations, guidelines, and reference images related to diabetic retinopathy. OKIS-DR uses combinations of findings to specify the information that must be retrieved. The second system focuses on nutrition related allergies and intolerances. Information on allergies and intolerances of a patient are used to retrieve general information on the specified combination of allergies and intolerances. As a special feature the system generates tables showing food types and products that are tolerated or not tolerated by patients. Evaluation by external experts and user groups showed that the described approach of knowledge-based information systems increases the precision and completeness of knowledge retrieval. Due to the structured and non-redundant representation of information the maintenance and update of the information can be simplified. Both systems are available as WWW based online knowledge bases and CD-ROMs (cf. http://mta.gsf.de topic: products).

Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection.

PubMed

Peer, Xavier; An, Gary

2014-10-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the C. difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, fecal microbial transplant. The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine.

Agent-based model of Fecal Microbial Transplant effect on Bile Acid Metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection

PubMed Central

Peer, Xavier; An, Gary

2014-01-01

Agent-based modeling is a computational modeling method that represents system-level behavior as arising from multiple interactions between the multiple components that make up a system. Biological systems are thus readily described using agent-based models (ABMs), as multi-cellular organisms can be viewed as populations of interacting cells, and microbial systems manifest as colonies of individual microbes. Intersections between these two domains underlie an increasing number of pathophysiological processes, and the intestinal tract represents one of the most significant locations for these inter-domain interactions, so much so that it can be considered an internal ecology of varying robustness and function. Intestinal infections represent significant disturbances of this internal ecology, and one of the most clinically relevant intestinal infections is Clostridium difficile infection (CDI). CDI is precipitated by the use of broad-spectrum antibiotics, involves the depletion of commensal microbiota, and alterations in bile acid composition in the intestinal lumen. We present an example ABM of CDI (the Clostridium difficile Infection ABM, or CDIABM) to examine fundamental dynamics of the pathogenesis of CDI and its response to treatment with anti-CDI antibiotics and a newer treatment therapy, Fecal Microbial Transplant (FMT). The CDIABM focuses on one specific mechanism of potential CDI suppression: commensal modulation of bile acid composition. Even given its abstraction, the CDIABM reproduces essential dynamics of CDI and its response to therapy, and identifies a paradoxical zone of behavior that provides insight into the role of intestinal nutritional status and the efficacy of anti-CDI therapies. It is hoped that this use case example of the CDIABM can demonstrate the usefulness of both agent-based modeling and the application of abstract functional representation as the biomedical community seeks to address the challenges of increasingly complex diseases with the goal of personalized medicine. PMID:25168489

Instruction-Based Clinical Eye-Tracking Study on the Visual Interpretation of Divergence: How Do Students Look at Vector Field Plots?

ERIC Educational Resources Information Center

Klein, P.; Viiri, J.; Mozaffari, S.; Dengel, A.; Kuhn, J.

2018-01-01

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux…

Profile of biology prospective teachers’ representation on plant anatomy learning

NASA Astrophysics Data System (ADS)

Ermayanti; Susanti, R.; Anwar, Y.

2018-04-01

This study aims to obtaining students’ representation ability in understanding the structure and function of plant tissues in plant anatomy course. Thirty students of The Biology Education Department of Sriwijaya University were involved in this study. Data on representation ability were collected using test and observation. The instruments had been validated by expert judgment. Test scores were used to represent students’ ability in 4 categories: 2D-image, 3D-image, spatial, and verbal representations. The results show that students’ representation ability is still low: 2D-image (40.0), 3D-image (25.0), spatial (20.0), and verbal representation (45.0). Based on the results of this study, it is suggested that instructional strategies be developed for plant anatomy course.

Three 3D graphical representations of DNA primary sequences based on the classifications of DNA bases and their applications.

PubMed

Xie, Guosen; Mo, Zhongxi

2011-01-21

In this article, we introduce three 3D graphical representations of DNA primary sequences, which we call RY-curve, MK-curve and SW-curve, based on three classifications of the DNA bases. The advantages of our representations are that (i) these 3D curves are strictly non-degenerate and there is no loss of information when transferring a DNA sequence to its mathematical representation and (ii) the coordinates of every node on these 3D curves have clear biological implication. Two applications of these 3D curves are presented: (a) a simple formula is derived to calculate the content of the four bases (A, G, C and T) from the coordinates of nodes on the curves; and (b) a 12-component characteristic vector is constructed to compare similarity among DNA sequences from different species based on the geometrical centers of the 3D curves. As examples, we examine similarity among the coding sequences of the first exon of beta-globin gene from eleven species and validate similarity of cDNA sequences of beta-globin gene from eight species. Copyright © 2010 Elsevier Ltd. All rights reserved.

Students' Construction of External Representations in Design-Based Learning Situations

ERIC Educational Resources Information Center

de Vries, Erica

2006-01-01

This article develops a theoretical framework for the study of students' construction of mixed multiple external representations in design-based learning situations involving an adaptation of professional tasks and tools to a classroom setting. The framework draws on research on professional design processes and on learning with multiple external…

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

How to make a good animation: A grounded cognition model of how visual representation design affects the construction of abstract physics knowledge

NASA Astrophysics Data System (ADS)

Chen, Zhongzhou; Gladding, Gary

2014-06-01

Visual representations play a critical role in teaching physics. However, since we do not have a satisfactory understanding of how visual perception impacts the construction of abstract knowledge, most visual representations used in instructions are either created based on existing conventions or designed according to the instructor's intuition, which leads to a significant variance in their effectiveness. In this paper we propose a cognitive mechanism based on grounded cognition, suggesting that visual perception affects understanding by activating "perceptual symbols": the basic cognitive unit used by the brain to construct a concept. A good visual representation activates perceptual symbols that are essential for the construction of the represented concept, whereas a bad representation does the opposite. As a proof of concept, we conducted a clinical experiment in which participants received three different versions of a multimedia tutorial teaching the integral expression of electric potential. The three versions were only different by the details of the visual representation design, only one of which contained perceptual features that activate perceptual symbols essential for constructing the idea of "accumulation." On a following post-test, participants receiving this version of tutorial significantly outperformed those who received the other two versions of tutorials designed to mimic conventional visual representations used in classrooms.

What recent research on diagrams suggests about learning with rather than learning from visual representations in science

NASA Astrophysics Data System (ADS)

Tippett, Christine D.

2016-03-01

The move from learning science from representations to learning science with representations has many potential and undocumented complexities. This thematic analysis partially explores the trends of representational uses in science instruction, examining 80 research studies on diagram use in science. These studies, published during 2000-2014, were located through searches of journal databases and books. Open coding of the studies identified 13 themes, 6 of which were identified in at least 10% of the studies: eliciting mental models, classroom-based research, multimedia principles, teaching and learning strategies, representational competence, and student agency. A shift in emphasis on learning with rather than learning from representations was evident across the three 5-year intervals considered, mirroring a pedagogical shift from science instruction as transmission of information to constructivist approaches in which learners actively negotiate understanding and construct knowledge. The themes and topics in recent research highlight areas of active interest and reveal gaps that may prove fruitful for further research, including classroom-based studies, the role of prior knowledge, and the use of eye-tracking. The results of the research included in this thematic review of the 2000-2014 literature suggest that both interpreting and constructing representations can lead to better understanding of science concepts.

Knowledge-base browsing: an application of hybrid distributed/local connectionist networks

NASA Astrophysics Data System (ADS)

Samad, Tariq; Israel, Peggy

1990-08-01

We describe a knowledge base browser based on a connectionist (or neural network) architecture that employs both distributed and local representations. The distributed representations are used for input and output thereby enabling associative noise-tolerant interaction with the environment. Internally all representations are fully local. This simplifies weight assignment and facilitates network configuration for specific applications. In our browser concepts and relations in a knowledge base are represented using " microfeatures. " The microfeatures can encode semantic attributes structural features contextual information etc. Desired portions of the knowledge base can then be associatively retrieved based on a structured cue. An ordered list of partial matches is presented to the user for selection. Microfeatures can also be used as " bookmarks" they can be placed dynamically at appropriate points in the knowledge base and subsequently used as retrieval cues. A proof-of-concept system has been implemented for an internally developed Honeywell-proprietary knowledge acquisition tool. 1.

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

Hologram representation of design data in an expert system knowledge base

NASA Technical Reports Server (NTRS)

Shiva, S. G.; Klon, Peter F.

1988-01-01

A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

Evidence for highly selective neuronal tuning to whole words in the "visual word form area".

PubMed

Glezer, Laurie S; Jiang, Xiong; Riesenhuber, Maximilian

2009-04-30

Theories of reading have posited the existence of a neural representation coding for whole real words (i.e., an orthographic lexicon), but experimental support for such a representation has proved elusive. Using fMRI rapid adaptation techniques, we provide evidence that the human left ventral occipitotemporal cortex (specifically the "visual word form area," VWFA) contains a representation based on neurons highly selective for individual real words, in contrast to current theories that posit a sublexical representation in the VWFA.

Combinatorial Labeling Method for Improving Peptide Fragmentation in Mass Spectrometry

NASA Astrophysics Data System (ADS)

Kuchibhotla, Bhanuramanand; Kola, Sankara Rao; Medicherla, Jagannadham V.; Cherukuvada, Swamy V.; Dhople, Vishnu M.; Nalam, Madhusudhana Rao

2017-06-01

Annotation of peptide sequence from tandem mass spectra constitutes the central step of mass spectrometry-based proteomics. Peptide mass spectra are obtained upon gas-phase fragmentation. Identification of the protein from a set of experimental peptide spectral matches is usually referred as protein inference. Occurrence and intensity of these fragment ions in the MS/MS spectra are dependent on many factors such as amino acid composition, peptide basicity, activation mode, protease, etc. Particularly, chemical derivatizations of peptides were known to alter their fragmentation. In this study, the influence of acetylation, guanidinylation, and their combination on peptide fragmentation was assessed initially on a lipase (LipA) from Bacillus subtilis followed by a bovine six protein mix digest. The dual modification resulted in improved fragment ion occurrence and intensity changes, and this resulted in the equivalent representation of b- and y-type fragment ions in an ion trap MS/MS spectrum. The improved representation has allowed us to accurately annotate the peptide sequences de novo. Dual labeling has significantly reduced the false positive protein identifications in standard bovine six peptide digest. Our study suggests that the combinatorial labeling of peptides is a useful method to validate protein identifications for high confidence protein inference. [Figure not available: see fulltext.

Soft Wall Ion Channel in Continuum Representation with Application to Modeling Ion Currents in α-Hemolysin

PubMed Central

Simakov, Nikolay A.

2010-01-01

A soft repulsion (SR) model of short range interactions between mobile ions and protein atoms is introduced in the framework of continuum representation of the protein and solvent. The Poisson-Nernst-Plank (PNP) theory of ion transport through biological channels is modified to incorporate this soft wall protein model. Two sets of SR parameters are introduced: the first is parameterized for all essential amino acid residues using all atom molecular dynamic simulations; the second is a truncated Lennard – Jones potential. We have further designed an energy based algorithm for the determination of the ion accessible volume, which is appropriate for a particular system discretization. The effects of these models of short-range interaction were tested by computing current-voltage characteristics of the α-hemolysin channel. The introduced SR potentials significantly improve prediction of channel selectivity. In addition, we studied the effect of choice of some space-dependent diffusion coefficient distributions on the predicted current-voltage properties. We conclude that the diffusion coefficient distributions largely affect total currents and have little effect on rectifications, selectivity or reversal potential. The PNP-SR algorithm is implemented in a new efficient parallel Poisson, Poisson-Boltzman and PNP equation solver, also incorporated in a graphical molecular modeling package HARLEM. PMID:21028776

Computation of the Genetic Code

NASA Astrophysics Data System (ADS)

Kozlov, Nicolay N.; Kozlova, Olga N.

2018-03-01

One of the problems in the development of mathematical theory of the genetic code (summary is presented in [1], the detailed -to [2]) is the problem of the calculation of the genetic code. Similar problems in the world is unknown and could be delivered only in the 21st century. One approach to solving this problem is devoted to this work. For the first time provides a detailed description of the method of calculation of the genetic code, the idea of which was first published earlier [3]), and the choice of one of the most important sets for the calculation was based on an article [4]. Such a set of amino acid corresponds to a complete set of representations of the plurality of overlapping triple gene belonging to the same DNA strand. A separate issue was the initial point, triggering an iterative search process all codes submitted by the initial data. Mathematical analysis has shown that the said set contains some ambiguities, which have been founded because of our proposed compressed representation of the set. As a result, the developed method of calculation was limited to the two main stages of research, where the first stage only the of the area were used in the calculations. The proposed approach will significantly reduce the amount of computations at each step in this complex discrete structure.

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Improving the learning of clinical reasoning through computer-based cognitive representation

PubMed Central

Wu, Bian; Wang, Minhong; Johnson, Janice M.; Grotzer, Tina A.

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Surface similarity-based molecular query-retrieval

PubMed Central

Singh, Rahul

2007-01-01

Background Discerning the similarity between molecules is a challenging problem in drug discovery as well as in molecular biology. The importance of this problem is due to the fact that the biochemical characteristics of a molecule are closely related to its structure. Therefore molecular similarity is a key notion in investigations targeting exploration of molecular structural space, query-retrieval in molecular databases, and structure-activity modelling. Determining molecular similarity is related to the choice of molecular representation. Currently, representations with high descriptive power and physical relevance like 3D surface-based descriptors are available. Information from such representations is both surface-based and volumetric. However, most techniques for determining molecular similarity tend to focus on idealized 2D graph-based descriptors due to the complexity that accompanies reasoning with more elaborate representations. Results This paper addresses the problem of determining similarity when molecules are described using complex surface-based representations. It proposes an intrinsic, spherical representation that systematically maps points on a molecular surface to points on a standard coordinate system (a sphere). Molecular surface properties such as shape, field strengths, and effects due to field super-positioningcan then be captured as distributions on the surface of the sphere. Surface-based molecular similarity is subsequently determined by computing the similarity of the surface-property distributions using a novel formulation of histogram-intersection. The similarity formulation is not only sensitive to the 3D distribution of the surface properties, but is also highly efficient to compute. Conclusion The proposed method obviates the computationally expensive step of molecular pose-optimisation, can incorporate conformational variations, and facilitates highly efficient determination of similarity by directly comparing molecular surfaces and surface-based properties. Retrieval performance, applications in structure-activity modeling of complex biological properties, and comparisons with existing research and commercial methods demonstrate the validity and effectiveness of the approach. PMID:17634096

Characterizing and Supporting Change in Algebra Students' Representational Fluency in a CAS/Paper-and-Pencil Environment

ERIC Educational Resources Information Center

Fonger, Nicole L.

2012-01-01

Representational fluency (RF) includes an ability to interpret, create, move within and among, and connect tool-based representations of mathematical objects. Taken as an indicator of conceptual understanding, there is a need to better support school algebra students' RF in learning environments that utilize both computer algebra systems…

Development of an Instrument to Evaluate High School Students' Chemical Symbol Representation Abilities

ERIC Educational Resources Information Center

Wang, Zuhao; Chi, Shaohui; Luo, Ma; Yang, Yuqin; Huang, Min

2017-01-01

Chemical symbol representation is a medium for transformations between the actual phenomena of the macroscopic world and those of the sub-microscopic world. The aim of this study is to develop an instrument to evaluate high school students' chemical symbol representation abilities (CSRA). Based on the current literature, we defined CSRA and…

Role of Mental Representations in Problem Solving: Students' Approaches to Nondirected Tasks

ERIC Educational Resources Information Center

Ibrahim, Bashirah; Rebello, N. Sanjay

2013-01-01

In this paper, we report on a project concerned with the role of cognition during problem solving. We specifically explore the categories of mental representations that students work with during problem solving of different representational task formats. The sample, consisting of 19 engineering students taking a calculus-based physics course,…

Social Representations of the Development of Intelligence, Parental Values and Parenting Styles: A Theoretical Model for Analysis

ERIC Educational Resources Information Center

Miguel, Isabel; Valentim, Joaquim Pires; Carugati, Felice

2013-01-01

Within the theoretical framework of social representations theory, a substantial body of literature has advocated and shown that, as interpretative systems and forms of knowledge concurring in the construction of a social reality, social representations are guides for action, influencing behaviours and social relations. Based on this assumption,…

Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort.

PubMed

Guell, Xavier; Gabrieli, John D E; Schmahmann, Jeremy D

2018-05-15

Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?). Copyright © 2018 Elsevier Inc. All rights reserved.

Method for making 2-electron response reduced density matrices approximately N-representable

NASA Astrophysics Data System (ADS)

Lanssens, Caitlin; Ayers, Paul W.; Van Neck, Dimitri; De Baerdemacker, Stijn; Gunst, Klaas; Bultinck, Patrick

2018-02-01

In methods like geminal-based approaches or coupled cluster that are solved using the projected Schrödinger equation, direct computation of the 2-electron reduced density matrix (2-RDM) is impractical and one falls back to a 2-RDM based on response theory. However, the 2-RDMs from response theory are not N-representable. That is, the response 2-RDM does not correspond to an actual physical N-electron wave function. We present a new algorithm for making these non-N-representable 2-RDMs approximately N-representable, i.e., it has the right symmetry and normalization and it fulfills the P-, Q-, and G-conditions. Next to an algorithm which can be applied to any 2-RDM, we have also developed a 2-RDM optimization procedure specifically for seniority-zero 2-RDMs. We aim to find the 2-RDM with the right properties which is the closest (in the sense of the Frobenius norm) to the non-N-representable 2-RDM by minimizing the square norm of the difference between this initial response 2-RDM and the targeted 2-RDM under the constraint that the trace is normalized and the 2-RDM, Q-matrix, and G-matrix are positive semidefinite, i.e., their eigenvalues are non-negative. Our method is suitable for fixing non-N-representable 2-RDMs which are close to being N-representable. Through the N-representability optimization algorithm we add a small correction to the initial 2-RDM such that it fulfills the most important N-representability conditions.

Object-based attention: strength of object representation and attentional guidance.

PubMed

Shomstein, Sarah; Behrmann, Marlene

2008-01-01

Two or more features belonging to a single object are identified more quickly and more accurately than are features belonging to different objects--a finding attributed to sensory enhancement of all features belonging to an attended or selected object. However, several recent studies have suggested that this "single-object advantage" may be a product of probabilistic and configural strategic prioritizations rather than of object-based perceptual enhancement per se, challenging the underlying mechanism that is thought to give rise to object-based attention. In the present article, we further explore constraints on the mechanisms of object-based selection by examining the contribution of the strength of object representations to the single-object advantage. We manipulated factors such as exposure duration (i.e., preview time) and salience of configuration (i.e., objects). Varying preview time changes the magnitude of the object-based effect, so that if there is ample time to establish an object representation (i.e., preview time of 1,000 msec), then both probability and configuration (i.e., objects) guide attentional selection. If, however, insufficient time is provided to establish a robust object-based representation, then only probabilities guide attentional selection. Interestingly, at a short preview time of 200 msec, when the two objects were sufficiently different from each other (i.e., different colors), both configuration and probability guided attention selection. These results suggest that object-based effects can be explained both in terms of strength of object representations (established at longer exposure durations and by pictorial cues) and probabilistic contingencies in the visual environment.

An XML Representation for Crew Procedures

NASA Technical Reports Server (NTRS)

Simpson, Richard C.

2005-01-01

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other activities start and stop), but do not capture the flow of data, materials, resources or priorities. Existing workflow representation languages are also limited to representing sequences of discrete activities, and cannot encode procedures involving continuous flow of information or materials between activities.

Characterizing representational learning: A combined simulation and tutorial on perturbation theory

NASA Astrophysics Data System (ADS)

Kohnle, Antje; Passante, Gina

2017-12-01

Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence") is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

A ganglion-cell-based primary image representation method and its contribution to object recognition

NASA Astrophysics Data System (ADS)

Wei, Hui; Dai, Zhi-Long; Zuo, Qing-Song

2016-10-01

A visual stimulus is represented by the biological visual system at several levels: in the order from low to high levels, they are: photoreceptor cells, ganglion cells (GCs), lateral geniculate nucleus cells and visual cortical neurons. Retinal GCs at the early level need to represent raw data only once, but meet a wide number of diverse requests from different vision-based tasks. This means the information representation at this level is general and not task-specific. Neurobiological findings have attributed this universal adaptation to GCs' receptive field (RF) mechanisms. For the purposes of developing a highly efficient image representation method that can facilitate information processing and interpretation at later stages, here we design a computational model to simulate the GC's non-classical RF. This new image presentation method can extract major structural features from raw data, and is consistent with other statistical measures of the image. Based on the new representation, the performances of other state-of-the-art algorithms in contour detection and segmentation can be upgraded remarkably. This work concludes that applying sophisticated representation schema at early state is an efficient and promising strategy in visual information processing.

Representation and visualization of variability in a 3D anatomical atlas using the kidney as an example

NASA Astrophysics Data System (ADS)

Hacker, Silke; Handels, Heinz

2006-03-01

Computer-based 3D atlases allow an interactive exploration of the human body. However, in most cases such 3D atlases are derived from one single individual, and therefore do not regard the variability of anatomical structures concerning their shape and size. Since the geometric variability across humans plays an important role in many medical applications, our goal is to develop a framework of an anatomical atlas for representation and visualization of the variability of selected anatomical structures. The basis of the project presented is the VOXEL-MAN atlas of inner organs that was created from the Visible Human data set. For modeling anatomical shapes and their variability we utilize "m-reps" which allow a compact representation of anatomical objects on the basis of their skeletons. As an example we used a statistical model of the kidney that is based on 48 different variants. With the integration of a shape description into the VOXEL-MAN atlas it is now possible to query and visualize different shape variations of an organ, e.g. by specifying a person's age or gender. In addition to the representation of individual shape variants, the average shape of a population can be displayed. Besides a surface representation, a volume-based representation of the kidney's shape variants is also possible. It results from the deformation of the reference kidney of the volume-based model using the m-rep shape description. In this way a realistic visualization of the shape variants becomes possible, as well as the visualization of the organ's internal structures.

Communication systems, transceivers, and methods for generating data based on channel characteristics

DOEpatents

Forman, Michael A; Young, Derek

2012-09-18

Examples of methods for generating data based on a communications channel are described. In one such example, a processing unit may generate a first vector representation based in part on at least two characteristics of a communications channel. A constellation having at least two dimensions may be addressed with the first vector representation to identify a first symbol associated with the first vector representation. The constellation represents a plurality of regions, each region associated with a respective symbol. The symbol may be used to generate data, which may stored in an electronic storage medium and used as a cryptographic key or a spreading code or hopping sequence in a modulation technique.

Attention During Natural Vision Warps Semantic Representation Across the Human Brain

PubMed Central

Çukur, Tolga; Nishimoto, Shinji; Huth, Alexander G.; Gallant, Jack L.

2013-01-01

Little is known about how attention changes the cortical representation of sensory information in humans. Based on neurophysiological evidence, we hypothesized that attention causes tuning changes to expand the representation of attended stimuli at the cost of unattended stimuli. To investigate this issue we used functional MRI (fMRI) to measure how semantic representation changes when searching for different object categories in natural movies. We find that many voxels across occipito-temporal and fronto-parietal cortex shift their tuning toward the attended category. These tuning shifts expand the representation of the attended category and of semantically-related but unattended categories, and compress the representation of categories semantically-dissimilar to the target. Attentional warping of semantic representation occurs even when the attended category is not present in the movie, thus the effect is not a target-detection artifact. These results suggest that attention dynamically alters visual representation to optimize processing of behaviorally relevant objects during natural vision. PMID:23603707

Spatially variant morphological restoration and skeleton representation.

PubMed

Bouaynaya, Nidhal; Charif-Chefchaouni, Mohammed; Schonfeld, Dan

2006-11-01

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

Specialized Representations of Value in the Orbital and Ventrolateral Prefrontal Cortex: Desirability versus Availability of Outcomes.

PubMed

Rudebeck, Peter H; Saunders, Richard C; Lundgren, Dawn A; Murray, Elisabeth A

2017-08-30

Advantageous foraging choices benefit from an estimation of two aspects of a resource's value: its current desirability and availability. Both orbitofrontal and ventrolateral prefrontal areas contribute to updating these valuations, but their precise roles remain unclear. To explore their specializations, we trained macaque monkeys on two tasks: one required updating representations of a predicted outcome's desirability, as adjusted by selective satiation, and the other required updating representations of an outcome's availability, as indexed by its probability. We evaluated performance on both tasks in three groups of monkeys: unoperated controls and those with selective, fiber-sparing lesions of either the OFC or VLPFC. Representations that depend on the VLPFC but not the OFC play a necessary role in choices based on outcome availability; in contrast, representations that depend on the OFC but not the VLPFC play a necessary role in choices based on outcome desirability. Copyright © 2017 Elsevier Inc. All rights reserved.

Illusions of having small or large invisible bodies influence visual perception of object size

PubMed Central

van der Hoort, Björn; Ehrsson, H. Henrik

2016-01-01

The size of our body influences the perceived size of the world so that objects appear larger to children than to adults. The mechanisms underlying this effect remain unclear. It has been difficult to dissociate visual rescaling of the external environment based on an individual’s visible body from visual rescaling based on a central multisensory body representation. To differentiate these potential causal mechanisms, we manipulated body representation without a visible body by taking advantage of recent developments in body representation research. Participants experienced the illusion of having a small or large invisible body while object-size perception was tested. Our findings show that the perceived size of test-objects was determined by the size of the invisible body (inverse relation), and by the strength of the invisible body illusion. These findings demonstrate how central body representation directly influences visual size perception, without the need for a visible body, by rescaling the spatial representation of the environment. PMID:27708344

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

Ramkumar, Barathram; Sabarimalai Manikandan, M.

2017-01-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Growth Points in Linking Representations of Function: A Research-Based Framework

ERIC Educational Resources Information Center

Ronda, Erlina

2015-01-01

This paper describes five growth points in linking representations of function developed from a study of secondary school learners. Framed within the cognitivist perspective and process-object conception of function, the growth points were identified and described based on linear and quadratic function tasks learners can do and their strategies…

Demonstration of the lack of cytotoxicity of unmodified and folic acid modified graphene oxide quantum dots, and their application to fluorescence lifetime imaging of HaCaT cells.

PubMed

Goreham, Renee V; Schroeder, Kathryn L; Holmes, Amy; Bradley, Siobhan J; Nann, Thomas

2018-01-24

The authors describe the synthesis of water-soluble and fluorescent graphene oxide quantum dots via acid exfoliation of graphite nanoparticles. The resultant graphene oxide quantum dots (GoQDs) were then modified with folic acid. Folic acid receptors are overexpressed in cancer cells and hence can bind to functionalized graphene oxide quantum dots. On excitation at 305 nm, the GoQDs display green fluorescence with a peak wavelength at ~520 nm. The modified GoQDs are non-toxic to macrophage cells even after prolonged exposure and high concentrations. Fluorescence lifetime imaging and multiphoton microscopy was used (in combination) to image HeCaT cells exposed to GoQDs, resulting in a superior method for bioimaging. Graphical abstract Schematic representation of graphene oxide quantum dots, folic acid modified graphene oxide quantum dots (red), and the use of fluorescence lifetime to discriminate against green auto-fluorescence of HeCaT cells.

How to Make a Good Animation: A Grounded Cognition Model of How Visual Representation Design Affects the Construction of Abstract Physics Knowledge

ERIC Educational Resources Information Center

Chen, Zhongzhou; Gladding, Gary

2014-01-01

Visual representations play a critical role in teaching physics. However, since we do not have a satisfactory understanding of how visual perception impacts the construction of abstract knowledge, most visual representations used in instructions are either created based on existing conventions or designed according to the instructor's intuition,…

The Effects of Self-Explanation and Metacognitive Instruction on Undergraduate Students' Learning of Statistics Materials Containing Multiple External Representations in a Web-Based Environment

ERIC Educational Resources Information Center

Hsu, Yu-Chang

2009-01-01

Students in the Science, Technology, Engineering, and Mathematics (STEM) fields are confronted with multiple external representations (MERs) in their learning materials. The ability to learn from and communicate with these MERs requires not only that students comprehend each representation individually but also that students recognize how the…

Gendered Family Lives through the Eyes of Young People: Diversity, Permanence and Change of Gender Representations in Portugal

ERIC Educational Resources Information Center

das Dores Guerreiro, Maria; Caetano, Ana; Rodrigues, Eduardo

2014-01-01

This article examines gender representations of family and parental roles among young people aged 11 to 14 years. It is based on the qualitative analysis of 792 essays written by Portuguese girls and boys attending compulsory education. The adolescents' texts express normative images and cultural representations about gender that are plural and…

Symbolic and Verbal Representation Process of Student in Solving Mathematics Problem Based Polya's Stages

ERIC Educational Resources Information Center

Anwar, Rahmad Bustanul; Rahmawati, Dwi

2017-01-01

The purpose of this research was to reveal how the construction process of symbolic representation and verbal representation made by students in problem solving. The construction process in this study referred to the problem-solving stage by Polya covering; 1) understanding the problem, 2) devising a plan, 3) carrying out the plan, and 4) looking…

Representations of Shape in Object Recognition and Long-Term Visual Memory

DTIC Science & Technology

1993-02-11

in anything other than linguistic terms ( Biederman , 1987 , for example). STATUS 1. Viewpoint-Dependent Features in Object Representation Tarr and...is object- based orientation-independent representations sufficient for "basic-level" categorization ( Biederman , 1987 ; Corballis, 1988). Alternatively...space. REFERENCES Biederman , I. ( 1987 ). Recognition-by-components: A theory of human image understanding. Psychological Review, 94,115-147. Cooper, L

Importance of perceptual representation in the visual control of action

NASA Astrophysics Data System (ADS)

Loomis, Jack M.; Beall, Andrew C.; Kelly, Jonathan W.; Macuga, Kristen L.

2005-03-01

In recent years, many experiments have demonstrated that optic flow is sufficient for visually controlled action, with the suggestion that perceptual representations of 3-D space are superfluous. In contrast, recent research in our lab indicates that some visually controlled actions, including some thought to be based on optic flow, are indeed mediated by perceptual representations. For example, we have demonstrated that people are able to perform complex spatial behaviors, like walking, driving, and object interception, in virtual environments which are rendered visible solely by cyclopean stimulation (random-dot cinematograms). In such situations, the absence of any retinal optic flow that is correlated with the objects and surfaces within the virtual environment means that people are using stereo-based perceptual representations to perform the behavior. The fact that people can perform such behaviors without training suggests that the perceptual representations are likely the same as those used when retinal optic flow is present. Other research indicates that optic flow, whether retinal or a more abstract property of the perceptual representation, is not the basis for postural control, because postural instability is related to perceived relative motion between self and the visual surroundings rather than to optic flow, even in the abstract sense.

Dissociations of the number and precision of visual short-term memory representations in change detection.

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

The present study dissociated the number (i.e., quantity) and precision (i.e., quality) of visual short-term memory (STM) representations in change detection using receiver operating characteristic (ROC) and experimental manipulations. Across three experiments, participants performed both recognition and recall tests of visual STM using the change-detection task and the continuous color-wheel recall task, respectively. Experiment 1 demonstrated that the estimates of the number and precision of visual STM representations based on the ROC model of change-detection performance were robustly correlated with the corresponding estimates based on the mixture model of continuous-recall performance. Experiments 2 and 3 showed that the experimental manipulation of mnemonic precision using white-noise masking and the experimental manipulation of the number of encoded STM representations using consolidation masking produced selective effects on the corresponding measures of mnemonic precision and the number of encoded STM representations, respectively, in both change-detection and continuous-recall tasks. Altogether, using the individual-differences (Experiment 1) and experimental dissociation (Experiment 2 and 3) approaches, the present study demonstrated the some-or-none nature of visual STM representations across recall and recognition.

Visual Tracking Based on Extreme Learning Machine and Sparse Representation

PubMed Central

Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

2015-01-01

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359

Representation and alignment of sung queries for music information retrieval

NASA Astrophysics Data System (ADS)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

Asymmetric translation between multiple representations in chemistry

NASA Astrophysics Data System (ADS)

Lin, Yulan I.; Son, Ji Y.; Rudd, James A., II

2016-03-01

Experts are more proficient in manipulating and translating between multiple representations (MRs) of a given concept than novices. Studies have shown that instruction using MR can increase student understanding of MR, and one model for MR instruction in chemistry is the chemistry triplet proposed by Johnstone. Concreteness fading theory suggests that presenting concrete representations before abstract representations can increase the effectiveness of MR instruction; however, little work has been conducted on varying the order of different representations during instruction and the role of concreteness in assessment. In this study, we investigated the application of concreteness fading to MR instruction and assessment in teaching chemistry. In two experiments, undergraduate students in either introductory psychology courses or general chemistry courses were given MR instruction on phase changes using different orders of presentation and MR assessment questions based on the representations in the chemistry triplet. Our findings indicate that the order of presentation based on levels of concreteness in MR chemistry instruction is less important than implementation of comprehensive MR assessments. Even after MR instruction, students display an asymmetric understanding of the chemical phenomenon on the MR assessments. Greater emphasis on MR assessments may be an important component in MR instruction that effectively moves novices toward more expert MR understanding.

The effect of training methodology on knowledge representation in categorization.

PubMed

Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W

2017-01-01

Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.

The effect of training methodology on knowledge representation in categorization

PubMed Central

Shamloo, Farzin; Ell, Shawn W.

2017-01-01

Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule–based (RB) category structures thought to promote between–category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between–category representations whereas concept training resulted in a bias toward within–category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within–category representations. With II structures, there was a bias toward within–category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within–category representations could support generalization during the test phase. These data suggest that within–category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization. PMID:28846732

Use of vectors in sequence analysis.

PubMed

Ishikawa, T; Yamamoto, K; Yoshikura, H

1987-10-01

Applications of the vector diagram, a new type of representation of protein structure, in homology search of various proteins including oncogene products are presented. The method takes account of various kinds of information concerning the properties of amino acids, such as Chou and Fasman's probability data. The method can detect conformational similarities of proteins which may not be detected by the conventional programs.

Cortical Representations of Speech in a Multitalker Auditory Scene.

PubMed

Puvvada, Krishna C; Simon, Jonathan Z

2017-09-20

The ability to parse a complex auditory scene into perceptual objects is facilitated by a hierarchical auditory system. Successive stages in the hierarchy transform an auditory scene of multiple overlapping sources, from peripheral tonotopically based representations in the auditory nerve, into perceptually distinct auditory-object-based representations in the auditory cortex. Here, using magnetoencephalography recordings from men and women, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in distinct hierarchical stages of the auditory cortex. Using systems-theoretic methods of stimulus reconstruction, we show that the primary-like areas in the auditory cortex contain dominantly spectrotemporal-based representations of the entire auditory scene. Here, both attended and ignored speech streams are represented with almost equal fidelity, and a global representation of the full auditory scene with all its streams is a better candidate neural representation than that of individual streams being represented separately. We also show that higher-order auditory cortical areas, by contrast, represent the attended stream separately and with significantly higher fidelity than unattended streams. Furthermore, the unattended background streams are more faithfully represented as a single unsegregated background object rather than as separated objects. Together, these findings demonstrate the progression of the representations and processing of a complex acoustic scene up through the hierarchy of the human auditory cortex. SIGNIFICANCE STATEMENT Using magnetoencephalography recordings from human listeners in a simulated cocktail party environment, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in separate hierarchical stages of the auditory cortex. We show that the primary-like areas in the auditory cortex use a dominantly spectrotemporal-based representation of the entire auditory scene, with both attended and unattended speech streams represented with almost equal fidelity. We also show that higher-order auditory cortical areas, by contrast, represent an attended speech stream separately from, and with significantly higher fidelity than, unattended speech streams. Furthermore, the unattended background streams are represented as a single undivided background object rather than as distinct background objects. Copyright © 2017 the authors 0270-6474/17/379189-08$15.00/0.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

PubMed

Bastien, Olivier; Ortet, Philippe; Roy, Sylvaine; Maréchal, Eric

2005-03-10

Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

[Experiences of a mother of a Down syndrome child].

PubMed

Sigaud, C H; Reis, A O

1999-06-01

The present thesis was developed based on "The Social Representations Theory" and its purpose was to understand the mother's representation of the Down syndrome child. The subjects were nine mothers of Down syndrome patients between the ages of six and twelve, at a São Paulo specialized facility. The study material was obtained through semi-structured and individual interview, and examined by means of content analysis, particularly the thematic analysis. The results pointed to a maternal representation of the child with a predominance of negative components. Based on that perception the mother experienced ambivalent feelings and behaved in a overprotective way.

An Algebraic Approach to Guarantee Harmonic Balance Method Using Gröbner Base

NASA Astrophysics Data System (ADS)

Yagi, Masakazu; Hisakado, Takashi; Okumura, Kohshi

Harmonic balance (HB) method is well known principle for analyzing periodic oscillations on nonlinear networks and systems. Because the HB method has a truncation error, approximated solutions have been guaranteed by error bounds. However, its numerical computation is very time-consuming compared with solving the HB equation. This paper proposes an algebraic representation of the error bound using Gröbner base. The algebraic representation enables to decrease the computational cost of the error bound considerably. Moreover, using singular points of the algebraic representation, we can obtain accurate break points of the error bound by collisions.

Image fusion based on Bandelet and sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Jiuxing; Zhang, Wei; Li, Xuzhi

2018-04-01

Bandelet transform could acquire geometric regular direction and geometric flow, sparse representation could represent signals with as little as possible atoms on over-complete dictionary, both of which could be used to image fusion. Therefore, a new fusion method is proposed based on Bandelet and Sparse Representation, to fuse Bandelet coefficients of multi-source images and obtain high quality fusion effects. The test are performed on remote sensing images and simulated multi-focus images, experimental results show that the performance of new method is better than tested methods according to objective evaluation indexes and subjective visual effects.

Graph representation of hepatic vessel based on centerline extraction and junction detection

NASA Astrophysics Data System (ADS)

Zhang, Xing; Tian, Jie; Deng, Kexin; Li, Xiuli; Yang, Fei

2012-02-01

In the area of computer-aided diagnosis (CAD), segmentation and analysis of hepatic vessel is a prerequisite for hepatic diseases diagnosis and surgery planning. For liver surgery planning, it is crucial to provide the surgeon with a patient-individual three-dimensional representation of the liver along with its vasculature and lesions. The representation allows an exploration of the vascular anatomy and the measurement of vessel diameters, following by intra-patient registration, as well as the analysis of the shape and volume of vascular territories. In this paper, we present an approach for generation of hepatic vessel graph based on centerline extraction and junction detection. The proposed approach involves the following concepts and methods: 1) Flux driven automatic centerline extraction; 2) Junction detection on the centerline using hollow sphere filtering; 3) Graph representation of hepatic vessel based on the centerline and junction. The approach is evaluated on contrast-enhanced liver CT datasets to demonstrate its availability and effectiveness.

Automatic frame-centered object representation and integration revealed by iconic memory, visual priming, and backward masking.

PubMed

Lin, Zhicheng; He, Sheng

2012-10-25

Object identities ("what") and their spatial locations ("where") are processed in distinct pathways in the visual system, raising the question of how the what and where information is integrated. Because of object motions and eye movements, the retina-based representations are unstable, necessitating nonretinotopic representation and integration. A potential mechanism is to code and update objects according to their reference frames (i.e., frame-centered representation and integration). To isolate frame-centered processes, in a frame-to-frame apparent motion configuration, we (a) presented two preceding or trailing objects on the same frame, equidistant from the target on the other frame, to control for object-based (frame-based) effect and space-based effect, and (b) manipulated the target's relative location within its frame to probe frame-centered effect. We show that iconic memory, visual priming, and backward masking depend on objects' relative frame locations, orthogonal of the retinotopic coordinate. These findings not only reveal that iconic memory, visual priming, and backward masking can be nonretinotopic but also demonstrate that these processes are automatically constrained by contextual frames through a frame-centered mechanism. Thus, object representation is robustly and automatically coupled to its reference frame and continuously being updated through a frame-centered, location-specific mechanism. These findings lead to an object cabinet framework, in which objects ("files") within the reference frame ("cabinet") are orderly coded relative to the frame.

Medical Named Entity Recognition for Indonesian Language Using Word Representations

NASA Astrophysics Data System (ADS)

Rahman, Arief

2018-03-01

Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.

Intelligence with representation.

PubMed

Steels, Luc

2003-10-15

Behaviour-based robotics has always been inspired by earlier cybernetics work such as that of W. Grey Walter. It emphasizes that intelligence can be achieved without the kinds of representations common in symbolic AI systems. The paper argues that such representations might indeed not be needed for many aspects of sensory-motor intelligence but become a crucial issue when bootstrapping to higher levels of cognition. It proposes a scenario in the form of evolutionary language games by which embodied agents develop situated grounded representations adapted to their needs and the conventions emerging in the population.

Acute effects of alcohol on intrusive memory development and viewpoint dependence in spatial memory support a dual representation model.

PubMed

Bisby, James A; King, John A; Brewin, Chris R; Burgess, Neil; Curran, H Valerie

2010-08-01

A dual representation model of intrusive memory proposes that personally experienced events give rise to two types of representation: an image-based, egocentric representation based on sensory-perceptual features; and a more abstract, allocentric representation that incorporates spatiotemporal context. The model proposes that intrusions reflect involuntary reactivation of egocentric representations in the absence of a corresponding allocentric representation. We tested the model by investigating the effect of alcohol on intrusive memories and, concurrently, on egocentric and allocentric spatial memory. With a double-blind independent group design participants were administered alcohol (.4 or .8 g/kg) or placebo. A virtual environment was used to present objects and test recognition memory from the same viewpoint as presentation (tapping egocentric memory) or a shifted viewpoint (tapping allocentric memory). Participants were also exposed to a trauma video and required to detail intrusive memories for 7 days, after which explicit memory was assessed. There was a selective impairment of shifted-view recognition after the low dose of alcohol, whereas the high dose induced a global impairment in same-view and shifted-view conditions. Alcohol showed a dose-dependent inverted "U"-shaped effect on intrusions, with only the low dose increasing the number of intrusions, replicating previous work. When same-view recognition was intact, decrements in shifted-view recognition were associated with increases in intrusions. The differential effect of alcohol on intrusive memories and on same/shifted-view recognition support a dual representation model in which intrusions might reflect an imbalance between two types of memory representation. These findings highlight important clinical implications, given alcohol's involvement in real-life trauma. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Alternative transitions between existing representations in multi-scale maps

NASA Astrophysics Data System (ADS)

Dumont, Marion; Touya, Guillaume; Duchêne, Cécile

2018-05-01

Map users may have issues to achieve multi-scale navigation tasks, as cartographic objects may have various representations across scales. We assume that adding intermediate representations could be one way to reduce the differences between existing representations, and to ease the transitions across scales. We consider an existing multiscale map on the scale range from 1 : 25k to 1 : 100k scales. Based on hypotheses about intermediate representations design, we build custom multi-scale maps with alternative transitions. We will conduct in a next future a user evaluation to compare the efficiency of these alternative maps for multi-scale navigation. This paper discusses the hypotheses and production process of these alternative maps.

A large and ubiquitous source of atmospheric formic acid

NASA Astrophysics Data System (ADS)

Millet, D. B.; Baasandorj, M.; Farmer, D. K.; Thornton, J. A.; Baumann, K.; Brophy, P.; Chaliyakunnel, S.; de Gouw, J. A.; Graus, M.; Hu, L.; Koss, A.; Lee, B. H.; Lopez-Hilfiker, F. D.; Neuman, J. A.; Paulot, F.; Peischl, J.; Pollack, I. B.; Ryerson, T. B.; Warneke, C.; Williams, B. J.; Xu, J.

2015-06-01

Formic acid (HCOOH) is one of the most abundant acids in the atmosphere, with an important influence on precipitation chemistry and acidity. Here we employ a chemical transport model (GEOS-Chem CTM) to interpret recent airborne and ground-based measurements over the US Southeast in terms of the constraints they provide on HCOOH sources and sinks. Summertime boundary layer concentrations average several parts-per-billion, 2-3× larger than can be explained based on known production and loss pathways. This indicates one or more large missing HCOOH sources, and suggests either a key gap in current understanding of hydrocarbon oxidation or a large, unidentified, direct flux of HCOOH. Model-measurement comparisons implicate biogenic sources (e.g., isoprene oxidation) as the predominant HCOOH source. Resolving the unexplained boundary layer concentrations based (i) solely on isoprene oxidation would require a 3× increase in the model HCOOH yield, or (ii) solely on direct HCOOH emissions would require approximately a 25× increase in its biogenic flux. However, neither of these can explain the high HCOOH amounts seen in anthropogenic air masses and in the free troposphere. The overall indication is of a large biogenic source combined with ubiquitous chemical production of HCOOH across a range of precursors. Laboratory work is needed to better quantify the rates and mechanisms of carboxylic acid production from isoprene and other prevalent organics. Stabilized Criegee intermediates (SCIs) provide a large model source of HCOOH, while acetaldehyde tautomerization accounts for ~ 15% of the simulated global burden. Because carboxylic acids also react with SCIs and catalyze the reverse tautomerization reaction, HCOOH buffers against its own production by both of these pathways. Based on recent laboratory results, reaction between CH3O2 and OH could provide a major source of atmospheric HCOOH; however, including this chemistry degrades the model simulation of CH3OOH and NOx : CH3OOH. Developing better constraints on SCI and RO2 + OH chemistry is a high priority for future work. The model neither captures the large diurnal amplitude in HCOOH seen in surface air, nor its inverted vertical gradient at night. This implies a substantial bias in our current representation of deposition as modulated by boundary layer dynamics, and may indicate an HCOOH sink underestimate and thus an even larger missing source. A more robust treatment of surface deposition is a key need for improving simulations of HCOOH and related trace gases, and our understanding of their budgets.

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations

PubMed Central

Frappier, Vincent; Najmanovich, Rafael J.

2014-01-01

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cα−only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations. PMID:24762569

A Process-Based Model of TCA Cycle Functioning to Analyze Citrate Accumulation in Pre- and Post-Harvest Fruits.

PubMed

Etienne, Audrey; Génard, Michel; Bugaud, Christophe

2015-01-01

Citrate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. The regulation of citrate accumulation throughout fruit development, and the origins of the phenotypic variability of the citrate concentration within fruit species remain to be clarified. In the present study, we developed a process-based model of citrate accumulation based on a simplified representation of the TCA cycle to predict citrate concentration in fruit pulp during the pre- and post-harvest stages. Banana fruit was taken as a reference because it has the particularity of having post-harvest ripening, during which citrate concentration undergoes substantial changes. The model was calibrated and validated on the two stages, using data sets from three contrasting cultivars in terms of citrate accumulation, and incorporated different fruit load, potassium supply, and harvest dates. The model predicted the pre and post-harvest dynamics of citrate concentration with fairly good accuracy for the three cultivars. The model suggested major differences in TCA cycle functioning among cultivars during post-harvest ripening of banana, and pointed to a potential role for NAD-malic enzyme and mitochondrial malate carriers in the genotypic variability of citrate concentration. The sensitivity of citrate accumulation to growth parameters and temperature differed among cultivars during post-harvest ripening. Finally, the model can be used as a conceptual basis to study citrate accumulation in fleshy fruits and may be a powerful tool to improve our understanding of fruit acidity.

Social representations of biosecurity in nursing: occupational health and preventive care.

PubMed

Sousa, Álvaro Francisco Lopes de; Queiroz, Artur Acelino Francisco Luz Nunes; Oliveira, Layze Braz de; Moura, Maria Eliete Batista; Batista, Odinéa Maria Amorim; Andrade, Denise de

2016-01-01

to understand the biosecurity social representations by primary care nursing professionals and analyze how they articulate with quality of care. exploratory and qualitative research based on social representation theory. The study participants were 36 nursing workers from primary health care in a state capital in the Northeast region of Brazil. The data were analyzed by descending hierarchical classification. five classes were obtained: occupational accidents suffered by professionals; occupational exposure to biological agents; biosecurity management in primary health care; the importance of personal protective equipment; and infection control and biosecurity. the different positions taken by the professionals seem to be based on a field of social representations related to the concept of biosecurity, namely exposure to accidents and risks to which they are exposed. However, occupational accidents are reported as inherent to the practice.

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

A Knowledge-Based Approach to Language Production

DTIC Science & Technology

1985-08-01

representation -- the internal structures which the system is generating from. and (3) the choice problem -- how the intricate relationship between the...texts from several different internal representations. One example of the output produced by MUMBLE is the following text, produced from a...brackets. This notation is used to illustrate some templates which are encoded in Ace. The internal representation of these templates is achieved using

Representation in Memory.

DTIC Science & Technology

1983-06-07

siderably in the development of theories of representation in psychology and in artificial intelligence, most especially the requirements that a... developed representational systems based on these "larger" units. We will discuss three of them here: 0 A theory of schemata as developed by Rumelhart...and Ortony (1977) and extended by Rumelhart and Norman (1978) and Rumelhart (1981). A theory of scripts and plans developed by Schank and Abelson (1977

A symbolic shaped-based retrieval of skull images.

PubMed

Lin, H Jill; Ruiz-Correa, Salvador; Shapiro, Linda G; Cunningham, Michael L; Sze, Raymond W

2005-01-01

In this work, we describe a novel symbolic representation of shapes for quantifying skull abnormalities in children with craniosynostosis. We show the efficacy of our work by demonstrating an application of this representation in shape-based retrieval of skull morphologies. This tool will enable correlation with potential pathogenesis and prognosis in order to enhance medical care.

Teachers and Students' Conceptions of Computer-Based Models in the Context of High School Chemistry: Elicitations at the Pre-Intervention Stage

ERIC Educational Resources Information Center

Waight, Noemi; Gillmeister, Kristina

2014-01-01

This study examined teachers' and students' initial conceptions of computer-based models--Flash and NetLogo models--and documented how teachers and students reconciled notions of multiple representations featuring macroscopic, submicroscopic and symbolic representations prior to actual intervention in eight high school chemistry…

Is Mathematical Representation of Problems an Evidence-Based Strategy for Students with Mathematics Difficulties?

ERIC Educational Resources Information Center

Jitendra, Asha K.; Nelson, Gena; Pulles, Sandra M.; Kiss, Allyson J.; Houseworth, James

2016-01-01

The purpose of the present review was to evaluate the quality of the research and evidence base for representation of problems as a strategy to enhance the mathematical performance of students with learning disabilities and those at risk for mathematics difficulties. The authors evaluated 25 experimental and quasiexperimental studies according to…

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

OF THE PROBLEM AND CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0... DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 9 Figure 5: The flow of data in a DNA analysis system based on an...logarithmic scale and a linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proof-of-Concept Experiments.

DTIC Science & Technology

1992-05-01

DNA ANALYSIS STRATEGY 4 2.1 Representation of DNA Bases 4 2.2 DNA Analysis Strategy 6 3.0 CUSTOM GENERATORS FOR DNA SEQUENCES 10 3.1 Hardware Design 10...of the DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 5 Figure 4: Coarse analysis of a DNA sequence. 7 Figure 5: Fine...a 20-bases long database. 32 xiii LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits long

Assessing the response of Emerald Lake, an alpine watershed in Sequoia National Park, California, to acidification during snowmelt by using a simple hydrochemical model

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

Hooper, R.P.; West, C.T.; Peters, N.E.

1990-01-01

A sparsely parameterized hydrochemical model has been developed by using data from Emerald Lake watershed, which is a 120-ha alpine catchment in Sequoia National Park, California. Greater than 90% of the precipitation to this watershed is snow; hence, snowmelt is the dominant hydrologic event. A model which uses a single alkalinity-generating mechanism, primary mineral weathering, was able to capture the pattern of solute concentrations in surface waters during snowmelt. An empirical representation of the weathering reaction, which is based on rock weathering stoichiometry and which uses discharge as a measure of residence time, was included in the model. Results ofmore » the model indicate that current deposition levels would have to be increased between three-fold and eight-fold to exhaust the alkalinity of the lake during snowmelt if their is a mild acidic pulse in the stream at the beginning of snowmelt as was observed during the study period. The acidic pulse in the inflow stream at the onset of snowmelt was less pronounced than acidic pulses observed in the meltwater draining the snowpack at a point using snow lysimeters or in the laboratory. Sulfate concentrations in the stream water were the most constant; chloride and nitrate concentrations increased slightly at the beginning of snowmelt. Additional field work is required to resolve whether an acidic meltwater pulse occurs over a large area as well as at a point or whether, due to physical and chemical processes within the snowpack, the acidic meltwater pulse is attenuated at the catchment scale. The modest data requirements of the model permit its applications to other alpine watersheds that are much less intensively studied than Emerald Lake watershed.« less

Professional autonomy and nursing: representations of health professionals.

PubMed

Santos, Érick Igor Dos; Alves, Yasmin Rayanne; Silva, Aline Cerqueira Santos Santana da; Gomes, Antonio Marcos Tosoli

2017-05-18

To analyse the social representations of the professional autonomy of nurses and nursing for non-nursing health professionals. This is a qualitative study based on the theory of social representations. Fifty-three non-nursing professionals of a municipal hospital participated in this study. Data were collected between March and April 2015, from hierarchical free evocations using the inductor terms, "professional autonomy of nurses" and "nursing". The data were analysed using EVOC 2003. The most likely core of the social representation of professional autonomy were the terms care, team, and responsibility. Moreover, the likely core of nursing comprises the elements care, team, responsibility, and work. The professional autonomy of nurses and nursing consists of fairly close objects of representation in the studied group, which makes them non-autonomous representations that are still sensitive to the incorporation of new elements.

Qualitative aspects of representational competence among college chemistry students: Multiple representations and their role in the understanding of ideal gases

NASA Astrophysics Data System (ADS)

Madden, Sean Patrick

This study examined the role of multiple representations of chemical phenomena, specifically, the temperature-pressure relationship of ideal gases, in the problem solving strategies of college chemistry students. Volunteers included students enrolled in a first semester general chemistry course at a western university. Two additional volunteers from the same university were asked to participate and serve as models of greater sophistication. One was a senior chemistry major; another was a junior science writing major. Volunteers completed an initial screening task involving multiple representations of concentration and dilution concepts. Based on the results of this screening instrument a smaller set of subjects were asked to complete a think aloud session involving multiple representations of the temperature-pressure relationship. Data consisted of the written work of the volunteers and transcripts from videotaped think aloud sessions. The data were evaluated by the researcher and two other graduate students in chemical education using a coding scheme (Kozma, Schank, Coppola, Michalchik, and Allen. 2000). This coding scheme was designed to identify essential features of representational competence and differences in uses of multiple representations. The results indicate that students tend to have a strong preference for one type of representation. Students scoring low on representational competence, as measured by the rubric, ignored important features of some representations or acknowledged them only superficially. Students scoring higher on representational competence made meaningful connections among representations. The more advanced students, those who rated highly on representational competence, tended to use their preferred representation in a heuristic manner to establish meaning for other representations. The more advanced students also reflected upon the problem at greater length before beginning work. Molecular level sketches seemed to be the most difficult type of representation for students to interpret. Most subjects scored higher on representational competence when engaged in creating graphs and sketches than when evaluating provided representations. This study suggests that students may benefit from an instruction that emphasizes heuristic use of multiple representations in chemistry problem solving. An instructional strategy that makes use of a variety of representations and requires students to create their own representations may have measurable benefits to chemistry students.

Representational similarity analysis reveals commonalities and differences in the semantic processing of words and objects.

PubMed

Devereux, Barry J; Clarke, Alex; Marouchos, Andreas; Tyler, Lorraine K

2013-11-27

Understanding the meanings of words and objects requires the activation of underlying conceptual representations. Semantic representations are often assumed to be coded such that meaning is evoked regardless of the input modality. However, the extent to which meaning is coded in modality-independent or amodal systems remains controversial. We address this issue in a human fMRI study investigating the neural processing of concepts, presented separately as written words and pictures. Activation maps for each individual word and picture were used as input for searchlight-based multivoxel pattern analyses. Representational similarity analysis was used to identify regions correlating with low-level visual models of the words and objects and the semantic category structure common to both. Common semantic category effects for both modalities were found in a left-lateralized network, including left posterior middle temporal gyrus (LpMTG), left angular gyrus, and left intraparietal sulcus (LIPS), in addition to object- and word-specific semantic processing in ventral temporal cortex and more anterior MTG, respectively. To explore differences in representational content across regions and modalities, we developed novel data-driven analyses, based on k-means clustering of searchlight dissimilarity matrices and seeded correlation analysis. These revealed subtle differences in the representations in semantic-sensitive regions, with representations in LIPS being relatively invariant to stimulus modality and representations in LpMTG being uncorrelated across modality. These results suggest that, although both LpMTG and LIPS are involved in semantic processing, only the functional role of LIPS is the same regardless of the visual input, whereas the functional role of LpMTG differs for words and objects.

3D hierarchical spatial representation and memory of multimodal sensory data

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.

SIRE: A Simple Interactive Rule Editor for NICBES

NASA Technical Reports Server (NTRS)

Bykat, Alex

1988-01-01

To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.

Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

PubMed Central

Lv, Zhuowen; Xing, Xianglei; Wang, Kejun; Guan, Donghai

2015-01-01

Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach. PMID:25574935

EVALLER: a web server for in silico assessment of potential protein allergenicity

PubMed Central

Barrio, Alvaro Martinez; Soeria-Atmadja, Daniel; Nistér, Anders; Gustafsson, Mats G.; Hammerling, Ulf; Bongcam-Rudloff, Erik

2007-01-01

Bioinformatics testing approaches for protein allergenicity, involving amino acid sequence comparisons, have evolved appreciably over the last several years to increased sophistication and performance. EVALLER, the web server presented in this article is based on our recently published ‘Detection based on Filtered Length-adjusted Allergen Peptides’ (DFLAP) algorithm, which affords in silico determination of potential protein allergenicity of high sensitivity and excellent specificity. To strengthen bioinformatics risk assessment in allergology EVALLER provides a comprehensive outline of its judgment on a query protein's potential allergenicity. Each such textual output incorporates a scoring figure, a confidence numeral of the assignment and information on high- or low-scoring matches to identified allergen-related motifs, including their respective location in accordingly derived allergens. The interface, built on a modified Perl Open Source package, enables dynamic and color-coded graphic representation of key parts of the output. Moreover, pertinent details can be examined in great detail through zoomed views. The server can be accessed at http://bioinformatics.bmc.uu.se/evaller.html. PMID:17537818

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Embedded Data Representations.

PubMed

Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre

2017-01-01

We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion of physical data referents - the real-world entities and spaces to which data corresponds - and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded representations, which display data so that it spatially coincides with data referents. Drawing on examples from visualization, ubiquitous computing, and art, we explore the role of spatial indirection, scale, and interaction for embedded representations. We also examine the tradeoffs between non-situated, situated, and embedded data displays, including both visualizations and physicalizations. Based on our observations, we identify a variety of design challenges for embedded data representation, and suggest opportunities for future research and applications.

A Novel Locally Linear KNN Method With Applications to Visual Recognition.

PubMed

Liu, Qingfeng; Liu, Chengjun

2017-09-01

A locally linear K Nearest Neighbor (LLK) method is presented in this paper with applications to robust visual recognition. Specifically, the concept of an ideal representation is first presented, which improves upon the traditional sparse representation in many ways. The objective function based on a host of criteria for sparsity, locality, and reconstruction is then optimized to derive a novel representation, which is an approximation to the ideal representation. The novel representation is further processed by two classifiers, namely, an LLK-based classifier and a locally linear nearest mean-based classifier, for visual recognition. The proposed classifiers are shown to connect to the Bayes decision rule for minimum error. Additional new theoretical analysis is presented, such as the nonnegative constraint, the group regularization, and the computational efficiency of the proposed LLK method. New methods such as a shifted power transformation for improving reliability, a coefficients' truncating method for enhancing generalization, and an improved marginal Fisher analysis method for feature extraction are proposed to further improve visual recognition performance. Extensive experiments are implemented to evaluate the proposed LLK method for robust visual recognition. In particular, eight representative data sets are applied for assessing the performance of the LLK method for various visual recognition applications, such as action recognition, scene recognition, object recognition, and face recognition.

The Arabidopsis thaliana REDUCED EPIDERMAL FLUORESCENCE1 Gene Encodes an Aldehyde Dehydrogenase Involved in Ferulic Acid and Sinapic Acid Biosynthesis

PubMed Central

Nair, Ramesh B.; Bastress, Kristen L.; Ruegger, Max O.; Denault, Jeff W.; Chapple, Clint

2004-01-01

Recent research has significantly advanced our understanding of the phenylpropanoid pathway but has left in doubt the pathway by which sinapic acid is synthesized in plants. The reduced epidermal fluorescence1 (ref1) mutant of Arabidopsis thaliana accumulates only 10 to 30% of the sinapate esters found in wild-type plants. Positional cloning of the REF1 gene revealed that it encodes an aldehyde dehydrogenase, a member of a large class of NADP+-dependent enzymes that catalyze the oxidation of aldehydes to their corresponding carboxylic acids. Consistent with this finding, extracts of ref1 leaves exhibit low sinapaldehyde dehydrogenase activity. These data indicate that REF1 encodes a sinapaldehyde dehydrogenase required for sinapic acid and sinapate ester biosynthesis. When expressed in Escherichia coli, REF1 was found to exhibit both sinapaldehyde and coniferaldehyde dehydrogenase activity, and further phenotypic analysis of ref1 mutant plants showed that they contain less cell wall–esterified ferulic acid. These findings suggest that both ferulic acid and sinapic acid are derived, at least in part, through oxidation of coniferaldehyde and sinapaldehyde. This route is directly opposite to the traditional representation of phenylpropanoid metabolism in which hydroxycinnamic acids are instead precursors of their corresponding aldehydes. PMID:14729911

The Arabidopsis thaliana REDUCED EPIDERMAL FLUORESCENCE1 gene encodes an aldehyde dehydrogenase involved in ferulic acid and sinapic acid biosynthesis.

PubMed

Nair, Ramesh B; Bastress, Kristen L; Ruegger, Max O; Denault, Jeff W; Chapple, Clint

2004-02-01

Recent research has significantly advanced our understanding of the phenylpropanoid pathway but has left in doubt the pathway by which sinapic acid is synthesized in plants. The reduced epidermal fluorescence1 (ref1) mutant of Arabidopsis thaliana accumulates only 10 to 30% of the sinapate esters found in wild-type plants. Positional cloning of the REF1 gene revealed that it encodes an aldehyde dehydrogenase, a member of a large class of NADP(+)-dependent enzymes that catalyze the oxidation of aldehydes to their corresponding carboxylic acids. Consistent with this finding, extracts of ref1 leaves exhibit low sinapaldehyde dehydrogenase activity. These data indicate that REF1 encodes a sinapaldehyde dehydrogenase required for sinapic acid and sinapate ester biosynthesis. When expressed in Escherichia coli, REF1 was found to exhibit both sinapaldehyde and coniferaldehyde dehydrogenase activity, and further phenotypic analysis of ref1 mutant plants showed that they contain less cell wall-esterified ferulic acid. These findings suggest that both ferulic acid and sinapic acid are derived, at least in part, through oxidation of coniferaldehyde and sinapaldehyde. This route is directly opposite to the traditional representation of phenylpropanoid metabolism in which hydroxycinnamic acids are instead precursors of their corresponding aldehydes.

Goal-Directed Visual Processing Differentially Impacts Human Ventral and Dorsal Visual Representations

PubMed Central

2017-01-01

Recent studies have challenged the ventral/“what” and dorsal/“where” two-visual-processing-pathway view by showing the existence of “what” and “where” information in both pathways. Is the two-pathway distinction still valid? Here, we examined how goal-directed visual information processing may differentially impact visual representations in these two pathways. Using fMRI and multivariate pattern analysis, in three experiments on human participants (57% females), by manipulating whether color or shape was task-relevant and how they were conjoined, we examined shape-based object category decoding in occipitotemporal and parietal regions. We found that object category representations in all the regions examined were influenced by whether or not object shape was task-relevant. This task effect, however, tended to decrease as task-relevant and irrelevant features were more integrated, reflecting the well-known object-based feature encoding. Interestingly, task relevance played a relatively minor role in driving the representational structures of early visual and ventral object regions. They were driven predominantly by variations in object shapes. In contrast, the effect of task was much greater in dorsal than ventral regions, with object category and task relevance both contributing significantly to the representational structures of the dorsal regions. These results showed that, whereas visual representations in the ventral pathway are more invariant and reflect “what an object is,” those in the dorsal pathway are more adaptive and reflect “what we do with it.” Thus, despite the existence of “what” and “where” information in both visual processing pathways, the two pathways may still differ fundamentally in their roles in visual information representation. SIGNIFICANCE STATEMENT Visual information is thought to be processed in two distinctive pathways: the ventral pathway that processes “what” an object is and the dorsal pathway that processes “where” it is located. This view has been challenged by recent studies revealing the existence of “what” and “where” information in both pathways. Here, we found that goal-directed visual information processing differentially modulates shape-based object category representations in the two pathways. Whereas ventral representations are more invariant to the demand of the task, reflecting what an object is, dorsal representations are more adaptive, reflecting what we do with the object. Thus, despite the existence of “what” and “where” information in both pathways, visual representations may still differ fundamentally in the two pathways. PMID:28821655

Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations.

PubMed

Branke, Jürgen; Hildebrandt, Torsten; Scholz-Reiter, Bernd

2015-01-01

Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by experts in a time consuming trial-and-error process. Recently, evolutionary algorithms have been proposed to automate the design process. There are several possibilities to represent rules for this hyper-heuristic search. Because the representation determines the search neighborhood and the complexity of the rules that can be evolved, a suitable choice of representation is key for a successful evolutionary algorithm. In this paper we empirically compare three different representations, both numeric and symbolic, for automated rule design: A linear combination of attributes, a representation based on artificial neural networks, and a tree representation. Using appropriate evolutionary algorithms (CMA-ES for the neural network and linear representations, genetic programming for the tree representation), we empirically investigate the suitability of each representation in a dynamic stochastic job shop scenario. We also examine the robustness of the evolved dispatching rules against variations in the underlying job shop scenario, and visualize what the rules do, in order to get an intuitive understanding of their inner workings. Results indicate that the tree representation using an improved version of genetic programming gives the best results if many candidate rules can be evaluated, closely followed by the neural network representation that already leads to good results for small to moderate computational budgets. The linear representation is found to be competitive only for extremely small computational budgets.

Insight and search in Katona's five-square problem.

PubMed

Ollinger, Michael; Jones, Gary; Knoblich, Günther

2014-01-01

Insights are often productive outcomes of human thinking. We provide a cognitive model that explains insight problem solving by the interplay of problem space search and representational change, whereby the problem space is constrained or relaxed based on the problem representation. By introducing different experimental conditions that either constrained the initial search space or helped solvers to initiate a representational change, we investigated the interplay of problem space search and representational change in Katona's five-square problem. Testing 168 participants, we demonstrated that independent hints relating to the initial search space and to representational change had little effect on solution rates. However, providing both hints caused a significant increase in solution rates. Our results show the interplay between problem space search and representational change in insight problem solving: The initial problem space can be so large that people fail to encounter impasse, but even when representational change is achieved the resulting problem space can still provide a major obstacle to finding the solution.

The semantic representation of prejudice and stereotypes.

PubMed

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

PubMed

De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

2017-11-13

Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant perceptual attribute such as pitch. Taken together, the results of our model-based encoding and decoding analyses indicated that the pitch of complex real life sounds is extracted and processed in lateral HG/STG regions, at locations consistent with those indicated in several previous fMRI studies using synthetic sounds. Within these regions, pitch-related sound representations reflect the modulatory combination of height and the salience of the pitch percept. Copyright © 2017 Elsevier Inc. All rights reserved.

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.

PubMed

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A

2017-03-01

The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.

User-based representation of time-resolved multimodal public transportation networks.

PubMed

Alessandretti, Laura; Karsai, Márton; Gauvin, Laetitia

2016-07-01

Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments.

bioWeb3D: an online webGL 3D data visualisation tool.

PubMed

Pettit, Jean-Baptiste; Marioni, John C

2013-06-07

Data visualization is critical for interpreting biological data. However, in practice it can prove to be a bottleneck for non trained researchers; this is especially true for three dimensional (3D) data representation. Whilst existing software can provide all necessary functionalities to represent and manipulate biological 3D datasets, very few are easily accessible (browser based), cross platform and accessible to non-expert users. An online HTML5/WebGL based 3D visualisation tool has been developed to allow biologists to quickly and easily view interactive and customizable three dimensional representations of their data along with multiple layers of information. Using the WebGL library Three.js written in Javascript, bioWeb3D allows the simultaneous visualisation of multiple large datasets inputted via a simple JSON, XML or CSV file, which can be read and analysed locally thanks to HTML5 capabilities. Using basic 3D representation techniques in a technologically innovative context, we provide a program that is not intended to compete with professional 3D representation software, but that instead enables a quick and intuitive representation of reasonably large 3D datasets.

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems

PubMed Central

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A.

2017-01-01

Abstract The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework. PMID:28328252

User-based representation of time-resolved multimodal public transportation networks

PubMed Central

Alessandretti, Laura; Gauvin, Laetitia

2016-01-01

Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments. PMID:27493773

fMRI-based Multivariate Pattern Analyses Reveal Imagery Modality and Imagery Content Specific Representations in Primary Somatosensory, Motor and Auditory Cortices.

PubMed

de Borst, Aline W; de Gelder, Beatrice

2017-08-01

Previous studies have shown that the early visual cortex contains content-specific representations of stimuli during visual imagery, and that these representational patterns of imagery content have a perceptual basis. To date, there is little evidence for the presence of a similar organization in the auditory and tactile domains. Using fMRI-based multivariate pattern analyses we showed that primary somatosensory, auditory, motor, and visual cortices are discriminative for imagery of touch versus sound. In the somatosensory, motor and visual cortices the imagery modality discriminative patterns were similar to perception modality discriminative patterns, suggesting that top-down modulations in these regions rely on similar neural representations as bottom-up perceptual processes. Moreover, we found evidence for content-specific representations of the stimuli during auditory imagery in the primary somatosensory and primary motor cortices. Both the imagined emotions and the imagined identities of the auditory stimuli could be successfully classified in these regions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An analysis of primary school students’ representational ability in mathematics based on gender perspective

NASA Astrophysics Data System (ADS)

Kowiyah; Mulyawati, I.

2018-01-01

Mathematic representation is one of the basic mathematic skills that allows students to communicate their mathematic ideas through visual realities such as pictures, tables, mathematic expressions and mathematic equities. The present research aims at: 1) analysing students’ mathematic representation ability in solving mathematic problems and 2) examining the difference of students’ mathematic ability based on their gender. A total of sixty primary school students participated in this study comprising of thirty males and thirty females. Data required in this study were collected through mathematic representation tests, interviews and test evaluation rubric. Findings of this study showed that students’ mathematic representation of visual realities (image and tables) was reported higher at 62.3% than at in the form of description (or statement) at 8.6%. From gender perspective, male students performed better than the females at action planning stage. The percentage of males was reported at 68% (the highest), 33% (medium) and 21.3% (the lowest) while the females were at 36% (the highest), 37.7% (medium) and 32.6% (the lowest).

An assessment of alternative fuel cell designs for residential and commercial cogeneration

NASA Technical Reports Server (NTRS)

Wakefield, R. A.

1980-01-01

A comparative assessment of three fuel cell systems for application in different buildings and geographic locations is presented. The study was performed at the NASA Lewis Center and comprised the fuel cell design, performance in different conditions, and the economic parameters. Applications in multifamily housing, stores and hospitals were considered, with a load of 10kW-1 MW. Designs were traced through system sizing, simulation/evaluation, and reliability analysis, and a computer simulation based on a fourth-order representation of a generalized system was performed. The cells were all phosphoric acid type cells, and were found to be incompatible with gas/electric systems and more favorable economically than the gas/electric systems in hospital uses. The methodology used provided an optimized energy-use pattern and minimized back-up system turn-on.

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

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

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

An approach to automated particle picking from electron micrographs based on reduced representation templates.

PubMed

Volkmann, Niels

2004-01-01

Reduced representation templates are used in a real-space pattern matching framework to facilitate automatic particle picking from electron micrographs. The procedure consists of five parts. First, reduced templates are constructed either from models or directly from the data. Second, a real-space pattern matching algorithm is applied using the reduced representations as templates. Third, peaks are selected from the resulting score map using peak-shape characteristics. Fourth, the surviving peaks are tested for distance constraints. Fifth, a correlation-based outlier screening is applied. Test applications to a data set of keyhole limpet hemocyanin particles indicate that the method is robust and reliable.

Theoretical foundations for information representation and constraint specification

NASA Technical Reports Server (NTRS)

Menzel, Christopher P.; Mayer, Richard J.

1991-01-01

Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification.

Reserve Design under Climate Change: From Land Facets Back to Ecosystem Representation

PubMed Central

Schneider, Richard R.; Bayne, Erin M.

2015-01-01

Ecosystem distributions are expected to shift as a result of global warming, raising concerns about the long-term utility of reserve systems based on coarse-filter ecosystem representation. We tested the extent to which proportional ecosystem representation targets would be maintained under a changing climate by projecting the distribution of the major ecosystems of Alberta, Canada, into the future using bioclimatic envelope models and then calculating the composition of reserves in successive periods. We used the Marxan conservation planning software to generate the suite of reserve systems for our test, varying the representation target and degree of reserve clumping. Our climate envelope projections for the 2080s indicate that virtually all reserves will, in time, be comprised of different ecosystem types than today. Nevertheless, our proportional targets for ecosystem representation were maintained across all time periods, with only minor exceptions. We hypothesize that this stability in representation arises because ecosystems may be serving as proxies for land facets, the stable abiotic landscape features that delineate major arenas of biological activity. The implication is that accommodating climate change may not require abandoning the conventional ecosystem-based approach to reserve design in favour of a strictly abiotic approach, since the two approaches may be largely synonymous. PMID:25978759

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

NASA Astrophysics Data System (ADS)

Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

The impact of category structure and training methodology on learning and generalizing within-category representations.

PubMed

Ell, Shawn W; Smith, David B; Peralta, Gabriela; Hélie, Sébastien

2017-08-01

When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.

Plane representations of graphs and visibility between parallel segments

NASA Astrophysics Data System (ADS)

Tamassia, R.; Tollis, I. G.

1985-04-01

Several layout compaction strategies for VLSI are based on the concept of visibility between parallel segments, where we say that two parallel segments of a given set are visible if they can be joined by a segment orthogonal to them, which does not intersect any other segment. This paper studies visibility representations of graphs, which are constructed by mapping vertices to horizontal segments, and edges to vertical segments drawn between visible vertex-segments. Clearly, every graph that admits such a representation must be a planar. The authors consider three types of visibility representations, and give complete characterizations of the classes of graphs that admit them. Furthermore, they present linear time algorithms for testing the existence of and constructing visibility representations of planar graphs.

A randomized trial of computer-based communications using imagery and text information to alter representations of heart disease risk and motivate protective behaviour.

PubMed

Lee, Tarryn J; Cameron, Linda D; Wünsche, Burkhard; Stevens, Carey

2011-02-01

Advances in web-based animation technologies provide new opportunities to develop graphic health communications for dissemination throughout communities. We developed imagery and text contents of brief, computer-based programmes about heart disease risk, with both imagery and text contents guided by the common-sense model (CSM) of self-regulation. The imagery depicts a three-dimensional, beating heart tailored to user-specific information. A 2 × 2 × 4 factorial design was used to manipulate concrete imagery (imagery vs. no imagery) and conceptual information (text vs. no text) about heart disease risk in prevention-oriented programmes and assess changes in representations and behavioural motivations from baseline to 2 days, 2 weeks, and 4 weeks post-intervention. Sedentary young adults (N= 80) were randomized to view one of four programmes: imagery plus text, imagery only, text only, or control. Participants completed measures of risk representations, worry, and physical activity and healthy diet intentions and behaviours at baseline, 2 days post-intervention (except behaviours), and 2 weeks (intentions and behaviours only) and 4 weeks later. The imagery contents increased representational beliefs and mental imagery relating to heart disease, worry, and intentions at post-intervention. Increases in sense of coherence (understanding of heart disease) and worry were sustained after 1 month. The imagery contents also increased healthy diet efforts after 2 weeks. The text contents increased beliefs about causal factors, mental images of clogged arteries, and worry at post-intervention, and increased physical activity 2 weeks later and sense of coherence 1 month later. The CSM-based programmes induced short-term changes in risk representations and behaviour motivation. The combination of CSM-based text and imagery appears to be most effective in instilling risk representations that motivate protective behaviour. ©2010 The British Psychological Society.

Knowledge representation and management enabling intelligent interoperability - principles and standards.

PubMed

Blobel, Bernd

2013-01-01

Based on the paradigm changes for health, health services and underlying technologies as well as the need for at best comprehensive and increasingly automated interoperability, the paper addresses the challenge of knowledge representation and management for medical decision support. After introducing related definitions, a system-theoretical, architecture-centric approach to decision support systems (DSSs) and appropriate ways for representing them using systems of ontologies is given. Finally, existing and emerging knowledge representation and management standards are presented. The paper focuses on the knowledge representation and management part of DSSs, excluding the reasoning part from consideration.

Conglomeration or Chameleon? Teachers' Representations of Language in the Assessment of Learners with English as an Additional Language.

ERIC Educational Resources Information Center

Gardner, Sheena; Rea-Dickins, Pauline

2001-01-01

Investigates teacher representations of language in relation to assessment contexts. Analyzes not only what is represented in teachers' use of metalanguage, but also how it is presented--in terms of expression, voice, and source. The analysis is based on interviews with teachers, transcripts of lessons, and classroom-based assessments, formal…

A Service Oriented Web Application for Learner Knowledge Representation, Management and Sharing Conforming to IMS LIP

ERIC Educational Resources Information Center

Lazarinis, Fotis

2014-01-01

iLM is a Web based application for representation, management and sharing of IMS LIP conformant user profiles. The tool is developed using a service oriented architecture with emphasis on the easy data sharing. Data elicitation from user profiles is based on the utilization of XQuery scripts and sharing with other applications is achieved through…

"It's Me. I'm Fixin' to Know the Hard Words": Children's Perceptions of "Good Readers" as Portrayed in Their Representational Drawings

ERIC Educational Resources Information Center

Cobb, Jeanne B.

2012-01-01

This study utilized a qualitative, interpretative, analytic technique based on image-based research. This descriptive study was designed to investigate children's perceptions of "good readers" as portrayed in their representational drawings. Children in grades kindergarten through 6, 156 total, in 14 schools in a small, rural school…

Minority Representation within Fields in Psychology: Implications for Career Counseling, Training, and APA Recruitment by Division.

ERIC Educational Resources Information Center

Steward, Robbie J.; Powers, Robin

An examination of the representation of doctoral level, United States-based, racial/ethnic minority professionals (n=1,597) by division within the American Psychological Association (APA) was conducted. Membership status (i.e., member, fellow), specialty area, and sex also are noted in the compilation of findings. Results indicate that U.S.-based,…

Gender Representation in Different Languages and Grammatical Marking on Pronouns: When Beauticians, Musicians, and Mechanics Remain Men

ERIC Educational Resources Information Center

Garnham, Alan; Gabriel, Ute; Sarrasin, Oriane; Gygax, Pascal; Oakhill, Jane

2012-01-01

Gygax, Gabriel, Sarrasin, Oakhill, and Garnham (2008) showed that readers form a mental representation of gender that is based on grammatical gender in French and German (i.e., masculine supposedly interpretable as a generic form) but is based on stereotypical information in English. In this study, a modification of their stimulus material was…

The Effects of Teacher-Introduced Multimodal Representations and Discourse on Students' Task Engagement and Scientific Language during Cooperative, Inquiry-Based Science

ERIC Educational Resources Information Center

Gillies, Robyn M.; Baffour, Bernard

2017-01-01

The study sought to determine the effects of teacher-introduced multimodal representations and discourse on students' task engagement and scientific language during cooperative, inquiry-based science. The study involved eight Year 6 teachers in two conditions (four very effective teachers and four effective teachers) who taught two units of…

Integrated argument-based inquiry with multiple representation approach to promote scientific argumentation skill

NASA Astrophysics Data System (ADS)

Suminar, Iin; Muslim, Liliawati, Winny

2017-05-01

The purpose of this research was to identify student's written argument embedded in scientific inqury investigation and argumentation skill using integrated argument-based inquiry with multiple representation approach. This research was using quasi experimental method with the nonequivalent pretest-posttest control group design. Sample ot this research was 10th grade students at one of High School in Bandung using two classes, they were 26 students of experiment class and 26 students of control class. Experiment class using integrated argument-based inquiry with multiple representation approach, while control class using argument-based inquiry. This study was using argumentation worksheet and argumentation test. Argumentation worksheet encouraged students to formulate research questions, design experiment, observe experiment and explain the data as evidence, construct claim, warrant, embedded multiple modus representation and reflection. Argumentation testinclude problem which asks students to explain evidence, warrants, and backings support of each claim. The result of this research show experiment class students's argumentation skill performed better than control class students that of experiment class was 0.47 and control class was 0.31. The results of unequal variance t-test for independent means show that students'sargumentationskill of experiment class performed better significantly than students'sargumentationskill of control class.

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Operator algebra as an application of logarithmic representation of infinitesimal generators

NASA Astrophysics Data System (ADS)

Iwata, Yoritaka

2018-02-01

The operator algebra is introduced based on the framework of logarithmic representation of infinitesimal generators. In conclusion a set of generally-unbounded infinitesimal generators is characterized as a module over the Banach algebra.

"The Madness of the Carnival": Representations of Latin America and the Caribbean in the U.S. Homophile Press.

PubMed

Gleibman, Shlomo

2017-01-01

This essay examines representations of Latin America and the Caribbean in U.S. homophile periodicals from 1953 to 1964. The 120 items in ONE, Mattachine Review, and The Ladder that referenced this region depicted Latin America and the Caribbean as different from the United States in a number of ways, in particular as more sexually repressive or more sexually liberal. These representations typically conformed to the general homophile movement tendency to challenge U.S. anti-homosexual campaigns during the "Lavender Scare," while arguing for acceptance based on rights claims. The representations also were based on Cold War, colonial, racist, nationalist, and imperialist frameworks. The essay argues that although the magazines generally affirmed the dominant homophile discourses of respectability and domesticity, they also challenged these discourses by presenting Latin American and Caribbean cultures as gender-nonconforming and sexually promiscuous.

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Is the asymmetry in young infants' categorization of humans versus nonhuman animals based on head, body, or global gestalt information?

PubMed

Quinn, Paul C

2004-02-01

Quinn and Eimas (1998) reported an asymmetry in the exclusivity of the category representations that young infants form for humans and nonhuman animals: category representations for nonhuman animal species were found to exclude humans, whereas a category representation for humans was found to include nonhuman animal species (i.e., cats, horses). The present experiment utilized the familiarization/novelty-preference procedure with 3- and 4-month-olds to determine the perceptual cues (i.e., whole stimulus, head alone, body alone) that provided the basis for this asymmetry. The data revealed the asymmetry to be observable only with the whole animal stimuli and not when infants were provided with information from just the head or the body of the exemplars. The results indicate that the incorporation of nonhuman animal species into a category representation for humans is based on holistic information.

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Gut Microbiota Markers in Obese Adolescent and Adult Patients: Age-Dependent Differential Patterns.

PubMed

Del Chierico, Federica; Abbatini, Francesca; Russo, Alessandra; Quagliariello, Andrea; Reddel, Sofia; Capoccia, Danila; Caccamo, Romina; Ginanni Corradini, Stefano; Nobili, Valerio; De Peppo, Francesco; Dallapiccola, Bruno; Leonetti, Frida; Silecchia, Gianfranco; Putignani, Lorenza

2018-01-01

Obesity levels, especially in children, have dramatically increased over the last few decades. Recently, several studies highlighted the involvement of gut microbiota in the pathophysiology of obesity. We investigated the composition of gut microbiota in obese adolescents and adults compared to age-matched normal weight (NW) volunteers in order to assemble age- and obesity-related microbiota profiles. The composition of gut microbiota was analyzed by 16S rRNA-based metagenomics. Ecological representations of microbial communities were computed, and univariate, multivariate, and correlation analyses performed on bacterial profiles. The prediction of metagenome functional content from 16S rRNA gene surveys was carried out. Ecological analyses revealed a dissimilarity among the subgroups, and resultant microbiota profiles differed between obese adolescents and adults. Using statistical analyses, we assigned, as microbial markers, Faecalibacterium prausnitzii and Actinomyces to the microbiota of obese adolescents, and Parabacteroides , Rikenellaceae, Bacteroides caccae , Barnesiellaceae, and Oscillospira to the microbiota of NW adolescents. The predicted metabolic profiles resulted different in adolescent groups. Particularly, biosynthesis of primary bile acid and steroid acids, metabolism of fructose, mannose, galactose, butanoate, and pentose phosphate and glycolysis/gluconeogenesis were for the majority associated to obese, while biosynthesis and metabolism of glycan, biosynthesis of secondary bile acid, metabolism of steroid hormone and lipoic acid were associated to NW adolescents. Our study revealed unique features of gut microbiota in terms of ecological patterns, microbial composition and metabolism in obese patients. The assignment of novel obesity bacterial markers may open avenues for the development of patient-tailored treatments dependent on age-related microbiota profiles.

Inadequacy representation of flamelet-based RANS model for turbulent non-premixed flame

NASA Astrophysics Data System (ADS)

Lee, Myoungkyu; Oliver, Todd; Moser, Robert

2017-11-01

Stochastic representations for model inadequacy in RANS-based models of non-premixed jet flames are developed and explored. Flamelet-based RANS models are attractive for engineering applications relative to higher-fidelity methods because of their low computational costs. However, the various assumptions inherent in such models introduce errors that can significantly affect the accuracy of computed quantities of interest. In this work, we develop an approach to represent the model inadequacy of the flamelet-based RANS model. In particular, we pose a physics-based, stochastic PDE for the triple correlation of the mixture fraction. This additional uncertain state variable is then used to construct perturbations of the PDF for the instantaneous mixture fraction, which is used to obtain an uncertain perturbation of the flame temperature. A hydrogen-air non-premixed jet flame is used to demonstrate the representation of the inadequacy of the flamelet-based RANS model. This work was supported by DARPA-EQUiPS(Enabling Quantification of Uncertainty in Physical Systems) program.

Automatic frame-centered object representation and integration revealed by iconic memory, visual priming, and backward masking

PubMed Central

Lin, Zhicheng; He, Sheng

2012-01-01

Object identities (“what”) and their spatial locations (“where”) are processed in distinct pathways in the visual system, raising the question of how the what and where information is integrated. Because of object motions and eye movements, the retina-based representations are unstable, necessitating nonretinotopic representation and integration. A potential mechanism is to code and update objects according to their reference frames (i.e., frame-centered representation and integration). To isolate frame-centered processes, in a frame-to-frame apparent motion configuration, we (a) presented two preceding or trailing objects on the same frame, equidistant from the target on the other frame, to control for object-based (frame-based) effect and space-based effect, and (b) manipulated the target's relative location within its frame to probe frame-centered effect. We show that iconic memory, visual priming, and backward masking depend on objects' relative frame locations, orthogonal of the retinotopic coordinate. These findings not only reveal that iconic memory, visual priming, and backward masking can be nonretinotopic but also demonstrate that these processes are automatically constrained by contextual frames through a frame-centered mechanism. Thus, object representation is robustly and automatically coupled to its reference frame and continuously being updated through a frame-centered, location-specific mechanism. These findings lead to an object cabinet framework, in which objects (“files”) within the reference frame (“cabinet”) are orderly coded relative to the frame. PMID:23104817

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

2017-08-29

In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

Network Analysis of Students' Use of Representations in Problem Solving

NASA Astrophysics Data System (ADS)

McPadden, Daryl; Brewe, Eric

2016-03-01

We present the preliminary results of a study on student use of representations in problem solving within the Modeling Instruction - Electricity and Magnetism (MI-E&M) course. Representational competence is a critical skill needed for students to develop a sophisticated understanding of college science topics and to succeed in their science courses. In this study, 70 students from the MI-E&M, calculus-based course were given a survey of 25 physics problem statements both pre- and post- instruction, covering both Newtonian Mechanics and Electricity and Magnetism (E&M). For each problem statement, students were asked which representations they would use in that given situation. We analyze the survey results through network analysis, identifying which representations are linked together in which contexts. We also compare the representation networks for those students who had already taken the first-semester Modeling Instruction Mechanics course and those students who had taken a non-Modeling Mechanics course.

Effects of an ontology display with history representation on organizational memory information systems.

PubMed

Hwang, Wonil; Salvendy, Gavriel

2005-06-10

Ontologies, as a possible element of organizational memory information systems, appear to support organizational learning. Ontology tools can be used to share knowledge among the members of an organization. However, current ontology-viewing user interfaces of ontology tools do not fully support organizational learning, because most of them lack proper history representation in their display. In this study, a conceptual model was developed that emphasized the role of ontology in the organizational learning cycle and explored the integration of history representation in the ontology display. Based on the experimental results from a split-plot design with 30 participants, two conclusions were derived: first, appropriately selected history representations in the ontology display help users to identify changes in the ontologies; and second, compatibility between types of ontology display and history representation is more important than ontology display and history representation in themselves.

Quantity processing in deaf and hard of hearing children: evidence from symbolic and nonsymbolic comparison tasks.

PubMed

Rodríguez-Santos, José Miguel; Calleja, Marina; García-Orza, Javier; Iza, Mauricio; Damas, Jesús

2014-01-01

Deaf children usually achieve lower scores on numerical tasks than normally hearing peers. Explanations for mathematical disabilities in hearing children are based on quantity representation deficits (Geary, 1994) or on deficits in accessing these representations (Rousselle & Noël, 2008). The present study aimed to verify, by means of symbolic (Arabic digits) and nonsymbolic (dot constellations and hands) magnitude comparison tasks, whether deaf children show deficits in representations or in accessing numerical representations. The study participants were 10 prelocutive deaf children and 10 normally hearing children. Numerical distance and magnitude were manipulated. Response time (RT) analysis showed similar magnitude and distance effects in both groups on the 3 tasks. However, slower RTs were observed among the deaf participants on the symbolic task alone. These results suggest that although both groups' quantity representations were similar, the deaf group experienced a delay in accessing representations from symbolic codes.

Graphical tensor product reduction scheme for the Lie algebras so(5) = sp(2) , su(3) , and g(2)

NASA Astrophysics Data System (ADS)

Vlasii, N. D.; von Rütte, F.; Wiese, U.-J.

2016-08-01

We develop in detail a graphical tensor product reduction scheme, first described by Antoine and Speiser, for the simple rank 2 Lie algebras so(5) = sp(2) , su(3) , and g(2) . This leads to an efficient practical method to reduce tensor products of irreducible representations into sums of such representations. For this purpose, the 2-dimensional weight diagram of a given representation is placed in a ;landscape; of irreducible representations. We provide both the landscapes and the weight diagrams for a large number of representations for the three simple rank 2 Lie algebras. We also apply the algebraic ;girdle; method, which is much less efficient for calculations by hand for moderately large representations. Computer code for reducing tensor products, based on the graphical method, has been developed as well and is available from the authors upon request.

State-Based Delay Representation and Its Transfer from a Game of Pong to Reaching and Tracking

PubMed Central

Leib, Raz; Pressman, Assaf; Simo, Lucia S.; Karniel, Amir

2017-01-01

Abstract To accurately estimate the state of the body, the nervous system needs to account for delays between signals from different sensory modalities. To investigate how such delays may be represented in the sensorimotor system, we asked human participants to play a virtual pong game in which the movement of the virtual paddle was delayed with respect to their hand movement. We tested the representation of this new mapping between the hand and the delayed paddle by examining transfer of adaptation to blind reaching and blind tracking tasks. These blind tasks enabled to capture the representation in feedforward mechanisms of movement control. A Time Representation of the delay is an estimation of the actual time lag between hand and paddle movements. A State Representation is a representation of delay using current state variables: the distance between the paddle and the ball originating from the delay may be considered as a spatial shift; the low sensitivity in the response of the paddle may be interpreted as a minifying gain; and the lag may be attributed to a mechanical resistance that influences paddle’s movement. We found that the effects of prolonged exposure to the delayed feedback transferred to blind reaching and tracking tasks and caused participants to exhibit hypermetric movements. These results, together with simulations of our representation models, suggest that delay is not represented based on time, but rather as a spatial gain change in visuomotor mapping. PMID:29379875

Cloning, characterization, expression and comparative analysis of pig Golgi membrane sphingomyelin synthase 1.

PubMed

Guillén, Natalia; Navarro, María A; Surra, Joaquín C; Arnal, Carmen; Fernández-Juan, Marta; Cebrián-Pérez, Jose Alvaro; Osada, Jesús

2007-02-15

Pig sphingomyelin synthase 1 (SMS1) cDNA was cloned, characterized and compared to the human ortholog. Porcine protein consists of 413 amino acids and displays a 97% sequence identity with human protein. A phylogenic tree of proteins reveals that porcine SMS1 is more closely related to bovine and rodent proteins than to human. Analysis of protein mass was higher than the theoretical prediction based on amino acid sequence suggesting a kind of posttranslational modification. Quantitative representation of tissue distribution obtained by real-time RT-PCR showed that it was widely expressed although important variations in levels were obtained among organs. Thus, the cardiovascular system, especially the heart, showed the highest value of all the tissues studied. Regional differences of expression were observed in the central nervous system and intestinal tract. Analysis of the hepatic mRNA and protein expressions of SMS1 following turpentine treatment revealed a progressive decrease in the former paralleled by a decrease in the protein concentration. These findings indicate the variation in expression in the different tissues might suggest a different requirement of Golgi sphingomyelin for the specific function in each organ and a regulation of the enzyme in response to turpentine-induced hepatic injury.

Structurally detailed coarse-grained model for Sec-facilitated co-translational protein translocation and membrane integration

PubMed Central

Miller, Thomas F.

2017-01-01

We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 μs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency. PMID:28328943

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

NASA Astrophysics Data System (ADS)

Ziegler, Benjamin; Rauhut, Guntram

2016-03-01

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions.

PubMed

Ziegler, Benjamin; Rauhut, Guntram

2016-03-21

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Integration of object-oriented knowledge representation with the CLIPS rule based system

NASA Technical Reports Server (NTRS)

Logie, David S.; Kamil, Hasan

1990-01-01

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Turning negative memories around: Contingency versus devaluation techniques.

PubMed

Dibbets, Pauline; Lemmens, Anke; Voncken, Marisol

2018-09-01

It is assumed that fear responses can be altered by changing the contingency between a conditioned stimulus (CS) and an unconditioned stimulus (US), or by devaluing the present mental representation of the US. The aim of the present study was to compare the efficacy of contingency- and devaluation-based intervention techniques on the diminishment in - and return of fear. We hypothesized that extinction (EXT, contingency-based) would outperform devaluation-based techniques regarding contingency measures, but that devaluation-based techniques would be most effective in reducing the mental representation of the US. Additionally, we expected that incorporations of the US during devaluation would result in less reinstatement of the US averseness. Healthy participants received a fear conditioning paradigm followed by one of three interventions: extinction (EXT, contingency-based), imagery rescripting (ImRs, devaluation-based) or eye movement desensitization and reprocessing (EMDR, devaluation-based). A reinstatement procedure and test followed the next day. EXT was indeed most successful in diminishing contingency-based US expectancies and skin conductance responses (SCRs), but all interventions were equally successful in reducing the averseness of the mental US representation. After reinstatement EXT showed lowest expectancies and SCRs; no differences were observed between the conditions concerning the mental US representation. A partial reinforcement schedule was used, resulting in a vast amount of contingency unaware participants. Additionally, a non-clinical sample was used, which may limit the generalizability to clinical populations. EXT is most effective in reducing conditioned fear responses. Copyright © 2018 Elsevier Ltd. All rights reserved.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

PubMed Central

Rolls, Edmund T.

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

PubMed

Rolls, Edmund T

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Neuroscience-inspired computational systems for speech recognition under noisy conditions

NASA Astrophysics Data System (ADS)

Schafer, Phillip B.

Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes advantage of the neural representation's invariance in noise. The scheme centers on a speech similarity measure based on the longest common subsequence between spike sequences. The combined encoding and decoding scheme outperforms a benchmark system in extremely noisy acoustic conditions. Finally, I consider methods for decoding spike representations of continuous speech. To help guide the alignment of templates to words, I design a syllable detection scheme that robustly marks the locations of syllabic nuclei. The scheme combines SVM-based training with a peak selection algorithm designed to improve noise tolerance. By incorporating syllable information into the ASR system, I obtain strong recognition results in noisy conditions, although the performance in noiseless conditions is below the state of the art. The work presented here constitutes a novel approach to the problem of ASR that can be applied in the many challenging acoustic environments in which we use computer technologies today. The proposed spike-based processing methods can potentially be exploited in effcient hardware implementations and could significantly reduce the computational costs of ASR. The work also provides a framework for understanding the advantages of spike-based acoustic coding in the human brain.

A Robust Concurrent Approach for Road Extraction and Urbanization Monitoring Based on Superpixels Acquired from Spectral Remote Sensing Images

NASA Astrophysics Data System (ADS)

Seppke, Benjamin; Dreschler-Fischer, Leonie; Wilms, Christian

2016-08-01

The extraction of road signatures from remote sensing images as a promising indicator for urbanization is a classical segmentation problem. However, some segmentation algorithms often lead to non-sufficient results. One way to overcome this problem is the usage of superpixels, that represent a locally coherent cluster of connected pixels. Superpixels allow flexible, highly adaptive segmentation approaches due to the possibility of merging as well as splitting and form new basic image entities. On the other hand, superpixels require an appropriate representation containing all relevant information about topology and geometry to maximize their advantages.In this work, we present a combined geometric and topological representation based on a special graph representation, the so-called RS-graph. Moreover, we present the use of the RS-graph by means of a case study: the extraction of partially occluded road networks in rural areas from open source (spectral) remote sensing images by tracking. In addition, multiprocessing and GPU-based parallelization is used to speed up the construction of the representation and the application.

Script-like attachment representations in dreams containing current romantic partners.

PubMed

Selterman, Dylan; Apetroaia, Adela; Waters, Everett

2012-01-01

Recent research has demonstrated parallels between romantic attachment styles and general dream content. The current study examined partner-specific attachment representations alongside dreams that contained significant others. The general prediction was that dreams would follow the "secure base script," and a general correspondence would emerge between secure attachment cognitions in waking life and in dreams. Sixty-one undergraduate student participants in committed dating relationships of six months duration or longer completed the Secure Base Script Narrative Assessment at Time 1, and then completed a dream diary for 14 consecutive days. Blind coders scored dreams that contained significant others using the same criteria for secure base content in laboratory narratives. Results revealed a significant association between relationship-specific attachment security and the degree to which dreams about romantic partners followed the secure base script. The findings illuminate our understanding of mental representations with regards to specific attachment figures. Implications for attachment theory and clinical applications are discussed.

Increasing the understanding of chemical concepts: The effectiveness of multiple exposures

NASA Astrophysics Data System (ADS)

Bius, Janet H.

Chemistry is difficult because it has multilevels of knowledge with each level presenting challenges in vocabulary, abstract thinking, and symbolic language. Students have to be able to transfer between levels to understand the concepts and the theoretical models of chemistry. The cognitive theories of constructivism and cognitive-load theory are used to explain the difficulties novice learners have with the subject of chemistry and methods to increase success for students. The relationship between external representations, misconceptions and topics on the success of students are addressed. If students do not know the formalisms associated with chemical diagrams and graphs, the representations will decrease student success. Misconceptions can be formed when new information is interpreted based on pre-existing knowledge that is faulty. Topics with large amount of interacting elements that must be processed simultaneously are considered difficult to understand. New variables were created to measure the number of times a student is exposed to a chemical concept. Each variable was coded according to topic and learning environment, which are the lecture and laboratory components of the course, homework assignments and textbook examples. The exposure variables are used to measure the success rate of students on similar exam questions. Question difficulty scales were adapted for this project from those found in the chemical education literature. The exposure variables were tested on each level of the difficulty scales to determine their effect at decreasing the cognitive demand of these questions. The subjects of this study were freshmen science majors at a large Midwest university. The effects of the difficulty scales and exposure variables were measured for those students whose exam scores were in the upper one-fourth percentile, for students whose test scores were in the middle one-half percentile, and the lower one-fourth percentile are those students that scored the lowest on the exam. The most difficult for all three percentiles were the topics of acid/base equilibria and aqueous equilibria. The exposure variables of recall and algorithmic homework increased student success for all percentiles. Students perform better on exam questions when they understand the terminology and symbolic representations of a topic.

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques.

PubMed

Bölling, Christian; Weidlich, Michael; Holzhütter, Hermann-Georg

2014-01-01

Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats.

Representational Similarity Analysis Reveals Commonalities and Differences in the Semantic Processing of Words and Objects

PubMed Central

Devereux, Barry J.; Clarke, Alex; Marouchos, Andreas; Tyler, Lorraine K.

2013-01-01

Understanding the meanings of words and objects requires the activation of underlying conceptual representations. Semantic representations are often assumed to be coded such that meaning is evoked regardless of the input modality. However, the extent to which meaning is coded in modality-independent or amodal systems remains controversial. We address this issue in a human fMRI study investigating the neural processing of concepts, presented separately as written words and pictures. Activation maps for each individual word and picture were used as input for searchlight-based multivoxel pattern analyses. Representational similarity analysis was used to identify regions correlating with low-level visual models of the words and objects and the semantic category structure common to both. Common semantic category effects for both modalities were found in a left-lateralized network, including left posterior middle temporal gyrus (LpMTG), left angular gyrus, and left intraparietal sulcus (LIPS), in addition to object- and word-specific semantic processing in ventral temporal cortex and more anterior MTG, respectively. To explore differences in representational content across regions and modalities, we developed novel data-driven analyses, based on k-means clustering of searchlight dissimilarity matrices and seeded correlation analysis. These revealed subtle differences in the representations in semantic-sensitive regions, with representations in LIPS being relatively invariant to stimulus modality and representations in LpMTG being uncorrelated across modality. These results suggest that, although both LpMTG and LIPS are involved in semantic processing, only the functional role of LIPS is the same regardless of the visual input, whereas the functional role of LpMTG differs for words and objects. PMID:24285896

A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models

PubMed Central

2011-01-01

Background Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). Results We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. Conclusions The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions. PMID:21429187

A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

PubMed

Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson

2011-03-23

Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

Research of Uncertainty Reasoning in Pineapple Disease Identification System

NASA Astrophysics Data System (ADS)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials

PubMed Central

Chen, Brian Y.

2014-01-01

Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins. PMID:25166865

Implementation multi representation and oral communication skills in Department of Physics Education on Elementary Physics II

NASA Astrophysics Data System (ADS)

Kusumawati, Intan; Marwoto, Putut; Linuwih, Suharto

2015-09-01

The ability of multi representation has been widely studied, but there has been no implementation through a model of learning. This study aimed to determine the ability of the students multi representation, relationships multi representation capabilities and oral communication skills, as well as the application of the relations between the two capabilities through learning model Presentatif Based on Multi representation (PBM) in solving optical geometric (Elementary Physics II). A concurrent mixed methods research methods with qualitative-quantitative weights. Means of collecting data in the form of the pre-test and post-test with essay form, observation sheets oral communication skills, and assessment of learning by observation sheet PBM-learning models all have a high degree of respectively validity category is 3.91; 4.22; 4.13; 3.88. Test reliability with Alpha Cronbach technique, reliability coefficient of 0.494. The students are department of Physics Education Unnes as a research subject. Sequence multi representation tendency of students from high to low in sequence, representation of M, D, G, V; whereas the order of accuracy, the group representation V, D, G, M. Relationship multi representation ability and oral communication skills, comparable/proportional. Implementation conjunction generate grounded theory. This study should be applied to the physics of matter, or any other university for comparison.

The Effect of Project-Based Learning on Students' Statistical Literacy Levels for Data Representation

ERIC Educational Resources Information Center

Koparan, Timur; Güven, Bülent

2015-01-01

The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35…

A Novel Method of Case Representation and Retrieval in CBR for E-Learning

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

On-board ephemeris representation for Topex/Poseidon

NASA Technical Reports Server (NTRS)

Salama, Ahmed H.

1990-01-01

The Topex/Poseidon satellite requires real-time on-board knowledge of the satellite and TDRS ephemeris for attitude determination and control and High-Gain Antenna (HGA) pointing. The ephemeris representation concept for the MMS (Multimission Modular Spacecraft) satellites has shown that compressing the predicted ephemeris in a Fourier Power Series (FPS) before uplinking in conjunction with the On-Board Computer (OBC) ephemeris reconstruction algorithms is an efficient technique for ephemeris representation. As an MMS-based satellite, Topex/Poseidon has inherited the Landsat ephemeris representation concept including a daily FPS upload. This paper presents the Topex/Poseidon concept, analysis, and results including the conclusion that the ephemeris representation duration could be extended to 10 days or more and convenient weekly uploading is adopted without an increase in OBC memory requirements.

Overcomplete compact representation of two-particle Green's functions

NASA Astrophysics Data System (ADS)

Shinaoka, Hiroshi; Otsuki, Junya; Haule, Kristjan; Wallerberger, Markus; Gull, Emanuel; Yoshimi, Kazuyoshi; Ohzeki, Masayuki

2018-05-01

Two-particle Green's functions and the vertex functions play a critical role in theoretical frameworks for describing strongly correlated electron systems. However, numerical calculations at the two-particle level often suffer from large computation time and massive memory consumption. We derive a general expansion formula for the two-particle Green's functions in terms of an overcomplete representation based on the recently proposed "intermediate representation" basis. The expansion formula is obtained by decomposing the spectral representation of the two-particle Green's function. We demonstrate that the expansion coefficients decay exponentially, while all high-frequency and long-tail structures in the Matsubara-frequency domain are retained. This representation therefore enables efficient treatment of two-particle quantities and opens a route to the application of modern many-body theories to realistic strongly correlated electron systems.

Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex.

PubMed

Nieder, Andreas; Miller, Earl K

2003-01-09

Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.

Attachment in families with Huntington's disease. A paradigm in clinical genetics.

PubMed

Van der Meer, Lucienne; Timman, Reinier; Trijsburg, Wim; Duisterhof, Marleen; Erdman, Ruud; Van Elderen, Thérèse; Tibben, Aad

2006-10-01

Based on the premise that attachment experiences lead to a working model for social relationships throughout life, this study investigates if there is a difference between adult attachment representations in individuals who were brought up by a parent with Huntington's disease (HD), compared to a non-clinical population. Specific events in the parents' disease process, especially those leading to trauma and loss will receive attention. Using the Adult Attachment Interview, adult attachment representations were investigated in 32 unaffected adults at 50% risk for HD who were raised by an affected parent. We found a lower percentage of secure attachment representations, a higher percentage of preoccupied representations, and a higher percentage of unresolved/disorganized representations in our sample, compared to a non-clinical population. A relatively late start of the parent's HD career was associated with a secure adult attachment representation. Death of the HD parent before the child's 18th birthday was associated with an unresolved/disorganized adult attachment representation. Growing up in a family where one of the parents has Huntington's disease appears to affect the offspring's adult attachment representation. This study can be of relevance for genetic counselling, as well as for counselling and intervention in childrearing matters.

Novice Interpretations of Visual Representations of Geosciences Data

NASA Astrophysics Data System (ADS)

Burkemper, L. K.; Arthurs, L.

2013-12-01

Past cognition research of individual's perception and comprehension of bar and line graphs are substantive enough that they have resulted in the generation of graph design principles and graph comprehension theories; however, gaps remain in our understanding of how people process visual representations of data, especially of geologic and atmospheric data. This pilot project serves to build on others' prior research and begin filling the existing gaps. The primary objectives of this pilot project include: (i) design a novel data collection protocol based on a combination of paper-based surveys, think-aloud interviews, and eye-tracking tasks to investigate student data handling skills of simple to complex visual representations of geologic and atmospheric data, (ii) demonstrate that the protocol yields results that shed light on student data handling skills, and (iii) generate preliminary findings upon which tentative but perhaps helpful recommendations on how to more effectively present these data to the non-scientist community and teach essential data handling skills. An effective protocol for the combined use of paper-based surveys, think-aloud interviews, and computer-based eye-tracking tasks for investigating cognitive processes involved in perceiving, comprehending, and interpreting visual representations of geologic and atmospheric data is instrumental to future research in this area. The outcomes of this pilot study provide the foundation upon which future more in depth and scaled up investigations can build. Furthermore, findings of this pilot project are sufficient for making, at least, tentative recommendations that can help inform (i) the design of physical attributes of visual representations of data, especially more complex representations, that may aid in improving students' data handling skills and (ii) instructional approaches that have the potential to aid students in more effectively handling visual representations of geologic and atmospheric data that they might encounter in a course, television news, newspapers and magazines, and websites. Such recommendations would also be the potential subject of future investigations and have the potential to impact the design features when data is presented to the public and instructional strategies not only in geoscience courses but also other science, technology, engineering, and mathematics (STEM) courses.

Evolution of Acid-Sensing Olfactory Circuits in Drosophilids.

PubMed

Prieto-Godino, Lucia L; Rytz, Raphael; Cruchet, Steeve; Bargeton, Benoîte; Abuin, Liliane; Silbering, Ana F; Ruta, Vanessa; Dal Peraro, Matteo; Benton, Richard

2017-02-08

Animals adapt their behaviors to specific ecological niches, but the genetic and cellular basis of nervous system evolution is poorly understood. We have compared the olfactory circuits of the specialist Drosophila sechellia-which feeds exclusively on Morinda citrifolia fruit-with its generalist cousins D. melanogaster and D. simulans. We show that D. sechellia exhibits derived odor-evoked attraction and physiological sensitivity to the abundant Morinda volatile hexanoic acid and characterize how the responsible sensory receptor (the variant ionotropic glutamate receptor IR75b) and attraction-mediating circuit have evolved. A single amino acid change in IR75b is sufficient to recode it as a hexanoic acid detector. Expanded representation of this sensory pathway in the brain relies on additional changes in the IR75b promoter and trans-acting loci. By contrast, higher-order circuit adaptations are not apparent, suggesting conserved central processing. Our work links olfactory ecology to structural and regulatory genetic changes influencing nervous system anatomy and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Spatial cognition

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Remington, Roger

1988-01-01

Spatial cognition is the ability to reason about geometric relationships in the real (or a metaphorical) world based on one or more internal representations of those relationships. The study of spatial cognition is concerned with the representation of spatial knowledge, and our ability to manipulate these representations to solve spatial problems. Spatial cognition is utilized most critically when direct perceptual cues are absent or impoverished. Examples are provided of how human spatial cognitive abilities impact on three areas of space station operator performance: orientation, path planning, and data base management. A videotape provides demonstrations of relevant phenomena (e.g., the importance of orientation for recognition of complex, configural forms). The presentation is represented by abstract and overhead visuals only.

Video Vectorization via Tetrahedral Remeshing.

PubMed

Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

2017-02-09

We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint.

PubMed

Naghibi Beidokhti, Hamid; Janssen, Dennis; van de Groes, Sebastiaan; Hazrati, Javad; Van den Boogaard, Ton; Verdonschot, Nico

2017-12-08

In finite element (FE) models knee ligaments can represented either by a group of one-dimensional springs, or by three-dimensional continuum elements based on segmentations. Continuum models closer approximate the anatomy, and facilitate ligament wrapping, while spring models are computationally less expensive. The mechanical properties of ligaments can be based on literature, or adjusted specifically for the subject. In the current study we investigated the effect of ligament modelling strategy on the predictive capability of FE models of the human knee joint. The effect of literature-based versus specimen-specific optimized material parameters was evaluated. Experiments were performed on three human cadaver knees, which were modelled in FE models with ligaments represented either using springs, or using continuum representations. In spring representation collateral ligaments were each modelled with three and cruciate ligaments with two single-element bundles. Stiffness parameters and pre-strains were optimized based on laxity tests for both approaches. Validation experiments were conducted to evaluate the outcomes of the FE models. Models (both spring and continuum) with subject-specific properties improved the predicted kinematics and contact outcome parameters. Models incorporating literature-based parameters, and particularly the spring models (with the representations implemented in this study), led to relatively high errors in kinematics and contact pressures. Using a continuum modelling approach resulted in more accurate contact outcome variables than the spring representation with two (cruciate ligaments) and three (collateral ligaments) single-element-bundle representations. However, when the prediction of joint kinematics is of main interest, spring ligament models provide a faster option with acceptable outcome. Copyright © 2017 Elsevier Ltd. All rights reserved.

Top-down attention based on object representation and incremental memory for knowledge building and inference.

PubMed

Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

2013-10-01

Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

Processing of odor mixtures in the zebrafish olfactory bulb.

PubMed

Tabor, Rico; Yaksi, Emre; Weislogel, Jan-Marek; Friedrich, Rainer W

2004-07-21

Components of odor mixtures often are not perceived individually, suggesting that neural representations of mixtures are not simple combinations of the representations of the components. We studied odor responses to binary mixtures of amino acids and food extracts at different processing stages in the olfactory bulb (OB) of zebrafish. Odor-evoked input to the OB was measured by imaging Ca2+ signals in afferents to olfactory glomeruli. Activity patterns evoked by mixtures were predictable within narrow limits from the component patterns, indicating that mixture interactions in the peripheral olfactory system are weak. OB output neurons, the mitral cells (MCs), were recorded extra- and intracellularly and responded to odors with stimulus-dependent temporal firing rate modulations. Responses to mixtures of amino acids often were dominated by one of the component responses. Responses to mixtures of food extracts, in contrast, were more distinct from both component responses. These results show that mixture interactions can result from processing in the OB. Moreover, our data indicate that mixture interactions in the OB become more pronounced with increasing overlap of input activity patterns evoked by the components. Emerging from these results are rules of mixture interactions that may explain behavioral data and provide a basis for understanding the processing of natural odor stimuli in the OB.

An atom is known by the company it keeps: Content, representation and pedagogy within the epistemic revolution of the complexity sciences

NASA Astrophysics Data System (ADS)

Blikstein, Paulo

The goal of this dissertation is to explore relations between content, representation, and pedagogy, so as to understand the impact of the nascent field of complexity sciences on science, technology, engineering and mathematics (STEM) learning. Wilensky & Papert coined the term "structurations" to express the relationship between knowledge and its representational infrastructure. A change from one representational infrastructure to another they call a "restructuration." The complexity sciences have introduced a novel and powerful structuration: agent-based modeling. In contradistinction to traditional mathematical modeling, which relies on equational descriptions of macroscopic properties of systems, agent-based modeling focuses on a few archetypical micro-behaviors of "agents" to explain emergent macro-behaviors of the agent collective. Specifically, this dissertation is about a series of studies of undergraduate students' learning of materials science, in which two structurations are compared (equational and agent-based), consisting of both design research and empirical evaluation. I have designed MaterialSim, a constructionist suite of computer models, supporting materials and learning activities designed within the approach of agent-based modeling, and over four years conducted an empirical inves3 tigation of an undergraduate materials science course. The dissertation is comprised of three studies: Study 1 - diagnosis . I investigate current representational and pedagogical practices in engineering classrooms. Study 2 - laboratory studies. I investigate the cognition of students engaging in scientific inquiry through programming their own scientific models. Study 3 - classroom implementation. I investigate the characteristics, advantages, and trajectories of scientific content knowledge that is articulated in epistemic forms and representational infrastructures unique to complexity sciences, as well as the feasibility of the integration of constructionist, agent-based learning environments in engineering classrooms. Data sources include classroom observations, interviews, videotaped sessions of model-building, questionnaires, analysis of computer-generated logfiles, and quantitative and qualitative analysis of artifacts. Results shows that (1) current representational and pedagogical practices in engineering classrooms were not up to the challenge of the complex content being taught, (2) by building their own scientific models, students developed a deeper understanding of core scientific concepts, and learned how to better identify unifying principles and behaviors in materials science, and (3) programming computer models was feasible within a regular engineering classroom.

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

PubMed Central

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

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

A Multi-factorial Model for Examining Racial and Ethnic Disparities in Acute Asthma Visits by Children

PubMed Central

Feldman, Jonathan M.; Serebrisky, Denise; Spray, Amanda

2012-01-01

Background Causes of children’s asthma health disparities are complex. Parents’ asthma illness representations may play a role. Purpose The study aims to test a theoretically based, multi-factorial model for ethnic disparities in children’s acute asthma visits through parental illness representations. Methods Structural equation modeling investigated the association of parental asthma illness representations, sociodemographic characteristics, health care provider factors, and social–environmental context with children’s acute asthma visits among 309 White, Puerto Rican, and African American families was conducted. Results Forty-five percent of the variance in illness representations and 30% of the variance in acute visits were accounted for. Statistically significant differences in illness representations were observed by ethnic group. Approximately 30% of the variance in illness representations was explained for whites, 23% for African Americans, and 26% for Puerto Ricans. The model accounted for >30% of the variance in acute visits for African Americans and Puerto Ricans but only 19% for the whites. Conclusion The model provides preliminary support that ethnic heterogeneity in asthma illness representations affects children’s health outcomes. PMID:22160799

Efficient Approaches for Evaluating the Planar Microstrip Green's Function and its Applications to the Analysis of Microstrip Antennas.

NASA Astrophysics Data System (ADS)

Barkeshli, Sina

A relatively simple and efficient closed form asymptotic representation of the microstrip dyadic surface Green's function is developed. The large parameter in this asymptotic development is proportional to the lateral separation between the source and field points along the planar microstrip configuration. Surprisingly, this asymptotic solution remains accurate even for very small (almost two tenths of a wavelength) lateral separation of the source and field points. The present asymptotic Green's function will thus allow a very efficient calculation of the currents excited on microstrip antenna patches/feed lines and monolithic millimeter and microwave integrated circuit (MIMIC) elements based on a moment method (MM) solution of an integral equation for these currents. The kernal of the latter integral equation is the present asymptotic form of the microstrip Green's function. It is noted that the conventional Sommerfeld integral representation of the microstrip surface Green's function is very poorly convergent when used in this MM formulation. In addition, an efficient exact steepest descent path integral form employing a radially propagating representation of the microstrip dyadic Green's function is also derived which exhibits a relatively faster convergence when compared to the conventional Sommerfeld integral representation. The same steepest descent form could also be obtained by deforming the integration contour of the conventional Sommerfeld representation; however, the radially propagating integral representation exhibits better convergence properties for laterally separated source and field points even before the steepest descent path of integration is used. Numerical results based on the efficient closed form asymptotic solution for the microstrip surface Green's function developed in this work are presented for the mutual coupling between a pair of dipoles on a single layer grounded dielectric slab. The accuracy of the latter calculations is confirmed by comparison with results based on an exact integral representation for that Green's function.

Emerging Standards for Medical Logic

PubMed Central

Clayton, Paul D.; Hripcsak, George; Pryor, T. Allan

1990-01-01

Sharing medical logic has traditionally occurred in the form of lectures, conversations, books and journals. As knowledge based computer systems have demonstrated their utility in the health care arena, individuals have pondered the best way to transfer knowledge in a computer based representation (1). A simple representation which allows the knowledge to be shared can be constructed when the knowledge base is modular. Within this representation, units have been named Medical Logic Modules (MLM's) and a syntax has emerged which would allow multiple users to create, criticize, and share those types of medical logic which can be represented in this format. In this paper we talk about why standards exist and why they emerge in some areas and not in others. The appropriateness of using the proposed standards for medical logic modules is then examined against this broader context.

[Social representations of Mexican pregnant teenagers about the puerperal care, lactation, and newborn care].

PubMed

Franco-Ramírez, Julieta A; Cabrera-Pivaral, Carlos E; Zárate-Guerrero, Gabriel; Franco-Chávez, Sergio A; Covarrubias-Bermúdez, María Á; Zavala-González, Marco A

2018-01-01

Puerperal care and feeding of the newborn are guided by entrenched cultural meanings between women, so it is important to know and identify how they are acquired and perpetuated. Regarding this knowledge, the social representations that Mexican pregnant teenagers have about puerperium, lactation and newborn care were studied. An interpretative study was made based on principles of the theory of social representations. Interviews were conducted to obtain information from 30 Mexican adolescents who attended prenatal care at the gynecological obstetrics area in a second-level hospital during 2015. Classical content analysis strategies were applied to analyze the information; this process consisted of coding and categorizing information. A conceptual map was also developed to describe the social representations found. In this study, 190 codes and three social representations were identified: "breastfeeding is a practice based on myths", "newborns are fragile" and "mother and child must be synchronized". Three social representations were identified that explain the practices of adolescents towards breastfeeding and the care of them and their children, which were acquired through family communication and strengthened by the need for support due to the temporary or permanent absence of the couple, personal crises motivated by bodily changes, fear of new modifications due to breastfeeding and ignorance about how carry out breastfeeding and care during the puerperium. Copyright: © 2018 Permanyer.

The use of multiple representations and visualizations in student learning of introductory physics: An example from work and energy

NASA Astrophysics Data System (ADS)

Zou, Xueli

In the past three decades, physics education research has primarily focused on student conceptual understanding; little work has been conducted to investigate student difficulties in problem solving. In cognitive science and psychology, however, extensive studies have explored the differences in problem solving between experts and naive students. A major finding indicates that experts often apply qualitative representations in problem solving, but that novices use an equation-centered method. This dissertation describes investigations into the use of multiple representations and visualizations in student understanding and problem solving with the concepts of work and energy. A multiple-representation strategy was developed to help students acquire expertise in solving work-energy problems. In this approach, a typical work-energy problem is considered as a physical process. The process is first described in words-the verbal representation of the process. Next, a sketch or a picture, called a pictorial representation, is used to represent the process. This is followed by work-energy bar charts-a physical representation of the same processes. Finally, this process is represented mathematically by using a generalized work-energy equation. In terms of the multiple representations, the goal of solving a work- energy problem is to represent the physical process the more intuitive pictorial and diagrammatic physical representations. Ongoing assessment of student learning indicates that this multiple-representation technique is more effective than standard instruction methods in student problem solving. visualize this difficult-to-understand concept, a guided- inquiry learning activity using a pair of model carts and an experiment problem using a sandbag were developed. Assessment results have shown that these research-based materials are effective in helping students visualize this concept and give a pictorial idea of ``where the kinetic energy goes'' during inelastic collisions. The research and curriculum development was conducted in the context of the introductory calculus-based physics course. Investigations were carried out using common physics education research tools, including open-ended surveys, written test questions, and individual student interviews.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

PubMed

Liu, Hu-Chen; Liu, Long; Lin, Qing-Lian; Liu, Nan

2013-06-01

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. The parameters in current FPN models could not accurately represent the increasingly complex knowledge-based systems, and the rules in most existing knowledge inference frameworks could not be dynamically adjustable according to propositions' variation as human cognition and thinking. In this paper, we present a knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems mentioned above. As is illustrated by the numerical example, the proposed approach can well capture experts' diversity experience, enhance the knowledge representation power, and reason the rule-based knowledge more intelligently.

bioWeb3D: an online webGL 3D data visualisation tool

PubMed Central

2013-01-01

Background Data visualization is critical for interpreting biological data. However, in practice it can prove to be a bottleneck for non trained researchers; this is especially true for three dimensional (3D) data representation. Whilst existing software can provide all necessary functionalities to represent and manipulate biological 3D datasets, very few are easily accessible (browser based), cross platform and accessible to non-expert users. Results An online HTML5/WebGL based 3D visualisation tool has been developed to allow biologists to quickly and easily view interactive and customizable three dimensional representations of their data along with multiple layers of information. Using the WebGL library Three.js written in Javascript, bioWeb3D allows the simultaneous visualisation of multiple large datasets inputted via a simple JSON, XML or CSV file, which can be read and analysed locally thanks to HTML5 capabilities. Conclusions Using basic 3D representation techniques in a technologically innovative context, we provide a program that is not intended to compete with professional 3D representation software, but that instead enables a quick and intuitive representation of reasonably large 3D datasets. PMID:23758781

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise

NASA Technical Reports Server (NTRS)

West, Thomas K., IV; Bretl, Katherine N.; Walker, Eric L.; Pinier, Jeremy T.

2015-01-01

The objective of this study was to outline an approach for the quantification of uncertainty in sonic boom measurements and to investigate the effect of various near-field uncertainty representation approaches on ground noise predictions. These approaches included a symmetric versus asymmetric uncertainty band representation and a dispersion technique based on a partial sum Fourier series that allows for the inclusion of random error sources in the uncertainty. The near-field uncertainty was propagated to the ground level, along with additional uncertainty in the propagation modeling. Estimates of perceived loudness were obtained for the various types of uncertainty representation in the near-field. Analyses were performed on three configurations of interest to the sonic boom community: the SEEB-ALR, the 69o DeltaWing, and the LM 1021-01. Results showed that representation of the near-field uncertainty plays a key role in ground noise predictions. Using a Fourier series based dispersion approach can double the amount of uncertainty in the ground noise compared to a pure bias representation. Compared to previous computational fluid dynamics results, uncertainty in ground noise predictions were greater when considering the near-field experimental uncertainty.

A Neurosemantic Theory of Concrete Noun Representation Based on the Underlying Brain Codes

PubMed Central

Just, Marcel Adam; Cherkassky, Vladimir L.; Aryal, Sandesh; Mitchell, Tom M.

2010-01-01

This article describes the discovery of a set of biologically-driven semantic dimensions underlying the neural representation of concrete nouns, and then demonstrates how a resulting theory of noun representation can be used to identify simple thoughts through their fMRI patterns. We use factor analysis of fMRI brain imaging data to reveal the biological representation of individual concrete nouns like apple, in the absence of any pictorial stimuli. From this analysis emerge three main semantic factors underpinning the neural representation of nouns naming physical objects, which we label manipulation, shelter, and eating. Each factor is neurally represented in 3–4 different brain locations that correspond to a cortical network that co-activates in non-linguistic tasks, such as tool use pantomime for the manipulation factor. Several converging methods, such as the use of behavioral ratings of word meaning and text corpus characteristics, provide independent evidence of the centrality of these factors to the representations. The factors are then used with machine learning classifier techniques to show that the fMRI-measured brain representation of an individual concrete noun like apple can be identified with good accuracy from among 60 candidate words, using only the fMRI activity in the 16 locations associated with these factors. To further demonstrate the generativity of the proposed account, a theory-based model is developed to predict the brain activation patterns for words to which the algorithm has not been previously exposed. The methods, findings, and theory constitute a new approach of using brain activity for understanding how object concepts are represented in the mind. PMID:20084104

A neurosemantic theory of concrete noun representation based on the underlying brain codes.

PubMed

Just, Marcel Adam; Cherkassky, Vladimir L; Aryal, Sandesh; Mitchell, Tom M

2010-01-13

This article describes the discovery of a set of biologically-driven semantic dimensions underlying the neural representation of concrete nouns, and then demonstrates how a resulting theory of noun representation can be used to identify simple thoughts through their fMRI patterns. We use factor analysis of fMRI brain imaging data to reveal the biological representation of individual concrete nouns like apple, in the absence of any pictorial stimuli. From this analysis emerge three main semantic factors underpinning the neural representation of nouns naming physical objects, which we label manipulation, shelter, and eating. Each factor is neurally represented in 3-4 different brain locations that correspond to a cortical network that co-activates in non-linguistic tasks, such as tool use pantomime for the manipulation factor. Several converging methods, such as the use of behavioral ratings of word meaning and text corpus characteristics, provide independent evidence of the centrality of these factors to the representations. The factors are then used with machine learning classifier techniques to show that the fMRI-measured brain representation of an individual concrete noun like apple can be identified with good accuracy from among 60 candidate words, using only the fMRI activity in the 16 locations associated with these factors. To further demonstrate the generativity of the proposed account, a theory-based model is developed to predict the brain activation patterns for words to which the algorithm has not been previously exposed. The methods, findings, and theory constitute a new approach of using brain activity for understanding how object concepts are represented in the mind.

Mobile visual object identification: from SIFT-BoF-RANSAC to Sketchprint

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Diephuis, Maurits; Holotyak, Taras

2015-03-01

Mobile object identification based on its visual features find many applications in the interaction with physical objects and security. Discriminative and robust content representation plays a central role in object and content identification. Complex post-processing methods are used to compress descriptors and their geometrical information, aggregate them into more compact and discriminative representations and finally re-rank the results based on the similarity geometries of descriptors. Unfortunately, most of the existing descriptors are not very robust and discriminative once applied to the various contend such as real images, text or noise-like microstructures next to requiring at least 500-1'000 descriptors per image for reliable identification. At the same time, the geometric re-ranking procedures are still too complex to be applied to the numerous candidates obtained from the feature similarity based search only. This restricts that list of candidates to be less than 1'000 which obviously causes a higher probability of miss. In addition, the security and privacy of content representation has become a hot research topic in multimedia and security communities. In this paper, we introduce a new framework for non- local content representation based on SketchPrint descriptors. It extends the properties of local descriptors to a more informative and discriminative, yet geometrically invariant content representation. In particular it allows images to be compactly represented by 100 SketchPrint descriptors without being fully dependent on re-ranking methods. We consider several use cases, applying SketchPrint descriptors to natural images, text documents, packages and micro-structures and compare them with the traditional local descriptors.

Analytical learning and term-rewriting systems

NASA Technical Reports Server (NTRS)

Laird, Philip; Gamble, Evan

1990-01-01

Analytical learning is a set of machine learning techniques for revising the representation of a theory based on a small set of examples of that theory. When the representation of the theory is correct and complete but perhaps inefficient, an important objective of such analysis is to improve the computational efficiency of the representation. Several algorithms with this purpose have been suggested, most of which are closely tied to a first order logical language and are variants of goal regression, such as the familiar explanation based generalization (EBG) procedure. But because predicate calculus is a poor representation for some domains, these learning algorithms are extended to apply to other computational models. It is shown that the goal regression technique applies to a large family of programming languages, all based on a kind of term rewriting system. Included in this family are three language families of importance to artificial intelligence: logic programming, such as Prolog; lambda calculus, such as LISP; and combinatorial based languages, such as FP. A new analytical learning algorithm, AL-2, is exhibited that learns from success but is otherwise quite different from EBG. These results suggest that term rewriting systems are a good framework for analytical learning research in general, and that further research should be directed toward developing new techniques.

Internal representations for face detection: an application of noise-based image classification to BOLD responses.

PubMed

Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

2013-11-01

What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

Analysis of genomic sequences by Chaos Game Representation.

PubMed

Almeida, J S; Carriço, J A; Maretzek, A; Noble, P A; Fletcher, M

2001-05-01

Chaos Game Representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to find the coordinates for their position in a continuous space. This distribution of positions has two properties: it is unique, and the source sequence can be recovered from the coordinates such that distance between positions measures similarity between the corresponding sequences. The possibility of using the latter property to identify succession schemes have been entirely overlooked in previous studies which raises the possibility that CGR may be upgraded from a mere representation technique to a sequence modeling tool. The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.

General tensor discriminant analysis and gabor features for gait recognition.

PubMed

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 state of the art classification methods in gait recognition.

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Electrophysiological evidence for parts and wholes in visual face memory.

PubMed

Towler, John; Eimer, Martin

2016-10-01

It is often assumed that upright faces are represented in a holistic fashion, while representations of inverted faces are essentially part-based. To assess this hypothesis, we recorded event-related potentials (ERPs) during a sequential face identity matching task where successively presented pairs of upright or inverted faces were either identical or differed with respect to their internal features, their external features, or both. Participants' task was to report on each trial whether the face pair was identical or different. To track the activation of visual face memory representations, we measured N250r components that emerge over posterior face-selective regions during the activation of visual face memory representations by a successful identity match. N250r components to full identity repetitions were smaller and emerged later for inverted as compared to upright faces, demonstrating that image inversion impairs face identity matching processes. For upright faces, N250r components were also elicited by partial repetitions of external or internal features, which suggest that the underlying identity matching processes are not exclusively based on non-decomposable holistic representations. However, the N250r to full identity repetitions was super-additive (i.e., larger than the sum of the two N250r components to partial repetitions of external or internal features) for upright faces, demonstrating that holistic representations were involved in identity matching processes. For inverted faces, N250r components to full and partial identity repetitions were strictly additive, indicating that the identity matching of external and internal features operated in an entirely part-based fashion. These results provide new electrophysiological evidence for qualitative differences between representations of upright and inverted faces in the occipital-temporal face processing system. Copyright © 2016 Elsevier Ltd. All rights reserved.

Basic-level and superordinate-like categorical representations in early infancy.

PubMed

Behl-Chadha, G

1996-08-01

A series of experiments using the paired-preference procedure examined 3- to 4-month-old infants' ability to form perceptually based categorical representations in the domains of natural kinds and artifacts and probed the underlying organizational structure of these representations. Experiments 1 and 2 found that infants could form categorical representations for chairs that excluded exemplars of couches, beds, and tables and also for couches that excluded exemplars of chairs, beds, and tables. Thus, the adult-like exclusivity shown by infants in the categorization of various animal pictures at the basic-level extends to the domain of artifacts as well--an ecologically significant ability given the numerous artifacts that populate the human environment. Experiments 3 and 4 examined infants' ability to form superordinate-like or global categorical representations for mammals and furniture. It was found that infants could form a global representation for mammals that included novel mammals and excluded other non-mammalian animals such as birds and fish as well as items from cross-ontological categories such as furniture. In addition, it was found that infants formed a representation for furniture that included novel categories of furniture and excluded exemplars from the cross-ontological category of mammals; however, it was less clear if infants' global representation for furniture also excluded other artifacts such as vehicles and thus the category of furniture may have been less exclusively represented. Overall, the present findings, by showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, underscore the importance of these early representations for later conceptual representations.

EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria.

PubMed

Boland, Mary Regina; Tu, Samson W; Carini, Simona; Sim, Ida; Weng, Chunhua

2012-01-01

Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation requirements of eligibility criteria by reviewing 100 temporal criteria. We developed EliXR-TIME, a frame-based representation designed to support semantic annotation for temporal expressions in eligibility criteria by reusing applicable classes from well-known clinical temporal knowledge representations. We used EliXR-TIME to analyze a training set of 50 new temporal eligibility criteria. We evaluated EliXR-TIME using an additional random sample of 20 eligibility criteria with temporal expressions that have no overlap with the training data, yielding 92.7% (76 / 82) inter-coder agreement on sentence chunking and 72% (72 / 100) agreement on semantic annotation. We conclude that this knowledge representation can facilitate semantic annotation of the temporal expressions in eligibility criteria.

The Effect of Two-dimensional and Stereoscopic Presentation on Middle School Students' Performance of Spatial Cognition Tasks

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, Hee-Sun

2010-02-01

We investigated whether and how student performance on three types of spatial cognition tasks differs when worked with two-dimensional or stereoscopic representations. We recruited nineteen middle school students visiting a planetarium in a large Midwestern American city and analyzed their performance on a series of spatial cognition tasks in terms of response accuracy and task completion time. Results show that response accuracy did not differ between the two types of representations while task completion time was significantly greater with the stereoscopic representations. The completion time increased as the number of mental manipulations of 3D objects increased in the tasks. Post-interviews provide evidence that some students continued to think of stereoscopic representations as two-dimensional. Based on cognitive load and cue theories, we interpret that, in the absence of pictorial depth cues, students may need more time to be familiar with stereoscopic representations for optimal performance. In light of these results, we discuss potential uses of stereoscopic representations for science learning.

Associations between early caregiving and rural, low-SES, African-American children's representations of attachment relationships.

PubMed

Brown, Geoffrey L; Gustafsson, Hanna C; Mills-Koonce, W Roger; Cox, Martha J

2017-08-01

Little research has examined the legacy of early maternal care for later attachment representations among low-income and ethnic minority school-aged children. Using data from a sample of 276 rural, low-income, African-American families, this study examined associations between maternal care in infancy and children's representations of attachment figures in middle childhood. Maternal care was coded from 10-min home-based observations at 6, 15, and 24 months of age. Representations of attachment figures were assessed using the Manchester Child Attachment Story Task at 6 years of age. Sensitive maternal care in infancy was not significantly related to attachment security or episodic disorganized behaviors in children's representations. However, children exposed to more harsh-intrusive parenting during infancy displayed less secure representations of attachment figures in middle childhood and more episodic disorganized behaviors, even after controlling for numerous child and family contextual covariates. Findings inform conceptualizations of attachment formation among rural, low-income, African-American parent-child dyads.

Representing the Electromagnetic Field: How Maxwell's Mathematics Empowered Faraday's Field Theory

NASA Astrophysics Data System (ADS)

Tweney, Ryan D.

2011-07-01

James Clerk Maxwell `translated' Michael Faraday's experimentally-based field theory into the mathematical representation now known as `Maxwell's Equations.' Working with a variety of mathematical representations and physical models Maxwell extended the reach of Faraday's theory and brought it into consistency with other results in the physics of electricity and magnetism. Examination of Maxwell's procedures opens many issues about the role of mathematical representation in physics and the learning background required for its success. Specifically, Maxwell's training in `Cambridge University' mathematical physics emphasized the use of analogous equations across fields of physics and the repeated solving of extremely difficult problems in physics. Such training develops an array of overlearned mathematical representations supported by highly sophisticated cognitive mechanisms for the retrieval of relevant information from long term memory. For Maxwell, mathematics constituted a new form of representation in physics, enhancing the formal derivational and calculational role of mathematics and opening a cognitive means for the conduct of `experiments in the mind' and for sophisticated representations of theory.

Tool-use: An open window into body representation and its plasticity

PubMed Central

Martel, Marie; Cardinali, Lucilla; Roy, Alice C.; Farnè, Alessandro

2016-01-01

ABSTRACT Over the last decades, scientists have questioned the origin of the exquisite human mastery of tools. Seminal studies in monkeys, healthy participants and brain-damaged patients have primarily focused on the plastic changes that tool-use induces on spatial representations. More recently, we focused on the modifications tool-use must exert on the sensorimotor system and highlighted plastic changes at the level of the body representation used by the brain to control our movements, i.e., the Body Schema. Evidence is emerging for tool-use to affect also more visually and conceptually based representations of the body, such as the Body Image. Here we offer a critical review of the way different tool-use paradigms have been, and should be, used to try disentangling the critical features that are responsible for tool incorporation into different body representations. We will conclude that tool-use may offer a very valuable means to investigate high-order body representations and their plasticity. PMID:27315277

Tracing Growth of Teachers' Classroom Interactions with Representations of Functions in the Connected Classroom

NASA Astrophysics Data System (ADS)

Morton, Brian Lee

The purpose of this study is to create an empirically based theoretic model of change of the use and treatment of representations of functions with the use of Connected Classroom Technology (CCT) using data previously collected for the Classroom Connectivity in Promoting Mathematics and Science Achievement (CCMS) project. Qualitative analysis of videotapes of three algebra teachers' instruction focused on different categories thought to influence teaching representations with technology: representations, discourse, technology, and decisions. Models for rating teachers low, medium, or high for each of these categories were created using a priori codes and grounded methodology. A cross case analysis was conducted after the completion of the case studies by comparing and contrasting the three cases. Data revealed that teachers' decisions shifted to incorporate the difference in student ideas/representations made visible by the CCT into their instruction and ultimately altered their orientation to mathematics teaching. The shift in orientation seemed to lead to the teachers' growth with regards to representations, discourse, and technology.

Tool-use: An open window into body representation and its plasticity.

PubMed

Martel, Marie; Cardinali, Lucilla; Roy, Alice C; Farnè, Alessandro

2016-01-01

Over the last decades, scientists have questioned the origin of the exquisite human mastery of tools. Seminal studies in monkeys, healthy participants and brain-damaged patients have primarily focused on the plastic changes that tool-use induces on spatial representations. More recently, we focused on the modifications tool-use must exert on the sensorimotor system and highlighted plastic changes at the level of the body representation used by the brain to control our movements, i.e., the Body Schema. Evidence is emerging for tool-use to affect also more visually and conceptually based representations of the body, such as the Body Image. Here we offer a critical review of the way different tool-use paradigms have been, and should be, used to try disentangling the critical features that are responsible for tool incorporation into different body representations. We will conclude that tool-use may offer a very valuable means to investigate high-order body representations and their plasticity.

Continous Representation Learning via User Feedback

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

Representation learning is a deep-learning based technique for extracting features from data for the purpose of machine learning. This requires a large amount of data, on order tens of thousands to millions of samples, to properly teach the deep neural network. This a system for continuous representation learning, where the system may be improved with a small number of additional samples (order 10-100). The unique characteristics of this invention include a human-computer feedback component, where assess the quality of the current representation and then provides a better representation to the system. The system then mixes the new data with oldmore » training examples to avoid overfitting and improve overall performance of the system. The model can be exported and shared with other users, and it may be applied to additional images the system hasn't seen before.« less

Attachment to Mother and Father at Transition to Middle Childhood.

PubMed

Di Folco, Simona; Messina, Serena; Zavattini, Giulio Cesare; Psouni, Elia

2017-01-01

The present study investigated concordance between representations of attachment to mother and attachment to father, and convergence between two narrative-based methods addressing these representations in middle childhood: the Manchester Child Attachment Story Task (MCAST) and the Secure Base Script Test (SBST). One hundred and twenty 6-year-old children were assessed by separate administrations of the MCAST for mother and father, respectively, and results showed concordance of representations of attachment to mother and attachment to father at age 6.5 years. 75 children were additionally tested about 12 months later, with the SBST, which assesses scripted knowledge of secure base (and safe haven), not differentiating between mother and father attachment relationships. Concerning attachment to father, dichotomous classifications (MCAST) and a continuous dimension capturing scripted secure base knowledge (MCAST) converged with secure base scriptedness (SBST), yet we could not show the same pattern of convergence concerning attachment to mother. Results suggest some convergence between the two narrative methods of assessment of secure base script but also highlight complications when using the MCAST for measuring attachment to father in middle childhood.

The application of brain-based learning principles aided by GeoGebra to improve mathematical representation ability

NASA Astrophysics Data System (ADS)

Priatna, Nanang

2017-08-01

The use of Information and Communication Technology (ICT) in mathematics instruction will help students in building conceptual understanding. One of the software products used in mathematics instruction is GeoGebra. The program enables simple visualization of complex geometric concepts and helps improve students' understanding of geometric concepts. Instruction applying brain-based learning principles is one oriented at the efforts of naturally empowering the brain potentials which enable students to build their own knowledge. One of the goals of mathematics instruction in school is to develop mathematical communication ability. Mathematical representation is regarded as a part of mathematical communication. It is a description, expression, symbolization, or modeling of mathematical ideas/concepts as an attempt of clarifying meanings or seeking for solutions to the problems encountered by students. The research aims to develop a learning model and teaching materials by applying the principles of brain-based learning aided by GeoGebra to improve junior high school students' mathematical representation ability. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2x3 factorial model. Based on analysis of the data, it is found that the increase in the mathematical representation ability of students who were treated with mathematics instruction applying the brain-based learning principles aided by GeoGebra was greater than the increase of the students given conventional instruction, both as a whole and based on the categories of students' initial mathematical ability.

Implementation multi representation and oral communication skills in Department of Physics Education on Elementary Physics II

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

Kusumawati, Intan, E-mail: intankusumawati10@gmail.com; Marwoto, Putut, E-mail: pmarwoto@yahoo.com; Linuwih, Suharto, E-mail: suhartolinuwih@gmail.com

The ability of multi representation has been widely studied, but there has been no implementation through a model of learning. This study aimed to determine the ability of the students multi representation, relationships multi representation capabilities and oral communication skills, as well as the application of the relations between the two capabilities through learning model Presentatif Based on Multi representation (PBM) in solving optical geometric (Elementary Physics II). A concurrent mixed methods research methods with qualitative–quantitative weights. Means of collecting data in the form of the pre-test and post-test with essay form, observation sheets oral communication skills, and assessment ofmore » learning by observation sheet PBM–learning models all have a high degree of respectively validity category is 3.91; 4.22; 4.13; 3.88. Test reliability with Alpha Cronbach technique, reliability coefficient of 0.494. The students are department of Physics Education Unnes as a research subject. Sequence multi representation tendency of students from high to low in sequence, representation of M, D, G, V; whereas the order of accuracy, the group representation V, D, G, M. Relationship multi representation ability and oral communication skills, comparable/proportional. Implementation conjunction generate grounded theory. This study should be applied to the physics of matter, or any other university for comparison.« less

Indicators that influence prospective mathematics teachers representational and reasoning abilities

NASA Astrophysics Data System (ADS)

Darta; Saputra, J.

2018-01-01

Representational and mathematical reasoning ability are very important ability as basic in mathematics learning process. The 2013 curriculum suggests that the use of a scientific approach emphasizes higher order thinking skills. Therefore, a scientific approach is required in mathematics learning to improve ability of representation and mathematical reasoning. The objectives of this research are: (1) to analyze representational and reasoning abilities, (2) to analyze indicators affecting the ability of representation and mathematical reasoning, (3) to analyze scientific approaches that can improve the ability of representation and mathematical reasoning. The subject of this research is the students of mathematics prospective teachers in the first semester at Private Higher Education of Bandung City. The research method of this research was descriptive analysis. The research data were collected using reasoning and representation tests on sixty-one students. Data processing was done by descriptive analysis specified based on the indicators of representation ability and mathematical reasoning that influenced it. The results of this first-year study showed that students still had many weaknesses in reasoning and mathematical representation that were influenced by the ability to understand the indicators of both capabilities. After observing the results of the first-year research, then in the second and third year, the development of teaching materials with a scientific approach in accordance with the needs of prospective students was planned.

The visual representations of motion and of gravity are functionally independent: Evidence of a differential effect of smooth pursuit eye movements.

PubMed

De Sá Teixeira, Nuno Alexandre

2016-09-01

The memory for the final position of a moving object which suddenly disappears has been found to be displaced forward, in the direction of motion, and downwards, in the direction of gravity. These phenomena were coined, respectively, Representational Momentum and Representational Gravity. Although both these and similar effects have been systematically linked with the functioning of internal representations of physical variables (e.g. momentum and gravity), serious doubts have been raised for a cognitively based interpretation, favouring instead a major role of oculomotor and perceptual factors which, more often than not, were left uncontrolled and even ignored. The present work aims to determine the degree to which Representational Momentum and Representational Gravity are epiphenomenal to smooth pursuit eye movements. Observers were required to indicate the offset locations of targets moving along systematically varied directions after a variable imposed retention interval. Each participant completed the task twice, varying the eye movements' instructions: gaze was either constrained or left free to track the targets. A Fourier decomposition analysis of the localization responses was used to disentangle both phenomena. The results show unambiguously that constraining eye movements significantly eliminates the harmonic components which index Representational Momentum, but have no effect on Representational Gravity or its time course. The found outcomes offer promising prospects for the study of the visual representation of gravity and its neurological substrates.

Vertex Space Analysis for Model-Based Target Recognition.

DTIC Science & Technology

1996-08-01

performed in our unique invariant representation, Vertex Space, that reduces both the dimensionality and size of the required search space. Vertex Space ... mapping results in a reduced representation that serves as a characteristic target signature which is invariant to four of the six viewing geometry

Behind Closed Doors: The Pedagogy and Interventionist Practice of Digital Storytelling

ERIC Educational Resources Information Center

Eisenhauer, Jennifer

2012-01-01

Through arts-based research and digital storytelling, the author investigates the representation of psychiatric disabilities in this article and proposes that digital storytelling can be an interventionist artistic and pedagogical process through which to challenge dominant stigmatizing representations of psychiatric disability.

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE PAGES

Fierce, Laura; McGraw, Robert L.

2017-07-26

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

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

Fierce, Laura; McGraw, Robert L.

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

The secure base script and the task of caring for elderly parents: implications for attachment theory and clinical practice.

PubMed

Chen, Cory K; Waters, Harriet Salatas; Hartman, Marilyn; Zimmerman, Sheryl; Miklowitz, David J; Waters, Everett

2013-01-01

This study explores links between adults' attachment representations and the task of caring for elderly parents with dementia. Participants were 87 adults serving as primary caregivers of a parent or parent-in-law with dementia. Waters and Waters' ( 2006 ) Attachment Script Assessment was adapted to assess script-like attachment representation in the context of caring for their elderly parent. The quality of adult-elderly parent interactions was assessed using the Level of Expressed Emotions Scale (Cole & Kazarian, 1988 ) and self-report measures of caregivers' perception of caregiving as difficult. Caregivers' secure base script knowledge predicted lower levels of negative expressed emotion. This effect was moderated by the extent to which participants experienced caring for elderly parents as difficult. Attachment representations played a greater role in caregiving when caregiving tasks were perceived as more difficult. These results support the hypothesis that attachment representations influence the quality of care that adults provide their elderly parents. Clinical implications are discussed.

Feature-based attentional weighting and spreading in visual working memory

PubMed Central

Niklaus, Marcel; Nobre, Anna C.; van Ede, Freek

2017-01-01

Attention can be directed at features and feature dimensions to facilitate perception. Here, we investigated whether feature-based-attention (FBA) can also dynamically weight feature-specific representations within multi-feature objects held in visual working memory (VWM). Across three experiments, participants retained coloured arrows in working memory and, during the delay, were cued to either the colour or the orientation dimension. We show that directing attention towards a feature dimension (1) improves the performance in the cued feature dimension at the expense of the uncued dimension, (2) is more efficient if directed to the same rather than to different dimensions for different objects, and (3) at least for colour, automatically spreads to the colour representation of non-attended objects in VWM. We conclude that FBA also continues to operate on VWM representations (with similar principles that govern FBA in the perceptual domain) and challenge the classical view that VWM representations are stored solely as integrated objects. PMID:28233830

Computational models of location-invariant orthographic processing

NASA Astrophysics Data System (ADS)

Dandurand, Frédéric; Hannagan, Thomas; Grainger, Jonathan

2013-03-01

We trained three topologies of backpropagation neural networks to discriminate 2000 words (lexical representations) presented at different positions of a horizontal letter array. The first topology (zero-deck) contains no hidden layer, the second (one-deck) has a single hidden layer, and for the last topology (two-deck), the task is divided in two subtasks implemented as two stacked neural networks, with explicit word-centred letters as intermediate representations. All topologies successfully simulated two key benchmark phenomena observed in skilled human reading: transposed-letter priming and relative-position priming. However, the two-deck topology most accurately simulated the ability to discriminate words from nonwords, while containing the fewest connection weights. We analysed the internal representations after training. Zero-deck networks implement a letter-based scheme with a position bias to differentiate anagrams. One-deck networks implement a holographic overlap coding in which representations are essentially letter-based and words are linear combinations of letters. Two-deck networks also implement holographic-coding.

Optical linear algebra processors - Architectures and algorithms

NASA Technical Reports Server (NTRS)

Casasent, David

1986-01-01

Attention is given to the component design and optical configuration features of a generic optical linear algebra processor (OLAP) architecture, as well as the large number of OLAP architectures, number representations, algorithms and applications encountered in current literature. Number-representation issues associated with bipolar and complex-valued data representations, high-accuracy (including floating point) performance, and the base or radix to be employed, are discussed, together with case studies on a space-integrating frequency-multiplexed architecture and a hybrid space-integrating and time-integrating multichannel architecture.

Semantic representation of CDC-PHIN vocabulary using Simple Knowledge Organization System.

PubMed

Zhu, Min; Mirhaji, Parsa

2008-11-06

PHIN Vocabulary Access and Distribution System (VADS) promotes the use of standards based vocabulary within CDC information systems. However, the current PHIN vocabulary representation hinders its wide adoption. Simple Knowledge Organization System (SKOS) is a W3C draft specification to support the formal representation of Knowledge Organization Systems (KOS) within the framework of the Semantic Web. We present a method of adopting SKOS to represent PHIN vocabulary in order to enable automated information sharing and integration.

A Model-based Approach to Reactive Self-Configuring Systems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Nayak, P. Pandurang

1996-01-01

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

H-SLAM: Rao-Blackwellized Particle Filter SLAM Using Hilbert Maps.

PubMed

Vallicrosa, Guillem; Ridao, Pere

2018-05-01

Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running online.

Speeded Probed Recall Is Affected by Grouping.

PubMed

Morra, Sergio; Epidendio, Valentina

2015-01-01

Most of the evidence from previous studies on speeded probed recall supported primacy-gradient models of serial order representation. Two experiments investigated the effect of grouping on speeded probed recall. Six-word lists, followed by a number between 1 and 6, were presented for speeded recall of the word in the position indicated by the number. Grouping was manipulated through interstimulus intervals. In both experiments, a significant Position × Grouping interaction was found in RT. It is concluded that the results are not consistent with models of order representation only based on a primacy gradient. Possible alternative representations of serial order are also discussed; a case is made for a holistic order representation.

Contingent plan structures for spacecraft

NASA Technical Reports Server (NTRS)

Drummond, M.; Currie, K.; Tate, A.

1987-01-01

Most current AI planners build partially ordered plan structures which delay decisions on action ordering. Such structures cannot easily represent contingent actions. A representation which can is presented. The representation has some other useful features: it provides a good account of the causal structure of a plan, can be used to describe disjunctive actions, and it offers a planner the opportunity of even less commitment than the classical partial order on actions. The use of this representation is demonstrated in an on-board spacecraft activity sequencing problem. Contingent plan execution in a spacecraft context highlights the requirements for a fully disjunctive representation, since communication delays often prohibit extensive ground-based accounting for remotely sensed information and replanning on execution failure.

Social representations about religion and spirituality.

PubMed

Borges, Moema da Silva; Santos, Marília Borges Couto; Pinheiro, Tiago Gomes

2015-01-01

to identify the social representations about the concepts of spirituality and religion of of health teachers. exploratory and descriptive study, based on a qualitative approach. 25 subjects participated in it. The following instruments were used to collect data: questionnaire to identify the profile; questionnaire of free association, whose inducing words were religion and spirituality, and an interview based on the scale FICA (Puchalski, 2006). the representations about religion and spirituality, for professors, are forged around the faith in God and it gives them meaning and purpose to deal with the challenges of personal and professional living. there are still barriers that need to be overcome with a view to a comprehensive care. For this, it is essential to incorporate spirituality in the process in the curricula of health courses.

LETTER TO THE EDITOR: Landau levels on the hyperbolic plane

NASA Astrophysics Data System (ADS)

Fakhri, H.; Shariati, M.

2004-11-01

The quantum states of a spinless charged particle on a hyperbolic plane in the presence of a uniform magnetic field with a generalized quantization condition are proved to be the bases of the irreducible Hilbert representation spaces of the Lie algebra u(1, 1). The dynamical symmetry group U(1, 1) with the explicit form of the Lie algebra generators is extracted. It is also shown that the energy has an infinite-fold degeneracy in each of the representation spaces which are allocated to the different values of the magnetic field strength. Based on the simultaneous shift of two parameters, it is also noted that the quantum states realize the representations of Lie algebra u(2) by shifting the magnetic field strength.

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

PubMed

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

Good-enough linguistic representations and online cognitive equilibrium in language processing.

PubMed

Karimi, Hossein; Ferreira, Fernanda

2016-01-01

We review previous research showing that representations formed during language processing are sometimes just "good enough" for the task at hand and propose the "online cognitive equilibrium" hypothesis as the driving force behind the formation of good-enough representations in language processing. Based on this view, we assume that the language comprehension system by default prefers to achieve as early as possible and remain as long as possible in a state of cognitive equilibrium where linguistic representations are successfully incorporated with existing knowledge structures (i.e., schemata) so that a meaningful and coherent overall representation is formed, and uncertainty is resolved or at least minimized. We also argue that the online equilibrium hypothesis is consistent with current theories of language processing, which maintain that linguistic representations are formed through a complex interplay between simple heuristics and deep syntactic algorithms and also theories that hold that linguistic representations are often incomplete and lacking in detail. We also propose a model of language processing that makes use of both heuristic and algorithmic processing, is sensitive to online cognitive equilibrium, and, we argue, is capable of explaining the formation of underspecified representations. We review previous findings providing evidence for underspecification in relation to this hypothesis and the associated language processing model and argue that most of these findings are compatible with them.