Multimodal registration via spatial-context mutual information.

PubMed

Yi, Zhao; Soatto, Stefano

2011-01-01

We propose a method to efficiently compute mutual information between high-dimensional distributions of image patches. This in turn is used to perform accurate registration of images captured under different modalities, while exploiting their local structure otherwise missed in traditional mutual information definition. We achieve this by organizing the space of image patches into orbits under the action of Euclidean transformations of the image plane, and estimating the modes of a distribution in such an orbit space using affinity propagation. This way, large collections of patches that are equivalent up to translations and rotations are mapped to the same representative, or "dictionary element". We then show analytically that computing mutual information for a joint distribution in this space reduces to computing mutual information between the (scalar) label maps, and between the transformations mapping each patch into its closest dictionary element. We show that our approach improves registration performance compared with the state of the art in multimodal registration, using both synthetic and real images with quantitative ground truth.

Problemes et methodes de la lexicographie quebecoise (Problems and Methods of Quebec Lexicography).

ERIC Educational Resources Information Center

Cormier, Monique C., Ed.; Francoeur, Aline, Ed.

Papers on lexicographic research in Quebec (Canada) include: "Indications semantiques dans les dictionnaires bilingues" ("Semantic Indications in Bilingual Dictionaries) (Johanne Blais, Roda P. Roberts); "Definitions predictionnairiques de 'maison, batiment, et pavillon'" ("Pre-dictionary definitions of 'house,…

Fighting the Big War with the Small Hammer: Operational Planning for the Medium Force

DTIC Science & Technology

2015-05-23

definition do not correlate to larger organizations as a whole. 13 Oxford English Dictionary (New York, NY: Oxford University Press, 1980), 413. 14 For...outside the scope of this monograph. 22 Oxford English Dictionary , 413. 23 Johnson, Grissom, and Oliker, 9-10; The definition of Medium cannot be found...1985. Osinga, Frans P. B. Science, Strategy and War: The Strategic Theory of John Boyd. New York, NY: Routledge, 2007. Oxford English Dictionary

Loops and Self-Reference in the Construction of Dictionaries

NASA Astrophysics Data System (ADS)

Levary, David; Eckmann, Jean-Pierre; Moses, Elisha; Tlusty, Tsvi

2012-07-01

Dictionaries link a given word to a set of alternative words (the definition) which in turn point to further descendants. Iterating through definitions in this way, one typically finds that definitions loop back upon themselves. We demonstrate that such definitional loops are created in order to introduce new concepts into a language. In contrast to the expectations for a random lexical network, in graphs of the dictionary, meaningful loops are quite short, although they are often linked to form larger, strongly connected components. These components are found to represent distinct semantic ideas. This observation can be quantified by a singular value decomposition, which uncovers a set of conceptual relationships arising in the global structure of the dictionary. Finally, we use etymological data to show that elements of loops tend to be added to the English lexicon simultaneously and incorporate our results into a simple model for language evolution that falls within the “rich-get-richer” class of network growth.

The Latent Structure of Dictionaries.

PubMed

Vincent-Lamarre, Philippe; Massé, Alexandre Blondin; Lopes, Marcos; Lord, Mélanie; Marcotte, Odile; Harnad, Stevan

2016-07-01

How many words-and which ones-are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a "Strongly Connected Subset" of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest-the graph's "minimum feedback vertex set" or MinSet-is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. Copyright © 2016 Cognitive Science Society, Inc.

Dictionary of Radio and Television.

ERIC Educational Resources Information Center

Pannett, W. E.

This dictionary presents definitions of both the well-established terms and many new ones that have come into use with the advances that have taken place in the fields of radio and television. In many cases extended definitions are given in order to describe briefly elementary principles and circuits, while newer and more complex devices and…

A fully automatic evolutionary classification of protein folds: Dali Domain Dictionary version 3

PubMed Central

Dietmann, Sabine; Park, Jong; Notredame, Cedric; Heger, Andreas; Lappe, Michael; Holm, Liisa

2001-01-01

The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families. PMID:11125048

Marks, Spaces and Boundaries: Punctuation (and Other Effects) in the Typography of Dictionaries

ERIC Educational Resources Information Center

Luna, Paul

2011-01-01

Dictionary compilers and designers use punctuation to structure and clarify entries and to encode information. Dictionaries with a relatively simple structure can have simple typography and simple punctuation; as dictionaries grew more complex, and encountered the space constraints of the printed page, complex encoding systems were developed,…

Data-Dictionary-Editing Program

NASA Technical Reports Server (NTRS)

Cumming, A. P.

1989-01-01

Access to data-dictionary relations and attributes made more convenient. Data Dictionary Editor (DDE) application program provides more convenient read/write access to data-dictionary table ("descriptions table") via data screen using SMARTQUERY function keys. Provides three main advantages: (1) User works with table names and field names rather than with table numbers and field numbers, (2) Provides online access to definitions of data-dictionary keys, and (3) Provides displayed summary list that shows, for each datum, which data-dictionary entries currently exist for any specific relation or attribute. Computer program developed to give developers of data bases more convenient access to the OMNIBASE VAX/IDM data-dictionary relations and attributes.

Dictionary of Marketing Terms.

ERIC Educational Resources Information Center

Everhardt, Richard M.

A listing of words and definitions compiled from more than 10 college and high school textbooks are presented in this dictionary of marketing terms. Over 1,200 entries of terms used in retailing, wholesaling, economics, and investments are included. This dictionary was designed to aid both instructors and students to better understand the…

EFL Students' "Yahoo!" Online Bilingual Dictionary Use Behavior

ERIC Educational Resources Information Center

Tseng, Fan-ping

2009-01-01

This study examined 38 EFL senior high school students' "Yahoo!" online dictionary look-up behavior. In a language laboratory, the participants read an article on a reading sheet, underlined any words they did not know, looked up their unknown words in "Yahoo!" online bilingual dictionary, and wrote down the definitions of…

Learning the Language of Difference: The Dictionary in the High School.

ERIC Educational Resources Information Center

Willinsky, John

1987-01-01

Reports on dictionaries' power to misrepresent gender. Examines the definitions of three terms (clitoris, penis, and vagina) in eight leading high school dictionaries. Concludes that the absence of certain female gender-related terms represents another instance of institutionalized silence about the experience of women. (MM)

78 FR 68343 - Homeownership Counseling Organizations Lists Interpretive Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-14

... into their definitional meanings, according to the Data Dictionary,\\7\\ to ensure clarity. This will be... dictionary for the Field ``Services'' can be found at http://data.hud.gov/Housing_Counselor/getServices , and a data dictionary for ``Languages'' can be found at http://data.hud.gov/Housing_Counselor/get...

Continuity of care: some experiences and thoughts.

PubMed

Volpe, F J

1994-09-01

Continuity of health care is a goal to be achieved. Most are for it. Many claim to provide it. But how do we know we have it? What are the key features of continuity? While dictionaries do not define the phrase "continuity of health care," we do find definitions of "continuity." The Oxford English Dictionary, Second Edition, includes in its definitions: "the state or quality of being uninterrupted in sequence or succession, or in essence or idea; connectedness, coherence, unbroken..." Stedman's Medical Dictionary includes: "absence of interruption, a succession of parts intimately united..." These definitions stress an uninterrupted succession and include the concept that there needs to be a connection to the parts. Without that connection, continuity, in health care delivery or elsewhere, does not exist.

Translation lexicon acquisition from bilingual dictionaries

NASA Astrophysics Data System (ADS)

Doermann, David S.; Ma, Huanfeng; Karagol-Ayan, Burcu; Oard, Douglas W.

2001-12-01

Bilingual dictionaries hold great potential as a source of lexical resources for training automated systems for optical character recognition, machine translation and cross-language information retrieval. In this work we describe a system for extracting term lexicons from printed copies of bilingual dictionaries. We describe our approach to page and definition segmentation and entry parsing. We have used the approach to parse a number of dictionaries and demonstrate the results for retrieval using a French-English Dictionary to generate a translation lexicon and a corpus of English queries applied to French documents to evaluation cross-language IR.

Aveiro method in reproducing kernel Hilbert spaces under complete dictionary

NASA Astrophysics Data System (ADS)

Mai, Weixiong; Qian, Tao

2017-12-01

Aveiro Method is a sparse representation method in reproducing kernel Hilbert spaces (RKHS) that gives orthogonal projections in linear combinations of reproducing kernels over uniqueness sets. It, however, suffers from determination of uniqueness sets in the underlying RKHS. In fact, in general spaces, uniqueness sets are not easy to be identified, let alone the convergence speed aspect with Aveiro Method. To avoid those difficulties we propose an anew Aveiro Method based on a dictionary and the matching pursuit idea. What we do, in fact, are more: The new Aveiro method will be in relation to the recently proposed, the so called Pre-Orthogonal Greedy Algorithm (P-OGA) involving completion of a given dictionary. The new method is called Aveiro Method Under Complete Dictionary (AMUCD). The complete dictionary consists of all directional derivatives of the underlying reproducing kernels. We show that, under the boundary vanishing condition, bring available for the classical Hardy and Paley-Wiener spaces, the complete dictionary enables an efficient expansion of any given element in the Hilbert space. The proposed method reveals new and advanced aspects in both the Aveiro Method and the greedy algorithm.

Navajo-English Dictionary.

ERIC Educational Resources Information Center

Wall, Leon; Morgan, William

A brief summary of the sound system of the Navajo language introduces this Navajo-English dictionary. Diacritical markings and an English definition are given for each Navajo word. Words are listed alphabetically by Navajo sound. (VM)

The Yale Kamusi Project: A Swahili-English, English-Swahili Dictionary.

ERIC Educational Resources Information Center

Hinnebusch, Thomas

2001-01-01

Evaluates the strengths and weaknesses of the Yale Online Kamusi project, an electronic Web-based Swahili-English and English-Swahili dictionary. The dictionary is described and checked for comprehensiveness, the adequacy and quality of the glosses and definitions are tested, and a number of recommendations are made to help make it a better and…

A Generative Theory of Relevance

DTIC Science & Technology

2004-09-01

73 5.3.1.4 Parameter estimation with a dictionary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5.3.1.5 Document ranking...engine [3]. The stemmer combines morphological rules with a large dictionary of special cases and exceptions. After stemming, 418 stop-words from the...goes over all Arabic training strings. Bulgarian definitions are identical. 5.3.1.4 Parameter estimation with a dictionary Parallel and comparable

The Junior Computer Dictionary. 101 Useful Words and Definitions to Introduce Students to Computer Terminology.

ERIC Educational Resources Information Center

Willing, Kathlene R.; Girard, Suzanne

Suitable for children from grades four to seven, this dictionary is designed to introduce children to computer terminology at a level that they will understand and find useful. It is also suitable as a home resource for parents, for library use, and as a handbook for teachers. For each word, the first sentence of the definition contains the kernel…

A practical implementation for a data dictionary in an environment of diverse data sets

USGS Publications Warehouse

Sprenger, Karla K.; Larsen, Dana M.

1993-01-01

The need for a data dictionary database at the U.S. Geological Survey's EROS Data Center (EDC) was reinforced with the Earth Observing System Data and Information System (EOSDIS) requirement for consistent field definitions of data sets residing at more than one archive center. The EDC requirement addresses the existence of multiple sets with identical field definitions using various naming conventions. The EDC is developing a data dictionary database to accomplish the following foals: to standardize field names for ease in software development; to facilitate querying and updating of the date; and to generate ad hoc reports. The structure of the EDC electronic data dictionary database supports different metadata systems as well as many different data sets. A series of reports is used to keep consistency among data sets and various metadata systems.

Chinese-English Aviation and Space Dictionary.

ERIC Educational Resources Information Center

Air Force Systems Command, Wright-Patterson AFB, OH. Foreign Technology Div.

The Aviation and Space Dictionary is the second of a series of Chinese-English technical dictionaries under preparation by the Foreign Technology Division, United States Air Force Systems Command. The purpose of the series is to provide rapid reference tools for translators, abstracters, and research analysts concerned with scientific and…

Earth Observatory Satellite system definition study. Report no. 3: Design/cost tradeoff studies. Appendix A: EOS program WBS dictionary. Appendix B: EOS mission functional analysis

NASA Technical Reports Server (NTRS)

1974-01-01

The work breakdown structure (WBS) dictionary for the Earth Observatory Satellite (EOS) is defined. The various elements of the EOS program are examined to include the aggregate of hardware, computer software, services, and data required to develop, produce, test, support, and operate the space vehicle and the companion ground data management system. A functional analysis of the EOS mission is developed. The operations for three typical EOS missions, Delta, Titan, and Shuttle launched are considered. The functions were determined for the top program elements, and the mission operations, function 2.0, was expanded to level one functions. Selection of ten level one functions for further analysis to level two and three functions were based on concern for the EOS operations and associated interfaces.

Yeni Redhouse Lugati; Ingilizce-Turkce (Revised Redhouse Dictionairy; English-Turkish).

ERIC Educational Resources Information Center

United Church Board for World Ministries, Istanbul (Turkey). Near East Mission.

The general plan of this dictionary, first prepared by Sir James Redhouse in 1861 and revised in 1950 and 1953, has been to include all words which appear in the Oxford Concise Dictionary and Webster's Collegiate Dictionary. In addition, a great number of idioms have been added; the volume now contains between 60,000 and 70,000 definitions.…

Department of Defense Dictionary of Military and Associated Terms

DTIC Science & Technology

2001-04-12

Standardization Agreement (STANAG) 3680, definitions, constitute approved DOD which ratifies the NATO Glossary of Terms terminology for general use by all...Webster. 6. Publication Format b. Terminology should be of general military or associated significance. Technical This edition of JP 1-02 has been... general a. Main Body. This part of the dictionary military or associated significance. contains all terms and definitions approved for use within the

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.

PubMed

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning

PubMed Central

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝd, and the dictionary is learned from the training data using the vector space structure of ℝd and its Euclidean L2-metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis. PMID:24129583

Standardized Representation of Clinical Study Data Dictionaries with CIMI Archetypes.

PubMed

Sharma, Deepak K; Solbrig, Harold R; Prud'hommeaux, Eric; Pathak, Jyotishman; Jiang, Guoqian

2016-01-01

Researchers commonly use a tabular format to describe and represent clinical study data. The lack of standardization of data dictionary's metadata elements presents challenges for their harmonization for similar studies and impedes interoperability outside the local context. We propose that representing data dictionaries in the form of standardized archetypes can help to overcome this problem. The Archetype Modeling Language (AML) as developed by the Clinical Information Modeling Initiative (CIMI) can serve as a common format for the representation of data dictionary models. We mapped three different data dictionaries (identified from dbGAP, PheKB and TCGA) onto AML archetypes by aligning dictionary variable definitions with the AML archetype elements. The near complete alignment of data dictionaries helped map them into valid AML models that captured all data dictionary model metadata. The outcome of the work would help subject matter experts harmonize data models for quality, semantic interoperability and better downstream data integration.

Detailed Facility Report Data Dictionary | ECHO | US EPA

EPA Pesticide Factsheets

The Detailed Facility Report Data Dictionary provides users with a list of the variables and definitions that have been incorporated into the Detailed Facility Report. The Detailed Facility Report provides a concise enforcement and compliance history for a facility.

48 CFR 247.001 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... OF DEFENSE CONTRACT MANAGEMENT TRANSPORTATION 247.001 Definitions. For definitions of “Civil Reserve Air Fleet” and “Voluntary Intermodal Sealift Agreement,” see Joint Pub 1-02, DoD Dictionary of...

System analysis study of space platform and station accommodations for life sciences research facilities. Volume 2: Study results, attachment 2. Phase A: Conceptual design and programmatics

NASA Technical Reports Server (NTRS)

Wiley, Lowell F.

1985-01-01

The study results from the conceptual design and programmatics segment of the Space Platform and Station Accommodation for Life Sciences Research Facilities. The results and significant findings of the conceptual design and programmatics were generated by these tasks: (1) the review and update engineering and science requirements; (2) analysis of life sciences mission transition scenario; (3) the review and update of key trade issues; (4) the development of conceptual definition and designs; and (5) the development of the work breakdown schedule and its dictionary, program schedule, and estimated costs.

Evaluation of a Hyperlinked Consumer Health Dictionary for reading EHR notes.

PubMed

Slaughter, Laura; Oyri, Karl; Fosse, Erik

2011-01-01

In this paper, we report on a pilot study conducted to test the usefulness and understandability of definitions in a Consumer Health Dictionary (IVS-CHD). Our two main goals for this study were to evaluate functionality of the dictionary when embedded in electronic health records (EHR) and determine the methodology for our larger-scale project to iteratively develop the IVS-CHD. The hyperlinked IVS-CHD was made available to thoracic surgery patients reading their own EHR. We asked patients to rate definitions on two 5-level Likert items measuring perceived usefulness and understandability. We also captured the terms that patients wanted defined, but that were not included in the IVS-CHD. Preliminary results indicate the types of problems that must be avoided when creating definitions, for example, that patients prefer detailed explanations that include medical outcomes, and that do not use "unfamiliar" terms they must also look up. We also have gained insight into the types of terms that patients want defined from their EHR notes, especially certain abbreviations. Patients further commented on the experience of reading EHR notes directly from the same system used by healthcare personnel and the help strategy of linking the contents to a hyperlinked dictionary.

Observables and microscopic entropy of higher spin black holes

NASA Astrophysics Data System (ADS)

Compère, Geoffrey; Jottar, Juan I.; Song, Wei

2013-11-01

In the context of recently proposed holographic dualities between higher spin theories in AdS3 and (1 + 1)-dimensional CFTs with symmetry algebras, we revisit the definition of higher spin black hole thermodynamics and the dictionary between bulk fields and dual CFT operators. We build a canonical formalism based on three ingredients: a gauge-invariant definition of conserved charges and chemical potentials in the presence of higher spin black holes, a canonical definition of entropy in the bulk, and a bulk-to-boundary dictionary aligned with the asymptotic symmetry algebra. We show that our canonical formalism shares the same formal structure as the so-called holomorphic formalism, but differs in the definition of charges and chemical potentials and in the bulk-to-boundary dictionary. Most importantly, we show that it admits a consistent CFT interpretation. We discuss the spin-2 and spin-3 cases in detail and generalize our construction to theories based on the hs[ λ] algebra, and on the sl( N,[InlineMediaObject not available: see fulltext.]) algebra for any choice of sl(2 ,[InlineMediaObject not available: see fulltext.]) embedding.

Dear Verity: Why Are All the Dictionaries Wrong?

ERIC Educational Resources Information Center

Dempsey, Deirdre; Marshall, John

2001-01-01

An education major enrolled in a mathematics education course ponders confusing definitions of "multiplication" functions in dictionaries and in a handout on Euclid. This student teacher wants to teach elementary students what multiplication really is, not just impart an algorithmic skill. (MLH)

Dictionary of Cotton

USDA-ARS?s Scientific Manuscript database

The Dictionary of Cotton has over 2,000 terms and definitions that were compiled by 33 researchers. It reflects the ongoing commitment of the International Cotton Advisory Committee, through its Technical Information Section, to the spread of knowledge about cotton to all those who have an interest ...

Standardized Representation of Clinical Study Data Dictionaries with CIMI Archetypes

PubMed Central

Sharma, Deepak K.; Solbrig, Harold R.; Prud’hommeaux, Eric; Pathak, Jyotishman; Jiang, Guoqian

2016-01-01

Researchers commonly use a tabular format to describe and represent clinical study data. The lack of standardization of data dictionary’s metadata elements presents challenges for their harmonization for similar studies and impedes interoperability outside the local context. We propose that representing data dictionaries in the form of standardized archetypes can help to overcome this problem. The Archetype Modeling Language (AML) as developed by the Clinical Information Modeling Initiative (CIMI) can serve as a common format for the representation of data dictionary models. We mapped three different data dictionaries (identified from dbGAP, PheKB and TCGA) onto AML archetypes by aligning dictionary variable definitions with the AML archetype elements. The near complete alignment of data dictionaries helped map them into valid AML models that captured all data dictionary model metadata. The outcome of the work would help subject matter experts harmonize data models for quality, semantic interoperability and better downstream data integration. PMID:28269909

Regularized spherical polar fourier diffusion MRI with optimal dictionary learning.

PubMed

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid; Shen, Dinggang; Yap, Pew-Thian

2013-01-01

Compressed Sensing (CS) takes advantage of signal sparsity or compressibility and allows superb signal reconstruction from relatively few measurements. Based on CS theory, a suitable dictionary for sparse representation of the signal is required. In diffusion MRI (dMRI), CS methods proposed for reconstruction of diffusion-weighted signal and the Ensemble Average Propagator (EAP) utilize two kinds of Dictionary Learning (DL) methods: 1) Discrete Representation DL (DR-DL), and 2) Continuous Representation DL (CR-DL). DR-DL is susceptible to numerical inaccuracy owing to interpolation and regridding errors in a discretized q-space. In this paper, we propose a novel CR-DL approach, called Dictionary Learning - Spherical Polar Fourier Imaging (DL-SPFI) for effective compressed-sensing reconstruction of the q-space diffusion-weighted signal and the EAP. In DL-SPFI, a dictionary that sparsifies the signal is learned from the space of continuous Gaussian diffusion signals. The learned dictionary is then adaptively applied to different voxels using a weighted LASSO framework for robust signal reconstruction. Compared with the start-of-the-art CR-DL and DR-DL methods proposed by Merlet et al. and Bilgic et al., respectively, our work offers the following advantages. First, the learned dictionary is proved to be optimal for Gaussian diffusion signals. Second, to our knowledge, this is the first work to learn a voxel-adaptive dictionary. The importance of the adaptive dictionary in EAP reconstruction will be demonstrated theoretically and empirically. Third, optimization in DL-SPFI is only performed in a small subspace resided by the SPF coefficients, as opposed to the q-space approach utilized by Merlet et al. We experimentally evaluated DL-SPFI with respect to L1-norm regularized SPFI (L1-SPFI), which uses the original SPF basis, and the DR-DL method proposed by Bilgic et al. The experiment results on synthetic and real data indicate that the learned dictionary produces sparser coefficients than the original SPF basis and results in significantly lower reconstruction error than Bilgic et al.'s method.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Marketing and Communications Media Dictionary.

ERIC Educational Resources Information Center

Vigrolio, Tom; Zahler, Jack

The authors have compiled a dictionary of terms used in marketing, advertising, public relations, and radio/television, photography/filmmaking, and graphics. Included in the volume are articles of a general and historical interest regarding the various media covered in the definitions. A list of trade publications is appended. (JY)

Vygotskyan Theory Applied to Japanese-English Lexicography.

ERIC Educational Resources Information Center

McCreary, Don R.

This paper discusses and demonstrates the use of Vygotskyan psycholinguistic theory in creating lexical translations and exemplifying sentences for a bilingual dictionary. The dictionary is a Japanese-English scientific and technical reference. The use of one Vygotskyan concept, definition of situation, relies on the users' expectations, given…

Dictionary of Microscopy

NASA Astrophysics Data System (ADS)

Heath, Julian

2005-10-01

The past decade has seen huge advances in the application of microscopy in all areas of science. This welcome development in microscopy has been paralleled by an expansion of the vocabulary of technical terms used in microscopy: terms have been coined for new instruments and techniques and, as microscopes reach even higher resolution, the use of terms that relate to the optical and physical principles underpinning microscopy is now commonplace. The Dictionary of Microscopy was compiled to meet this challenge and provides concise definitions of over 2,500 terms used in the fields of light microscopy, electron microscopy, scanning probe microscopy, x-ray microscopy and related techniques. Written by Dr Julian P. Heath, Editor of Microscopy and Analysis, the dictionary is intended to provide easy navigation through the microscopy terminology and to be a first point of reference for definitions of new and established terms. The Dictionary of Microscopy is an essential, accessible resource for: students who are new to the field and are learning about microscopes equipment purchasers who want an explanation of the terms used in manufacturers' literature scientists who are considering using a new microscopical technique experienced microscopists as an aide mémoire or quick source of reference librarians, the press and marketing personnel who require definitions for technical reports.

Bookbinding and the Conservation of Books. A Dictionary of Descriptive Terminology.

ERIC Educational Resources Information Center

Roberts, Matt T.; Etherington, Don

Intended for bookbinders and conservators of library and archival material and for those working in related fields, such as bibliography and librarianship, this dictionary contains definitions for the nomenclature of bookbinding and the conservation of archival material, illustrations of bookbinding equipment and processes, and biographical…

Tibetan-English Dictionary with Supplement.

ERIC Educational Resources Information Center

Buck, Stuart H.

The format of this Tibetan-English dictionary includes the following: (1) after the Tibetan word or phrase, variant spellings are noted in parentheses; (2) irregular past, future, or imperative forms of the verb are also given in parentheses; (3) English definitions are separated into categories by semicolons; (4) verbal forms in English are…

A Dictionary of Mining, Mineral and Related Terms.

ERIC Educational Resources Information Center

Thrush, Paul W., Comp.

This dictionary contains about 55,000 terms with approximately 150,000 definitions. These terms are of both a technical and local nature and apply to metal mining, coal mining, quarrying, geology, metallurgy, ceramics and clays, glassmaking, minerals and mineralogy, and general terminology. Petroleum, natural gas, and legal mining terminology,…

Writing in Maths

ERIC Educational Resources Information Center

Australian Primary Mathematics Classroom, 2009

2009-01-01

Students write definitions or explanations of mathematical words or symbols in their own words. These can be collated and added to as the year progresses to form a class dictionary that all students can access as required, or students could create their own personal dictionaries. This article presents a collection of ideas for incorporating…

Learning Words from Context and Dictionaries: An Experimental Comparison.

ERIC Educational Resources Information Center

Fischer, Ute

1994-01-01

Investigated the independent and interactive effects of contextual and definitional information on vocabulary learning. German students of English received either a text with unfamiliar English words or their monolingual English dictionary entries. A third group received both. Information about word context is crucial to understanding meaning. (44…

Plasma Dictionary Website

NASA Astrophysics Data System (ADS)

Correll, Don; Heeter, Robert; Alvarez, Mitch

2000-10-01

In response to many inquiries for a list of plasma terms, a database driven Plasma Dictionary website (plasmadictionary.llnl.gov) was created that allows users to submit new terms, search for specific terms or browse alphabetic listings. The Plasma Dictionary website contents began with the Fusion & Plasma Glossary terms available at the Fusion Energy Educational website (fusedweb.llnl.gov). Plasma researchers are encouraged to add terms and definitions. By clarifying the meanings of specific plasma terms, it is envisioned that the primary use of the Plasma Dictionary website will be by students, teachers, researchers, and writers for (1) Enhancing literacy in plasma science, (2) Serving as an educational aid, (3) Providing practical information, and (4) Helping clarify plasma writings. The Plasma Dictionary website has already proved useful in responding to a request from the CRC Press (www.crcpress.com) to add plasma terms to its CRC physics dictionary project (members.aol.com/physdict/).

Understanding the Soviet Threat: The Necessity of Analyzing Soviet Military Thought and Actions from a Soviet Perspective.

DTIC Science & Technology

1987-12-01

discipline comparable to physics or chemistry in its application. This concept is quite unusual for an American, as military affairs are not often studied in...Sanderson cites definitions from The Pocket Oxford Dictionary, The 67 Oxford Dictionary of English Etymology , and Blackie ’s Compact Etymological

An Historical Albanian-English Dictionary: Part II, N-Z.

ERIC Educational Resources Information Center

Mann, Stuart E.

The second of a two-volume, historical, Albanian-English dictionary, spanning a time period from 1496-1938, this reference work is based on Albanian word usage in literature and among the peasant culture. Entries are alphabetically listed from "n" through "z" with abbreviated reference to the word's bibliographic origin. Definitions are brief and…

The Generalist versus the Specialist: The New Oxford Dictionary Reveals a Gap.

ERIC Educational Resources Information Center

Levine, Martin Lyon

1981-01-01

There is a gap, it is suggested, separating the generally cultured person, not just from the scientist, but from specialists in many fields. Dictionary definitions are seen as one means of seeing the extent to which specialists and those in the general culture speak the same language. (MLW)

The Primary Computer Dictionary.

ERIC Educational Resources Information Center

Girard, Suzanne; Willing, Kathlene

Suitable for children from kindergarten to grade three, this dictionary is designed to introduce young children to computer terminology at a level that they will understand and find useful. It is also suitable for parents as a home resource, for library use, and as a handbook for teachers. The first sentence of each definition contains the kernel…

The Language of Show Biz: A Dictionary.

ERIC Educational Resources Information Center

Sergel, Sherman Louis, Ed.

This dictionary of the language of show biz provides the layman with definitions and essays on terms and expressions often used in show business. The overall pattern of selection was intended to be more rather than less inclusive, though radio, television, and film terms were deliberately omitted. Lengthy explanations are sometimes used to express…

Metadata Dictionary Database: A Proposed Tool for Academic Library Metadata Management

ERIC Educational Resources Information Center

Southwick, Silvia B.; Lampert, Cory

2011-01-01

This article proposes a metadata dictionary (MDD) be used as a tool for metadata management. The MDD is a repository of critical data necessary for managing metadata to create "shareable" digital collections. An operational definition of metadata management is provided. The authors explore activities involved in metadata management in…

Note regarding the word 'behavior' in glossaries of introductory textbooks, dictionaries, and encyclopedias devoted to psychology.

PubMed

Abramson, Charles I; Place, Aaron J

2005-10-01

Glossaries of introductory textbooks in psychology, biology, and animal behavior were surveyed to find whether they induded the word 'behavior'. In addition to texts, encyclopedias and dictionaries devoted to the study of behavior were also surveyed. Of the 138 tests sampled across all three fields, only 38 (27%) included the term 'behavior' in their glossaries. Of the 15 encyclopedias and dictionaries surveyed, only 5 defined 'behavior'. To assess whether the term 'behavior' has disappeared from textbook glossaries or whether it has usually been absent, we sampled 23 introductory psychology texts written from 1886 to 1958. Only two texts contained glossaries, and the word 'behavior' was defined in both. An informal survey was conducted of students enrolled in introductory classes in psychology, biology, and animal behavior to provide data on the consistency of definitions. Students were asked to "define the word 'behavior'." Analysis indicated the definition was dependent upon the course. We suggest that future introductory textbook authors and editors of psychology-based dictionaries and encyclopedias include 'behavior' in their glossaries.

Kinematic space for conical defects

NASA Astrophysics Data System (ADS)

Cresswell, Jesse C.; Peet, Amanda W.

2017-11-01

Kinematic space can be used as an intermediate step in the AdS/CFT dictionary and lends itself naturally to the description of diffeomorphism invariant quantities. From the bulk it has been defined as the space of boundary anchored geodesics, and from the boundary as the space of pairs of CFT points. When the bulk is not globally AdS3 the appearance of non-minimal geodesics leads to ambiguities in these definitions. In this work conical defect spacetimes are considered as an example where non-minimal geodesics are common. From the bulk it is found that the conical defect kinematic space can be obtained from the AdS3 kinematic space by the same quotient under which one obtains the defect from AdS3. The resulting kinematic space is one of many equivalent fundamental regions. From the boundary the conical defect kinematic space can be determined by breaking up OPE blocks into contributions from individual bulk geodesics. A duality is established between partial OPE blocks and bulk fields integrated over individual geodesics, minimal or non-minimal.

Core Standards of the EUBIROD Project. Defining a European Diabetes Data Dictionary for Clinical Audit and Healthcare Delivery.

PubMed

Cunningham, S G; Carinci, F; Brillante, M; Leese, G P; McAlpine, R R; Azzopardi, J; Beck, P; Bratina, N; Bocquet, V; Doggen, K; Jarosz-Chobot, P K; Jecht, M; Lindblad, U; Moulton, T; Metelko, Ž; Nagy, A; Olympios, G; Pruna, S; Skeie, S; Storms, F; Di Iorio, C T; Massi Benedetti, M

2016-01-01

A set of core diabetes indicators were identified in a clinical review of current evidence for the EUBIROD project. In order to allow accurate comparisons of diabetes indicators, a standardised currency for data storage and aggregation was required. We aimed to define a robust European data dictionary with appropriate clinical definitions that can be used to analyse diabetes outcomes and provide the foundation for data collection from existing electronic health records for diabetes. Existing clinical datasets used by 15 partner institutions across Europe were collated and common data items analysed for consistency in terms of recording, data definition and units of measurement. Where necessary, data mappings and algorithms were specified in order to allow partners to meet the standard definitions. A series of descriptive elements were created to document metadata for each data item, including recording, consistency, completeness and quality. While datasets varied in terms of consistency, it was possible to create a common standard that could be used by all. The minimum dataset defined 53 data items that were classified according to their feasibility and validity. Mappings and standardised definitions were used to create an electronic directory for diabetes care, providing the foundation for the EUBIROD data analysis repository, also used to implement the diabetes registry and model of care for Cyprus. The development of data dictionaries and standards can be used to improve the quality and comparability of health information. A data dictionary has been developed to be compatible with other existing data sources for diabetes, within and beyond Europe.

When a domain isn’t a domain, and why it’s important to properly filter proteins in databases

PubMed Central

Towse, Clare-Louise; Daggett, Valerie

2013-01-01

Summary Membership in a protein domain database does not a domain make; a feature we realized when generating a consensus view of protein fold space with our Consensus Domain Dictionary (CDD). This dictionary was used to select representative structures for characterization of the protein dynameome: the Dynameomics initiative. Through this endeavor we rejected a surprising 40% of the 1695 folds in the CDD as being non-autonomous folding units. Although some of this was due to the challenges of grouping similar fold topologies, the dissonance between the cataloguing and structural qualification of protein domains remains surprising. Another potential factor is previously overlooked intrinsic disorder; predicted estimates suggest 40% of proteins to have either local or global disorder. One thing is clear, filtering a structural database and ensuring a consistent definition for protein domains is crucial, and caution is prescribed when generalizations of globular domains are drawn from unfiltered protein domain datasets. PMID:23108912

Concepts of happiness across time and cultures.

PubMed

Oishi, Shigehiro; Graham, Jesse; Kesebir, Selin; Galinha, Iolanda Costa

2013-05-01

We explored cultural and historical variations in concepts of happiness. First, we analyzed the definitions of happiness in dictionaries from 30 nations to understand cultural similarities and differences in happiness concepts. Second, we analyzed the definition of happiness in Webster's dictionaries from 1850 to the present day to understand historical changes in American English. Third, we coded the State of the Union addresses given by U.S. presidents from 1790 to 2010. Finally, we investigated the appearance of the phrases happy nation versus happy person in Google's Ngram Viewer from 1800 to 2008. Across cultures and time, happiness was most frequently defined as good luck and favorable external conditions. However, in American English, this definition was replaced by definitions focused on favorable internal feeling states. Our findings highlight the value of a historical perspective in the study of psychological concepts.

Fast dictionary-based reconstruction for diffusion spectrum imaging.

PubMed

Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar

2013-11-01

Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging

PubMed Central

Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar

2015-01-01

Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466

Rdesign: A data dictionary with relational database design capabilities in Ada

NASA Technical Reports Server (NTRS)

Lekkos, Anthony A.; Kwok, Teresa Ting-Yin

1986-01-01

Data Dictionary is defined to be the set of all data attributes, which describe data objects in terms of their intrinsic attributes, such as name, type, size, format and definition. It is recognized as the data base for the Information Resource Management, to facilitate understanding and communication about the relationship between systems applications and systems data usage and to help assist in achieving data independence by permitting systems applications to access data knowledge of the location or storage characteristics of the data in the system. A research and development effort to use Ada has produced a data dictionary with data base design capabilities. This project supports data specification and analysis and offers a choice of the relational, network, and hierarchical model for logical data based design. It provides a highly integrated set of analysis and design transformation tools which range from templates for data element definition, spreadsheet for defining functional dependencies, normalization, to logical design generator.

The Role of Sanctuary in an Insurgency

DTIC Science & Technology

2008-05-22

42 Gearoid O Tuathail, “De- Territorialised Threats and Global Dangers: Geopolitics and...Dictionary definition of “law,” http://www.merriam- webster.com/dictionary/law, accessed April 16, 2008. 44 Tuathail, “De- Territorialised Threats and...Chapel Hill: The University of North Carolina Press, 1994. Tuathail, Geroid O., “De- Territorialised Threats and Global Dangers: Geopolitics and Risk

The Impact of the Computer on the English Language.

ERIC Educational Resources Information Center

Perry, Devern

1990-01-01

Study analyzed 224 product announcements from 69 hardware and software companies to detail computer-related words that are in common usage and compare the words and definitions with those in the Merriam-Webster dictionary. It was found that 67.3 percent of the words were not included in the dictionary, pointing out the need for teachers to help…

Instructional Note: Using "The Devil's Dictionary" to Teach Definitions

ERIC Educational Resources Information Center

Lane, Mary T.

2004-01-01

Known as Bitter Bierce, the writer Ambrose Bierce spent years ironically redefining the terms for a host of people, things, actions, and concepts, compiling his redefinitions into the "The Devil's Dictionary." In this article, the author describes how she uses this caustic work as a model for an exercise when her developmental writing class begins…

Russian-English Dictionary of Cybernetics and Computer Technology.

ERIC Educational Resources Information Center

Holland, Wade B.

This work contains over 5,350 terms which have special or unique definition when applied in a cybernetic context. Corrections and improvements to the first edition of the dictionary have been made in this second edition. Entries are made for terms encountered in the Soviet cybernetic literature, without any attempt to define the field or to…

Development of Foreign Language Lexical Competence on the Basis of a Learner's Terminological Thesaurus and Dictionary

ERIC Educational Resources Information Center

Chainikova, Galina R.; Zatonskiy, Andrey V.; Mitiukov, Nicholas W.; Busygina, Helena L.

2018-01-01

The article suggests a method of foreign language lexical competence development on the basis of a Learner's terminological thesaurus and dictionary of software terms which includes four main components: classification part demonstrating the inner logic of the subject area, glossary with definitions of key terms, thesaurus demonstrating logical…

The Role of Context and Dictionary Definitions on Varying Levels of Word Knowledge.

ERIC Educational Resources Information Center

Nist, Sherrie L.; Olejnik, Stephen

1995-01-01

Examines contextual and definitional factors that determine whether and to what extent college students learn unknown words without instruction. Finds that the quality of the definition appears to determine the extent to which college students are able to learn unknown words. (RS)

9 CFR 166.1 - Definitions in alphabetical order.

Code of Federal Regulations, 2014 CFR

2014-01-01

... OF AGRICULTURE SWINE HEALTH PROTECTION SWINE HEALTH PROTECTION General Provisions § 166.1 Definitions... by definitions in a standard dictionary. Act. The Swine Health Protection Act (Pub. L. 96-468) as... cooked as a food for swine and which are fenced in or otherwise constructed so that swine are unable to...

9 CFR 166.1 - Definitions in alphabetical order.

Code of Federal Regulations, 2012 CFR

2012-01-01

... OF AGRICULTURE SWINE HEALTH PROTECTION SWINE HEALTH PROTECTION General Provisions § 166.1 Definitions... by definitions in a standard dictionary. Act. The Swine Health Protection Act (Pub. L. 96-468) as... cooked as a food for swine and which are fenced in or otherwise constructed so that swine are unable to...

9 CFR 166.1 - Definitions in alphabetical order.

Code of Federal Regulations, 2011 CFR

2011-01-01

... OF AGRICULTURE SWINE HEALTH PROTECTION SWINE HEALTH PROTECTION General Provisions § 166.1 Definitions... by definitions in a standard dictionary. Act. The Swine Health Protection Act (Pub. L. 96-468) as... cooked as a food for swine and which are fenced in or otherwise constructed so that swine are unable to...

9 CFR 166.1 - Definitions in alphabetical order.

Code of Federal Regulations, 2013 CFR

2013-01-01

... OF AGRICULTURE SWINE HEALTH PROTECTION SWINE HEALTH PROTECTION General Provisions § 166.1 Definitions... by definitions in a standard dictionary. Act. The Swine Health Protection Act (Pub. L. 96-468) as... cooked as a food for swine and which are fenced in or otherwise constructed so that swine are unable to...

Chinese-English Technical Dictionaries. Volume 1, Aviation and Space.

ERIC Educational Resources Information Center

Library of Congress, Washington, DC. Aerospace Technology Div.

The present dictionary is the first of a series of Chinese-English technical dictionaries under preparation by the Aerospace Technology Division of the Library of Congress. The purpose of the series is to provide rapid reference tools for translators, abstractors, and research analysts concerned with scientific and technical materials published in…

Dictionnaire contextuel anglais-francais de l'energie solaire (Contextual English-French Dictionary on Solar Energy).

ERIC Educational Resources Information Center

Serre, Robert

This English-French dictionary on solar energy is intended for translators and purports to contain all the elements necessary for doing quality translations. Each entry contains the following elements: (1) the basic English word with its synonyms and equivalents; (2) the definition in English and reference to its source; and (3) sentences or…

Information Sharing and Collaboration Business Plan

DTIC Science & Technology

2006-03-30

for information sharing The proposed environment will need a common definition of terms and dictionaries of competing terms where common definitions...a lexicon, a monolingual on-line handbook, and a thesaurus and ontology of abbreviations, acronyms, and terminology. (ISCO 2005, 18

Password-only authenticated three-party key exchange proven secure against insider dictionary attacks.

PubMed

Nam, Junghyun; Choo, Kim-Kwang Raymond; Paik, Juryon; Won, Dongho

2014-01-01

While a number of protocols for password-only authenticated key exchange (PAKE) in the 3-party setting have been proposed, it still remains a challenging task to prove the security of a 3-party PAKE protocol against insider dictionary attacks. To the best of our knowledge, there is no 3-party PAKE protocol that carries a formal proof, or even definition, of security against insider dictionary attacks. In this paper, we present the first 3-party PAKE protocol proven secure against both online and offline dictionary attacks as well as insider and outsider dictionary attacks. Our construct can be viewed as a protocol compiler that transforms any 2-party PAKE protocol into a 3-party PAKE protocol with 2 additional rounds of communication. We also present a simple and intuitive approach of formally modelling dictionary attacks in the password-only 3-party setting, which significantly reduces the complexity of proving the security of 3-party PAKE protocols against dictionary attacks. In addition, we investigate the security of the well-known 3-party PAKE protocol, called GPAKE, due to Abdalla et al. (2005, 2006), and demonstrate that the security of GPAKE against online dictionary attacks depends heavily on the composition of its two building blocks, namely a 2-party PAKE protocol and a 3-party key distribution protocol.

Kamusi ya Kwanza Kiswahili-Kiingereza. A First Dictionary Swahili-English.

ERIC Educational Resources Information Center

Cahill, William F.

This dictionary is written for students who are learning Swahili as a second language. The 1,837 words that are defined in it are words likely to be encountered by a primary school student in East Africa who is learning Swahili. Most of the English words in the definitions have been taken from among the English words taught during the first four…

Department of Defense Dictionary of Military and Associated Terms

DTIC Science & Technology

2001-04-12

together with their definitions, constitute approved DOD terminology for general use by all components of the Department of Defense. The Secretary...accepted dictionary, e.g., by Merriam- Webster. b. Terminology should be of general military or associated significance. Technical or highly...specialized terms may be included if they can be defined in easily understood language and if their inclusion is of general military or associated

A dictionary without definitions: romanticist science in the production and presentation of the Grimm brothers' German dictionary, 1838-1863.

PubMed

Kistner, Kelly

2014-12-01

Between 1838 and 1863 the Grimm brothers led a collaborative research project to create a new kind of dictionary documenting the history of the German language. They imagined the work would present a scientific account of linguistic cohesiveness and strengthen German unity. However, their dictionary volumes (most of which were arranged and written by Jacob Grimm) would be variously criticized for their idiosyncratic character and ultimately seen as a poor, and even prejudicial, piece of scholarship. This paper argues that such criticisms may reflect a misunderstanding of the dictionary. I claim it can be best understood as an artifact of romanticist science and its epistemological privileging of subjective perception coupled with a deeply-held faith in inter-subjective congruence. Thus situated, it is a rare and detailed case of Romantic ideas and ideals applied to the scientific study of social artifacts. Moreover, the dictionary's organization, reception, and legacy provide insights into the changing landscape of scientific practice in Germany, showcasing the difficulties of implementing a romanticist vision of science amidst widening gaps between the public and professionals, generalists and specialists.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

A Dictionary of Acquisition and Contracting Terms

DTIC Science & Technology

1990-12-01

consolidated national effort had been undertaken in this regard. Various individuals, commands and schools have attempted to assemble elements of definitions...however, the lack of a consolidated effort has caused a disparity in the definitions of terms. Previous graduate theses have researched definitions and...Supply Corps (SC), United States Navy (USN) initiated the consolidation of baseline consensus definitions in 1988. In 1989, Captain (CPT) John Cannaday

A Space-Time-Frequency Dictionary for Sparse Cortical Source Localization.

PubMed

Korats, Gundars; Le Cam, Steven; Ranta, Radu; Louis-Dorr, Valerie

2016-09-01

Cortical source imaging aims at identifying activated cortical areas on the surface of the cortex from the raw electroencephalogram (EEG) data. This problem is ill posed, the number of channels being very low compared to the number of possible source positions. In some realistic physiological situations, the active areas are sparse in space and of short time durations, and the amount of spatio-temporal data to carry the inversion is then limited. In this study, we propose an original data driven space-time-frequency (STF) dictionary which takes into account simultaneously both spatial and time-frequency sparseness while preserving smoothness in the time frequency (i.e., nonstationary smooth time courses in sparse locations). Based on these assumptions, we take benefit of the matching pursuit (MP) framework for selecting the most relevant atoms in this highly redundant dictionary. We apply two recent MP algorithms, single best replacement (SBR) and source deflated matching pursuit, and we compare the results using a spatial dictionary and the proposed STF dictionary to demonstrate the improvements of our multidimensional approach. We also provide comparison using well-established inversion methods, FOCUSS and RAP-MUSIC, analyzing performances under different degrees of nonstationarity and signal to noise ratio. Our STF dictionary combined with the SBR approach provides robust performances on realistic simulations. From a computational point of view, the algorithm is embedded in the wavelet domain, ensuring high efficiency in term of computation time. The proposed approach ensures fast and accurate sparse cortical localizations on highly nonstationary and noisy data.

Concepts and definitions for "supportive care," "best supportive care," "palliative care," and "hospice care" in the published literature, dictionaries, and textbooks.

PubMed

Hui, David; De La Cruz, Maxine; Mori, Masanori; Parsons, Henrique A; Kwon, Jung Hye; Torres-Vigil, Isabel; Kim, Sun Hyun; Dev, Rony; Hutchins, Ronald; Liem, Christiana; Kang, Duck-Hee; Bruera, Eduardo

2013-03-01

Commonly used terms such as "supportive care," "best supportive care," "palliative care," and "hospice care" were rarely and inconsistently defined in the palliative oncology literature. We conducted a systematic review of the literature to further identify concepts and definitions for these terms. We searched MEDLINE, PsycInfo, EMBASE, and CINAHL for published peer-reviewed articles from 1948 to 2011 that conceptualized, defined, or examined these terms. Two researchers independently reviewed each citation for inclusion and then extracted the concepts/definitions when available. Dictionaries/textbooks were also searched. Nine of 32 "SC/BSC," 25 of 182 "PC," and 12 of 42 "HC" articles focused on providing a conceptual framework/definition. Common concepts for all three terms were symptom control and quality-of-life for patients with life-limiting illness. "SC" focused more on patients on active treatment compared to other categories (9/9 vs. 8/37) and less often involved interdisciplinary care (4/9 vs. 31/37). In contrast, "HC" focused more on volunteers (6/12 vs. 6/34), bereavement care (9/12 vs. 7/34), and community care (9/12 vs. 6/34). Both "PC" and "SC/BSC" were applicable earlier in the disease trajectory (16/34 vs. 0/9). We found 13, 24, and 17 different definitions for "SC/BSC," "PC," and "HC," respectively. "SC/BSC" was the most variably defined, ranging from symptom management during cancer therapy to survivorship care. Dictionaries/textbooks showed similar findings. We identified defining concepts for "SC/BSC," "PC," and "HC" and developed a preliminary conceptual framework unifying these terms along the continuum of care to help build consensus toward standardized definitions.

Space transfer vehicle concepts and requirements study. Volume 3: Program cost estimates. Book 2: WBS and dictionary

NASA Technical Reports Server (NTRS)

Peffley, A. F.

1991-01-01

This document describes the products and services to be developed, tested, produced, and operated for the Space Transfer Vehicle (STV) Program. The Work Breakdown Structure (WBS) and WBS Dictionary are program management tools used to catalog, account by task, and summarize work packages of a space system program. The products or services to be delivered or accomplished during the STV C/D phase are the primary focus of this work breakdown structure document.

Password-Only Authenticated Three-Party Key Exchange Proven Secure against Insider Dictionary Attacks

PubMed Central

Nam, Junghyun; Choo, Kim-Kwang Raymond

2014-01-01

While a number of protocols for password-only authenticated key exchange (PAKE) in the 3-party setting have been proposed, it still remains a challenging task to prove the security of a 3-party PAKE protocol against insider dictionary attacks. To the best of our knowledge, there is no 3-party PAKE protocol that carries a formal proof, or even definition, of security against insider dictionary attacks. In this paper, we present the first 3-party PAKE protocol proven secure against both online and offline dictionary attacks as well as insider and outsider dictionary attacks. Our construct can be viewed as a protocol compiler that transforms any 2-party PAKE protocol into a 3-party PAKE protocol with 2 additional rounds of communication. We also present a simple and intuitive approach of formally modelling dictionary attacks in the password-only 3-party setting, which significantly reduces the complexity of proving the security of 3-party PAKE protocols against dictionary attacks. In addition, we investigate the security of the well-known 3-party PAKE protocol, called GPAKE, due to Abdalla et al. (2005, 2006), and demonstrate that the security of GPAKE against online dictionary attacks depends heavily on the composition of its two building blocks, namely a 2-party PAKE protocol and a 3-party key distribution protocol. PMID:25309956

Bayesian nonparametric dictionary learning for compressed sensing MRI.

PubMed

Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

2014-12-01

We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

Informatics with Systems Science and Cybernetics--Concepts and Definitions.

ERIC Educational Resources Information Center

Samuelson, Kjell

This dictionary defines information science, computer science, systems theory, and cybernetic terms in English and provides the Swedish translation of each term. An index of Swedish terms refers the user to the page where the English equivalent and definition appear. Most of the 38 references listed are in English. (RAA)

Definition and maintenance of a telemetry database dictionary

NASA Technical Reports Server (NTRS)

Knopf, William P. (Inventor)

2007-01-01

A telemetry dictionary database includes a component for receiving spreadsheet workbooks of telemetry data over a web-based interface from other computer devices. Another component routes the spreadsheet workbooks to a specified directory on the host processing device. A process then checks the received spreadsheet workbooks for errors, and if no errors are detected the spreadsheet workbooks are routed to another directory to await initiation of a remote database loading process. The loading process first converts the spreadsheet workbooks to comma separated value (CSV) files. Next, a network connection with the computer system that hosts the telemetry dictionary database is established and the CSV files are ported to the computer system that hosts the telemetry dictionary database. This is followed by a remote initiation of a database loading program. Upon completion of loading a flatfile generation program is manually initiated to generate a flatfile to be used in a mission operations environment by the core ground system.

Automated storage and retrieval of data obtained in the Interkosmos project

NASA Technical Reports Server (NTRS)

Ziolkovski, K.; Pakholski, V.

1975-01-01

The formation of a data bank and information retrieval system for scientific data is described. The stored data can be digital or documentation data. Data classification methods are discussed along with definition and compilation of the dictionary utilized, definition of the indexing scheme, and definition of the principles used in constructing a file for documents, data blocks, and tapes. Operating principles are also presented.

Dictionary Learning on the Manifold of Square Root Densities and Application to Reconstruction of Diffusion Propagator Fields*

PubMed Central

Sun, Jiaqi; Xie, Yuchen; Ye, Wenxing; Ho, Jeffrey; Entezari, Alireza; Blackband, Stephen J.

2013-01-01

In this paper, we present a novel dictionary learning framework for data lying on the manifold of square root densities and apply it to the reconstruction of diffusion propagator (DP) fields given a multi-shell diffusion MRI data set. Unlike most of the existing dictionary learning algorithms which rely on the assumption that the data points are vectors in some Euclidean space, our dictionary learning algorithm is designed to incorporate the intrinsic geometric structure of manifolds and performs better than traditional dictionary learning approaches when applied to data lying on the manifold of square root densities. Non-negativity as well as smoothness across the whole field of the reconstructed DPs is guaranteed in our approach. We demonstrate the advantage of our approach by comparing it with an existing dictionary based reconstruction method on synthetic and real multi-shell MRI data. PMID:24684004

History lessons.

PubMed

Metcalfe, Sarah

2013-08-01

There was a time when epidemics were solely the province of infectious diseases. Indeed, most dictionary definitions of the term refer first to contagious diseases that spread rapidly among a given population.

Problems in Bilingual Lexicography: Romance and English

ERIC Educational Resources Information Center

Wiezell, Richard John

1975-01-01

A bilingual dictionary must be more accurate in definitions than a monolingual. This paper touches on problems of transference between languages, linguistic "cannibalism," and lexical versus connotative meaning. (CK)

Reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning.

PubMed

Song, Ying; Zhu, Zhen; Lu, Yang; Liu, Qiegen; Zhao, Jun

2014-03-01

To improve the magnetic resonance imaging (MRI) data acquisition speed while maintaining the reconstruction quality, a novel method is proposed for multislice MRI reconstruction from undersampled k-space data based on compressed-sensing theory using dictionary learning. There are two aspects to improve the reconstruction quality. One is that spatial correlation among slices is used by extending the atoms in dictionary learning from patches to blocks. The other is that the dictionary-learning scheme is used at two resolution levels; i.e., a low-resolution dictionary is used for sparse coding and a high-resolution dictionary is used for image updating. Numerical experiments are carried out on in vivo 3D MR images of brains and abdomens with a variety of undersampling schemes and ratios. The proposed method (dual-DLMRI) achieves better reconstruction quality than conventional reconstruction methods, with the peak signal-to-noise ratio being 7 dB higher. The advantages of the dual dictionaries are obvious compared with the single dictionary. Parameter variations ranging from 50% to 200% only bias the image quality within 15% in terms of the peak signal-to-noise ratio. Dual-DLMRI effectively uses the a priori information in the dual-dictionary scheme and provides dramatically improved reconstruction quality. Copyright © 2013 Wiley Periodicals, Inc.

Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA.

PubMed

Jiansen Li; Jianqi Sun; Ying Song; Yanran Xu; Jun Zhao

2014-01-01

An effective way to improve the data acquisition speed of magnetic resonance imaging (MRI) is using under-sampled k-space data, and dictionary learning method can be used to maintain the reconstruction quality. Three-dimensional dictionary trains the atoms in dictionary in the form of blocks, which can utilize the spatial correlation among slices. Dual-dictionary learning method includes a low-resolution dictionary and a high-resolution dictionary, for sparse coding and image updating respectively. However, the amount of data is huge for three-dimensional reconstruction, especially when the number of slices is large. Thus, the procedure is time-consuming. In this paper, we first utilize the NVIDIA Corporation's compute unified device architecture (CUDA) programming model to design the parallel algorithms on graphics processing unit (GPU) to accelerate the reconstruction procedure. The main optimizations operate in the dictionary learning algorithm and the image updating part, such as the orthogonal matching pursuit (OMP) algorithm and the k-singular value decomposition (K-SVD) algorithm. Then we develop another version of CUDA code with algorithmic optimization. Experimental results show that more than 324 times of speedup is achieved compared with the CPU-only codes when the number of MRI slices is 24.

Optimal Dictionaries for Sparse Solutions of Multi-frame Blind Deconvolution

DTIC Science & Technology

2014-09-01

object is the Hubble Space Telescope (HST). As stated above, the dictionary training used the first 100 of the total of the simulated PSFs. The second set...diffraction-limited Hubble image and HubbleRE is the reconstructed image from the 100 simulated atmospheric turbulence degraded images of the HST

Une Vision francaise de l'environnement: les mots et les choses (A French View of Environment: Words and Things)

ERIC Educational Resources Information Center

Antoine, Gerald

1978-01-01

An examination by a French lexicologist of four terms current in ecological movements: "ecologie,""environnement,""qualite de vie," and "ambiance." For each term, several French and English dictionary definitions are given and clarifying distinctions are made. In conclusion, four composite definitions are given. (Text is in French.) (AMH)

Study of Tools for Command and Telemetry Dictionaries

NASA Technical Reports Server (NTRS)

Pires, Craig; Knudson, Matthew D.

2017-01-01

The Command and Telemetry Dictionary is at the heart of space missions. The C&T Dictionary represents all of the information that is exchanged between the various systems both in space and on the ground. Large amounts of ever-changing information has to be disseminated to all for the various systems and sub-systems throughout all phases of the mission. The typical approach of having each sub-system manage it's own information flow, results in a patchwork of methods within a mission. This leads to significant duplication of effort and potential errors. More centralized methods have been developed to manage this data flow. This presentation will compare two tools that have been developed for this purpose, CCDD and SCIMI that were designed to work with the Core Flight System (cFS).

"Convenience Food."

ERIC Educational Resources Information Center

Lemieux, Colette

1980-01-01

Defines the meaning of the American expression "convenience food," quoting definitions given by dictionaries and specialized publications. Discusses the problem of finding the exact equivalent of this expression in French, and recommends some acceptable translations. (MES)

System technology analysis of aeroassisted orbital transfer vehicles: Moderate lift/drag (0.75-1.5). Volume 3: Cost estimates and work breakdown structure/dictionary, phase 1 and 2

NASA Technical Reports Server (NTRS)

1985-01-01

Technology payoffs of representative ground based (Phase 1) and space based (Phase 2) mid lift/drag ratio aeroassisted orbit transfer vehicles (AOTV) were assessed and prioritized. A narrative summary of the cost estimates and work breakdown structure/dictionary for both study phases is presented. Costs were estimated using the Grumman Space Programs Algorithm for Cost Estimating (SPACE) computer program and results are given for four AOTV configurations. The work breakdown structure follows the standard of the joint government/industry Space Systems Cost Analysis Group (SSCAG). A table is provided which shows cost estimates for each work breakdown structure element.

Combining dictionary techniques with extensible markup language (XML)--requirements to a new approach towards flexible and standardized documentation.

PubMed Central

Altmann, U.; Tafazzoli, A. G.; Noelle, G.; Huybrechts, T.; Schweiger, R.; Wächter, W.; Dudeck, J. W.

1999-01-01

In oncology various international and national standards exist for the documentation of different aspects of a disease. Since elements of these standards are repeated in different contexts, a common data dictionary could support consistent representation in any context. For the construction of such a dictionary existing documents have to be worked up in a complex procedure, that considers aspects of hierarchical decomposition of documents and of domain control as well as aspects of user presentation and models of the underlying model of patient data. In contrast to other thesauri, text chunks like definitions or explanations are very important and have to be preserved, since oncologic documentation often means coding and classification on an aggregate level and the safe use of coding systems is an important precondition for comparability of data. This paper discusses the potentials of the use of XML in combination with a dictionary for the promotion and development of standard conformable applications for tumor documentation. PMID:10566311

dREL: a relational expression language for dictionary methods.

PubMed

Spadaccini, Nick; Castleden, Ian R; du Boulay, Doug; Hall, Sydney R

2012-08-27

The provision of precise metadata is an important but a largely underrated challenge for modern science [Nature 2009, 461, 145]. We describe here a dictionary methods language dREL that has been designed to enable complex data relationships to be expressed as formulaic scripts in data dictionaries written in DDLm [Spadaccini and Hall J. Chem. Inf. Model.2012 doi:10.1021/ci300075z]. dREL describes data relationships in a simple but powerful canonical form that is easy to read and understand and can be executed computationally to evaluate or validate data. The execution of dREL expressions is not a substitute for traditional scientific computation; it is to provide precise data dependency information to domain-specific definitions and a means for cross-validating data. Some scientific fields apply conventional programming languages to methods scripts but these tend to inhibit both dictionary development and accessibility. dREL removes the programming barrier and encourages the production of the metadata needed for seamless data archiving and exchange in science.

Orbital transfer vehicle concept definition and system analysis study, 1985. Volume 5: Work breakdown structure and dictionary

NASA Technical Reports Server (NTRS)

Nelson, James H.; Callan, Daniel R.

1985-01-01

To establish consistency and visibility within the Orbital Transfer Vehicle (OTV) program, a preliminary work breakdown structure (WBS) and dictionary were developed. The dictionary contains definitions of terms to be used in conjunction with the WBS so that a clear understanding of the content of the hardware, function, and cost elements may be established. The OTV WBS matrix is a two-dimensional structure which shows the interrelationship of these dimensions: the hardware elements dimension and the phase and function dimension. The dimension of time cannot be shown graphically, but must be considered. Each cost entry varies with time so that it is necessary to know these cost values by year for budget planning and approval as well as for establishing cost streams for discounting purposes in the economic analysis. While a multiple dimensional approach may at first appear complex, it actually provides benefits which outweigh any concern. This structural interrelationship provides the capability to view and analyze the OTV costs from a number of different financial and management aspects. Cost may be summed by hardware groupings, phases, or functions. The WBS may be used in a number of dimensional or single listing format applications.

32 CFR 50.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... policy governing commercial sponsorship. 1 Copies may be obtained at http://www.dtic.mil/whs/directives... Dictionary of Military and Associated Terms.” 2 2 See http://www.dtic.mil/doctrine/jel/doddict/indexs.html...

Alternatively Constrained Dictionary Learning For Image Superresolution.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Yan, Pingkun

2014-03-01

Dictionaries are crucial in sparse coding-based algorithm for image superresolution. Sparse coding is a typical unsupervised learning method to study the relationship between the patches of high-and low-resolution images. However, most of the sparse coding methods for image superresolution fail to simultaneously consider the geometrical structure of the dictionary and the corresponding coefficients, which may result in noticeable superresolution reconstruction artifacts. In other words, when a low-resolution image and its corresponding high-resolution image are represented in their feature spaces, the two sets of dictionaries and the obtained coefficients have intrinsic links, which has not yet been well studied. Motivated by the development on nonlocal self-similarity and manifold learning, a novel sparse coding method is reported to preserve the geometrical structure of the dictionary and the sparse coefficients of the data. Moreover, the proposed method can preserve the incoherence of dictionary entries and provide the sparse coefficients and learned dictionary from a new perspective, which have both reconstruction and discrimination properties to enhance the learning performance. Furthermore, to utilize the model of the proposed method more effectively for single-image superresolution, this paper also proposes a novel dictionary-pair learning method, which is named as two-stage dictionary training. Extensive experiments are carried out on a large set of images comparing with other popular algorithms for the same purpose, and the results clearly demonstrate the effectiveness of the proposed sparse representation model and the corresponding dictionary learning algorithm.

Habits.

PubMed

Robbins, T W; Costa, Rui M

2017-11-20

What is a habit? One problem with the concept of habit has been that virtually everyone has their own ideas of what is meant by such a term. Whilst not eschewing folk psychology, it is useful to re-examine dictionary definitions of 'habit'. The Oxford Dictionary of English defines habit as "a settled or regular tendency or practice, especially one that is hard to give up" and also "an automatic reaction to a specific situation". The latter, reassuringly, is not too far from what has come to be known as stimulus-response theory. Copyright © 2017 Elsevier Ltd. All rights reserved.

Organizing the present, looking to the future: an online knowledge repository to facilitate collaboration.

PubMed

Burchill, C; Roos, L L; Fergusson, P; Jebamani, L; Turner, K; Dueck, S

2000-01-01

Comprehensive data available in the Canadian province of Manitoba since 1970 have aided study of the interaction between population health, health care utilization, and structural features of the health care system. Given a complex linked database and many ongoing projects, better organization of available epidemiological, institutional, and technical information was needed. The Manitoba Centre for Health Policy and Evaluation wished to develop a knowledge repository to handle data, document research Methods, and facilitate both internal communication and collaboration with other sites. This evolving knowledge repository consists of both public and internal (restricted access) pages on the World Wide Web (WWW). Information can be accessed using an indexed logical format or queried to allow entry at user-defined points. The main topics are: Concept Dictionary, Research Definitions, Meta-Index, and Glossary. The Concept Dictionary operationalizes concepts used in health research using administrative data, outlining the creation of complex variables. Research Definitions specify the codes for common surgical procedures, tests, and diagnoses. The Meta-Index organizes concepts and definitions according to the Medical Sub-Heading (MeSH) system developed by the National Library of Medicine. The Glossary facilitates navigation through the research terms and abbreviations in the knowledge repository. An Education Resources heading presents a web-based graduate course using substantial amounts of material in the Concept Dictionary, a lecture in the Epidemiology Supercourse, and material for Manitoba's Regional Health Authorities. Confidential information (including Data Dictionaries) is available on the Centre's internal website. Use of the public pages has increased dramatically since January 1998, with almost 6,000 page hits from 250 different hosts in May 1999. More recently, the number of page hits has averaged around 4,000 per month, while the number of unique hosts has climbed to around 400. This knowledge repository promotes standardization and increases efficiency by placing concepts and associated programming in the Centre's collective memory. Collaboration and project management are facilitated.

Organizing the Present, Looking to the Future: An Online Knowledge Repository to Facilitate Collaboration

PubMed Central

Burchill, Charles; Fergusson, Patricia; Jebamani, Laurel; Turner, Ken; Dueck, Stephen

2000-01-01

Background Comprehensive data available in the Canadian province of Manitoba since 1970 have aided study of the interaction between population health, health care utilization, and structural features of the health care system. Given a complex linked database and many ongoing projects, better organization of available epidemiological, institutional, and technical information was needed. Objective The Manitoba Centre for Health Policy and Evaluation wished to develop a knowledge repository to handle data, document research methods, and facilitate both internal communication and collaboration with other sites. Methods This evolving knowledge repository consists of both public and internal (restricted access) pages on the World Wide Web (WWW). Information can be accessed using an indexed logical format or queried to allow entry at user-defined points. The main topics are: Concept Dictionary, Research Definitions, Meta-Index, and Glossary. The Concept Dictionary operationalizes concepts used in health research using administrative data, outlining the creation of complex variables. Research Definitions specify the codes for common surgical procedures, tests, and diagnoses. The Meta-Index organizes concepts and definitions according to the Medical Sub-Heading (MeSH) system developed by the National Library of Medicine. The Glossary facilitates navigation through the research terms and abbreviations in the knowledge repository. An Education Resources heading presents a web-based graduate course using substantial amounts of material in the Concept Dictionary, a lecture in the Epidemiology Supercourse, and material for Manitoba's Regional Health Authorities. Confidential information (including Data Dictionaries) is available on the Centre's internal website. Results Use of the public pages has increased dramatically since January 1998, with almost 6,000 page hits from 250 different hosts in May 1999. More recently, the number of page hits has averaged around 4,000 per month, while the number of unique hosts has climbed to around 400. Conclusions This knowledge repository promotes standardization and increases efficiency by placing concepts and associated programming in the Centre's collective memory. Collaboration and project management are facilitated. PMID:11720929

Embedded sparse representation of fMRI data via group-wise dictionary optimization

NASA Astrophysics Data System (ADS)

Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

2016-03-01

Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

Validation of an Improved Computer-Assisted Technique for Mining Free-Text Electronic Medical Records.

PubMed

Duz, Marco; Marshall, John F; Parkin, Tim

2017-06-29

The use of electronic medical records (EMRs) offers opportunity for clinical epidemiological research. With large EMR databases, automated analysis processes are necessary but require thorough validation before they can be routinely used. The aim of this study was to validate a computer-assisted technique using commercially available content analysis software (SimStat-WordStat v.6 (SS/WS), Provalis Research) for mining free-text EMRs. The dataset used for the validation process included life-long EMRs from 335 patients (17,563 rows of data), selected at random from a larger dataset (141,543 patients, ~2.6 million rows of data) and obtained from 10 equine veterinary practices in the United Kingdom. The ability of the computer-assisted technique to detect rows of data (cases) of colic, renal failure, right dorsal colitis, and non-steroidal anti-inflammatory drug (NSAID) use in the population was compared with manual classification. The first step of the computer-assisted analysis process was the definition of inclusion dictionaries to identify cases, including terms identifying a condition of interest. Words in inclusion dictionaries were selected from the list of all words in the dataset obtained in SS/WS. The second step consisted of defining an exclusion dictionary, including combinations of words to remove cases erroneously classified by the inclusion dictionary alone. The third step was the definition of a reinclusion dictionary to reinclude cases that had been erroneously classified by the exclusion dictionary. Finally, cases obtained by the exclusion dictionary were removed from cases obtained by the inclusion dictionary, and cases from the reinclusion dictionary were subsequently reincluded using Rv3.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Manual analysis was performed as a separate process by a single experienced clinician reading through the dataset once and classifying each row of data based on the interpretation of the free-text notes. Validation was performed by comparison of the computer-assisted method with manual analysis, which was used as the gold standard. Sensitivity, specificity, negative predictive values (NPVs), positive predictive values (PPVs), and F values of the computer-assisted process were calculated by comparing them with the manual classification. Lowest sensitivity, specificity, PPVs, NPVs, and F values were 99.82% (1128/1130), 99.88% (16410/16429), 94.6% (223/239), 100.00% (16410/16412), and 99.0% (100×2×0.983×0.998/[0.983+0.998]), respectively. The computer-assisted process required few seconds to run, although an estimated 30 h were required for dictionary creation. Manual classification required approximately 80 man-hours. The critical step in this work is the creation of accurate and inclusive dictionaries to ensure that no potential cases are missed. It is significantly easier to remove false positive terms from a SS/WS selected subset of a large database than search that original database for potential false negatives. The benefits of using this method are proportional to the size of the dataset to be analyzed. ©Marco Duz, John F Marshall, Tim Parkin. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 29.06.2017.

Validation of an Improved Computer-Assisted Technique for Mining Free-Text Electronic Medical Records

PubMed Central

Marshall, John F; Parkin, Tim

2017-01-01

Background The use of electronic medical records (EMRs) offers opportunity for clinical epidemiological research. With large EMR databases, automated analysis processes are necessary but require thorough validation before they can be routinely used. Objective The aim of this study was to validate a computer-assisted technique using commercially available content analysis software (SimStat-WordStat v.6 (SS/WS), Provalis Research) for mining free-text EMRs. Methods The dataset used for the validation process included life-long EMRs from 335 patients (17,563 rows of data), selected at random from a larger dataset (141,543 patients, ~2.6 million rows of data) and obtained from 10 equine veterinary practices in the United Kingdom. The ability of the computer-assisted technique to detect rows of data (cases) of colic, renal failure, right dorsal colitis, and non-steroidal anti-inflammatory drug (NSAID) use in the population was compared with manual classification. The first step of the computer-assisted analysis process was the definition of inclusion dictionaries to identify cases, including terms identifying a condition of interest. Words in inclusion dictionaries were selected from the list of all words in the dataset obtained in SS/WS. The second step consisted of defining an exclusion dictionary, including combinations of words to remove cases erroneously classified by the inclusion dictionary alone. The third step was the definition of a reinclusion dictionary to reinclude cases that had been erroneously classified by the exclusion dictionary. Finally, cases obtained by the exclusion dictionary were removed from cases obtained by the inclusion dictionary, and cases from the reinclusion dictionary were subsequently reincluded using Rv3.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Manual analysis was performed as a separate process by a single experienced clinician reading through the dataset once and classifying each row of data based on the interpretation of the free-text notes. Validation was performed by comparison of the computer-assisted method with manual analysis, which was used as the gold standard. Sensitivity, specificity, negative predictive values (NPVs), positive predictive values (PPVs), and F values of the computer-assisted process were calculated by comparing them with the manual classification. Results Lowest sensitivity, specificity, PPVs, NPVs, and F values were 99.82% (1128/1130), 99.88% (16410/16429), 94.6% (223/239), 100.00% (16410/16412), and 99.0% (100×2×0.983×0.998/[0.983+0.998]), respectively. The computer-assisted process required few seconds to run, although an estimated 30 h were required for dictionary creation. Manual classification required approximately 80 man-hours. Conclusions The critical step in this work is the creation of accurate and inclusive dictionaries to ensure that no potential cases are missed. It is significantly easier to remove false positive terms from a SS/WS selected subset of a large database than search that original database for potential false negatives. The benefits of using this method are proportional to the size of the dataset to be analyzed. PMID:28663163

Schema for Spacecraft-Command Dictionary

NASA Technical Reports Server (NTRS)

Laubach, Sharon; Garcia, Celina; Maxwell, Scott; Wright, Jesse

2008-01-01

An Extensible Markup Language (XML) schema was developed as a means of defining and describing a structure for capturing spacecraft command- definition and tracking information in a single location in a form readable by both engineers and software used to generate software for flight and ground systems. A structure defined within this schema is then used as the basis for creating an XML file that contains command definitions.

A Communications Strategy for Disaster Relief

DTIC Science & Technology

2015-03-01

there were “ pockets ” of cellular coverage in the immediate aftermath of the earthquake, thus enabling some critical life-saving SMS traffic.105 4...Accessed 30 October 2014. http://www.oxfam.org/en/haiti-earthquake-our-response. Oxford Learners Dictionary . “Definition of Wicked.” Oxford University...Press. Assessed 02 September 2014. http://www.oxfordlearnersdictionaries.com/ definition/ english /wicked_1. Pacific Disaster Center. “Disaster Response

High-Order Local Pooling and Encoding Gaussians Over a Dictionary of Gaussians.

PubMed

Li, Peihua; Zeng, Hui; Wang, Qilong; Shiu, Simon C K; Zhang, Lei

2017-07-01

Local pooling (LP) in configuration (feature) space proposed by Boureau et al. explicitly restricts similar features to be aggregated, which can preserve as much discriminative information as possible. At the time it appeared, this method combined with sparse coding achieved competitive classification results with only a small dictionary. However, its performance lags far behind the state-of-the-art results as only the zero-order information is exploited. Inspired by the success of high-order statistical information in existing advanced feature coding or pooling methods, we make an attempt to address the limitation of LP. To this end, we present a novel method called high-order LP (HO-LP) to leverage the information higher than the zero-order one. Our idea is intuitively simple: we compute the first- and second-order statistics per configuration bin and model them as a Gaussian. Accordingly, we employ a collection of Gaussians as visual words to represent the universal probability distribution of features from all classes. Our problem is naturally formulated as encoding Gaussians over a dictionary of Gaussians as visual words. This problem, however, is challenging since the space of Gaussians is not a Euclidean space but forms a Riemannian manifold. We address this challenge by mapping Gaussians into the Euclidean space, which enables us to perform coding with common Euclidean operations rather than complex and often expensive Riemannian operations. Our HO-LP preserves the advantages of the original LP: pooling only similar features and using a small dictionary. Meanwhile, it achieves very promising performance on standard benchmarks, with either conventional, hand-engineered features or deep learning-based features.

Dictionary Indexing of Electron Channeling Patterns.

PubMed

Singh, Saransh; De Graef, Marc

2017-02-01

The dictionary-based approach to the indexing of diffraction patterns is applied to electron channeling patterns (ECPs). The main ingredients of the dictionary method are introduced, including the generalized forward projector (GFP), the relevant detector model, and a scheme to uniformly sample orientation space using the "cubochoric" representation. The GFP is used to compute an ECP "master" pattern. Derivative free optimization algorithms, including the Nelder-Mead simplex and the bound optimization by quadratic approximation are used to determine the correct detector parameters and to refine the orientation obtained from the dictionary approach. The indexing method is applied to poly-silicon and shows excellent agreement with the calibrated values. Finally, it is shown that the method results in a mean disorientation error of 1.0° with 0.5° SD for a range of detector parameters.

Sensitivity computation of the ell1 minimization problem and its application to dictionary design of ill-posed problems

NASA Astrophysics Data System (ADS)

Horesh, L.; Haber, E.

2009-09-01

The ell1 minimization problem has been studied extensively in the past few years. Recently, there has been a growing interest in its application for inverse problems. Most studies have concentrated in devising ways for sparse representation of a solution using a given prototype dictionary. Very few studies have addressed the more challenging problem of optimal dictionary construction, and even these were primarily devoted to the simplistic sparse coding application. In this paper, sensitivity analysis of the inverse solution with respect to the dictionary is presented. This analysis reveals some of the salient features and intrinsic difficulties which are associated with the dictionary design problem. Equipped with these insights, we propose an optimization strategy that alleviates these hurdles while utilizing the derived sensitivity relations for the design of a locally optimal dictionary. Our optimality criterion is based on local minimization of the Bayesian risk, given a set of training models. We present a mathematical formulation and an algorithmic framework to achieve this goal. The proposed framework offers the design of dictionaries for inverse problems that incorporate non-trivial, non-injective observation operators, where the data and the recovered parameters may reside in different spaces. We test our algorithm and show that it yields improved dictionaries for a diverse set of inverse problems in geophysics and medical imaging.

Target Classification of Canonical Scatterers Using Classical Estimation and Dictionary Based Techniques

DTIC Science & Technology

2012-03-22

shapes tested , when the objective parameter set was confined to a dictionary’s de - fined parameter space. These physical characteristics included...8 2.3 Hypothesis Testing and Detection Theory . . . . . . . . . . . . . . . 8 2.4 3-D SAR Scattering Models...basis pursuit de -noising (BPDN) algorithm is chosen to perform extraction due to inherent efficiency and error tolerance. Multiple shape dictionaries

75 FR 63888 - Occupational Information Development Advisory Panel Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-18

... independent advice and recommendations on plans and activities to replace the Dictionary of Occupational...: Medical and vocational analysis of disability claims; occupational analysis, including definitions... to our disability programs and improve the medical-vocational adjudication policies and processes...

Definitions of idioms in preadolescents, adolescents, and adults.

PubMed

Chan, Yen-Ling; Marinellie, Sally A

2008-01-01

The purpose of this study was to expand the current literature on word definitions by focusing on definitions of idioms provided by several age groups. Preadolescents, young adolescents, older adolescents, and adults wrote definitions for 10 frequently used idioms and also rated their familiarity with the idiomatic expressions. Participants' definitions were scored based on the degree to which their definitions reflected use of critical elements (determined by a standard dictionary of idioms), use of examples or related/associated concepts, and errors. Significant age differences were found in both idiom familiarity and idiom definition tasks: both idiom familiarity and definitional skill improved with age. In addition, we found a positive correlation between idiom familiarity and idiom definition. Results are discussed with respect to age-related changes in definitional response types and understanding of figurative language.

SciReader enables reading of medical content with instantaneous definitions.

PubMed

Gradie, Patrick R; Litster, Megan; Thomas, Rinu; Vyas, Jay; Schiller, Martin R

2011-01-25

A major problem patients encounter when reading about health related issues is document interpretation, which limits reading comprehension and therefore negatively impacts health care. Currently, searching for medical definitions from an external source is time consuming, distracting, and negatively impacts reading comprehension and memory of the material. SciReader was built as a Java application with a Flex-based front-end client. The dictionary used by SciReader was built by consolidating data from several sources and generating new definitions with a standardized syntax. The application was evaluated by measuring the percentage of words defined in different documents. A survey was used to test the perceived effect of SciReader on reading time and comprehension. We present SciReader, a web-application that simplifies document interpretation by allowing users to instantaneously view medical, English, and scientific definitions as they read any document. This tool reveals the definitions of any selected word in a small frame at the top of the application. SciReader relies on a dictionary of ~750,000 unique Biomedical and English word definitions. Evaluation of the application shows that it maps ~98% of words in several different types of documents and that most users tested in a survey indicate that the application decreases reading time and increases comprehension. SciReader is a web application useful for reading medical and scientific documents. The program makes jargon-laden content more accessible to patients, educators, health care professionals, and the general public.

A Standard-Driven Data Dictionary for Data Harmonization of Heterogeneous Datasets in Urban Geological Information Systems

NASA Astrophysics Data System (ADS)

Liu, G.; Wu, C.; Li, X.; Song, P.

2013-12-01

The 3D urban geological information system has been a major part of the national urban geological survey project of China Geological Survey in recent years. Large amount of multi-source and multi-subject data are to be stored in the urban geological databases. There are various models and vocabularies drafted and applied by industrial companies in urban geological data. The issues such as duplicate and ambiguous definition of terms and different coding structure increase the difficulty of information sharing and data integration. To solve this problem, we proposed a national standard-driven information classification and coding method to effectively store and integrate urban geological data, and we applied the data dictionary technology to achieve structural and standard data storage. The overall purpose of this work is to set up a common data platform to provide information sharing service. Research progresses are as follows: (1) A unified classification and coding method for multi-source data based on national standards. Underlying national standards include GB 9649-88 for geology and GB/T 13923-2006 for geography. Current industrial models are compared with national standards to build a mapping table. The attributes of various urban geological data entity models are reduced to several categories according to their application phases and domains. Then a logical data model is set up as a standard format to design data file structures for a relational database. (2) A multi-level data dictionary for data standardization constraint. Three levels of data dictionary are designed: model data dictionary is used to manage system database files and enhance maintenance of the whole database system; attribute dictionary organizes fields used in database tables; term and code dictionary is applied to provide a standard for urban information system by adopting appropriate classification and coding methods; comprehensive data dictionary manages system operation and security. (3) An extension to system data management function based on data dictionary. Data item constraint input function is making use of the standard term and code dictionary to get standard input result. Attribute dictionary organizes all the fields of an urban geological information database to ensure the consistency of term use for fields. Model dictionary is used to generate a database operation interface automatically with standard semantic content via term and code dictionary. The above method and technology have been applied to the construction of Fuzhou Urban Geological Information System, South-East China with satisfactory results.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

PubMed

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

Retrieving definitional content for ontology development.

PubMed

Smith, L; Wilbur, W J

2004-12-01

Ontology construction requires an understanding of the meaning and usage of its encoded concepts. While definitions found in dictionaries or glossaries may be adequate for many concepts, the actual usage in expert writing could be a better source of information for many others. The goal of this paper is to describe an automated procedure for finding definitional content in expert writing. The approach uses machine learning on phrasal features to learn when sentences in a book contain definitional content, as determined by their similarity to glossary definitions provided in the same book. The end result is not a concise definition of a given concept, but for each sentence, a predicted probability that it contains information relevant to a definition. The approach is evaluated automatically for terms with explicit definitions, and manually for terms with no available definition.

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

PubMed

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Readability versus Leveling.

ERIC Educational Resources Information Center

Fry, Edward

2002-01-01

Shows some similarities and differences between readability formulas and leveling procedures and reports some current large-scale uses of readability formulas. Presents a dictionary definition of readability and leveling, and a history and background of readability and leveling. Discusses what goes into determining readability and leveling scores.…

The "Instructional Leader" Must Go.

ERIC Educational Resources Information Center

Evans, Dennis L.

Using some dictionary definitions, one might easily infer that supervision of teaching is a managerial/administrative function closely related to evaluation and control, implying hierarchical connotations. However, Guthrie and Reed (1991) describe teacher supervision as "a function of leadership concerned with improving, enhancing, and reinforcing…

A Robust Shape Reconstruction Method for Facial Feature Point Detection.

PubMed

Tan, Shuqiu; Chen, Dongyi; Guo, Chenggang; Huang, Zhiqi

2017-01-01

Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

Analysis of the Concept Continuing Education in Nursing Education

ERIC Educational Resources Information Center

Agyepong, Edith Biamah; Okyere, Enoch Danso

2018-01-01

The term continuing education is extensively used throughout nursing education literature. This paper sought to re-examine the concept 'continuing education' for its meaning, relevance and appropriateness of application. The authors examined the definitions of continuing education from dictionaries, thesauruses, and current nursing education…

Turning Equations Into Stories: Using "Equation Dictionaries" in an Introductory Geophysics Class

NASA Astrophysics Data System (ADS)

Caplan-Auerbach, J.

2008-12-01

To students with math fear, equations can be intimidating and overwhelming. This discomfort is reflected in some of the frequent questions heard in introductory geophysics: "which equation should I use?" and "does T stand for travel time or period?" Questions such as these indicate that many students view equations as a series of variables and operators rather than as a representation of a physical process. To solve a problem they may simply look for an equation with the correct variables and assume that it meets their needs, rather than selecting an equation that represents the appropriate physical process. These issues can be addressed by encouraging students to think of equations as stories, and to describe them in prose. This is the goal of the Equation Dictionary project, used in Western Washington University's introductory geophysics course. Throughout the course, students create personal equation dictionaries, adding an entry each time an equation is introduced. Entries consist of (a) the equation itself, (b) a brief description of equation variables, (c) a prose description of the physical process described by the equation, and (d) any additional notes that help them understand the equation. Thus, rather than simply writing down the equations for the velocity of body waves, a student might write "The speed of a seismic body wave is controlled by the material properties of the medium through which it passes." In a study of gravity a student might note that the International Gravity Formula describes "the expected value of g at a given latitude, correcting for Earth's shape and rotation." In writing these definitions students learn that equations are simplified descriptions of physical processes, and that understanding the process is more useful than memorizing a sequence of variables. Dictionaries also serve as formula sheets for exams, which encourages students to write definitions that are meaningful to them, and to organize their thoughts clearly. Finally, instructor review of the dictionaries is an excellent way to identify student misconceptions and learn how well they understand derivations and lectures.

Satellite Power Systems (SPS) concept definition study. Volume 2, part 2: System engineering. [cost and programmatics

NASA Technical Reports Server (NTRS)

Hanley, G. M.

1980-01-01

The latest technical and programmatic developments are considered as well as expansions of the Rockwell SPS cost model covering each phase of the program through the year 2030. Comparative cost/economic analyses cover elements of the satellite, construction system, space transportation vehicles and operations, and the ground receiving station. System plans to define time phased costs and planning requirements that support major milestones through the year 2000. A special analysis is included on natural resources required to build the SPS reference configuration. An appendix contains the SPS Work Breakdown Structure and dictionary along with detail cost data sheet on each system and main element of the program. Over 200 line items address DDT&E, theoretical first unit, investment cost per satellite, and operations charges for replacement capital and normal operations and maintenance costs.

Group-sparse representation with dictionary learning for medical image denoising and fusion.

PubMed

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

Satellite power systems (SPS) concept definition study. Volume 7: SPS program plan and economic analysis, appendixes

NASA Technical Reports Server (NTRS)

Hanley, G.

1978-01-01

Three appendixes in support of Volume 7 are contained in this document. The three appendixes are: (1) Satellite Power System Work Breakdown Structure Dictionary; (2) SPS cost Estimating Relationships; and (3) Financial and Operational Concept. Other volumes of the final report that provide additional detail are: Executive Summary; SPS Systems Requirements; SPS Concept Evolution; SPS Point Design Definition; Transportation and Operations Analysis; and SPS Technology Requirements and Verification.

Stewardship

ERIC Educational Resources Information Center

Canada, Benjamin O.

2005-01-01

In this article, the author found himself particularly drawn to a book he received in the mail--"Stewardship: Choosing Service Over Self-Interest" by Peter Block. Although the dictionary definition of steward is "one who manages another's property, finances or other affairs," from his vantage point as the first African-American superintendent in…

Aleph to Zloty.

ERIC Educational Resources Information Center

Spradling, Charles

1984-01-01

First, third, and fifth graders master advanced vocabulary through a principal's "word for the day" strategy. Volunteer students look up the word in the dictionary, write the definition on the board, use it in a sentence, and create a poster. Retention is periodically tested and prizes awarded for top performance. (MJL)

A hospital-wide clinical findings dictionary based on an extension of the International Classification of Diseases (ICD).

PubMed

Bréant, C; Borst, F; Campi, D; Griesser, V; Momjian, S

1999-01-01

The use of a controlled vocabulary set in a hospital-wide clinical information system is of crucial importance for many departmental database systems to communicate and exchange information. In the absence of an internationally recognized clinical controlled vocabulary set, a new extension of the International statistical Classification of Diseases (ICD) is proposed. It expands the scope of the standard ICD beyond diagnosis and procedures to clinical terminology. In addition, the common Clinical Findings Dictionary (CFD) further records the definition of clinical entities. The construction of the vocabulary set and the CFD is incremental and manual. Tools have been implemented to facilitate the tasks of defining/maintaining/publishing dictionary versions. The design of database applications in the integrated clinical information system is driven by the CFD which is part of the Medical Questionnaire Designer tool. Several integrated clinical database applications in the field of diabetes and neuro-surgery have been developed at the HUG.

A hospital-wide clinical findings dictionary based on an extension of the International Classification of Diseases (ICD).

PubMed Central

Bréant, C.; Borst, F.; Campi, D.; Griesser, V.; Momjian, S.

1999-01-01

The use of a controlled vocabulary set in a hospital-wide clinical information system is of crucial importance for many departmental database systems to communicate and exchange information. In the absence of an internationally recognized clinical controlled vocabulary set, a new extension of the International statistical Classification of Diseases (ICD) is proposed. It expands the scope of the standard ICD beyond diagnosis and procedures to clinical terminology. In addition, the common Clinical Findings Dictionary (CFD) further records the definition of clinical entities. The construction of the vocabulary set and the CFD is incremental and manual. Tools have been implemented to facilitate the tasks of defining/maintaining/publishing dictionary versions. The design of database applications in the integrated clinical information system is driven by the CFD which is part of the Medical Questionnaire Designer tool. Several integrated clinical database applications in the field of diabetes and neuro-surgery have been developed at the HUG. Images Figure 1 PMID:10566451

Adapting irrigated agriculture to drought in the San Joaquin Valley of California

USDA-ARS?s Scientific Manuscript database

Webster’s dictionary defines drought as a continuous state of dryness but does not identify a cause for that dryness, just the existence. Irrigated agriculture is in a continuous state of drought by definition, simply because water is supplied by stored surface or groundwater supplies. This results ...

Commentary: Communications Doesn't Define PR, It Diminishes It.

ERIC Educational Resources Information Center

Budd, John, Jr.

1995-01-01

Gives the dictionary definition of "communications," and then suggests that communications is the last act in the process of public relations. Presents hypothetical situations to show that PR is the final implementation step in a management process rather than just "communications." Argues that some companies, however, use…

The Explicit Siphon

ERIC Educational Resources Information Center

Binder, P.-M.; Richert, A.

2011-01-01

A series of papers have recently addressed the mechanism by which a siphon works. While all this started as an effort to clarify words--namely, dictionary definitions--the authors feel that words, along with the misguided use of physical concepts, are currently contributing to considerable confusion and casuistry on this subject. They wish to make…

Lexicography and Mathematics Learning: A Case Study of "Variable."

ERIC Educational Resources Information Center

Frawley, William

1992-01-01

Lexicography is shown to offer some useful new tools to researchers in mathematics education. The paper examines the relationship between the sublanguage of mathematics and the acquisition of mathematical knowledge, and also the use of definitions in research and curriculum design. An Explanatory Combinatorial Dictionary is advocated for improving…

Terminologie de Base de la Documentation. (Basic Terminology of Documentation).

ERIC Educational Resources Information Center

Commission des Communautes Europeennes (Luxembourg). Bureau de Terminologie.

This glossary is designed to aid non-specialists whose activities require that they have some familiarity with the terminology of the modern methods of documentation. Definitions have been assembled from various dictionaries, manuals, etc., with particular attention being given to the publications of UNESCO and the International Standards…

Forum: The Lecture and Student Learning. The Lecture's Absent Audience

ERIC Educational Resources Information Center

Sciullo, Nick J.

2017-01-01

According to the "Oxford English Dictionary" ("OED"), the noun "lecture" dates from the 14th century and means the "action of reading, perusal. Also, that which is read or perused." This definition, while accurate and resonates today in many college classrooms, ignores a key feature of any lecture. The…

Optimism and Well-Being

ERIC Educational Resources Information Center

Reivich, Karen

2010-01-01

Dictionary definitions of optimism encompass two related concepts. The first of these is a hopeful disposition or a conviction that good will ultimately prevail. The second, broader conception of optimism refers to the belief, or the inclination to believe, that the world is the best of all possible worlds. In psychological research, optimism has…

Indigenous Research Capability in Aotearoa

ERIC Educational Resources Information Center

Ormond, Adreanne; Williams, Les R. Tumoana

2013-01-01

This article begins by considering the general nature of capability, from some dictionary meanings, then extends to theoretical perspectives related to the capability approach. As a consequence, we arrive at an operational definition that emphasises the ability to solve problems in a systematic way that brings transformation. In these terms,…

Low rank approximation methods for MR fingerprinting with large scale dictionaries.

PubMed

Yang, Mingrui; Ma, Dan; Jiang, Yun; Hamilton, Jesse; Seiberlich, Nicole; Griswold, Mark A; McGivney, Debra

2018-04-01

This work proposes new low rank approximation approaches with significant memory savings for large scale MR fingerprinting (MRF) problems. We introduce a compressed MRF with randomized singular value decomposition method to significantly reduce the memory requirement for calculating a low rank approximation of large sized MRF dictionaries. We further relax this requirement by exploiting the structures of MRF dictionaries in the randomized singular value decomposition space and fitting them to low-degree polynomials to generate high resolution MRF parameter maps. In vivo 1.5T and 3T brain scan data are used to validate the approaches. T 1 , T 2 , and off-resonance maps are in good agreement with that of the standard MRF approach. Moreover, the memory savings is up to 1000 times for the MRF-fast imaging with steady-state precession sequence and more than 15 times for the MRF-balanced, steady-state free precession sequence. The proposed compressed MRF with randomized singular value decomposition and dictionary fitting methods are memory efficient low rank approximation methods, which can benefit the usage of MRF in clinical settings. They also have great potentials in large scale MRF problems, such as problems considering multi-component MRF parameters or high resolution in the parameter space. Magn Reson Med 79:2392-2400, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

D1-3: Marshfield Dictionary of Clinical and Translational Science (MD-CTS): An Online Reference for Clinical and Translational Science Terminology

PubMed Central

Finamore, Joe; Ray, William; Kadolph, Chris; Rastegar-Mojarad, Majid; Ye, Zhan; Jacqueline, Bohne; Tachinardi, Umberto; Mendonça, Eneida; Finnegan, Brian; Bartkowiak, Barbara; Weichelt, Bryan; Lin, Simon

2014-01-01

Background/Aims New terms are rapidly appearing in the literature and practice of clinical medicine and translational research. To catalog real-world usage of medical terms, we report the first construction of an online dictionary of clinical and translational medicinal terms, which are computationally generated in near real-time using a big data approach. This project is NIH CTSA-funded and developed by the Marshfield Clinic Research Foundation in conjunction with University of Wisconsin - Madison. Currently titled Marshfield Dictionary of Clinical and Translational Science (MD-CTS), this application is a Google-like word search tool. By entering a term into the search bar, MD-CTS will display that term’s definition, usage examples, contextual terms, related images, and ontological information. A prototype is available for public viewing at http://spellchecker.mfldclin.edu/. Methods We programmatically derived the lexicon for MD-CTS from scholarly communications by parsing through 15,156,745 MEDLINE abstracts and extracting all of the unique words found therein. We then ran this list through several filters in order to remove words that were not relevant for searching, such as common English words and numeric expressions. We then loaded the resulting 1,795,769 terms into SQL tables. Each term is cross-referenced with every occurrence in all abstracts in which it was found. Additional information is aggregated from Wiktionary, Bioportal, and Wikipedia in real-time and displayed on-screen. From this lexicon we created a supplemental dictionary resource (updated quarterly) to be used in Microsoft Office® products. Results We evaluated the utility of MD-CTS by creating a list of 100 words derived from recent clinical and translational medicine publications in the week of July 22, 2013. We then performed comparative searches for each term with Taber’s Cyclopedic Medical Dictionary, Stedman’s Medical Dictionary, Dorland’s Illustrated Medical Dictionary, Medical Subject Headings (MeSH), and MD-CTS. We compared our supplemental dictionary resource to OpenMedSpell for effectiveness in accuracy of term recognition. Conclusions In summary, we developed an online mobile and desktop reference, which comprehensively integrates Wiktionary (term information), Bioportal (ontological information), Wikipedia (related images), and Medline abstract information (term usage) for scientists and clinicians to browse in real-time. We also created a supplemental dictionary resource to be used in Microsoft Office® products.

Dictionary Pair Learning on Grassmann Manifolds for Image Denoising.

PubMed

Zeng, Xianhua; Bian, Wei; Liu, Wei; Shen, Jialie; Tao, Dacheng

2015-11-01

Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary pair (i.e., the left and right dictionaries) by employing a subspace partition technique on the Grassmann manifold, wherein the refined dictionary pair is obtained through a sub-dictionary pair merging. The DPLG obtains a sparse representation by encoding each image patch only with the selected sub-dictionary pair. The non-zero elements of the sparse representation are further smoothed by the graph Laplacian operator to remove the noise. Consequently, the DPLG algorithm not only preserves the inherent 2D geometric structure of natural images but also performs manifold smoothing in the 2D sparse coding space. We demonstrate that the DPLG algorithm also improves the structural SIMilarity values of the perceptual visual quality for denoised images using the experimental evaluations on the benchmark images and Berkeley segmentation data sets. Moreover, the DPLG also produces the competitive peak signal-to-noise ratio values from popular image denoising algorithms.

The ADAMS interactive interpreter

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

Rietscha, E.R.

1990-12-17

The ADAMS (Advanced DAta Management System) project is exploring next generation database technology. Database management does not follow the usual programming paradigm. Instead, the database dictionary provides an additional name space environment that should be interactively created and tested before writing application code. This document describes the implementation and operation of the ADAMS Interpreter, an interactive interface to the ADAMS data dictionary and runtime system. The Interpreter executes individual statements of the ADAMS Interface Language, providing a fast, interactive mechanism to define and access persistent databases. 5 refs.

Evolutionary space platform concept study. Volume 3: Programmatics for manned space platform concepts

NASA Technical Reports Server (NTRS)

1982-01-01

The programmatic data for the reference concept of the Manned Space Platform is presented. Details regarding work breakdown structure (WBS) and dictionary, the facilities and equipment required to produce the modules, the project schedule and logic diagram, a preliminary assessment of environmental impacts and details regarding the estimated costs for the reference concept are included. The proposed WBS which was developed to provide summary and system level segregation of the nonrecurring and recurring portions of the Manned Space Platform project is also included. The accompanying dictionary outlines the function and activities contained within each WBS element. The facility and equipment required to produce the various modules is discussed. Generally, required equipment is within the existing state of the art although the size of some of the items to be manufactured is a consideration. A preliminary manufacturing flow was also provided. The project schedules presented consist of the Master Project Summary Schedule, the Master Project Phasing Chart and the Logic Network.

TMDD & MS/ETMCC guide : standard for functional level traffic management data dictionary (TMDD) and message sets for external traffic management center communications

DOT National Transportation Integrated Search

2000-01-01

These draft standards are intended to work together to provide a high level of interoperability among regional and local traffic control centers. They provide consistent names, definitions and concepts similar to spelling and parts of speech to world...

Teachers' Views on Course Supervision Competencies of Secondary School Managers

ERIC Educational Resources Information Center

Bayram, Arslan

2016-01-01

The definition of supervision in the dictionary is "to look after", "to direct," "to watch over," and "to check." It is usually seen as a tool to manage the teacher. Understanding of supervision in education has shown a change and progress in line with approaches and theories regarding management. The…

In the River of Ordinary Courage

ERIC Educational Resources Information Center

Melvoin, Rick

2011-01-01

In society, courage gets associated with soldiers, police, firefighters--those men and women who risk their lives in ways that are public and visible and immediate. For school heads also, as a different dictionary definition puts it, courage is demonstrated through "strength in the face of pain or grief" and the ability to do something that…

Words Matter: A Semantic Differential Study of Recreation, Leisure, Play, Activity, and Sport

ERIC Educational Resources Information Center

Schlag, Paul A.; Yoder, Daniel G.; Sheng, Zhaohui

2015-01-01

Beyond the standard definitions found in the dictionary, words commonly used in the recreation field have subtle, yet powerful connotations of which senders and receivers of information may not be consciously aware. These words elicit different conscious and subconscious reactions that likely bear significant consequences for recreation agencies…

Power Extension Package (PEP) system definition extension, orbital service module systems analysis study. Volume 11: PEP, cost, schedules, and work breakdown structure dictionary

NASA Technical Reports Server (NTRS)

1979-01-01

Cost scheduling and funding data are presented for the reference design of the power extension package. Major schedule milestones are correlated with current Spacelab flight dates. Funding distributions provide for minimum expenditure during the first year of the project.

Complex Adaptive Systems Based Data Integration: Theory and Applications

ERIC Educational Resources Information Center

Rohn, Eliahu

2008-01-01

Data Definition Languages (DDLs) have been created and used to represent data in programming languages and in database dictionaries. This representation includes descriptions in the form of data fields and relations in the form of a hierarchy, with the common exception of relational databases where relations are flat. Network computing created an…

Czech Basic Course: Verb List.

ERIC Educational Resources Information Center

Stoner, William; Vit, Karel V.

This compilation of verbs, intended for students of the Defense Language Institute (DLI) Basic Course, provides brief definitions for each entry. No sentence examples are included. The text is intended to serve as a compact reference and study aid. Examples are selected from the Basic Course and the DLI Czech-English Dictionary. Entries are listed…

MD-CTS: An integrated terminology reference of clinical and translational medicine.

PubMed

Ray, Will; Finamore, Joe; Rastegar-Mojarad, Majid; Kadolph, Chris; Ye, Zhan; Bohne, Jacquie; Xu, Yin; Burish, Dan; Sondelski, Joshua; Easker, Melissa; Finnegan, Brian; Bartkowiak, Barbara; Smith, Catherine Arnott; Tachinardi, Umberto; Mendonca, Eneida A; Weichelt, Bryan; Lin, Simon M

2016-01-01

New vocabularies are rapidly evolving in the literature relative to the practice of clinical medicine and translational research. To provide integrated access to new terms, we developed a mobile and desktop online reference-Marshfield Dictionary of Clinical and Translational Science (MD-CTS). It is the first public resource that comprehensively integrates Wiktionary (word definition), BioPortal (ontology), Wiki (image reference), and Medline abstract (word usage) information. MD-CTS is accessible at http://spellchecker.mfldclin.edu/. The website provides a broadened capacity for the wider clinical and translational science community to keep pace with newly emerging scientific vocabulary. An initial evaluation using 63 randomly selected biomedical words suggests that online references generally provided better coverage (73%-95%) than paper-based dictionaries (57-71%).

Machine-Aided Indexing at NASA.

ERIC Educational Resources Information Center

Silvester, June P.; And Others

1994-01-01

Describes the National Aeronautics and Space Administration (NASA) Lexical Dictionary (NLD), a machine-aided indexing system used online at the NASA Center for AeroSpace Information (CASI). The functions of NLD system components are described in detail, and production and quality benefits resulting from machine-aided indexing at CASI are…

A Dictionary of Acquisition and Contracting Terms.

DTIC Science & Technology

1997-06-01

No Comment 0 (0 %) C_ Responses: The following comments were used to revise the definition: - Not necessarily binding; may be non-binding. (3) - I agree with your definition; however, if I’m not mistaken, there may be some instances wherein the arbitration decision is not binding. (4) 10 - I would consider deleting the word "most." While the ADR process is the current buzzword, the word "arbitration" has been around a lot longer and to a lot of folks extends to processes for handling issues of personnel matter, international contracting,

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

PubMed

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.

The Language Skill Change Project (LSCP): Background, Procedures, and Preliminary Findings

DTIC Science & Technology

1987-12-01

word in the dictionary so I can understand what I am reading. 49. I use flashcards (with the new word or phrase on one side and the definition or...mostly on a term paper rather than multiple choice tests. 6. I would rather watch a heated debate on a controversial topic than a popular music program

SUGGESTIONS FOR DEVELOPING INDEPENDENT WORD ATTACK IN READING, FOR USE IN BASIC INSTITUTE MEETINGS, GRADES THREE AND FOUR.

ERIC Educational Resources Information Center

REECE, THOMAS E.; AND OTHERS

A GUIDE FOR PLANNING SPECIFIC INSTRUCTION FOR DEVELOPING INDEPENDENT WORD ATTACK PRESENTS THE SKILLS NECESSARY FOR MASTERING SIGHT VOCABULARY, WORD RECOGNITION, AND THE USE OF THE DICTIONARY. SPECIFIC DEFINITIONS OF TERMS AND EXAMPLES OF TEACHING TECHNIQUES WITH THE SEQUENCE OF INSTRUCTION FOR THE DEVELOPMENT OF PHONETIC AND STRUCTURAL ANALYSIS…

Ethic's Askew: A Case Study of Ethics in an Educational Environment

ERIC Educational Resources Information Center

Shurden, Susan; Santandreu, Juan; Shurden, Mike

2010-01-01

For a formal definition of ethics, Webster's New World Dictionary (1995) defines the term as "the study of standards of conduct and moral judgment". Ethics is important to individuals because we are concerned with what leaders do and who they are--their conduct and character. "Conduct" is a word that implies behavior. Behavior…

Politics, Quality, and Passion: A Case Study of Reorganization in Higher Education. ASHE 1985 Annual Meeting Paper.

ERIC Educational Resources Information Center

Reid, John Y.

The reorganization of the College of Education and Allied Professions at the University of Toledo is discussed. The analysis is based on Baldridge's political model, Bacharach and Lawler's views of politics and power, Pirsig's concept of quality, and the Oxford English Dictionary definitions of "passion." To investigate the…

78 FR 76067 - Defense Federal Acquisition Regulation Supplement: Item Unique Identifier Update (DFARS Case 2011...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-16

... with the Air Transport Association Common Support Data Dictionary; and (ii) The encoded data elements... 211.274-2(a)(2) and (3) are revised to consolidate requirements. The definition of ``data matrix... Registry'' is added at 252.211-7003(c)(2). The phrase ``ECC200 data matrix specification'' is added at 252...

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1995-01-01

The Spatial Data Transfer Standard (SOTS) is a mechanism for the transfer of spatial data between dissimilar computer systems. The SOTS specifies exchange constructs, addressing formats, structure, and content for spatially referenced vector and raster (including gridded) data. SOTS components are a conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

Culture: Yes; Organization; No!

DTIC Science & Technology

1983-09-01

Posner. " Socialization Practices, Job Satisfaction and Commitment." Presentation, Western Division, Academy of Management, March, 1983. April, 1983... corporate culture by organizational scientists and managers in government and industry. A premise prevalent in current formulations Is that an...culture in organizational settings. COMPONENTS OF A DEFINITION What is culture? A dictionary defines culture as: the totality of socially transmitted

Coding of adverse events of suicidality in clinical study reports of duloxetine for the treatment of major depressive disorder: descriptive study.

PubMed

Maund, Emma; Tendal, Britta; Hróbjartsson, Asbjørn; Lundh, Andreas; Gøtzsche, Peter C

2014-06-04

To assess the effects of coding and coding conventions on summaries and tabulations of adverse events data on suicidality within clinical study reports. Systematic electronic search for adverse events of suicidality in tables, narratives, and listings of adverse events in individual patients within clinical study reports. Where possible, for each event we extracted the original term reported by the investigator, the term as coded by the medical coding dictionary, medical coding dictionary used, and the patient's trial identification number. Using the patient's trial identification number, we attempted to reconcile data on the same event between the different formats for presenting data on adverse events within the clinical study report. 9 randomised placebo controlled trials of duloxetine for major depressive disorder submitted to the European Medicines Agency for marketing approval. Clinical study reports obtained from the EMA in 2011. Six trials used the medical coding dictionary COSTART (Coding Symbols for a Thesaurus of Adverse Reaction Terms) and three used MedDRA (Medical Dictionary for Regulatory Activities). Suicides were clearly identifiable in all formats of adverse event data in clinical study reports. Suicide attempts presented in tables included both definitive and provisional diagnoses. Suicidal ideation and preparatory behaviour were obscured in some tables owing to the lack of specificity of the medical coding dictionary, especially COSTART. Furthermore, we found one event of suicidal ideation described in narrative text that was absent from tables and adverse event listings of individual patients. The reason for this is unclear, but may be due to the coding conventions used. Data on adverse events in tables in clinical study reports may not accurately represent the underlying patient data because of the medical dictionaries and coding conventions used. In clinical study reports, the listings of adverse events for individual patients and narratives of adverse events can provide additional information, including original investigator reported adverse event terms, which can enable a more accurate estimate of harms. © Maund et al 2014.

[Definition of ashi point from the view of linguistics].

PubMed

Jiang, Shan; Zhao, Jingsheng

2017-01-12

The definition of ashi point has not been unified yet till now. Likewise, the precise explanation on its connotation has always been an elusive question in acupuncture theory. By collecting diverse definitions on ashi point in the textbooks of Acupuncture and Moxibustion , dictionaries and term standards, several rational elements in definitions with consensus were screened. With the assistance of two important theories of cognitive linguistics, such as figure-ground theory and distance iconicity theory, the concept of ashi point was newly defined. Additiona-lly, on the base of the understanding on several similar terms such as "taking the painful site as acupoint", "responding point" and "reactive point", the semanteme analytic method was used to distinguish the difference among them so that the more profound explorations on acupuncture therapy are expounded.

Development of a data dictionary for the Strategies for Post Arrest Resuscitation Care (SPARC) network for post cardiac arrest research.

PubMed

Lin, Steve; Morrison, Laurie J; Brooks, Steven C

2011-04-01

The widely accepted Utstein style has standardized data collection and analysis in resuscitation and post resuscitation research. However, collection of many of these variables poses significant practical challenges. In addition, several important variables in post resuscitation research are missing. Our aim was to develop a comprehensive data dictionary and web-based data collection tool as part of the Strategies for Post Arrest Resuscitation Care (SPARC) Network project, which implemented a knowledge translation program for post cardiac arrest therapeutic hypothermia in 37 Ontario hospitals. A list of data variables was generated based on the current Utstein style, previous studies and expert opinion within our group of investigators. We developed a data dictionary by creating clear definitions and establishing abstraction instructions for each variable. The data dictionary was integrated into a web-based collection form allowing for interactive data entry. Two blinded investigators piloted the data collection tool, by performing a retrospective chart review. A total of 454 variables were included of which 400 were Utstein, 2 were adapted from existing studies and 52 were added to address missing elements. Kappa statistics for two outcome variables, survival to discharge and induction of therapeutic hypothermia were 0.86 and 0.64, respectively. This is the first attempt in the literature to develop a data dictionary as part of a standardized, pragmatic data collection tool for post cardiac arrest research patients. In addition, our dataset defined important variables that were previously missing. This data collection tool can serve as a reference for future trials in post cardiac arrest care. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

The role of local terminologies in electronic health records. The HEGP experience.

PubMed

Daniel-Le Bozec, Christel; Steichen, Olivier; Dart, Thierry; Jaulent, Marie-Christine

2007-01-01

Despite decades of work, there is no universally accepted standard medical terminology and no generally usable terminological tools have yet emerged. The local dictionary of concepts of the Georges Pompidou European Hospital (HEGP) is a Terminological System (TS) designed to support clinical data entry. It covers 93 data entry forms and contains definitions and synonyms of more than 5000 concepts, sometimes linked to reference terminologies such as ICD-10. In this article, we evaluate to which extend SNOMED CT could fully replace or rather be mapped to the local terminology system. We first describe the local dictionary of concepts of HEGP according to some published TS characterization framework. Then we discuss the specific role that a local terminology system plays with regards to reference terminologies.

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

PubMed

Qi, Jin; Yang, Zhiyong

2014-01-01

Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

Satellite Power Systems (SPS) concept definition study, exhibit C. Volume 2, part 2: System engineering, cost and programmatics, appendixes

NASA Technical Reports Server (NTRS)

Hanley, G. M.

1979-01-01

Appendixes for Volume 2 (Part 2) of a seven volume Satellite (SPS) report are presented. The document contains two appendixes. The first is a SPS work breakdown structure dictionary. The second gives SPS cost estimating relationships and contains the cost analyses and a description of cost elements that comprise the SPS program.

Computing Areas Using Green's Theorem and a Software Planimeter

ERIC Educational Resources Information Center

Davis, Paul; Raianu, Serban

2007-01-01

According to the Merriam-Webster dictionary, a planimeter is "an instrument for measuring the area of a plane figure by tracing its boundary line". Even without knowing how a planimeter works, it is clear from the definition that the idea behind it is that one can compute the area of a figure just by "walking" on the boundary. For someone who has…

Identifying missing dictionary entries with frequency-conserving context models.

PubMed

Williams, Jake Ryland; Clark, Eric M; Bagrow, James P; Danforth, Christopher M; Dodds, Peter Sheridan

2015-10-01

In an effort to better understand meaning from natural language texts, we explore methods aimed at organizing lexical objects into contexts. A number of these methods for organization fall into a family defined by word ordering. Unlike demographic or spatial partitions of data, these collocation models are of special importance for their universal applicability. While we are interested here in text and have framed our treatment appropriately, our work is potentially applicable to other areas of research (e.g., speech, genomics, and mobility patterns) where one has ordered categorical data (e.g., sounds, genes, and locations). Our approach focuses on the phrase (whether word or larger) as the primary meaning-bearing lexical unit and object of study. To do so, we employ our previously developed framework for generating word-conserving phrase-frequency data. Upon training our model with the Wiktionary, an extensive, online, collaborative, and open-source dictionary that contains over 100000 phrasal definitions, we develop highly effective filters for the identification of meaningful, missing phrase entries. With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique and expanding our knowledge of the defined English lexicon of phrases.

Reverse engineering genius: historiometric studies of superlative talent.

PubMed

Simonton, Dean Keith

2016-08-01

Although genius has been defined in the dictionary as requiring an IQ above 140, this definition depends on an arbitrary methodological decision made by Lewis Terman for his longitudinal study of more than 1500 intellectually gifted children, a study that occupies four of the five volumes of Genetic Studies of Genius. Yet, only the second volume, by Catharine Cox, studied bona fide geniuses, by applying historiometric methods to 301 highly eminent creators and leaders. After defining historiometric research, I examine the difference between historical genius and intellectual giftedness with respect to heterogeneous intellects, personality differences, and early development and show that the actual relation between IQ and genius is small and heavily contingent on domain-specific assessment, the operation of traits like persistence and openness to experience, and the impact of diversifying experiences, including both developmental adversity and subclinical psychopathology. Hence, the dictionary definition of "genius" has minimal, if any, justification. If, using historiometric methods, one works backward from recognized geniuses, such as those studied by Cox, one might not obtain the kind of sample that Terman obtained for his longitudinal study. The two methods produce two distinct subgroups of the larger population. © 2016 New York Academy of Sciences.

Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning.

PubMed

Jing, Xiao-Yuan; Zhu, Xiaoke; Wu, Fei; Hu, Ruimin; You, Xinge; Wang, Yunhong; Feng, Hui; Yang, Jing-Yu

2017-03-01

Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high resolution (HR), while probe images are usually low resolution (LR) in the identification scenarios with large variation of illumination, weather, or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD 2 L) approach for SR person re-identification task. With the HR and LR dictionary pair and mapping matrices learned from the features of HR and LR training images, SLD 2 L can convert the features of the LR probe images into HR features. To ensure that the converted features have favorable discriminative capability and the learned dictionaries can well characterize intrinsic feature spaces of the HR and LR images, we design a discriminant term and a low-rank regularization term for SLD 2 L. Moreover, considering that low resolution results in different degrees of loss for different types of visual appearance features, we propose a multi-view SLD 2 L (MVSLD 2 L) approach, which can learn the type-specific dictionary pair and mappings for each type of feature. Experimental results on multiple publicly available data sets demonstrate the effectiveness of our proposed approaches for the SR person re-identification task.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Where love flies free: women, home, and writing in Cook County Jail.

PubMed

Stanford, Ann Folwell

2005-01-01

Several definitions of "home," drawn from dozens provided by the Oxford Dictionary of the English Language, underscore how a large urban county jail becomes many forms of home for the women detainees there. Drawing on the women's poetry and the mechanics of creative writing workshops facilitated by the author for the last seven years at Cook County Jail, this essay describes some of the realities of the criminal (in)justice system and how the women's writing becomes a way of writing against the grain of official discourse, thus altering certain definitions of this "home."

Developing a data dictionary for the irish nursing minimum dataset.

PubMed

Henry, Pamela; Mac Neela, Pádraig; Clinton, Gerard; Scott, Anne; Treacy, Pearl; Butler, Michelle; Hyde, Abbey; Morris, Roisin; Irving, Kate; Byrne, Anne

2006-01-01

One of the challenges in health care in Ireland is the relatively slow acceptance of standardised clinical information systems. Yet the national Irish health reform programme indicates that an Electronic Health Care Record (EHCR) will be implemented on a phased basis. [3-5]. While nursing has a key role in ensuring the quality and comparability of health information, the so- called 'invisibility' of some nursing activities makes this a challenging aim to achieve [3-5]. Any integrated health care system requires the adoption of uniform standards for electronic data exchange [1-2]. One of the pre-requisites for uniform standards is the composition of a data dictionary. Inadequate definition of data elements in a particular dataset hinders the development of an integrated data depository or electronic health care record (EHCR). This paper outlines how work on the data dictionary for the Irish Nursing Minimum Dataset (INMDS) has addressed this issue. Data set elements were devised on the basis of a large scale empirical research programme. ISO 18104, the reference terminology for nursing [6], was used to cross-map the data set elements with semantic domains, categories and links and data set items were dissected.

Characteristics of health interventions: a systematic analysis of the Austrian Procedure Catalogue.

PubMed

Neururer, Sabrina B; Pfeiffer, Karl-Peter

2012-01-01

The Austrian Procedure Catalogue contains 1,500 codes for health interventions used for performance-oriented hospital financing in Austria. It offers a multiaxial taxonomy. The aim of this study is to identify characteristics of medical procedures. Therefore a definition analysis followed by a typological analysis was conducted. Search strings were generated out of code descriptions regarding the heart, large vessels and cardiovascular system. Their definitions were looked up in the Pschyrembel Clinical Dictionary and documented. Out of these definitions, types which represent characteristics of health interventions were abstracted. The three axes of the Austrian Procedure Catalogue were approved as well as new, relevant information identified. The results are the foundation of a further enhancement of the Austrian Procedure Catalogue.

Error analysis of the crystal orientations obtained by the dictionary approach to EBSD indexing.

PubMed

Ram, Farangis; Wright, Stuart; Singh, Saransh; De Graef, Marc

2017-10-01

The efficacy of the dictionary approach to Electron Back-Scatter Diffraction (EBSD) indexing was evaluated through the analysis of the error in the retrieved crystal orientations. EBSPs simulated by the Callahan-De Graef forward model were used for this purpose. Patterns were noised, distorted, and binned prior to dictionary indexing. Patterns with a high level of noise, with optical distortions, and with a 25 × 25 pixel size, when the error in projection center was 0.7% of the pattern width and the error in specimen tilt was 0.8°, were indexed with a 0.8° mean error in orientation. The same patterns, but 60 × 60 pixel in size, were indexed by the standard 2D Hough transform based approach with almost the same orientation accuracy. Optimal detection parameters in the Hough space were obtained by minimizing the orientation error. It was shown that if the error in detector geometry can be reduced to 0.1% in projection center and 0.1° in specimen tilt, the dictionary approach can retrieve a crystal orientation with a 0.2° accuracy. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of the system of reactor thermophysical data on the basis of ontological modelling

NASA Astrophysics Data System (ADS)

Chusov, I. A.; Kirillov, P. L.; Bogoslovskaya, G. P.; Yunusov, L. K.; Obysov, N. A.; Novikov, G. E.; Pronyaev, V. G.; Erkimbaev, A. O.; Zitserman, V. Yu; Kobzev, G. A.; Trachtengerts, M. S.; Fokin, L. R.

2017-11-01

Compilation and processing of the thermophysical data was always an important task for the nuclear industry. The difficulties of the present stage of this activity are explained by sharp increase of the data volume and the number of new materials, as well as by the increased requirements to the reliability of the data used in the nuclear industry. General trend in the fields with predominantly orientation at the work with data (material science, chemistry and others) consists in the transition to a common infrastructure with integration of separate databases, Web-portals and other resources. This infrastructure provides the interoperability, the procedures of the data exchange, storage and dissemination. Key elements of this infrastructure is a domain-specific ontology, which provides a single information model and dictionary for semantic definitions. Formalizing the subject area, the ontology adapts the definitions for the different database schemes and provides the integration of heterogeneous data. The important property to be inherent for ontologies is a possibility of permanent expanding of new definitions, e.g. list of materials and properties. The expansion of the thermophysical data ontology at the reactor materials includes the creation of taxonomic dictionaries for thermophysical properties; the models for data presentation and their uncertainties; the inclusion along with the parameters of the state, some additional factors, such as the material porosity, the burnup rate, the irradiation rate and others; axiomatics of the properties applicable to the given class of materials.

106-17 Telemetry Standards Chapter 1

DTIC Science & Technology

2017-07-01

Telemetry Standards , RCC Standard 106-17 Chapter 1, July 2017 1-1 CHAPTER 1 Introduction The Telemetry Standards address the here-to-date...generally devoted to a different element of the telemetry system or process . Chapters 21 through 28 address the topic of network telemetry. These...Commonly used terms are defined in standard reference glossaries and dictionaries. Definitions of terms with special applications are included when

Comparing User-Assisted and Automatic Query Translation

DTIC Science & Technology

2005-01-01

do their strategies differ from those used in monolingual applications? How do individual differences in subject knowledge, language skills, search...Translation Ideally, we would prefer to provide the searcher with English definitions for each German translation alternative. Dictionaries with these...keeping with the common usage in monolingual contexts [1], we call this approach “key- word in context” or “KWIC.” For each German translation of an

Space transportation system and associated payloads: Glossary, acronyms, and abbreviations

NASA Technical Reports Server (NTRS)

1992-01-01

A collection of some of the acronyms and abbreviations now in everyday use in the shuttle world is presented. It is a combination of lists that were prepared at Marshall Space Flight Center and Kennedy and Johnson Space Centers, places where intensive shuttle activities are being carried out. This list is intended as a guide or reference and should not be considered to have the status and sanction of a dictionary.

Coding of adverse events of suicidality in clinical study reports of duloxetine for the treatment of major depressive disorder: descriptive study

PubMed Central

Tendal, Britta; Hróbjartsson, Asbjørn; Lundh, Andreas; Gøtzsche, Peter C

2014-01-01

Objective To assess the effects of coding and coding conventions on summaries and tabulations of adverse events data on suicidality within clinical study reports. Design Systematic electronic search for adverse events of suicidality in tables, narratives, and listings of adverse events in individual patients within clinical study reports. Where possible, for each event we extracted the original term reported by the investigator, the term as coded by the medical coding dictionary, medical coding dictionary used, and the patient’s trial identification number. Using the patient’s trial identification number, we attempted to reconcile data on the same event between the different formats for presenting data on adverse events within the clinical study report. Setting 9 randomised placebo controlled trials of duloxetine for major depressive disorder submitted to the European Medicines Agency for marketing approval. Data sources Clinical study reports obtained from the EMA in 2011. Results Six trials used the medical coding dictionary COSTART (Coding Symbols for a Thesaurus of Adverse Reaction Terms) and three used MedDRA (Medical Dictionary for Regulatory Activities). Suicides were clearly identifiable in all formats of adverse event data in clinical study reports. Suicide attempts presented in tables included both definitive and provisional diagnoses. Suicidal ideation and preparatory behaviour were obscured in some tables owing to the lack of specificity of the medical coding dictionary, especially COSTART. Furthermore, we found one event of suicidal ideation described in narrative text that was absent from tables and adverse event listings of individual patients. The reason for this is unclear, but may be due to the coding conventions used. Conclusion Data on adverse events in tables in clinical study reports may not accurately represent the underlying patient data because of the medical dictionaries and coding conventions used. In clinical study reports, the listings of adverse events for individual patients and narratives of adverse events can provide additional information, including original investigator reported adverse event terms, which can enable a more accurate estimate of harms. PMID:24899651

A redefining Wernicke's area: receptive language and discourse semantics.

PubMed

Tanner, Dennis C

2007-01-01

This report calls for a more exacting definition of Wernicke's area in the discipline of communication sciences and disorders to reflect an accurate view of brain functioning with regard to decoding discourse semantics. Conventional definitions are provided to delineate the general usages of important terms used by many professional dictionaries and glossaries when defining Wernicke's area, receptive aphasia, understanding, and comprehension. Five levels of semantic decoding are described. A stanza from Tennyson's In Memoriam is used to show the dynamics of discourse semantic decoding and to logically establish that "language understanding" can virtually engage the brain as a whole and the totality of a person's mind. A more accurate definition is provided, indicating that Wernicke's area is not the center for oral language understanding, only an important conduit to language comprehension.

Generalism: The Discipline of Family Medicine

PubMed Central

MacDonald, Peter J.

1981-01-01

The term ‘discipline’, as applied to family medicine, is widely used, yet poorly understood. The dictionary definitions of discipline as “a branch of knowledge or learning; training that develops self-control, character, or orderliness and efficiency” are related in this article to the personal discipline of family physicians. This discipline requires a commitment to whole person medicine, learning and growth; it is both efficient and humane. PMID:21289826

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1999-01-01

The American National Standards Institute?s (ANSI) Spatial Data Transfer Standard (SDTS) is a mechanism for archiving and transferring of spatial data (including metadata) between dissimilar computer systems. The SDTS specifies exchange constructs, such as format, structure, and content, for spatially referenced vector and raster (including gridded) data. The SDTS includes a flexible conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

[Towards universal nomenclature for urgent surgical care].

PubMed

Liakhovs'kyĭ, V I; Dem'ianiuk, D H; Kravtsiv, M I; Borkunov, A L; Sapun, L V

2013-06-01

In a modern professional literature the diseases, which undoubtedly threaten the patient's health and life, are called an urgent, special, emergent, fixed-date, etc. Not rare these terms are used simultaneously. Such a plurality of names of a quite dangerous state causes sometimes in these conditions uncertainty to seek help of a specialists and loss of a time. Modern dictionaries of a foreign languages words, of a foreign languages words in Ukrainian language, medical, big explanatory dictionary of a modern Ukrainian language definitely explains, that these terms are synonyms. All of them mean unconditional, timing. And every expression may be used in this context. The above mentioned suggestions and thoughts do not promote a secure fixing in the citizens consciousness the undoubtedness, the disease consequences danger, a threat to health and life. To deposit this in their awareness it is possible not by amorphous depiction, but using a singular, brief, firm term - an urgent.

The effect of polysemy on lexical decision time: now you see it, now you don't.

PubMed

Millis, M L; Button, S B

1989-03-01

Gernsbacher (1984) found that number of word meanings (polysemy) did not influence lexical decision time when it was operationalized as number of dictionary definitions. This finding supports her contention that subjects do not store all possible dictionary meanings for words in memory. The present experiments extended Gernsbacher's research by determining whether more psychologically valid measures of polysemy affect lexical decision time. Three metrics were used to represent the meanings that subjects actually access from memory (accessible polysemy): (1) the first meanings subjects think of when asked to define stimulus words, (2) all the meanings subjects generate for words, and (3) the average number of meanings subjects generate. The results showed that the second and third metrics of polysemy influenced lexical decision time, whereas the first metric (representing mostly the access to dominant meanings for words) only approached significance.

Identifying missing dictionary entries with frequency-conserving context models

NASA Astrophysics Data System (ADS)

Williams, Jake Ryland; Clark, Eric M.; Bagrow, James P.; Danforth, Christopher M.; Dodds, Peter Sheridan

2015-10-01

In an effort to better understand meaning from natural language texts, we explore methods aimed at organizing lexical objects into contexts. A number of these methods for organization fall into a family defined by word ordering. Unlike demographic or spatial partitions of data, these collocation models are of special importance for their universal applicability. While we are interested here in text and have framed our treatment appropriately, our work is potentially applicable to other areas of research (e.g., speech, genomics, and mobility patterns) where one has ordered categorical data (e.g., sounds, genes, and locations). Our approach focuses on the phrase (whether word or larger) as the primary meaning-bearing lexical unit and object of study. To do so, we employ our previously developed framework for generating word-conserving phrase-frequency data. Upon training our model with the Wiktionary, an extensive, online, collaborative, and open-source dictionary that contains over 100 000 phrasal definitions, we develop highly effective filters for the identification of meaningful, missing phrase entries. With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique and expanding our knowledge of the defined English lexicon of phrases.

Phase unwinding for dictionary compression with multiple channel transmission in magnetic resonance fingerprinting.

PubMed

Lattanzi, Riccardo; Zhang, Bei; Knoll, Florian; Assländer, Jakob; Cloos, Martijn A

2018-06-01

Magnetic Resonance Fingerprinting reconstructions can become computationally intractable with multiple transmit channels, if the B 1 + phases are included in the dictionary. We describe a general method that allows to omit the transmit phases. We show that this enables straightforward implementation of dictionary compression to further reduce the problem dimensionality. We merged the raw data of each RF source into a single k-space dataset, extracted the transceiver phases from the corresponding reconstructed images and used them to unwind the phase in each time frame. All phase-unwound time frames were combined in a single set before performing SVD-based compression. We conducted synthetic, phantom and in-vivo experiments to demonstrate the feasibility of SVD-based compression in the case of two-channel transmission. Unwinding the phases before SVD-based compression yielded artifact-free parameter maps. For fully sampled acquisitions, parameters were accurate with as few as 6 compressed time frames. SVD-based compression performed well in-vivo with highly under-sampled acquisitions using 16 compressed time frames, which reduced reconstruction time from 750 to 25min. Our method reduces the dimensions of the dictionary atoms and enables to implement any fingerprint compression strategy in the case of multiple transmit channels. Copyright © 2018 Elsevier Inc. All rights reserved.

Dave Sperling's Guide to the Internet's Best Writing Resources.

ERIC Educational Resources Information Center

Sperling, Dave

2003-01-01

Provides a guide to writing resources on the Internet, including resources for business writing, dictionaries and thesauruses, e-mail, encyclopedias, free Web space, grammar, fun, online help, online writing labs, punctuation, and spelling. Lists useful Internet tips. (Author/VWL)

The definition of polytrauma: the need for international consensus.

PubMed

Butcher, Nerida; Balogh, Zsolt J

2009-11-01

Polytrauma patients represent the ultimate challenge to trauma care and the optimisation of their care is a major focus of clinical and basic science research. A universally accepted definition for polytrauma is vital for comparing datasets and conducting multicentre trials. The purpose of this review is to identify and evaluate the published definitions of the term "polytrauma". A literature search was conducted for the time period January 1950-August 2008. The Medline, Embase and Cochrane Library databases were searched using the keyword "polytrauma". Articles were evaluated without language exclusion for the occurrence of the word "polytrauma" in the text and the presence of a subsequent definition. Relevant online resources and medical dictionaries were also reviewed. A total of 1,665 publications used the term polytrauma, 47 of which included a definition of the term. The available definitions can be divided into eight groups according to the crux of the definition. No uniformly used consensus definition exists. None of the existing definitions were found to be validated or supported by evidence higher than Level 4. This review identified the lack of a validated or consensus definition of the term polytrauma. The international trauma community should consider establishing a consensus definition for polytrauma, which could be validated prospectively and serve as a basis for future research.

Booksearch: What Dictionary (General or Specialized) Do You Find Useful or Interesting for Students?

ERIC Educational Resources Information Center

English Journal, 1988

1988-01-01

Presents classroom teachers' recommendations for a variety of dictionaries that may heighten students' interest in language: a reverse dictionary, a visual dictionary, WEIGHTY WORD BOOK, a collegiate desk dictionary, OXFORD ENGLISH DICTIONARY, DICTIONARY OF AMERICAN REGIONAL ENGLISH, and a dictionary of idioms. (ARH)

Data Base Directions: Information Resource Management - Strategies and Tools. Proceedings of the Workshop of the National Bureau of Standards and the Association for Computing Machinery (Ft. Lauderdale, Florida, October 20-22, 1980).

ERIC Educational Resources Information Center

Goldfine, Alan H., Ed.

This workshop investigated how managers can evaluate, select, and effectively use information resource management (IRM) tools, especially data dictionary systems (DDS). An executive summary, which provides a definition of IRM as developed by workshop participants, precedes the keynote address, "Data: The Raw Material of a Paper Factory,"…

Software Testing for Evolutionary Iterative Rapid Prototyping

DTIC Science & Technology

1990-12-01

kept later hours than I did. Amidst the hustle and bustle, their prayers and help around the house were a great ast.. Finally, if anything shows the...possible meanings. A basic dictionary definition describes prototyping as "an original type , form, or instance that serves as a modfe] on which later...on program size. Asset instruments 49 the subject procedure and produces a graph of the structure for the type of data flow testing conducted. It

The PDS4 Data Dictionary Tool - Metadata Design for Data Preparers

NASA Astrophysics Data System (ADS)

Raugh, A.; Hughes, J. S.

2017-12-01

One of the major design goals of the PDS4 development effort was to create an extendable Information Model (IM) for the archive, and to allow mission data designers/preparers to create extensions for metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity in the data itself, it is in the best interests of the PDS archive and its users that all extensions to the IM follow the same design techniques, conventions, and restrictions as the core implementation itself. But it is unrealistic to expect mission data designers to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy in order to define their own metadata. To bridge that expertise gap and bring the power of information modeling to the data label designer, the PDS Engineering Node has developed the data dictionary creation tool known as "LDDTool". This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his extension to the IM using the same, standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define context-specific validation rules. We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

The Planetary Data System (PDS) Data Dictionary Tool (LDDTool)

NASA Astrophysics Data System (ADS)

Raugh, Anne C.; Hughes, John S.

2017-10-01

One of the major design goals of the PDS4 development effort was to provide an avenue for discipline specialists and large data preparers such as mission archivists to extend the core PDS4 Information Model (IM) to include metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity, it is in the best interests of the PDS archive and its users that all extensions to the core IM follow the same design techniques, conventions, and restrictions as the core implementation itself. Notwithstanding, expecting all mission and discipline archivist seeking to define metadata for a new context to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy is unrealistic, to say the least.To bridge that expertise gap, the PDS Engineering Node has developed the data dictionary creation tool known as “LDDTool”. This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his contextual information model using the same, open standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define very sophisticated validation rules.We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

Learners' Dictionaries: State of the Art. Anthology Series 23.

ERIC Educational Resources Information Center

Tickoo, Makhan L., Ed.

A collection of articles on dictionaries for advanced second language learners includes essays on the past, present, and future of learners' dictionaries; alternative dictionaries; dictionary construction; and dictionaries and their users. Titles include: "Idle Thoughts of an Idle Fellow; or Vaticinations on the Learners' Dictionary"…

The SMAP Dictionary Management System

NASA Technical Reports Server (NTRS)

Smith, Kevin A.; Swan, Christoper A.

2014-01-01

The Soil Moisture Active Passive (SMAP) Dictionary Management System is a web-based tool to develop and store a mission dictionary. A mission dictionary defines the interface between a ground system and a spacecraft. In recent years, mission dictionaries have grown in size and scope, making it difficult for engineers across multiple disciplines to coordinate the dictionary development effort. The Dictionary Management Systemaddresses these issues by placing all dictionary information in one place, taking advantage of the efficiencies inherent in co-locating what were once disparate dictionary development efforts.

A consensus view of fold space: Combining SCOP, CATH, and the Dali Domain Dictionary

PubMed Central

Day, Ryan; Beck, David A.C.; Armen, Roger S.; Daggett, Valerie

2003-01-01

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web. PMID:14500873

A consensus view of fold space: combining SCOP, CATH, and the Dali Domain Dictionary.

PubMed

Day, Ryan; Beck, David A C; Armen, Roger S; Daggett, Valerie

2003-10-01

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.

Dictionaries: British and American. The Language Library.

ERIC Educational Resources Information Center

Hulbert, James Root

An account of the dictionaries, great and small, of the English-speaking world is given in this book. Subjects covered include the origin of English dictionaries, early dictionaries, Noah Webster and his successors to the present, abridged dictionaries, "The Oxford English Dictionary" and later dictionaries patterned after it, the…

A stereoscopic look into the bulk

DOE PAGES

Czech, Bartlomiej; Lamprou, Lampros; McCandlish, Samuel; ...

2016-07-26

Here, we present the foundation for a holographic dictionary with depth perception. The dictionary consists of natural CFT operators whose duals are simple, diffeomorphism-invariant bulk operators. The CFT operators of interest are the “OPE blocks,” contributions to the OPE from a single conformal family. In holographic theories, we show that the OPE blocks are dual at leading order in 1/N to integrals of effective bulk fields along geodesics or homogeneous minimal surfaces in anti-de Sitter space. One widely studied example of an OPE block is the modular Hamiltonian, which is dual to the fluctuation in the area of a minimalmore » surface. Thus, our operators pave the way for generalizing the Ryu-Takayanagi relation to other bulk fields. Although the OPE blocks are non-local operators in the CFT, they admit a simple geometric description as fields in kinematic space — the space of pairs of CFT points. We develop the tools for constructing local bulk operators in terms of these non-local objects. The OPE blocks also allow for conceptually clean and technically simple derivations of many results known in the literature, including linearized Einstein’s equations and the relation between conformal blocks and geodesic Witten diagrams.« less

Gene/protein name recognition based on support vector machine using dictionary as features.

PubMed

Mitsumori, Tomohiro; Fation, Sevrani; Murata, Masaki; Doi, Kouichi; Doi, Hirohumi

2005-01-01

Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedical named entities is the first step in information extraction. We developed an automated recognition system based on the SVM algorithm and evaluated it in Task 1.A of BioCreAtIvE, a competition for automated gene/protein name recognition. In the work presented here, our recognition system uses the feature set of the word, the part-of-speech (POS), the orthography, the prefix, the suffix, and the preceding class. We call these features "internal resource features", i.e., features that can be found in the training data. Additionally, we consider the features of matching against dictionaries to be external resource features. We investigated and evaluated the effect of these features as well as the effect of tuning the parameters of the SVM algorithm. We found that the dictionary matching features contributed slightly to the improvement in the performance of the f-score. We attribute this to the possibility that the dictionary matching features might overlap with other features in the current multiple feature setting. During SVM learning, each feature alone had a marginally positive effect on system performance. This supports the fact that the SVM algorithm is robust on the high dimensionality of the feature vector space and means that feature selection is not required.

Markov Chain Monte Carlo Inference of Parametric Dictionaries for Sparse Bayesian Approximations

PubMed Central

Chaspari, Theodora; Tsiartas, Andreas; Tsilifis, Panagiotis; Narayanan, Shrikanth

2016-01-01

Parametric dictionaries can increase the ability of sparse representations to meaningfully capture and interpret the underlying signal information, such as encountered in biomedical problems. Given a mapping function from the atom parameter space to the actual atoms, we propose a sparse Bayesian framework for learning the atom parameters, because of its ability to provide full posterior estimates, take uncertainty into account and generalize on unseen data. Inference is performed with Markov Chain Monte Carlo, that uses block sampling to generate the variables of the Bayesian problem. Since the parameterization of dictionary atoms results in posteriors that cannot be analytically computed, we use a Metropolis-Hastings-within-Gibbs framework, according to which variables with closed-form posteriors are generated with the Gibbs sampler, while the remaining ones with the Metropolis Hastings from appropriate candidate-generating densities. We further show that the corresponding Markov Chain is uniformly ergodic ensuring its convergence to a stationary distribution independently of the initial state. Results on synthetic data and real biomedical signals indicate that our approach offers advantages in terms of signal reconstruction compared to previously proposed Steepest Descent and Equiangular Tight Frame methods. This paper demonstrates the ability of Bayesian learning to generate parametric dictionaries that can reliably represent the exemplar data and provides the foundation towards inferring the entire variable set of the sparse approximation problem for signal denoising, adaptation and other applications. PMID:28649173

The semantics of Chemical Markup Language (CML): dictionaries and conventions.

PubMed

Murray-Rust, Peter; Townsend, Joe A; Adams, Sam E; Phadungsukanan, Weerapong; Thomas, Jens

2011-10-14

The semantic architecture of CML consists of conventions, dictionaries and units. The conventions conform to a top-level specification and each convention can constrain compliant documents through machine-processing (validation). Dictionaries conform to a dictionary specification which also imposes machine validation on the dictionaries. Each dictionary can also be used to validate data in a CML document, and provide human-readable descriptions. An additional set of conventions and dictionaries are used to support scientific units. All conventions, dictionaries and dictionary elements are identifiable and addressable through unique URIs.

The semantics of Chemical Markup Language (CML): dictionaries and conventions

PubMed Central

2011-01-01

The semantic architecture of CML consists of conventions, dictionaries and units. The conventions conform to a top-level specification and each convention can constrain compliant documents through machine-processing (validation). Dictionaries conform to a dictionary specification which also imposes machine validation on the dictionaries. Each dictionary can also be used to validate data in a CML document, and provide human-readable descriptions. An additional set of conventions and dictionaries are used to support scientific units. All conventions, dictionaries and dictionary elements are identifiable and addressable through unique URIs. PMID:21999509

Statutory Interpretation: General Principles and Recent Trends

DTIC Science & Technology

2006-03-30

although the Court’s pathway through the mix is often not clearly foreseeable, an understanding of interpretational possibilities may nonetheless lessen...dictionary definitions to interpret the word “ marketing ” as used in the Plant Variety Protection Act,24 and the word “principal” as used to modify a...exclusive”conditions that can rule out mixing and matching. United States v. Williams, 326 F.3d 535, 541 (4th Cir. 2003) (“a crime may qualify as a

Department of Defense Dictionary of Military and Associated Terms

DTIC Science & Technology

2010-11-08

Terminology. 4. Publication Format This edition of JP 1-02 has been published in two basic parts: a . Terms and definitions. These are...understanding and management of the associated term. 5. JP 1-02 Online Availability and Update Schedule JP 1-02 is accessible online as a searchable...As Amended Through 15 February 2016 ii JP 1-02 address: https://jdeis.js.mil/jdeis/. The contents of JP 1-02 are updated on a monthly basis to

A Database Design for a Unit Status Reporting System.

DTIC Science & Technology

1987-03-01

definitions. g. Extraction of data dictionary entries from existing programs. [Ref. 7:pp. 63-66] The third tool is used to define the logic of the...Automation of the Unit Status Reporting System is feasible, and would require: integrated files of data, some direct data extraction from those files...an extract of AR 220-1. Relevant sections of the regulation are included to provide an easy reference for the reader. The last section of the

System analysis study of space platform and station accommodations for life sciences research facilities. Volume 2: Study results. Appendix E: Work breakdown structure and dictionary

NASA Technical Reports Server (NTRS)

Wiley, Lowell F.

1985-01-01

A work breakdown structure for the Space Station Life Sciences Research Facility (LSRF) is presented up to level 5. The purpose is to provide the framework for task planning and control and to serve as a basis for budgeting, task assignment, cost collection and report, and contractual performance measurement and tracking of the Full Scale Development Phase tasks.

Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

PubMed

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

Boundary kinematic space

DOE PAGES

Karch, Andreas; Sully, James; Uhlemann, Christoph F.; ...

2017-08-10

We extend kinematic space to a simple scenario where the state is not fixed by conformal invariance: the vacuum of a conformal field theory with a boundary (bCFT). We identify the kinematic space associated with the boundary operator product expansion (bOPE) as a subspace of the full kinematic space. In addition, we establish representations of the corresponding bOPE blocks in a dual gravitational description. We show how the new kinematic dictionary and the dynamical data in bOPE allows one to reconstruct the bulk geometry. This is evidence that kinematic space may be a useful construction for understanding bulk physics beyondmore » just kinematics.« less

Boundary kinematic space

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

Karch, Andreas; Sully, James; Uhlemann, Christoph F.

We extend kinematic space to a simple scenario where the state is not fixed by conformal invariance: the vacuum of a conformal field theory with a boundary (bCFT). We identify the kinematic space associated with the boundary operator product expansion (bOPE) as a subspace of the full kinematic space. In addition, we establish representations of the corresponding bOPE blocks in a dual gravitational description. We show how the new kinematic dictionary and the dynamical data in bOPE allows one to reconstruct the bulk geometry. This is evidence that kinematic space may be a useful construction for understanding bulk physics beyondmore » just kinematics.« less

Space Transportation Booster Engine Configuration Study. Volume 3: Program Cost estimates and work breakdown structure and WBS dictionary

NASA Technical Reports Server (NTRS)

1989-01-01

The objective of the Space Transportation Booster Engine Configuration Study is to contribute to the ALS development effort by providing highly reliable, low cost booster engine concepts for both expendable and reusable rocket engines. The objectives of the Space Transportation Booster Engine (STBE) Configuration Study were: (1) to identify engine development configurations which enhance vehicle performance and provide operational flexibility at low cost; and (2) to explore innovative approaches to the follow-on Full-Scale Development (FSD) phase for the STBE.

The Environment-Power System Analysis Tool development program. [for spacecraft power supplies

NASA Technical Reports Server (NTRS)

Jongeward, Gary A.; Kuharski, Robert A.; Kennedy, Eric M.; Wilcox, Katherine G.; Stevens, N. John; Putnam, Rand M.; Roche, James C.

1989-01-01

The Environment Power System Analysis Tool (EPSAT) is being developed to provide engineers with the ability to assess the effects of a broad range of environmental interactions on space power systems. A unique user-interface-data-dictionary code architecture oversees a collection of existing and future environmental modeling codes (e.g., neutral density) and physical interaction models (e.g., sheath ionization). The user-interface presents the engineer with tables, graphs, and plots which, under supervision of the data dictionary, are automatically updated in response to parameter change. EPSAT thus provides the engineer with a comprehensive and responsive environmental assessment tool and the scientist with a framework into which new environmental or physical models can be easily incorporated.

XML technology planning database : lessons learned

NASA Technical Reports Server (NTRS)

Some, Raphael R.; Neff, Jon M.

2005-01-01

A hierarchical Extensible Markup Language(XML) database called XCALIBR (XML Analysis LIBRary) has been developed by Millennium Program to assist in technology investment (ROI) analysis and technology Language Capability the New return on portfolio optimization. The database contains mission requirements and technology capabilities, which are related by use of an XML dictionary. The XML dictionary codifies a standardized taxonomy for space missions, systems, subsystems and technologies. In addition to being used for ROI analysis, the database is being examined for use in project planning, tracking and documentation. During the past year, the database has moved from development into alpha testing. This paper describes the lessons learned during construction and testing of the prototype database and the motivation for moving from an XML taxonomy to a standard XML-based ontology.

An Operational System for Subject Switching between Controlled Vocabularies.

ERIC Educational Resources Information Center

Silvester, June P.; Klingbiel, Paul H.

1993-01-01

Describes a system developed at the National Aeronautics and Space Administration (NASA) that automatically converts index terms from the Defense Technical Information Center (DTIC) to NASA thesaurus terms. The NASA Lexical Dictionary (NLD) that generates thesaurus terms for indexing is explained, and the development of machine-aided indexing is…

Nomenclature in laboratory robotics and automation (IUPAC Recommendation 1994)

PubMed Central

(Skip) Kingston, H. M.; Kingstonz, M. L.

1994-01-01

These recommended terms have been prepared to help provide a uniform approach to terminology and notation in laboratory automation and robotics. Since the terminology used in laboratory automation and robotics has been derived from diverse backgrounds, it is often vague, imprecise, and in some cases, in conflict with classical automation and robotic nomenclature. These dejinitions have been assembled from standards, monographs, dictionaries, journal articles, and documents of international organizations emphasizing laboratory and industrial automation and robotics. When appropriate, definitions have been taken directly from the original source and identified with that source. However, in some cases no acceptable definition could be found and a new definition was prepared to define the object, term, or action. Attention has been given to defining specific robot types, coordinate systems, parameters, attributes, communication protocols and associated workstations and hardware. Diagrams are included to illustrate specific concepts that can best be understood by visualization. PMID:18924684

The Role of Dictionaries in Language Learning.

ERIC Educational Resources Information Center

White, Philip A.

1997-01-01

Examines assumptions about dictionaries, especially the bilingual dictionary, and suggests ways of integrating the monolingual dictionary into the second-language instructional process. Findings indicate that the monolingual dictionary can coexist with bilingual dictionaries within a foreign-language course if the latter are appropriately used as…

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

PubMed

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

Which Dictionary? A Review of the Leading Learners' Dictionaries.

ERIC Educational Resources Information Center

Nesi, Hilary

Three major dictionaries designed for learners of English as a second language are reviewed, their elements and approaches compared and evaluated, their usefulness for different learners discussed, and recommendations for future dictionary improvement made. The dictionaries in question are the "Oxford Advanced Learner's Dictionary," the…

French Dictionaries. Series: Specialised Bibliographies.

ERIC Educational Resources Information Center

Klaar, R. M.

This is a list of French monolingual, French-English and English-French dictionaries available in December 1975. Dictionaries of etymology, phonetics, place names, proper names, and slang are included, as well as dictionaries for children and dictionaries of Belgian, Canadian, and Swiss French. Most other specialized dictionaries, encyclopedias,…

Which Desk Dictionary Is Best for Foreign Students of English?

ERIC Educational Resources Information Center

Yorkey, Richard

1969-01-01

"The American College Dictionary, "Funk and Wagnalls Standard College Dictionary," Webster's New World Dictionary of the American Language," The Random House Dictionary of the English Language," and Webster's Seventh New Collegiate Dictionary" are analyzed and ranked as to their usefulness for the foreign learner of English. (FWB)

Holographic entanglement and Poincaré blocks in three-dimensional flat space

NASA Astrophysics Data System (ADS)

Hijano, Eliot; Rabideau, Charles

2018-05-01

We propose a covariant prescription to compute holographic entanglement entropy and Poincaré blocks (Global BMS blocks) in the context of three-dimensional Einstein gravity in flat space. We first present a prescription based on worldline methods in the probe limit, inspired by recent analog calculations in AdS/CFT. Building on this construction, we propose a full extrapolate dictionary and use it to compute holographic correlators and blocks away from the probe limit.

Department of Defense Dictionary of Military and Associated Terms. Incorporating the NATO Glossary of Terms and Definitions (English and French)

DTIC Science & Technology

1989-12-01

can operate combination of airborne units, air transport - beyond the atmosphere. able units, and types of transport aircraft, de - pending on the mission...amphibious transport dock-(DOD) A ship de - anchor-See sinker. signed to transport and land troops, equip- ment, and supplies by means of embarked...attack and requiring emergency operations dock landing ship-(DOD) A naval ship de - during and following that attack. It may be signed to transport and

Referral Coordination in the Next TRICARE Contract Environment: A Case Study Applying Failure Mode Effects Analysis

DTIC Science & Technology

2004-06-13

antiquity. Plutarch is credited for saying in Morals--Against Colotes the Epicurean, "For to err in opinion, though it be not the part of wise men, it is at...least human" ( Plutarch , AD 110). Of the 5 definitions for error given in Merriam-Webster’s Collegiate Dictionary, the third one listed "an act that...Identifying and managing inappropriate hospital utilization: A policy synthesis. Health Services Research, 22(5), 710-57. Plutarch . (AD 110) . Worldofquotes

An Analysis of Contracting Terms: Expanding the Body of Knowledge Within the Contract Management Profession

DTIC Science & Technology

1992-09-01

products that are essential to the intended end use. (1987:110) According to Government Contract Law , brand name or equal is defined as: "The minimum...definitions agree, but Government Contract Law says it most clearly and succinctly; therefore, based on the above, the following was selected as the...followed by the words "or equal" (Government Contract Law , 1988:8-2). Breach of Contract The Dictionary of Purchasing Terms defines this term as "the

The optimistic heretic

NASA Astrophysics Data System (ADS)

Dyson, Freeman

2008-01-01

The Oxford English Dictionary defines the word “heretic” as “the holder of an unorthodox opinion”. By his own admission, physicist Freeman Dyson has most definitely not been a heretic as far as his contributions to science are concerned, having carried out significant research on quantum electrodynamics and the stability of bulk matter. However, he certainly has unorthodox views when it comes to social issues related to science, which he has discussed at length in a number of books over the last two decades.

The concept of hierarchy in general systems theory.

PubMed

Gasparski, W

1994-01-01

The paper reviews main ideas related to the concept of hierarchy as they are discussed in contemporary general systems theory. After presenting a dictionary definition of the concept, the author examines the intuitive idea of hierarchy quoting Mario Bunge's notion of level structure. Then relationship between two other concepts: a system and a hierarchy is characterised on the bases of Bowler's, Bunge's again, Klir's, and the author's studies. Finally, the paper is concluded that hierarchy is not an otological concept but epistemological one.

When Cancer Returns

MedlinePlus

... content 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Coping with Advanced Cancer

MedlinePlus

... content 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Thinking about Complementary and Alternative Medicine

MedlinePlus

... content 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Caring for the Caregiver

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

The Use of Monolingual Mobile Dictionaries in the Context of Reading by Intermediate Cantonese EFL Learners in Hong Kong

ERIC Educational Resources Information Center

Zou, Di; Xie, Haoran; Wang, Fu Lee

2015-01-01

Previous studies on dictionary consultation investigated mainly online dictionaries or simple pocket electronic dictionaries as they were commonly used among learners back then, yet the more updated mobile dictionaries were superficially investigated though they have already replaced the pocket electronic dictionaries. These studies are also…

The Power of Math Dictionaries in the Classroom

ERIC Educational Resources Information Center

Patterson, Lynn Gannon; Young, Ashlee Futrell

2013-01-01

This article investigates the value of a math dictionary in the elementary classroom and if elementary students prefer using a traditional math dictionary or a dictionary on an iPad. In each child's journey to reading with understanding, the dictionary can be a comforting and valuable resource. Would students find a math dictionary to be a…

Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

PubMed Central

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-01-01

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively. PMID:24871988

Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

PubMed

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-05-27

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Sparse regularization for force identification using dictionaries

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng

2016-04-01

The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.

Cancer Information Summaries: Screening/Detection

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Children with Cancer: A Guide for Parents

MedlinePlus

... content 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

First Encounters of the Close Kind: The Formation Process of Airline Flight Crews

DTIC Science & Technology

1987-01-01

process and aircrew performance, Foushee notes an interesting etymological parallel: "Webster’s New Collegiate Dictionary (1961) defines cockpit as ’a...here combines applications from the physical science of chemistry and the modern science of computers. In chemistry , a shell is a space occupied by

Non-stationary noise estimation using dictionary learning and Gaussian mixture models

NASA Astrophysics Data System (ADS)

Hughes, James M.; Rockmore, Daniel N.; Wang, Yang

2014-02-01

Stationarity of the noise distribution is a common assumption in image processing. This assumption greatly simplifies denoising estimators and other model parameters and consequently assuming stationarity is often a matter of convenience rather than an accurate model of noise characteristics. The problematic nature of this assumption is exacerbated in real-world contexts, where noise is often highly non-stationary and can possess time- and space-varying characteristics. Regardless of model complexity, estimating the parameters of noise dis- tributions in digital images is a difficult task, and estimates are often based on heuristic assumptions. Recently, sparse Bayesian dictionary learning methods were shown to produce accurate estimates of the level of additive white Gaussian noise in images with minimal assumptions. We show that a similar model is capable of accu- rately modeling certain kinds of non-stationary noise processes, allowing for space-varying noise in images to be estimated, detected, and removed. We apply this modeling concept to several types of non-stationary noise and demonstrate the model's effectiveness on real-world problems, including denoising and segmentation of images according to noise characteristics, which has applications in image forensics.

Usage Notes in the Oxford American Dictionary.

ERIC Educational Resources Information Center

Berner, R. Thomas

1981-01-01

Compares the "Oxford American Dictionary" with the "American Heritage Dictionary." Examines the dictionaries' differences in philosophies of language, introductory essays, and usage notes. Concludes that the "Oxford American Dictionary" is too conservative, paternalistic, and dogmatic for the 1980s. (DMM)

Treatment Choices for Men with Early-Stage Prostate Cancer

MedlinePlus

... content 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Pain Control: Support for People with Cancer

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Chemotherapy and You: Support for People with Cancer

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Facing Forward Series: Life After Cancer Treatment

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Eating Hints: Before, During, and After Cancer Treatment

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Taking Time: Support for People with Cancer

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

Radiation Therapy and You: Support for People with Cancer

MedlinePlus

... Español 1-800-4-CANCER Live Chat Publications Dictionary Menu Contact Dictionary Search About Cancer Causes and Prevention Risk Factors ... Levels of Evidence: Integrative Therapies Fact Sheets NCI Dictionaries NCI Dictionary of Cancer Terms NCI Drug Dictionary ...

A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI.

PubMed

Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Sapiro, Guillermo; Lenglet, Christophe

2017-09-01

We propose a sparse Bayesian learning algorithm for improved estimation of white matter fiber parameters from compressed (under-sampled q-space) multi-shell diffusion MRI data. The multi-shell data is represented in a dictionary form using a non-monoexponential decay model of diffusion, based on continuous gamma distribution of diffusivities. The fiber volume fractions with predefined orientations, which are the unknown parameters, form the dictionary weights. These unknown parameters are estimated with a linear un-mixing framework, using a sparse Bayesian learning algorithm. A localized learning of hyperparameters at each voxel and for each possible fiber orientations improves the parameter estimation. Our experiments using synthetic data from the ISBI 2012 HARDI reconstruction challenge and in-vivo data from the Human Connectome Project demonstrate the improvements.

Highly undersampled MR image reconstruction using an improved dual-dictionary learning method with self-adaptive dictionaries.

PubMed

Li, Jiansen; Song, Ying; Zhu, Zhen; Zhao, Jun

2017-05-01

Dual-dictionary learning (Dual-DL) method utilizes both a low-resolution dictionary and a high-resolution dictionary, which are co-trained for sparse coding and image updating, respectively. It can effectively exploit a priori knowledge regarding the typical structures, specific features, and local details of training sets images. The prior knowledge helps to improve the reconstruction quality greatly. This method has been successfully applied in magnetic resonance (MR) image reconstruction. However, it relies heavily on the training sets, and dictionaries are fixed and nonadaptive. In this research, we improve Dual-DL by using self-adaptive dictionaries. The low- and high-resolution dictionaries are updated correspondingly along with the image updating stage to ensure their self-adaptivity. The updated dictionaries incorporate both the prior information of the training sets and the test image directly. Both dictionaries feature improved adaptability. Experimental results demonstrate that the proposed method can efficiently and significantly improve the quality and robustness of MR image reconstruction.

Iterative dictionary construction for compression of large DNA data sets.

PubMed

Kuruppu, Shanika; Beresford-Smith, Bryan; Conway, Thomas; Zobel, Justin

2012-01-01

Genomic repositories increasingly include individual as well as reference sequences, which tend to share long identical and near-identical strings of nucleotides. However, the sequential processing used by most compression algorithms, and the volumes of data involved, mean that these long-range repetitions are not detected. An order-insensitive, disk-based dictionary construction method can detect this repeated content and use it to compress collections of sequences. We explore a dictionary construction method that improves repeat identification in large DNA data sets. Our adaptation, COMRAD, of an existing disk-based method identifies exact repeated content in collections of sequences with similarities within and across the set of input sequences. COMRAD compresses the data over multiple passes, which is an expensive process, but allows COMRAD to compress large data sets within reasonable time and space. COMRAD allows for random access to individual sequences and subsequences without decompressing the whole data set. COMRAD has no competitor in terms of the size of data sets that it can compress (extending to many hundreds of gigabytes) and, even for smaller data sets, the results are competitive compared to alternatives; as an example, 39 S. cerevisiae genomes compressed to 0.25 bits per base.

What Dictionary to Use? A Closer Look at the "Oxford Advanced Learner's Dictionary," the "Longman Dictionary of Contemporary English" and the "Longman Lexicon of Contempory English."

ERIC Educational Resources Information Center

Shaw, A. M.

1983-01-01

Three dictionaries are compared for their usefulness to teachers of English as a foreign language, teachers in training, students, and other users of English as a foreign language. The issue of monolingual versus bilingual dictionary format is discussed, and a previous analysis of the two bilingual dictionaries is summarized. Pronunciation…

[Analysis on composition principles of formulae containing Gardeniae Fructus in dictionary of traditional Chinese medicine prescriptions].

PubMed

Hu, Yan-Zhen; Wei, Jun-Ying; Tang, Shi-Huan; Yang, Hong-Jun

2016-04-01

Gardeniae Fructus, which is widely used in health foods and clinical medicines, is a type of edible food and medicine. Dictionary of traditional Chinese medicine prescriptions provides good materials for prescription analysis and the R&D of traditional Chinese medicines. The composition regularity of formulae containing Gardeniae Fructus in dictionary of traditional Chinese medicine prescriptions was analyzed on the basis of the traditional Chinese medicine inheritance support system(TCMISS), in order to provide reference for clinical application and the R&D of new drugs. TCMISS was applied to establish a database of prescriptions containing Gardeniae Fructus. The software's frequency statistics and association rules and other date mining technologies were adopted to analyze commonly used drugs, combination rules and core combined formulae containing Gardeniae Fructus. Totally 3 523 prescriptions were included in this study and involved 1 725 Chinese herbs. With a support degree of 352(10%) and confidence coefficient of 90%, 57 most commonly used drug combinations were screened. Drugs adopted in core combinations were relatively concentrated and selected according to definite composition methods. They were used to mainly treat 18 diseases. Gardeniae Fructus have often been combined with herbs for heat-clearing and detoxification, expelling pathogenic wind, relieving exterior syndrome, invigorating the circulation of blood and gas and promoting blood circulation for removing blood stasis to mainly treat jaundice, typhoid, headache and other syndromes. Copyright© by the Chinese Pharmaceutical Association.

DICTIONARIES AND LANGUAGE CHANGE.

ERIC Educational Resources Information Center

POOLEY, ROBERT C.

TWO VIEWS OF A DICTIONARY'S PURPOSE CAME INTO SHARP CONFLICT UPON THE PUBLICATION OF WEBSTER'S "THIRD NEW INTERNATIONAL UNABRIDGED DICTIONARY." THE FIRST VIEW IS THAT A DICTIONARY IS A REFERENCE BOOK ON LANGUAGE ETIQUETTE, AN AUTHORITY FOR MAINTAINING THE PURITY OF THE ENGLISH LANGUAGE. THE SECOND IS THAT A DICTIONARY IS A SCIENTIFIC…

Do Dictionaries Help Students Write?

ERIC Educational Resources Information Center

Nesi, Hilary

Examples are given of real lexical errors made by learner writers, and consideration is given to the way in which three learners' dictionaries could deal with the lexical items that were misused. The dictionaries were the "Oxford Advanced Learner's Dictionary," the "Longman Dictionary of Contemporary English," and the "Chambers Universal Learners'…

Information on Quantifiers and Argument Structure in English Learner's Dictionaries.

ERIC Educational Resources Information Center

Lee, Thomas Hun-tak

1993-01-01

Lexicographers have been arguing for the inclusion of abstract and complex grammatical information in dictionaries. This paper examines the extent to which information about quantifiers and the argument structure of verbs is encoded in English learner's dictionaries. The Oxford Advanced Learner's Dictionary (1989), the Longman Dictionary of…

Seismic classification through sparse filter dictionaries

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

Hickmann, Kyle Scott; Srinivasan, Gowri

We tackle a multi-label classi cation problem involving the relation between acoustic- pro le features and the measured seismogram. To isolate components of the seismo- grams unique to each class of acoustic pro le we build dictionaries of convolutional lters. The convolutional- lter dictionaries for the individual classes are then combined into a large dictionary for the entire seismogram set. A given seismogram is classi ed by computing its representation in the large dictionary and then comparing reconstruction accuracy with this representation using each of the sub-dictionaries. The sub-dictionary with the minimal reconstruction error identi es the seismogram class.

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

Definitions of components of the master water data index maintained by the National Water Data Exchange

USGS Publications Warehouse

Perry, R.A.; Williams, O.O.

1982-01-01

The Master Water Data Index is a computerized data base developed and maintained by the National Water Data Exchange (NAWDEX). The Index contains information about water-data collection sites. This information includes: the identification of new sites for which water data are available, the locations of these sites, the type of site, the data-collection organization, the types of data available, the major water-data parameters for which data are available, the frequency at which these parameters are measured, the period of time for which data are available, and the medial in which the data are stored. This document, commonly referred to as the MWDI data dictionary, contains a definition and description of each component of the Master Water Data Index data base. (USGS)

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis : Distributed dictionary representation.

PubMed

Garten, Justin; Hoover, Joe; Johnson, Kate M; Boghrati, Reihane; Iskiwitch, Carol; Dehghani, Morteza

2018-02-01

Theory-driven text analysis has made extensive use of psychological concept dictionaries, leading to a wide range of important results. These dictionaries have generally been applied through word count methods which have proven to be both simple and effective. In this paper, we introduce Distributed Dictionary Representations (DDR), a method that applies psychological dictionaries using semantic similarity rather than word counts. This allows for the measurement of the similarity between dictionaries and spans of text ranging from complete documents to individual words. We show how DDR enables dictionary authors to place greater emphasis on construct validity without sacrificing linguistic coverage. We further demonstrate the benefits of DDR on two real-world tasks and finally conduct an extensive study of the interaction between dictionary size and task performance. These studies allow us to examine how DDR and word count methods complement one another as tools for applying concept dictionaries and where each is best applied. Finally, we provide references to tools and resources to make this method both available and accessible to a broad psychological audience.

Dictionary Learning Algorithms for Sparse Representation

PubMed Central

Kreutz-Delgado, Kenneth; Murray, Joseph F.; Rao, Bhaskar D.; Engan, Kjersti; Lee, Te-Won; Sejnowski, Terrence J.

2010-01-01

Algorithms for data-driven learning of domain-specific overcomplete dictionaries are developed to obtain maximum likelihood and maximum a posteriori dictionary estimates based on the use of Bayesian models with concave/Schur-concave (CSC) negative log priors. Such priors are appropriate for obtaining sparse representations of environmental signals within an appropriately chosen (environmentally matched) dictionary. The elements of the dictionary can be interpreted as concepts, features, or words capable of succinct expression of events encountered in the environment (the source of the measured signals). This is a generalization of vector quantization in that one is interested in a description involving a few dictionary entries (the proverbial “25 words or less”), but not necessarily as succinct as one entry. To learn an environmentally adapted dictionary capable of concise expression of signals generated by the environment, we develop algorithms that iterate between a representative set of sparse representations found by variants of FOCUSS and an update of the dictionary using these sparse representations. Experiments were performed using synthetic data and natural images. For complete dictionaries, we demonstrate that our algorithms have improved performance over other independent component analysis (ICA) methods, measured in terms of signal-to-noise ratios of separated sources. In the overcomplete case, we show that the true underlying dictionary and sparse sources can be accurately recovered. In tests with natural images, learned overcomplete dictionaries are shown to have higher coding efficiency than complete dictionaries; that is, images encoded with an over-complete dictionary have both higher compression (fewer bits per pixel) and higher accuracy (lower mean square error). PMID:12590811

Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

PubMed

Akhtar, Naveed; Mian, Ajmal

2017-10-03

We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

Fast Low-Rank Shared Dictionary Learning for Image Classification.

PubMed

Tiep Huu Vu; Monga, Vishal

2017-11-01

Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recently proposed dictionary learning framework by separating the particularity and the commonality (COPAR). Inspired by this, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification with more intuitive constraints. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low-rank constraint, i.e., claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Furthermore, we develop new fast and accurate algorithms to solve the subproblems in the learning step, accelerating its convergence. The said algorithms could also be applied to FDDL and its extensions. The efficiencies of these algorithms are theoretically and experimentally verified by comparing their complexities and running time with those of other well-known dictionary learning methods. Experimental results on widely used image data sets establish the advantages of our method over the state-of-the-art dictionary learning methods.

Fast Low-Rank Shared Dictionary Learning for Image Classification

NASA Astrophysics Data System (ADS)

Vu, Tiep Huu; Monga, Vishal

2017-11-01

Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recently proposed dictionary learning framework by separating the particularity and the commonality (COPAR). Inspired by this, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification with more intuitive constraints. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low-rank constraint, i.e. claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Further, we develop new fast and accurate algorithms to solve the subproblems in the learning step, accelerating its convergence. The said algorithms could also be applied to FDDL and its extensions. The efficiencies of these algorithms are theoretically and experimentally verified by comparing their complexities and running time with those of other well-known dictionary learning methods. Experimental results on widely used image datasets establish the advantages of our method over state-of-the-art dictionary learning methods.

Emo, love and god: making sense of Urban Dictionary, a crowd-sourced online dictionary.

PubMed

Nguyen, Dong; McGillivray, Barbara; Yasseri, Taha

2018-05-01

The Internet facilitates large-scale collaborative projects and the emergence of Web 2.0 platforms, where producers and consumers of content unify, has drastically changed the information market. On the one hand, the promise of the 'wisdom of the crowd' has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based information in many languages. On the other hand, the decentralized and often unmonitored environment of such projects may make them susceptible to low-quality content. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. Urban Dictionary also contains offensive content, but highly offensive content tends to receive lower scores through the dictionary's voting system. The low threshold to include new material in Urban Dictionary enables quick recording of new words and new meanings, but the resulting heterogeneous content can pose challenges in using Urban Dictionary as a source to study language innovation.

A Study of Comparatively Low Achievement Students' Bilingualized Dictionary Use and Their English Learning

ERIC Educational Resources Information Center

Chen, Szu-An

2016-01-01

This study investigates bilingualized dictionary use of Taiwanese university students. It aims to examine EFL learners' overall dictionary use behavior and their perspectives on book dictionary as well as the necessity of advance guidance in using dictionaries. Data was collected through questionnaires and analyzed by SPSS 15.0. Findings indicate…

Using Different Types of Dictionaries for Improving EFL Reading Comprehension and Vocabulary Learning

ERIC Educational Resources Information Center

Alharbi, Majed A.

2016-01-01

This study investigated the effects of monolingual book dictionaries, popup dictionaries, and type-in dictionaries on improving reading comprehension and vocabulary learning in an EFL program. An experimental design involving four groups and a post-test was chosen for the experiment: (1) pop-up dictionary (experimental group 1); (2) type-in…

Students Working with an English Learners' Dictionary on CD-ROM.

ERIC Educational Resources Information Center

Winkler, Birgit

This paper examines the growing literature on pedagogical lexicography and the growing focus on how well the learner uses the dictionary in second language learning. Dictionaries are becoming more user-friendly. This study used the writing task to reveal new insights into how students use a CD-ROM dictionary. It found a lack of dictionary-using…

The Effects of Dictionary Use on the Vocabulary Learning Strategies Used by Language Learners of Spanish.

ERIC Educational Resources Information Center

Hsien-jen, Chin

This study investigated the effects of dictionary use on the vocabulary learning strategies used by intermediate college-level Spanish learners to understand new vocabulary items in a reading test. Participants were randomly assigned to one of three groups: control (without a dictionary), bilingual dictionary (using a Spanish-English dictionary),…

Resilience - A Concept

DTIC Science & Technology

2016-04-05

dictionary ]. Retrieved from http://www.investopedia.com/terms/b/blackbox.asp Bodeau, D., Brtis, J., Graubart, R., & Salwen, J. (2013). Resiliency...techniques for systems-of-systems (Report No. 13-3513). Bedford, MA: The MITRE Corporation. Confidence, (n.d.). In Oxford dictionaries [Online dictionary ...Acquisition, Technology and Logistics. Holistic Strategy Approach. (n.d.). In BusinessDictionary.com [Online business dictionary ]. Retrieved from http

Tug fleet and ground operations schedules and controls. Volume 3: Program cost estimates

NASA Technical Reports Server (NTRS)

1975-01-01

Cost data for the tug DDT&E and operations phases are presented. Option 6 is the recommended option selected from seven options considered and was used as the basis for ground processing estimates. Option 6 provides for processing the tug in a factory clean environment in the low bay area of VAB with subsequent cleaning to visibly clean. The basis and results of the trade study to select Option 6 processing plan is included. Cost estimating methodology, a work breakdown structure, and a dictionary of WBS definitions is also provided.

Improving the Incoherence of a Learned Dictionary via Rank Shrinkage.

PubMed

Ubaru, Shashanka; Seghouane, Abd-Krim; Saad, Yousef

2017-01-01

This letter considers the problem of dictionary learning for sparse signal representation whose atoms have low mutual coherence. To learn such dictionaries, at each step, we first update the dictionary using the method of optimal directions (MOD) and then apply a dictionary rank shrinkage step to decrease its mutual coherence. In the rank shrinkage step, we first compute a rank 1 decomposition of the column-normalized least squares estimate of the dictionary obtained from the MOD step. We then shrink the rank of this learned dictionary by transforming the problem of reducing the rank to a nonnegative garrotte estimation problem and solving it using a path-wise coordinate descent approach. We establish theoretical results that show that the rank shrinkage step included will reduce the coherence of the dictionary, which is further validated by experimental results. Numerical experiments illustrating the performance of the proposed algorithm in comparison to various other well-known dictionary learning algorithms are also presented.

The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank

PubMed Central

Westbrook, John D.; Shao, Chenghua; Feng, Zukang; Zhuravleva, Marina; Velankar, Sameer; Young, Jasmine

2015-01-01

Summary: The Chemical Component Dictionary (CCD) is a chemical reference data resource that describes all residue and small molecule components found in Protein Data Bank (PDB) entries. The CCD contains detailed chemical descriptions for standard and modified amino acids/nucleotides, small molecule ligands and solvent molecules. Each chemical definition includes descriptions of chemical properties such as stereochemical assignments, chemical descriptors, systematic chemical names and idealized coordinates. The content, preparation, validation and distribution of this CCD chemical reference dataset are described. Availability and implementation: The CCD is updated regularly in conjunction with the scheduled weekly release of new PDB structure data. The CCD and amino acid variant reference datasets are hosted in the public PDB ftp repository at ftp://ftp.wwpdb.org/pub/pdb/data/monomers/components.cif.gz, ftp://ftp.wwpdb.org/pub/pdb/data/monomers/aa-variants-v1.cif.gz, and its mirror sites, and can be accessed from http://wwpdb.org. Contact: jwest@rcsb.rutgers.edu. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25540181

The Making of the "Oxford English Dictionary."

ERIC Educational Resources Information Center

Winchester, Simon

2003-01-01

Summarizes remarks made to open the Gallaudet University conference on Dictionaries and the Standardization of languages. It concerns the making of what is arguably the world's greatest dictionary, "The Oxford English Dictionary." (VWL)

A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

NASA Astrophysics Data System (ADS)

Karimi, Davood; Ward, Rabab K.

2016-03-01

Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

Dictionary Approaches to Image Compression and Reconstruction

NASA Technical Reports Server (NTRS)

Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

1998-01-01

This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Dictionary Approaches to Image Compression and Reconstruction

NASA Technical Reports Server (NTRS)

Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

1998-01-01

This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as lambda, are discrete time signals, where y represents the dictionary index. A dictionary with a collection of these waveforms Is typically complete or over complete. Given such a dictionary, the goal is to obtain a representation Image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

The ABCs of Data Dictionaries

ERIC Educational Resources Information Center

Gould, Tate; Nicholas, Amy; Blandford, William; Ruggiero, Tony; Peters, Mary; Thayer, Sara

2014-01-01

This overview of the basic components of a data dictionary is designed to educate and inform IDEA Part C and Part B 619 state staff about the purpose and benefits of having up-to-date data dictionaries for their data systems. This report discusses the following topics: (1) What Is a Data Dictionary?; (2) Why Is a Data Dictionary Needed and How Can…

Evaluating Online Dictionaries From Faculty Prospective: A Case Study Performed On English Faculty Members At King Saud University--Wadi Aldawaser Branch

ERIC Educational Resources Information Center

Abouserie, Hossam Eldin Mohamed Refaat

2010-01-01

The purpose of this study was to evaluate online dictionaries from faculty prospective. The study tried to obtain in depth information about various forms of dictionaries the faculty used; degree of awareness and accessing online dictionaries; types of online dictionaries accessed; basic features of information provided; major benefits gained…

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

Xu, Q; Han, H; Xing, L

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, amore » conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning based method.« less

A dictionary to identify small molecules and drugs in free text.

PubMed

Hettne, Kristina M; Stierum, Rob H; Schuemie, Martijn J; Hendriksen, Peter J M; Schijvenaars, Bob J A; Mulligen, Erik M van; Kleinjans, Jos; Kors, Jan A

2009-11-15

From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary. The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

PubMed Central

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-01-01

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods. PMID:27669250

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks.

PubMed

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-09-22

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It's theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

The Dynameomics Entropy Dictionary: A Large-Scale Assessment of Conformational Entropy across Protein Fold Space.

PubMed

Towse, Clare-Louise; Akke, Mikael; Daggett, Valerie

2017-04-27

Molecular dynamics (MD) simulations contain considerable information with regard to the motions and fluctuations of a protein, the magnitude of which can be used to estimate conformational entropy. Here we survey conformational entropy across protein fold space using the Dynameomics database, which represents the largest existing data set of protein MD simulations for representatives of essentially all known protein folds. We provide an overview of MD-derived entropies accounting for all possible degrees of dihedral freedom on an unprecedented scale. Although different side chains might be expected to impose varying restrictions on the conformational space that the backbone can sample, we found that the backbone entropy and side chain size are not strictly coupled. An outcome of these analyses is the Dynameomics Entropy Dictionary, the contents of which have been compared with entropies derived by other theoretical approaches and experiment. As might be expected, the conformational entropies scale linearly with the number of residues, demonstrating that conformational entropy is an extensive property of proteins. The calculated conformational entropies of folding agree well with previous estimates. Detailed analysis of specific cases identifies deviations in conformational entropy from the average values that highlight how conformational entropy varies with sequence, secondary structure, and tertiary fold. Notably, α-helices have lower entropy on average than do β-sheets, and both are lower than coil regions.

Innovation Engine for Blog Spaces

DTIC Science & Technology

2011-09-01

183 7.2.2 Architecture for mining Wikipedia as a sense-annotated corpus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183...are mined from a corpus by dictionary learning, and the representation is com- puted by sparse coding (Sec. 5.5). The topics can be embedded into a...intend to deter- mine the exact sense of a word whose surface form is unknown. This generalizes the original word sense disambiguation problem since we

Developing a National-Level Concept Dictionary for EHR Implementations in Kenya.

PubMed

Keny, Aggrey; Wanyee, Steven; Kwaro, Daniel; Mulwa, Edwin; Were, Martin C

2015-01-01

The increasing adoption of Electronic Health Records (EHR) by developing countries comes with the need to develop common terminology standards to assure semantic interoperability. In Kenya, where the Ministry of Health has rolled out an EHR at 646 sites, several challenges have emerged including variable dictionaries across implementations, inability to easily share data across systems, lack of expertise in dictionary management, lack of central coordination and custody of a terminology service, inadequately defined policies and processes, insufficient infrastructure, among others. A Concept Working Group was constituted to address these challenges. The country settled on a common Kenya data dictionary, initially derived as a subset of the Columbia International eHealth Laboratory (CIEL)/Millennium Villages Project (MVP) dictionary. The initial dictionary scope largely focuses on clinical needs. Processes and policies around dictionary management are being guided by the framework developed by Bakhshi-Raiez et al. Technical and infrastructure-based approaches are also underway to streamline workflow for dictionary management and distribution across implementations. Kenya's approach on comprehensive common dictionary can serve as a model for other countries in similar settings.

The Use of the Medical Dictionary for Regulatory Activities in the Identification of Mitochondrial Dysfunction in HIV-Infected Children.

PubMed

Chernoff, Miriam; Ford-Chatterton, Heather; Crain, Marilyn J

2012-10-01

To demonstrate the utility of a medical terminology-based method for identifying cases of possible mitochondrial dysfunction (MD) in a large cohort of youths with perinatal HIV infection and to describe the scoring algorithms. Medical Dictionary for Regulatory Activities (MedDRA) ® version 6 terminology was used to query clinical criteria for mitochondrial dysfunction by two published classifications, the Enquête Périnatale Française (EPF) and the Mitochondrial Disease Classification (MDC). Data from 2,931 participants with perinatal HIV infection on PACTG 219/219C were analyzed. Data were qualified for severity and persistence, after which clinical reviews of MedDRA-coded and other study data were performed. Of 14,000 data records captured by the EPF MedDRA query, there were 3,331 singular events. Of 18,000 captured by the MDC query, there were 3,841 events. Ten clinicians blindly reviewed non MedDRA-coded supporting data for 15 separate clinical conditions. We used the Statistical Analysis System (SAS) language to code scoring algorithms. 768 participants (26%) met the EPF case definition of possible MD; 694 (24%) met the MDC case definition, and 480 (16%) met both definitions. Subjective application of codes could have affected our results. MedDRA terminology does not include indicators of severity or persistence. Version 6.0 of MedDRA did not include Standard MedDRA Queries, which would have reduced the time needed to map MedDRA terms to EPF and MDC criteria. Together with a computer-coded scoring algorithm, MedDRA terminology enabled identification of potential MD based on clinical data from almost 3000 children with substantially less effort than a case by case review. The article is accessible to readers with a background in statistical hypothesis testing. An exposure to public health issues is useful but not strictly necessary.

The Use of the Medical Dictionary for Regulatory Activities in the Identification of Mitochondrial Dysfunction in HIV-Infected Children

PubMed Central

Chernoff, Miriam; Ford-Chatterton, Heather; Crain, Marilyn J.

2012-01-01

Objective To demonstrate the utility of a medical terminology-based method for identifying cases of possible mitochondrial dysfunction (MD) in a large cohort of youths with perinatal HIV infection and to describe the scoring algorithms. Methods Medical Dictionary for Regulatory Activities (MedDRA)® version 6 terminology was used to query clinical criteria for mitochondrial dysfunction by two published classifications, the Enquête Périnatale Française (EPF) and the Mitochondrial Disease Classification (MDC). Data from 2,931 participants with perinatal HIV infection on PACTG 219/219C were analyzed. Data were qualified for severity and persistence, after which clinical reviews of MedDRA-coded and other study data were performed. Results Of 14,000 data records captured by the EPF MedDRA query, there were 3,331 singular events. Of 18,000 captured by the MDC query, there were 3,841 events. Ten clinicians blindly reviewed non MedDRA-coded supporting data for 15 separate clinical conditions. We used the Statistical Analysis System (SAS) language to code scoring algorithms. 768 participants (26%) met the EPF case definition of possible MD; 694 (24%) met the MDC case definition, and 480 (16%) met both definitions. Limitations Subjective application of codes could have affected our results. MedDRA terminology does not include indicators of severity or persistence. Version 6.0 of MedDRA did not include Standard MedDRA Queries, which would have reduced the time needed to map MedDRA terms to EPF and MDC criteria. Conclusion Together with a computer-coded scoring algorithm, MedDRA terminology enabled identification of potential MD based on clinical data from almost 3000 children with substantially less effort than a case by case review. The article is accessible to readers with a background in statistical hypothesis testing. An exposure to public health issues is useful but not strictly necessary. PMID:23797349

A Model-Driven, Science Data Product Registration Service

NASA Astrophysics Data System (ADS)

Hardman, S.; Ramirez, P.; Hughes, J. S.; Joyner, R.; Cayanan, M.; Lee, H.; Crichton, D. J.

2011-12-01

The Planetary Data System (PDS) has undertaken an effort to overhaul the PDS data architecture (including the data model, data structures, data dictionary, etc.) and to deploy an upgraded software system (including data services, distributed data catalog, etc.) that fully embraces the PDS federation as an integrated system while taking advantage of modern innovations in information technology (including networking capabilities, processing speeds, and software breakthroughs). A core component of this new system is the Registry Service that will provide functionality for tracking, auditing, locating, and maintaining artifacts within the system. These artifacts can range from data files and label files, schemas, dictionary definitions for objects and elements, documents, services, etc. This service offers a single reference implementation of the registry capabilities detailed in the Consultative Committee for Space Data Systems (CCSDS) Registry Reference Model White Book. The CCSDS Reference Model in turn relies heavily on the Electronic Business using eXtensible Markup Language (ebXML) standards for registry services and the registry information model, managed by the OASIS consortium. Registries are pervasive components in most information systems. For example, data dictionaries, service registries, LDAP directory services, and even databases provide registry-like services. These all include an account of informational items that are used in large-scale information systems ranging from data values such as names and codes, to vocabularies, services and software components. The problem is that many of these registry-like services were designed with their own data models associated with the specific type of artifact they track. Additionally these services each have their own specific interface for interacting with the service. This Registry Service implements the data model specified in the ebXML Registry Information Model (RIM) specification that supports the various artifacts above as well as offering the flexibility to support customer-defined artifacts. Key features for the Registry Service include: - Model-based configuration specifying customer-defined artifact types, metadata attributes to capture for each artifact type, supported associations and classification schemes. - A REST-based external interface that is accessible via the Hypertext Transfer Protocol (HTTP). - Federation of Registry Service instances allowing associations between registered artifacts across registries as well as queries for artifacts across those same registries. A federation also enables features such as replication and synchronization if desired for a given deployment. In addition to its use as a core component of the PDS, the generic implementation of the Registry Service facilitates its applicability as a core component in any science data archive or science data system.

Behavior analysis and mechanism: One is not the other

PubMed Central

Morris, Edward K.

1993-01-01

Behavior analysts have been called mechanists, and behavior analysis is said to be mechanistic; that is, they are claimed to be aligned with the philosophy of mechanism. What this means is analyzed by (a) examining standard and specialized dictionary and encyclopedia definitions and descriptions of mechanism and its cognates and (b) reviewing contemporary representations of the mechanistic worldview in the literature on the philosophy of psychology. Although the term mechanism and its cognates are sometimes an honorific (e.g., “natural science”), their standard meanings, usages, and functions in society, science, psychology, and philosophy do not aptly characterize the discipline. These terms mischaracterize how behavior analysts conceptualize (a) the behavior of their subjects and the individuals with whom they work and (b) their own behavior as scientists. Discussion is interwoven throughout about the nature of terms and definitions in science. PMID:22478129

Specifications for a Federal Information Processing Standard Data Dictionary System

NASA Technical Reports Server (NTRS)

Goldfine, A.

1984-01-01

The development of a software specification that Federal agencies may use in evaluating and selecting data dictionary systems (DDS) is discussed. To supply the flexibility needed by widely different applications and environments in the Federal Government, the Federal Information Processing Standard (FIPS) specifies a core DDS together with an optimal set of modules. The focus and status of the development project are described. Functional specifications for the FIPS DDS are examined for the dictionary, the dictionary schema, and the dictionary processing system. The DDS user interfaces and DDS software interfaces are discussed as well as dictionary administration.

Manifold optimization-based analysis dictionary learning with an ℓ1∕2-norm regularizer.

PubMed

Li, Zhenni; Ding, Shuxue; Li, Yujie; Yang, Zuyuan; Xie, Shengli; Chen, Wuhui

2018-02-01

Recently there has been increasing attention towards analysis dictionary learning. In analysis dictionary learning, it is an open problem to obtain the strong sparsity-promoting solutions efficiently while simultaneously avoiding the trivial solutions of the dictionary. In this paper, to obtain the strong sparsity-promoting solutions, we employ the ℓ 1∕2 norm as a regularizer. The very recent study on ℓ 1∕2 norm regularization theory in compressive sensing shows that its solutions can give sparser results than using the ℓ 1 norm. We transform a complex nonconvex optimization into a number of one-dimensional minimization problems. Then the closed-form solutions can be obtained efficiently. To avoid trivial solutions, we apply manifold optimization to update the dictionary directly on the manifold satisfying the orthonormality constraint, so that the dictionary can avoid the trivial solutions well while simultaneously capturing the intrinsic properties of the dictionary. The experiments with synthetic and real-world data verify that the proposed algorithm for analysis dictionary learning can not only obtain strong sparsity-promoting solutions efficiently, but also learn more accurate dictionary in terms of dictionary recovery and image processing than the state-of-the-art algorithms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emo, love and god: making sense of Urban Dictionary, a crowd-sourced online dictionary

PubMed Central

McGillivray, Barbara

2018-01-01

The Internet facilitates large-scale collaborative projects and the emergence of Web 2.0 platforms, where producers and consumers of content unify, has drastically changed the information market. On the one hand, the promise of the ‘wisdom of the crowd’ has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based information in many languages. On the other hand, the decentralized and often unmonitored environment of such projects may make them susceptible to low-quality content. In this work, we focus on Urban Dictionary, a crowd-sourced online dictionary. We combine computational methods with qualitative annotation and shed light on the overall features of Urban Dictionary in terms of growth, coverage and types of content. We measure a high presence of opinion-focused entries, as opposed to the meaning-focused entries that we expect from traditional dictionaries. Furthermore, Urban Dictionary covers many informal, unfamiliar words as well as proper nouns. Urban Dictionary also contains offensive content, but highly offensive content tends to receive lower scores through the dictionary’s voting system. The low threshold to include new material in Urban Dictionary enables quick recording of new words and new meanings, but the resulting heterogeneous content can pose challenges in using Urban Dictionary as a source to study language innovation. PMID:29892417

NMR structure calculation for all small molecule ligands and non-standard residues from the PDB Chemical Component Dictionary.

PubMed

Yilmaz, Emel Maden; Güntert, Peter

2015-09-01

An algorithm, CYLIB, is presented for converting molecular topology descriptions from the PDB Chemical Component Dictionary into CYANA residue library entries. The CYANA structure calculation algorithm uses torsion angle molecular dynamics for the efficient computation of three-dimensional structures from NMR-derived restraints. For this, the molecules have to be represented in torsion angle space with rotations around covalent single bonds as the only degrees of freedom. The molecule must be given a tree structure of torsion angles connecting rigid units composed of one or several atoms with fixed relative positions. Setting up CYANA residue library entries therefore involves, besides straightforward format conversion, the non-trivial step of defining a suitable tree structure of torsion angles, and to re-order the atoms in a way that is compatible with this tree structure. This can be done manually for small numbers of ligands but the process is time-consuming and error-prone. An automated method is necessary in order to handle the large number of different potential ligand molecules to be studied in drug design projects. Here, we present an algorithm for this purpose, and show that CYANA structure calculations can be performed with almost all small molecule ligands and non-standard amino acid residues in the PDB Chemical Component Dictionary.

Alzheimer's disease detection via automatic 3D caudate nucleus segmentation using coupled dictionary learning with level set formulation.

PubMed

Al-Shaikhli, Saif Dawood Salman; Yang, Michael Ying; Rosenhahn, Bodo

2016-12-01

This paper presents a novel method for Alzheimer's disease classification via an automatic 3D caudate nucleus segmentation. The proposed method consists of segmentation and classification steps. In the segmentation step, we propose a novel level set cost function. The proposed cost function is constrained by a sparse representation of local image features using a dictionary learning method. We present coupled dictionaries: a feature dictionary of a grayscale brain image and a label dictionary of a caudate nucleus label image. Using online dictionary learning, the coupled dictionaries are learned from the training data. The learned coupled dictionaries are embedded into a level set function. In the classification step, a region-based feature dictionary is built. The region-based feature dictionary is learned from shape features of the caudate nucleus in the training data. The classification is based on the measure of the similarity between the sparse representation of region-based shape features of the segmented caudate in the test image and the region-based feature dictionary. The experimental results demonstrate the superiority of our method over the state-of-the-art methods by achieving a high segmentation (91.5%) and classification (92.5%) accuracy. In this paper, we find that the study of the caudate nucleus atrophy gives an advantage over the study of whole brain structure atrophy to detect Alzheimer's disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dictionary Based Machine Translation from Kannada to Telugu

NASA Astrophysics Data System (ADS)

Sindhu, D. V.; Sagar, B. M.

2017-08-01

Machine Translation is a task of translating from one language to another language. For the languages with less linguistic resources like Kannada and Telugu Dictionary based approach is the best approach. This paper mainly focuses on Dictionary based machine translation for Kannada to Telugu. The proposed methodology uses dictionary for translating word by word without much correlation of semantics between them. The dictionary based machine translation process has the following sub process: Morph analyzer, dictionary, transliteration, transfer grammar and the morph generator. As a part of this work bilingual dictionary with 8000 entries is developed and the suffix mapping table at the tag level is built. This system is tested for the children stories. In near future this system can be further improved by defining transfer grammar rules.

The efficacy of dictionary use while reading for learning new words.

PubMed

Hamilton, Harley

2012-01-01

The researcher investigated the use of three types of dictionaries while reading by high school students with severe to profound hearing loss. The objective of the study was to determine the effectiveness of each type of dictionary for acquiring the meanings of unknown vocabulary in text. The three types of dictionaries were (a) an online bilingual multimedia English-American Sign Language (ASL) dictionary (OBMEAD), (b) a paper English-ASL dictionary (PBEAD), and (c) an online monolingual English dictionary (OMED). It was found that for immediate recall of target words, the OBMEAD was superior to both the PBEAD and the OMED. For later recall, no significant difference appeared between the OBMEAD and the PBEAD. For both of these, recall was statistically superior to recall for words learned via the OMED.

What Online Traditional Medicine Dictionaries Bring To English Speakers Now? Concepts or Equivalents?

PubMed Central

Fang, Lu

2018-01-01

Nowadays, more and more Chinese medicine practices are applied in the world and popularizing that becomes an urgent task. To meet the requiremets, an increasing number of Chinese - English traditional medicine dictionaries have been produced at home or abroad in recent decades. Nevertheless, the users are still struggling to spot the information in dictionaries. What traditional medicine dictionaries are needed for the English speakers now? To identify an entry model for online TCM dictionaries, I compared the entries in five printed traditional medicine dictionaries and two online ones. Based upon this, I tentatively put forward two samples, “阳经 (yángjīng)” and “阴经 (yīn jīng)”, focusing on concepts transmitting, for online Chinese - English TCM dictionaries. PMID:29875861

Label consistent K-SVD: learning a discriminative dictionary for recognition.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2013-11-01

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.

Gapped Spectral Dictionaries and Their Applications for Database Searches of Tandem Mass Spectra*

PubMed Central

Jeong, Kyowon; Kim, Sangtae; Bandeira, Nuno; Pevzner, Pavel A.

2011-01-01

Generating all plausible de novo interpretations of a peptide tandem mass (MS/MS) spectrum (Spectral Dictionary) and quickly matching them against the database represent a recently emerged alternative approach to peptide identification. However, the sizes of the Spectral Dictionaries quickly grow with the peptide length making their generation impractical for long peptides. We introduce Gapped Spectral Dictionaries (all plausible de novo interpretations with gaps) that can be easily generated for any peptide length thus addressing the limitation of the Spectral Dictionary approach. We show that Gapped Spectral Dictionaries are small thus opening a possibility of using them to speed-up MS/MS searches. Our MS-GappedDictionary algorithm (based on Gapped Spectral Dictionaries) enables proteogenomics applications (such as searches in the six-frame translation of the human genome) that are prohibitively time consuming with existing approaches. MS-GappedDictionary generates gapped peptides that occupy a niche between accurate but short peptide sequence tags and long but inaccurate full length peptide reconstructions. We show that, contrary to conventional wisdom, some high-quality spectra do not have good peptide sequence tags and introduce gapped tags that have advantages over the conventional peptide sequence tags in MS/MS database searches. PMID:21444829

Chinese-English Nuclear and Physics Dictionary.

ERIC Educational Resources Information Center

Air Force Systems Command, Wright-Patterson AFB, OH. Foreign Technology Div.

The Nuclear and Physics Dictionary is one of a series of Chinese-English technical dictionaries prepared by the Foreign Technology Division, United States Air Force Systems Command. The purpose of this dictionary is to provide rapid reference tools for translators, abstractors, and research analysts concerned with scientific and technical…

Mandarin Chinese Dictionary: English-Chinese.

ERIC Educational Resources Information Center

Wang, Fred Fangyu

This dictionary is a companion volume to the "Mandarin Chinese Dictionary (Chinese-English)" published in 1967 by Seton Hall University. The purpose of the dictionary is to help English-speaking students produce Chinese sentences in certain cultural situations by looking up the English expressions. Natural, spoken Chinese expressions within the…

Intertwining thesauri and dictionaries

NASA Technical Reports Server (NTRS)

Buchan, R. L.

1989-01-01

The use of dictionaries and thesauri in information retrieval is discussed. The structure and functions of thesauri and dictionaries are described. Particular attention is given to the format of the NASA Thesaurus. The relationship between thesauri and dictionaries, the need to regularize terminology, and the capitalization of words are examined.

MEANING DISCRIMINATION IN BILINGUAL DICTIONARIES.

ERIC Educational Resources Information Center

IANNUCCI, JAMES E.

SEMANTIC DISCRIMINATION OF POLYSEMOUS ENTRY WORDS IN BILINGUAL DICTIONARIES WAS DISCUSSED IN THE PAPER. HANDICAPS OF PRESENT BILINGUAL DICTIONARIES AND BARRIERS TO THEIR FULL UTILIZATION WERE ENUMERATED. THE AUTHOR CONCLUDED THAT (1) A BILINGUAL DICTIONARY SHOULD HAVE A DISCRIMINATION FOR EVERY TRANSLATION OF AN ENTRY WORD WHICH HAS SEVERAL…

The Use of Hyper-Reference and Conventional Dictionaries.

ERIC Educational Resources Information Center

Aust, Ronald; And Others

1993-01-01

Describes a study of 80 undergraduate foreign language learners that compared the use of a hyper-reference source incorporating an electronic dictionary and a conventional paper dictionary. Measures of consultation frequency, study time, efficiency, and comprehension are examined; bilingual and monolingual dictionary use is compared; and further…

Object Classification With Joint Projection and Low-Rank Dictionary Learning.

PubMed

Foroughi, Homa; Ray, Nilanjan; Hong Zhang

2018-02-01

For an object classification system, the most critical obstacles toward real-world applications are often caused by large intra-class variability, arising from different lightings, occlusion, and corruption, in limited sample sets. Most methods in the literature would fail when the training samples are heavily occluded, corrupted or have significant illumination or viewpoint variations. Besides, most of the existing methods and especially deep learning-based methods, need large training sets to achieve a satisfactory recognition performance. Although using the pre-trained network on a generic large-scale data set and fine-tune it to the small-sized target data set is a widely used technique, this would not help when the content of base and target data sets are very different. To address these issues simultaneously, we propose a joint projection and low-rank dictionary learning method using dual graph constraints. Specifically, a structured class-specific dictionary is learned in the low-dimensional space, and the discrimination is further improved by imposing a graph constraint on the coding coefficients, that maximizes the intra-class compactness and inter-class separability. We enforce structural incoherence and low-rank constraints on sub-dictionaries to reduce the redundancy among them, and also make them robust to variations and outliers. To preserve the intrinsic structure of data, we introduce a supervised neighborhood graph into the framework to make the proposed method robust to small-sized and high-dimensional data sets. Experimental results on several benchmark data sets verify the superior performance of our method for object classification of small-sized data sets, which include a considerable amount of different kinds of variation, and may have high-dimensional feature vectors.

Toward better public health reporting using existing off the shelf approaches: The value of medical dictionaries in automated cancer detection using plaintext medical data.

PubMed

Kasthurirathne, Suranga N; Dixon, Brian E; Gichoya, Judy; Xu, Huiping; Xia, Yuni; Mamlin, Burke; Grannis, Shaun J

2017-05-01

Existing approaches to derive decision models from plaintext clinical data frequently depend on medical dictionaries as the sources of potential features. Prior research suggests that decision models developed using non-dictionary based feature sourcing approaches and "off the shelf" tools could predict cancer with performance metrics between 80% and 90%. We sought to compare non-dictionary based models to models built using features derived from medical dictionaries. We evaluated the detection of cancer cases from free text pathology reports using decision models built with combinations of dictionary or non-dictionary based feature sourcing approaches, 4 feature subset sizes, and 5 classification algorithms. Each decision model was evaluated using the following performance metrics: sensitivity, specificity, accuracy, positive predictive value, and area under the receiver operating characteristics (ROC) curve. Decision models parameterized using dictionary and non-dictionary feature sourcing approaches produced performance metrics between 70 and 90%. The source of features and feature subset size had no impact on the performance of a decision model. Our study suggests there is little value in leveraging medical dictionaries for extracting features for decision model building. Decision models built using features extracted from the plaintext reports themselves achieve comparable results to those built using medical dictionaries. Overall, this suggests that existing "off the shelf" approaches can be leveraged to perform accurate cancer detection using less complex Named Entity Recognition (NER) based feature extraction, automated feature selection and modeling approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

The Oxford English Dictionary: A Brief History.

ERIC Educational Resources Information Center

Fritze, Ronald H.

1989-01-01

Reviews the development of English dictionaries in general and the Oxford English Dictionary (OED) in particular. The discussion covers the decision by the Philological Society to create the dictionary, the principles that guided its development, the involvement of James Augustus Henry Murray, the magnitude and progress of the project, and the…

Dictionary Making: A Case of Kiswahili Dictionaries.

ERIC Educational Resources Information Center

Mohamed, Mohamed A.

Two Swahili dictionaries and two bilingual dictionaries by the same author (one English-Swahili and one Swahili-English) are evaluated for their form and content, with illustrations offered from each. Aspects examined include: the compilation of headwords, including their meanings with relation to basic and extended meanings; treatment of…

The New Unabridged English-Persian Dictionary.

ERIC Educational Resources Information Center

Aryanpur, Abbas; Saleh, Jahan Shah

This five-volume English-Persian dictionary is based on Webster's International Dictionary (1960 and 1961) and The Shorter Oxford English Dictionary (1959); it attempts to provide Persian equivalents of all the words of Oxford and all the key-words of Webster. Pronunciation keys for the English phonetic transcription and for the difficult Persian…

Evaluating L2 Readers' Vocabulary Strategies and Dictionary Use

ERIC Educational Resources Information Center

Prichard, Caleb

2008-01-01

A review of the relevant literature concerning second language dictionary use while reading suggests that selective dictionary use may lead to improved comprehension and efficient vocabulary development. This study aims to examine the dictionary use of Japanese university students to determine just how selective they are when reading nonfiction…

Research Timeline: Dictionary Use by English Language Learners

ERIC Educational Resources Information Center

Nesi, Hilary

2014-01-01

The history of research into dictionary use tends to be characterised by small-scale studies undertaken in a variety of different contexts, rather than larger-scale, longer-term funded projects. The research conducted by dictionary publishers is not generally made public, because of its commercial sensitivity, yet because dictionary production is…

The Dictionary and Vocabulary Behavior: A Single Word or a Handful?

ERIC Educational Resources Information Center

Baxter, James

1980-01-01

To provide a context for dictionary selection, the vocabulary behavior of students is examined. Distinguishing between written and spoken English, the relation between dictionary use, classroom vocabulary behavior, and students' success in meeting their communicative needs is discussed. The choice of a monolingual English learners' dictionary is…

Phase B - final definition and preliminary design study for the initial Atmospheric Cloud Physics Laboratory (ACPL): A spacelab mission payload. Work breakdown structure for phase C/D DR-MA-06 (preliminary issue)

NASA Technical Reports Server (NTRS)

1976-01-01

The Work Breakdown Structure (WBS) and Dictionary (DR-MA-06) for initial and subsequent flights of the Atmospheric Cloud Physics Laboratory (ACPL) is presented. An attempt is made to identify specific equipment and components in each of the eleven subsystems; they are listed under the appropriate subdivisions of the WBS. The reader is cautioned that some of these components are likely to change substantially during the course of the study, and the list provided should only be considered representative.

Differences and discrepancies between 2005 and 2008 Abbreviated Injury Scale versions - time to standardise

PubMed Central

2012-01-01

The aim of this letter is to facilitate the standardisation of Abbreviated Injury Scale (AIS) codesets used to code injuries in trauma registries. We have compiled a definitive list of the changes which have been implemented between the AIS 2005 and Update 2008 versions. While the AIS 2008 codeset appears to have remained consistent since its release, we have identified discrepancies between the codesets in copies of AIS 2005 dictionaries. As a result, we recommend that use of the AIS 2005 should be discontinued in favour of the Update 2008 version. PMID:22301065

Differences and discrepancies between 2005 and 2008 Abbreviated Injury Scale versions - time to standardise.

PubMed

Ringdal, Kjetil G; Hestnes, Morten; Palmer, Cameron S

2012-02-02

The aim of this letter is to facilitate the standardisation of Abbreviated Injury Scale (AIS) codesets used to code injuries in trauma registries. We have compiled a definitive list of the changes which have been implemented between the AIS 2005 and Update 2008 versions. While the AIS 2008 codeset appears to have remained consistent since its release, we have identified discrepancies between the codesets in copies of AIS 2005 dictionaries. As a result, we recommend that use of the AIS 2005 should be discontinued in favour of the Update 2008 version.

Signalling crosstalk in plants: emerging issues.

PubMed

Taylor, Jane E; McAinsh, Martin R

2004-01-01

The Oxford English Dictionary defines crosstalk as 'unwanted transfer of signals between communication channels'. How does this definition relate to the way in which we view the organization and function of signalling pathways? Recent advances in the field of plant signalling have challenged the traditional view of a signalling transduction cascade as isolated linear pathways. Instead the picture emerging of the mechanisms by which plants transduce environmental signals is of the interaction between transduction chains. The manner in which these interactions occur (and indeed whether the transfer of these signals is 'unwanted' or beneficial) is currently the topic of intense research.

The River Danube: An Examination of Navigation on the River

NASA Astrophysics Data System (ADS)

Cooper, R. W.

One of the definitions of Navigation that gets little attention in this Institute is (Oxford English Dictionary), and which our French friends call La Navigation. I have always found this subject fascinating, and have previously navigated the Rivers Mekong, Irrawaddy, Hooghly, Indus, Shatt-al-Arab, Savannah and RhMainKanal (RMDK) and the River Danube, a distance of approximately 4000 km. This voyage has only recently become possible with the opening of the connecting RMDK at the end of 1992, but has been made little use of because of the civil war in the former Yugoslavia.

Multivariate temporal dictionary learning for EEG.

PubMed

Barthélemy, Q; Gouy-Pailler, C; Isaac, Y; Souloumiac, A; Larue, A; Mars, J I

2013-04-30

This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG signals, this article proposes a data-driven method to obtain an adapted dictionary. To reach an efficient dictionary learning, appropriate spatial and temporal modeling is required. Inter-channels links are taken into account in the spatial multivariate model, and shift-invariance is used for the temporal model. Multivariate learned kernels are informative (a few atoms code plentiful energy) and interpretable (the atoms can have a physiological meaning). Using real EEG data, the proposed method is shown to outperform the classical multichannel matching pursuit used with a Gabor dictionary, as measured by the representative power of the learned dictionary and its spatial flexibility. Moreover, dictionary learning can capture interpretable patterns: this ability is illustrated on real data, learning a P300 evoked potential. Copyright © 2013 Elsevier B.V. All rights reserved.

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

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

Concept dictionary creation and maintenance under resource constraints: lessons from the AMPATH Medical Record System.

PubMed

Were, Martin C; Mamlin, Burke W; Tierney, William M; Wolfe, Ben; Biondich, Paul G

2007-10-11

The challenges of creating and maintaining concept dictionaries are compounded in resource-limited settings. Approaches to alleviate this burden need to be based on information derived in these settings. We created a concept dictionary and evaluated new concept proposals for an open source EMR in a resource-limited setting. Overall, 87% of the concepts in the initial dictionary were used. There were 5137 new concepts proposed, with 77% of these proposed only once. Further characterization of new concept proposals revealed that 41% were due to deficiency in the existing dictionary, and 19% were synonyms to existing concepts. 25% of the requests contained misspellings, 41% were complex terms, and 17% were ambiguous. Given the resource-intensive nature of dictionary creation and maintenance, there should be considerations for centralizing the concept dictionary service, using standards, prioritizing concept proposals, and redesigning the user-interface to reduce this burden in settings with limited resources.

Concept Dictionary Creation and Maintenance Under Resource Constraints: Lessons from the AMPATH Medical Record System

PubMed Central

Were, Martin C.; Mamlin, Burke W.; Tierney, William M.; Wolfe, Ben; Biondich, Paul G.

2007-01-01

The challenges of creating and maintaining concept dictionaries are compounded in resource-limited settings. Approaches to alleviate this burden need to be based on information derived in these settings. We created a concept dictionary and evaluated new concept proposals for an open source EMR in a resource-limited setting. Overall, 87% of the concepts in the initial dictionary were used. There were 5137 new concepts proposed, with 77% of these proposed only once. Further characterization of new concept proposals revealed that 41% were due to deficiency in the existing dictionary, and 19% were synonyms to existing concepts. 25% of the requests contained misspellings, 41% were complex terms, and 17% were ambiguous. Given the resource-intensive nature of dictionary creation and maintenance, there should be considerations for centralizing the concept dictionary service, using standards, prioritizing concept proposals, and redesigning the user-interface to reduce this burden in settings with limited resources. PMID:18693945

NHEXAS PHASE I ARIZONA STUDY--STANDARD OPERATING PROCEDURE FOR THE GENERATION AND OPERATION OF DATA DICTIONARIES (UA-D-4.0)

EPA Science Inventory

The purpose of this SOP is to provide a standard method for the writing of data dictionaries. This procedure applies to the dictionaries used during the Arizona NHEXAS project and the "Border" study. Keywords: guidelines; data dictionaries.

The National Human Exposure Assessme...

The Influence of Electronic Dictionaries on Vocabulary Knowledge Extension

ERIC Educational Resources Information Center

Rezaei, Mojtaba; Davoudi, Mohammad

2016-01-01

Vocabulary learning needs special strategies in language learning process. The use of dictionaries is a great help in vocabulary learning and nowadays the emergence of electronic dictionaries has added a new and valuable resource for vocabulary learning. The present study aims to explore the influence of Electronic Dictionaries (ED) Vs. Paper…

Should Dictionaries Be Used in Translation Tests and Examinations?

ERIC Educational Resources Information Center

Mahmoud, Abdulmoneim

2017-01-01

Motivated by the conflicting views regarding the use of the dictionary in translation tests and examinations this study was intended to verify the dictionary-free vs dictionary-based translation hypotheses. The subjects were 135 Arabic-speaking male and female EFL third-year university students. A group consisting of 62 students translated a text…

Corpora and Collocations in Chinese-English Dictionaries for Chinese Users

ERIC Educational Resources Information Center

Xia, Lixin

2015-01-01

The paper identifies the major problems of the Chinese-English dictionary in representing collocational information after an extensive survey of nine dictionaries popular among Chinese users. It is found that the Chinese-English dictionary only provides the collocation types of "v+n" and "v+n," but completely ignores those of…

The Creation of Learner-Centred Dictionaries for Endangered Languages: A Rotuman Example

ERIC Educational Resources Information Center

Vamarasi, M.

2014-01-01

This article examines the creation of dictionaries for endangered languages (ELs). Though each dictionary is uniquely prepared for its users, all dictionaries should be based on sound principles of vocabulary learning, including the importance of lexical chunks, as emphasised by Michael Lewis in his "Lexical Approach." Many of the…

Evaluating Bilingual and Monolingual Dictionaries for L2 Learners.

ERIC Educational Resources Information Center

Hunt, Alan

1997-01-01

A discussion of dictionaries and their use for second language (L2) learning suggests that lack of computerized modern language corpora can adversely affect bilingual dictionaries, commonly used by L2 learners, and shows how use of such corpora has benefitted two contemporary monolingual L2 learner dictionaries (1995 editions of the Longman…

Developing a hybrid dictionary-based bio-entity recognition technique.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Discriminative Bayesian Dictionary Learning for Classification.

PubMed

Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

2016-12-01

We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

PubMed

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Developing a hybrid dictionary-based bio-entity recognition technique

PubMed Central

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

PubMed

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems.

PubMed

Ravishankar, Saiprasad; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-12-01

The sparsity of signals in a transform domain or dictionary has been exploited in applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis dictionaries has shown promise compared to analytical dictionary models. However, dictionary learning problems are typically non-convex and NP-hard, and the usual alternating minimization approaches for these problems are often computationally expensive, with the computations dominated by the NP-hard synthesis sparse coding step. This paper exploits the ideas that drive algorithms such as K-SVD, and investigates in detail efficient methods for aggregate sparsity penalized dictionary learning by first approximating the data with a sum of sparse rank-one matrices (outer products) and then using a block coordinate descent approach to estimate the unknowns. The resulting block coordinate descent algorithms involve efficient closed-form solutions. Furthermore, we consider the problem of dictionary-blind image reconstruction, and propose novel and efficient algorithms for adaptive image reconstruction using block coordinate descent and sum of outer products methodologies. We provide a convergence study of the algorithms for dictionary learning and dictionary-blind image reconstruction. Our numerical experiments show the promising performance and speedups provided by the proposed methods over previous schemes in sparse data representation and compressed sensing-based image reconstruction.

Cross-View Action Recognition via Transferable Dictionary Learning.

PubMed

Zheng, Jingjing; Jiang, Zhuolin; Chellappa, Rama

2016-05-01

Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. In the first approach, we learn a set of view-specific dictionaries where each dictionary corresponds to one camera view. These dictionaries are learned simultaneously from the sets of correspondence videos taken at different views with the aim of encouraging each video in the set to have the same sparse representation. In the second approach, we additionally learn a common dictionary shared by different views to model view-shared features. This approach represents the videos in each view using a view-specific dictionary and the common dictionary. More importantly, it encourages the set of videos taken from the different views of the same action to have the similar sparse representations. The learned common dictionary not only has the capability to represent actions from unseen views, but also makes our approach effective in a semi-supervised setting where no correspondence videos exist and only a few labeled videos exist in the target view. The extensive experiments using three public datasets demonstrate that the proposed approach outperforms recently developed approaches for cross-view action recognition.

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation.

PubMed

Grossi, Giuliano; Lanzarotti, Raffaella; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD's robustness and wide applicability.

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems

PubMed Central

Ravishankar, Saiprasad; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

The sparsity of signals in a transform domain or dictionary has been exploited in applications such as compression, denoising and inverse problems. More recently, data-driven adaptation of synthesis dictionaries has shown promise compared to analytical dictionary models. However, dictionary learning problems are typically non-convex and NP-hard, and the usual alternating minimization approaches for these problems are often computationally expensive, with the computations dominated by the NP-hard synthesis sparse coding step. This paper exploits the ideas that drive algorithms such as K-SVD, and investigates in detail efficient methods for aggregate sparsity penalized dictionary learning by first approximating the data with a sum of sparse rank-one matrices (outer products) and then using a block coordinate descent approach to estimate the unknowns. The resulting block coordinate descent algorithms involve efficient closed-form solutions. Furthermore, we consider the problem of dictionary-blind image reconstruction, and propose novel and efficient algorithms for adaptive image reconstruction using block coordinate descent and sum of outer products methodologies. We provide a convergence study of the algorithms for dictionary learning and dictionary-blind image reconstruction. Our numerical experiments show the promising performance and speedups provided by the proposed methods over previous schemes in sparse data representation and compressed sensing-based image reconstruction. PMID:29376111

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

14 CFR 1214.701 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Definitions. 1214.701 Section 1214.701 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT The Authority of the Space Shuttle Commander § 1214.701 Definitions. (a) Space Shuttle Elements consists of the Orbiter, an External...

14 CFR 1214.701 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Definitions. 1214.701 Section 1214.701 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT The Authority of the Space Shuttle Commander § 1214.701 Definitions. (a) Space Shuttle Elements consists of the Orbiter, an External...

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

Using Bilingual Dictionaries.

ERIC Educational Resources Information Center

Thompson, Geoff

1987-01-01

Monolingual dictionaries have serious disadvantages in many language teaching situations; bilingual dictionaries are potentially more efficient and more motivating sources of information for language learners. (Author/CB)

Patient-Specific Seizure Detection in Long-Term EEG Using Signal-Derived Empirical Mode Decomposition (EMD)-based Dictionary Approach.

PubMed

Kaleem, Muhammad; Gurve, Dharmendra; Guergachi, Aziz; Krishnan, Sridhar

2018-06-25

The objective of the work described in this paper is development of a computationally efficient methodology for patient-specific automatic seizure detection in long-term multi-channel EEG recordings. Approach: A novel patient-specific seizure detection approach based on signal-derived Empirical Mode Decomposition (EMD)-based dictionary approach is proposed. For this purpose, we use an empirical framework for EMD-based dictionary creation and learning, inspired by traditional dictionary learning methods, in which the EMD-based dictionary is learned from the multi-channel EEG data being analyzed for automatic seizure detection. We present the algorithm for dictionary creation and learning, whose purpose is to learn dictionaries with a small number of atoms. Using training signals belonging to seizure and non-seizure classes, an initial dictionary, termed as the raw dictionary, is formed. The atoms of the raw dictionary are composed of intrinsic mode functions obtained after decomposition of the training signals using the empirical mode decomposition algorithm. The raw dictionary is then trained using a learning algorithm, resulting in a substantial decrease in the number of atoms in the trained dictionary. The trained dictionary is then used for automatic seizure detection, such that coefficients of orthogonal projections of test signals against the trained dictionary form the features used for classification of test signals into seizure and non-seizure classes. Thus no hand-engineered features have to be extracted from the data as in traditional seizure detection approaches. Main results: The performance of the proposed approach is validated using the CHB-MIT benchmark database, and averaged accuracy, sensitivity and specificity values of 92.9%, 94.3% and 91.5%, respectively, are obtained using support vector machine classifier and five-fold cross-validation method. These results are compared with other approaches using the same database, and the suitability of the approach for seizure detection in long-term multi-channel EEG recordings is discussed. Significance: The proposed approach describes a computationally efficient method for automatic seizure detection in long-term multi-channel EEG recordings. The method does not rely on hand-engineered features, as are required in traditional approaches. Furthermore, the approach is suitable for scenarios where the dictionary once formed and trained can be used for automatic seizure detection of newly recorded data, making the approach suitable for long-term multi-channel EEG recordings. © 2018 IOP Publishing Ltd.

Grammar Coding in the "Oxford Advanced Learner's Dictionary of Current English."

ERIC Educational Resources Information Center

Wekker, Herman

1992-01-01

Focuses on the revised system of grammar coding for verbs in the fourth edition of the "Oxford Advanced Learner's Dictionary of Current English" (OALD4), comparing it with two other similar dictionaries. It is shown that the OALD4 is found to be more favorable on many criteria than the other comparable dictionaries. (16 references) (VWL)

A Study on the Use of Mobile Dictionaries in Vocabulary Teaching

ERIC Educational Resources Information Center

Aslan, Erdinç

2016-01-01

In recent years, rapid developments in technology have placed books and notebooks into the mobile phones and tablets and also the dictionaries into these small boxes. Giant dictionaries, which we once barely managed to carry, have been replaced by mobile dictionaries through which we can reach any words we want with only few touches. Mobile…

Letters to a Dictionary: Competing Views of Language in the Reception of "Webster's Third New International Dictionary"

ERIC Educational Resources Information Center

Bello, Anne Pence

2013-01-01

The publication of "Webster's Third New International Dictionary" in September 1961 set off a national controversy about dictionaries and language that ultimately included issues related to linguistics and English education. The negative reviews published in the press about the "Third" have shaped beliefs about the nature of…

Effects of Printed, Pocket Electronic, and Online Dictionaries on High School Students' English Vocabulary Retention

ERIC Educational Resources Information Center

Chiu, Li-Ling; Liu, Gi-Zen

2013-01-01

This study obtained empirical evidence regarding the effects of using printed dictionaries (PD), pocket electronic dictionaries (PED), and online type-in dictionaries (OTID) on English vocabulary retention at a junior high school. A mixed-methods research methodology was adopted in this study. Thirty-three seventh graders were asked to use all…

The Efficacy of Dictionary Use while Reading for Learning New Words

ERIC Educational Resources Information Center

Hamilton, Harley

2012-01-01

The researcher investigated the use of three types of dictionaries while reading by high school students with severe to profound hearing loss. The objective of the study was to determine the effectiveness of each type of dictionary for acquiring the meanings of unknown vocabulary in text. The three types of dictionaries were (a) an online…

A Selected Bibliography of Dictionaries. General Information Series, No. 9. Indochinese Refugee Education Guides. Revised.

ERIC Educational Resources Information Center

Center for Applied Linguistics, Arlington, VA.

The purpose of this bulletin is to provide the American teacher or sponsor with information on the use, limitations and availability of dictionaries that can be used by Indochinese refugees. The introductory material contains descriptions of both monolingual and bilingual dictionaries, a discussion of the inadequacies of bilingual dictionaries in…

Dictionaries Can Help Writing--If Students Know How To Use Them.

ERIC Educational Resources Information Center

Jacobs, George M.

A study investigated whether instruction in how to use a dictionary led to improved second language performance and greater dictionary use among English majors (N=54) in a reading and writing course at a Thai university. One of three participating classes was instructed in the use of a monolingual learner's dictionary. A passage correction test…

Dictionary-Based Tensor Canonical Polyadic Decomposition

NASA Astrophysics Data System (ADS)

Cohen, Jeremy Emile; Gillis, Nicolas

2018-04-01

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

Remote Sensing Terminology in a Global and Knowledge-Based World

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana

The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy, GIS, etc. Our belief is that the elaboration of bilingual and multilingual dictionaries and glossaries in this spreading, most technically advanced and promising field of human expertise is of great practical importance. The work on an English-Bulgarian Dictionary of Remote Sensing Terms is described including considerations on its scope, structure, information content, sellection of terms, and etc. The vision builds upon previous national and international experience and makes use of ongoing activities on the subject. Any interest in cooperation and initiating suchlike collaborative projects is welcome and highly appreciated.

The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank.

PubMed

Westbrook, John D; Shao, Chenghua; Feng, Zukang; Zhuravleva, Marina; Velankar, Sameer; Young, Jasmine

2015-04-15

The Chemical Component Dictionary (CCD) is a chemical reference data resource that describes all residue and small molecule components found in Protein Data Bank (PDB) entries. The CCD contains detailed chemical descriptions for standard and modified amino acids/nucleotides, small molecule ligands and solvent molecules. Each chemical definition includes descriptions of chemical properties such as stereochemical assignments, chemical descriptors, systematic chemical names and idealized coordinates. The content, preparation, validation and distribution of this CCD chemical reference dataset are described. The CCD is updated regularly in conjunction with the scheduled weekly release of new PDB structure data. The CCD and amino acid variant reference datasets are hosted in the public PDB ftp repository at ftp://ftp.wwpdb.org/pub/pdb/data/monomers/components.cif.gz, ftp://ftp.wwpdb.org/pub/pdb/data/monomers/aa-variants-v1.cif.gz, and its mirror sites, and can be accessed from http://wwpdb.org. jwest@rcsb.rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Oak Ridge Environmental Information System (OREIS) functional system design document

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

Birchfield, T.E.; Brown, M.O.; Coleman, P.R.

1994-03-01

The OREIS Functional System Design document provides a detailed functional description of the Oak Ridge Environmental Information System (OREIS). It expands the system requirements defined in the OREIS Phase 1-System Definition Document (ES/ER/TM-34). Documentation of OREIS development is based on the Automated Data Processing System Development Methodology, a Martin Marietta Energy Systems, Inc., procedure written to assist in developing scientific and technical computer systems. This document focuses on the development of the functional design of the user interface, which includes the integration of commercial applications software. The data model and data dictionary are summarized briefly; however, the Data Management Planmore » for OREIS (ES/ER/TM-39), a companion document to the Functional System Design document, provides the complete data dictionary and detailed descriptions of the requirements for the data base structure. The OREIS system will provide the following functions, which are executed from a Menu Manager: (1) preferences, (2) view manager, (3) macro manager, (4) data analysis (assisted analysis and unassisted analysis), and (5) spatial analysis/map generation (assisted ARC/INFO and unassisted ARC/INFO). Additional functionality includes interprocess communications, which handle background operations of OREIS.« less

Effective real-time vehicle tracking using discriminative sparse coding on local patches

NASA Astrophysics Data System (ADS)

Chen, XiangJun; Ye, Feiyue; Ruan, Yaduan; Chen, Qimei

2016-01-01

A visual tracking framework that provides an object detector and tracker, which focuses on effective and efficient visual tracking in surveillance of real-world intelligent transport system applications, is proposed. The framework casts the tracking task as problems of object detection, feature representation, and classification, which is different from appearance model-matching approaches. Through a feature representation of discriminative sparse coding on local patches called DSCLP, which trains a dictionary on local clustered patches sampled from both positive and negative datasets, the discriminative power and robustness has been improved remarkably, which makes our method more robust to a complex realistic setting with all kinds of degraded image quality. Moreover, by catching objects through one-time background subtraction, along with offline dictionary training, computation time is dramatically reduced, which enables our framework to achieve real-time tracking performance even in a high-definition sequence with heavy traffic. Experiment results show that our work outperforms some state-of-the-art methods in terms of speed, accuracy, and robustness and exhibits increased robustness in a complex real-world scenario with degraded image quality caused by vehicle occlusion, image blur of rain or fog, and change in viewpoint or scale.

Capturing the semiotic relationship between terms

NASA Astrophysics Data System (ADS)

Hargood, Charlie; Millard, David E.; Weal, Mark J.

2010-04-01

Tags describing objects on the web are often treated as facts about a resource, whereas it is quite possible that they represent more subjective observations. Existing methods of term expansion expand terms based on dictionary definitions or statistical information on term occurrence. Here we propose the use of a thematic model for term expansion based on semiotic relationships between terms; this has been shown to improve a system's thematic understanding of content and tags and to tease out the more subjective implications of those tags. Such a system relies on a thematic model that must be made by hand. In this article, we explore a method to capture a semiotic understanding of particular terms using a rule-based guide to authoring a thematic model. Experimentation shows that it is possible to capture valid definitions that can be used for semiotic term expansion but that the guide itself may not be sufficient to support this on a large scale. We argue that whilst the formation of super definitions will mitigate some of these problems, the development of an authoring support tool may be necessary to solve others.

On describing human white matter anatomy: the white matter query language.

PubMed

Wassermann, Demian; Makris, Nikos; Rathi, Yogesh; Shenton, Martha; Kikinis, Ron; Kubicki, Marek; Westin, Carl-Fredrik

2013-01-01

The main contribution of this work is the careful syntactical definition of major white matter tracts in the human brain based on a neuroanatomist's expert knowledge. We present a technique to formally describe white matter tracts and to automatically extract them from diffusion MRI data. The framework is based on a novel query language with a near-to-English textual syntax. This query language allows us to construct a dictionary of anatomical definitions describing white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This enables automated coherent labeling of white matter anatomy across subjects. We use our method to encode anatomical knowledge in human white matter describing 10 association and 8 projection tracts per hemisphere and 7 commissural tracts. The technique is shown to be comparable in accuracy to manual labeling. We present results applying this framework to create a white matter atlas from 77 healthy subjects, and we use this atlas in a proof-of-concept study to detect tract changes specific to schizophrenia.

Advanced transportation system studies technical area 2 (TA-2): Heavy lift launch vehicle development. volume 3; Program Cost estimates

NASA Technical Reports Server (NTRS)

McCurry, J. B.

1995-01-01

The purpose of the TA-2 contract was to provide advanced launch vehicle concept definition and analysis to assist NASA in the identification of future launch vehicle requirements. Contracted analysis activities included vehicle sizing and performance analysis, subsystem concept definition, propulsion subsystem definition (foreign and domestic), ground operations and facilities analysis, and life cycle cost estimation. The basic period of performance of the TA-2 contract was from May 1992 through May 1993. No-cost extensions were exercised on the contract from June 1993 through July 1995. This document is part of the final report for the TA-2 contract. The final report consists of three volumes: Volume 1 is the Executive Summary, Volume 2 is Technical Results, and Volume 3 is Program Cost Estimates. The document-at-hand, Volume 3, provides a work breakdown structure dictionary, user's guide for the parametric life cycle cost estimation tool, and final report developed by ECON, Inc., under subcontract to Lockheed Martin on TA-2 for the analysis of heavy lift launch vehicle concepts.

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation

PubMed Central

Grossi, Giuliano; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD’s robustness and wide applicability. PMID:28103283

Personalized Age Progression with Bi-Level Aging Dictionary Learning.

PubMed

Shu, Xiangbo; Tang, Jinhui; Li, Zechao; Lai, Hanjiang; Zhang, Liyan; Yan, Shuicheng

2018-04-01

Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a personalized way. Basically, for each age group, we learn an aging dictionary to reveal its aging characteristics (e.g., wrinkles), where the dictionary bases corresponding to the same index yet from two neighboring aging dictionaries form a particular aging pattern cross these two age groups, and a linear combination of all these patterns expresses a particular personalized aging process. Moreover, two factors are taken into consideration in the dictionary learning process. First, beyond the aging dictionaries, each person may have extra personalized facial characteristics, e.g., mole, which are invariant in the aging process. Second, it is challenging or even impossible to collect faces of all age groups for a particular person, yet much easier and more practical to get face pairs from neighboring age groups. To this end, we propose a novel Bi-level Dictionary Learning based Personalized Age Progression (BDL-PAP) method. Here, bi-level dictionary learning is formulated to learn the aging dictionaries based on face pairs from neighboring age groups. Extensive experiments well demonstrate the advantages of the proposed BDL-PAP over other state-of-the-arts in term of personalized age progression, as well as the performance gain for cross-age face verification by synthesizing aging faces.

U.S.-MEXICO BORDER PROGRAM ARIZONA BORDER STUDY--STANDARD OPERATING PROCEDURE FOR THE GENERATION AND OPERATION OF DATA DICTIONARIES (UA-D-4.0)

EPA Science Inventory

The purpose of this SOP is to provide a standard method for the writing of data dictionaries. This procedure applies to the dictionaries used during the Arizona NHEXAS project and the Border study. Keywords: guidelines; data dictionaries.

The U.S.-Mexico Border Program is spon...

Multimodal Task-Driven Dictionary Learning for Image Classification

DTIC Science & Technology

2015-12-18

1 Multimodal Task-Driven Dictionary Learning for Image Classification Soheil Bahrampour, Student Member, IEEE, Nasser M. Nasrabadi, Fellow, IEEE...Asok Ray, Fellow, IEEE, and W. Kenneth Jenkins, Life Fellow, IEEE Abstract— Dictionary learning algorithms have been suc- cessfully used for both...reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms. While these methods are

A Study of the Relationship between Type of Dictionary Used and Lexical Proficiency in Writings of Iranian EFL Students

ERIC Educational Resources Information Center

Vahdany, Fereidoon; Abdollahzadeh, Milad; Gholami, Shokoufeh; Ghanipoor, Mahmood

2014-01-01

This study aimed at investigating the relationship between types of dictionaries used and lexical proficiency in writing. Eighty TOEFL students took part in responding to two Questionnaires collecting information about their dictionary type preferences and habits of dictionary use, along with an interview for further in-depth responses. They were…

English-Chinese Cross-Language IR Using Bilingual Dictionaries

DTIC Science & Technology

2006-01-01

specialized dictionaries together contain about two million entries [6]. 4 Monolingual Experiment The Chinese documents and the Chinese translations of... monolingual performance. The main performance-limiting factor is the limited coverage of the dictionary used in query translation. Some of the key con...English-Chinese Cross-Language IR using Bilingual Dictionaries Aitao Chen , Hailing Jiang , and Fredric Gey School of Information Management

Discriminative object tracking via sparse representation and online dictionary learning.

PubMed

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis.

PubMed

Seghouane, Abd-Krim; Iqbal, Asif

2017-09-01

Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.

The Planetary Data System Web Catalog Interface--Another Use of the Planetary Data System Data Model

NASA Technical Reports Server (NTRS)

Hughes, S.; Bernath, A.

1995-01-01

The Planetary Data System Data Model consists of a set of standardized descriptions of entities within the Planetary Science Community. These can be real entities in the space exploration domain such as spacecraft, instruments, and targets; conceptual entities such as data sets, archive volumes, and data dictionaries; or the archive data products such as individual images, spectrum, series, and qubes.

Investigation into Suitability of Geopolymers (Illite & Metakaolin) for the Space Environment

DTIC Science & Technology

2012-09-13

most disastrous if a spacecraft telescope made of a hybrid composite mirror with a geopolymer adhesive became distorted or damaged on orbit due to...background According to the Dictionary of Composite Materials Technology, (Lee 1989) a geopolymer is defined as: “A family of refractory ceramics...polysilicates to form polymeric Si-O-Al bonds”. Geopolymers and geopolymer composites are a relatively newly defined class of ceramic materials whose

High-recall protein entity recognition using a dictionary

PubMed Central

Kou, Zhenzhen; Cohen, William W.; Murphy, Robert F.

2010-01-01

Protein name extraction is an important step in mining biological literature. We describe two new methods for this task: semiCRFs and dictionary HMMs. SemiCRFs are a recently-proposed extension to conditional random fields that enables more effective use of dictionary information as features. Dictionary HMMs are a technique in which a dictionary is converted to a large HMM that recognizes phrases from the dictionary, as well as variations of these phrases. Standard training methods for HMMs can be used to learn which variants should be recognized. We compared the performance of our new approaches to that of Maximum Entropy (Max-Ent) and normal CRFs on three datasets, and improvement was obtained for all four methods over the best published results for two of the datasets. CRFs and semiCRFs achieved the highest overall performance according to the widely-used F-measure, while the dictionary HMMs performed the best at finding entities that actually appear in the dictionary—the measure of most interest in our intended application. PMID:15961466

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Development Of International Data Standards For The COSMOS/PEER-LL Virtual Data Center

NASA Astrophysics Data System (ADS)

Swift, J. N.

2005-12-01

The COSMOS -PEER Lifelines Project 2L02 completed a Pilot Geotechnical Virtual Data Center (GVDC) system capable of both archiving geotechnical data and of disseminating data from multiple linked geotechnical databases. The Pilot GVDC system links geotechnical databases of four organizations: the California Geological Survey, Caltrans, PG&E, and the U. S. Geological Survey The System was presented and reviewed in the COSMOS-PEER Lifelines workshop on June 21 - 23, 2004, which was co-sponsored by the Federal Highway Administration (FHWA) and included participation by the United Kingdom Highways Agency (UKHA) , the Association of Geotechnical and Geoenvironmental Specialists in the United Kingdom (AGS), the United States Army Corp of Engineers (USACOE), Caltrans, United States Geological Survey (USGS), California Geological Survey (CGS), a number of state Departments of Transportation (DOTs), county building code officials, and representatives of academic institutions and private sector geotechnical companies. As of February 2005 COSMOS-PEER Lifelines Project 2L03 is currently funded to accomplish the following tasks: 1) expand the Pilot GVDC Geotechnical Data Dictionary and XML Schema to include data definitions and structures to describe in-situ measurements such as shear wave velocity profiles, and additional laboratory geotechnical test types; 2) participate in an international cooperative working group developing a single geotechnical data exchange standard that has broad international acceptance; and 3) upgrade the GVDC system to support corresponding exchange standard data dictionary and schema improvements. The new geophysical data structures being developed will include PS-logs, downhole geophysical logs, cross-hole velocity data, and velocity profiles derived using surface waves. A COSMOS-PEER Lifelines Geophysical Data Dictionary Working Committee constituted of experts in the development of data dictionary standards and experts in the specific data to be captured are presently working on this task. The international geotechnical data dictionary and schema development is a highly collaborative effort funded by a pooled fund study coordinated by state DOTs and FHWA. The technical development of the standards called DIGGS (Data Interchange for Geotechnical and Geoenvironmental Specialists) is lead by a team consisting of representatives from the University of Florida, Department of Civil Engineering (UF), AGS, Construction Industry Research and Information Association (CIRIA), UKHA, Ohio DOT, and COSMOS. The first draft of DIGGS is currently in preparation. A Geotechnical Management System Group (GMS group), composed of representatives from 13 State DOTs, FHWA, US EPA, USACOE, USGS and UKHA, oversees and approves the development of the standards. The ultimate goal of both COSMOS-PEER Lifelines Project 2L03 and the international GMS working group is to produce open and flexible, GML-compliant XML schema-based data structures and data dictionaries for review and approval by DOTs, other public agencies, and the international engineering and geoenvironmental community at large, leading to adoption of internationally accepted geotechnical and geophysical data transfer standards. Establishment of these standards is intended to significantly facilitate the accessibility and exchange of geotechnical information world wide.

Speech and Language and Language Translation (SALT)

DTIC Science & Technology

2012-12-01

Resources are classified as: Parallel Text Dictionaries Monolingual Text Other Dictionaries are further classified as: Text: can download entire...not clear how many are translated http://www.redsea-online.com/modules.php?name= dictionary Monolingual Text Monolingual Text; An Crubadan web...attached to a following word. A program could be written to detach the character د from unknown words, when the remaining word matches a dictionary

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining.

PubMed

Hettne, Kristina M; Williams, Antony J; van Mulligen, Erik M; Kleinjans, Jos; Tkachenko, Valery; Kors, Jan A

2010-03-23

Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web at http://www.biosemantics.org/chemlist.

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

PubMed Central

2010-01-01

Background Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. Results We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. Conclusions We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web at http://www.biosemantics.org/chemlist. PMID:20331846

Relaxations to Sparse Optimization Problems and Applications

NASA Astrophysics Data System (ADS)

Skau, Erik West

Parsimony is a fundamental property that is applied to many characteristics in a variety of fields. Of particular interest are optimization problems that apply rank, dimensionality, or support in a parsimonious manner. In this thesis we study some optimization problems and their relaxations, and focus on properties and qualities of the solutions of these problems. The Gramian tensor decomposition problem attempts to decompose a symmetric tensor as a sum of rank one tensors.We approach the Gramian tensor decomposition problem with a relaxation to a semidefinite program. We study conditions which ensure that the solution of the relaxed semidefinite problem gives the minimal Gramian rank decomposition. Sparse representations with learned dictionaries are one of the leading image modeling techniques for image restoration. When learning these dictionaries from a set of training images, the sparsity parameter of the dictionary learning algorithm strongly influences the content of the dictionary atoms.We describe geometrically the content of trained dictionaries and how it changes with the sparsity parameter.We use statistical analysis to characterize how the different content is used in sparse representations. Finally, a method to control the structure of the dictionaries is demonstrated, allowing us to learn a dictionary which can later be tailored for specific applications. Variations of dictionary learning can be broadly applied to a variety of applications.We explore a pansharpening problem with a triple factorization variant of coupled dictionary learning. Another application of dictionary learning is computer vision. Computer vision relies heavily on object detection, which we explore with a hierarchical convolutional dictionary learning model. Data fusion of disparate modalities is a growing topic of interest.We do a case study to demonstrate the benefit of using social media data with satellite imagery to estimate hazard extents. In this case study analysis we apply a maximum entropy model, guided by the social media data, to estimate the flooded regions during a 2013 flood in Boulder, CO and show that the results are comparable to those obtained using expert information.

Developing a distributed data dictionary service

NASA Technical Reports Server (NTRS)

U'Ren, J.

2000-01-01

This paper will explore the use of the Lightweight Directory Access Protocol (LDAP) using the ISO 11179 Data Dictionary Schema as a mechanism for standardizing the structure and communication links between data dictionaries.

Multiple Sparse Representations Classification

PubMed Central

Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

2015-01-01

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and sparsity level. PMID:26177106

LeadMine: a grammar and dictionary driven approach to entity recognition.

PubMed

Lowe, Daniel M; Sayle, Roger A

2015-01-01

Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution.

LeadMine: a grammar and dictionary driven approach to entity recognition

PubMed Central

2015-01-01

Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776

A dictionary server for supplying context sensitive medical knowledge.

PubMed

Ruan, W; Bürkle, T; Dudeck, J

2000-01-01

The Giessen Data Dictionary Server (GDDS), developed at Giessen University Hospital, integrates clinical systems with on-line, context sensitive medical knowledge to help with making medical decisions. By "context" we mean the clinical information that is being presented at the moment the information need is occurring. The dictionary server makes use of a semantic network supported by a medical data dictionary to link terms from clinical applications to their proper information sources. It has been designed to analyze the network structure itself instead of knowing the layout of the semantic net in advance. This enables us to map appropriate information sources to various clinical applications, such as nursing documentation, drug prescription and cancer follow up systems. This paper describes the function of the dictionary server and shows how the knowledge stored in the semantic network is used in the dictionary service.

Emergency department performance measures updates: proceedings of the 2014 emergency department benchmarking alliance consensus summit.

PubMed

Wiler, Jennifer L; Welch, Shari; Pines, Jesse; Schuur, Jeremiah; Jouriles, Nick; Stone-Griffith, Suzanne

2015-05-01

The objective was to review and update key definitions and metrics for emergency department (ED) performance and operations. Forty-five emergency medicine leaders convened for the Third Performance Measures and Benchmarking Summit held in Las Vegas, February 21-22, 2014. Prior to arrival, attendees were assigned to workgroups to review, revise, and update the definitions and vocabulary being used to communicate about ED performance and operations. They were provided with the prior definitions of those consensus summits that were published in 2006 and 2010. Other published definitions from key stakeholders in emergency medicine and health care were also reviewed and circulated. At the summit, key terminology and metrics were discussed and debated. Workgroups communicated online, via teleconference, and finally in a face-to-face meeting to reach consensus regarding their recommendations. Recommendations were then posted and open to a 30-day comment period. Participants then reanalyzed the recommendations, and modifications were made based on consensus. A comprehensive dictionary of ED terminology related to ED performance and operation was developed. This article includes definitions of operating characteristics and internal and external factors relevant to the stratification and categorization of EDs. Time stamps, time intervals, and measures of utilization were defined. Definitions of processes and staffing measures are also presented. Definitions were harmonized with performance measures put forth by the Centers for Medicare and Medicaid Services (CMS) for consistency. Standardized definitions are necessary to improve the comparability of EDs nationally for operations research and practice. More importantly, clear precise definitions describing ED operations are needed for incentive-based pay-for-performance models like those developed by CMS. This document provides a common language for front-line practitioners, managers, health policymakers, and researchers. © 2015 by the Society for Academic Emergency Medicine.

Sparsity and Nullity: Paradigm for Analysis Dictionary Learning

DTIC Science & Technology

2016-08-09

16. SECURITY CLASSIFICATION OF: Sparse models in dictionary learning have been successfully applied in a wide variety of machine learning and...we investigate the relation between the SNS problem and the analysis dictionary learning problem, and show that the SNS problem plays a central role...and may be utilized to solve dictionary learning problems. 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12

Parsing and Tagging of Bilingual Dictionary

DTIC Science & Technology

2003-09-01

LAMP-TR-106 CAR-TR-991 CS-TR-4529 UMIACS-TR-2003-97 PARSING ANS TAGGING OF BILINGUAL DICTIONARY Huanfeng Ma1,2, Burcu Karagol-Ayan1,2, David... dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine...translation, and cross-language information retrieval. In this paper, we describe a system for extracting term lexicons from printed bilingual dictionaries

Readers' opinions of romantic poetry are consistent with emotional measures based on the Dictionary of Affect in Language.

PubMed

Whissell, Cynthia

2003-06-01

A principal components analysis of 68 volunteers' subjective ratings of 20 excerpts of Romantic poetry and of Dictionary of Affect scores for the same excerpts produced four components representing Pleasantness, Activation, Romanticism, and Nature. Dictionary measures and subjective ratings of the same constructs loaded on the same factor. Results are interpreted as providing construct validity for the Dictionary of Affect.

Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

2014-12-01

Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.

Adaptive Greedy Dictionary Selection for Web Media Summarization.

PubMed

Cong, Yang; Liu, Ji; Sun, Gan; You, Quanzeng; Li, Yuncheng; Luo, Jiebo

2017-01-01

Initializing an effective dictionary is an indispensable step for sparse representation. In this paper, we focus on the dictionary selection problem with the objective to select a compact subset of basis from original training data instead of learning a new dictionary matrix as dictionary learning models do. We first design a new dictionary selection model via l 2,0 norm. For model optimization, we propose two methods: one is the standard forward-backward greedy algorithm, which is not suitable for large-scale problems; the other is based on the gradient cues at each forward iteration and speeds up the process dramatically. In comparison with the state-of-the-art dictionary selection models, our model is not only more effective and efficient, but also can control the sparsity. To evaluate the performance of our new model, we select two practical web media summarization problems: 1) we build a new data set consisting of around 500 users, 3000 albums, and 1 million images, and achieve effective assisted albuming based on our model and 2) by formulating the video summarization problem as a dictionary selection issue, we employ our model to extract keyframes from a video sequence in a more flexible way. Generally, our model outperforms the state-of-the-art methods in both these two tasks.

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Natural-Annotation-based Unsupervised Construction of Korean-Chinese Domain Dictionary

NASA Astrophysics Data System (ADS)

Liu, Wuying; Wang, Lin

2018-03-01

The large-scale bilingual parallel resource is significant to statistical learning and deep learning in natural language processing. This paper addresses the automatic construction issue of the Korean-Chinese domain dictionary, and presents a novel unsupervised construction method based on the natural annotation in the raw corpus. We firstly extract all Korean-Chinese word pairs from Korean texts according to natural annotations, secondly transform the traditional Chinese characters into the simplified ones, and finally distill out a bilingual domain dictionary after retrieving the simplified Chinese words in an extra Chinese domain dictionary. The experimental results show that our method can automatically build multiple Korean-Chinese domain dictionaries efficiently.

The Pocket Dictionary: A Textbook for Spelling.

ERIC Educational Resources Information Center

Doggett, Maran

1982-01-01

Reports on a productive approach to secondary-school spelling instruction--one that emphasizes how and when to use the dictionary. Describes two of the many class activities that cultivate student use of the dictionary. (RL)

Cheap Words: A Paperback Dictionary Roundup.

ERIC Educational Resources Information Center

Kister, Ken

1979-01-01

Surveys currently available paperback editions in three classes of dictionaries: collegiate, abridged, and pocket. A general discussion distinguishes among the classes and offers seven consumer tips, followed by an annotated listing of dictionaries now available. (SW)

An analysis dictionary learning algorithm under a noisy data model with orthogonality constraint.

PubMed

Zhang, Ye; Yu, Tenglong; Wang, Wenwu

2014-01-01

Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as represented by the Analysis K-SVD (AK-SVD) algorithm. The other problem is the trivial solution to the dictionary, for example, the null dictionary matrix that may be given by a dictionary learning algorithm, as discussed in the learning overcomplete sparsifying transform (LOST) algorithm. Here we propose a novel optimization model and an iterative algorithm to learn the analysis dictionary, where we directly employ the observed data to compute the approximate analysis sparse representation of the original signals (leading to a fast optimization procedure) and enforce an orthogonality constraint on the optimization criterion to avoid the trivial solutions. Experiments demonstrate the competitive performance of the proposed algorithm as compared with three baselines, namely, the AK-SVD, LOST, and NAAOLA algorithms.

Chinese-English Aviation and Space Dictionary

DTIC Science & Technology

1973-04-01

i.e., individual characters with re- duced numbers of strokes. this process is in effect eroding the traditional classification of a character by its...side rod 17 b X1&jt d aolyu- edge effect 18 birajie boundary; border; bound; 19 frontier; ,nd binJie jiaoy’,; .iý K! M narginal checking 20 bianjie...range missile; 23 very-long-range missile chaoynianchegb oghli151 .’ . long-range bomber; global 24 bomber; superbomber chaoyue h mhshu 14

Office of Space Terrestrial Applications (OSTA)/Applications Data Service (ADS) data systems standards

NASA Technical Reports Server (NTRS)

Walton, B. A. (Editor)

1981-01-01

Standards needed to interconnect applications data service pilots for data sharing were identified. Current pilot methodologies are assessed. Recommendations for future work are made. A preliminary set of requirements for guidelines and standards for catalogues, directories, and dictionaries was identified. The user was considered to be a scientist at a terminal. Existing and emerging national and international telecommunication standards were adopted where possible in view of new and unproven standards.

The evolution and practical application of machine translation system (1)

NASA Astrophysics Data System (ADS)

Tominaga, Isao; Sato, Masayuki

This paper describes a development, practical applicatioin, problem of a system, evaluation of practical system, and development trend of machine translation. Most recent system contains next four problems. 1) the vagueness of a text, 2) a difference of the definition of the terminology between different language, 3) the preparing of a large-scale translation dictionary, 4) the development of a software for the logical inference. Machine translation system is already used practically in many industry fields. However, many problems are not solved. The implementation of an ideal system will be after 15 years. Also, this paper described seven evaluation items detailedly. This English abstract was made by Mu system.

SaRAD: a Simple and Robust Abbreviation Dictionary.

PubMed

Adar, Eytan

2004-03-01

Due to recent interest in the use of textual material to augment traditional experiments it has become necessary to automatically cluster, classify and filter natural language information. The Simple and Robust Abbreviation Dictionary (SaRAD) provides an easy to implement, high performance tool for the construction of a biomedical symbol dictionary. The algorithms, applied to the MEDLINE document set, result in a high quality dictionary and toolset to disambiguate abbreviation symbols automatically.

University of Glasgow at TREC 2008: Experiments in Blog, Enterprise, and Relevance Feedback Tracks with Terrier

DTIC Science & Technology

2008-11-01

improves our TREC 2007 dictionary -based approach by automatically building an internal opinion dictionary from the collection itself. We measure the opin...detecting opinionated documents. The first approach improves our TREC 2007 dictionary -based approach by automat- ically building an internal opinion... dictionary from the collection itself. The second approach is based on the OpinionFinder tool, which identifies subjective sentences in text. In particular

The Effect of Bilingual Term List Size on Dictionary-Based Cross-Language Information Retrieval

DTIC Science & Technology

2006-01-01

The Effect of Bilingual Term List Size on Dictionary -Based Cross-Language Information Retrieval Dina Demner-Fushman Department of Computer Science... dictionary -based Cross-Language Information Retrieval (CLIR), in which the goal is to find documents written in one natural language based on queries that...in which the documents are written. In dictionary -based CLIR techniques, the princi- pal source of translation knowledge is a translation lexicon

Robust Multimodal Dictionary Learning

PubMed Central

Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674

Evaluation of techniques for increasing recall in a dictionary approach to gene and protein name identification.

PubMed

Schuemie, Martijn J; Mons, Barend; Weeber, Marc; Kors, Jan A

2007-06-01

Gene and protein name identification in text requires a dictionary approach to relate synonyms to the same gene or protein, and to link names to external databases. However, existing dictionaries are incomplete. We investigate two complementary methods for automatic generation of a comprehensive dictionary: combination of information from existing gene and protein databases and rule-based generation of spelling variations. Both methods have been reported in literature before, but have hitherto not been combined and evaluated systematically. We combined gene and protein names from several existing databases of four different organisms. The combined dictionaries showed a substantial increase in recall on three different test sets, as compared to any single database. Application of 23 spelling variation rules to the combined dictionaries further increased recall. However, many rules appeared to have no effect and some appear to have a detrimental effect on precision.

A dictionary server for supplying context sensitive medical knowledge.

PubMed Central

Ruan, W.; Bürkle, T.; Dudeck, J.

2000-01-01

The Giessen Data Dictionary Server (GDDS), developed at Giessen University Hospital, integrates clinical systems with on-line, context sensitive medical knowledge to help with making medical decisions. By "context" we mean the clinical information that is being presented at the moment the information need is occurring. The dictionary server makes use of a semantic network supported by a medical data dictionary to link terms from clinical applications to their proper information sources. It has been designed to analyze the network structure itself instead of knowing the layout of the semantic net in advance. This enables us to map appropriate information sources to various clinical applications, such as nursing documentation, drug prescription and cancer follow up systems. This paper describes the function of the dictionary server and shows how the knowledge stored in the semantic network is used in the dictionary service. PMID:11079978

The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

NASA Astrophysics Data System (ADS)

Tan, Linglong; Li, Changkai; Wang, Yueqin

2018-04-01

SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

Heterogeneous iris image hallucination using sparse representation on a learned heterogeneous patch dictionary

NASA Astrophysics Data System (ADS)

Li, Yung-Hui; Zheng, Bo-Ren; Ji, Dai-Yan; Tien, Chung-Hao; Liu, Po-Tsun

2014-09-01

Cross sensor iris matching may seriously degrade the recognition performance because of the sensor mis-match problem of iris images between the enrollment and test stage. In this paper, we propose two novel patch-based heterogeneous dictionary learning method to attack this problem. The first method applies the latest sparse representation theory while the second method tries to learn the correspondence relationship through PCA in heterogeneous patch space. Both methods learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at test stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. The experimental results showed the satisfied results both visually and in terms of recognition rate. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 39.4% relatively by the proposed method.

Low rank magnetic resonance fingerprinting.

PubMed

Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

2016-08-01

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

14 CFR 1214.502 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT Mission Critical Space System Personnel Reliability Program § 1214.502 Definitions. (a) Mission Critical Space Systems. The Space Shuttle and other critical space systems, including Space Station Freedom, designated Expendable Launch...

Machine-aided indexing at NASA

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1994-01-01

This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.

Learning overcomplete representations from distributed data: a brief review

NASA Astrophysics Data System (ADS)

Raja, Haroon; Bajwa, Waheed U.

2016-05-01

Most of the research on dictionary learning has focused on developing algorithms under the assumption that data is available at a centralized location. But often the data is not available at a centralized location due to practical constraints like data aggregation costs, privacy concerns, etc. Using centralized dictionary learning algorithms may not be the optimal choice in such settings. This motivates the design of dictionary learning algorithms that consider distributed nature of data as one of the problem variables. Just like centralized settings, distributed dictionary learning problem can be posed in more than one way depending on the problem setup. Most notable distinguishing features are the online versus batch nature of data and the representative versus discriminative nature of the dictionaries. In this paper, several distributed dictionary learning algorithms that are designed to tackle different problem setups are reviewed. One of these algorithms is cloud K-SVD, which solves the dictionary learning problem for batch data in distributed settings. One distinguishing feature of cloud K-SVD is that it has been shown to converge to its centralized counterpart, namely, the K-SVD solution. On the other hand, no such guarantees are provided for other distributed dictionary learning algorithms. Convergence of cloud K-SVD to the centralized K-SVD solution means problems that are solvable by K-SVD in centralized settings can now be solved in distributed settings with similar performance. Finally, cloud K-SVD is used as an example to show the advantages that are attainable by deploying distributed dictionary algorithms for real world distributed datasets.

Dictionnaires et encyclopedies: cuvee 89 (Dictionaries and Encyclopedias: Vintage 89).

ERIC Educational Resources Information Center

Ibrahim, Amr Helmy

1989-01-01

For the first time since its initial publication in 1905, the much-imitated "Petit Larousse" dictionary/reference book has a true competitor in Hachette's "Le Dictionnaire de notre temps", a new dictionary reflecting modern French usage. (MSE)

Using dictionaries to study the mental lexicon.

PubMed

Anshen, F; Aronoff, M

The notion of a mental lexicon has its historical roots in practical reference dictionaries. The distributional analysis of dictionaries provides one means of investigating the structure of the mental lexicon. We review our earlier work with dictionaries, based on a three-way horserace model of lexical access and production, and then present the most recent results of our ongoing analysis of the Oxford English Dictionary, Second Edition on CD-ROM, which traces changes in productivity over time of the English suffixes -ment and -ity, both of which originate in French borrowings. Our results lead us to question the validity of automatic analogy from a set of existing words as the driving force behind morphological productivity. Copyright 1999 Academic Press.

Compressed sampling and dictionary learning framework for wavelength-division-multiplexing-based distributed fiber sensing.

PubMed

Weiss, Christian; Zoubir, Abdelhak M

2017-05-01

We propose a compressed sampling and dictionary learning framework for fiber-optic sensing using wavelength-tunable lasers. A redundant dictionary is generated from a model for the reflected sensor signal. Imperfect prior knowledge is considered in terms of uncertain local and global parameters. To estimate a sparse representation and the dictionary parameters, we present an alternating minimization algorithm that is equipped with a preprocessing routine to handle dictionary coherence. The support of the obtained sparse signal indicates the reflection delays, which can be used to measure impairments along the sensing fiber. The performance is evaluated by simulations and experimental data for a fiber sensor system with common core architecture.

The T.M.R. Data Dictionary: A Management Tool for Data Base Design

PubMed Central

Ostrowski, Maureen; Bernes, Marshall R.

1984-01-01

In January 1981, a dictionary-driven ambulatory care information system known as TMR (The Medical Record) was installed at a large private medical group practice in Los Angeles. TMR's data dictionary has enabled the medical group to adapt the software to meet changing user needs largely without programming support. For top management, the dictionary is also a tool for navigating through the system's complexity and assuring the integrity of management goals.

An Improved Sparse Representation over Learned Dictionary Method for Seizure Detection.

PubMed

Li, Junhui; Zhou, Weidong; Yuan, Shasha; Zhang, Yanli; Li, Chengcheng; Wu, Qi

2016-02-01

Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific method is proposed for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings. This seizure detection method is based on sparse representation with online dictionary learning and elastic net constraint. The online learned dictionary could sparsely represent the testing samples more accurately, and the elastic net constraint which combines the 11-norm and 12-norm not only makes the coefficients sparse but also avoids over-fitting problem. First, the EEG signals are preprocessed using wavelet filtering and differential filtering, and the kernel function is applied to make the samples closer to linearly separable. Then the dictionaries of seizure and nonseizure are respectively learned from original ictal and interictal training samples with online dictionary optimization algorithm to compose the training dictionary. After that, the test samples are sparsely coded over the learned dictionary and the residuals associated with ictal and interictal sub-dictionary are calculated, respectively. Eventually, the test samples are classified as two distinct categories, seizure or nonseizure, by comparing the reconstructed residuals. The average segment-based sensitivity of 95.45%, specificity of 99.08%, and event-based sensitivity of 94.44% with false detection rate of 0.23/h and average latency of -5.14 s have been achieved with our proposed method.

Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

Dictionary as Database.

ERIC Educational Resources Information Center

Painter, Derrick

1996-01-01

Discussion of dictionaries as databases focuses on the digitizing of The Oxford English dictionary (OED) and the use of Standard Generalized Mark-Up Language (SGML). Topics include the creation of a consortium to digitize the OED, document structure, relational databases, text forms, sequence, and discourse. (LRW)

A method for named entity normalization in biomedical articles: application to diseases and plants.

PubMed

Cho, Hyejin; Choi, Wonjun; Lee, Hyunju

2017-10-13

In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles. After NER is applied to articles, the next step is to normalize the identified names into standard concepts (i.e., disease names are mapped to the National Library of Medicine's Medical Subject Headings disease terms). In biomedical articles, many entity normalization methods rely on domain-specific dictionaries for resolving synonyms and abbreviations. However, the dictionaries are not comprehensive except for some entities such as genes. In recent years, biomedical articles have accumulated rapidly, and neural network-based algorithms that incorporate a large amount of unlabeled data have shown considerable success in several natural language processing problems. In this study, we propose an approach for normalizing biological entities, such as disease names and plant names, by using word embeddings to represent semantic spaces. For diseases, training data from the National Center for Biotechnology Information (NCBI) disease corpus and unlabeled data from PubMed abstracts were used to construct word representations. For plants, a training corpus that we manually constructed and unlabeled PubMed abstracts were used to represent word vectors. We showed that the proposed approach performed better than the use of only the training corpus or only the unlabeled data and showed that the normalization accuracy was improved by using our model even when the dictionaries were not comprehensive. We obtained F-scores of 0.808 and 0.690 for normalizing the NCBI disease corpus and manually constructed plant corpus, respectively. We further evaluated our approach using a data set in the disease normalization task of the BioCreative V challenge. When only the disease corpus was used as a dictionary, our approach significantly outperformed the best system of the task. The proposed approach shows robust performance for normalizing biological entities. The manually constructed plant corpus and the proposed model are available at http://gcancer.org/plant and http://gcancer.org/normalization , respectively.

Brain tumor classification and segmentation using sparse coding and dictionary learning.

PubMed

Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

2016-08-01

This paper presents a novel fully automatic framework for multi-class brain tumor classification and segmentation using a sparse coding and dictionary learning method. The proposed framework consists of two steps: classification and segmentation. The classification of the brain tumors is based on brain topology and texture. The segmentation is based on voxel values of the image data. Using K-SVD, two types of dictionaries are learned from the training data and their associated ground truth segmentation: feature dictionary and voxel-wise coupled dictionaries. The feature dictionary consists of global image features (topological and texture features). The coupled dictionaries consist of coupled information: gray scale voxel values of the training image data and their associated label voxel values of the ground truth segmentation of the training data. For quantitative evaluation, the proposed framework is evaluated using different metrics. The segmentation results of the brain tumor segmentation (MICCAI-BraTS-2013) database are evaluated using five different metric scores, which are computed using the online evaluation tool provided by the BraTS-2013 challenge organizers. Experimental results demonstrate that the proposed approach achieves an accurate brain tumor classification and segmentation and outperforms the state-of-the-art methods.

Measurement of negativity bias in personal narratives using corpus-based emotion dictionaries.

PubMed

Cohen, Shuki J

2011-04-01

This study presents a novel methodology for the measurement of negativity bias using positive and negative dictionaries of emotion words applied to autobiographical narratives. At odds with the cognitive theory of mood dysregulation, previous text-analytical studies have failed to find significant correlation between emotion dictionaries and negative affectivity or dysphoria. In the present study, an a priori list dictionary of emotion words was refined based on the actual use of these words in personal narratives collected from close to 500 college students. Half of the corpus was used to construct, via concordance analysis, the grammatical structures associated with the words in their emotional sense. The second half of the corpus served as a validation corpus. The resulting dictionary ignores words that are not used in their intended emotional sense, including negated emotions, homophones, frozen idioms etc. Correlations of the resulting corpus-based negative and positive emotion dictionaries with self-report measures of negative affectivity were in the expected direction, and were statistically significant, with medium effect size. The potential use of these dictionaries as implicit measures of negativity bias and in the analysis of psychotherapy transcripts is discussed.

Joint seismic data denoising and interpolation with double-sparsity dictionary learning

NASA Astrophysics Data System (ADS)

Zhu, Lingchen; Liu, Entao; McClellan, James H.

2017-08-01

Seismic data quality is vital to geophysical applications, so that methods of data recovery, including denoising and interpolation, are common initial steps in the seismic data processing flow. We present a method to perform simultaneous interpolation and denoising, which is based on double-sparsity dictionary learning. This extends previous work that was for denoising only. The original double-sparsity dictionary learning algorithm is modified to track the traces with missing data by defining a masking operator that is integrated into the sparse representation of the dictionary. A weighted low-rank approximation algorithm is adopted to handle the dictionary updating as a sparse recovery optimization problem constrained by the masking operator. Compared to traditional sparse transforms with fixed dictionaries that lack the ability to adapt to complex data structures, the double-sparsity dictionary learning method learns the signal adaptively from selected patches of the corrupted seismic data, while preserving compact forward and inverse transform operators. Numerical experiments on synthetic seismic data indicate that this new method preserves more subtle features in the data set without introducing pseudo-Gibbs artifacts when compared to other directional multi-scale transform methods such as curvelets.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition.

PubMed

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-03-27

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K -nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction.

Bilevel Model-Based Discriminative Dictionary Learning for Recognition.

PubMed

Zhou, Pan; Zhang, Chao; Lin, Zhouchen

2017-03-01

Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the l 0 or l 1 norm to encode each datum independently, limiting the performance of the learnt dictionaries. We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks. The upper level directly minimizes the classification error, while the lower level uses the sparsity term and the Laplacian term to characterize the intrinsic data structure. The lower level is subordinate to the upper level. Therefore, our model achieves an overall optimality for recognition in that the learnt dictionary is directly tailored for recognition. Moreover, the sparse codes learning models in the training and the testing phases can be the same. We further propose a novel method to solve our bilevel optimization problem. It first replaces the lower level with its Karush-Kuhn-Tucker conditions and then applies the alternating direction method of multipliers to solve the equivalent problem. Extensive experiments demonstrate the effectiveness and robustness of our method.

Compressive sensing of electrocardiogram signals by promoting sparsity on the second-order difference and by using dictionary learning.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2014-04-01

A new algorithm for the reconstruction of electrocardiogram (ECG) signals and a dictionary learning algorithm for the enhancement of its reconstruction performance for a class of signals are proposed. The signal reconstruction algorithm is based on minimizing the lp pseudo-norm of the second-order difference, called as the lp(2d) pseudo-norm, of the signal. The optimization involved is carried out using a sequential conjugate-gradient algorithm. The dictionary learning algorithm uses an iterative procedure wherein a signal reconstruction and a dictionary update steps are repeated until a convergence criterion is satisfied. The signal reconstruction step is implemented by using the proposed signal reconstruction algorithm and the dictionary update step is implemented by using the linear least-squares method. Extensive simulation results demonstrate that the proposed algorithm yields improved reconstruction performance for temporally correlated ECG signals relative to the state-of-the-art lp(1d)-regularized least-squares and Bayesian learning based algorithms. Also for a known class of signals, the reconstruction performance of the proposed algorithm can be improved by applying it in conjunction with a dictionary obtained using the proposed dictionary learning algorithm.

14 CFR 1214.502 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... and other critical space systems, including Space Station Freedom, designated Expendable Launch... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Definitions. 1214.502 Section 1214.502 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT Mission Critical Space System...

14 CFR 1214.502 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... and other critical space systems, including Space Station Freedom, designated Expendable Launch... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Definitions. 1214.502 Section 1214.502 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT Mission Critical Space System...

14 CFR 1214.502 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... and other critical space systems, including Space Station Freedom, designated Expendable Launch... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Definitions. 1214.502 Section 1214.502 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT Mission Critical Space System...

Tissue microstructure estimation using a deep network inspired by a dictionary-based framework.

PubMed

Ye, Chuyang

2017-12-01

Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies. It models the diffusion signal with three compartments that are characterized by distinct diffusion properties, and the parameters in the model describe tissue microstructure. In NODDI, these parameters are estimated in a maximum likelihood framework, where the nonlinear model fitting is computationally intensive. Therefore, efforts have been made to develop efficient and accurate algorithms for NODDI microstructure estimation, which is still an open problem. In this work, we propose a deep network based approach that performs end-to-end estimation of NODDI microstructure, which is named Microstructure Estimation using a Deep Network (MEDN). MEDN comprises two cascaded stages and is motivated by the AMICO algorithm, where the NODDI microstructure estimation is formulated in a dictionary-based framework. The first stage computes the coefficients of the dictionary. It resembles the solution to a sparse reconstruction problem, where the iterative process in conventional estimation approaches is unfolded and truncated, and the weights are learned instead of predetermined by the dictionary. In the second stage, microstructure properties are computed from the output of the first stage, which resembles the weighted sum of normalized dictionary coefficients in AMICO, and the weights are also learned. Because spatial consistency of diffusion signals can be used to reduce the effect of noise, we also propose MEDN+, which is an extended version of MEDN. MEDN+ allows incorporation of neighborhood information by inserting a stage with learned weights before the MEDN structure, where the diffusion signals in the neighborhood of a voxel are processed. The weights in MEDN or MEDN+ are jointly learned from training samples that are acquired with diffusion gradients densely sampling the q-space. We performed MEDN and MEDN+ on brain dMRI scans, where two shells each with 30 gradient directions were used, and measured their accuracy with respect to the gold standard. Results demonstrate that the proposed networks outperform the competing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Trying Out a New Dictionary.

ERIC Educational Resources Information Center

Benson, Morton; Benson, Evelyn

1988-01-01

Describes the BBI Combinatory Dictionary of English and demonstrates its usefulness for advanced learners of English by administering a monolingual completion test, first without a dictionary and then with the BBI, to Hungarian and Russian English teachers. Both groups' scores improved dramatically on the posttest. (LMO)

The Effect of Bilingual Term List Size on Dictionary-Based Cross-Language Information Retrieval

DTIC Science & Technology

2003-02-01

FEB 2003 2. REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE The Effect of Bilingual Term List Size on Dictionary ...298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 The Effect of Bilingual Term List Size on Dictionary -Based Cross-Language Information Retrieval Dina...are extensively used as a resource for dictionary -based Cross-Language Information Retrieval (CLIR), in which the goal is to find documents written

Travel time tomography with local image regularization by sparsity constrained dictionary learning

NASA Astrophysics Data System (ADS)

Bianco, M.; Gerstoft, P.

2017-12-01

We propose a regularization approach for 2D seismic travel time tomography which models small rectangular groups of slowness pixels, within an overall or `global' slowness image, as sparse linear combinations of atoms from a dictionary. The groups of slowness pixels are referred to as patches and a dictionary corresponds to a collection of functions or `atoms' describing the slowness in each patch. These functions could for example be wavelets.The patch regularization is incorporated into the global slowness image. The global image models the broad features, while the local patch images incorporate prior information from the dictionary. Further, high resolution slowness within patches is permitted if the travel times from the global estimates support it. The proposed approach is formulated as an algorithm, which is repeated until convergence is achieved: 1) From travel times, find the global slowness image with a minimum energy constraint on the pixel variance relative to a reference. 2) Find the patch level solutions to fit the global estimate as a sparse linear combination of dictionary atoms.3) Update the reference as the weighted average of the patch level solutions.This approach relies on the redundancy of the patches in the seismic image. Redundancy means that the patches are repetitions of a finite number of patterns, which are described by the dictionary atoms. Redundancy in the earth's structure was demonstrated in previous works in seismics where dictionaries of wavelet functions regularized inversion. We further exploit redundancy of the patches by using dictionary learning algorithms, a form of unsupervised machine learning, to estimate optimal dictionaries from the data in parallel with the inversion. We demonstrate our approach on densely, but irregularly sampled synthetic seismic images.

Model-based semantic dictionaries for medical language understanding.

PubMed Central

Rassinoux, A. M.; Baud, R. H.; Ruch, P.; Trombert-Paviot, B.; Rodrigues, J. M.

1999-01-01

Semantic dictionaries are emerging as a major cornerstone towards achieving sound natural language understanding. Indeed, they constitute the main bridge between words and conceptual entities that reflect their meanings. Nowadays, more and more wide-coverage lexical dictionaries are electronically available in the public domain. However, associating a semantic content with lexical entries is not a straightforward task as it is subordinate to the existence of a fine-grained concept model of the treated domain. This paper presents the benefits and pitfalls in building and maintaining multilingual dictionaries, the semantics of which is directly established on an existing concept model. Concrete cases, handled through the GALEN-IN-USE project, illustrate the use of such semantic dictionaries for the analysis and generation of multilingual surgical procedures. PMID:10566333

Talking Shop with Moira Runcie.

ERIC Educational Resources Information Center

Bowers, Rogers

1998-01-01

Presents an interview with Moira Runcie, Editorial Director for ELT (English Language Teaching) dictionaries at Oxford University Press. The interview focuses on the work of A.S. Hornby in creating the first learners dictionary of English and shows how modern dictionaries draw on his work. (Author/JL)

Cross-label Suppression: a Discriminative and Fast Dictionary Learning with Group Regularization.

PubMed

Wang, Xiudong; Gu, Yuantao

2017-05-10

This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we propose crosslabel suppression constraint to enlarge the difference among representations for different classes. Meanwhile, we introduce group regularization to enforce representations to preserve label properties of original samples, meaning the representations for the same class are encouraged to be similar. Upon the cross-label suppression, we don't resort to frequently-used `0-norm or `1- norm for coding, and obtain computational efficiency without losing the discriminative power for categorization. Moreover, two simple classification schemes are also developed to take full advantage of the learnt dictionary. Extensive experiments on six data sets including face recognition, object categorization, scene classification, texture recognition and sport action categorization are conducted, and the results show that the proposed approach can outperform lots of recently presented dictionary algorithms on both recognition accuracy and computational efficiency.

A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification.

PubMed

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

2017-02-01

Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the locality-constrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, the locality information was preserved using the graph Laplacian matrix of the learned dictionary instead of the conventional one derived from the training samples. Then, the label embedding term was constructed using the label information of atoms instead of the classification error term, which contained discriminating information of the learned dictionary. The optimal coding coefficients derived by the locality-based and label-based reconstruction were effective for image classification. Experimental results demonstrated that the LCLE-DL algorithm can achieve better performance than some state-of-the-art algorithms.

14 CFR § 1214.502 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... The Space Shuttle and other critical space systems, including Space Station Freedom, designated... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Definitions. § 1214.502 Section § 1214.502 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT Mission Critical...

49 CFR Appendix B to Part 604 - Reasons for Removal

Code of Federal Regulations, 2012 CFR

2012-10-01

... honest mistake. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn... performing it. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn., 1968... force. In addition, no other policy of insurance has taken its place. Black's Law Dictionary, Revised...

49 CFR Appendix B to Part 604 - Reasons for Removal

Code of Federal Regulations, 2013 CFR

2013-10-01

... honest mistake. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn... performing it. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn., 1968... force. In addition, no other policy of insurance has taken its place. Black's Law Dictionary, Revised...

49 CFR Appendix B to Part 604 - Reasons for Removal

Code of Federal Regulations, 2014 CFR

2014-10-01

... honest mistake. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn... performing it. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn., 1968... force. In addition, no other policy of insurance has taken its place. Black's Law Dictionary, Revised...

Ahtna Athabaskan Dictionary.

ERIC Educational Resources Information Center

Kari, James, Ed.

This dictionary of Ahtna, a dialect of the Athabaskan language family, is the first to integrate all morphemes into a single alphabetically arranged section of main entries, with verbs arranged according to a theory of Ahtna (and Athabascan) verb theme categories. An introductory section details dictionary format conventions used, presents a brief…

A Novel Approach to Creating Disambiguated Multilingual Dictionaries

ERIC Educational Resources Information Center

Boguslavsky, Igor; Cardenosa, Jesus; Gallardo, Carolina

2009-01-01

Multilingual lexicons are needed in various applications, such as cross-lingual information retrieval, machine translation, and some others. Often, these applications suffer from the ambiguity of dictionary items, especially when an intermediate natural language is involved in the process of the dictionary construction, since this language adds…

49 CFR Appendix B to Part 604 - Reasons for Removal

Code of Federal Regulations, 2010 CFR

2010-10-01

... honest mistake. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn... performing it. Black's Law Dictionary, Revised Fourth Edition, West Publishing Company, St. Paul, Minn., 1968... force. In addition, no other policy of insurance has taken its place. Black's Law Dictionary, Revised...

21 CFR 701.3 - Designation of ingredients.

Code of Federal Regulations, 2010 CFR

2010-04-01

....) Cosmetic Ingredient Dictionary, Second Ed., 1977 (available from the Cosmetic, Toiletry and Fragrance... revised monographs are published in supplements to this dictionary edition by July 18, 1980. Acid Black 2.../federal_register/code_of_federal_regulations/ibr_locations.html. (v) USAN and the USP dictionary of drug...

National data elements for the clinical management of acute coronary syndromes.

PubMed

Chew, Derek P B; Allan, Roger M; Aroney, Constantine N; Sheerin, Noella J

2005-05-02

Patients with acute coronary syndromes represent a clinically diverse group and their care remains heterogeneous. These patients account for a significant burden of morbidity and mortality in Australia. Optimal patient outcomes depend on rapid diagnosis, accurate risk stratification and the effective implementation of proven therapies, as advocated by clinical guidelines. The challenge is in effectively applying evidence in clinical practice. Objectivity and standardised quantification of clinical practice are essential in understanding the evidence-practice gap. Observational registries are key to understanding the link between evidence-based medicine, clinical practice and patient outcome. Data elements for monitoring clinical management of patients with acute coronary syndromes have been adapted from internationally accepted definitions and incorporated into the National Health Data Dictionary, the national standard for health data definitions in Australia. Widespread use of these data elements will assist in the local development of "quality-of-care" initiatives and performance indicators, facilitate collaboration in cardiovascular outcomes research, and aid in the development of electronic data collection methods.

Space Station needs, attributes and architectural options, volume 2, book 3: Cost and programmatics

NASA Technical Reports Server (NTRS)

1983-01-01

The cost and programmatic considerations which integrate mission requirements and architectural options into a cohesive system for exploitation of space opportunities within affordable limits are discussed. The mission requirements, baseline architecture, a top level baseline schedule, and acquisition costs are summarized. The work breakdown structure (WBS) used to structure the program, and the WBS dictionary are included. The costing approach used, including the operation of the primary costing tool, the SPACE cost model are described. The rationale for the choice of cost estimating relationships is given and costs at the module level are shown. Detailed costs at the subsystem level are shown. The baseline schedule and annual funding profiles are provided. Alternate schedules are developed to provide different funding profiles. Alternate funding sources are discussed and foreign and contractor participation is outlined. The results of the benefit analysis are given and the accrued benefits deriving from an implemented space station program are outlined.

The Use of Electronic Dictionaries for Pronunciation Practice by University EFL Students

ERIC Educational Resources Information Center

Metruk, Rastislav

2017-01-01

This paper attempts to explore how Slovak learners of English use electronic dictionaries with regard to pronunciation practice and improvement. A total of 24 Slovak university students (subjects) completed a questionnaire which contained pronunciation-related questions in connection with the use of electronic dictionaries. The questions primarily…

Dictionary of Multicultural Education.

ERIC Educational Resources Information Center

Grant, Carl A., Ed.; Ladson-Billings, Gloria, Ed.

The focus of this dictionary is the meanings and perspectives of various terms that are used in multicultural education. Contributors have often addressed the literal meanings of words and terms as well as contextual meanings and examples that helped create those meanings. Like other dictionaries, this one is arranged alphabetically, but it goes…

Sparse Representation Based Classification with Structure Preserving Dimension Reduction

DTIC Science & Technology

2014-03-13

dictionary learning [39] used stochastic approximations to update dictionary with a large data set. Laplacian score dictionary ( LSD ) [58], which is based on...vol. 4. 2003. p. 864–7. 47. Shaw B, Jebara T. Structure preserving embedding. In: The 26th annual international conference on machine learning, ICML

Chinese-Cantonese Dictionary of Common Chinese-Cantonese Characters.

ERIC Educational Resources Information Center

Defense Language Inst., Washington, DC.

This dictionary contains 1,500 Chinese-Cantonese characters (selected from three frequency lists), and more than 6,000 Chinese-Cantonese terms (selected from three Cantonese-English dictionaries). The characters are arranged alphabetically according to the U.S. Army Language School System of Romanization, which is described in the…

Chinese-English Electronics and Telecommunications Dictionary, Vol. 2.

ERIC Educational Resources Information Center

Air Force Systems Command, Wright-Patterson AFB, OH. Foreign Technology Div.

This is the second volume of the Electronics and Telecommunications Dictionary, the third of the series of Chinese-English technical dictionaries under preparation by the Foreign Technology Division, United States Air Force Systems Command. The purpose of the series is to provide rapid reference tools for translators, abstracters, and research…

Chinese-English Electronics and Telecommunications Dictionary. Vol. 1.

ERIC Educational Resources Information Center

Air Force Systems Command, Wright-Patterson AFB, OH. Foreign Technology Div.

This is the first volume of the Electronics and Telecommunications Dictionary, the third of the series of Chinese-English technical dictionaries under preparation by the Foreign Technology Division, United States Air Force Systems Command. The purpose of the series is to provide rapid reference tools for translators, abstracters, and research…

Binukid Dictionary.

ERIC Educational Resources Information Center

Otanes, Fe T., Ed.; Wrigglesworth, Hazel

1992-01-01

The dictionary of Binukid, a language spoken in the Bukidnon province of the Philippines, is intended as a tool for students of Binukid and for native Binukid-speakers interested in learning English. A single dialect was chosen for this work. The dictionary is introduced by notes on Binukid grammar, including basic information about phonology and…

75 FR 22805 - Federal Travel Regulation; Relocation Allowances; Standard Data Dictionary for Collection of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-30

... GENERAL SERVICES ADMINISTRATION [Proposed GSA Bulletin FTR 10-XXX; Docket 2010-0009; Sequence 1] Federal Travel Regulation; Relocation Allowances; Standard Data Dictionary for Collection of Transaction... GSA is posting online a proposed FTR bulletin that contains the data dictionary that large Federal...

Defining Moments \\ di-'fi-ning 'mo-mnts \\

ERIC Educational Resources Information Center

Kilman, Carrie

2012-01-01

Children encounter new words every day. Although dictionaries designed for young readers can help students explore and experiment with language, it turns out many mainstream children's dictionaries fail to accurately describe the world in which many students live. The challenges to children's dictionary publishers can be steep. First, there is the…

Getting the Most out of the Dictionary

ERIC Educational Resources Information Center

Marckwardt, Albert H.

2012-01-01

The usefulness of the dictionary as a reliable source of information for word meanings, spelling, and pronunciation is widely recognized. But even in these obvious matters, the information that the dictionary has to offer is not always accurately interpreted. With respect to pronunciation there seem to be two general pitfalls: (1) the…

A dictionary of commonly used terms and terminologies in nonwovens

USDA-ARS?s Scientific Manuscript database

A need for a comprehensive dictionary of cotton was assessed by the International Cotton Advisory Committee (ICAC), Washington, DC. The ICAC has selected the topics (from the fiber to fabric) to be covered in the dictionary. The ICAC has invited researchers/scientists from across the globe, to compi...

Measurement of Negativity Bias in Personal Narratives Using Corpus-Based Emotion Dictionaries

ERIC Educational Resources Information Center

Cohen, Shuki J.

2011-01-01

This study presents a novel methodology for the measurement of negativity bias using positive and negative dictionaries of emotion words applied to autobiographical narratives. At odds with the cognitive theory of mood dysregulation, previous text-analytical studies have failed to find significant correlation between emotion dictionaries and…

A Proposal To Develop the Axiological Aspect in Onomasiological Dictionaries.

ERIC Educational Resources Information Center

Felices Lago, Angel Miguel

It is argued that English dictionaries currently provide evaluative information in addition to descriptive information about the words they contain, and that this aspect of dictionaries should be developed and expanded on. First, the historical background and distribution of the axiological parameter in English-language onomasiological…

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

PubMed Central

Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, UK Arvind

2016-01-01

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

MR fingerprinting reconstruction with Kalman filter.

PubMed

Zhang, Xiaodi; Zhou, Zechen; Chen, Shiyang; Chen, Shuo; Li, Rui; Hu, Xiaoping

2017-09-01

Magnetic resonance fingerprinting (MR fingerprinting or MRF) is a newly introduced quantitative magnetic resonance imaging technique, which enables simultaneous multi-parameter mapping in a single acquisition with improved time efficiency. The current MRF reconstruction method is based on dictionary matching, which may be limited by the discrete and finite nature of the dictionary and the computational cost associated with dictionary construction, storage and matching. In this paper, we describe a reconstruction method based on Kalman filter for MRF, which avoids the use of dictionary to obtain continuous MR parameter measurements. With this Kalman filter framework, the Bloch equation of inversion-recovery balanced steady state free-precession (IR-bSSFP) MRF sequence was derived to predict signal evolution, and acquired signal was entered to update the prediction. The algorithm can gradually estimate the accurate MR parameters during the recursive calculation. Single pixel and numeric brain phantom simulation were implemented with Kalman filter and the results were compared with those from dictionary matching reconstruction algorithm to demonstrate the feasibility and assess the performance of Kalman filter algorithm. The results demonstrated that Kalman filter algorithm is applicable for MRF reconstruction, eliminating the need for a pre-define dictionary and obtaining continuous MR parameter in contrast to the dictionary matching algorithm. Copyright © 2017 Elsevier Inc. All rights reserved.

Weakly Supervised Dictionary Learning

NASA Astrophysics Data System (ADS)

You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

2018-05-01

We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition

PubMed Central

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-01-01

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K-nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction. PMID:28346385

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

Blind compressive sensing dynamic MRI

PubMed Central

Lingala, Sajan Goud; Jacob, Mathews

2013-01-01

We propose a novel blind compressive sensing (BCS) frame work to recover dynamic magnetic resonance images from undersampled measurements. This scheme models the dynamic signal as a sparse linear combination of temporal basis functions, chosen from a large dictionary. In contrast to classical compressed sensing, the BCS scheme simultaneously estimates the dictionary and the sparse coefficients from the undersampled measurements. Apart from the sparsity of the coefficients, the key difference of the BCS scheme with current low rank methods is the non-orthogonal nature of the dictionary basis functions. Since the number of degrees of freedom of the BCS model is smaller than that of the low-rank methods, it provides improved reconstructions at high acceleration rates. We formulate the reconstruction as a constrained optimization problem; the objective function is the linear combination of a data consistency term and sparsity promoting ℓ1 prior of the coefficients. The Frobenius norm dictionary constraint is used to avoid scale ambiguity. We introduce a simple and efficient majorize-minimize algorithm, which decouples the original criterion into three simpler sub problems. An alternating minimization strategy is used, where we cycle through the minimization of three simpler problems. This algorithm is seen to be considerably faster than approaches that alternates between sparse coding and dictionary estimation, as well as the extension of K-SVD dictionary learning scheme. The use of the ℓ1 penalty and Frobenius norm dictionary constraint enables the attenuation of insignificant basis functions compared to the ℓ0 norm and column norm constraint assumed in most dictionary learning algorithms; this is especially important since the number of basis functions that can be reliably estimated is restricted by the available measurements. We also observe that the proposed scheme is more robust to local minima compared to K-SVD method, which relies on greedy sparse coding. Our phase transition experiments demonstrate that the BCS scheme provides much better recovery rates than classical Fourier-based CS schemes, while being only marginally worse than the dictionary aware setting. Since the overhead in additionally estimating the dictionary is low, this method can be very useful in dynamic MRI applications, where the signal is not sparse in known dictionaries. We demonstrate the utility of the BCS scheme in accelerating contrast enhanced dynamic data. We observe superior reconstruction performance with the BCS scheme in comparison to existing low rank and compressed sensing schemes. PMID:23542951

14 CFR 1214.701 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., and support hardware/software carried into space to accomplish a scientific mission or discrete... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Definitions. 1214.701 Section 1214.701 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT The Authority of the Space...

14 CFR 1214.701 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., and support hardware/software carried into space to accomplish a scientific mission or discrete... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Definitions. 1214.701 Section 1214.701 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT The Authority of the Space...

NASA in-house Commercially Developed Space Facility (CDSF) study report. Volume 1: Concept configuration definition

NASA Technical Reports Server (NTRS)

Deryder, L. J.; Chiger, H. D.; Deryder, D. D.; Detweiler, K. N.; Dupree, R. L.; Gillespie, V. P.; Hall, J. B.; Heck, M. L.; Herrick, D. C.; Katzberg, S. J.

1989-01-01

The results of a NASA in-house team effort to develop a concept definition for a Commercially Developed Space Facility (CDSF) are presented. Science mission utilization definition scenarios are documented, the conceptual configuration definition system performance parameters qualified, benchmark operational scenarios developed, space shuttle interface descriptions provided, and development schedule activity was assessed with respect to the establishment of a proposed launch date.

14 CFR 1203b.102 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Definitions. 1203b.102 Section 1203b.102 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SECURITY PROGRAMS; ARREST AUTHORITY AND USE OF FORCE BY NASA SECURITY FORCE PERSONNEL § 1203b.102 Definitions. Accredited Course of Training...

14 CFR 1203b.102 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Definitions. 1203b.102 Section 1203b.102 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SECURITY PROGRAMS; ARREST AUTHORITY AND USE OF FORCE BY NASA SECURITY FORCE PERSONNEL § 1203b.102 Definitions. Accredited Course of Training...

14 CFR 1203b.102 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Definitions. 1203b.102 Section 1203b.102 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SECURITY PROGRAMS; ARREST AUTHORITY AND USE OF FORCE BY NASA SECURITY FORCE PERSONNEL § 1203b.102 Definitions. Accredited Course of Training...

14 CFR 1203b.102 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Definitions. 1203b.102 Section 1203b.102 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SECURITY PROGRAMS; ARREST AUTHORITY AND USE OF FORCE BY NASA SECURITY FORCE PERSONNEL § 1203b.102 Definitions. Accredited Course of Training...

Review of "A Dictionary of Global Huayu"

ERIC Educational Resources Information Center

Li, Rui

2016-01-01

As the first Huayu dictionary published by the Commercial Press, "A Dictionary of Global Huayu" (Chinese Language) did a pioneer work in many aspects. It did expand the influence of Chinese and provided Chinese speaker abroad a valuable reference book for study and communication. Nevertheless, there are still some demerits. First of all,…

Variant Spellings in Modern American Dictionaries.

ERIC Educational Resources Information Center

Emery, Donald W.

A record of how present-day desk dictionaries are recognizing the existence of variant or secondary spellings for many common English words, this reference list can be used by teachers of English and authors of spelling lists. Originally published in 1958, this revised edition uses two dictionaries not in existence then and the revised editions of…