SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

Directory of Open Access Journals (Sweden)

Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

Directory of Open Access Journals (Sweden)

Xiangwei Xing

2014-01-01

Full Text Available 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.

Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA

Directory of Open Access Journals (Sweden)

Shunfang Wang

2015-12-01

Full Text Available An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC, pseudo-amino acid composition (PseAAC and position specific scoring matrix (PSSM, are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

Convolution-based classification of audio and symbolic representations of music

DEFF Research Database (Denmark)

Velarde, Gissel; Cancino Chacón, Carlos; Meredith, David

2018-01-01

We present a novel convolution-based method for classification of audio and symbolic representations of music, which we apply to classification of music by style. Pieces of music are first sampled to pitch–time representations (piano-rolls or spectrograms) and then convolved with a Gaussian filter......-class composer identification, methods specialised for classifying symbolic representations of music are more effective. We also performed experiments on symbolic representations, synthetic audio and two different recordings of The Well-Tempered Clavier by J. S. Bach to study the method’s capacity to distinguish...

Learning word vector representations based on acoustic counts

OpenAIRE

Ribeiro, Sam; Watts, Oliver; Yamagishi, Junichi

2017-01-01

This paper presents a simple count-based approach to learning word vector representations by leveraging statistics of cooccurrences between text and speech. This type of representation requires two discrete sequences of units defined across modalities. Two possible methods for the discretization of an acoustic signal are presented, which are then applied to fundamental frequency and energy contours of a transcribed corpus of speech, yielding a sequence of textual objects (e.g. words, syllable...

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs

Representations of space based on haptic input

NARCIS (Netherlands)

Zuidhoek, S.

2005-01-01

The present thesis focused on the representations of grasping space based on haptic input. We aimed at identifying their characteristics, and the underlying neurocognitive processes and mechanisms. To this end, we studied the systematic distortions in performance on several orientation perception

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction

PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

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Xingxing Zhu

2018-05-01

Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

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

Science.gov (United States)

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…

Prototype Theory Based Feature Representation for PolSAR Images

OpenAIRE

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

2016-01-01

This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

3D ear identification based on sparse representation.

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Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

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

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Qi Jia

2015-03-01

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

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

Science.gov (United States)

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.

Group representations, error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E

1996-01-01

This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

Conformal-Based Surface Morphing and Multi-Scale Representation

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Ka Chun Lam

2014-05-01

Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.

Acids and bases solvent effects on acid-base strenght

CERN Document Server

Cox, Brian G

2013-01-01

Acids and bases are ubiquitous in chemistry. Our understanding of them, however, is dominated by their behaviour in water. Transfer to non-aqueous solvents leads to profound changes in acid-base strengths and to the rates and equilibria of many processes: for example, synthetic reactions involving acids, bases and nucleophiles; isolation of pharmaceutical actives through salt formation; formation of zwitter- ions in amino acids; and chromatographic separation of substrates. This book seeks to enhance our understanding of acids and bases by reviewing and analysing their behaviour in non-aqueous solvents. The behaviour is related where possible to that in water, but correlations and contrasts between solvents are also presented.

Knowledge representation and knowledge base design for operator advisor system

International Nuclear Information System (INIS)

Hangos, K.M.; Sziano, T.; Tapolcai, L.

1990-01-01

The problems of knowledge representation, knowledge base handling and design has been described for an Operator Advisor System in the Paks Nuclear Power Plant. The Operator Advisor System is to be implemented as a part of the 5th and 6th unit. The knowledge of the Operator Advisor system is described by a few elementary knowledge items (diagnostic event functions, fault graph, action trees), weighted directed graphs have been found as their common structure. List-type and relational representation of these graphs have been used for the on-line and off-line part of the knowledge base respectively. A uniform data base design and handling has been proposed which consists of a design system, a knowledge base editor and a knowledge base compiler

Order-based representation in random networks of cortical neurons.

Directory of Open Access Journals (Sweden)

Goded Shahaf

2008-11-01

Full Text Available The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Learning connective-based word representations for implicit discourse relation identification

DEFF Research Database (Denmark)

Braud, Chloé Elodie; Denis, Pascal

2016-01-01

We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represen...... their simplicity, these connective-based rep-resentations outperform various off-the-shelf word embeddings, and achieve state-of-the-art performance on this problem.......We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represent...... words in the space of discourse connectives as a way to directly encode their rhetorical function. Experiments on the Penn Discourse Treebank demonstrate the effectiveness of these task-tailored repre-sentations in predicting implicit discourse re-lations. Our results indeed show that, despite...

Towards Web-based representation and processing of health information

DEFF Research Database (Denmark)

Gao, S.; Mioc, Darka; Yi, X.L.

2009-01-01

facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC) services. It brought a new solution in better health data representation and initial exploration of the Web-based processing of health information. Conclusion: The designed......Background: There is great concern within health surveillance, on how to grapple with environmental degradation, rapid urbanization, population mobility and growth. The Internet has emerged as an efficient way to share health information, enabling users to access and understand data....... For the representation of health information through Web-mapping applications, there still lacks a standard format to accommodate all fixed (such as location) and variable (such as age, gender, health outcome, etc) indicators in the representation of health information. Furthermore, net-centric computing has not been...

Reference Frame Fields based on Quantum Theory Representations of Real and Complex Numbers

OpenAIRE

Benioff, Paul

2007-01-01

A quantum theory representations of real (R) and complex (C) numbers is given that is based on states of single, finite strings of qukits for any base k > 1. Both unary representations and the possibility that qukits with k a prime number are elementary and the rest composite are discussed. Cauchy sequences of qukit string states are defined from the arithmetic properties. The representations of R and C, as equivalence classes of these sequences, differ from classical kit string state represe...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Teaching object concepts for XML-based representations.

Energy Technology Data Exchange (ETDEWEB)

Kelsey, R. L. (Robert L.)

2002-01-01

Students learned about object-oriented design concepts and knowledge representation through the use of a set of toy blocks. The blocks represented a limited and focused domain of knowledge and one that was physical and tangible. The blocks helped the students to better visualize, communicate, and understand the domain of knowledge as well as how to perform object decomposition. The blocks were further abstracted to an engineering design kit for water park design. This helped the students to work on techniques for abstraction and conceptualization. It also led the project from tangible exercises into software and programming exercises. Students employed XML to create object-based knowledge representations and Java to use the represented knowledge. The students developed and implemented software allowing a lay user to design and create their own water slide and then to take a simulated ride on their slide.

An Improved Information Hiding Method Based on Sparse Representation

Directory of Open Access Journals (Sweden)

Minghai Yao

2015-01-01

Full Text Available A novel biometric authentication information hiding method based on the sparse representation is proposed for enhancing the security of biometric information transmitted in the network. In order to make good use of abundant information of the cover image, the sparse representation method is adopted to exploit the correlation between the cover and biometric images. Thus, the biometric image is divided into two parts. The first part is the reconstructed image, and the other part is the residual image. The biometric authentication image cannot be restored by any one part. The residual image and sparse representation coefficients are embedded into the cover image. Then, for the sake of causing much less attention of attackers, the visual attention mechanism is employed to select embedding location and embedding sequence of secret information. Finally, the reversible watermarking algorithm based on histogram is utilized for embedding the secret information. For verifying the validity of the algorithm, the PolyU multispectral palmprint and the CASIA iris databases are used as biometric information. The experimental results show that the proposed method exhibits good security, invisibility, and high capacity.

Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations

DEFF Research Database (Denmark)

Endelt, Line Ørtoft

We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found using...... the minimization methods basis pursuit and best orthogonal basis. Visualizations of the time-frequency distribution are constructed based on a simplified energy distribution in the wavelet packet decomposition. The time-frequency distributions emphasizes structured musical content, including non-stationary content...

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

Directory of Open Access Journals (Sweden)

Bian Wu

2014-12-01

Full Text Available 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

Converting biomolecular modelling data based on an XML representation.

Science.gov (United States)

Sun, Yudong; McKeever, Steve

2008-08-25

Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

Converting Biomolecular Modelling Data Based on an XML Representation

Directory of Open Access Journals (Sweden)

Sun Yudong

2008-06-01

Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

A Description Logic Based Knowledge Representation Model for Concept Understanding

DEFF Research Database (Denmark)

Badie, Farshad

2017-01-01

This research employs Description Logics in order to focus on logical description and analysis of the phenomenon of ‘concept understanding’. The article will deal with a formal-semantic model for figuring out the underlying logical assumptions of ‘concept understanding’ in knowledge representation...... systems. In other words, it attempts to describe a theoretical model for concept understanding and to reflect the phenomenon of ‘concept understanding’ in terminological knowledge representation systems. Finally, it will design an ontology that schemes the structure of concept understanding based...

Energetic macroscopic representation and inversion-based control of a CVT-based HEV

NARCIS (Netherlands)

Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

2014-01-01

A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

Energetic macroscopic representation and inversion- based control of a CVT-based HEV

NARCIS (Netherlands)

Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

2013-01-01

A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

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Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

Science.gov (United States)

Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Video based object representation and classification using multiple covariance matrices.

Science.gov (United States)

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.

A Representation System User Interface for Knowledge Base Designers

OpenAIRE

Fikes, Richard E.

1982-01-01

A major strength of frame-based knowledge representation languages is their ability to provide the knowledge base designer with a concise and intuitively appealing means expression. The claim of intuitive appeal is based on the observation that the object -centered style of description provided by these languages often closely matches a designer's understanding of the domain being modeled and therefore lessens the burden of reformulation involved in developing a formal description. To be effe...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Refining the Construct of Classroom-Based Writing-from-Readings Assessment: The Role of Task Representation

Science.gov (United States)

Wolfersberger, Mark

2013-01-01

This article argues that task representation should be considered as part of the construct of classroom-based academic writing. Task representation is a process that writers move through when creating a unique mental model of the requirements for each new writing task they encounter. Writers' task representations evolve throughout the composing…

The Acid-Base Titration of a Very Weak Acid: Boric Acid

Science.gov (United States)

Celeste, M.; Azevedo, C.; Cavaleiro, Ana M. V.

2012-01-01

A laboratory experiment based on the titration of boric acid with strong base in the presence of d-mannitol is described. Boric acid is a very weak acid and direct titration with NaOH is not possible. An auxiliary reagent that contributes to the release of protons in a known stoichiometry facilitates the acid-base titration. Students obtain the…

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available 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.

Reexamining the language account of cross-national differences in base-10 number representations.

Science.gov (United States)

Vasilyeva, Marina; Laski, Elida V; Ermakova, Anna; Lai, Weng-Feng; Jeong, Yoonkyung; Hachigian, Amy

2015-01-01

East Asian students consistently outperform students from other nations in mathematics. One explanation for this advantage is a language account; East Asian languages, unlike most Western languages, provide cues about the base-10 structure of multi-digit numbers, facilitating the development of base-10 number representations. To test this view, the current study examined how kindergartners represented two-digit numbers using single unit-blocks and ten-blocks. The participants (N=272) were from four language groups (Korean, Mandarin, English, and Russian) that vary in the extent of "transparency" of the base-10 structure. In contrast to previous findings with older children, kindergartners showed no cross-language variability in the frequency of producing base-10 representations. Furthermore, they showed a pattern of within-language variability that was not consistent with the language account and was likely attributable to experiential factors. These findings suggest that language might not play as critical a role in the development of base-10 representations as suggested in earlier research. Copyright © 2014 Elsevier Inc. All rights reserved.

A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model

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Tao Chen

2015-08-01

Full Text Available In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

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

Science.gov (United States)

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.

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

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José Manuel Molina

2012-09-01

Full Text Available 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.

A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

DEFF Research Database (Denmark)

Srivastava, Shashank; Hovy, Dirk

2013-01-01

We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations......, such an approach captures both distributional semantic similarities among words as well as the structural relations between them (encoded as the structure of the parse tree). We show an efficient formulation to compute this kernel using simple matrix multiplication operations. We present our results on three...

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

Energy Technology Data Exchange (ETDEWEB)

Johnson, J. D. (Prostat, Mesa, AZ); Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

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 model 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.

Integration of object-oriented knowledge representation with the CLIPS rule based system

Science.gov (United States)

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.

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

Directory of Open Access Journals (Sweden)

Rui Sun

2016-08-01

Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

Multi-Label Classification Based on Low Rank Representation for Image Annotation

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Qiaoyu Tan

2017-01-01

Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

Science.gov (United States)

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

Features based approach for indexation and representation of unstructured Arabic documents

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Mohamed Salim El Bazzi

2017-06-01

Full Text Available The increase of textual information published in Arabic language on the internet, public libraries and administrations requires implementing effective techniques for the extraction of relevant information contained in large corpus of texts. The purpose of indexing is to create a document representation that easily find and identify the relevant information in a set of documents. However, mining textual data is becoming a complicated task, especially when taking semantic into consideration. In this paper, we will present an indexation system based on contextual representation that will take the advantage of semantic links given in a document. Our approach is based on the extraction of keyphrases. Then, each document is represented by its relevant keyphrases instead of its simple keywords. The experimental results confirms the effectiveness of our approach.

Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition

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Shirui Huo

2017-01-01

Full Text Available Human action recognition is an important recent challenging task. Projecting depth images onto three depth motion maps (DMMs and extracting deep convolutional neural network (DCNN features are discriminant descriptor features to characterize the spatiotemporal information of a specific action from a sequence of depth images. In this paper, a unified improved collaborative representation framework is proposed in which the probability that a test sample belongs to the collaborative subspace of all classes can be well defined and calculated. The improved collaborative representation classifier (ICRC based on l2-regularized for human action recognition is presented to maximize the likelihood that a test sample belongs to each class, then theoretical investigation into ICRC shows that it obtains a final classification by computing the likelihood for each class. Coupled with the DMMs and DCNN features, experiments on depth image-based action recognition, including MSRAction3D and MSRGesture3D datasets, demonstrate that the proposed approach successfully using a distance-based representation classifier achieves superior performance over the state-of-the-art methods, including SRC, CRC, and SVM.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers

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Ting Shu

2017-01-01

Full Text Available 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.

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

Science.gov (United States)

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.

Inadequacy representation of flamelet-based RANS model for turbulent non-premixed flame

Science.gov (United States)

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.

Alternative approach to nuclear data representation

International Nuclear Information System (INIS)

Pruet, J.; Brown, D.; Beck, B.; McNabb, D.P.

2006-01-01

This paper considers an approach for representing nuclear data that is qualitatively different from the approach currently adopted by the nuclear science community. Specifically, we examine a representation in which complicated data is described through collections of distinct and self-contained simple data structures. This structure-based representation is compared with the ENDF and ENDL formats, which can be roughly characterized as dictionary-based representations. A pilot data representation for replacing the format currently used at LLNL is presented. Examples are given as is a discussion of promises and shortcomings associated with moving from traditional dictionary-based formats to a structure-rich or class-like representation

The role of representation in experience-based choice

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Ben R. Newell

2009-12-01

Full Text Available Recently it has been observed that different choices can be made about structurally identical risky decisions depending on whether information about outcomes and their probabilities is learned by description or from experience. Current evidence is equivocal with respect to whether this choice ``gap'' is entirely an artefact of biased samples. The current experiment investigates whether a representational bias exists at the point of encoding by examining choice in light of decision makers' mental representations of the alternatives, measured with both verbal and nonverbal judgment probes. We found that, when estimates were gauged by the nonverbal probe, participants presented with information in description format (as opposed to experience had a greater tendency to overestimate rare events and underestimate common events. The choice gap, however, remained even when accounting for this judgment distortion and the effects of sampling bias. Indeed, participants' estimation of the outcome distribution did not mediate their subsequent choice. It appears that experience-based choices may derive from a process that does not explicitly use probability information.

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

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Jonathan C.W. Edwards

2016-09-01

Full Text Available It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with 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 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 emphasises the need for a ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an

Video rate morphological processor based on a redundant number representation

Science.gov (United States)

Kuczborski, Wojciech; Attikiouzel, Yianni; Crebbin, Gregory A.

1992-03-01

This paper presents a video rate morphological processor for automated visual inspection of printed circuit boards, integrated circuit masks, and other complex objects. Inspection algorithms are based on gray-scale mathematical morphology. Hardware complexity of the known methods of real-time implementation of gray-scale morphology--the umbra transform and the threshold decomposition--has prompted us to propose a novel technique which applied an arithmetic system without carrying propagation. After considering several arithmetic systems, a redundant number representation has been selected for implementation. Two options are analyzed here. The first is a pure signed digit number representation (SDNR) with the base of 4. The second option is a combination of the base-2 SDNR (to represent gray levels of images) and the conventional twos complement code (to represent gray levels of structuring elements). Operation principle of the morphological processor is based on the concept of the digit level systolic array. Individual processing units and small memory elements create a pipeline. The memory elements store current image windows (kernels). All operation primitives of processing units apply a unified direction of digit processing: most significant digit first (MSDF). The implementation technology is based on the field programmable gate arrays by Xilinx. This paper justified the rationality of a new approach to logic design, which is the decomposition of Boolean functions instead of Boolean minimization.

The first proton sponge-based amino acids: synthesis, acid-base properties and some reactivity.

Science.gov (United States)

Ozeryanskii, Valery A; Gorbacheva, Anastasia Yu; Pozharskii, Alexander F; Vlasenko, Marina P; Tereznikov, Alexander Yu; Chernov'yants, Margarita S

2015-08-21

The first hybrid base constructed from 1,8-bis(dimethylamino)naphthalene (proton sponge or DMAN) and glycine, N-methyl-N-(8-dimethylamino-1-naphthyl)aminoacetic acid, was synthesised in high yield and its hydrobromide was structurally characterised and used to determine the acid-base properties via potentiometric titration. It was found that the basic strength of the DMAN-glycine base (pKa = 11.57, H2O) is on the level of amidine amino acids like arginine and creatine and its structure, zwitterionic vs. neutral, based on the spectroscopic (IR, NMR, mass) and theoretical (DFT) approaches has a strong preference to the zwitterionic form. Unlike glycine, the DMAN-glycine zwitterion is N-chiral and is hydrolytically cleaved with the loss of glycolic acid on heating in DMSO. This reaction together with the mild decarboxylative conversion of proton sponge-based amino acids into 2,3-dihydroperimidinium salts under air-oxygen was monitored with the help of the DMAN-alanine amino acid. The newly devised amino acids are unique as they combine fluorescence, strongly basic and redox-active properties.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

Science.gov (United States)

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

Sinusoidal Representation of Acoustic Signals

Science.gov (United States)

Honda, Masaaki

Sinusoidal representation of acoustic signals has been an important tool in speech and music processing like signal analysis, synthesis and time scale or pitch modifications. It can be applicable to arbitrary signals, which is an important advantage over other signal representations like physical modeling of acoustic signals. In sinusoidal representation, acoustic signals are composed as sums of sinusoid (sine wave) with different amplitudes, frequencies and phases, which is based on the timedependent short-time Fourier transform (STFT). This article describes the principles of acoustic signal analysis/synthesis based on a sinusoid representation with focus on sine waves with rapidly varying frequency.

Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

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Fan Yang

2015-07-01

Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

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

Science.gov (United States)

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.

Facial expression recognition based on weber local descriptor and sparse representation

Science.gov (United States)

Ouyang, Yan

2018-03-01

Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

Representation Discovery using Harmonic Analysis

CERN Document Server

Mahadevan, Sridhar

2008-01-01

Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

Understanding representations in design

DEFF Research Database (Denmark)

Bødker, Susanne

1998-01-01

Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work situations...... and computer applications. It suggests that representations are primarily containers of ideas and that representation is situated at the same time as representations are crossing boundaries between various design and use activities. As such, representations should be carriers of their own contexts regarding...

A kernel-based multi-feature image representation for histopathology image classification

International Nuclear Information System (INIS)

Moreno J; Caicedo J Gonzalez F

2010-01-01

This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

J Carlos Moreno

2010-09-01

Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

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Yidong Tang

2016-01-01

Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

Training data representation in a neural based robot position estimation system

International Nuclear Information System (INIS)

Taraglio, S.; Di Fonzo, F.; Burrascano, P.

1997-03-01

The vision subsystem of an autonomous vehicle is studies. It is based on a multi layer perceptron that uses TV images to estimate the position of the vehicle. A comparative study of the effects of output data representation and input data processing is presented and discussed

Complexity in Acid-Base Titrations: Multimer Formation Between Phosphoric Acids and Imines.

Science.gov (United States)

Malm, Christian; Kim, Heejae; Wagner, Manfred; Hunger, Johannes

2017-08-10

Solutions of Brønsted acids with bases in aprotic solvents are not only common model systems to study the fundamentals of proton transfer pathways but are also highly relevant to Brønsted acid catalysis. Despite their importance the light nature of the proton makes characterization of acid-base aggregates challenging. Here, we track such acid-base interactions over a broad range of relative compositions between diphenyl phosphoric acid and the base quinaldine in dichloromethane, by using a combination of dielectric relaxation and NMR spectroscopy. In contrast to what one would expect for an acid-base titration, we find strong deviations from quantitative proton transfer from the acid to the base. Even for an excess of the base, multimers consisting of one base and at least two acid molecules are formed, in addition to the occurrence of proton transfer from the acid to the base and simultaneous formation of ion pairs. For equimolar mixtures such multimers constitute about one third of all intermolecular aggregates. Quantitative analysis of our results shows that the acid-base association constant is only around six times larger than that for the acid binding to an acid-base dimer, that is, to an already protonated base. Our findings have implications for the interpretation of previous studies of reactive intermediates in organocatalysis and provide a rationale for previously observed nonlinear effects in phosphoric acid catalysis. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Value representations: a value based dialogue tool

DEFF Research Database (Denmark)

Petersen, Marianne Graves; Rasmussen, Majken Kirkegaard

2011-01-01

Stereotypic presumptions about gender affect the design process, both in relation to how users are understood and how products are designed. As a way to decrease the influence of stereotypic presumptions in design process, we propose not to disregard the aspect of gender in the design process......, as the perspective brings valuable insights on different approaches to technology, but instead to view gender through a value lens. Contributing to this perspective, we have developed Value Representations as a design-oriented instrument for staging a reflective dialogue with users. Value Representations...

SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

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Wu Yiquan

2017-08-01

Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

The Role of Familiarity for Representations in Norm-Based Face Space.

Science.gov (United States)

Faerber, Stella J; Kaufmann, Jürgen M; Leder, Helmut; Martin, Eva Maria; Schweinberger, Stefan R

2016-01-01

According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

The Role of Familiarity for Representations in Norm-Based Face Space.

Directory of Open Access Journals (Sweden)

Stella J Faerber

Full Text Available According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991, any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face should be equidistant to a hypothetical prototype face (norm, such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV, and distinctiveness (face in the crowd: FITC for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV. In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1 that familiarity needs to be considered in studies of mental representations of faces, and (2 that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

Modeling the acid-base chemistry of organic solutes in Adirondack, New York, lakes

Science.gov (United States)

Driscoll, Charles T.; Lehtinen, Michael D.; Sullivan, Timothy J.

1994-02-01

Data from the large and diverse Adirondack Lake Survey were used to calibrate four simple organic acid analog models in an effort to quantify the influence of naturally occurring organic acids on lake water pH and acid-neutralizing capacity (ANC). The organic acid analog models were calibrated to observations of pH, dissolved organic carbon (DOC), and organic anion (An-) concentrations from a reduced data set representing 1128 individual lake samples, expressed as 41 observations of mean pH, in intervals of 0.1 pH units from pH 3.9 to 7.0. Of the four organic analog approaches examined, including the Oliver et al. (1983) model, as well as monoprotic, diprotic, and triprotic representations, the triprotic analog model yielded the best fit (r2 = 0.92) to the observed data. Moreover, the triprotic model was qualitatively consistent with observed patterns of change in organic solute charge density as a function of pH. A low calibrated value for the first H+ dissociation constant (pKal = 2.62) and the observation that organic anion concentrations were significant even at very low pH (acidic functional groups. Inclusion of organic acidity in model calculations resulted in good agreement between measured and predicted values of lake water pH and ANC. Assessments to project the response of surface waters to future changes in atmospheric deposition, through the use of acidification models, will need to include representations of organic acids in model structure to make accurate predictions of pH and ANC.

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

Science.gov (United States)

Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

2018-02-01

The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

Amino acid "little Big Bang": representing amino acid substitution matrices as dot products of Euclidian vectors.

Science.gov (United States)

Zimmermann, Karel; Gibrat, Jean-François

2010-01-04

Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices. We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices. This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.

Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors

Directory of Open Access Journals (Sweden)

Zimmermann Karel

2010-01-01

Full Text Available Abstract Background Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This paper deals with the problem of finding a representation that provides a comprehensive description of amino acid intrinsic properties consistent with the substitution matrices. Results We present a Euclidian vector representation of the amino acids, obtained by the singular value decomposition of the substitution matrices. The substitution matrix entries correspond to the dot product of amino acid vectors. We apply this vector encoding to the study of the relative importance of various amino acid physicochemical properties upon the substitution matrices. We also characterize and compare the PAM and BLOSUM series substitution matrices. Conclusions This vector encoding introduces a Euclidian metric in the amino acid space, consistent with substitution matrices. Such a numerical description of the amino acid is useful when intrinsic properties of amino acids are necessary, for instance, building sequence profiles or finding consensus sequences, using machine learning algorithms such as Support Vector Machine and Neural Networks algorithms.

A knowledge representation meta-model for rule-based modelling of signalling networks

Directory of Open Access Journals (Sweden)

Adrien Basso-Blandin

2016-03-01

Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

Science.gov (United States)

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Attention-spreading based on hierarchical spatial representations for connected objects.

Science.gov (United States)

Kasai, Tetsuko

2010-01-01

Attention selects objects or groups as the most fundamental unit, and this may be achieved through a process in which attention automatically spreads throughout their entire region. Previously, we found that a lateralized potential relative to an attended hemifield at occipito-temporal electrode sites reflects attention-spreading in response to connected bilateral stimuli [Kasai, T., & Kondo, M. Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93-98, 2007]. The present study examined the nature of object representations by manipulating the extent of grouping through connectedness, while controlling the symmetrical structure of bilateral stimuli. The electrophysiological results of two experiments consistently indicated that attention was guided twice in association with perceptual grouping in the early phase (N1, 150-200 msec poststimulus) and with the unity of an object in the later phase (N2pc, 310/330-390 msec). This suggests that there are two processes in object-based spatial selection, and these are discussed with regard to their cognitive mechanisms and object representations.

Complexity in Acid?Base Titrations: Multimer Formation Between Phosphoric Acids and Imines

OpenAIRE

Malm, Christian; Kim, Heejae; Wagner, Manfred; Hunger, Johannes

2017-01-01

Abstract Solutions of Br?nsted acids with bases in aprotic solvents are not only common model systems to study the fundamentals of proton transfer pathways but are also highly relevant to Br?nsted acid catalysis. Despite their importance the light nature of the proton makes characterization of acid?base aggregates challenging. Here, we track such acid?base interactions over a broad range of relative compositions between diphenyl phosphoric acid and the base quinaldine in dichloromethane, by u...

Effect of acute acid loading on acid-base and calcium metabolism

DEFF Research Database (Denmark)

Osther, Palle J

2006-01-01

OBJECTIVE: To investigate the acid-base and calcium metabolic responses to acute non-carbonic acid loading in idiopathic calcium stone-formers and healthy males using a quantitative organ physiological approach. MATERIAL AND METHODS: Five-h ammonium chloride loading studies were performed in 12...... male recurrent idiopathic calcium stone-formers and 12 matched healthy men using a randomized, placebo-controlled, cross-over design. Arterialized capillary blood, serum and urine were collected hourly for measurement of electrolytes, ionized calcium, magnesium, phosphate, parathyroid hormone and acid-base...... status. Concentrations of non-metabolizable base (NB) and acid (NA) were calculated from measured concentrations of non-metabolizable ions. RESULTS: The extracellular acid-base status in the stone-formers during basal conditions and acid loading was comparable to the levels in the healthy controls...

Representations of coherent states in non-orthogonal bases

International Nuclear Information System (INIS)

Ali, S Twareque; Roknizadeh, R; Tavassoly, M K

2004-01-01

Starting with the canonical coherent states, we demonstrate that all the so-called nonlinear coherent states, used in the physical literature, as well as large classes of other generalized coherent states, can be obtained by changes of bases in the underlying Hilbert space. This observation leads to an interesting duality between pairs of generalized coherent states, bringing into play a Gelfand triple of (rigged) Hilbert spaces. Moreover, it is shown that in each dual pair of families of nonlinear coherent states, at least one family is related to a (generally) non-unitary projective representation of the Weyl-Heisenberg group, which can then be thought of as characterizing the dual pair

Sequential injection redox or acid-base titration for determination of ascorbic acid or acetic acid.

Science.gov (United States)

Lenghor, Narong; Jakmunee, Jaroon; Vilen, Michael; Sara, Rolf; Christian, Gary D; Grudpan, Kate

2002-12-06

Two sequential injection titration systems with spectrophotometric detection have been developed. The first system for determination of ascorbic acid was based on redox reaction between ascorbic acid and permanganate in an acidic medium and lead to a decrease in color intensity of permanganate, monitored at 525 nm. A linear dependence of peak area obtained with ascorbic acid concentration up to 1200 mg l(-1) was achieved. The relative standard deviation for 11 replicate determinations of 400 mg l(-1) ascorbic acid was 2.9%. The second system, for acetic acid determination, was based on acid-base titration of acetic acid with sodium hydroxide using phenolphthalein as an indicator. The decrease in color intensity of the indicator was proportional to the acid content. A linear calibration graph in the range of 2-8% w v(-1) of acetic acid with a relative standard deviation of 4.8% (5.0% w v(-1) acetic acid, n=11) was obtained. Sample throughputs of 60 h(-1) were achieved for both systems. The systems were successfully applied for the assays of ascorbic acid in vitamin C tablets and acetic acid content in vinegars, respectively.

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

Science.gov (United States)

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).

Top-down attention based on object representation and incremental memory for knowledge building and inference.

Science.gov (United States)

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.

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

Science.gov (United States)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

A Knowledge-Based Representation Scheme for Environmental Science Models

Science.gov (United States)

Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

Mental Representation and Motor Imagery Training

Directory of Open Access Journals (Sweden)

Thomas eSchack

2014-05-01

Full Text Available 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, SDA-M (structural dimensional analysis of mental representation, 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 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.

Procedural Media Representation

OpenAIRE

Henrysson, Anders

2002-01-01

We present a concept for using procedural techniques to represent media. Procedural methods allow us to represent digital media (2D images, 3D environments etc.) with very little information and to render it photo realistically. Since not all kind of content can be created procedurally, traditional media representations (bitmaps, polygons etc.) must be used as well. We have adopted an object-based media representation where an object can be represented either with a procedure or with its trad...

PHYSIOLOGY OF ACID BASE BALANCE

Directory of Open Access Journals (Sweden)

Awati

2014-12-01

Full Text Available Acid-base, electrolyte, and metabolic disturbances are common in the intensive care unit. Almost all critically ill patients often suffer from compound acid-base and electrolyte disorders. Successful evaluation and management of such patients requires recognition of common patterns (e.g., metabolic acidosis and the ability to dissect one disorder from another. The intensivists needs to identify and correct these condition with the easiest available tools as they are the associated with multiorgan failure. Understanding the elements of normal physiology in these areas is very important so as to diagnose the pathological condition and take adequate measures as early as possible. Arterial blood gas analysis is one such tool for early detection of acid base disorder. Physiology of acid base is complex and here is the attempt to simplify it in our day to day application for the benefit of critically ill patients.

Physiologically based pharmacokinetic modeling of dibromoacetic acid in F344 rats

International Nuclear Information System (INIS)

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.

Representation mutations from standard genetic codes

Science.gov (United States)

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.

INVESTIGATING SHAPE REPRESENTATION USING SENSITIVITY TO PART- AND AXIS-BASED TRANSFORMATIONS

OpenAIRE

Denisova, Kristina; Feldman, Jacob; Su, Xiaotao; Singh, Manish

2016-01-01

Part -and axis-based approaches organize shape representations in terms of simple parts and their spatial relationships. Shape transformations that alter qualitative part structure have been shown to be more detectable than those that preserve it. We compared sensitivity to various transformations that change quantitative properties of parts and their spatial relationships, while preserving qualitative part structure. Shape transformations involving changes in length, width, curvature, orient...

Structure-reactivity modeling using mixture-based representation of chemical reactions.

Science.gov (United States)

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

Multi-stream CNN: Learning representations based on human-related regions for action recognition

NARCIS (Netherlands)

Tu, Zhigang; Xie, Wei; Qin, Qianqing; Poppe, R.W.; Veltkamp, R.C.; Li, Baoxin; Yuan, Junsong

2018-01-01

The most successful video-based human action recognition methods rely on feature representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two-stream network (TS-Net), we propose a multi-stream Convolutional Neural Network (CNN) architecture to recognize human actions. We

Knowledge Representation and Ontologies

Science.gov (United States)

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.

The Conjugate Acid-Base Chart.

Science.gov (United States)

Treptow, Richard S.

1986-01-01

Discusses the difficulties that beginning chemistry students have in understanding acid-base chemistry. Describes the use of conjugate acid-base charts in helping students visualize the conjugate relationship. Addresses chart construction, metal ions, buffers and pH titrations, and the organic functional groups and nonaqueous solvents. (TW)

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging

Directory of Open Access Journals (Sweden)

Xiaodong Zhang

2016-01-01

Full Text Available Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L0-norm/L1-norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118 than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610. The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

EFFECT OF CASEIN-BASED SEMISYNTHETIC FOOD ON RENAL ACID EXCRETION AND ACID-BASE STATE OF BLOOD IN DOGS

NARCIS (Netherlands)

ZIJLSTRA, WG; LANGBROEK, AJM; KRAAN, J; RISPENS, P; NIJMEIJER, A

1995-01-01

Urinary acid excretion and blood acid-base stare were determined in dogs fed a casein-based semi-synthetic food (SSF), to which different amounts of salts had been added, in comparison with feeding normal dog food. Net acid excretion (NAE) and inorganic acid excretion (IAE) increased during SSF

A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

Directory of Open Access Journals (Sweden)

Allah Bux Sargano

2017-01-01

Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.

Vietnamese Document Representation and Classification

Science.gov (United States)

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.

Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

NARCIS (Netherlands)

Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

2007-01-01

Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

Internal representations for face detection: an application of noise-based image classification to BOLD responses.

Science.gov (United States)

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.

Representations for Supporting Students' Context Awareness

DEFF Research Database (Denmark)

Demetriadis, Stavros N.; Papadopoulos, Pantelis M.

2005-01-01

The context of the specific situation where knowledge is applied affects significantly the problem solving process by forcing people to negotiate and reconsider the priorities of their mental representations and problem solving operators, in relation to this process. In this work we argue...... that students’ context awareness can significantly be enhanced by the use of appropriate external representations which guide them to activate context inducing cognitive processes. By embedding such representations in a case based learning environment we expect to guide students’ processing of the rich...... in contextual information material, in a way that improves both their context awareness and metacontextual competence. After presenting a context model, we discuss the design of such representations based on this model and explain why we expect that their use in a learning situation would enhance context...

Exploring the Structure of Spatial Representations

Science.gov (United States)

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

Experience-driven formation of parts-based representations in a model of layered visual memory

Directory of Open Access Journals (Sweden)

Jenia Jitsev

2009-09-01

Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

A General Simulator for Acid-Base Titrations

Science.gov (United States)

de Levie, Robert

1999-07-01

General formal expressions are provided to facilitate the automatic computer calculation of acid-base titration curves of arbitrary mixtures of acids, bases, and salts, without and with activity corrections based on the Davies equation. Explicit relations are also given for the buffer strength of mixtures of acids, bases, and salts.

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

Science.gov (United States)

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.

(Self)-representations on youtube

DEFF Research Database (Denmark)

Simonsen, Thomas Mosebo

This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can...... be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how certain forms of representation can be identified as representations of the self (Turkle 1995, Scannell...... 1996, Walker 2005) and further how these forms must be comprehended within a context of technological constrains, institutional structures and social as well as economical practices on YouTube (Burgess and Green 2009, Van Dijck 2009). It is argued that these different contexts play a vital part...

Computability and Representations of the Zero Set

NARCIS (Netherlands)

P.J. Collins (Pieter)

2008-01-01

htmlabstractIn this note we give a new representation for closed sets under which the robust zero set of a function is computable. We call this representation the component cover representation. The computation of the zero set is based on topological index theory, the most powerful tool for finding

Impossibility Theorem in Proportional Representation Problem

International Nuclear Information System (INIS)

Karpov, Alexander

2010-01-01

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).

Familiarity and Voice Representation: From Acoustic-Based Representation to Voice Averages

Directory of Open Access Journals (Sweden)

Maureen Fontaine

2017-07-01

Full Text Available The ability to recognize an individual from their voice is a widespread ability with a long evolutionary history. Yet, the perceptual representation of familiar voices is ill-defined. In two experiments, we explored the neuropsychological processes involved in the perception of voice identity. We specifically explored the hypothesis that familiar voices (trained-to-familiar (Experiment 1, and famous voices (Experiment 2 are represented as a whole complex pattern, well approximated by the average of multiple utterances produced by a single speaker. In experiment 1, participants learned three voices over several sessions, and performed a three-alternative forced-choice identification task on original voice samples and several “speaker averages,” created by morphing across varying numbers of different vowels (e.g., [a] and [i] produced by the same speaker. In experiment 2, the same participants performed the same task on voice samples produced by familiar speakers. The two experiments showed that for famous voices, but not for trained-to-familiar voices, identification performance increased and response times decreased as a function of the number of utterances in the averages. This study sheds light on the perceptual representation of familiar voices, and demonstrates the power of average in recognizing familiar voices. The speaker average captures the unique characteristics of a speaker, and thus retains the information essential for recognition; it acts as a prototype of the speaker.

A Computer-Based Simulation of an Acid-Base Titration

Science.gov (United States)

Boblick, John M.

1971-01-01

Reviews the advantages of computer simulated environments for experiments, referring in particular to acid-base titrations. Includes pre-lab instructions and a sample computer printout of a student's use of an acid-base simulation. Ten references. (PR)

Investigating Students' Reasoning about Acid-Base Reactions

Science.gov (United States)

Cooper, Melanie M.; Kouyoumdjian, Hovig; Underwood, Sonia M.

2016-01-01

Acid-base chemistry is central to a wide range of reactions. If students are able to understand how and why acid-base reactions occur, it should provide a basis for reasoning about a host of other reactions. Here, we report the development of a method to characterize student reasoning about acid-base reactions based on their description of…

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

Data.gov (United States)

National Aeronautics and Space Administration — This article presented a discussion on uncertainty representation and management for model-based prog- nostics methodologies based on the Bayesian tracking framework...

Committee Representation and Medicare Reimbursements-An Examination of the Resource-Based Relative Value Scale.

Science.gov (United States)

Gao, Y Nina

2018-04-06

The Resource-Based Relative Value Scale Update Committee (RUC) submits recommended reimbursement values for physician work (wRVUs) under Medicare Part B. The RUC includes rotating representatives from medical specialties. To identify changes in physician reimbursements associated with RUC rotating seat representation. Relative Value Scale Update Committee members 1994-2013; Medicare Part B Relative Value Scale 1994-2013; Physician/Supplier Procedure Summary Master File 2007; Part B National Summary Data File 2000-2011. I match service and procedure codes to specialties using 2007 Medicare billing data. Subsequently, I model wRVUs as a function of RUC rotating committee representation and level of code specialization. An annual RUC rotating seat membership is associated with a statistically significant 3-5 percent increase in Medicare expenditures for codes billed to that specialty. For codes that are performed by a small number of physicians, the association between reimbursement and rotating subspecialty representation is positive, 0.177 (SE = 0.024). For codes that are performed by a large number of physicians, the association is negative, -0.183 (SE = 0.026). Rotating representation on the RUC is correlated with overall reimbursement rates. The resulting differential changes may exacerbate existing reimbursement discrepancies between generalist and specialist practitioners. © Health Research and Educational Trust.

Research-Based Worksheets on Using Multiple Representations in Science Classrooms

Science.gov (United States)

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…

Prediction of Protein-Protein Interaction By Metasample-Based Sparse Representation

Directory of Open Access Journals (Sweden)

Xiuquan Du

2015-01-01

Full Text Available Protein-protein interactions (PPIs play key roles in many cellular processes such as transcription regulation, cell metabolism, and endocrine function. Understanding these interactions takes a great promotion to the pathogenesis and treatment of various diseases. A large amount of data has been generated by experimental techniques; however, most of these data are usually incomplete or noisy, and the current biological experimental techniques are always very time-consuming and expensive. In this paper, we proposed a novel method (metasample-based sparse representation classification, MSRC for PPIs prediction. A group of metasamples are extracted from the original training samples and then use the l1-regularized least square method to express a new testing sample as the linear combination of these metasamples. PPIs prediction is achieved by using a discrimination function defined in the representation coefficients. The MSRC is applied to PPIs dataset; it achieves 84.9% sensitivity, and 94.55% specificity, which is slightly lower than support vector machine (SVM and much higher than naive Bayes (NB, neural networks (NN, and k-nearest neighbor (KNN. The result shows that the MSRC is efficient for PPIs prediction.

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

Science.gov (United States)

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.

Hologram representation of design data in an expert system knowledge base

Science.gov (United States)

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.

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

Science.gov (United States)

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…

Teaching Acid/Base Physiology in the Laboratory

Science.gov (United States)

Friis, Ulla G.; Plovsing, Ronni; Hansen, Klaus; Laursen, Bent G.; Wallstedt, Birgitta

2010-01-01

Acid/base homeostasis is one of the most difficult subdisciplines of physiology for medical students to master. A different approach, where theory and practice are linked, might help students develop a deeper understanding of acid/base homeostasis. We therefore set out to develop a laboratory exercise in acid/base physiology that would provide…

An XML Representation for Crew Procedures

Science.gov (United States)

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

Force Concept Inventory-based multiple-choice test for investigating students’ representational consistency

Directory of Open Access Journals (Sweden)

Pasi Nieminen

2010-08-01

Full Text Available 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 (FCI. These original FCI items were redesigned using various representations (such as motion map, vectorial and graphical, yielding 27 multiple-choice items concerning four central concepts underpinning the force concept: Newton’s first, second, and third laws, and gravitation. We provide some evidence for the validity and reliability of the R-FCI; this analysis is limited to the student population of one Finnish high school. The students took the R-FCI at the beginning and at the end of their first high school physics course. We found that students’ (n=168 representational consistency (whether scientifically correct or not varied considerably depending on the concept. On average, representational consistency and scientifically correct understanding increased during the instruction, although in the post-test only a few students performed consistently both in terms of representations and scientifically correct understanding. We also compared students’ (n=87 results of the R-FCI and the FCI, and found that they correlated quite well.

No functional role of attention-based rehearsal in maintenance of spatial working memory representations

NARCIS (Netherlands)

Belopolsky, A.V.; Theeuwes, J.

2009-01-01

The present study systematically examined the role of attention in maintenance of spatial representations in working memory as proposed by the attention-based rehearsal hypothesis [Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental

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

Science.gov (United States)

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.

A generalized wavelet extrema representation

Energy Technology Data Exchange (ETDEWEB)

Lu, Jian; Lades, M.

1995-10-01

The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.

Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

Science.gov (United States)

Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

2017-05-01

Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

The application of brain-based learning principles aided by GeoGebra to improve mathematical representation ability

Science.gov (United States)

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.

Model's sparse representation based on reduced mixed GMsFE basis methods

Energy Technology Data Exchange (ETDEWEB)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in

Locality-preserving sparse representation-based classification in hyperspectral imagery

Science.gov (United States)

Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting

2016-10-01

This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

Alchemical and structural distribution based representation for universal quantum machine learning

Science.gov (United States)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Assessment of acid-base balance. Stewart's approach.

Science.gov (United States)

Fores-Novales, B; Diez-Fores, P; Aguilera-Celorrio, L J

2016-04-01

The study of acid-base equilibrium, its regulation and its interpretation have been a source of debate since the beginning of 20th century. Most accepted and commonly used analyses are based on pH, a notion first introduced by Sorensen in 1909, and on the Henderson-Hasselbalch equation (1916). Since then new concepts have been development in order to complete and make easier the understanding of acid-base disorders. In the early 1980's Peter Stewart brought the traditional interpretation of acid-base disturbances into question and proposed a new method. This innovative approach seems more suitable for studying acid-base abnormalities in critically ill patients. The aim of this paper is to update acid-base concepts, methods, limitations and applications. Copyright © 2015 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

(Self)-representations on youtube

OpenAIRE

Simonsen, Thomas Mosebo

2011-01-01

This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how ...

DEVELOPMENT OF INTERACTIVE E-BOOK BASED ON CHEMICAL REPRESENTATION REFER TO CURRICULUM 2013

Directory of Open Access Journals (Sweden)

L. Tania

2015-11-01

Full Text Available This research aimed to develop an interactive e-book based representations of chemistry; describes the characteristics of the interactive e-book developed; the teachers responses in content suitability with curriculum and graphics aspects; and student responses in readibility aspects. The method used was research and development. The characteristics of interactive e-book: it was developed referring to the core competencies (KI and basic competence (KD in the curriculum 2013, allowed active interaction between students and e-book, completed with pictures, animations or videos in three levels of the chemical representation. Teachers’ responses to the content suitability and graphic aspects were very good with the percentage of each 98.46% and 97.5%. The students’ responses in readibility aspects was very good with percentage of 88.5%.

Whole body acid-base modeling revisited.

Science.gov (United States)

Ring, Troels; Nielsen, Søren

2017-04-01

The textbook account of whole body acid-base balance in terms of endogenous acid production, renal net acid excretion, and gastrointestinal alkali absorption, which is the only comprehensive model around, has never been applied in clinical practice or been formally validated. To improve understanding of acid-base modeling, we managed to write up this conventional model as an expression solely on urine chemistry. Renal net acid excretion and endogenous acid production were already formulated in terms of urine chemistry, and we could from the literature also see gastrointestinal alkali absorption in terms of urine excretions. With a few assumptions it was possible to see that this expression of net acid balance was arithmetically identical to minus urine charge, whereby under the development of acidosis, urine was predicted to acquire a net negative charge. The literature already mentions unexplained negative urine charges so we scrutinized a series of seminal papers and confirmed empirically the theoretical prediction that observed urine charge did acquire negative charge as acidosis developed. Hence, we can conclude that the conventional model is problematic since it predicts what is physiologically impossible. Therefore, we need a new model for whole body acid-base balance, which does not have impossible implications. Furthermore, new experimental studies are needed to account for charge imbalance in urine under development of acidosis. Copyright © 2017 the American Physiological Society.

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

Science.gov (United States)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the

Knowledge Representation and Inference for Analysis and Design of Database and Tabular Rule-Based Systems

Directory of Open Access Journals (Sweden)

Antoni Ligeza

2001-01-01

Full Text Available Rulebased systems constitute a powerful tool for specification of knowledge in design and implementation of knowledge based systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and operational knowledge encoding. In order to assure safe and reliable performance, such system should satisfy certain formal requirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such system in a systematic way. A uniform, tabular scheme of single-level rule-based systems is considered. Such systems can be applied as a generalized form of databases for specification of data pattern (unconditional knowledge, or can be used for defining attributive decision tables (conditional knowledge in form of rules. They can also serve as lower-level components of a hierarchical multi-level control and decision support knowledge-based systems. An algebraic knowledge representation paradigm using extended tabular representation, similar to relational database tables is presented and algebraic bases for system analysis, verification and design support are outlined.

Knowledge Representation Using Multilevel Flow Model in Expert System

International Nuclear Information System (INIS)

Wang, Wenlin; Yang, Ming

2015-01-01

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available

Knowledge Representation Using Multilevel Flow Model in Expert System

Energy Technology Data Exchange (ETDEWEB)

Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)

2015-05-15

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.

Model-based object classification using unification grammars and abstract representations

Science.gov (United States)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

The effect of project-based learning on students' statistical literacy levels for data representation

Science.gov (United States)

Koparan, Timur; Güven, Bülent

2015-07-01

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 in the experimental group and 35 in the control group, took this test twice, one before the application and one after the application. All the raw scores were turned into linear points by using the Winsteps 3.72 modelling program that makes the Rasch analysis and t-tests, and an ANCOVA analysis was carried out with the linear points. Depending on the findings, it was concluded that the project-based learning approach increases students' level of statistical literacy for data representation. Students' levels of statistical literacy before and after the application were shown through the obtained person-item maps.

Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG

Directory of Open Access Journals (Sweden)

Daniela Danciulescu

2017-04-01

Full Text Available In Tudor (Preda (2010 a method for formal languages generation based on labeled stratified graph representations is sketched. The author proves that the considered method can generate regular languages and context-sensitive languages by considering an exemplification of the proposed method for a particular regular language and another one for a particular contextsensitive language. At the end of the study, the author highlights some open problems for future research among which we remind: (1 The study of the language families that can be generated by means of these structures; (2 The study of the infiniteness of the languages that can be represented in stratified graphs. In this paper, we extend the method presented in Tudor (Preda(2010, by considering the stratified graph formalism in a system of knowledge representation and reasoning. More precisely, we propose a method that can be applied for generating any Right Linear Language construction. Our method is proved and exemplified in several cases.

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

Science.gov (United States)

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.

Transient Variable Caching in Java’s Stack-Based Intermediate Representation

Directory of Open Access Journals (Sweden)

Paul Týma

1999-01-01

Full Text Available Java’s stack‐based intermediate representation (IR is typically coerced to execute on register‐based architectures. Unoptimized compiled code dutifully replicates transient variable usage designated by the programmer and common optimization practices tend to introduce further usage (i.e., CSE, Loop‐invariant Code Motion, etc.. On register based machines, often transient variables are cached within registers (when available saving the expense of actually accessing memory. Unfortunately, in stack‐based environments because of the need to push and pop the transient values, further performance improvement is possible. This paper presents Transient Variable Caching (TVC, a technique for eliminating transient variable overhead whenever possible. This optimization would find a likely home in optimizers attached to the back of popular Java compilers. Side effects of the algorithm include significant instruction reordering and introduction of many stack‐manipulation operations. This combination has proven to greatly impede the ability to decompile stack‐based IR code sequences. The code that results from the transform is faster, smaller, and greatly impedes decompilation.

Quantification of Lewis acid induced Brønsted acidity of protogenic Lewis bases.

Science.gov (United States)

Lathem, A Paige; Heiden, Zachariah M

2017-05-09

Proton transfer promoted by the coordination of protogenic Lewis bases to a Lewis acid is a critical step in catalytic transformations. Although the acidification of water upon coordination to a Lewis acid has been known for decades, no attempts have been made to correlate the Brønsted acidity of the coordinated water molecule with Lewis acid strength. To probe this effect, the pK a 's (estimated error of 1.3 pK a units) in acetonitrile of ten protogenic Lewis bases coordinated to seven Lewis acids containing Lewis acidities varying 70 kcal mol -1 , were computed. To quantify Lewis acid strength, the ability to transfer a hydride (hydride donor ability) from the respective main group hydride was used. Coordination of a Lewis acid to water increased the acidity of the bound water molecule between 20 and 50 pK a units. A linear correlation exhibiting a 2.6 pK a unit change of the Lewis acid-water adduct per ten kcal mol -1 change in hydride donor ability of the respective main group hydride was obtained. For the ten protogenic Lewis bases studied, the coordinated protogenic Lewis bases were acidified between 10 and 50 pK a units. On average, a ten kcal mol -1 change in hydride donor ability of the respective main group hydride resulted in about a 2.8 pK a unit change in the Brønsted acidity of the Lewis acid-Lewis base adducts. Since attempts to computationally investigate the pK a of main group dihydrogen complexes were unsuccessful, experimental determination of the first reported pK a of a main group dihydrogen complex is described. The pK a of H 2 -B(C 6 F 5 ) 3 was determined to be 5.8 ± 0.2 in acetonitrile.

Elucidating the hard/soft acid/base principle: A perspective based on half-reactions

International Nuclear Information System (INIS)

Ayers, Paul W.; Parr, Robert G.; Pearson, Ralph G.

2006-01-01

A comprehensive analysis is presented for the acid-base double-exchange reaction as well as the associated acid-displacement and base-displacement 'half-reactions' with the goal of elucidating the meaning of the hard/soft acid/base (HSAB) principle and the conditions for its validity. When electron-transfer effects are important and other effects are negligible, the HSAB principle is driven by the surpassing stability of the soft acid/soft base product. When electrostatic effects dominate the reactivity, the HSAB principle is driven by the surpassing stability of the hard acid/hard base product. Because electron-transfer effects favor soft/soft interactions, while electrostatic effects favor hard/hard interactions, acid-base exchange reactions may be used to determine whether a reagent's reactivity is dominated by electron-transfer or by electrostatic effects. Because electron-transfer and electrostatic considerations separately favor the HSAB principle whenever the electronic chemical potentials of the acids and bases involved in the reaction are similar, our analysis provides strong support for the HSAB principle. The electronic chemical potential measures the intrinsic strength of acids and bases

Preon representations and composite models

International Nuclear Information System (INIS)

Kang, Kyungsik

1982-01-01

This is a brief report on the preon models which are investigated by In-Gyu Koh, A. N. Schellekens and myself and based on complex, anomaly-free and asymptotically free representations of SU(3) to SU(8), SO(4N+2) and E 6 with no more than two different preons. Complete list of the representations that are complex anomaly-free and asymptotically free has been given by E. Eichten, I.-G. Koh and myself. The assumptions made about the ground state composites and the role of Fermi statistics to determine the metaflavor wave functions are discussed in some detail. We explain the method of decompositions of tensor products with definite permutation properties which has been developed for this purpose by I.-G. Koh, A.N. Schellekens and myself. An example based on an anomaly-free representation of the confining metacolor group SU(5) is discussed

An introduction to quiver representations

CERN Document Server

Derksen, Harm

2017-01-01

This book is an introduction to the representation theory of quivers and finite dimensional algebras. It gives a thorough and modern treatment of the algebraic approach based on Auslander-Reiten theory as well as the approach based on geometric invariant theory. The material in the opening chapters is developed starting slowly with topics such as homological algebra, Morita equivalence, and Gabriel's theorem. Next, the book presents Auslander-Reiten theory, including almost split sequences and the Auslander-Reiten transform, and gives a proof of Kac's generalization of Gabriel's theorem. Once this basic material is established, the book goes on with developing the geometric invariant theory of quiver representations. The book features the exposition of the saturation theorem for semi-invariants of quiver representations and its application to Littlewood-Richardson coefficients. In the final chapters, the book exposes tilting modules, exceptional sequences and a connection to cluster categories. The book is su...

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

Science.gov (United States)

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…

Spatially variant morphological restoration and skeleton representation.

Science.gov (United States)

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.

Volume-based Representation of the Magnetic Field

CERN Document Server

Amapane, N; Drollinger, V; Karimäki, V; Klyukhin, V; Todorov, T

2005-01-01

Simulation and reconstruction of events in high-energy experiments require the knowledge of the value of the magnetic field at any point within the detector. The way this information is extracted from the actual map of the magnetic field and served to simulation and reconstruction applications has a large impact on accuracy and performance in terms of speed. As an example, the CMS high level trigger performs on-line tracking of muons within the magnet yoke, where the field is discontinuous and largely inhomogeneous. In this case the high level trigger execution time is dominated by the time needed to access the magnetic field map.For this reason, an optimized approach for the access to the CMS field was developed, based on a dedicated representation of thedetector geometry. The detector is modeled in terms of volumes, constructed in such a way that their boundaries correspond to the fiel d discontinuities due to changes in the magnetic permeability of the materials. The field within each volume is therefore c...

Representational Thickness

DEFF Research Database (Denmark)

Mullins, Michael

Contemporary communicational and informational processes contribute to the shaping of our physical environment by having a powerful influence on the process of design. Applications of virtual reality (VR) are transforming the way architecture is conceived and produced by introducing dynamic...... elements into the process of design. Through its immersive properties, virtual reality allows access to a spatial experience of a computer model very different to both screen based simulations as well as traditional forms of architectural representation. The dissertation focuses on processes of the current...... representation? How is virtual reality used in public participation and how do virtual environments affect participatory decision making? How does VR thus affect the physical world of built environment? Given the practical collaborative possibilities of immersive technology, how can they best be implemented...

A Direct, Biomass-Based Synthesis of Benzoic Acid: Formic Acid-Mediated Deoxygenation of the Glucose-Derived Materials Quinic Acid and Shikimic Acid

Energy Technology Data Exchange (ETDEWEB)

Arceo, Elena; Ellman, Jonathan; Bergman, Robert

2010-05-03

An alternative biomass-based route to benzoic acid from the renewable starting materials quinic acid and shikimic acid is described. Benzoic acid is obtained selectively using a highly efficient, one-step formic acid-mediated deoxygenation method.

Robust Face Recognition Via Gabor Feature and Sparse Representation

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Hao Yu-Juan

2016-01-01

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

Paired structures in knowledge representation

DEFF Research Database (Denmark)

Montero, J.; Bustince, H.; Franco de los Ríos, Camilo

2016-01-01

In this position paper we propose a consistent and unifying view to all those basic knowledge representation models that are based on the existence of two somehow opposite fuzzy concepts. A number of these basic models can be found in fuzzy logic and multi-valued logic literature. Here...... of the relationships between several existing knowledge representation formalisms, providing a basis from which more expressive models can be later developed....

Efficient Online Aggregates in Dense-Region-Based Data Cube Representations

Science.gov (United States)

Haddadin, Kais; Lauer, Tobias

In-memory OLAP systems require a space-efficient representation of sparse data cubes in order to accommodate large data sets. On the other hand, most efficient online aggregation techniques, such as prefix sums, are built on dense array-based representations. These are often not applicable to real-world data due to the size of the arrays which usually cannot be compressed well, as most sparsity is removed during pre-processing. A possible solution is to identify dense regions in a sparse cube and only represent those using arrays, while storing sparse data separately, e.g. in a spatial index structure. Previous dense-region-based approaches have concentrated mainly on the effectiveness of the dense-region detection (i.e. on the space-efficiency of the result). However, especially in higher-dimensional cubes, data is usually more cluttered, resulting in a potentially large number of small dense regions, which negatively affects query performance on such a structure. In this paper, our focus is not only on space-efficiency but also on time-efficiency, both for the initial dense-region extraction and for queries carried out in the resulting hybrid data structure. We describe two methods to trade available memory for increased aggregate query performance. In addition, optimizations in our approach significantly reduce the time to build the initial data structure compared to former systems. Also, we present a straightforward adaptation of our approach to support multi-core or multi-processor architectures, which can further enhance query performance. Experiments with different real-world data sets show how various parameter settings can be used to adjust the efficiency and effectiveness of our algorithms.

Aspect-Aided Dynamic Non-Negative Sparse Representation-Based Microwave Image Classification

Directory of Open Access Journals (Sweden)

Xinzheng Zhang

2016-09-01

Full Text Available Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ 1 -regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance.

A communication-channel-based representation system for software

NARCIS (Netherlands)

Demirezen, Zekai; Tanik, Murat M.; Aksit, Mehmet; Skjellum, Anthony

We observed that before initiating software development the objectives are minimally organized and developers introduce comparatively higher organization throughout the design process. To be able to formally capture this observation, a new communication channel representation system for software is

Tensor-based cortical surface morphometry via weighted spherical harmonic representation.

Science.gov (United States)

Chung, Moo K; Dalton, Kim M; Davidson, Richard J

2008-08-01

We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.

Inequivalent coherent state representations in group field theory

Science.gov (United States)

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.

Assessing Acid-Base Status: Physiologic Versus Physicochemical Approach.

Science.gov (United States)

Adrogué, Horacio J; Madias, Nicolaos E

2016-11-01

The physiologic approach has long been used in assessing acid-base status. This approach considers acids as hydrogen ion donors and bases as hydrogen ion acceptors and the acid-base status of the organism as reflecting the interaction of net hydrogen ion balance with body buffers. In the physiologic approach, the carbonic acid/bicarbonate buffer pair is used for assessing acid-base status and blood pH is determined by carbonic acid (ie, Paco 2 ) and serum bicarbonate levels. More recently, the physicochemical approach was introduced, which has gained popularity, particularly among intensivists and anesthesiologists. This approach posits that the acid-base status of body fluids is determined by changes in the dissociation of water that are driven by the interplay of 3 independent variables: the sum of strong (fully dissociated) cation concentrations minus the sum of strong anion concentrations (strong ion difference); the total concentration of weak acids; and Paco 2 . These 3 independent variables mechanistically determine both hydrogen ion concentration and bicarbonate concentration of body fluids, which are considered as dependent variables. Our experience indicates that the average practitioner is familiar with only one of these approaches and knows very little, if any, about the other approach. In the present Acid-Base and Electrolyte Teaching Case, we attempt to bridge this knowledge gap by contrasting the physiologic and physicochemical approaches to assessing acid-base status. We first outline the essential features, advantages, and limitations of each of the 2 approaches and then apply each approach to the same patient presentation. We conclude with our view about the optimal approach. Copyright © 2016 National Kidney Foundation, Inc. All rights reserved.

The Kidney and Acid-Base Regulation

Science.gov (United States)

Koeppen, Bruce M.

2009-01-01

Since the topic of the role of the kidneys in the regulation of acid base balance was last reviewed from a teaching perspective (Koeppen BM. Renal regulation of acid-base balance. Adv Physiol Educ 20: 132-141, 1998), our understanding of the specific membrane transporters involved in H+, HCO , and NH transport, and especially how these…

Acid-base properties of 2-phenethyldithiocarbamoylacetic acid, an antitumor agent

Science.gov (United States)

Novozhilova, N. E.; Kutina, N. N.; Petukhova, O. A.; Kharitonov, Yu. Ya.

2013-07-01

The acid-base properties of the 2-phenethyldithiocarbamoylacetic acid (PET) substance belonging to the class of isothiocyanates and capable of inhibiting the development of tumors on many experimental models were studied. The acidity and hydrolysis constants of the PET substance in ethanol, acetone, aqueous ethanol, and aqueous acetone solutions were determined from the data of potentiometric (pH-metric) titration of ethanol and acetone solutions of PET with aqueous solidum hydroxide at room temperature.

Knowledge representation to support reasoning based on multiple models

Science.gov (United States)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

[Acid-base imbalance in acute obstructive uropathies].

Science.gov (United States)

Belyĭ, L E

2007-01-01

The aim of this study was to evaluate impairment of acid-base balance (ABB) in acute obstructive uropathies. Evaluation of acid-base balance was performed by pH, partial carbon dioxide pressure, plasma bicarbonate concentration, buffer bases, basis excess, hydrogen ion concentration. An automatic gas analyzer was used, plasma anion gap was calculated. Characteristic ABB alterations in different acute obstructive uropathies were detected. Acidotic shifts in acute obstruction of the upper urinary tracts and its inflammatory complications were assessed pathophysiologically. A comparative study of pathological acid-base disorders in acute supra- and infravesical obstructive uropathies was performed.

Optimal Meter Placement for Distribution Network State Estimation: A Circuit Representation Based MILP Approach

DEFF Research Database (Denmark)

Chen, Xiaoshuang; Lin, Jin; Wan, Can

2016-01-01

State estimation (SE) in distribution networks is not as accurate as that in transmission networks. Traditionally, distribution networks (DNs) are lack of direct measurements due to the limitations of investments and the difficulties of maintenance. Therefore, it is critical to improve the accuracy...... of SE in distribution networks by placing additional physical meters. For state-of-the-art SE models, it is difficult to clearly quantify measurements' influences on SE errors, so the problems of optimal meter placement for reducing SE errors are mostly solved by heuristic or suboptimal algorithms....... Under this background, this paper proposes a circuit representation model to represent SE errors. Based on the matrix formulation of the circuit representation model, the problem of optimal meter placement can be transformed to a mixed integer linear programming problem (MILP) via the disjunctive model...

A Constrained Algorithm Based NMFα for Image Representation

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Chenxue Yang

2014-01-01

Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.

A neural network model of semantic memory linking feature-based object representation and words.

Science.gov (United States)

Cuppini, C; Magosso, E; Ursino, M

2009-06-01

Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).

Renal acidification responses to respiratory acid-base disorders.

Science.gov (United States)

Madias, Nicolaos E

2010-01-01

Respiratory acid-base disorders are those abnormalities in acid-base equilibrium that are expressed as primary changes in the arterial carbon dioxide tension (PaCO2). An increase in PaCO2 (hypercapnia) acidifies body fluids and initiates the acid-base disturbance known as respiratory acidosis. By contrast, a decrease in PaCO2 (hypocapnia) alkalinizes body fluids and initiates the acid-base disturbance known as respiratory alkalosis. The impact on systemic acidity of these primary changes in PaCO2 is ameliorated by secondary, directional changes in plasma [HCO3¯] that occur in 2 stages. Acutely, hypercapnia or hypocapnia yields relatively small changes in plasma [HCO3¯] that originate virtually exclusively from titration of the body's nonbicarbonate buffers. During sustained hypercapnia or hypocapnia, much larger changes in plasma [HCO3¯] occur that reflect adjustments in renal acidification mechanisms. Consequently, the deviation of systemic acidity from normal is smaller in the chronic forms of these disorders. Here we provide an overview of the renal acidification responses to respiratory acid-base disorders. We also identify gaps in knowledge that require further research.

Mental Representations Formed From Educational Website Formats

Energy Technology Data Exchange (ETDEWEB)

Elizabeth T. Cady; Kimberly R. Raddatz; Tuan Q. Tran; Bernardo de la Garza; Peter D. Elgin

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, which 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.

The Effect of Project-Based Learning on Students' Statistical Literacy Levels for Data Representation

Science.gov (United States)

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…

The semantic representation of prejudice and stereotypes.

Science.gov (United States)

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.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

Science.gov (United States)

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.

Quantum Computation-Based Image Representation, Processing Operations and Their Applications

Directory of Open Access Journals (Sweden)

Fei Yan

2014-10-01

Full Text Available A flexible representation of quantum images (FRQI was proposed to facilitate the extension of classical (non-quantum-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI, quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.

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

Science.gov (United States)

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.

How initial representations shape coupled learning processes

DEFF Research Database (Denmark)

Puranam, Phanish; Swamy, M.

2016-01-01

Coupled learning processes, in which specialists from different domains learn how to make interdependent choices among alternatives, are common in organizations. We explore the role played by initial representations held by the learners in coupled learning processes using a formal agent-based model....... We find that initial representations have important consequences for the success of the coupled learning process, particularly when communication is constrained and individual rates of learning are high. Under these conditions, initial representations that generate incorrect beliefs can outperform...... one that does not discriminate among alternatives, or even a mix of correct and incorrect representations among the learners. We draw implications for the design of coupled learning processes in organizations. © 2016 INFORMS....

Acid-base titrations using microfluidic paper-based analytical devices.

Science.gov (United States)

Karita, Shingo; Kaneta, Takashi

2014-12-16

Rapid and simple acid-base titration was accomplished using a novel microfluidic paper-based analytical device (μPAD). The μPAD was fabricated by wax printing and consisted of ten reservoirs for reaction and detection. The reaction reservoirs contained various amounts of a primary standard substance, potassium hydrogen phthalate (KHPth), whereas a constant amount of phenolphthalein was added to all the detection reservoirs. A sample solution containing NaOH was dropped onto the center of the μPAD and was allowed to spread to the reaction reservoirs where the KHPth neutralized it. When the amount of NaOH exceeded that of the KHPth in the reaction reservoirs, unneutralized hydroxide ion penetrated the detection reservoirs, resulting in a color reaction from the phenolphthalein. Therefore, the number of the detection reservoirs with no color change determined the concentration of the NaOH in the sample solution. The titration was completed within 1 min by visually determining the end point, which required neither instrumentation nor software. The volumes of the KHPth and phenolphthalein solutions added to the corresponding reservoirs were optimized to obtain reproducible and accurate results for the concentration of NaOH. The μPADs determined the concentration of NaOH at orders of magnitude ranging from 0.01 to 1 M. An acid sample, HCl, was also determined using Na2CO3 as a primary standard substance instead of KHPth. Furthermore, the μPAD was applicable to the titrations of nitric acid, sulfuric acid, acetic acid, and ammonia solutions. The μPADs were stable for more than 1 month when stored in darkness at room temperature, although this was reduced to only 5 days under daylight conditions. The analysis of acidic hot spring water was also demonstrated in the field using the μPAD, and the results agreed well with those obtained by classic acid-base titration.

Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

Directory of Open Access Journals (Sweden)

YANG Zhaoxia

2015-07-01

Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

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Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

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

Science.gov (United States)

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.

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.

Science.gov (United States)

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.

General regression and representation model for classification.

Directory of Open Access Journals (Sweden)

Jianjun Qian

Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

Fuzzy Control of a Lead Acid Battery Charger

Directory of Open Access Journals (Sweden)

A. DAOUD

2005-03-01

Full Text Available In this paper, an alternative battery charging control technique based on fuzzy logic for photovoltaic (PV applications is presented. A PV module is connected to a buck type DC/DC power converter and a microcontroller based unit is used to control the lead acid battery charging voltage. The fuzzy control is used due to the simplicity of implementation, robustness and independence from the complex mathematical representation of the battery. The usefulness of this control method is confirmed by experiments.

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

Science.gov (United States)

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Content-adaptive pyramid representation for 3D object classification

DEFF Research Database (Denmark)

Kounalakis, Tsampikos; Boulgouris, Nikolaos; Triantafyllidis, Georgios

2016-01-01

In this paper we introduce a novel representation for the classification of 3D images. Unlike most current approaches, our representation is not based on a fixed pyramid but adapts to image content and uses image regions instead of rectangular pyramid scales. Image characteristics, such as depth...... and color, are used for defining regions within images. Multiple region scales are formed in order to construct the proposed pyramid image representation. The proposed method achieves excellent results in comparison to conventional representations....

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed; Zhang, Xiangliang

2017-01-01

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed

2017-02-07

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Analysis of graphic representations of activity theory in international journals

Directory of Open Access Journals (Sweden)

Marco André Mazzarotto

2016-05-01

Full Text Available Activity theory is a relevant framework for the Design field, and their graphic representations are cognitive artifacts that aid the understanding, use and communication of this theory. However, there is a lack of consistency around the graphics and labels used in these representations. Based on this, the aim of this study was to identify, analyze and evaluate these differences and propose a representation that aims to be more suitable for the theory. For this, uses as method a literature review based on Engeström (2001 and its three generations of visual models, combined with graphical analysis of representations collected in a hundred papers from international journals.

The acid-base resistant zone in three dentin bonding systems.

Science.gov (United States)

Inoue, Go; Nikaido, Toru; Foxton, Richard M; Tagami, Junji

2009-11-01

An acid-base resistant zone has been found to exist after acid-base challenge adjacent to the hybrid layer using SEM. The aim of this study was to examine the acid-base resistant zone using three different bonding systems. Dentin disks were applied with three different bonding systems, and then a resin composite was light-cured to make dentin disk sandwiches. After acid-base challenge, the polished surfaces were observed using SEM. For both one- and two-step self-etching primer systems, an acid-base resistant zone was clearly observed adjacent to the hybrid layer - but with differing appearances. For the wet bonding system, the presence of an acid-base resistant zone was unclear. This was because the self-etching primer systems etched the dentin surface mildly, such that the remaining mineral phase of dentin and the bonding agent yielded clear acid-base resistant zones. In conclusion, the acid-base resistant zone was clearly observed when self-etching primer systems were used, but not so for the wet bonding system.

Representations of quantum algebras and combinatorics of Young tableaux

CERN Document Server

Ariki, Susumu

2002-01-01

Among several tools used in studying representations of quantum groups (or quantum algebras) are the notions of Kashiwara's crystal bases and Lusztig's canonical bases. Mixing both approaches allows us to use a combinatorial approach to representations of quantum groups and to apply the theory to representations of Hecke algebras. The primary goal of this book is to introduce the representation theory of quantum groups using quantum groups of type A_{r-1}^{(1)} as a main example. The corresponding combinatorics, developed by Misra and Miwa, turns out to be the combinatorics of Young tableaux. The second goal of this book is to explain the proof of the (generalized) Leclerc-Lascoux-Thibon conjecture. This conjecture, which is now a theorem, is an important breakthrough in the modular representation theory of the Hecke algebras of classical type. The book contains most of the nonstandard material necessary to get acquainted with this new rapidly developing area. It can be used as a good entry point into the stu...

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

Science.gov (United States)

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

Acid-base status and changes in Swedish forest soils

International Nuclear Information System (INIS)

Karltun, Erik; Stendahl, Johan; Lundin, Lars

2003-01-01

In this paper we use data from the Swedish National Survey of Forest Soils and Vegetation (NSFSV) to evaluate the present acid-base status of forest soils to try to answer the following questions. Which role do anthropogenic and biological acidification play for the present acid-base status of the soil profile? What is the present acid-base status of Swedish forest soils and how large areas may be considered as severely acidified? Do the current tendencies in soil acid-base status correspond with the positive development in surface waters?

Factorizations and physical representations

International Nuclear Information System (INIS)

Revzen, M; Khanna, F C; Mann, A; Zak, J

2006-01-01

A Hilbert space in M dimensions is shown explicitly to accommodate representations that reflect the decomposition of M into prime numbers. Representations that exhibit the factorization of M into two relatively prime numbers: the kq representation (Zak J 1970 Phys. Today 23 51), and related representations termed q 1 q 2 representations (together with their conjugates) are analysed, as well as a representation that exhibits the complete factorization of M. In this latter representation each quantum number varies in a subspace that is associated with one of the prime numbers that make up M

Representations of braid group obtained from quantum sl(3) enveloping algebra

International Nuclear Information System (INIS)

Ma Zhongqi.

1989-07-01

The quantum Clebsch-Gordan coefficients for the coproduct 6x6 of the quantum sl(3) enveloping algebra are computed. Based on the representation 6, the representation of the braid group and the corresponding link polynomial are obtained. The link polynomials based on the representations of the quantum sl(3) enveloping algebra with one row Young tableau are discussed. (author). 11 refs, 3 tabs

Assessing College Students' Understanding of Acid Base Chemistry Concepts

Science.gov (United States)

Wan, Yanjun Jean

2014-01-01

Typically most college curricula include three acid base models: Arrhenius', Bronsted-Lowry's, and Lewis'. Although Lewis' acid base model is generally thought to be the most sophisticated among these three models, and can be further applied in reaction mechanisms, most general chemistry curricula either do not include Lewis' acid base model, or…

Representations of G+++ and the role of space-time

International Nuclear Information System (INIS)

Kleinschmidt, A.; West, P.

2004-01-01

We consider the decomposition of the adjoint and fundamental representations of very extended Kac-Moody algebras G+++ with respect to their regular A type subalgebra which, in the corresponding non-linear realisation, is associated with gravity. We find that for many very extended algebras almost all the A type representations that occur in the decomposition of the fundamental representations also occur in the adjoint representation of G+++ . In particular, for E 8 +++ , this applies to all its fundamental representations. However, there are some important examples, such as A N-3 +++ , where this is not true and indeed the adjoint representation contains no generator that can be identified with a space-time translation. We comment on the significance of these results for how space-time can occur in the non-linear realisation based on G+++ . Finally we show that there is a correspondence between the A representations that occur in the fundamental representation associated with the very extended node and the adjoint representation of G+++ which is consistent with the interpretation of the former as charges associated with brane solutions. (author)

Advances in visual representation of molecular potentials.

Science.gov (United States)

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.

Preparation and Optimization of Amorphous Ursodeoxycholic Acid Nano-suspensions by Nanoprecipitation based on Acid-base Neutralization for Enhanced Dissolution.

Science.gov (United States)

Xie, Yike; Chen, Zhongjian; Su, Rui; Li, Ye; Qi, Jianping; Wu, Wei; Lu, Yi

2017-01-01

Ursodeoxycholic acid, usually used to dissolve cholesterol gallstones in clinic, is a typical hydrophobic drug with poor oral bioavailability due to dissolution rate-limited performance. The objective of this study was to increase the dissolution of ursodeoxycholic acid by amorphous nanosuspensions. Nanoprecipitation based on acid-base neutralization was used to prepare the nanosuspensions with central composite design to optimize the formula. The nanosuspensions were characterized by particle size, morphology, crystallology and dissolution. The ursodeoxycholic acid nanosuspensions showed mean particle size around 380 nm with polydispersion index value about 0.25. Scanning electron microscope observed high coverage of HPMC-E50 onto the surface of the nanosuspensions. Differential scanning calorimetry and powder X-ray diffractometry revealed amorphous structure of the ursodeoxycholic acid nanosuspensions. A significant increase of dissolution in acidic media was achieved by the amorphous nanosuspensions compared with the physical mixture. It can be predicted that the amorphous nanosuspensions show great potential in improving the oral bioavailability of ursodeoxycholic acid. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A generative representation for the evolution of jazz solos

DEFF Research Database (Denmark)

Bäckman, Kjell; Dahlstedt, Palle

2008-01-01

This paper describes a system developed to create computer based jazz improvisation solos. The generation of the improvisation material uses interactive evolution, based on a dual genetic representation: a basic melody line representation, with energy constraints ("rubber band") and a hierarchic...... developed for this specific type of music. This is the first published part of an ongoing research project in generative jazz, based on probabilistic and evolutionary strategies....

History of Medical Understanding and Misunderstanding of Acid Base Balance

Science.gov (United States)

Aiken, Christopher Geoffrey Alexander

2013-01-01

To establish how controversies in understanding acid base balance arose, the literature on acid base balance was reviewed from 1909, when Henderson described how the neutral reaction of blood is determined by carbonic and organic acids being in equilibrium with an excess of mineral bases over mineral acids. From 1914 to 1930, Van Slyke and others established our acid base principles. They recognised that carbonic acid converts into bicarbonate all non-volatile mineral bases not bound by mineral acids and determined therefore that bicarbonate represents the alkaline reserve of the body and should be a physiological constant. They showed that standard bicarbonate is a good measure of acidosis caused by increased production or decreased elimination of organic acids. However, they recognised that bicarbonate improved low plasma bicarbonate but not high urine acid excretion in diabetic ketoacidosis, and that increasing pCO2 caused chloride to shift into cells raising plasma titratable alkali. Both indicate that minerals influence pH. In 1945 Darrow showed that hyperchloraemic metabolic acidosis in preterm infants fed milk with 5.7 mmol of chloride and 2.0 mmol of sodium per 100 kcal was caused by retention of chloride in excess of sodium. Similar findings were made but not recognised in later studies of metabolic acidosis in preterm infants. Shohl in 1921 and Kildeberg in 1978 presented the theory that carbonic and organic acids are neutralised by mineral base, where mineral base is the excess of mineral cations over anions and organic acid is the difference between mineral base, bicarbonate and protein anion. The degree of metabolic acidosis measured as base excess is determined by deviation in both mineral base and organic acid from normal. PMID:24179938

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

Science.gov (United States)

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Using Willie's Acid-Base Box for Blood Gas Analysis

Science.gov (United States)

Dietz, John R.

2011-01-01

In this article, the author describes a method developed by Dr. William T. Lipscomb for teaching blood gas analysis of acid-base status and provides three examples using Willie's acid-base box. Willie's acid-base box is constructed using three of the parameters of standard arterial blood gas analysis: (1) pH; (2) bicarbonate; and (3) CO[subscript…

Students' Alternate Conceptions on Acids and Bases

Science.gov (United States)

Pan, Hanqing; Henriques, Laura

2015-01-01

Knowing what students bring to the classroom can and should influence how we teach them. This study is a review of the literature associated with secondary and postsecondary students' ideas about acids and bases. It was found that there are six types of alternate ideas about acids and bases that students hold. These are: macroscopic properties of…

Rigid Body Attitude Control Based on a Manifold Representation of Direction Cosine Matrices

International Nuclear Information System (INIS)

Nakath, David; Clemens, Joachim; Rachuy, Carsten

2017-01-01

Autonomous systems typically actively observe certain aspects of their surroundings, which makes them dependent on a suitable controller. However, building an attitude controller for three degrees of freedom is a challenging task, mainly due to singularities in the different parametrizations of the three dimensional rotation group SO (3). Thus, we propose an attitude controller based on a manifold representation of direction cosine matrices: In state space, the attitude is globally and uniquely represented as a direction cosine matrix R ∈ SO (3). However, differences in the state space, i.e., the attitude errors, are exposed to the controller in the vector space ℝ 3 . This is achieved by an operator, which integrates the matrix logarithm mapping from SO (3) to so(3) and the map from so(3) to ℝ 3 . Based on this representation, we derive a proportional and derivative feedback controller, whose output has an upper bound to prevent actuator saturation. Additionally, the feedback is preprocessed by a particle filter to account for measurement and state transition noise. We evaluate our approach in a simulator in three different spacecraft maneuver scenarios: (i) stabilizing, (ii) rest-to-rest, and (iii) nadir-pointing. The controller exhibits stable behavior from initial attitudes near and far from the setpoint. Furthermore, it is able to stabilize a spacecraft and can be used for nadir-pointing maneuvers. (paper)

Public Library Representations and Internet Appropriations

Directory of Open Access Journals (Sweden)

Paula Sequeiros

2013-11-01

Full Text Available May the changes in the representations of the public library be propitiated by readers' appropriations of the Internet? To answer this question, a theoretically-driven and empirically-based research was developed in a public library in Portugal, combining the analysis of documents uses, the ethnography of space and Internet use, of social relations developed while reading, with the analysis of representations of the public library. No clear-cut association emerged between social-demographics or user profiles, and representations, in general. No disruptive Internet "impact" was found: Internet use may contribute to reinforce traditional representations of the library, while it may also update and democratise other representations. If the library and the Internet are represented as synonymous, the former does not make sense without the latter; but an Internet widespread and intensive use conflicts with the image of an institution dedicated to high-brow culture. Changes in uses of the public library are, instead, clearly associated with new types of readers, which in their turn reflect changes in urban social composition. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1401141

A fast image encryption system based on chaotic maps with finite precision representation

International Nuclear Information System (INIS)

Kwok, H.S.; Tang, Wallace K.S.

2007-01-01

In this paper, a fast chaos-based image encryption system with stream cipher structure is proposed. In order to achieve a fast throughput and facilitate hardware realization, 32-bit precision representation with fixed point arithmetic is assumed. The major core of the encryption system is a pseudo-random keystream generator based on a cascade of chaotic maps, serving the purpose of sequence generation and random mixing. Unlike the other existing chaos-based pseudo-random number generators, the proposed keystream generator not only achieves a very fast throughput, but also passes the statistical tests of up-to-date test suite even under quantization. The overall design of the image encryption system is to be explained while detail cryptanalysis is given and compared with some existing schemes

Violence against women: adolescents’ social representations

Directory of Open Access Journals (Sweden)

Ana Márcia de Almeida Rezende

2018-02-01

Full Text Available Violence against women in affectionate intimate relationships is a serious problem that causes damages to its victims. In the social imaginary there are ways of thinking and representations that tend to trivialize this type of violence, considering it a natural practice. In this sense, this article brings a study that aimed to know the social representations elaborated by adolescents on violence against women in affectionate relationships. Data were collected through a semi-structured interview conducted with 22 adolescents, and analyzed through the content analysis technique (BARDIN, 2011. The results revealed that the adolescents represent violence against women objectified in an everyday phenomenon, which happens even in their families. They have also elaborated social representations anchored in patriarchy, in which men use violence as means to dominate partners. It was observed the need for preventive work that would make adolescents aware of patriarchal ideologies present in the society, helping them to construct social representations based on respect and gender equity.

Visual tracking based on the sparse representation of the PCA subspace

Science.gov (United States)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Science.gov (United States)

Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

2015-07-01

In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

Minutia-pair spectral representations for fingerprint template protection

NARCIS (Netherlands)

Stanko, T.; Skoric, B.

2017-01-01

We introduce a new fixed-length representation of fingerprint minutiae, for use in template protection. It is similar to the `spectral minutiae' representation of Xu et al. but is based on coordinate differences between pairs of minutiae. Our technique has the advantage that it does not discard the

Propositional matrices as alternative representation of truth values ...

African Journals Online (AJOL)

The paper considered the subject of representation of truth values in symbolic logic. An alternative representation was given based on the rows and columns properties of matrices, with the operations involving the logical connectives subjected to the laws of algebra of propositions. Matrices of various propositions detailing ...

Boronic acid-based autoligation of nucleic acids

DEFF Research Database (Denmark)

Barbeyron, R.; Vasseur, J.-J.; Smietana, M.

2013-01-01

Abstract: The development of synthetic systems displaying dynamic and adaptive characteristics is a formidable challenge with wide applications from biotechnology to therapeutics. Recently, we described a dynamic and programmable nucleic acid-based system relying on the formation of reversible bo....... Evidence suggests that geometric and steric factors are key features for controlling the equilibria. Graphical Abstract: [Figure not available: see fulltext.]...

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

Science.gov (United States)

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.

No functional role of attention-based rehearsal in maintenance of spatial working memory representations.

Science.gov (United States)

Belopolsky, Artem V; Theeuwes, Jan

2009-10-01

The present study systematically examined the role of attention in maintenance of spatial representations in working memory as proposed by the attention-based rehearsal hypothesis [Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental Psychology--Human Perception and Performance, 24(3), 780-790]. Three main issues were examined. First, Experiments 1-3 demonstrated that inhibition and not facilitation of visual processing is often observed at the memorized location during the retention interval. This inhibition was caused by keeping a location in memory and not by the exogenous nature of the memory cue. Second, Experiment 4 showed that inhibition of the memorized location does not lead to any significant impairment in memory accuracy. Finally, Experiment 5 connected current results to the previous findings and demonstrated facilitation of processing at the memorized location. Importantly, facilitation of processing did not lead to more accurate memory performance. The present results challenge the functional role of attention in maintenance of spatial working memory representations.

Pattern of acid base abnormalities in critically ill patinets

International Nuclear Information System (INIS)

Ahmad, T.M.; Mehmood, A.; Malik, T.M.

2015-01-01

To find out the pattern of acid base abnormalities in critically ill patients in a tertiary care health facility. Study Design: A descriptive study. Place and Duration of Study: The study was carried out in the department of pathology, Combined Military Hospital Kharian from January 2013 to June 2013. Patients and Methods: Two hundred and fifty patients suffering from various diseases and presenting with exacerbation of their clinical conditions were studied. These patients were hospitalized and managed in acute care units of the hospital. Arterial blood gases were analysed to detect acid base status and their correlation with their clinical condition. Concomitant analysis of electrolytes was carried out. Tests related to concurrent illnesses e.g. renal and liver function tests, cardiac enzymes and plasma glucose were assayed by routine end point and kinetic methods. Standard reference materials were used to ensure internal quantify control of analyses. Results: Two hundred and fifteen patients out of 250 studied suffered from acid base disorders. Gender distribution showed a higher percentage of male patients and the mean age was 70.5 ± 17.4 years. Double acid base disorders were the commonest disorders (34%) followed by metabolic acidosis (30%). Anion gap was calculated to further stratify metabolic acidosis and cases of diabetic ketoacidosis were the commonest in this category (47%). Other simple acid base disorders were relatively less frequent. Delta bicarbonate was calculated to unmask the superimposition of respiratory alkalosis or acidosis with metabolic acidosis and metabolic alkalosis. Though triple acid base disorders were noted in a small percentage of cases (05%), but were found to be the most complicated and challenging. Mixed acid base disorders were associated with high mortality. Conclusion: A large number of critically ill patients manifested acid base abnormalities over the full spectrum of these disorders. Mixed acid base disorders were

A robust probabilistic collaborative representation based classification for multimodal biometrics

Science.gov (United States)

Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

2018-04-01

Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

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

Science.gov (United States)

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.

Acid-base transport in pancreas-new challenges

DEFF Research Database (Denmark)

Novak, Ivana; Haanes, Kristian Agmund; Wang, Jing

2013-01-01

Along the gastrointestinal tract a number of epithelia contribute with acid or basic secretions in order to aid digestive processes. The stomach and pancreas are the most extreme examples of acid (H+) and base (HCO-3) transporters, respectively. Nevertheless, they share the same challenges...... to consider in pancreas are the proton pumps (H-K-ATPases), as well as the calcium-activated K and Cl channels, such as K3.1 and TMEM16A/ANO1. Local regulators, such as purinergic signaling, fine-tune, and coordinate pancreatic secretion. Lastly, we speculate whether dys-regulation of acid-base transport...

Representation in Memory.

Science.gov (United States)

Rumelhart, David E.; Norman, Donald A.

This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…

Stable Kernel Representations as Nonlinear Left Coprime Factorizations

NARCIS (Netherlands)

Paice, A.D.B.; Schaft, A.J. van der

1994-01-01

A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

Court representation in Russia before 1917 (historical aspect

Directory of Open Access Journals (Sweden)

Konstantin V. Ilyashenko

2015-12-01

Full Text Available Objective basing on the research and analysis of the legislation historical legal sources and other materials to study the process of formation and development of the institution of legal representation in Russia before 1917. Methods the theoretical basis of research is the works of Russian scientists on various aspects of formation development and functioning of the institution of legal representation in Russia from ancient times till 1917. The methodological basis of the research is general scientific methods historical formallogical system and general logical methods analysis synthesis induction and deduction synthesis analogy abstraction. Historicallegal formallegal logicallegal comparative legal methods were applied in the study. The author used the retrospective approach to the study of the issues of legal representation in Russia. Results basing on analysis of normative legal acts regulating relations in the sphere of judicial representation and various doctrinal sources the author has examined the process of the formation and development of the legal representation institution in Russia before 1917 raised the question of providing legal assistance in prerevolutionary Russia. An analogy is drawn between the prerevolutionary legal regulation of the legal representation institution and the modern legislation regulating this legal institution. The conclusion is made about the inadequacy of prerevolutionary legislation regulating relations in the sphere of judicial representation as well as the modern legal regulation of relations in this sphere. It is established that the judicial reform of 1864 improved regulation in this sphere but still did not solve all the problems in this area. The relevance of the study is due to the topicality and the constitutional importance of legal representation for the entire Russian society the need to examine the origins of this legal phenomenon as well as the fact that the institution of legal representation

Attention and Representational Momentum

OpenAIRE

Hayes, Amy; Freyd, Jennifer J

1995-01-01

Representational momentum, the tendency for memory to be distorted in the direction of an implied transformation, suggests that dynamics are an intrinsic part of perceptual representations. We examined the effect of attention on dynamic representation by testing for representational momentum under conditions of distraction. Forward memory shifts increase when attention is divided. Attention may be involved in halting but not in maintaining dynamic representations.

Constructing visual representations

DEFF Research Database (Denmark)

Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

2014-01-01

tangible building blocks. We learned that all participants, most of whom had little experience in visualization authoring, were readily able to create and talk about their own visualizations. Based on our observations, we discuss participants’ actions during the development of their visual representations......The accessibility of infovis authoring tools to a wide audience has been identified as a major research challenge. A key task in the authoring process is the development of visual mappings. While the infovis community has long been deeply interested in finding effective visual mappings......, comparatively little attention has been placed on how people construct visual mappings. In this paper, we present the results of a study designed to shed light on how people transform data into visual representations. We asked people to create, update and explain their own information visualizations using only...

Acid-base interactions in microbial adhesion to hexadecane and chloroform

NARCIS (Netherlands)

Bos, R; Busscher, HJ; Geertsema-Doornbusch, GI; Van Der Mei, HC; Mittal, KL

2000-01-01

Acid-base interactions play an important role in adhesion, including microbial adhesion to surfaces. Qualitatively acid-base interactions in microbial adhesion can be demonstrated by comparing adhesion to hexadecane (a negatively charged interface in aqueous solutions, unable to exert acid-base

LGBT Representations on Facebook : Representations of the Self and the Content

OpenAIRE

Chu, Yawen

2017-01-01

The topic of LGBT rights has been increasingly discussed and debated over recent years. More and more scholars show their interests in the field of LGBT representations in media. However, not many studies involved LGBT representations in social media. This paper explores LGBT representations on Facebook by analysing posts on an open page and in a private group, including both representations of the self as the identity of sexual minorities, content that is displayed on Facebook and the simila...

Acid-base titrations by stepwise addition of equal volumes of titrant with special reference to automatic titrations-II Theory of titration of mixtures of acids, polyprotic acids, acids in mixture with weak bases, and ampholytes.

Science.gov (United States)

Pehrsson, L; Ingman, F; Johansson, S

A general method for evaluating titration data for mixtures of acids and for acids in mixture with weak bases is presented. Procedures are given that do not require absolute [H]-data, i.e., relative [H]-data may be used. In most cases a very rough calibration of the electrode system is enough. Further, for simple systems, very approximate values of the stability constants are sufficient. As examples, the titration of the following are treated in some detail: a mixture of two acids, a diprotic acid, an acid in presence of its conjugate base, and an ampholyte.

Synthesis of bio-based methacrylic acid by decarboxylation of itaconic acid and citric acid catalyzed by solid transition-metal catalysts.

Science.gov (United States)

Le Nôtre, Jérôme; Witte-van Dijk, Susan C M; van Haveren, Jacco; Scott, Elinor L; Sanders, Johan P M

2014-09-01

Methacrylic acid, an important monomer for the plastics industry, was obtained in high selectivity (up to 84%) by the decarboxylation of itaconic acid using heterogeneous catalysts based on Pd, Pt and Ru. The reaction takes place in water at 200-250 °C without any external added pressure, conditions significantly milder than those described previously for the same conversion with better yield and selectivity. A comprehensive study of the reaction parameters has been performed, and the isolation of methacrylic acid was achieved in 50% yield. The decarboxylation procedure is also applicable to citric acid, a more widely available bio-based feedstock, and leads to the production of methacrylic acid in one pot in 41% selectivity. Aconitic acid, the intermediate compound in the pathway from citric acid to itaconic acid was also used successfully as a substrate. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Poincaré Embeddings for Learning Hierarchical Representations

CERN Multimedia

CERN. Geneva

2018-01-01

Abstracts: Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, while complex symbolic datasets often exhibit a latent hierarchical structure, state-of-the-art methods typically do not account for this property. In this talk, I will discuss a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an n-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows us to learn parsimonious representations of symbolic data by simultaneously capturing hierarchy and similarity. We introduce an efficient algorithm to learn the embeddings based on Riemannian optimization and show experimentally that Poincaré embeddings outperform Euclidean embeddings significantly on data with latent hierarchies, both in terms of representation capacity and in terms of generalization ability.      &...

Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

Science.gov (United States)

Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben

2017-08-02

It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.

Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations.

Science.gov (United States)

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.

A Closer Look at Acid-Base Olfactory Titrations

Science.gov (United States)

Neppel, Kerry; Oliver-Hoyo, Maria T.; Queen, Connie; Reed, Nicole

2005-01-01

Olfactory titrations using raw onions and eugenol as acid-base indicators are reported. An in-depth investigation on olfactory titrations is presented to include requirements for potential olfactory indicators and protocols for using garlic, onions, and vanillin as acid-base olfactory indicators are tested.

Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation.

Science.gov (United States)

Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng

2009-04-21

In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.

The Schrödinger representation and its relation to the holomorphic representation in linear and affine field theory

International Nuclear Information System (INIS)

Oeckl, Robert

2012-01-01

We establish a precise isomorphism between the Schrödinger representation and the holomorphic representation in linear and affine field theory. In the linear case, this isomorphism is induced by a one-to-one correspondence between complex structures and Schrödinger vacua. In the affine case we obtain similar results, with the role of the vacuum now taken by a whole family of coherent states. In order to establish these results we exhibit a rigorous construction of the Schrödinger representation and use a suitable generalization of the Segal-Bargmann transform. Our construction is based on geometric quantization and applies to any real polarization and its pairing with any Kähler polarization.

Patent Keyword Extraction Algorithm Based on Distributed Representation for Patent Classification

Directory of Open Access Journals (Sweden)

Jie Hu

2018-02-01

Full Text Available Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM classification, which are valuable when human-annotated keywords are not available. We used a standard benchmark dataset and a homemade patent dataset to evaluate the performance of PKEA. Our patent dataset includes 2500 patents from five distinct technological fields related to autonomous cars (GPS systems, lidar systems, object recognition systems, radar systems, and vehicle control systems. We compared our method with Frequency, Term Frequency-Inverse Document Frequency (TF-IDF, TextRank and Rapid Automatic Keyword Extraction (RAKE. The experimental results show that our proposed algorithm provides a promising way to extract keywords from patent texts for patent classification.

Social representation of the kinesiotherapist profession

Directory of Open Access Journals (Sweden)

Beatrice ABALAŞE

2017-03-01

Full Text Available The scientific approach is focused on identifying the social representation of the profession of physical therapist referring to mental images of social reality to a group consensus meeting. The goal of research identifies social representation of the profession of physical therapist, on the premise that students of the Faculty of Physical Education and Sport have made a social representation of the profession of physical therapist in accordance with the description of the occupation of COR. Working method was based on the questionnaire. Interpretation of results, the first two items of the questionnaire was done through word association technique, developed by P. Verges (1 and an alternative method for determining the structure and organization of elements representation proposed by. C. Havârneanu (2. Qualitative analysis reveals that students’ specialization Physical Therapy and Special Motricity believes that a therapist uses therapy as a strategy to work, and it must be applied professionally. Respondents considered, as shown in the data collected, that this profession is subject to skills, education, cognitive baggage, all sending to knowledge, experience and passion. The core refers to the complex representation obtained thanks cognitive process by which individuals or groups in familiar transforms abstract and it integrates knowledge of their system.

Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts

OpenAIRE

Tulkens, Stéphan; Šuster, Simon; Daelemans, Walter

2016-01-01

In this paper, we report a knowledge-based method for Word Sense Disambiguation in the domains of biomedical and clinical text. We combine word representations created on large corpora with a small number of definitions from the UMLS to create concept representations, which we then compare to representations of the context of ambiguous terms. Using no relational information, we obtain comparable performance to previous approaches on the MSH-WSD dataset, which is a well-known dataset in the bi...

Asymptotical representation of discrete groups

International Nuclear Information System (INIS)

Mishchenko, A.S.; Mohammad, N.

1995-08-01

If one has a unitary representation ρ: π → U(H) of the fundamental group π 1 (M) of the manifold M then one can do may useful things: 1. To construct a natural vector bundle over M; 2. To construct the cohomology groups with respect to the local system of coefficients; 3. To construct the signature of manifold M with respect to the local system of coefficients; and others. In particular, one can write the Hirzebruch formula which compares the signature with the characteristic classes of the manifold M, further based on this, find the homotopy invariant characteristic classes (i.e. the Novikov conjecture). Taking into account that the family of known representations is not sufficiently large, it would be interesting to extend this family to some larger one. Using the ideas of A.Connes, M.Gromov and H.Moscovici a proper notion of asymptotical representation is defined. (author). 7 refs

Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes.

Science.gov (United States)

Kumar, Manoj; Federmeier, Kara D; Fei-Fei, Li; Beck, Diane M

2017-07-15

A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. "sandy beach") describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

Science.gov (United States)

Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

2016-05-01

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Representation Elements of Spatial Thinking

Science.gov (United States)

Fiantika, F. R.

2017-04-01

This paper aims to add a reference in revealing spatial thinking. There several definitions of spatial thinking but it is not easy to defining it. We can start to discuss the concept, its basic a forming representation. Initially, the five sense catch the natural phenomenon and forward it to memory for processing. Abstraction plays a role in processing information into a concept. There are two types of representation, namely internal representation and external representation. The internal representation is also known as mental representation; this representation is in the human mind. The external representation may include images, auditory and kinesthetic which can be used to describe, explain and communicate the structure, operation, the function of the object as well as relationships. There are two main elements, representations properties and object relationships. These elements play a role in forming a representation.

The influence of hen age on fatty acid composition of commercial eggs

Directory of Open Access Journals (Sweden)

Tina Lešić

2017-01-01

Full Text Available The aim of this study was to investigate the nutritional composition of commercial eggs from Lohman Brown hens through fat and fatty acid content analysis, as well as to evaluate the effect of hen age on the above parameters. Egg samples (n=108 were collected every two weeks from 21- to 55- week old hens during the 2015/2016 autumn/winter period. The results revealed significant differences in fatty acid composition dependent on hen age (p 0.05. The total polyunsaturated fatty acid (PUFA content was statistically significantly higher in eggs laid by 55- week old hens as compared to those laid by 21- week old hens. The n-6/n-3 and PUFA/SFA ratios were more favourable in the elder hens. In general, the results revealed hen ageing-based variations in fatty acid composition of their eggs, in particular in the representation of linoleic (LA, alpha-linolenic (ALA and arachidonic acid (AA, for which statistically significant hen age-based differences were found.

Design Case Retrieval by Generic Representations

NARCIS (Netherlands)

Achten, H.H.; Gero, J.S.

2000-01-01

Case-Based Reasoning and Case-Based Design have been proposed to utilize knowledge of previous design solutions to understand or solve current design problems. Case retrieval is often performed on the basis of verbal indexing systems, whereas in design the use of graphic representations is

Superalgebras, their quantum deformations and the induced representation method

International Nuclear Information System (INIS)

Nguyen Anh Ky.

1996-08-01

In this paper some introductory concepts and basic definitions of the Lie superalgebras and their quantum deformations are exposed. Especially the induced representation methods in both cases are described. Up to now, based on the Kac representation theory we have succeeded in constructing representations of several higher rank superalgebras. When representations of quantum superalgebras are concerned, we develop a method which can be applied not only to the one-parametric quantum deformations but also to the multi-parametric ones. Here, being illustrations of the above-mentioned methods, the superalgebra gl(2/1) and its (one-parametric) quantum deformation U q [gl(2/1)] are considered as their finite-dimensional representations are investigated in detail and constructed explicitly. Also, it is shown that the finite-dimensional representations obtained constitute classes of all irreducible (typical and non-typical) finite-dimensional representations of gl(2/1) and U q [gl(2/1)]. Some of the detailed results may be simple but they are given for the first time. (author). 64 refs

Acid-base homeostasis in the human system

Science.gov (United States)

White, R. J.

1974-01-01

Acid-base regulation is a cooperative phenomena in vivo with body fluids, extracellular and intracellular buffers, lungs, and kidneys all playing important roles. The present account is much too brief to be considered a review of present knowledge of these regulatory systems, and should be viewed, instead, as a guide to the elements necessary to construct a simple model of the mutual interactions of the acid-base regulatory systems of the body.

Scenarios, personas and user stories: user-centered evidence-based design representations of communicable disease investigations.

Science.gov (United States)

Turner, Anne M; Reeder, Blaine; Ramey, Judith

2013-08-01

Despite years of effort and millions of dollars spent to create unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of user-centered design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to CD monitoring and control at a local health agency, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health agency CD workflow. Informed by principles of design ethnography and user-centered design we created persona, scenarios and user stories to accurately represent the user to system designers. We sought to convey to designers the key findings from ethnographic studies: (1) public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed, (2) health agency efforts are focused on CD investigation and response rather than reporting and (3) current CD information systems must conform to public health workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Through application of user-centered design principles, we were able to create design representations that illustrate complex public health communicable disease workflow and key user characteristics to inform the design of CD information

Towards a Script-Based Representation Language for Educational Films.

Science.gov (United States)

Parkes, Alan P.

1987-01-01

Discusses aspects of the syntax and semantics of film, and presents a scenario for the use of film by intelligent computer assisted instruction (ICAI) systems. An outline of a representation language for educational films on videodisc is presented, and an appendix provides conceptual graphs that explain notations used in examples. (Author/LRW)

Acid-base characteristics of powdered-activated-carbon surfaces

Energy Technology Data Exchange (ETDEWEB)

Reed, B.E. (West Virginia Univ., Morgantown (United States)); Jensen, J.N.; Matsumoto, M.R. (State Univ. of New York, Buffalo (United States))

Adsorption of heavy metals onto activated carbon has been described using the surface-complex-formation (SCF) model, a chemical equilibrium model. The SCF model requires a knowledge of the amphoteric nature of activated carbon prior to metal adsorption modeling. In the past, a single-diprotic-acid-site model had been employed to describe the amphoteric nature of activated-carbon surfaces. During this study, the amphoteric nature of two powdered activated carbons were investigated, and a three-monoprotic site surface model was found to be a plausible alternative. The single-diprotic-acid-site and two-monoprotic-site models did not describe the acid-base behavior of the two carbons studied adequately. The two-diprotic site was acceptable for only one of the study carbons. The acid-base behavior of activated carbon surfaces seem to be best modeled as a series of weak monoprotic acids.

Frame representations of quantum mechanics and the necessity of negativity in quasi-probability representations

International Nuclear Information System (INIS)

Ferrie, Christopher; Emerson, Joseph

2008-01-01

Several finite-dimensional quasi-probability representations of quantum states have been proposed to study various problems in quantum information theory and quantum foundations. These representations are often defined only on restricted dimensions and their physical significance in contexts such as drawing quantum-classical comparisons is limited by the non-uniqueness of the particular representation. Here we show how the mathematical theory of frames provides a unified formalism which accommodates all known quasi-probability representations of finite-dimensional quantum systems. Moreover, we show that any quasi-probability representation is equivalent to a frame representation and then prove that any such representation of quantum mechanics must exhibit either negativity or a deformed probability calculus. (fast track communication)

Paired structures and bipolar knowledge representation

DEFF Research Database (Denmark)

Montero, Javier; Bustince, Humberto; Franco, Camilo

In this strictly positional paper we propose a general approach to bipolar knowledge representation, where the meaning of concepts can be modelled by examining their decomposition into opposite and neutral categories. In particular, it is the semantic relationship between the opposite categories...... and at the same time the type of neutrality rising in between opposites. Based on this first level of bipolar knowledge representation, paired structures in fact offer the means to characterize a specific bipolar valuation scale depending on the meaning of the concept that has to be verified. In this sense...

A dipstick sensor for coulometric acid-base titrations

NARCIS (Netherlands)

Olthuis, Wouter; van der Schoot, B.H.; Chavez, F.; Bergveld, Piet

1989-01-01

By performing an acid-base titration by coulometric generation of OH− or H+ ions at an inert electrode in close proximity to the pH-sensitive gate of an ISFET, it is possible to determine the acid or base concentration of a solution using the ISFET as an indicator device for the equivalence point in

Usage of semantic representations in recognition memory.

Science.gov (United States)

Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

2017-11-01

Meanings of words facilitate false acceptance as well as correct rejection of lures in recognition memory tests, depending on the experimental context. This suggests that semantic representations are both directly and indirectly (i.e., mediated by perceptual representations) used in remembering. Studies using memory conjunction errors (MCEs) paradigms, in which the lures consist of component parts of studied words, have reported semantic facilitation of rejection of the lures. However, attending to components of the lures could potentially cause this. Therefore, we investigated whether semantic overlap of lures facilitates MCEs using Japanese Kanji words in which a whole-word image is more concerned in reading. Experiments demonstrated semantic facilitation of MCEs in a delayed recognition test (Experiment 1), and in immediate recognition tests in which participants were prevented from using phonological or orthographic representations (Experiment 2), and the salient effect on individuals with high semantic memory capacities (Experiment 3). Additionally, analysis of the receiver operating characteristic suggested that this effect is attributed to familiarity-based memory judgement and phantom recollection. These findings indicate that semantic representations can be directly used in remembering, even when perceptual representations of studied words are available.

Poetic representation

DEFF Research Database (Denmark)

Wulf-Andersen, Trine Østergaard

2012-01-01

, and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...

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

Science.gov (United States)

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.

Tailoring peritoneal dialysis fluid for optimal acid-base targets.

Science.gov (United States)

Feriani, Mariano

2009-01-01

Mild derangements of acid-base status are common features in peritoneal dialysis patients, metabolic acidosis being the most frequent alteration. One of the main tasks of dialysis is to correct these derangements and the target is the normalization of the acid-base parameters since they affect several organs and functions. Since factors affecting acid-base homeostasis are intrinsic characteristics of the individual patient (metabolic acid production, distribution space for bicarbonate, dialytic prescription, etc.), it is not surprising that only relatively few patients achieve the normal range. Only a certain modulation of buffer infusion by using different buffer concentrations in the dialysis fluid may ensure a good correction in a large percentage of patients.

A Possible Neural Representation of Mathematical Group Structures.

Science.gov (United States)

Pomi, Andrés

2016-09-01

Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation. A formal neurocognitive theory must account for all the activities developed by our brain and provide a possible neural representation for them. Associative memories are neural network models that have a good chance of achieving a universal representation of cognitive phenomena. In this work, we present a possible neural representation of mathematical group structures based on associative memory models that store finite groups through their Cayley graphs. A context-dependent associative memory stores the transitions between elements of the group when multiplied by each generator of a given presentation of the group. Under a convenient election of the vector basis mapping the elements of the group in the neural activity, the input of a vector corresponding to a generator of the group collapses the context-dependent rectangular matrix into a virtual square permutation matrix that is the matrix representation of the generator. This neural representation corresponds to the regular representation of the group, in which to each element is assigned a permutation matrix. This action of the generator on the memory matrix can also be seen as the dissection of the corresponding monochromatic subgraph of the Cayley graph of the group, and the adjacency matrix of this subgraph is the permutation matrix corresponding to the generator.

A randomized trial of computer-based communications using imagery and text information to alter representations of heart disease risk and motivate protective behaviour.

Science.gov (United States)

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.

Integral representations of solutions of the wave equation based on relativistic wavelets

International Nuclear Information System (INIS)

Perel, Maria; Gorodnitskiy, Evgeny

2012-01-01

A representation of solutions of the wave equation with two spatial coordinates in terms of localized elementary ones is presented. Elementary solutions are constructed from four solutions with the help of transformations of the affine Poincaré group, i.e. with the help of translations, dilations in space and time and Lorentz transformations. The representation can be interpreted in terms of the initial-boundary value problem for the wave equation in a half-plane. It gives the solution as an integral representation of two types of solutions: propagating localized solutions running away from the boundary under different angles and packet-like surface waves running along the boundary and exponentially decreasing away from the boundary. Properties of elementary solutions are discussed. A numerical investigation of coefficients of the decomposition is carried out. An example of the decomposition of the field created by sources moving along a line with different speeds is considered, and the dependence of coefficients on speeds of sources is discussed. (paper)

Acid-base equilibrium: The best clinical approach

OpenAIRE

Aristizábal-Salazar, Raúl E; Calvo-Torres, L. Felipe; Valencia-Arango, Luis Alfonso; Montoya-Canon, Mauricio; Barbosa-Gantiva, Oscar; Hincapié-Baena, Vanessa

2015-01-01

Acid-base balance disorders can be found in a primary or secondary form in patients with a disease process such as Diabetes Mellitus or acute renal failure, among others. The objective of this article is to explain and guide the correlation ship between the clinical findings in the patient and the parameters of arterial blood gases in a simple and precise manner, in order to make the correct acid-base balance diagnosis and adequate therapeutic interventions. A non-systematic review of the sci...

Cortical Representations of Speech in a Multitalker Auditory Scene.

Science.gov (United States)

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

New solutions of the Yang-Baxter equation based on root of 1 representations of the Para-Bose superalgebra Uq[osp(1/2)

International Nuclear Information System (INIS)

Palev, T.D.; Stoilova, N.I.

1995-07-01

New solutions of the quantum Yang-Baxter equation, depending in general on three arbitrary parameters, are written down. They are based on the root of unity representations of the quantum orthosymplectic superalgebra U q [osp(1/2)], which were found recently. Representations of the braid group B N are defined within any N th tensorial power of root of 1 U q [osp(1/2)] modules. (author). 40 refs

Covariant representations of nuclear *-algebras

International Nuclear Information System (INIS)

Moore, S.M.

1978-01-01

Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations

Acid-base transport in pancreas – new challenges

Directory of Open Access Journals (Sweden)

Ivana eNovak

2013-12-01

Full Text Available Along the gastrointestinal tract a number of epithelia contribute with acid or basic secretions in order to aid digestive processes. The stomach and pancreas are the most extreme examples of acid (H+ and base (HCO3- transporters, respectively. Nevertheless, they share the same challenges of transporting acid and bases across epithelia and effectively regulating their intracellular pH. In this review, we will make use of comparative physiology to enlighten the cellular mechanisms of pancreatic HCO3- and fluid secretion, which is still challenging physiologists. Some of the novel transporters to consider in pancreas are the proton pumps (H+-K+-ATPases, as well as the calcium-activated K+ and Cl- channels, such as KCa3.1 and TMEM16A/ANO1. Local regulators, such as purinergic signalling, fine-tune and coordinate pancreatic secretion. Lastly, we speculate whether dys-regulation of acid-base transport contributes to pancreatic diseases including cystic fibrosis, pancreatitis and cancer.

The normal acid-base status of mice.

Science.gov (United States)

Iversen, Nina K; Malte, Hans; Baatrup, Erik; Wang, Tobias

2012-03-15

Rodent models are commonly used for various physiological studies including acid-base regulation. Despite the widespread use of especially genetic modified mice, little attention have been made to characterise the normal acid-base status in these animals in order to reveal proper control values. Furthermore, several studies report blood gas values obtained in anaesthetised animals. We, therefore, decided to characterise blood CO(2) binding characteristic of mouse blood in vitro and to characterise normal acid-base status in conscious BALBc mice. In vitro CO(2) dissociation curves, performed on whole blood equilibrated to various PCO₂ levels in rotating tonometers, revealed a typical mammalian pK' (pK'=7.816-0.234 × pH (r=0.34)) and a non-bicarbonate buffer capacity (16.1 ± 2.6 slyke). To measure arterial acid-base status, small blood samples were taken from undisturbed mice with indwelling catheters in the carotid artery. In these animals, pH was 7.391 ± 0.026, plasma [HCO(3)(-)] 18.4 ± 0.83 mM, PCO₂ 30.3 ± 2.1 mm Hg and lactate concentration 4.6 ± 0.7 mM. Our study, therefore, shows that mice have an arterial pH that resembles other mammals, although arterial PCO₂ tends to be lower than in larger mammals. However, pH from arterial blood sampled from mice anaesthetised with isoflurane was significantly lower (pH 7.239 ± 0.021), while plasma [HCO(3)(-)] was 18.5 ± 1.4 mM, PCO₂ 41.9 ± 2.9 mm Hg and lactate concentration 4.48 ± 0.67 mM. Furthermore, we measured metabolism and ventilation (V(E)) in order to determine the ventilation requirements (VE/VO₂) to answer whether small mammals tend to hyperventilate. We recommend, therefore, that studies on acid-base regulation in mice should be based on samples taken for indwelling catheters rather than cardiac puncture of terminally anaesthetised mice. Copyright © 2011 Elsevier B.V. All rights reserved.

Profile of biology prospective teachers’ representation on plant anatomy learning

Science.gov (United States)

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.

Face antispoofing based on frame difference and multilevel representation

Science.gov (United States)

Benlamoudi, Azeddine; Aiadi, Kamal Eddine; Ouafi, Abdelkrim; Samai, Djamel; Oussalah, Mourad

2017-07-01

Due to advances in technology, today's biometric systems become vulnerable to spoof attacks made by fake faces. These attacks occur when an intruder attempts to fool an established face-based recognition system by presenting a fake face (e.g., print photo or replay attacks) in front of the camera instead of the intruder's genuine face. For this purpose, face antispoofing has become a hot topic in face analysis literature, where several applications with antispoofing task have emerged recently. We propose a solution for distinguishing between real faces and fake ones. Our approach is based on extracting features from the difference between successive frames instead of individual frames. We also used a multilevel representation that divides the frame difference into multiple multiblocks. Different texture descriptors (local binary patterns, local phase quantization, and binarized statistical image features) have then been applied to each block. After the feature extraction step, a Fisher score is applied to sort the features in ascending order according to the associated weights. Finally, a support vector machine is used to differentiate between real and fake faces. We tested our approach on three publicly available databases: CASIA Face Antispoofing database, Replay-Attack database, and MSU Mobile Face Spoofing database. The proposed approach outperforms the other state-of-the-art methods in different media and quality metrics.

Orienting Attention to Sound Object Representations Attenuates Change Deafness

Science.gov (United States)

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…

Reusable Lexical Representations for Idioms

NARCIS (Netherlands)

Odijk, J.E.J.M.

2004-01-01

In this paper I introduce (1) a technically simple and highly theory-independent way for lexically representing flexible idiomatic expressions, and (2) a procedure to incorporate these lexical representations in a wide variety of NLP systems. The method is based on Structural EQuivalence Classes

Conceptual Knowledge Representation and Reasoning

DEFF Research Database (Denmark)

Oldager, Steen Nikolaj

2003-01-01

One of the main areas in knowledge representation and logic-based artificial intelligence concerns logical formalisms that can be used for representing and reasoning with concepts. For almost 30 years, since research in this area began, the issue of intensionality has had a special status...

Reactive Distillation for Esterification of Bio-based Organic Acids

Energy Technology Data Exchange (ETDEWEB)

Fields, Nathan; Miller, Dennis J.; Asthana, Navinchandra S.; Kolah, Aspi K.; Vu, Dung; Lira, Carl T.

2008-09-23

The following is the final report of the three year research program to convert organic acids to their ethyl esters using reactive distillation. This report details the complete technical activities of research completed at Michigan State University for the period of October 1, 2003 to September 30, 2006, covering both reactive distillation research and development and the underlying thermodynamic and kinetic data required for successful and rigorous design of reactive distillation esterification processes. Specifically, this project has led to the development of economical, technically viable processes for ethyl lactate, triethyl citrate and diethyl succinate production, and on a larger scale has added to the overall body of knowledge on applying fermentation based organic acids as platform chemicals in the emerging biorefinery. Organic acid esters constitute an attractive class of biorenewable chemicals that are made from corn or other renewable biomass carbohydrate feedstocks and replace analogous petroleum-based compounds, thus lessening U.S. dependence on foreign petroleum and enhancing overall biorefinery viability through production of value-added chemicals in parallel with biofuels production. Further, many of these ester products are candidates for fuel (particularly biodiesel) components, and thus will serve dual roles as both industrial chemicals and fuel enhancers in the emerging bioeconomy. The technical report from MSU is organized around the ethyl esters of four important biorenewables-based acids: lactic acid, citric acid, succinic acid, and propionic acid. Literature background on esterification and reactive distillation has been provided in Section One. Work on lactic acid is covered in Sections Two through Five, citric acid esterification in Sections Six and Seven, succinic acid in Section Eight, and propionic acid in Section Nine. Section Ten covers modeling of ester and organic acid vapor pressure properties using the SPEAD (Step Potential

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

Energy Technology Data Exchange (ETDEWEB)

Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Chen, Ken Chung [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Stomatology, National Cheng Kung University Medical College and Hospital, Tainan, Taiwan 70403 (China); Shen, Steve G. F.; Yan, Jin [Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Lee, Philip K. M.; Chow, Ben [Hong Kong Dental Implant and Maxillofacial Centre, Hong Kong, China 999077 (China); Liu, Nancy X. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, China 100050 (China); Xia, James J. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul, 136701 (Korea, Republic of)

2014-04-15

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

International Nuclear Information System (INIS)

Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang; Chen, Ken Chung; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Liu, Nancy X.; Xia, James J.; Shen, Dinggang

2014-01-01

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

A knowledge based advisory system for acid/base titrations in non-aqueous solvents

NARCIS (Netherlands)

Bos, M.; van der Linden, W.E.

1996-01-01

A computer program was developed that could advice on the choice of solvent and titrant for acid/base titrations in nonaqueous media. It is shown that the feasibility of a titration in a given solvent can be calculated from solvent properties and intrinsic acid/base properties of the sample

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

Science.gov (United States)

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.

Interactive Shape Modeling using a Skeleton-Mesh Co-Representation

DEFF Research Database (Denmark)

Bærentzen, Jacob Andreas; Abdrashitov, Rinat; Singh, Karan

2014-01-01

We introduce the Polar-Annular Mesh representation (PAM). A PAM is a mesh-skeleton co-representation designed for the modeling of 3D organic, articulated shapes. A PAM represents a manifold mesh as a partition of polar (triangle fans) and annular (rings of quads) regions. The skeletal topology of...... a PAM to a quad-only mesh. We further present a PAM-based multi-touch sculpting application in order to demonstrate its utility as a shape representation for the interactive modeling of organic, articulated figures as well as for editing and posing of pre-existing models....

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

Science.gov (United States)

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.

Social representations about religion and spirituality.

Science.gov (United States)

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.

Standard model of knowledge representation

Science.gov (United States)

Yin, Wensheng

2016-09-01

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

The relationship between odd- and branched-chain fatty acids and microbial nucleic acid bases in rumen

Directory of Open Access Journals (Sweden)

Keyuan Liu

2017-11-01

Full Text Available Objective This study aims to identify the relationship between odd- and branched-chain fatty acids (OBCFAs and microbial nucleic acid bases in the rumen, and to establish a model to accurately predict microbial protein flow by using OBCFA. Methods To develop the regression equations, data on the rumen contents of individual cows were obtained from 2 feeding experiments. In the first experiment, 3 rumen-fistulated dry dairy cows arranged in a 3×3 Latin square were fed diets of differing forage to concentration ratios (F:C. The second experiment consisted of 9 lactating Holstein dairy cows of similar body weights at the same stage of pregnancy. For each lactation stage, 3 cows with similar milk production were selected. The rumen contents were sampled at 4 time points of every two hours after morning feeding 6 h, and then to analyse the concentrations of OBCFA and microbial nucleic acid bases in the rumen samples. Results The ruminal bacteria nucleic acid bases were significantly influenced by feeding diets of differing forge to concentration ratios and lactation stages of dairy cows (p<0.05. The concentrations of OBCFAs, especially odd-chain fatty acids and C15:0 isomers, strongly correlated with the microbial nucleic acid bases in the rumen (p<0.05. The equations of ruminal microbial nucleic acid bases established by ruminal OBCFAs contents showed a good predictive capacity, as indicated by reasonably low standard errors and high R-squared values. Conclusion This finding suggests that the rumen OBCFA composition could be used as an internal marker of rumen microbial matter.

Anticipation in cybernetic systems : A case against mindless anti-representationalism

NARCIS (Netherlands)

Schomaker, L

2004-01-01

The developments in behavior-based robotics and in ecological psychology have had a strong effect on theoretical development in some research communities. A new belief has emerged under the name of anti-representationalism, which is strongly opposed to the notion of representations in cognition.

3D base: a geometrical data base system for the analysis and visualisation of 3D-shapes obtained from parallel serial sections including three different geometrical representations

NARCIS (Netherlands)

Verbeek, F. J.; de Groot, M. M.; Huijsmans, D. P.; Lamers, W. H.; Young, I. T.

1993-01-01

In this paper we discuss a geometrical data base that includes three different geometrical representations of one and the same reconstructed 3D shape: the contour-pile, the voxel enumeration, and the triangulation of a surface. The data base is tailored for 3D shapes obtained from plan-parallel

In situ Recovery of Bio-Based Carboxylic Acids

Energy Technology Data Exchange (ETDEWEB)

Karp, Eric M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Saboe, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Manker, Lorenz [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Michener, William E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Peterson, Darren J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Brandner, David [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Deutch, Stephen P [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cywar, Robin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Beckham, Gregg T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kumar, Manish [Pennsylvania State University

2018-03-16

The economics of chemical and biological processes is often dominated by the expense of downstream product separations from dilute product streams. Continuous separation techniques, such as in situ product recovery (ISPR), are attractive in that they can concentrate products from a reactor and minimize solvent loss, thereby increasing purity and sustainability of the process. In bioprocesses, ISPR can have an additional advantage of increasing productivity by alleviating product inhibition on the microorganism. In this work, we developed a liquid-liquid extraction (LLE)-based ISPR system integrated with downstream distillation to selectively purify free carboxylic acids, which were selected as exemplary bioproducts due to their ability to be produced at industrially relevant titers and productivities. Equilibrium constants for the extraction of carboxylic acids into a phosphine-oxide based organic phase were experimentally determined. Complete recovery of acids from the extractant and recyclability of the organic phase were demonstrated through multiple extraction-distillation cycles. Using these data, an equilibrium model was developed to predict the acid loading in the organic phase as a function of the extraction equilibrium constant, initial aqueous acid concentration, pH, organic to aqueous volume ratio, and temperature. A distillation process model was then used to predict the energy input required to distill neat acid from an organic phase as a function of the acid loading in the organic phase feed. The heat integrated distillation train can achieve neat recovery of acetic acid with an energy input of 2.6 MJ kg-1 of acetic acid. This LLE-based ISPR system integrated with downstream distillation has an estimated carbon footprint of less than 0.36 kg CO2 per kg of acetic acid, and provides a green approach to enable both new industrial bioprocesses, and process intensification of existing industrial operations by (1) increasing the productivity and titer of

Converting boundary representation solid models to half-space representation models for Monte Carlo analysis

International Nuclear Information System (INIS)

Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.

2007-01-01

Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)

Multimodal semantic quantity representations: further evidence from Korean Sign Language

Directory of Open Access Journals (Sweden)

Frank eDomahs

2012-01-01

Full Text Available Korean deaf signers performed a number comparison task on pairs of Arabic digits. In their RT profiles, the expected magnitude effect was systematically modified by properties of number signs in Korean Sign Language in a culture-specific way (not observed in hearing and deaf Germans or hearing Chinese. We conclude that finger-based quantity representations are automatically activated even in simple tasks with symbolic input although this may be irrelevant and even detrimental for task performance. These finger-based numerical representations are accessed in addition to another, more basic quantity system which is evidenced by the magnitude effect. In sum, these results are inconsistent with models assuming only one single amodal representation of numerical quantity.

The Past Is Present: Representations of Parents, Friends, and Romantic Partners Predict Subsequent Romantic Representations.

Science.gov (United States)

Furman, Wyndol; Collibee, Charlene

2018-01-01

This study examined how representations of parent-child relationships, friendships, and past romantic relationships are related to subsequent romantic representations. Two-hundred 10th graders (100 female; M age  = 15.87 years) from diverse neighborhoods in a Western U.S. city were administered questionnaires and were interviewed to assess avoidant and anxious representations of their relationships with parents, friends, and romantic partners. Participants then completed similar questionnaires and interviews about their romantic representations six more times over the next 7.5 years. Growth curve analyses revealed that representations of relationships with parents, friends, and romantic partners each uniquely predicted subsequent romantic representations across development. Consistent with attachment and behavioral systems theory, representations of romantic relationships are revised by representations and experiences in other relationships. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

Science.gov (United States)

Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

2017-01-21

RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA

Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets

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Wu, Yue; Shang, Pengjian; Li, Yilong

2018-03-01

A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.

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

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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

Concise and Accessible Representations for Multidimensional Datasets: Introducing a Framework Based on the nD-EVM and Kohonen Networks

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Ricardo Pérez-Aguila

2015-01-01

Full Text Available A new framework intended for representing and segmenting multidimensional datasets resulting in low spatial complexity requirements and with appropriate access to their contained information is described. Two steps are going to be taken in account. The first step is to specify (n-1D hypervoxelizations, n≥2, as Orthogonal Polytopes whose nth dimension corresponds to color intensity. Then, the nD representation is concisely expressed via the Extreme Vertices Model in the n-Dimensional Space (nD-EVM. Some examples are presented, which, under our methodology, have storing requirements minor than those demanded by their original hypervoxelizations. In the second step, 1-Dimensional Kohonen Networks (1D-KNs are applied in order to segment datasets taking in account their geometrical and topological properties providing a non-supervised way to compact even more the proposed n-Dimensional representations. The application of our framework shares compression ratios, for our set of study cases, in the range 5.6496 to 32.4311. Summarizing, the contribution combines the power of the nD-EVM and 1D-KNs by producing very concise datasets’ representations. We argue that the new representations also provide appropriate segmentations by introducing some error functions such that our 1D-KNs classifications are compared against classifications based only in color intensities. Along the work, main properties and algorithms behind the nD-EVM are introduced for the purpose of interrogating the final representations in such a way that it efficiently obtains useful geometrical and topological information.

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

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Antje Kohnle

2017-11-01

Full Text Available 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.

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

Science.gov (United States)

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.

Fall Detection for Elderly from Partially Observed Depth-Map Video Sequences Based on View-Invariant Human Activity Representation

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Rami Alazrai

2017-03-01

Full Text Available This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for human activity representation, called the motion-pose geometric descriptor (MPGD. Furthermore, we have developed a histogram-based representation (HBR based on the MPGD to construct a length-independent representation of the observed video subsequences. Using the constructed HBR, we formulate the fall detection problem as a posterior-maximization problem in which the posteriori probability for each observed video subsequence is estimated using a multi-class SVM (support vector machine classifier. Then, we combine the computed posteriori probabilities from all of the observed subsequences to obtain an overall class posteriori probability of the entire partially-observed depth-map video sequence. To evaluate the performance of the proposed approach, we have utilized the Kinect sensor to record a dataset of depth-map video sequences that simulates four fall-related activities of elderly people, including: walking, sitting, falling form standing and falling from sitting. Then, using the collected dataset, we have developed three evaluation scenarios based on the number of unobserved video subsequences in the testing videos, including: fully-observed video sequence scenario, single unobserved video subsequence of random lengths scenarios and two unobserved video subsequences of random lengths scenarios. Experimental results show that the proposed approach achieved an average recognition accuracy of 93 . 6 % , 77 . 6 % and 65 . 1 % , in recognizing the activities during the first, second and third evaluation scenario, respectively. These results demonstrate the feasibility of the proposed approach to detect falls from partially-observed videos.

Lewis Acid-Base Chemistry of 7-Azaisoindigo-Based Organic Semiconductors.

Science.gov (United States)

Randell, Nicholas M; Fransishyn, Kyle M; Kelly, Timothy L

2017-07-26

Low-band-gap organic semiconductors are important in a variety of organic electronics applications, such as organic photovoltaic devices, photodetectors, and field effect transistors. Building on our previous work, which introduced 7-azaisoindigo as an electron-deficient building block for the synthesis of donor-acceptor organic semiconductors, we demonstrate how Lewis acids can be used to further tune the energies of the frontier molecular orbitals. Coordination of a Lewis acid to the pyridinic nitrogen of 7-azaisoindigo greatly diminishes the electron density in the azaisoindigo π-system, resulting in a substantial reduction in the lowest unoccupied molecular orbital (LUMO) energy. This results in a smaller highest occupied molecular orbital-LUMO gap and shifts the lowest-energy electronic transition well into the near-infrared region. Both H + and BF 3 are shown to coordinate to azaisoindigo and affect the energy of the S 0 → S 1 transition. A combination of time-dependent density functional theory and UV/vis and 1 H NMR spectroscopic titrations reveal that when two azaisoindigo groups are present and high concentrations of acid are used, both pyridinic nitrogens bind Lewis acids. Importantly, we demonstrate that this acid-base chemistry can be carried out at the solid-vapor interface by exposing thin films of aza-substituted organic semiconductors to vapor-phase BF 3 ·Et 2 O. This suggests the possibility of using the BF 3 -bound 7-azaisoindigo-based semiconductors as n-type materials in various organic electronic applications.

Scenarios, personas and user stories from design ethnography: Evidence-based design representations of communicable disease investigations

Science.gov (United States)

Turner, Anne M; Reeder, Blaine; Ramey, Judith

2014-01-01

Purpose Despite years of effort and millions of dollars spent to create a unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of User Center Design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to communicable disease (CD) monitoring and control at a local health department, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. Methods We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health department communicable disease workflow. Informed by principles of design ethnography and user-centered design (UCD) we created persona, scenarios and user stories to accurately represent the user to system designers. Results We sought to convey to designers the key findings from ethnographic studies: 1) that public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed 2) health department efforts are focused on CD investigation and response rather than reporting and 3) current CD information systems must conform to PH workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Conclusions Through application of user centered design principles, we were able to create design representations that illustrate complex public health communicable

Boronic acid-based chemical sensors for saccharides.

Science.gov (United States)

Zhang, Xiao-Tai; Liu, Guang-Jian; Ning, Zhang-Wei; Xing, Guo-Wen

2017-11-27

During the past decades, the interaction between boronic acids-functionalized sensors and saccharides is of great interest in the frontier domain of the interdiscipline concerning both biology and chemistry. Various boronic acid-based sensing systems have been developed to detect saccharides and corresponding derivatives in vitro as well as in vivo, which embrace unimolecular sensors, two-component sensing ensembles, functional assemblies, and boronic acid-loaded nanomaterials or surfaces. New sensing strategies emerge in endlessly with excellent selectivity and sensitivity. In this review, several typical sensing systems were introduced and some promising examples were highlighted to enable the deep insight of saccharides sensing on the basis of boronic acids. Copyright © 2017 Elsevier Ltd. All rights reserved.

Perception of oyster-based products by French consumers. The effect of processing and role of social representations.

Science.gov (United States)

Debucquet, Gervaise; Cornet, Josiane; Adam, Isabelle; Cardinal, Mireille

2012-12-01

The search for new markets in the seafood sector, associated with the question of the continuity of raw oyster consumption over generations can be an opportunity for processors to extend their ranges with oyster-based products. The twofold aim of this study was to evaluate the impact of processing and social representation on perception of oyster-based products by French consumers and to identify the best means of development in order to avoid possible failure in the market. Five products with different degrees of processing (cooked oysters in a half-shell, hot preparation for toast, potted oyster, oyster butter and oyster-based soup) were presented within focus groups and consumer tests, at home and in canteens with the staff of several companies in order to reach consumers with different ages and professional activities. The results showed that social representation had a strong impact and that behaviours were contrasted according to the initial profile of the consumer (traditional raw oyster consumers or non-consumers) and their age distribution (younger and older people). The degree of processing has to be adapted to each segment. It is suggested to develop early exposure to influence the food choices and preferences of the youngest consumers on a long-term basis. Copyright © 2012 Elsevier Ltd. All rights reserved.

Acidic-Basic Properties of Three Alanine-Based Peptides Containing Acidic and Basic Side Chains: Comparison Between Theory and Experiment

OpenAIRE

Makowska, Joanna; Bagińska, Katarzyna; Liwo, Adam; Chmurzyński, Lech; Scheraga, Harold A.

2008-01-01

The purpose of this work was to evaluate the effect of the nature of the ionizable end groups, and the solvent, on their acid-base properties in alanine-based peptides. Hence, the acid-base properties of three alanine-based peptides: Ac-KK-(A)7-KK-NH2 (KAK), Ac-OO-(A)7-DD-NH2 (OAD), Ac-KK-(A)7-EE-NH2 (KAE), where A, D, E, K, and O denote alanine, aspartic acid, glutamic acid, lysine, and ornithine, respectively, were determined in water and in methanol by potentiometry. With the availability ...

Activities of Heterogeneous Acid-Base Catalysts for Fragrances Synthesis: A Review

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Hartati Hartati

2013-06-01

Full Text Available This paper reviews various types of heterogeneous acid-base catalysts for fragrances preparation. Catalytic activities of various types of heterogeneous acid and base catalysts in fragrances preparation, i.e. non-zeolitic, zeolitic, and mesoporous molecular sieves have been reported. Generally, heterogeneous acid catalysts are commonly used in fragrance synthesis as compared to heterogeneous base catalysts. Heteropoly acids and hydrotalcites type catalysts are widely used as heterogeneous acid and base catalysts, respectively. © 2013 BCREC UNDIP. All rights reservedReceived: 20th January 2013; Revised: 31st March 2013; Accepted: 1st April 2013[How to Cite: Hartati, H., Santoso, M., Triwahyono, S., Prasetyoko, D. (2013. Activities of Heterogeneous Acid-Base Catalysts for Fragrances Synthesis: A Review. Bulletin of Chemical Reaction Engineering & Catalysis, 8 (1: 14-33. (doi:10.9767/bcrec.8.1.4394.14-33][Permalink/DOI: http://dx.doi.org/10.9767/bcrec.8.1.4394.14-33] | View in  |

Evaluating Interest in Acids-Bases: Development of an Acid-Base Interest Scale (ABIS) and Assessment of Pre-Service Science Teachers' Interest

Science.gov (United States)

Çiçek, Ö.; Ilhan, N.

2017-01-01

Students are more likely to be successful in topics they are interested in than others. This study aims to develop an Acid-Base Interest Scale (ABIS) and subsequently evaluate the interest of pre-service science teachers in acids-bases according to gender, years at the university, type of high school the pre-service science teachers attended, and…

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

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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.

Soluble adenylyl cyclase is an acid-base sensor in epithelial base-secreting cells.

Science.gov (United States)

Roa, Jinae N; Tresguerres, Martin

2016-08-01

Blood acid-base regulation by specialized epithelia, such as gills and kidney, requires the ability to sense blood acid-base status. Here, we developed primary cultures of ray (Urolophus halleri) gill cells to study mechanisms for acid-base sensing without the interference of whole animal hormonal regulation. Ray gills have abundant base-secreting cells, identified by their noticeable expression of vacuolar-type H(+)-ATPase (VHA), and also express the evolutionarily conserved acid-base sensor soluble adenylyl cyclase (sAC). Exposure of cultured cells to extracellular alkalosis (pH 8.0, 40 mM HCO3 (-)) triggered VHA translocation to the cell membrane, similar to previous reports in live animals experiencing blood alkalosis. VHA translocation was dependent on sAC, as it was blocked by the sAC-specific inhibitor KH7. Ray gill base-secreting cells also express transmembrane adenylyl cyclases (tmACs); however, tmAC inhibition by 2',5'-dideoxyadenosine did not prevent alkalosis-dependent VHA translocation, and tmAC activation by forskolin reduced the abundance of VHA at the cell membrane. This study demonstrates that sAC is a necessary and sufficient sensor of extracellular alkalosis in ray gill base-secreting cells. In addition, this study indicates that different sources of cAMP differentially modulate cell biology. Copyright © 2016 the American Physiological Society.

Respiratory Acid-Base Disorders in the Critical Care Unit.

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Hopper, Kate

2017-03-01

The incidence of respiratory acid-base abnormalities in the critical care unit (CCU) is unknown, although respiratory alkalosis is suspected to be common in this population. Abnormal carbon dioxide tension can have many physiologic effects, and changes in Pco 2 may have a significant impact on outcome. Monitoring Pco 2 in CCU patients is an important aspect of critical patient assessment, and identification of respiratory acid-base abnormalities can be valuable as a diagnostic tool. Treatment of respiratory acid-base disorders is largely focused on resolution of the primary disease, although mechanical ventilation may be indicated in cases with severe respiratory acidosis. Published by Elsevier Inc.

Social Representations of Intelligence

Directory of Open Access Journals (Sweden)

Elena Zubieta

2016-02-01

Full Text Available The article stresses the relationship between Explicit and Implicit theories of Intelligence. Following the line of common sense epistemology and the theory of Social Representations, a study was carried out in order to analyze naive’s explanations about Intelligence Definitions. Based on Mugny & Carugati (1989 research, a self-administered questionnaire was designed and filled in by 286 subjects. Results are congruent with the main hyphotesis postulated: A general overlap between explicit and implicit theories showed up. According to the results Intelligence appears as both, a social attribute related to social adaptation and as a concept defined in relation with contextual variables similar to expert’s current discourses. Nevertheless, conceptions based on “gifted ideology” still are present stressing the main axes of Intelligence debate: biological and sociological determinism. In the same sense, unfamiliarity and social identity are reaffirmed as organizing principles of social representation. The distance with the object -measured as the belief in intelligence differences as a solve/non solve problem- and the level of implication with the topic -teachers/no teachers- appear as discriminating elements at the moment of supporting specific dimensions. 

Introduction to computer data representation

CERN Document Server

Fenwick, Peter

2014-01-01

Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and 'universal' or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic repre

Acidity constants from DFT-based molecular dynamics simulations

International Nuclear Information System (INIS)

Sulpizi, Marialore; Sprik, Michiel

2010-01-01

In this contribution we review our recently developed method for the calculation of acidity constants from density functional theory based molecular dynamics simulations. The method is based on a half reaction scheme in which protons are formally transferred from solution to the gas phase. The corresponding deprotonation free energies are computed from the vertical energy gaps for insertion or removal of protons. Combined to full proton transfer reactions, the deprotonation energies can be used to estimate relative acidity constants and also the Broensted pK a when the deprotonation free energy of a hydronium ion is used as a reference. We verified the method by investigating a series of organic and inorganic acids and bases spanning a wide range of pK a values (20 units). The thermochemical corrections for the biasing potentials assisting and directing the insertion are discussed in some detail.

Respiratory Adaptations in Acid-base Disturbances: Role of Cerebral Fluids,

Science.gov (United States)

1979-06-19

The respiratory and metabolic components of acid-base homeostasis are defined. A quantitative empirical description of the (incomplete) mutual...literature. Respiratory adaptations in steady acid-base disturbances of metabolic origin (hyperventilation with hypocapnia in primary metabolic acidosis, and...hypoventilation with hypercapnia in metabolic alkalosis ) are analyzed as a function of the acidity of the cerebral fluids (cerebrospinal and cerebral interstitial fluid). (Author)

Acid-base equilibria inside amine-functionalized mesoporous silica.

Science.gov (United States)

Yamaguchi, Akira; Namekawa, Manato; Kamijo, Toshio; Itoh, Tetsuji; Teramae, Norio

2011-04-15

Acid-base equilibria and effective proton concentration inside a silica mesopore modified with a trimethyl ammonium (TMAP) layer were studied by steady-state fluorescence experiments. The mesoporous silica with a dense TMAP layer (1.4 molecules/nm(2)) was prepared by a post grafting of N-trimethoxysilylpropyl-N,N,N-trimethylammonium at surfactant-templated mesoporous silica (diameter of silica framework =3.1 nm). The resulting TMAP-modified mesoporous silica strongly adsorbed of anionic fluorescence indicator dyes (8-hydroxypyrene-1,3,6-trisulfonate (pyranine), 8-aminopyrene-1,3,6-trisulfonate (APTS), 5,10,15,20-tetraphenyl-21H,23H-porphinetetrasulfonic acid disulfuric acid (TPPS), 2-naphthol-3,6-disulfonate (2NT)) and fluorescence excitation spectra of these dyes within TMAP-modified mesoporous silica were measured by varying the solution pH. The fluorescence experiments revealed that the acid-base equilibrium reactions of all pH indicator dyes within the TMAP-modified silica mesopore were quite different from those in bulk water. From the analysis of the acid-base equilibrium of pyranine, the following relationships between solution pH (pH(bulk)) and the effective proton concentration inside the pore (pH(pore)) were obtained: (1) shift of pH(pore) was 1.8 (ΔpH(pore)=1.8) for the pH(bulk) change from 2.1 to 9.1 (ΔpH(bulk)=7.0); (2) pH(pore) was not simply proportional to pH(bulk); (3) the inside of the TMAP-modified silica mesopore was suggested to be in a weak acidic or neutral condition when pH(bulk) was changed from 2.0 to 9.1. Since these relationships between pH(bulk) and pH(pore) could explain the acid-base equilibria of other pH indicator dyes (APTS, TPPS, 2NT), these relationships were inferred to describe the effective proton concentration inside the TMAP-modified silica mesopore. © 2011 American Chemical Society

An Alternative to Synthetic Acid Base Indicator-Tagetes Erecta Linn

OpenAIRE

*A. Elumalai; M. C. Eswariah; M. K. Chinna; B. A. Kumar

2012-01-01

The present work highlights the use of the methanolic extract of the flowers of Tagetes erecta as an acid-base indicator in acid-base titrations. This natural indicator is easy to extract as well as easily available. Indicators used in titration show well marked changes of colour in certain intervals of pH. Most of these indicators are organic dyes and are of synthetic origin. Today synthetic indicators are the choice of acid-base titrations. But due to environmental pollution, availability a...

Synthesis and antimicrobial activities of new higher amino acid Schiff base derivatives of 6-aminopenicillanic acid and 7-aminocephalosporanic acid

Science.gov (United States)

Özdemir (nee Güngör), Özlem; Gürkan, Perihan; Özçelik, Berrin; Oyardı, Özlem

2016-02-01

Novel β-lactam derivatives (1c-3c) (1d-3d) were produced by using 6-aminopenicillanic acid (6-APA), 7-aminocephalosporanic acid (7-ACA) and the higher amino acid Schiff bases. The synthesized compounds were characterized by elemental analysis, IR, 1H/13C NMR and UV-vis spectra. Antibacterial activities of all the higher amino acid Schiff bases (1a-3a) (1b-3b) and β-lactam derivatives were screened against three gram negative bacteria (Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, Acinetobacter baumannii RSKK 02026), three gram positive bacteria (Staphylococcus aureus ATCC 25923, Enterococcus faecalis ATCC 07005, Bacillus subtilis ATCC 6633) and their drug-resistant isolates by using broth microdilution method. Two fungi (Candida albicans and Candida krusei) were used for antifungal activity.

An evaluation of space time cube representation of spatiotemporal patterns.

Science.gov (United States)

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.

Semi-analytical Karhunen-Loeve representation of irregular waves based on the prolate spheroidal wave functions

Science.gov (United States)

Lee, Gibbeum; Cho, Yeunwoo

2018-01-01

A new semi-analytical approach is presented to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of direct numerical approach to this matrix eigenvalue problem, which may suffer from the computational inaccuracy for big data, a pair of integral and differential equations are considered, which are related to the so-called prolate spheroidal wave functions (PSWF). First, the PSWF is expressed as a summation of a small number of the analytical Legendre functions. After substituting them into the PSWF differential equation, a much smaller size matrix eigenvalue problem is obtained than the direct numerical K-L matrix eigenvalue problem. By solving this with a minimal numerical effort, the PSWF and the associated eigenvalue of the PSWF differential equation are obtained. Then, the eigenvalue of the PSWF integral equation is analytically expressed by the functional values of the PSWF and the eigenvalues obtained in the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data such as ordinary irregular waves. It is found that, with the same accuracy, the required memory size of the present method is smaller than that of the direct numerical K-L representation and the computation time of the present method is shorter than that of the semi-analytical method based on the sinusoidal functions.

Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

Directory of Open Access Journals (Sweden)

Bo Kong

2017-01-01

Full Text Available In an integrated radar-communication network, multiuser access techniques with minimal performance degradation and without range-Doppler ambiguities are required, especially in a dense user environment. In this paper, a multiuser access scheme with random subcarrier allocation mechanism is proposed for orthogonal frequency division multiplexing (OFDM based integrated radar-communication networks. The expression of modulation Symbol-Domain method combined with sparse representation (SR for range-Doppler estimation is introduced and a parallel reconstruction algorithm is employed. The radar target detection performance is improved with less spectrum occupation. Additionally, a Doppler frequency detector is exploited to decrease the computational complexity. Numerical simulations show that the proposed method outperforms the traditional modulation Symbol-Domain method under ideal and realistic nonideal scenarios.

When acid-base titrations are carried out in unusual conditions

Directory of Open Access Journals (Sweden)

Domenico De Marco

2012-12-01

Full Text Available Uncommon aspects in acid-base titrations are presented, which occur in titrations between both mono- and/or poly-functional acid and bases but are rarely introduced in ordinary analytical chemistry courses.

Hard and soft acids and bases: atoms and atomic ions.

Science.gov (United States)

Reed, James L

2008-07-07

The structural origin of hard-soft behavior in atomic acids and bases has been explored using a simple orbital model. The Pearson principle of hard and soft acids and bases has been taken to be the defining statement about hard-soft behavior and as a definition of chemical hardness. There are a number of conditions that are imposed on any candidate structure and associated property by the Pearson principle, which have been exploited. The Pearson principle itself has been used to generate a thermodynamically based scale of relative hardness and softness for acids and bases (operational chemical hardness), and a modified Slater model has been used to discern the electronic origin of hard-soft behavior. Whereas chemical hardness is a chemical property of an acid or base and the operational chemical hardness is an experimental measure of it, the absolute hardness is a physical property of an atom or molecule. A critical examination of chemical hardness, which has been based on a more rigorous application of the Pearson principle and the availability of quantitative measures of chemical hardness, suggests that the origin of hard-soft behavior for both acids and bases resides in the relaxation of the electrons not undergoing transfer during the acid-base interaction. Furthermore, the results suggest that the absolute hardness should not be taken as synonymous with chemical hardness but that the relationship is somewhat more complex. Finally, this work provides additional groundwork for a better understanding of chemical hardness that will inform the understanding of hardness in molecules.

The Roles of Acids and Bases in Enzyme Catalysis

Science.gov (United States)

Weiss, Hilton M.

2007-01-01

Many organic reactions are catalyzed by strong acids or bases that protonate or deprotonate neutral reactants leading to reactive cations or anions that proceed to products. In enzyme reactions, only weak acids and bases are available to hydrogen bond to reactants and to transfer protons in response to developing charges. Understanding this…

Complexity in Acid–Base Titrations: Multimer Formation Between Phosphoric Acids and Imines

Science.gov (United States)

Malm, Christian; Kim, Heejae; Wagner, Manfred

2017-01-01

Abstract Solutions of Brønsted acids with bases in aprotic solvents are not only common model systems to study the fundamentals of proton transfer pathways but are also highly relevant to Brønsted acid catalysis. Despite their importance the light nature of the proton makes characterization of acid–base aggregates challenging. Here, we track such acid–base interactions over a broad range of relative compositions between diphenyl phosphoric acid and the base quinaldine in dichloromethane, by using a combination of dielectric relaxation and NMR spectroscopy. In contrast to what one would expect for an acid–base titration, we find strong deviations from quantitative proton transfer from the acid to the base. Even for an excess of the base, multimers consisting of one base and at least two acid molecules are formed, in addition to the occurrence of proton transfer from the acid to the base and simultaneous formation of ion pairs. For equimolar mixtures such multimers constitute about one third of all intermolecular aggregates. Quantitative analysis of our results shows that the acid‐base association constant is only around six times larger than that for the acid binding to an acid‐base dimer, that is, to an already protonated base. Our findings have implications for the interpretation of previous studies of reactive intermediates in organocatalysis and provide a rationale for previously observed nonlinear effects in phosphoric acid catalysis. PMID:28597513

Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

Directory of Open Access Journals (Sweden)

Ruan Jishou

2007-04-01

Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are

Embedded data representations

DEFF Research Database (Denmark)

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...

Categorification and higher representation theory

CERN Document Server

Beliakova, Anna

2017-01-01

The emergent mathematical philosophy of categorification is reshaping our view of modern mathematics by uncovering a hidden layer of structure in mathematics, revealing richer and more robust structures capable of describing more complex phenomena. Categorified representation theory, or higher representation theory, aims to understand a new level of structure present in representation theory. Rather than studying actions of algebras on vector spaces where algebra elements act by linear endomorphisms of the vector space, higher representation theory describes the structure present when algebras act on categories, with algebra elements acting by functors. The new level of structure in higher representation theory arises by studying the natural transformations between functors. This enhanced perspective brings into play a powerful new set of tools that deepens our understanding of traditional representation theory. This volume exhibits some of the current trends in higher representation theory and the diverse te...

Structure and functioning of the acid-base system in the Baltic Sea

Science.gov (United States)

Kuliński, Karol; Schneider, Bernd; Szymczycha, Beata; Stokowski, Marcin

2017-12-01

The marine acid-base system is relatively well understood for oceanic waters. Its structure and functioning is less obvious for the coastal and shelf seas due to a number of regionally specific anomalies. In this review article we collect and integrate existing knowledge of the acid-base system in the Baltic Sea. Hydrographical and biogeochemical characteristics of the Baltic Sea, as manifested in horizontal and vertical salinity gradients, permanent stratification of the water column, eutrophication, high organic-matter concentrations and high anthropogenic pressure, make the acid-base system complex. In this study, we summarize the general knowledge of the marine acid-base system as well as describe the peculiarities identified and reported for the Baltic Sea specifically. In this context we discuss issues such as dissociation constants in brackish water, different chemical alkalinity models including contributions by organic acid-base systems, long-term changes in total alkalinity, anomalies of borate alkalinity, and the acid-base effects of biomass production and mineralization. Finally, we identify research gaps and specify limitations concerning the Baltic Sea acid-base system.

Carbon-based strong solid acid for cornstarch hydrolysis

Science.gov (United States)

Nata, Iryanti Fatyasari; Irawan, Chairul; Mardina, Primata; Lee, Cheng-Kang

2015-10-01

Highly sulfonated carbonaceous spheres with diameter of 100-500 nm can be generated by hydrothermal carbonization of glucose in the presence of hydroxyethylsulfonic acid and acrylic acid at 180 °C for 4 h. The acidity of the prepared carbonaceous sphere C4-SO3H can reach 2.10 mmol/g. It was used as a solid acid catalyst for the hydrolysis of cornstarch. Total reducing sugar (TRS) concentration of 19.91 mg/mL could be obtained by hydrolyzing 20 mg/mL cornstarch at 150 °C for 6 h using C4-SO3H as solid acid catalyst. The solid acid catalyst demonstrated good stability that only 9% decrease in TRS concentration was observed after five repeat uses. The as-prepared carbon-based solid acid catalyst can be an environmentally benign replacement for homogeneous catalyst.

Wigner functions for noncommutative quantum mechanics: A group representation based construction

Energy Technology Data Exchange (ETDEWEB)

Chowdhury, S. Hasibul Hassan, E-mail: shhchowdhury@gmail.com [Chern Institute of Mathematics, Nankai University, Tianjin 300071 (China); Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada); Ali, S. Twareque, E-mail: twareque.ali@concordia.ca [Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada)

2015-12-15

This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group G{sub NC}, which is the three fold central extension of the Abelian group of ℝ{sup 4}. These representations have been exhaustively studied in earlier papers. The group G{sub NC} is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only.

Developing nucleic acid-based electrical detection systems

Directory of Open Access Journals (Sweden)

Gabig-Ciminska Magdalena

2006-03-01

Full Text Available Abstract Development of nucleic acid-based detection systems is the main focus of many research groups and high technology companies. The enormous work done in this field is particularly due to the broad versatility and variety of these sensing devices. From optical to electrical systems, from label-dependent to label-free approaches, from single to multi-analyte and array formats, this wide range of possibilities makes the research field very diversified and competitive. New challenges and requirements for an ideal detector suitable for nucleic acid analysis include high sensitivity and high specificity protocol that can be completed in a relatively short time offering at the same time low detection limit. Moreover, systems that can be miniaturized and automated present a significant advantage over conventional technology, especially if detection is needed in the field. Electrical system technology for nucleic acid-based detection is an enabling mode for making miniaturized to micro- and nanometer scale bio-monitoring devices via the fusion of modern micro- and nanofabrication technology and molecular biotechnology. The electrical biosensors that rely on the conversion of the Watson-Crick base-pair recognition event into a useful electrical signal are advancing rapidly, and recently are receiving much attention as a valuable tool for microbial pathogen detection. Pathogens may pose a serious threat to humans, animal and plants, thus their detection and analysis is a significant element of public health. Although different conventional methods for detection of pathogenic microorganisms and their toxins exist and are currently being applied, improvements of molecular-based detection methodologies have changed these traditional detection techniques and introduced a new era of rapid, miniaturized and automated electrical chip detection technologies into pathogen identification sector. In this review some developments and current directions in

The coulometric titration of acids and bases in m-cresol medium

NARCIS (Netherlands)

Bos, M.; Dahmen, E.A.M.F.

1974-01-01

A method is described for the coulometric titration of acids and bases in the solvent m-cresol. The method is suitable for bases with pKa values greater than 11 in m-cresol, or for acids with pKa values below 13 in m-cresol. Amounts of 5–50 μeq of acid or base can be determined with a relative

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

Science.gov (United States)

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.

Action simulation: time course and representational mechanisms

Science.gov (United States)

Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

2013-01-01

The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

Science.gov (United States)

Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

2001-03-01

This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

Representation and alignment of sung queries for music information retrieval

Science.gov (United States)

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.

Linking Video and Text via Representations of Narrative

OpenAIRE

Salway, Andrew; Graham, Mike; Tomadaki, Eleftheria; Xu, Yan

2003-01-01

The ongoing TIWO project is investigating the synthesis of language technologies, like information extraction and corpus-based text analysis, video data modeling and knowledge representation. The aim is to develop a computational account of how video and text can be integrated by representations of narrative in multimedia systems. The multimedia domain is that of film and audio description – an emerging text type that is produced specifically to be informative about the events and objects dep...

Consultation system with knowledge representation by decision rules

Energy Technology Data Exchange (ETDEWEB)

Senne, E L.F.; Simoni, P O

1982-04-01

The use of decision rules in the representation of empirical knowledge supplied by application domain experts is discussed. Based on this representation, a system is described which employs artificial intelligence techniques to yield inferences within a specific domain. Three modules composing the system are described: the acquisition one, that allows the insertion of new rules; the diagnostic one, that uses rules in the inference process; and the explanation one, that exhibits reasons for each system action.

Acid-base chemistry of white wine: analytical characterisation and chemical modelling.

Science.gov (United States)

Prenesti, Enrico; Berto, Silvia; Toso, Simona; Daniele, Pier Giuseppe

2012-01-01

A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria). Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids) with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture), ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic "wine" especially adapted for testing.

Acid-Base Chemistry of White Wine: Analytical Characterisation and Chemical Modelling

Directory of Open Access Journals (Sweden)

Enrico Prenesti

2012-01-01

Full Text Available A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria. Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture, ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic “wine” especially adapted for testing.

Acid-Base Chemistry of White Wine: Analytical Characterisation and Chemical Modelling

Science.gov (United States)

Prenesti, Enrico; Berto, Silvia; Toso, Simona; Daniele, Pier Giuseppe

2012-01-01

A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria). Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids) with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture), ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic “wine” especially adapted for testing. PMID:22566762

Carbon-based strong solid acid for cornstarch hydrolysis

Energy Technology Data Exchange (ETDEWEB)

Nata, Iryanti Fatyasari, E-mail: yanti_tkunlam@yahoo.com [Chemical Engineering Study Program, Faculty of Engineering, Lambung Mangkurat University, Jl. A. Yani Km. 36 Banjarbaru, South Kalimantan 70714 (Indonesia); Irawan, Chairul; Mardina, Primata [Chemical Engineering Study Program, Faculty of Engineering, Lambung Mangkurat University, Jl. A. Yani Km. 36 Banjarbaru, South Kalimantan 70714 (Indonesia); Lee, Cheng-Kang, E-mail: cklee@mail.ntust.edu.tw [Department of Chemical Engineering, National Taiwan University of Science and Technology, 43 Keelung Rd. Sec.4, Taipei 106, Taiwan (China)

2015-10-15

Highly sulfonated carbonaceous spheres with diameter of 100–500 nm can be generated by hydrothermal carbonization of glucose in the presence of hydroxyethylsulfonic acid and acrylic acid at 180 °C for 4 h. The acidity of the prepared carbonaceous sphere C4-SO{sub 3}H can reach 2.10 mmol/g. It was used as a solid acid catalyst for the hydrolysis of cornstarch. Total reducing sugar (TRS) concentration of 19.91 mg/mL could be obtained by hydrolyzing 20 mg/mL cornstarch at 150 °C for 6 h using C4-SO{sub 3}H as solid acid catalyst. The solid acid catalyst demonstrated good stability that only 9% decrease in TRS concentration was observed after five repeat uses. The as-prepared carbon-based solid acid catalyst can be an environmentally benign replacement for homogeneous catalyst. - Highlights: • Carbon solid acid was successfully prepared by one-step hydrothermal carbonization. • The acrylic acid as monomer was effectively reduce the diameter size of particle. • The solid acid catalyst show good catalytic performance of starch hydrolysis. • The solid acid catalyst is not significantly deteriorated after repeated use.

Carbon-based strong solid acid for cornstarch hydrolysis

International Nuclear Information System (INIS)

Nata, Iryanti Fatyasari; Irawan, Chairul; Mardina, Primata; Lee, Cheng-Kang

2015-01-01

Highly sulfonated carbonaceous spheres with diameter of 100–500 nm can be generated by hydrothermal carbonization of glucose in the presence of hydroxyethylsulfonic acid and acrylic acid at 180 °C for 4 h. The acidity of the prepared carbonaceous sphere C4-SO 3 H can reach 2.10 mmol/g. It was used as a solid acid catalyst for the hydrolysis of cornstarch. Total reducing sugar (TRS) concentration of 19.91 mg/mL could be obtained by hydrolyzing 20 mg/mL cornstarch at 150 °C for 6 h using C4-SO 3 H as solid acid catalyst. The solid acid catalyst demonstrated good stability that only 9% decrease in TRS concentration was observed after five repeat uses. The as-prepared carbon-based solid acid catalyst can be an environmentally benign replacement for homogeneous catalyst. - Highlights: • Carbon solid acid was successfully prepared by one-step hydrothermal carbonization. • The acrylic acid as monomer was effectively reduce the diameter size of particle. • The solid acid catalyst show good catalytic performance of starch hydrolysis. • The solid acid catalyst is not significantly deteriorated after repeated use

Discrete variable representation for singular Hamiltonians

DEFF Research Database (Denmark)

Schneider, B. I.; Nygaard, Nicolai

2004-01-01

We discuss the application of the discrete variable representation (DVR) to Schrodinger problems which involve singular Hamiltonians. Unlike recent authors who invoke transformations to rid the eigenvalue equation of singularities at the cost of added complexity, we show that an approach based...

Intrinsic resonance representation of quantum mechanics

DEFF Research Database (Denmark)

Carioli, M.; Heller, E.J.; Møller, Klaus Braagaard

1997-01-01

an optimal representation, based purely on classical mechanics. ''Hidden'' constants of the motion and good actions already known to the classical mechanics are thus incorporated into the basis, leaving the quantum effects to be isolated and included by small matrix diagonalizations. This simplifies...

Quiver representations

CERN Document Server

Schiffler, Ralf

2014-01-01

This book is intended to serve as a textbook for a course in Representation Theory of Algebras at the beginning graduate level. The text has two parts. In Part I, the theory is studied in an elementary way using quivers and their representations. This is a very hands-on approach and requires only basic knowledge of linear algebra. The main tool for describing the representation theory of a finite-dimensional algebra is its Auslander-Reiten quiver, and the text introduces these quivers as early as possible. Part II then uses the language of algebras and modules to build on the material developed before. The equivalence of the two approaches is proved in the text. The last chapter gives a proof of Gabriel’s Theorem. The language of category theory is developed along the way as needed.

A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

Directory of Open Access Journals (Sweden)

Hossien Pourghassem

2011-04-01

Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

Medical Named Entity Recognition for Indonesian Language Using Word Representations

Science.gov (United States)

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.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

Directory of Open Access Journals (Sweden)

Su Yang

Full Text Available Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1 Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2 The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3 The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

Science.gov (United States)

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

[The fragmentation of representational space in schizophrenia].

Science.gov (United States)

Plagnol, A; Oïta, M; Montreuil, M; Granger, B; Lubart, T

2003-01-01

Existent neurocognitive models of schizophrenia converge towards a core of impairments involving working memory, context processing, action planning, controlled and intentional processing. However, the emergence of this core remains itself difficult to explain and more specific hypotheses do not explain the heterogeneity of schizophrenia. To overcome these limits, we propose a new paradigm based on representational theory from cognitive science. Some recent developments of this theory enable us to describe a subjective universe as a representational space which is displayed from memory. We outline a conceptual framework to construct such a representational space from analogical -representations that can be activated in working memory and are connected to a network of symbolic structures. These connections are notably made through an analytic process of the analogical fragments, which involves the attentional focus. This framework allows us to define rigorously some defense processes in response to traumatic tensions that are expressed on the representational space. The fragmentation of representational space is a consequence of a defensive denial based on an impairment of the analytic process. The fragmentation forms some parasitic areas in memory which are excluded from the main part of the representational space and disturb information processing. The key clinical concepts of paranoid syndromes can be defined in this conceptual framework: mental automatism, delusional intuition, acute destructuration, psychotic dissociation, and autistic withdrawal. We show that these syndromes imply each other, which in return increases the fragmentation of the representational space. Some new concepts emerge naturally in this framework, such as the concept of "suture" which is defined as a link between a parasitic area and the main representational space. Schizophrenia appears as a borderline case of fragmentation of the representational space. This conceptual framework is

Learning Multimodal Deep Representations for Crowd Anomaly Event Detection

Directory of Open Access Journals (Sweden)

Shaonian Huang

2018-01-01

Full Text Available Anomaly event detection in crowd scenes is extremely important; however, the majority of existing studies merely use hand-crafted features to detect anomalies. In this study, a novel unsupervised deep learning framework is proposed to detect anomaly events in crowded scenes. Specifically, low-level visual features, energy features, and motion map features are simultaneously extracted based on spatiotemporal energy measurements. Three convolutional restricted Boltzmann machines are trained to model the mid-level feature representation of normal patterns. Then a multimodal fusion scheme is utilized to learn the deep representation of crowd patterns. Based on the learned deep representation, a one-class support vector machine model is used to detect anomaly events. The proposed method is evaluated using two available public datasets and compared with state-of-the-art methods. The experimental results show its competitive performance for anomaly event detection in video surveillance.

3D hierarchical spatial representation and memory of multimodal sensory data

Science.gov (United States)

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

Efficacy of pretreating oil palm fronds with an acid-base mixture catalyst.

Science.gov (United States)

Jung, Young Hoon; Park, Hyun Min; Park, Yong-Cheol; Park, Kyungmoon; Kim, Kyoung Heon

2017-07-01

Oil palm fronds are abundant but recalcitrant to chemical pretreatment. Herein, an acid-base mixture was applied as a catalyst to efficiently pretreat oil palm fronds. Optimized conditions for the pretreatment were a 0.1M acidic acid-base mixture and 3min ramping to 190°C and 12min holding. The oil palm fronds pretreated and washed with the acid-base mixture exhibited an enzymatic digestibility of 85% by 15 FPU Accellerase 1000/g glucan after 72h hydrolysis, which was significantly higher than the enzymatic digestibilities obtained by acid or alkali pretreatment alone. This could be attributed to the synergistic actions of the acid and base, producing an 87% glucose recovery with 100% and 40.3% removal of xylan and lignin, respectively, from the solids. Therefore, an acid-base mixture can be a feasible catalyst to deconstruct oil palm fronds for sugar production. Copyright © 2017 Elsevier Ltd. All rights reserved.

Representational Classroom Practices that Contribute to Students' Conceptual and Representational Understanding of Chemical Bonding

Science.gov (United States)

Hilton, Annette; Nichols, Kim

2011-11-01

Understanding bonding is fundamental to success in chemistry. A number of alternative conceptions related to chemical bonding have been reported in the literature. Research suggests that many alternative conceptions held by chemistry students result from previous teaching; if teachers are explicit in the use of representations and explain their content-specific forms and functions, this might be avoided. The development of an understanding of and ability to use multiple representations is crucial to students' understanding of chemical bonding. This paper draws on data from a larger study involving two Year 11 chemistry classes (n = 27, n = 22). It explores the contribution of explicit instruction about multiple representations to students' understanding and representation of chemical bonding. The instructional strategies were documented using audio-recordings and the teacher-researcher's reflection journal. Pre-test-post-test comparisons showed an improvement in conceptual understanding and representational competence. Analysis of the students' texts provided further evidence of the students' ability to use multiple representations to explain macroscopic phenomena on the molecular level. The findings suggest that explicit instruction about representational form and function contributes to the enhancement of representational competence and conceptual understanding of bonding in chemistry. However, the scaffolding strategies employed by the teacher play an important role in the learning process. This research has implications for professional development enhancing teachers' approaches to these aspects of instruction around chemical bonding.

Crystal and molecular structure of eight organic acid-base adducts from 2-methylquinoline and different acids

Science.gov (United States)

Zhang, Jing; Jin, Shouwen; Tao, Lin; Liu, Bin; Wang, Daqi

2014-08-01

Eight supramolecular complexes with 2-methylquinoline and acidic components as 4-aminobenzoic acid, 2-aminobenzoic acid, salicylic acid, 5-chlorosalicylic acid, 3,5-dinitrosalicylic acid, malic acid, sebacic acid, and 1,5-naphthalenedisulfonic acid were synthesized and characterized by X-ray crystallography, IR, mp, and elemental analysis. All of the complexes are organic salts except compound 2. All supramolecular architectures of 1-8 involve extensive classical hydrogen bonds as well as other noncovalent interactions. The results presented herein indicate that the strength and directionality of the classical hydrogen bonds (ionic or neutral) between acidic components and 2-methylquinoline are sufficient to bring about the formation of binary organic acid-base adducts. The role of weak and strong noncovalent interactions in the crystal packing is ascertained. These weak interactions combined, the complexes 1-8 displayed 2D-3D framework structure.

Social representations and normative beliefs of aging.

Science.gov (United States)

Torres, Tatiana de Lucena; Camargo, Brigido Vizeu; Boulsfield, Andréa Barbará; Silva, Antônia Oliveira

2015-12-01

This study adopted the theory of social representations as a theoretical framework in order to characterize similarities and differences in social representations and normative beliefs of aging for different age groups. The 638 participants responded to self-administered questionnaire and were equally distributed by sex and age. The results show that aging is characterized by positive stereotypes (knowledge and experience); however, retirement is linked to aging, but in a negative way, particularly for men, involving illness, loneliness and disability. When age was considered, it was verified that the connections with the representational elements became more complex for older groups, showing social representation functionality, largely for the elderly. Adulthood seems to be preferred and old age is disliked. There were divergences related to the perception of the beginning of life phases, especially that of old age. Work was characterized as the opposite of aging, and it revealed the need for actions intended for the elderly and retired workers, with post-retirement projects. In addition, it suggests investment in public policies that encourage intergenerational contact, with efforts to reduce intolerance and discrimination based on age of people.

Evolved Representation and Computational Creativity

Directory of Open Access Journals (Sweden)

Ashraf Fouad Hafez Ismail

2001-01-01

Full Text Available Advances in science and technology have influenced designing activity in architecture throughout its history. Observing the fundamental changes to architectural designing due to the substantial influences of the advent of the computing era, we now witness our design environment gradually changing from conventional pencil and paper to digital multi-media. Although designing is considered to be a unique human activity, there has always been a great dependency on design aid tools. One of the greatest aids to architectural design, amongst the many conventional and widely accepted computational tools, is the computer-aided object modeling and rendering tool, commonly known as a CAD package. But even though conventional modeling tools have provided designers with fast and precise object handling capabilities that were not available in the pencil-and-paper age, they normally show weaknesses and limitations in covering the whole design process.In any kind of design activity, the design worked on has to be represented in some way. For a human designer, designs are for example represented using models, drawings, or verbal descriptions. If a computer is used for design work, designs are usually represented by groups of pixels (paintbrush programs, lines and shapes (general-purpose CAD programs or higher-level objects like ‘walls’ and ‘rooms’ (purpose-specific CAD programs.A human designer usually has a large number of representations available, and can use the representation most suitable for what he or she is working on. Humans can also introduce new representations and thereby represent objects that are not part of the world they experience with their sensory organs, for example vector representations of four and five dimensional objects. In design computing on the other hand, the representation or representations used have to be explicitly defined. Many different representations have been suggested, often optimized for specific design domains

Teaching acid/base physiology in the laboratory

DEFF Research Database (Denmark)

Friis, Ulla G; Plovsing, Ronni; Hansen, Klaus

2010-01-01

exercise in acid/base physiology that would provide students with unambiguous and reproducible data that clearly would illustrate the theory in practice. The laboratory exercise was developed to include both metabolic acidosis and respiratory alkalosis. Data were collected from 56 groups of medical...... students that had participated in this laboratory exercise. The acquired data showed very consistent and solid findings after the development of both metabolic acidosis and respiratory alkalosis. All results were consistent with the appropriate diagnosis of the acid/base disorder. Not one single group...... failed to obtain data that were compatible with the diagnosis; it was only the degree of acidosis/alkalosis and compensation that varied....

Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

Science.gov (United States)

Gómez-Adorno, Helena; Markov, Ilia; Sidorov, Grigori; Posadas-Durán, Juan-Pablo; Sanchez-Perez, Miguel A; Chanona-Hernandez, Liliana

2016-01-01

We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.

Indicators that influence prospective mathematics teachers representational and reasoning abilities

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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.

A Conceptual Schema Language for the Management of Multiple Representations of Geographic Entities

DEFF Research Database (Denmark)

Friis-Christensen, A.; Jensen, Christian Søndergaard; Nytun, J.P.

2005-01-01

Multiple representation of geographic information occurs when a real-world entity is represented more than once in the same or different databases. This occurs frequently in practice, and it invariably results in the occurrence of inconsistencies among the different representations of the same...... entity. In this paper, we propose an approach to the modeling of multiply represented entities, which is based on the relationships among the entities and their representations. Central to our approach is the Multiple Representation Schema Language that, by intuitive and declarative means, is used...... to specify rules that match objects representing the same entity, maintain consistency among these representations, and restore consistency if necessary. The rules configure a Multiple Representation Management System, the aim of which is to manage multiple representations over a number of autonomous...

The relationship between odd- and branched-chain fatty acids and microbial nucleic acid bases in rumen.

Science.gov (United States)

Liu, Keyuan; Hao, Xiaoyan; Li, Yang; Luo, Guobin; Zhang, Yonggen; Xin, Hangshu

2017-11-01

This study aims to identify the relationship between odd- and branched-chain fatty acids (OBCFAs) and microbial nucleic acid bases in the rumen, and to establish a model to accurately predict microbial protein flow by using OBCFA. To develop the regression equations, data on the rumen contents of individual cows were obtained from 2 feeding experiments. In the first experiment, 3 rumen-fistulated dry dairy cows arranged in a 3×3 Latin square were fed diets of differing forage to concentration ratios (F:C). The second experiment consisted of 9 lactating Holstein dairy cows of similar body weights at the same stage of pregnancy. For each lactation stage, 3 cows with similar milk production were selected. The rumen contents were sampled at 4 time points of every two hours after morning feeding 6 h, and then to analyse the concentrations of OBCFA and microbial nucleic acid bases in the rumen samples. The ruminal bacteria nucleic acid bases were significantly influenced by feeding diets of differing forge to concentration ratios and lactation stages of dairy cows (pacids and C15:0 isomers, strongly correlated with the microbial nucleic acid bases in the rumen (pacid bases established by ruminal OBCFAs contents showed a good predictive capacity, as indicated by reasonably low standard errors and high R-squared values. This finding suggests that the rumen OBCFA composition could be used as an internal marker of rumen microbial matter.

Operator representations of frames

DEFF Research Database (Denmark)

Christensen, Ole; Hasannasab, Marzieh

2017-01-01

of the properties of the operator T requires more work. For example it is a delicate issue to obtain a representation with a bounded operator, and the availability of such a representation not only depends on the frame considered as a set, but also on the chosen indexing. Using results from operator theory we show......The purpose of this paper is to consider representations of frames {fk}k∈I in a Hilbert space ℋ of the form {fk}k∈I = {Tkf0}k∈I for a linear operator T; here the index set I is either ℤ or ℒ0. While a representation of this form is available under weak conditions on the frame, the analysis...... that by embedding the Hilbert space ℋ into a larger Hilbert space, we can always represent a frame via iterations of a bounded operator, composed with the orthogonal projection onto ℋ. The paper closes with a discussion of an open problem concerning representations of Gabor frames via iterations of a bounded...

Group and representation theory

CERN Document Server

Vergados, J D

2017-01-01

This volume goes beyond the understanding of symmetries and exploits them in the study of the behavior of both classical and quantum physical systems. Thus it is important to study the symmetries described by continuous (Lie) groups of transformations. We then discuss how we get operators that form a Lie algebra. Of particular interest to physics is the representation of the elements of the algebra and the group in terms of matrices and, in particular, the irreducible representations. These representations can be identified with physical observables. This leads to the study of the classical Lie algebras, associated with unitary, unimodular, orthogonal and symplectic transformations. We also discuss some special algebras in some detail. The discussion proceeds along the lines of the Cartan-Weyl theory via the root vectors and root diagrams and, in particular, the Dynkin representation of the roots. Thus the representations are expressed in terms of weights, which are generated by the application of the elemen...

Introduction to representation theory

CERN Document Server

Etingof, Pavel; Hensel, Sebastian; Liu, Tiankai; Schwendner, Alex

2011-01-01

Very roughly speaking, representation theory studies symmetry in linear spaces. It is a beautiful mathematical subject which has many applications, ranging from number theory and combinatorics to geometry, probability theory, quantum mechanics, and quantum field theory. The goal of this book is to give a "holistic" introduction to representation theory, presenting it as a unified subject which studies representations of associative algebras and treating the representation theories of groups, Lie algebras, and quivers as special cases. Using this approach, the book covers a number of standard topics in the representation theories of these structures. Theoretical material in the book is supplemented by many problems and exercises which touch upon a lot of additional topics; the more difficult exercises are provided with hints. The book is designed as a textbook for advanced undergraduate and beginning graduate students. It should be accessible to students with a strong background in linear algebra and a basic k...

Generalized Tellegen Principle and Physical Correctness of System Representations

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Vaclav Cerny

2006-06-01

Full Text Available The paper deals with a new problem of physical correctness detection in the area of strictly causal system representations. The proposed approach to the problem solution is based on generalization of Tellegen's theorem well known from electrical engineering. Consequently, mathematically as well as physically correct results are obtained. Some known and often used system representation structures are discussed from the developed point of view as an addition.

BIM-enabled Conceptual Modelling and Representation of Building Circulation

OpenAIRE

Lee, Jin Kook; Kim, Mi Jeong

2014-01-01

This paper describes how a building information modelling (BIM)-based approach for building circulation enables us to change the process of building design in terms of its computational representation and processes, focusing on the conceptual modelling and representation of circulation within buildings. BIM has been designed for use by several BIM authoring tools, in particular with the widely known interoperable industry foundation classes (IFCs), which follow an object-oriented data modelli...

The role of acid-base imbalance in statin-induced myotoxicity.

Science.gov (United States)

Taha, Dhiaa A; De Moor, Cornelia H; Barrett, David A; Lee, Jong Bong; Gandhi, Raj D; Hoo, Chee Wei; Gershkovich, Pavel

2016-08-01

Disturbances in acid-base balance, such as acidosis and alkalosis, have potential to alter the pharmacologic and toxicologic outcomes of statin therapy. Statins are commonly prescribed for elderly patients who have multiple comorbidities such as diabetes mellitus, cardiovascular, and renal diseases. These patients are at risk of developing acid-base imbalance. In the present study, the effect of disturbances in acid-base balance on the interconversion of simvastatin and pravastatin between lactone and hydroxy acid forms have been investigated in physiological buffers, human plasma, and cell culture medium over pH ranging from 6.8-7.8. The effects of such interconversion on cellular uptake and myotoxicity of statins were assessed in vitro using C2C12 skeletal muscle cells under conditions relevant to acidosis, alkalosis, and physiological pH. Results indicate that the conversion of the lactone forms of simvastatin and pravastatin to the corresponding hydroxy acid is strongly pH dependent. At physiological and alkaline pH, substantial proportions of simvastatin lactone (SVL; ∼87% and 99%, respectively) and pravastatin lactone (PVL; ∼98% and 99%, respectively) were converted to the active hydroxy acid forms after 24 hours of incubation at 37°C. At acidic pH, conversion occurs to a lower extent, resulting in greater proportion of statin remaining in the more lipophilic lactone form. However, pH alteration did not influence the conversion of the hydroxy acid forms of simvastatin and pravastatin to the corresponding lactones. Furthermore, acidosis has been shown to hinder the metabolism of the lactone form of statins by inhibiting hepatic microsomal enzyme activities. Lipophilic SVL was found to be more cytotoxic to undifferentiated and differentiated skeletal muscle cells compared with more hydrophilic simvastatin hydroxy acid, PVL, and pravastatin hydroxy acid. Enhanced cytotoxicity of statins was observed under acidic conditions and is attributed to increased

Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

Directory of Open Access Journals (Sweden)

Ashley M. Matheny

2017-02-01

Full Text Available Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

Analysis of visual representation techniques for product configuration systems in industrial companies

DEFF Research Database (Denmark)

Shafiee, Sara; Kristjansdottir, Katrin; Hvam, Lars

2016-01-01

with knowledge representations and communications with domain experts. The results presented in the paper are therefore aimed to provide insight into the impact from using visual knowledge representations techniques in PCSs projects. The findings indicate that use of visual knowledge representations techniques...... in PCSs projects will result in improved quality of maintenance and development support for the knowledge base and improved quality of the communication with domain experts....

Student representational competence and self-assessment when solving physics problems

Directory of Open Access Journals (Sweden)

Noah D. Finkelstein

2005-10-01

Full Text Available Student success in solving physics problems is related to the representational format of the problem. We study student representational competence in two large-lecture algebra-based introductory university physics courses with approximately 600 participants total. We examined student performance on homework problems given in four different representational formats (mathematical, pictorial, graphical, verbal, with problem statements as close to isomorphic as possible. In addition to the homeworks, we examine students’ assessment of representations by providing follow-up quizzes in which they chose between various problem formats. As a control, some parts of the classes were assigned a random-format follow-up quiz. We find that there are statistically significant performance differences between different representations of nearly isomorphic statements of quiz and homework problems. We also find that allowing students to choose which representational format they use improves student performance under some circumstances and degrades it in others. Notably, one of the two courses studied shows much greater performance differences between the groups that received a choice of format and those that did not, and we consider possible causes. Overall, we observe that student representational competence is tied to both micro- and macrolevel features of the task and environment.

Network Analysis of Students' Use of Representations in Problem Solving

Science.gov (United States)

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.

Extraction of domoic acid from seawater and urine using a resin based on 2-(trifluoromethyl)acrylic acid.

Science.gov (United States)

Piletska, Elena V; Villoslada, Fernando Navarro; Chianella, Iva; Bossi, Alessandra; Karim, Kal; Whitcombe, Michael J; Piletsky, Sergey A; Doucette, Gregory J; Ramsdell, John S

2008-03-03

A new solid-phase extraction (SPE) matrix with high affinity for the neurotoxin domoic acid (DA) was designed and tested. A computational modelling study led to the selection of 2-(trifluoromethyl)acrylic acid (TFMAA) as a functional monomer capable of imparting affinity towards domoic acid. Polymeric adsorbents containing TFMAA were synthesised and tested in high ionic strength solutions such as urine and seawater. The TFMAA-based polymers demonstrated excellent performance in solid-phase extraction of domoic acid, retaining the toxin while salts and other interfering compounds such as aspartic and glutamic acids were removed by washing and selective elution. It was shown that the TFMAA-based polymer provided the level of purification of domoic acid from urine and seawater acceptable for its quantification by high performance liquid chromatography-mass spectrometry (HPLC-MS) and enzyme-linked immunosorbent assay (ELISA) without any additional pre-concentration and purification steps.

Mechanisms of acid-base regulation in peritoneal dialysis.

Science.gov (United States)

Sow, Amadou; Morelle, Johann; Hautem, Nicolas; Bettoni, Carla; Wagner, Carsten A; Devuyst, Olivier

2017-11-22

Peritoneal dialysis (PD) contributes to restore acid-base homeostasis in patients with end-stage renal disease. The transport pathways for buffers and carbon dioxide (CO2) across the peritoneal membrane remain poorly understood. Combining well-established PD protocols, whole-body plethysmography and renal function studies in mice, we investigated molecular mechanisms of acid-base regulation in PD, including the potential role of the water channel aquaporin-1 (AQP1). After instillation in peritoneal cavity, the pH of acidic dialysis solutions increased within minutes to rapidly equilibrate with blood pH, whereas the neutral pH of biocompatible solutions remained constant. Predictions from the three-pore model of peritoneal transport suggested that local production of HCO3- accounts at least in part for the changes in intraperitoneal pH observed with acidic solutions. Carbonic anhydrase (CA) isoforms were evidenced in the peritoneal membrane and their inhibition with acetazolamide significantly decreased local production of HCO3- and delayed changes in intraperitoneal pH. On the contrary, genetic deletion of AQP1 had no effect on peritoneal transport of buffers and diffusion of CO2. Besides intraperitoneal modifications, the use of acidic dialysis solutions enhanced acid excretion both at pulmonary and renal levels. These findings suggest that changes in intraperitoneal pH during PD are mediated by bidirectional buffer transport and by CA-mediated production of HCO3- in the membrane. The use of acidic solutions enhances acid excretion through respiratory and renal responses, which should be considered in patients with renal failure. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Investigating shape representation using sensitivity to part- and axis-based transformations.

Science.gov (United States)

Denisova, Kristina; Feldman, Jacob; Su, Xiaotao; Singh, Manish

2016-09-01

Part- and axis-based approaches organize shape representations in terms of simple parts and their spatial relationships. Shape transformations that alter qualitative part structure have been shown to be more detectable than those that preserve it. We compared sensitivity to various transformations that change quantitative properties of parts and their spatial relationships, while preserving qualitative part structure. Shape transformations involving changes in length, width, curvature, orientation and location were applied to a small part attached to a larger base of a two-part shape. Increment thresholds were estimated for each transformation using a 2IFC procedure. Thresholds were converted into common units of shape difference to enable comparisons across transformations. Higher sensitivity was consistently found for transformations involving a parameter of a single part (length, width, curvature) than those involving spatial relations between two parts (relative orientation and location), suggesting a single-part superiority effect. Moreover, sensitivity to shifts in part location - a biomechanically implausible shape transformation - was consistently poorest. The influence of region-based geometry was investigated via stereoscopic manipulation of figure and ground. Sensitivity was compared across positive parts (protrusions) and negative parts (indentations) for transformations involving a change in orientation or location. For changes in part orientation (biomechanically plausible), sensitivity was better for positive than negative parts; whereas for changes in part location (biomechanically implausible), no systematic difference was observed. Copyright © 2015 Elsevier Ltd. All rights reserved.

A schema for knowledge representation and its implementation in a computer-aided design and manufacturing system

Energy Technology Data Exchange (ETDEWEB)

Tamir, D.E.

1989-01-01

Modularity in the design and implementation of expert systems relies upon cooperation among the expert systems and communication of knowledge between them. A prerequisite for an effective modular approach is some standard for knowledge representation to be used by the developers of the different modules. In this work the author presents a schema for knowledge representation, and apply this schema in the design of a rule-based expert system. He also implements a cooperative expert system using the proposed knowledge representation method. A knowledge representation schema is a formal specification of the internal, conceptual, and external components of a knowledge base, each specified in a separate schema. The internal schema defines the structure of a knowledge base, the conceptual schema defines the concepts, and the external schema formalizes the pragmatics of a knowledge base. The schema is the basis for standardizing knowledge representation systems and it is used in the various phases of design and specification of the knowledge base. A new model of knowledge representation based on a pattern recognition interpretation of implications is developed. This model implements the concept of linguistic variables and can, therefore, emulate human reasoning with linguistic imprecision. The test case for the proposed schema of knowledge representation is a system is a cooperative expert system composed of two expert systems. This system applies a pattern recognition interpretation of a generalized one-variable implication with linguistic variables.

Poly(Lactic Acid) Based Flexible Films

OpenAIRE

Fathilah binti Ali; Jamarosliza Jamaluddin; Arun Kumar Upadhyay

2014-01-01

Poly(lactic acid) (PLA) is a biodegradable polymer which has good mechanical properties, however, its brittleness limits its usage especially in packaging materials. Therefore, in this work, PLA based polyurethane films were prepared by synthesizing with different types of isocyanates; methylene diisocyanate (MDI) and hexamethylene diisocyanates (HDI). For this purpose, PLA based polyurethane must have good strength and flexibility. Therefore, polycaprolactone which has b...

Basic-level and superordinate-like categorical representations in early infancy.

Science.gov (United States)

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.

Strongly and weakly directed approaches to teaching multiple representation use in physics

Directory of Open Access Journals (Sweden)

Patrick B. Kohl

2007-06-01

Full Text Available Good use of multiple representations is considered key to learning physics, and so there is considerable motivation both to learn how students use multiple representations when solving problems and to learn how best to teach problem solving using multiple representations. In this study of two large-lecture algebra-based physics courses at the University of Colorado (CU and Rutgers, the State University of New Jersey, we address both issues. Students in each of the two courses solved five common electrostatics problems of varying difficulty, and we examine their solutions to clarify the relationship between multiple representation use and performance on problems involving free-body diagrams. We also compare our data across the courses, since the two physics-education-research-based courses take substantially different approaches to teaching the use of multiple representations. The course at Rutgers takes a strongly directed approach, emphasizing specific heuristics and problem-solving strategies. The course at CU takes a weakly directed approach, modeling good problem solving without teaching a specific strategy. We find that, in both courses, students make extensive use of multiple representations, and that this use (when both complete and correct is associated with significantly increased performance. Some minor differences in representation use exist, and are consistent with the types of instruction given. Most significant are the strong and broad similarities in the results, suggesting that either instructional approach or a combination thereof can be useful for helping students learn to use multiple representations for problem solving and concept development.

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

Science.gov (United States)

Li, Qing; Liang, Steven Y

2018-04-20

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

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

Science.gov (United States)

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.

Wavelet images and Chou's pseudo amino acid composition for protein classification.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2012-08-01

The last decade has seen an explosion in the collection of protein data. To actualize the potential offered by this wealth of data, it is important to develop machine systems capable of classifying and extracting features from proteins. Reliable machine systems for protein classification offer many benefits, including the promise of finding novel drugs and vaccines. In developing our system, we analyze and compare several feature extraction methods used in protein classification that are based on the calculation of texture descriptors starting from a wavelet representation of the protein. We then feed these texture-based representations of the protein into an Adaboost ensemble of neural network or a support vector machine classifier. In addition, we perform experiments that combine our feature extraction methods with a standard method that is based on the Chou's pseudo amino acid composition. Using several datasets, we show that our best approach outperforms standard methods. The Matlab code of the proposed protein descriptors is available at http://bias.csr.unibo.it/nanni/wave.rar .

On Behavioral Equivalence of Rational Representations

NARCIS (Netherlands)

Trentelman, Harry L.; Willems, JC; Hara, S; Ohta, Y; Fujioka, H

2010-01-01

This article deals with the equivalence of representations of behaviors of linear differential systems In general. the behavior of a given linear differential system has many different representations. In this paper we restrict ourselves to kernel representations and image representations Two kernel

Functional representations for quantized fields

International Nuclear Information System (INIS)

Jackiw, R.

1988-01-01

This paper provides information on Representing transformations in quantum theory bosonic quantum field theories: Schrodinger Picture; Represnting Transformations in Bosonic Quantum Field Theory; Two-Dimensional Conformal Transformations, Schrodinger picture representation, Fock space representation, Inequivalent Schrodinger picture representations; Discussion, Self-Dual and Other Models; Field Theory in de Sitter Space. Fermionic Quantum Field Theories: Schroedinger Picture; Schrodinger Picture Representation for Two-Dimensional; Conformal Transformations; Fock Space Dynamics in the Schrodinger Picture; Fock Space Evaluation of Anomalous Current and Conformal Commutators

Impact of the second semester University Modeling Instruction course on students’ representation choices

Directory of Open Access Journals (Sweden)

Daryl McPadden

2017-11-01

Full Text Available 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 scientific models, has made representation use a primary learning goal with explicit class time devoted to introducing and coordinating representations as part of the model building process. However, because of the semester break, the second semester course, Modeling Instruction-Electricity and Magnetism (MI-EM, contains a mixture of students who are returning from the Modeling Instruction-mechanics course (to whom we refer to as “returning students” and students who are new to Modeling Instruction with the MI-EM course (to whom we refer to as “new students”. In this study, we analyze the impact of MI-EM on students’ representation choices across the introductory physics content for these different groups of students by examining both what individual representations students choose and their average number of representations on a modified card-sort survey with a variety of mechanics and EM questions. Using Wilcoxon-signed-rank tests, Wilcoxon-Mann-Whitney tests, Cliff’s delta effect sizes, and box plots, we compare students’ representation choices from pre- to postsemester, from new and returning students, and from mechanics and EM content. We find that there is a significant difference between returning and new students’ representation choices, which serves as a baseline comparison between Modeling Instruction and traditional lecture-based physics classes. We also find that returning students maintain a high representation use across the MI-EM semester, while new students see significant growth in their representation use regardless of content.

Ontology-based representation and analysis of host-Brucella interactions.

Science.gov (United States)

Lin, Yu; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

Energy distribution for Coefficients of Redundant Signal Representations of Music

DEFF Research Database (Denmark)

Endelt, Line Ørtoft; la Cour-Harbo, Anders

2005-01-01

different time-frequency dictionaries. We have applied these methods to music to examine their ability to express music signals in a sparse manner for a number of dictionaries and window lengths. The evaluation is based on the m-term approximation needed to represent 90 %, 95 %, 99 % and 99......In this paper we investigate how the energy is distributed in the coefficients vector of various redundant signal representations of music signals. The representations are found using Basis Pursuit, Matching Pursuit, Alternating Projections, Best Orthogonal Basis and Method of Frames, with five.......9 % of the energy in the coefficients, also the time consummation for finding the representations are considered. The distribution of energy in the coefficients of the representations found using Basis Pursuit, Matching Pursuit, Alternating Projections and Best Orthogonal Basis depends mainly on the signal...

Study on a phase space representation of quantum theory

International Nuclear Information System (INIS)

Ranaivoson, R.T.R; Raoelina Andriambololona; Hanitriarivo, R.; Raboanary, R.

2013-01-01

A study on a method for the establishment of a phase space representation of quantum theory is presented. The approach utilizes the properties of Gaussian distribution, the properties of Hermite polynomials, Fourier analysis and the current formulation of quantum mechanics which is based on the use of Hilbert space and linear operators theory. Phase space representation of quantum states and wave functions in phase space are introduced using properties of a set of functions called harmonic Gaussian functions. Then, new operators called dispersion operators are defined and identified as the operators which admit as eigenstates the basis states of the phase space representation. Generalization of the approach for multidimensional cases is shown. Examples of applications are given.

The protection of warranties and representations

International Nuclear Information System (INIS)

Spence, C.D.; Thusoo, N.

1999-01-01

Most acquisition contracts within the oil and gas industry consist of representations and warranties. The legal distinction between representations and warranties was explained as follows: a representation is a statement of fact made by the representor before making the contract, but a warranty is a statement of fact which forms part of the terms of the contract. The paper outlines the nature of a representation or warranty and explains why certain warranties are not given. The protection offered by representations and warranties in breach of contract cases is also explained. Suggestions are offered for increasing protection by representations and warranties. 22 refs

Environmentally Benign Bifunctional Solid Acid and Base Catalysts

NARCIS (Netherlands)

Elmekawy, A.; Shiju, N.R.; Rothenberg, G.; Brown, D.R.

2014-01-01

Solid bifunctional acid-​base catalysts were prepd. in two ways on an amorphous silica support: (1) by grafting mercaptopropyl units (followed by oxidn. to propylsulfonic acid) and aminopropyl groups to the silica surface (NH2-​SiO2-​SO3H)​, and (2) by grafting only aminopropyl groups and then

Harmonic Analysis and Group Representation

CERN Document Server

Figa-Talamanca, Alessandro

2011-01-01

This title includes: Lectures - A. Auslander, R. Tolimeri - Nilpotent groups and abelian varieties, M Cowling - Unitary and uniformly bounded representations of some simple Lie groups, M. Duflo - Construction de representations unitaires d'un groupe de Lie, R. Howe - On a notion of rank for unitary representations of the classical groups, V.S. Varadarajan - Eigenfunction expansions of semisimple Lie groups, and R. Zimmer - Ergodic theory, group representations and rigidity; and, Seminars - A. Koranyi - Some applications of Gelfand pairs in classical analysis.

Memetics of representation

Directory of Open Access Journals (Sweden)

Roberto De Rubertis

2012-06-01

Full Text Available This article will discuss about the physiological genesis of representation and then it will illustrate the developments, especially in evolutionary perspective, and it will show how these are mainly a result of accidental circumstances, rather than of deliberate intention of improvement. In particular, it will be argue that the representation has behaved like a meme that has arrived to its own progressive evolution coming into symbiosis with the different cultures in which it has spread, and using in this activity human work “unconsciously”. Finally it will be shown how in this action the geometry is an element key, linked to representation both to construct images using graphics operations and to erect buildings using concrete operations.

Essentials in the diagnosis of acid-base disorders and their high altitude application.

Science.gov (United States)

Paulev, P E; Zubieta-Calleja, G R

2005-09-01

This report describes the historical development in the clinical application of chemical variables for the interpretation of acid-base disturbances. The pH concept was already introduced in 1909. Following World War II, disagreements concerning the definition of acids and bases occurred, and since then two strategies have been competing. Danish scientists in 1923 defined an acid as a substance able to give off a proton at a given pH, and a base as a substance that could bind a proton, whereas the North American Singer-Hasting school in 1948 defined acids as strong non-buffer anions and bases as non-buffer cations. As a consequence of this last definition, electrolyte disturbances were mixed up with real acid-base disorders and the variable, strong ion difference (SID), was introduced as a measure of non-respiratory acid-base disturbances. However, the SID concept is only an empirical approximation. In contrast, the Astrup/Siggaard-Andersen school of scientists, using computer strategies and the Acid-base Chart, has made diagnosis of acid-base disorders possible at a glance on the Chart, when the data are considered in context with the clinical development. Siggaard-Andersen introduced Base Excess (BE) or Standard Base Excess (SBE) in the extracellular fluid volume (ECF), extended to include the red cell volume (eECF), as a measure of metabolic acid-base disturbances and recently replaced it by the term Concentration of Titratable Hydrogen Ion (ctH). These two concepts (SBE and ctH) represent the same concentration difference, but with opposite signs. Three charts modified from the Siggaard-Andersen Acid-Base Chart are presented for use at low, medium and high altitudes of 2500 m, 3500 m, and 4000 m, respectively. In this context, the authors suggest the use of Titratable Hydrogen Ion concentration Difference (THID) in the extended extracellular fluid volume, finding it efficient and better than any other determination of the metabolic component in acid-base

On knowledge representation for high energy physics control systems

International Nuclear Information System (INIS)

Huuskonen, P.; Kaarela, K.; Meri, M.; Le Goff, J.M.

1994-01-01

A framework for knowledge representation in the domain of high energy physics control systems is presented. Models of process equipment, controls, documents, information systems, functional dependencies, physical interconnections, and design decisions are necessary to allow for automated reasoning about such systems. A number of support systems can use these models: alarm processing, fault diagnosis, sensor validation, preventive maintenance, action analysis, information abstraction, intelligent help systems, and on-line documentation. Our aim is to achieve representations that would be understood by end users, could be constructed by domain experts, and would be powerful enough to function as a basis for these support systems. It is proposed to base these models on means-end-analysis, implemented through an entity-relationship type of representation and extended with the notion of contribution. The paper outlines class hierarchies and relation types to form a vocabulary for talking about this specific domain. A number of implementation concerns are raised and some examples of how these representations can be used in real cases are offered. The representations are likely to prove most useful for support systems that function in the user assisting mode, as opposed to fully autonomous systems. Intelligent help and information abstraction applications, in particular, are expected to benefit. The main focus of the work is that of the control information system concepts based on encapsulated real- time objects (CICERO) project at CERN, experiment controls, but the results are usable for accelerator control systems and for industrial control systems in general. (author). 37 refs., 7 figs

Baikov-Lee representations of cut Feynman integrals

International Nuclear Information System (INIS)

Harley, Mark; Moriello, Francesco; Schabinger, Robert M.

2017-01-01

We develop a general framework for the evaluation of d-dimensional cut Feynman integrals based on the Baikov-Lee representation of purely-virtual Feynman integrals. We implement the generalized Cutkosky cutting rule using Cauchy’s residue theorem and identify a set of constraints which determine the integration domain. The method applies equally well to Feynman integrals with a unitarity cut in a single kinematic channel and to maximally-cut Feynman integrals. Our cut Baikov-Lee representation reproduces the expected relation between cuts and discontinuities in a given kinematic channel and furthermore makes the dependence on the kinematic variables manifest from the beginning. By combining the Baikov-Lee representation of maximally-cut Feynman integrals and the properties of periods of algebraic curves, we are able to obtain complete solution sets for the homogeneous differential equations satisfied by Feynman integrals which go beyond multiple polylogarithms. We apply our formalism to the direct evaluation of a number of interesting cut Feynman integrals.

Acid-base disorders in calves with chronic diarrhea.

Science.gov (United States)

Bednarski, M; Kupczyński, R; Sobiech, P

2015-01-01

The aim of this study was to analyze disorders of acid-base balance in calves with chronic diarrhea caused by mixed, viral, bacterial and Cryptosporydium parvum infection. We compared results ob- tained with the classic model (Henderson-Hasselbalch) and strong ion approach (the Steward model). The study included 36 calves aged between 14 and 21 days. The calves were allocated to three groups: I - (control) non-diarrheic calves, group II - animals with compensated acid-base imbalance and group III calves with compensated acid-base disorders and hypoalbuminemia. Plasma concentrations of Na+, K+, Cl-, C12+, Mg2+, P, albumin and lactate were measured. In the classic model, acid-base balance was determined on the basis of blood pH, pCO2, HCO3-, BE and anion gap. In the strong ion model, strong ion difference (SID), effective strong anion difference, total plasma concentration of nonvolatile buffers (A(Tot)) and strong ion gap (SIG) were measured. The control calves and the animals from groups II and III did not differ significantly in terms of their blood pH. The plasma concentration of HCO3-, BE and partial pressure of CO2 in animals from the two groups with chronic diarrhea were significantly higher than those found in the controls. The highest BE (6.03 mmol/l) was documented in calves from group II. The animals from this group presented compensation resulted from activation of metabolic mechanisms. The calves with hypoal- buminemia (group III) showed lower plasma concentrations of albumin (15.37 g/L), Cl (74.94 mmol/L), Mg2+ (0.53 mmol/L), P (1.41 mmol/L) and higher value of anion gap (39.03 mmol/L). This group III presented significantly higher SID3 (71.89 mmol/L), SID7 (72.92 mmol/L) and SIG (43.53 mmol/L) values than animals from the remaining groups (P acid-base disturbance in these cases suggests that classic model have some limitations. This model can not be recommended for use whenever serum albumin or phosphate concentrations are markedly abnormal.

Acid-base properties of complexes with three-dimensional polyligands. Complexes with three-dimensional polyphosphoric acids

International Nuclear Information System (INIS)

Kopylova, V.D.; Bojko, Eh.T.; Saldadze, K.M.

1985-01-01

By the method of potentiometric titration acid-base properties of uranyl (2) complexes with three-dimensional polyphosphoric acids, KRF-8p, KF-1, KF-7 prepared by phosphorylation of copolymer of styrene and divinylbenzene or saponification of the copolymers of di-2,2'-chloroethyl ester of vinylphosphonic acid with divinyl benzene are studied. It is shown that in case of formation in the phase of three-dimensional polyphosphoric acids of UO 2 2+ complexes with the growth of bond covalence of metal ion-phosphonic group the acidjty of the second hydroxyl of the phosphonic group increases

Synthesis of bio-based methacrylic acid by decarboxylation of itaconic acid and citric acid catalyzed by solid transition-metal catalysts

NARCIS (Netherlands)

Notre, le J.E.L.; Witte-van Dijk, S.C.M.; Haveren, van J.; Scott, E.L.; Sanders, J.P.M.

2014-01-01

Methacrylic acid, an important monomer for the plastics industry, was obtained in high selectivity (up to 84%) by the decarboxylation of itaconic acid using heterogeneous catalysts based on Pd, Pt and Ru. The reaction takes place in water at 200–2508C without any external added pressure, conditions

From scenarios to domain models: processes and representations

Science.gov (United States)

Haddock, Gail; Harbison, Karan

1994-03-01

The domain specific software architectures (DSSA) community has defined a philosophy for the development of complex systems. This philosophy improves productivity and efficiency by increasing the user's role in the definition of requirements, increasing the systems engineer's role in the reuse of components, and decreasing the software engineer's role to the development of new components and component modifications only. The scenario-based engineering process (SEP), the first instantiation of the DSSA philosophy, has been adopted by the next generation controller project. It is also the chosen methodology of the trauma care information management system project, and the surrogate semi-autonomous vehicle project. SEP uses scenarios from the user to create domain models and define the system's requirements. Domain knowledge is obtained from a variety of sources including experts, documents, and videos. This knowledge is analyzed using three techniques: scenario analysis, task analysis, and object-oriented analysis. Scenario analysis results in formal representations of selected scenarios. Task analysis of the scenario representations results in descriptions of tasks necessary for object-oriented analysis and also subtasks necessary for functional system analysis. Object-oriented analysis of task descriptions produces domain models and system requirements. This paper examines the representations that support the DSSA philosophy, including reference requirements, reference architectures, and domain models. The processes used to create and use the representations are explained through use of the scenario-based engineering process. Selected examples are taken from the next generation controller project.

The influence of naturally-occurring organic acids on model estimates of lakewater acidification using the model of acidification of groundwater in catchments (MAGIC)

International Nuclear Information System (INIS)

Sullivan, T.J.; Eilers, J.M.; Cosby, B.J.; Driscoll, C.T.; Hemond, H.F.; Charles, D.F.; Norton, S.A.

1993-01-01

A project for the US Department of Energy, entitled ''Incorporation of an organic acid representation into MAGIC (Model of Acidification of Groundwater in Catchments) and Testing of the Revised Model UsingIndependent Data Sources'' was initiated by E ampersand S Environmental Chemistry, Inc. in March, 1992. Major components of the project include: improving the MAGIC model by incorporating a rigorous organic acid representation, based on empirical data and geochemical considerations, and testing the revised model using data from paleolimnological hindcasts of preindustrial chemistry for 33 Adirondack Mountain lakes, and the results of whole-catchment artificial acidification projects in Maine and Norway. The ongoing research in this project involves development of an organic acid representation to be incorporated into the MAGIC modeland testing of the improved model using three independent data sources. The research during Year 1 has included conducting two workshops to agree on an approach for the organic acid modeling, developing the organic subroutine and incorporating it into MAGIC (Task 1), conducing MAGIC hindcasts for Adirondack lakes and comparing the results with paleolimnological reconstructions (Task 2), and conducting site visits to the manipulation project sites in Maine and Norway. The purpose of this report is to provide a summary of the work that has been conducted on this project during Year 1. Tasks 1 and 2 have now been completed

The influence of naturally-occurring organic acids on model estimates of lakewater acidification using the model of acidification of groundwater in catchments (MAGIC)

Energy Technology Data Exchange (ETDEWEB)

Sullivan, T.J.; Eilers, J.M. (E and S Environmental Chemistry, Inc., Corvallis, OR (United States)); Cosby, B.J. (Virginia Univ., Charlottesville, VA (United States). Dept. of Environmental Sciences); Driscoll, C.T. (Syracuse Univ., NY (United States). Dept. of Civil Engineering); Hemond, H.F. (Massachusetts Inst. of Tech., Cambridge, MA (United States). Dept. of Civil Engineering); Charles, D.F.

1993-03-05

A project for the US Department of Energy, entitled Incorporation of an organic acid representation into MAGIC (Model of Acidification of Groundwater in Catchments) and Testing of the Revised Model UsingIndependent Data Sources'' was initiated by E S Environmental Chemistry, Inc. in March, 1992. Major components of the project include: improving the MAGIC model by incorporating a rigorous organic acid representation, based on empirical data and geochemical considerations, and testing the revised model using data from paleolimnological hindcasts of preindustrial chemistry for 33 Adirondack Mountain lakes, and the results of whole-catchment artificial acidification projects in Maine and Norway. The ongoing research in this project involves development of an organic acid representation to be incorporated into the MAGIC modeland testing of the improved model using three independent data sources. The research during Year 1 has included conducting two workshops to agree on an approach for the organic acid modeling, developing the organic subroutine and incorporating it into MAGIC (Task 1), conducing MAGIC hindcasts for Adirondack lakes and comparing the results with paleolimnological reconstructions (Task 2), and conducting site visits to the manipulation project sites in Maine and Norway. The purpose of this report is to provide a summary of the work that has been conducted on this project during Year 1. Tasks 1 and 2 have now been completed.

How Do Undergraduate Students Conceptualize Acid-Base Chemistry? Measurement of a Concept Progression

Science.gov (United States)

Romine, William L.; Todd, Amber N.; Clark, Travis B.

2016-01-01

We developed and validated a new instrument, called "Measuring Concept progressions in Acid-Base chemistry" (MCAB) and used it to better understand the progression of undergraduate students' understandings about acid-base chemistry. Items were developed based on an existing learning progression for acid-base chemistry. We used the Rasch…

Virtual terrain: a security-based representation of a computer network

Science.gov (United States)

Holsopple, Jared; Yang, Shanchieh; Argauer, Brian

2008-03-01

Much research has been put forth towards detection, correlating, and prediction of cyber attacks in recent years. As this set of research progresses, there is an increasing need for contextual information of a computer network to provide an accurate situational assessment. Typical approaches adopt contextual information as needed; yet such ad hoc effort may lead to unnecessary or even conflicting features. The concept of virtual terrain is, therefore, developed and investigated in this work. Virtual terrain is a common representation of crucial information about network vulnerabilities, accessibilities, and criticalities. A virtual terrain model encompasses operating systems, firewall rules, running services, missions, user accounts, and network connectivity. It is defined as connected graphs with arc attributes defining dynamic relationships among vertices modeling network entities, such as services, users, and machines. The virtual terrain representation is designed to allow feasible development and maintenance of the model, as well as efficacy in terms of the use of the model. This paper will describe the considerations in developing the virtual terrain schema, exemplary virtual terrain models, and algorithms utilizing the virtual terrain model for situation and threat assessment.

Jigsaw Cooperative Learning: Acid-Base Theories

Science.gov (United States)

Tarhan, Leman; Sesen, Burcin Acar

2012-01-01

This study focused on investigating the effectiveness of jigsaw cooperative learning instruction on first-year undergraduates' understanding of acid-base theories. Undergraduates' opinions about jigsaw cooperative learning instruction were also investigated. The participants of this study were 38 first-year undergraduates in chemistry education…

Holistic face representation is highly orientation-specific.

Science.gov (United States)

Rosenthal, Gideon; Levakov, Gidon; Avidan, Galia

2017-09-29

It has long been argued that face processing requires disproportionate reliance on holistic processing (HP), relative to that required for nonface object recognition. Nevertheless, whether the holistic nature of face perception is achieved via a unique internal representation or by the employment of an automated attention mechanism is still debated. Previous studies had used the face inversion effect (FIE), a unique face-processing marker, or the face composite task, a gold standard paradigm measuring holistic processing, to examine the validity of these two different hypotheses, with some studies combining the two paradigms. However, the results of such studies remain inconclusive, particularly pertaining to the issue of the two proposed HP mechanisms-an internal representation as opposed to an automated attention mechanism. Here, using the complete composite paradigm design, we aimed to examine whether face rotation yields a nonlinear or a linear drop in HP, thus supporting an account that face processing is based either on an orientation-dependent internal representation or on automated attention. Our results reveal that even a relatively small perturbation in face orientation (30 deg away from upright) already causes a sharp decline in HP. These findings support the face internal representation hypothesis and the notion that the holistic processing of faces is highly orientation-specific.

A searching and reporting system for relational databases using a graph-based metadata representation.

Science.gov (United States)

Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

2005-01-01

Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.