WorldWideScience

Sample records for extract relevant information

  1. Information extraction

    NARCIS (Netherlands)

    Zhang, Lei; Hoede, C.

    2002-01-01

    In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that

  2. Linking attentional processes and conceptual problem solving: Visual cues facilitate the automaticity of extracting relevant information from diagrams

    Directory of Open Access Journals (Sweden)

    Amy eRouinfar

    2014-09-01

    Full Text Available This study investigated links between lower-level visual attention processes and higher-level problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants’ attention to relevant areas to facilitate problem solving. Participants (N = 80 individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants’ verbal responses were used to determine their accuracy. The study produced two major findings. First, short duration visual cues can improve problem solving performance on a variety of insight physics problems, including transfer problems not sharing the surface features of the training problems, but instead sharing the underlying solution path. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers’ attention necessarily embodying the solution to the problem. Instead, the cueing effects were caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, these short duration visual cues when administered repeatedly over multiple training problems resulted in participants becoming more efficient at extracting the relevant information on the transfer problem, showing that such cues can improve the automaticity with which solvers extract relevant information from a problem. Both of these results converge on the conclusion that lower-order visual processes driven by attentional cues can influence higher-order cognitive processes

  3. Is Information Still Relevant?

    Science.gov (United States)

    Ma, Lia

    2013-01-01

    Introduction: The term "information" in information science does not share the characteristics of those of a nomenclature: it does not bear a generally accepted definition and it does not serve as the bases and assumptions for research studies. As the data deluge has arrived, is the concept of information still relevant for information…

  4. Information Needs/Relevance

    OpenAIRE

    Wildemuth, Barbara M.

    2009-01-01

    A user's interaction with a DL is often initiated as the result of the user experiencing an information need of some kind. Aspects of that experience and how it might affect the user's interactions with the DL are discussed in this module. In addition, users continuously make decisions about and evaluations of the materials retrieved from a DL, relative to their information needs. Relevance judgments, and their relationship to the user's information needs, are discussed in this module. Draft

  5. Has Financial Statement Information become Less Relevant?

    DEFF Research Database (Denmark)

    Thinggaard, Frank; Damkier, Jesper

    as the total market-adjusted return that could be earned from investment strategies based on foreknowledge of financial statement information. It answers the question: Are investments based on financial statement information able to capture progressively less information in security returns over time......? The sample is based on non-financial companies listed on the Copenhagen Stock Exchange in the period 1984-2002. Our analyses show that all the applied accounting measures are value-relevant as investment strategies based on the information earn positive market-adjusted returns in our sample period....... The results provide some indication of a decline in the value-relevance of earnings information in the 1984-2001 period, and mixed, but not statistically reliable, evidence for accounting measures where book value information and asset values are also extracted from financial statements. The results seem...

  6. Has Financial Statement Information become Less Relevant?

    DEFF Research Database (Denmark)

    Thinggaard, Frank; Damkier, Jesper

    as the total market-adjusted return that could be earned from investment strategies based on foreknowledge of financial statement information. It answers the question: Are investments based on financial statement information able to capture progressively less information in security returns over time......? The sample is based on non-financial companies listed on the Copenhagen Stock Exchange in the period 1984-2002. Our analyses show that all the applied accounting measures are value-relevant as investment strategies based on the information earn positive market-adjusted returns in our sample period....... The results provide some indication of a decline in the value-relevance of earnings information in the 1984-2001 period, and mixed, but not statistically reliable, evidence for accounting measures where book value information and asset values are also extracted from financial statements. The results seem...

  7. Information extraction system

    Science.gov (United States)

    Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

    2014-05-13

    An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

  8. Multimedia Information Extraction

    CERN Document Server

    Maybury, Mark T

    2012-01-01

    The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

  9. Relevance: An Interdisciplinary and Information Science Perspective

    Directory of Open Access Journals (Sweden)

    Howard Greisdorf

    2000-01-01

    Full Text Available Although relevance has represented a key concept in the field of information science for evaluating information retrieval effectiveness, the broader context established by interdisciplinary frameworks could provide greater depth and breadth to on-going research in the field. This work provides an overview of the nature of relevance in the field of information science with a cursory view of how cross-disciplinary approaches to relevance could represent avenues for further investigation into the evaluative characteristics of relevance as a means for enhanced understanding of human information behavior.

  10. Probing for Relevance: Information Theories and Translation

    Directory of Open Access Journals (Sweden)

    Daniel Dejica

    2009-06-01

    Full Text Available Recent studies claim that the more translators know about the structure and the dynamics of discourse, the more readily and accurately they can translate both the content and the spirit of a text. Similarly, international research projects highlight directions of research which aim at helping translators make reasonable and consistent decisions as to the relevance and reliability of source text features in the target text. Other recent studies stress the importance of developing information structure theories for translation. In line with such current research desiderata, the aim of this article is to test the relevance of information theories for translation. In the first part, information theories are presented from different linguistic perspectives. In the second part, their relevance for translation is tested on a series of texts by examining how they have been or can be applied to translation. The last part presents the conclusions of the analysis.

  11. Relevance, Pertinence and Information System Development

    Science.gov (United States)

    Kemp, D. A.

    1974-01-01

    The difference between pertinence and relevance is discussed. Other pairs of terms and the differences between their members are examined, and the suggestion is made that such studies could increase our understanding of the theory of information systems, and thence lead to practical improvements. (Author)

  12. Extracting information from multiplex networks.

    Science.gov (United States)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ̃(S) for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  13. Extracting Information from Multiplex Networks

    CERN Document Server

    Iacovacci, Jacopo

    2016-01-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from Big Data. For these reasons characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function $\\widetilde{\\Theta}^{S}$ for describing their mesoscale organization and community structure. As working examples for studying thes...

  14. Extracting information from multiplex networks

    Science.gov (United States)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  15. ACCOUNTING INFORMATION RELEVANCE ON CAPITAL MARKETS

    OpenAIRE

    Ciprian-Dan COSTEA

    2015-01-01

    The research in accounting with specific application on capital markets represents a special resort of accounting research. The development of such studies was favored by the evolution and strong growth of capital markets in our daily contemporary life and by the extention of base accounting concepts to international level. In such circumstances, studies regarding the evolution of concepts like value relevance, efficient markets, accounting information and its dissemination, fair value, are ...

  16. IDENTIFICATION OF INFORMATION RELEVANT FOR INTERNATIONAL MARKETING

    Directory of Open Access Journals (Sweden)

    Jovanovic, Z.

    2016-07-01

    Full Text Available A basic ingredient of any market selection program is the availability of market information. As a general observation, the sources of international market and product information can be characterized as overwhelming, the problem being to identify the relevant data when needed. For international marketers this identification problem can be partly solved through the establishment of computerized databases, which must be continually screened and updated. For selecting new markets, and to support ongoing decisions, marketing decision support systems have been developed to simplify the whole process.

  17. 基于主题描述模型的相关性判断在网页信息抽取中的应用%The Application of Topic-Relevance in Web Information Extraction

    Institute of Scientific and Technical Information of China (English)

    谭胜; 马静; 吴一占

    2011-01-01

    Information extraction from the massive web source is an important way to obtain valuable information and the topic relevant judgment of target web page contents is one of the important steps. At present, manual screening and document training that is the main method for relevance judgment is low efficiency and duplication. In this paper, we attempt to introduce topic description model for measuring relevant analysis. Topic description model measures the topic relevance from the object of task. After the page content analysis, we will weight the document by analyzing the document frequency of the keywords and the change trends of the frequency from the task topic description model for correlation judgment. The experiment verified that the method can effectively improve the efficiency of web information extraction and accuracy, and we get the principle for setting the parameters.%信息抽取是从海量网页获取有价值信息的重要方式,对目标网页内容进行主题相关性判断是提高信息抽取效率和准确性的关键环节.目前的相关性判断主要采用人工筛选和文档训练的方法,这其中存在效率低、重复训练等问题,而本文尝试针对抽取任务引入主题描述模型用于网页内容的主题相关性判断.从任务的主题描述模型的角度出发,计算模型中的关键词基于标记信息的加权频率,将网页内容进行量化表示,然后分析关键词加权频率关于任务主题描述模型的变化来判断网页内容的主题相关性.最后通过对比该方法在国防产品信息抽取中结果,实验证明该方法大大提高了网页信息抽取的效率和准确性.

  18. ACCOUNTING INFORMATION RELEVANCE ON CAPITAL MARKETS

    Directory of Open Access Journals (Sweden)

    Ciprian-Dan COSTEA

    2015-06-01

    Full Text Available The research in accounting with specific application on capital markets represents a special resort of accounting research. The development of such studies was favored by the evolution and strong growth of capital markets in our daily contemporary life and by the extention of base accounting concepts to international level. In such circumstances, studies regarding the evolution of concepts like value relevance, efficient markets, accounting information and its dissemination, fair value, are welcomed on the field of accounting research with applicability to the capital markets. This study comes to outline some positions regarding this topic of accounting research.

  19. ACCOUNTING INFORMATION RELEVANCE ON CAPITAL MARKETS

    Directory of Open Access Journals (Sweden)

    Ciprian-Dan COSTEA

    2015-06-01

    Full Text Available The research in accounting with specific application on capital markets represents a special resort of accounting research. The development of such studies was favored by the evolution and strong growth of capital markets in our daily contemporary life and by the extention of base accounting concepts to international level. In such circumstances, studies regarding the evolution of concepts like value relevance, efficient markets, accounting information and its dissemination, fair value, are welcomed on the field of accounting research with applicability to the capital markets. This study comes to outline some positions regarding this topic of accounting research.

  20. An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

    Science.gov (United States)

    Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

    2010-04-01

    Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

  1. Advances in the quantification of relevant allergens in allergenic extracts.

    Science.gov (United States)

    Batard, T; Nony, E; Hrabina, M; Chabre, H; Frati, F; Moingeon, P

    2013-10-01

    Relevant allergens are major contributors to the safety and efficacy of allergenic extracts used in allergen immunotherapy (AIT). As such, they should be accurately quantified, as recommended by the 2008 European guidelines on allergen products. Until now, the quantification of relevant allergens was mainly performed by using immunoassays (e.g. ELISA) that relying upon specific antibodies. Although antibody-based quantification is commonly used to assess the concentration of relevant allergens in allergenic extracts, results must be taken with caution in the light of the inherent limitations of such techniques. In the present study, we discuss how those limitations can be overcome by using comprehensive mass spectrometry-based techniques.

  2. Extracting laboratory test information from biomedical text

    Directory of Open Access Journals (Sweden)

    Yanna Shen Kang

    2013-01-01

    Full Text Available Background: No previous study reported the efficacy of current natural language processing (NLP methods for extracting laboratory test information from narrative documents. This study investigates the pathology informatics question of how accurately such information can be extracted from text with the current tools and techniques, especially machine learning and symbolic NLP methods. The study data came from a text corpus maintained by the U.S. Food and Drug Administration, containing a rich set of information on laboratory tests and test devices. Methods: The authors developed a symbolic information extraction (SIE system to extract device and test specific information about four types of laboratory test entities: Specimens, analytes, units of measures and detection limits. They compared the performance of SIE and three prominent machine learning based NLP systems, LingPipe, GATE and BANNER, each implementing a distinct supervised machine learning method, hidden Markov models, support vector machines and conditional random fields, respectively. Results: Machine learning systems recognized laboratory test entities with moderately high recall, but low precision rates. Their recall rates were relatively higher when the number of distinct entity values (e.g., the spectrum of specimens was very limited or when lexical morphology of the entity was distinctive (as in units of measures, yet SIE outperformed them with statistically significant margins on extracting specimen, analyte and detection limit information in both precision and F-measure. Its high recall performance was statistically significant on analyte information extraction. Conclusions: Despite its shortcomings against machine learning methods, a well-tailored symbolic system may better discern relevancy among a pile of information of the same type and may outperform a machine learning system by tapping into lexically non-local contextual information such as the document structure.

  3. Automated information extraction from web APIs documentation

    OpenAIRE

    Ly, Papa Alioune; Pedrinaci, Carlos; Domingue, John

    2012-01-01

    A fundamental characteristic of Web APIs is the fact that, de facto, providers hardly follow any standard practices while implementing, publishing, and documenting their APIs. As a consequence, the discovery and use of these services by third parties is significantly hampered. In order to achieve further automation while exploiting Web APIs we present an approach for automatically extracting relevant technical information from the Web pages documenting them. In particular we have devised two ...

  4. Extracting useful information from images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    2011-01-01

    The paper presents an overview of methods for extracting useful information from digital images. It covers various approaches that utilized different properties of images, like intensity distribution, spatial frequencies content and several others. A few case studies including isotropic...... and heterogeneous, congruent and non-congruent images are used to illustrate how the described methods work and to compare some of them...

  5. Informed consent in dental extractions.

    Directory of Open Access Journals (Sweden)

    José Luis Capote Femenías

    2009-07-01

    Full Text Available When performing any oral intervention, particularly dental extractions, the specialist should have the oral or written consent of the patient. This consent includes the explanation of all possible complications, whether typical, very serious or personalized associated with the previous health condition, age, profession, religion or any other characteristic of the patient, as well as the possi.ble benefits of the intervention. This article is related with the bioethical aspects related with dental extractions, in order to determine the main elements that the informed consent should include.

  6. Relevance of information in informed consent to digestive endoscopy.

    Science.gov (United States)

    Stroppa, I

    2000-09-01

    In the field of instrumental methodologies, digestive endoscopy is widely applied diagnostic and therapeutic investigation, involving ethical and medico-legal problems connected with its performance. So, in the light of the present doctor-patient relationship, we therefore wished to reconsider the relevant meaning of preventive information which is indispensable for obtaining the patient's consent to the doctor's action. The aim of this present paper is to provide adequate knowledge, for who ever is about to undergo endoscopic examination, by introducing new informative forms and a new system for their distribution, without negatively affecting the patient's state of anxiety. We have tried to attribute greater responsibility to the person of the doctor requesting the examination, in providing information for the patient, and to underline, in the case of complications, the important conduct of the endoscopic specialist, who must not fail to obtain new informed consent before submitting the patient to any action directed towards treatment of the specific complication. If ignored, these medico-legal aspects can formulate the responsibility of the doctor both in clinical or penal context.

  7. Signal Enhancement as Minimization of Relevant Information Loss

    CERN Document Server

    Geiger, Bernhard C

    2012-01-01

    We introduce the notion of relevant information loss for the purpose of casting the signal enhancement problem in information-theoretic terms. We show that many algorithms from machine learning can be reformulated using relevant information loss, which allows their application to the aforementioned problem. As a particular example we analyze principle component analysis for dimensionality reduction, discuss its optimality, and show that the relevant information loss can indeed vanish if the relevant information is concentrated on a lower-dimensional subspace of the input space.

  8. Web-Based Information Extraction Technology

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Information extraction techniques on the Web are the current research hotspot. Now many information extraction techniques based on different principles have appeared and have different capabilities. We classify the existing information extraction techniques by the principle of information extraction and analyze the methods and principles of semantic information adding, schema defining,rule expression, semantic items locating and object locating in the approaches. Based on the above survey and analysis,several open problems are discussed.

  9. Information Extraction and Webpage Understanding

    Directory of Open Access Journals (Sweden)

    M.Sharmila Begum

    2011-11-01

    Full Text Available The two most important tasks in information extraction from the Web are webpage structure understanding and natural language sentences processing. However, little work has been done toward an integrated statistical model for understanding webpage structures and processing natural language sentences within the HTML elements. Our recent work on webpage understanding introduces a joint model of Hierarchical Conditional Random Fields (HCRFs and extended Semi-Markov Conditional Random Fields (Semi-CRFs to leverage the page structure understanding results in free text segmentation and labeling. In this top-down integration model, the decision of the HCRF model could guide the decision making of the Semi-CRF model. However, the drawback of the topdown integration strategy is also apparent, i.e., the decision of the Semi-CRF model could not be used by the HCRF model to guide its decision making. This paper proposed a novel framework called WebNLP, which enables bidirectional integration of page structure understanding and text understanding in an iterative manner. We have applied the proposed framework to local business entity extraction and Chinese person and organization name extraction. Experiments show that the WebNLP framework achieved significantly better performance than existing methods.

  10. Value Relevance of Accounting Information in the United Arab Emirates

    National Research Council Canada - National Science Library

    Jamal Barzegari Khanagha

    2011-01-01

    This paper examines the value relevance of accounting information in per and post-periods of International Financial Reporting Standards implementation using the regression and portfolio approaches...

  11. Extracting the relevant delays in time series modelling

    DEFF Research Database (Denmark)

    Goutte, Cyril

    1997-01-01

    selection, and more precisely stepwise forward selection. The method is compared to other forward selection schemes, as well as to a nonparametric tests aimed at estimating the embedding dimension of time series. The final application extends these results to the efficient estimation of FIR filters on some......In this contribution, we suggest a convenient way to use generalisation error to extract the relevant delays from a time-varying process, i.e. the delays that lead to the best prediction performance. We design a generalisation-based algorithm that takes its inspiration from traditional variable...

  12. Machine learning for relevance of information in crisis response

    NARCIS (Netherlands)

    C.P.M. Netten

    2015-01-01

    Efficient communication during crisis response situations is a major challenge for involved emergency responders. Lack of relevant information or too much irrelevant information hampers the emergency responders’ decision-making process, workflow and situational awareness. Despite efforts to better c

  13. SEMANTIC INFORMATION EXTRACTION IN UNIVERSITY DOMAIN

    Directory of Open Access Journals (Sweden)

    Swathi

    2012-07-01

    Full Text Available Today’s conventional search engines hardly do provide the essential content relevant to the user’s search query. This is because the context and semantics of the request made by the user is not analyzed to the full extent. So here the need for a semantic web search arises. SWS is upcoming in the area of web search which combines Natural Language Processing and Artificial Intelligence. The objective of the work done here is to design, develop and implement a semantic search engine- SIEU(Semantic Information Extraction in University Domain confined to the university domain. SIEU uses ontology as a knowledge base for the information retrieval process. It is not just a mere keyword search. It is one layer above what Google or any other search engines retrieve by analyzing just the keywords. Here the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the user query through keyword expansion. The results obtained here will be accurate enough to satisfy the request made by the user. The level of accuracy will be enhanced since the query is analyzed semantically. The system will be of great use to the developers and researchers who work on web. The Google results are re-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied which fetches more apt results for the user query.

  14. A Compositional Relevance Model for Adaptive Information Retrieval

    Science.gov (United States)

    Mathe, Nathalie; Chen, James; Lu, Henry, Jr. (Technical Monitor)

    1994-01-01

    There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

  15. Improving information extraction using a probability-based approach

    DEFF Research Database (Denmark)

    Kim, S.; Ahmed, Saeema; Wallace, K.

    2007-01-01

    or retire. It is becoming essential to retrieve vital information from archived product documents, if it is available. There is, therefore, great interest in ways of extracting relevant and sharable information from documents. A keyword-based search is commonly used, but studies have shown...

  16. Value Relevance of Accounting Information in the United Arab Emirates

    Directory of Open Access Journals (Sweden)

    Jamal Barzegari Khanagha

    2011-01-01

    Full Text Available This paper examines the value relevance of accounting information in per and post-periods of International Financial Reporting Standards implementation using the regression and portfolio approaches for sample of the UAE companies. The results obtained from a combination of regression and portfolio approaches, show accounting information is value relevant in UAE stock market. A comparison of the results for the periods before and after adoption, based on both regression and portfolio approaches, shows a decline in value relevance of accounting information after the reform in accounting standards. It could be interpreted to mean that following to IFRS in UAE didn’t improve value relevancy of accounting information. However, results based on and portfolio approach shows that cash flows’ incremental information content increased for the post-IFRS period.

  17. Robo-Psychophysics: Extracting Behaviorally Relevant Features from the Output of Sensors on a Prosthetic Finger.

    Science.gov (United States)

    Delhaye, Benoit P; Schluter, Erik W; Bensmaia, Sliman J

    2016-01-01

    Efforts are underway to restore sensorimotor function in amputees and tetraplegic patients using anthropomorphic robotic hands. For this approach to be clinically viable, sensory signals from the hand must be relayed back to the patient. To convey tactile feedback necessary for object manipulation, behaviorally relevant information must be extracted in real time from the output of sensors on the prosthesis. In the present study, we recorded the sensor output from a state-of-the-art bionic finger during the presentation of different tactile stimuli, including punctate indentations and scanned textures. Furthermore, the parameters of stimulus delivery (location, speed, direction, indentation depth, and surface texture) were systematically varied. We developed simple decoders to extract behaviorally relevant variables from the sensor output and assessed the degree to which these algorithms could reliably extract these different types of sensory information across different conditions of stimulus delivery. We then compared the performance of the decoders to that of humans in analogous psychophysical experiments. We show that straightforward decoders can extract behaviorally relevant features accurately from the sensor output and most of them outperform humans.

  18. Information Extraction from Unstructured Text for the Biodefense Knowledge Center

    Energy Technology Data Exchange (ETDEWEB)

    Samatova, N F; Park, B; Krishnamurthy, R; Munavalli, R; Symons, C; Buttler, D J; Cottom, T; Critchlow, T J; Slezak, T

    2005-04-29

    The Bio-Encyclopedia at the Biodefense Knowledge Center (BKC) is being constructed to allow an early detection of emerging biological threats to homeland security. It requires highly structured information extracted from variety of data sources. However, the quantity of new and vital information available from every day sources cannot be assimilated by hand, and therefore reliable high-throughput information extraction techniques are much anticipated. In support of the BKC, Lawrence Livermore National Laboratory and Oak Ridge National Laboratory, together with the University of Utah, are developing an information extraction system built around the bioterrorism domain. This paper reports two important pieces of our effort integrated in the system: key phrase extraction and semantic tagging. Whereas two key phrase extraction technologies developed during the course of project help identify relevant texts, our state-of-the-art semantic tagging system can pinpoint phrases related to emerging biological threats. Also we are enhancing and tailoring the Bio-Encyclopedia by augmenting semantic dictionaries and extracting details of important events, such as suspected disease outbreaks. Some of these technologies have already been applied to large corpora of free text sources vital to the BKC mission, including ProMED-mail, PubMed abstracts, and the DHS's Information Analysis and Infrastructure Protection (IAIP) news clippings. In order to address the challenges involved in incorporating such large amounts of unstructured text, the overall system is focused on precise extraction of the most relevant information for inclusion in the BKC.

  19. Personalized Web Services for Web Information Extraction

    CERN Document Server

    Jarir, Zahi; Erradi, Mahammed

    2011-01-01

    The field of information extraction from the Web emerged with the growth of the Web and the multiplication of online data sources. This paper is an analysis of information extraction methods. It presents a service oriented approach for web information extraction considering both web data management and extraction services. Then we propose an SOA based architecture to enhance flexibility and on-the-fly modification of web extraction services. An implementation of the proposed architecture is proposed on the middleware level of Java Enterprise Edition (JEE) servers.

  20. Factors Affecting the Value Relevance of Accounting Information

    OpenAIRE

    Mahmoud Dehghan Nayeri; Ali Faal Ghayoumi; Mohammad Ali Bidari

    2012-01-01

    The present study examines the factors affecting the value relevance of accounting information for investors in the Tehran Stock Exchange over the period of six years. In this study, the effect of four factors; being profitable or loss generating, company size, earnings stability and company growth on the value relevance of accounting information have been studied. For this purpose Ohlson model and the cumulative regression analysis is used in order to examine the hypotheses and as the basis ...

  1. Extract relevant features from DEM for groundwater potential mapping

    Science.gov (United States)

    Liu, T.; Yan, H.; Zhai, L.

    2015-06-01

    Multi-criteria evaluation (MCE) method has been applied much in groundwater potential mapping researches. But when to data scarce areas, it will encounter lots of problems due to limited data. Digital Elevation Model (DEM) is the digital representations of the topography, and has many applications in various fields. Former researches had been approved that much information concerned to groundwater potential mapping (such as geological features, terrain features, hydrology features, etc.) can be extracted from DEM data. This made using DEM data for groundwater potential mapping is feasible. In this research, one of the most widely used and also easy to access data in GIS, DEM data was used to extract information for groundwater potential mapping in batter river basin in Alberta, Canada. First five determining factors for potential ground water mapping were put forward based on previous studies (lineaments and lineament density, drainage networks and its density, topographic wetness index (TWI), relief and convergence Index (CI)). Extraction methods of the five determining factors from DEM were put forward and thematic maps were produced accordingly. Cumulative effects matrix was used for weight assignment, a multi-criteria evaluation process was carried out by ArcGIS software to delineate the potential groundwater map. The final groundwater potential map was divided into five categories, viz., non-potential, poor, moderate, good, and excellent zones. Eventually, the success rate curve was drawn and the area under curve (AUC) was figured out for validation. Validation result showed that the success rate of the model was 79% and approved the method's feasibility. The method afforded a new way for researches on groundwater management in areas suffers from data scarcity, and also broaden the application area of DEM data.

  2. Software Helps Retrieve Information Relevant to the User

    Science.gov (United States)

    Mathe, Natalie; Chen, James

    2003-01-01

    The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

  3. An architecture for biological information extraction and representation.

    Science.gov (United States)

    Vailaya, Aditya; Bluvas, Peter; Kincaid, Robert; Kuchinsky, Allan; Creech, Michael; Adler, Annette

    2005-02-15

    Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. In this paper, we present a general architecture, called ALFA, for information extraction and representation from diverse biological data. The ALFA architecture consists of: (i) a networked, hierarchical, hyper-graph object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. As part of our research efforts to explore this space, we have currently prototyped the ALFA object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. In particular, we describe BioFerret, a meta-search tool for searching and filtering relevant information from the web, and ALFA Text Viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. We further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying ALFA representation. aditya_vailaya@agilent.com.

  4. Information- Theoretic Analysis for the Difficulty of Extracting Hidden Information

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wei-ming; LI Shi-qu; CAO Jia; LIU Jiu-fen

    2005-01-01

    The difficulty of extracting hidden information,which is essentially a kind of secrecy, is analyzed by information-theoretic method. The relations between key rate, message rate, hiding capacity and difficulty of extraction are studied in the terms of unicity distance of stego-key, and the theoretic conclusion is used to analyze the actual extracting attack on Least Significant Bit(LSB) steganographic algorithms.

  5. Enhanced Pattern Representation in Information Extraction

    Institute of Scientific and Technical Information of China (English)

    廖乐健; 曹元大; 张映波

    2004-01-01

    Traditional pattern representation in information extraction lack in the ability of representing domain-specific concepts and are therefore devoid of flexibility. To overcome these restrictions, an enhanced pattern representation is designed which includes ontological concepts, neighboring-tree structures and soft constraints. An information-extraction inference engine based on hypothesis-generation and conflict-resolution is implemented. The proposed technique is successfully applied to an information extraction system for Chinese-language query front-end of a job-recruitment search engine.

  6. Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

    Science.gov (United States)

    Eugster, Manuel J. A.; Ruotsalo, Tuukka; Spapé, Michiel M.; Barral, Oswald; Ravaja, Niklas; Jacucci, Giulio; Kaski, Samuel

    2016-12-01

    Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications.

  7. THE RELEVANCE OF ECONOMIC INFORMATION IN ANALYZING THE ECONOMIC PERFORMANCE

    Directory of Open Access Journals (Sweden)

    PATRUTA MIRCEA IOAN

    2016-12-01

    Full Text Available The performance analysis is based on an informational system, which provides financial information in various formatsand with various applicabilities.We intend to formulate a set of important caracteristics of financial information along with identifying a set of relevant financial rates and indicatorsused to appreciate the performance level of a company. Economic performance can be interpreted in different ways at each level of analysis. Generally, it refers to economic growth, increased productivity and profitability. The growth of labor productivity or increased production per worker is a measure of efficient use of resources in value creation.

  8. Information Extraction From Chemical Patents

    Directory of Open Access Journals (Sweden)

    Sandra Bergmann

    2012-01-01

    Full Text Available The development of new chemicals or pharmaceuticals is preceded by an indepth analysis of published patents in this field. This information retrieval is a costly and time inefficient step when done by a human reader, yet it is mandatory for potential success of an investment. The goal of the research project UIMA-HPC is to automate and hence speed-up the process of knowledge mining about patents. Multi-threaded analysis engines, developed according to UIMA (Unstructured Information Management Architecture standards, process texts and images in thousands of documents in parallel. UNICORE (UNiform Interface to COmputing Resources workflow control structures make it possible to dynamically allocate resources for every given task to gain best cpu-time/realtime ratios in an HPC environment.

  9. The pricing relevance of insider information; Die Preiserheblichkeit von Insiderinformationen

    Energy Technology Data Exchange (ETDEWEB)

    Kruse, Dominik

    2011-07-01

    The publication attempts to describe the so far discussion concerning the feature of pricing relevance and to develop it further with the aid of new research approaches. First, a theoretical outline is presented of the elementary regulation problem of insider trading, its historical development, and the regulation goals of the WpHG. This is followed by an analysis of the concrete specifications of the law. In view of the exemplarity of US law, a country with long experience in regulation of the capital market, the materiality doctrine of US insider law is gone into in some detail. The goals and development of the doctrine are reviewed in the light of court rulings. The third part outlines the requirements of German law in order to forecast the pricing relevance of insider information, while the final part presents a critical review of the current regulations on pricing relevance. (orig./RHM)

  10. Application of GIS to Geological Information Extraction

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    GIS. a powerful tool for processing spatial data, is advantageous in its spatial overlaying. In this paper, GIS is applied to the extraction of geological information. Information associated with mineral resources is chosen to delineate the geo-anomalies, the basis of ore-forming anomalies and of mineral-deposit location. This application is illustrated with an example in Weixi area, Yunnan Province.

  11. Bootstrapping agency: How control-relevant information affects motivation.

    Science.gov (United States)

    Karsh, Noam; Eitam, Baruch; Mark, Ilya; Higgins, E Tory

    2016-10-01

    How does information about one's control over the environment (e.g., having an own-action effect) influence motivation? The control-based response selection framework was proposed to predict and explain such findings. Its key tenant is that control relevant information modulates both the frequency and speed of responses by determining whether a perceptual event is an outcome of one's actions or not. To test this framework empirically, the current study examines whether and how temporal and spatial contiguity/predictability-previously established as being important for one's sense of agency-modulate motivation from control. In 5 experiments, participants responded to a cue, potentially triggering a perceptual effect. Temporal (Experiments 1a-c) and spatial (Experiments 2a and b) contiguity/predictability between actions and their potential effects were experimentally manipulated. The influence of these control-relevant factors was measured, both indirectly (through their effect on explicit judgments of agency) and directly on response time and response frequency. The pattern of results was highly consistent with the control-based response selection framework in suggesting that control relevant information reliably modulates the impact of "having an effect" on different levels of action selection. We discuss the implications of this study for the notion of motivation from control and for the empirical work on the sense of agency. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Extraction of the relevant delays for temporal modeling

    DEFF Research Database (Denmark)

    Goutte, Cyril

    2000-01-01

    When modeling temporal processes, just like in pattern recognition, selecting the optimal number of inputs is of central concern. We take advantage of specific features of temporal modeling to propose a novel method for extracting the inputs that attempts to yield the best predictive performance....... The method relies on the use of estimators of the generalization error to assess the predictive performance of the model. This technique is first applied to time series processing, where we perform a number of experiments on synthetic data, as well as a real life dataset, and compare the results...

  13. Iterative Filtering of Retrieved Information to Increase Relevance

    Directory of Open Access Journals (Sweden)

    Robert Zeidman

    2007-12-01

    Full Text Available Efforts have been underway for years to find more effective ways to retrieve information from large knowledge domains. This effort is now being driven particularly by the Internet and the vast amount of information that is available to unsophisticated users. In the early days of the Internet, some effort involved allowing users to enter Boolean equations of search terms into search engines, for example, rather than just a list of keywords. More recently, effort has focused on understanding a user's desires from past search histories in order to narrow searches. Also there has been much effort to improve the ranking of results based on some measure of relevancy. This paper discusses using iterative filtering of retrieved information to focus in on useful information. This work was done for finding source code correlation and the author extends his findings to Internet searching and e-commerce. The paper presents specific information about a particular filtering application and then generalizes it to other forms of information retrieval.

  14. Relevant Feature Integration and Extraction for Single-Trial Motor Imagery Classification

    Directory of Open Access Journals (Sweden)

    Lili Li

    2017-06-01

    Full Text Available Brain computer interfaces provide a novel channel for the communication between brain and output devices. The effectiveness of the brain computer interface is based on the classification accuracy of single trial brain signals. The common spatial pattern (CSP algorithm is believed to be an effective algorithm for the classification of single trial brain signals. As the amplitude feature for spatial projection applied by this algorithm is based on a broad frequency bandpass filter (mainly 5–30 Hz in which the frequency band is often selected by experience, the CSP is sensitive to noise and the influence of other irrelevant information in the selected broad frequency band. In this paper, to improve the CSP, a novel relevant feature integration and extraction algorithm is proposed. Before projecting, we integrated the motor relevant information to suppress the interference of noise and irrelevant information, as well as to improve the spatial difference for projection. The algorithm was evaluated with public datasets. It showed significantly better classification performance with single trial electroencephalography (EEG data, increasing by 6.8% compared with the CSP.

  15. Extraction of information from a single quantum

    OpenAIRE

    Paraoanu, G. S.

    2011-01-01

    We investigate the possibility of performing quantum tomography on a single qubit with generalized partial measurements and the technique of measurement reversal. Using concepts from statistical decision theory, we prove that, somewhat surprisingly, no information can be obtained using this scheme. It is shown that, irrespective of the measurement technique used, extraction of information from single quanta is at odds with other general principles of quantum physics.

  16. DKIE: Open Source Information Extraction for Danish

    DEFF Research Database (Denmark)

    Derczynski, Leon; Field, Camilla Vilhelmsen; Bøgh, Kenneth Sejdenfaden

    2014-01-01

    Danish is a major Scandinavian language spoken daily by around six million people. However, it lacks a unified, open set of NLP tools. This demonstration will introduce DKIE, an extensible open-source toolkit for processing Danish text. We implement an information extraction architecture for Danish...

  17. DKIE: Open Source Information Extraction for Danish

    DEFF Research Database (Denmark)

    Derczynski, Leon; Field, Camilla Vilhelmsen; Bøgh, Kenneth Sejdenfaden

    2014-01-01

    Danish is a major Scandinavian language spoken daily by around six million people. However, it lacks a unified, open set of NLP tools. This demonstration will introduce DKIE, an extensible open-source toolkit for processing Danish text. We implement an information extraction architecture for Danish...... independently or with the Stanford NLP toolkit....

  18. Advanced applications of natural language processing for performing information extraction

    CERN Document Server

    Rodrigues, Mário

    2015-01-01

    This book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and regulations, books and newspapers, and social web. Readers are introduced to the problem of IE and its current challenges and limitations, supported with examples. The book discusses the need to fill the gap between documents, data, and people, and provides a broad overview of the technology supporting IE. The authors present a generic architecture for developing systems that are able to learn how to extract relevant information from natural language documents, and illustrate how to implement working systems using state-of-the-art and freely available software tools. The book also discusses concrete applications illustrating IE uses.   ·         Provides an overview of state-of-the-art technology in information extraction (IE), discussing achievements and limitations for t...

  19. Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb.

    Directory of Open Access Journals (Sweden)

    Anat Kahan

    2016-03-01

    Full Text Available For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse's strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female's receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons.

  20. Web Information Extraction%Web信息抽取

    Institute of Scientific and Technical Information of China (English)

    李晶; 陈恩红

    2003-01-01

    With the tremendous amount of information available on the Web, the ability to quickly obtain information has become a crucial problem. It is not enough for us to acquire information only with Web information retrieval technology. Therefore more and more people pay attention to Web information extraction technology. This paper first in- troduces some concepts of information extraction technology, then introduces and analyzes several typical Web information extraction methods based on the differences in extraction patterns.

  1. Unsupervised information extraction by text segmentation

    CERN Document Server

    Cortez, Eli

    2013-01-01

    A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

  2. Extracting the information backbone in online system.

    Science.gov (United States)

    Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

    2013-01-01

    Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

  3. Extracting the information backbone in online system

    CERN Document Server

    Zhang, Qian-Ming; Shang, Ming-Sheng

    2013-01-01

    Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers mainly dedicated to improve the recommendation performance (accuracy and diversity) of the algorithms while overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improve both of...

  4. Diagnostically relevant facial gestalt information from ordinary photos.

    Science.gov (United States)

    Ferry, Quentin; Steinberg, Julia; Webber, Caleb; FitzPatrick, David R; Ponting, Chris P; Zisserman, Andrew; Nellåker, Christoffer

    2014-06-24

    Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

  5. Inclusion of Relevance Information in the Term Discrimination Model.

    Science.gov (United States)

    Biru, Tesfaye; And Others

    1989-01-01

    Discusses the effect of including relevance data on the calculation of term discrimination values in bibliographic databases. Algorithms that calculate the ability of index terms to discriminate between relevant and non-relevant documents are described and tested. The results are discussed in terms of the relationship between term frequency and…

  6. Audio enabled information extraction system for cricket and hockey domains

    CERN Document Server

    Saraswathi, S; B., Sai Vamsi Krishna; S, Suresh Reddy

    2010-01-01

    The proposed system aims at the retrieval of the summarized information from the documents collected from web based search engine as per the user query related to cricket and hockey domain. The system is designed in a manner that it takes the voice commands as keywords for search. The parts of speech in the query are extracted using the natural language extractor for English. Based on the keywords the search is categorized into 2 types: - 1.Concept wise - information retrieved to the query is retrieved based on the keywords and the concept words related to it. The retrieved information is summarized using the probabilistic approach and weighted means algorithm.2.Keyword search - extracts the result relevant to the query from the highly ranked document retrieved from the search by the search engine. The relevant search results are retrieved and then keywords are used for summarizing part. During summarization it follows the weighted and probabilistic approaches in order to identify the data comparable to the k...

  7. Digital image processing for information extraction.

    Science.gov (United States)

    Billingsley, F. C.

    1973-01-01

    The modern digital computer has made practical image processing techniques for handling nonlinear operations in both the geometrical and the intensity domains, various types of nonuniform noise cleanup, and the numerical analysis of pictures. An initial requirement is that a number of anomalies caused by the camera (e.g., geometric distortion, MTF roll-off, vignetting, and nonuniform intensity response) must be taken into account or removed to avoid their interference with the information extraction process. Examples illustrating these operations are discussed along with computer techniques used to emphasize details, perform analyses, classify materials by multivariate analysis, detect temporal differences, and aid in human interpretation of photos.

  8. Extraction of information from unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H.; DeLand, S.M.; Crowder, S.V.

    1995-11-01

    Extracting information from unstructured text has become an emphasis in recent years due to the large amount of text now electronically available. This status report describes the findings and work done by the end of the first year of a two-year LDRD. Requirements of the approach included that it model the information in a domain independent way. This means that it would differ from current systems by not relying on previously built domain knowledge and that it would do more than keyword identification. Three areas that are discussed and expected to contribute to a solution include (1) identifying key entities through document level profiling and preprocessing, (2) identifying relationships between entities through sentence level syntax, and (3) combining the first two with semantic knowledge about the terms.

  9. Extracting the information backbone in online system.

    Directory of Open Access Journals (Sweden)

    Qian-Ming Zhang

    Full Text Available Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such "less can be more" feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.

  10. Extracting the Information Backbone in Online System

    Science.gov (United States)

    Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

    2013-01-01

    Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such “less can be more” feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency. PMID:23690946

  11. Extraction of quantifiable information from complex systems

    CERN Document Server

    Dahmen, Wolfgang; Griebel, Michael; Hackbusch, Wolfgang; Ritter, Klaus; Schneider, Reinhold; Schwab, Christoph; Yserentant, Harry

    2014-01-01

    In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as w...

  12. The relevance of irrelevant information in the dictator game

    OpenAIRE

    Ramalingam, Abhijit

    2012-01-01

    We examine the sensitivity of the dictator game to information provided to subjects. We investigate if individuals internalize completely irrelevant information about players when making allocation decisions. Subjects are provided with their score and the scores of recipients on a quiz prior to making decisions in multiple dictator games. Quiz scores have no bearing on the game or on players' endowments and hence represent extraneous information. We find that dictators reward good performance...

  13. Respiratory Information Extraction from Electrocardiogram Signals

    KAUST Repository

    Amin, Gamal El Din Fathy

    2010-12-01

    The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs. In this thesis, several methods for the extraction of respiratory process information from the ECG signal are presented. These methods allow an estimation of the lung volume and the lung pressure from the ECG signal. The potential benefit of this is to eliminate the corresponding sensors used to measure the respiration activity. A reduction of the number of sensors connected to patients will increase patients’ comfort and reduce the costs associated with healthcare. As a further result, the efficiency of diagnosing respirational disorders will increase since the respiration activity can be monitored with a common, widely available method. The developed methods can also improve the detection of respirational disorders that occur while patients are sleeping. Such disorders are commonly diagnosed in sleeping laboratories where the patients are connected to a number of different sensors. Any reduction of these sensors will result in a more natural sleeping environment for the patients and hence a higher sensitivity of the diagnosis.

  14. relevance of information warfare models to critical infrastructure ...

    African Journals Online (AJOL)

    ismith

    Department of Homeland Security defines critical infrastructure as “the assets, systems, and networks, whether physical or virtual, so vital to the United States that ... result in noticeable effects in the information, energy or physical distribution ...

  15. 50 CFR 424.13 - Sources of information and relevant data.

    Science.gov (United States)

    2010-10-01

    ... 50 Wildlife and Fisheries 7 2010-10-01 2010-10-01 false Sources of information and relevant data... Sources of information and relevant data. When considering any revision of the lists, the Secretary shall..., administrative reports, maps or other graphic materials, information received from experts on the subject, and...

  16. Method for Extracting Product Information from TV Commercial

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2011-09-01

    Full Text Available Television (TV Commercial program contains important product information that displayed only in seconds. People who need that information has no insufficient time for noted it, even just for reading that information. This research work focus on automatically detect text and extract important information from a TV commercial to provide information in real time and for video indexing. We propose method for product information extraction from TV commercial using knowledge based system with pattern matching rule based method. Implementation and experiments on 50 commercial screenshot images achieved a high accuracy result on text extraction and information recognition.

  17. DOES VOLUNTARY DISCLOSURE LEVEL AFFECT THE VALUE RELEVANCE OF ACCOUNTING INFORMATION?

    OpenAIRE

    2011-01-01

    This paper seeks to explore whether voluntary disclosure level affects the value relevance of accounting information from an investor’s perspective on Kuwait Stock Exchange (KSE). Based on the assumption that an increased focus on the informational needs of investors should increase the value relevance of the information contained in financial statements we expect that value relevance will increase along with increases in the level of voluntary disclosure. As a consequence, we expect that gre...

  18. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris.

    Directory of Open Access Journals (Sweden)

    Martin F Strube-Bloss

    Full Text Available To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol. The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.

  19. Rendering Information Literacy Relevant: A Case-Based Pedagogy

    Science.gov (United States)

    Spackman, Andy; Camacho, Leticia

    2009-01-01

    The authors describe the use of case studies in a program of extracurricular library instruction and explain the benefits of case teaching in developing information literacy. The paper presents details of example cases and analyzes surveys to evaluate the impact of case teaching on student satisfaction. (Contains 3 tables.)

  20. The relevance of visual information on learning sounds in infancy

    NARCIS (Netherlands)

    ter Schure, S.M.M.

    2016-01-01

    Newborn infants are sensitive to combinations of visual and auditory speech. Does this ability to match sounds and sights affect how infants learn the sounds of their native language? And are visual articulations the only type of visual information that can influence sound learning? This

  1. The relevance of visual information on learning sounds in infancy

    NARCIS (Netherlands)

    S.M.M. ter Schure

    2016-01-01

    Newborn infants are sensitive to combinations of visual and auditory speech. Does this ability to match sounds and sights affect how infants learn the sounds of their native language? And are visual articulations the only type of visual information that can influence sound learning? This dissertatio

  2. Information Extraction on the Web with Credibility Guarantee

    OpenAIRE

    Nguyen, Thanh Tam

    2015-01-01

    The Web became the central medium for valuable sources of information extraction applications. However, such user-generated resources are often plagued by inaccuracies and misinformation due to the inherent openness and uncertainty of the Web. In this work we study the problem of extracting structured information out of Web data with a credibility guarantee. The ultimate goal is that not only the structured information should be extracted as much as possible but also its credibility is high. ...

  3. Information Extraction from Large-Multi-Layer Social Networks

    Science.gov (United States)

    2015-08-06

    paper we introduce a novel method to extract information from such multi-layer networks, where each type of link forms its own layer. Using the concept...Approved for public release; distribution is unlimited. Information extraction from large-multi-layer social networks The views, opinions and/or findings...Information extraction from large-multi-layer social networks Report Title Social networks often encode community structure using multiple distinct

  4. Revealing Relationships among Relevant Climate Variables with Information Theory

    CERN Document Server

    Knuth, Kevin H; Curry, Charles T; Huyser, Karen A; Wheeler, Kevin R; Rossow, William B

    2013-01-01

    A primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist suf...

  5. Revealing Relationships among Relevant Climate Variables with Information Theory

    Science.gov (United States)

    Knuth, Kevin H.; Golera, Anthony; Curry, Charles T.; Huyser, Karen A.; Kevin R. Wheeler; Rossow, William B.

    2005-01-01

    The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

  6. New perspectives on sustainable development and barriers to relevant information.

    Science.gov (United States)

    Regier, H A; Bronson, E A

    1992-03-01

    Sustainable development may mean different things to people with different worldviews. We sketch four worldviews, drawing on a schema developed by Bryan Norton. Of these four worldviews, i.e. exploitist, utilitist, integrist and inherentist, the third is the most consistent with the Brundtland Report (WCED 1987) and the Great Lakes Water Quality Agreement (GLWQA 1987).The integrist perspective combines analytic reductionistic study with comparative contextual study, with emphasis on the latter. This integrative approach moves from over-reliance on utilist information services such as impact assessment towards transactive study. Our own compromise emphasizes a stress-response approach to a partial understanding of complex cultural-natural interactions within ecosystems. Both cultural and natural attributes of ecosystems must be addressed.Currently the federal Canadian government tends toward an exploitist worldview; current government R&D funding and subsidies reflect this view. Old-fashioned scientists who rely on a monocular analytical vision of the world's minutiae may find contextual historical study offensive; these scientists hold sway on some advisory boards and hence research funding. Difficulty in finding funding for integrist information services should not be interpreted as a lack of need for this information; rather this difficulty results from resistance to a changing worldview.

  7. Value relevance of accounting information: evidence from South Eastern European countries

    OpenAIRE

    Pervan, Ivica; Bartulović, Marijana

    2014-01-01

    In this article the authors analysed value relevance of accounting information based on a sample of 97 corporations listed on one of the following capital markets: Ljubljana Stock Exchange, Zagreb Stock Exchange, Sarajevo Stock Exchange, Banja Luka Stock Exchange and Belgrade Stock Exchange. Research results show that accounting information is value relevant on all the observed markets. Value relevance analysis for the period 2005–2010 has shown that there was no increase in the explanatory p...

  8. Testing the idea of privileged awareness of self-relevant information.

    Science.gov (United States)

    Stein, Timo; Siebold, Alisha; van Zoest, Wieske

    2016-03-01

    Self-relevant information is prioritized in processing. Some have suggested the mechanism driving this advantage is akin to the automatic prioritization of physically salient stimuli in information processing (Humphreys & Sui, 2015). Here we investigate whether self-relevant information is prioritized for awareness under continuous flash suppression (CFS), as has been found for physical salience. Gabor patches with different orientations were first associated with the labels You or Other. Participants were more accurate in matching the self-relevant association, replicating previous findings of self-prioritization. However, breakthrough into awareness from CFS did not differ between self- and other-associated Gabors. These findings demonstrate that self-relevant information has no privileged access to awareness. Rather than modulating the initial visual processes that precede and lead to awareness, the advantage of self-relevant information may better be characterized as prioritization at later processing stages.

  9. Sample-based XPath Ranking for Web Information Extraction

    NARCIS (Netherlands)

    Jundt, Oliver; van Keulen, Maurice

    Web information extraction typically relies on a wrapper, i.e., program code or a configuration that specifies how to extract some information from web pages at a specific website. Manually creating and maintaining wrappers is a cumbersome and error-prone task. It may even be prohibitive as some

  10. A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

    Science.gov (United States)

    Mathe, Nathalie; Chen, James

    1994-01-01

    Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

  11. Integrated Land Information System - a relevant step for development of information background for PEEX?

    Science.gov (United States)

    Shvidenko, Anatoly; Schepaschenko, Dmitry; Baklanov, Alexander

    2014-05-01

    PEEX, as a long-term multidisciplinary integrated study, needs a systems design of a relevant information background. The idea of development of an Integrated Land Information System (ILIS) for the region as an initial step of future advanced integrated observing systems is considered as a promising way. The ILIS could serve (1) for introduction of a unified system of classification and quantification of environment, ecosystems and landscapes; (2) as a benchmark for tracing the dynamics of land use - land cover and ecosystems parameters, particularly for forests; (3) as a systems background for empirical assessment of indicators of an interest (e.g., components of biogeochemical cycles); (4) comparisons, harmonizing and mutual constraints of the results obtained by different methods; (5) for parameterization of surface fluxes for the 'atmosphere-land' system; (6) for use in divers models and for models' validation; (7) for downscaling of available information to a required scale; (8) for understanding of gradients for up-scaling of "point" data, etc. The ILIS is presented in form of multi-layer and multi-scale GIS that includes a hybrid land cover (HLC) by a definite date and corresponding legends and attributive databases. The HLC is based on relevant combination of a "multi" remote sensing concept that includes sensors of different type and resolution and ground data. The ILIS includes inter alia (1) general geographical and biophysical description of the territory (landscapes, soil, vegetation, hydrology, bioclimatic zones, permafrost etc.); (2) diverse datasets of measurements in situ; (3) sets of empirical and semi-empirical aggregation and auxiliary models, (4) data on different inventories and surveys (forest inventory, land account, results of forest monitoring); (5) spatial and temporal description of anthropogenic and natural disturbances; (5) climatic data with relevant temporal resolution etc. The ILIS should include only the data with known

  12. The Agent of extracting Internet Information with Lead Order

    Science.gov (United States)

    Mo, Zan; Huang, Chuliang; Liu, Aijun

    In order to carry out e-commerce better, advanced technologies to access business information are in need urgently. An agent is described to deal with the problems of extracting internet information that caused by the non-standard and skimble-scamble structure of Chinese websites. The agent designed includes three modules which respond to the process of extracting information separately. A method of HTTP tree and a kind of Lead algorithm is proposed to generate a lead order, with which the required web can be retrieved easily. How to transform the extracted information structuralized with natural language is also discussed.

  13. Post-processing of Deep Web Information Extraction Based on Domain Ontology

    Directory of Open Access Journals (Sweden)

    PENG, T.

    2013-11-01

    Full Text Available Many methods are utilized to extract and process query results in deep Web, which rely on the different structures of Web pages and various designing modes of databases. However, some semantic meanings and relations are ignored. So, in this paper, we present an approach for post-processing deep Web query results based on domain ontology which can utilize the semantic meanings and relations. A block identification model (BIM based on node similarity is defined to extract data blocks that are relevant to specific domain after reducing noisy nodes. Feature vector of domain books is obtained by result set extraction model (RSEM based on vector space model (VSM. RSEM, in combination with BIM, builds the domain ontology on books which can not only remove the limit of Web page structures when extracting data information, but also make use of semantic meanings of domain ontology. After extracting basic information of Web pages, a ranking algorithm is adopted to offer an ordered list of data records to users. Experimental results show that BIM and RSEM extract data blocks and build domain ontology accurately. In addition, relevant data records and basic information are extracted and ranked. The performances precision and recall show that our proposed method is feasible and efficient.

  14. Pattern information extraction from crystal structures

    OpenAIRE

    Okuyan, Erhan

    2005-01-01

    Cataloged from PDF version of article. Determining crystal structure parameters of a material is a quite important issue in crystallography. Knowing the crystal structure parameters helps to understand physical behavior of material. For complex structures, particularly for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be quite hard. This work provides a tool that will extract crystal parameters such as primitive vect...

  15. Extraction of microalgae derived lipids with supercritical carbon dioxide in an industrial relevant pilot plant.

    Science.gov (United States)

    Lorenzen, Jan; Igl, Nadine; Tippelt, Marlene; Stege, Andrea; Qoura, Farah; Sohling, Ulrich; Brück, Thomas

    2017-06-01

    Microalgae are capable of producing up to 70% w/w triglycerides with respect to their dry cell weight. Since microalgae utilize the greenhouse gas CO2, they can be cultivated on marginal lands and grow up to ten times faster than terrestrial plants, the generation of algae oils is a promising option for the development of sustainable bioprocesses, that are of interest for the chemical lubricant, cosmetic and food industry. For the first time we have carried out the optimization of supercritical carbon dioxide (SCCO2) mediated lipid extraction from biomass of the microalgae Scenedesmus obliquus and Scenedesmus obtusiusculus under industrrially relevant conditions. All experiments were carried out in an industrial pilot plant setting, according to current ATEX directives, with batch sizes up to 1.3 kg. Different combinations of pressure (7-80 MPa), temperature (20-200 °C) and CO2 to biomass ratio (20-200) have been tested on the dried biomass. The most efficient conditions were found to be 12 MPa pressure, a temperature of 20 °C and a CO2 to biomass ratio of 100, resulting in a high extraction efficiency of up to 92%. Since the optimized CO2 extraction still yields a crude triglyceride product that contains various algae derived contaminants, such as chlorophyll and carotenoids, a very effective and scalable purification procedure, based on cost efficient bentonite based adsorbers, was devised. In addition to the sequential extraction and purification procedure, we present a consolidated online-bleaching procedure for algae derived oils that is realized within the supercritical CO2 extraction plant.

  16. Multi-agent-based modeling for extracting relevant association rules using a multi-criteria analysis approach

    Directory of Open Access Journals (Sweden)

    Addi Ait-Mlouk

    2016-06-01

    Full Text Available Abstract Recently, association rule mining plays a vital role in knowledge discovery in database. In fact, in most cases, the real datasets lead to a very large number of rules, which do not allow users to make their own selection of the most relevant. The difficult task is mining useful and non-redundant rules. Several approaches have been proposed, such as rule clustering, informative cover method and quality measurements. Another way to selecting relevant association rules, we believe that it is necessary to integrate a decisional approach within the knowledge discovery process. Therefore, in this paper, we propose an approach to discover a category of relevant association rules based on multi-criteria analysis. In other side, the general process of association rules extraction becomes more and more complex, to solve such problem, we also proposed a multi-agent system for modeling the different process of our proposed approach. Therefore, we conclude our work by an empirical study applied to a set of banking data to illustrate the performance of our approach.

  17. Beyond Categories: A Structural Analysis of the Social Representations of Information Users' Collective Perceptions on 'Relevance'

    Directory of Open Access Journals (Sweden)

    Ju, Boryung

    2013-06-01

    Full Text Available Relevance has a long history of scholarly investigation and discussion in information science. One of its notable concepts is that of 'user-based' relevance. The purpose of this study is to examine how users construct their perspective on the concept of relevance; to analyze what the constituent elements (facets of relevance are, in terms of core-periphery status; and to compare the difference of constructions of two groups of users (information users vs. information professionals as applied with a social representations theory perspective. Data were collected from 244 information users and 123 information professionals through use of a free word association method. Three methods were employed to analyze data: (1 content analysis was used to elicit 26 categories (facets of the concept of relevance; (2 structural analysis of social representations was used to determine the core-periphery status of those facets in terms of coreness, sum of similarity, and weighted frequency; and, (3 maximum tree analysis was used to present and compare the differences between the two groups. Elicited categories in this study overlap with the ones from previous relevance studies, while the findings of a core-periphery analysis show that Topicality, User-needs, Reliability/Credibility, and Importance are configured as core concepts for the information user group, while Topicality, User-needs, Reliability/Credibility, and Currency are core concepts for the information professional group. Differences between the social representations of relevance revealed that Topicality was similar to User-needs and to Importance. Author is closely related to Title while Reliability/Credibility is linked with Currency. Easiness/Clarity is similar to Accuracy. Overall, information users and professionals function with a similar social collective of shared meanings for the concept of relevance. The overall findings identify the core and periphery concepts of relevance and their

  18. Real-Time Information Extraction from Big Data

    Science.gov (United States)

    2015-10-01

    I N S T I T U T E F O R D E F E N S E A N A L Y S E S Real-Time Information Extraction from Big Data Robert M. Rolfe...Information Extraction from Big Data Jagdeep Shah Robert M. Rolfe Francisco L. Loaiza-Lemos October 7, 2015 I N S T I T U T E F O R D E F E N S E...AN A LY S E S Abstract We are drowning under the 3 Vs (volume, velocity and variety) of big data . Real-time information extraction from big

  19. On Using Genetic Algorithms for Multimodal Relevance Optimization in Information Retrieval.

    Science.gov (United States)

    Boughanem, M.; Christment, C.; Tamine, L.

    2002-01-01

    Presents a genetic relevance optimization process performed in an information retrieval system that uses genetic techniques for solving multimodal problems (niching) and query reformulation techniques. Explains that the niching technique allows the process to reach different relevance regions of the document space, and that query reformulations…

  20. On Using Genetic Algorithms for Multimodal Relevance Optimization in Information Retrieval.

    Science.gov (United States)

    Boughanem, M.; Christment, C.; Tamine, L.

    2002-01-01

    Presents a genetic relevance optimization process performed in an information retrieval system that uses genetic techniques for solving multimodal problems (niching) and query reformulation techniques. Explains that the niching technique allows the process to reach different relevance regions of the document space, and that query reformulations…

  1. Membrane Dialysis Extraction (MDE): a novel approach for extracting toxicologically relevant hydrophobic organic compounds from soils and sediments for assessment in biotests

    Energy Technology Data Exchange (ETDEWEB)

    Seiler, T.B.; Leist, E.; Braunbeck, T.; Hollert, H. [Dept. of Zoology, Aquatic Ecology and Toxicology, Univ. of Heidelberg (Germany); Rastall, A.C.; Erdinger, L. [Inst. of Hygiene and Medical Microbiology, Univ. of Heidelberg (Germany)

    2006-02-15

    Goal, scope and background. Organic solvents are routinely used to extract toxicants from polluted soils and sediments prior to chemical analysis or bioassay. Conventional extraction methods often require the use of heated organic solvents, in some cases under high pressure. These conditions can result in loss of volatile compounds from the sample and the degradation of thermally labile target analytes. Moreover, extracts of soils and sediments also frequently contain substantial quantities of organic macromolecules which can act as sorbing phases for target analytes and in doing so interfere with both chemical analysis and bioassays. Membrane dialysis extraction (MDE) is described as a simple, passive extraction method for selectively extracting toxicologically relevant hydrophobic organic compounds (HOCs) from polluted soils and sediments and analyzed for its applicability in ecotoxicological investigations. Methods. Toxicologically relevant hydrophobic organic compounds were extracted from wet and dry sediments by sealing replicate samples in individual lengths of pre-cleaned low-density polyethylene (LD-PE) tubing and then dialysing in n-hexane. Results. The membrane dialysis extraction was found to be at least as efficient as Soxhlet methodology to extract toxicologically relevant HOCs from sediment samples. In most cases, MDE-derived extracts showed a higher toxicological potential than the Soxhlet extracts. Lack of any significant effects in any MDE controls indicated these differences were not caused by contamination of the LD-PE membrane used. The elevated toxicological potential of MDE extracts is most likely the result of enhanced bioavailability of toxic compounds in consequence of lower amounts of organic macromolecules (i.e. sorbing phases) in the MDE extracts. This effect is probably the result of a size-selective restriction by the LD-PE membrane. Conclusion. Membrane dialysis extraction was found to be a simple, efficient and cost-effective method

  2. Influencing Tomorrow: A Study of Emerging Influence Techniques and Their Relevance to United States Information Operations

    Science.gov (United States)

    2015-06-12

    groups and governmental institutions; the possibility of economic loss directed at entrepreneurs; or the prospect of United States undue influence or... INFLUENCING TOMORROW: A STUDY OF EMERGING INFLUENCE TECHNIQUES AND THEIR RELEVANCE TO UNITED STATES INFORMATION OPERATIONS A...

  3. Source-specific Informative Prior for i-Vector Extraction

    DEFF Research Database (Denmark)

    Shepstone, Sven Ewan; Lee, Kong Aik; Li, Haizhou

    2015-01-01

    -informative, since for homogeneous datasets there is no gain in generality in using an informative prior. This work shows that extracting i-vectors for a heterogeneous dataset, containing speech samples recorded from multiple sources, using informative priors instead is applicable, and leads to favorable results...

  4. CTSS: A Tool for Efficient Information Extraction with Soft Matching Rules for Text Mining

    Directory of Open Access Journals (Sweden)

    A. Christy

    2008-01-01

    Full Text Available The abundance of information available digitally in modern world had made a demand for structured information. The problem of text mining which dealt with discovering useful information from unstructured text had attracted the attention of researchers. The role of Information Extraction (IE software was to identify relevant information from texts, extracting information from a variety of sources and aggregating it to create a single view. Information extraction systems depended on particular corpora and were poor in recall values. Therefore, developing the system as domain-independent as well as improving the recall was an important challenge for IE. In this research, the authors proposed a domain-independent algorithm for information extraction, called SOFTRULEMINING for extracting the aim, methodology and conclusion from technical abstracts. The algorithm was implemented by combining trigram model with softmatching rules. A tool CTSS was constructed using SOFTRULEMINING and was tested with technical abstracts of www.computer.org and www.ansinet.org and found that the tool had improved its recall value and therefore the precision value in comparison with other search engines.

  5. Addressing Information Proliferation: Applications of Information Extraction and Text Mining

    Science.gov (United States)

    Li, Jingjing

    2013-01-01

    The advent of the Internet and the ever-increasing capacity of storage media have made it easy to store, deliver, and share enormous volumes of data, leading to a proliferation of information on the Web, in online libraries, on news wires, and almost everywhere in our daily lives. Since our ability to process and absorb this information remains…

  6. Addressing Information Proliferation: Applications of Information Extraction and Text Mining

    Science.gov (United States)

    Li, Jingjing

    2013-01-01

    The advent of the Internet and the ever-increasing capacity of storage media have made it easy to store, deliver, and share enormous volumes of data, leading to a proliferation of information on the Web, in online libraries, on news wires, and almost everywhere in our daily lives. Since our ability to process and absorb this information remains…

  7. Extracting information from two-dimensional electrophoresis gels by partial least squares regression

    DEFF Research Database (Denmark)

    Jessen, Flemming; Lametsch, R.; Bendixen, E.;

    2002-01-01

    of all proteins/spots in the gels. In the present study it is demonstrated how information can be extracted by multivariate data analysis. The strategy is based on partial least squares regression followed by variable selection to find proteins that individually or in combination with other proteins vary......Two-dimensional gel electrophoresis (2-DE) produces large amounts of data and extraction of relevant information from these data demands a cautious and time consuming process of spot pattern matching between gels. The classical approach of data analysis is to detect protein markers that appear...

  8. Mars Target Encyclopedia: Information Extraction for Planetary Science

    Science.gov (United States)

    Wagstaff, K. L.; Francis, R.; Gowda, T.; Lu, Y.; Riloff, E.; Singh, K.

    2017-06-01

    Mars surface targets / and published compositions / Seek and ye will find. We used text mining methods to extract information from LPSC abstracts about the composition of Mars surface targets. Users can search by element, mineral, or target.

  9. Can we replace curation with information extraction software?

    Science.gov (United States)

    Karp, Peter D

    2016-01-01

    Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL.

  10. Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

    Energy Technology Data Exchange (ETDEWEB)

    Boscá, A., E-mail: alberto.bosca@upm.es [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Pedrós, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain); Martínez, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ciencia de Materiales, E.T.S.I de Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Calle, F. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain)

    2015-01-28

    Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method output values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process.

  11. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu

    2015-03-01

    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  12. Phase synchronization of delta and theta oscillations increase during the detection of relevant lexical information

    Directory of Open Access Journals (Sweden)

    Enzo eBrunetti

    2013-06-01

    Full Text Available During monitoring of the discourse, the detection of the relevance of incoming lexical information could be critical for its incorporation to update mental representations in memory. Because, in these situations, the relevance for lexical information is defined by abstract rules that are maintained in memory, results critical to understand how an abstract level of knowledge maintained in mind mediates the detection of the lower-level semantic information. In the present study, we propose that neuronal oscillations participate in the detection of relevant lexical information, based on ‘kept in mind’ rules deriving from more abstract semantic information. We tested our hypothesis using an experimental paradigm that restricted the detection of relevance to inferences based on explicit information, thus controlling for ambiguities derived from implicit aspects. We used a categorization task, in which the semantic relevance was previously defined based on the congruency between a kept in mind category (abstract knowledge, and the lexical-semantic information presented. Our results show that during the detection of the relevant lexical information, phase synchronization of neuronal oscillations selectively increases in delta and theta frequency bands during the interval of semantic analysis. These increments were independent of the semantic category maintained in memory, had a temporal profile specific for each subject, and were mainly induced, as they had no effect on the evoked mean global field power. Also, recruitment of an increased number of pairs of electrodes was a robust observation during the detection of semantic contingent words. These results are consistent with the notion that the detection of relevant lexical information based on a particular semantic rule, could be mediated by increasing the global phase synchronization of neuronal oscillations, which may contribute to the recruitment of an extended number of cortical regions.

  13. Pattern information extraction from crystal structures

    Science.gov (United States)

    Okuyan, Erhan; Güdükbay, Uğur; Gülseren, Oğuz

    2007-04-01

    Determining the crystal structure parameters of a material is an important issue in crystallography and material science. Knowing the crystal structure parameters helps in understanding the physical behavior of material. It can be difficult to obtain crystal parameters for complex structures, particularly those materials that show local symmetry as well as global symmetry. This work provides a tool that extracts crystal parameters such as primitive vectors, basis vectors and space groups from the atomic coordinates of crystal structures. A visualization tool for examining crystals is also provided. Accordingly, this work could help crystallographers, chemists and material scientists to analyze crystal structures efficiently. Program summaryTitle of program: BilKristal Catalogue identifier: ADYU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYU_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: None Programming language used: C, C++, Microsoft .NET Framework 1.1 and OpenGL Libraries Computer: Personal Computers with Windows operating system Operating system: Windows XP Professional RAM: 20-60 MB No. of lines in distributed program, including test data, etc.:899 779 No. of bytes in distributed program, including test date, etc.:9 271 521 Distribution format:tar.gz External routines/libraries: Microsoft .NET Framework 1.1. For visualization tool, graphics card driver should also support OpenGL Nature of problem: Determining crystal structure parameters of a material is a quite important issue in crystallography. Knowing the crystal structure parameters helps to understand physical behavior of material. For complex structures, particularly, for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be quite hard. Solution method: The tool extracts crystal parameters such as primitive vectors, basis vectors and identify the space group from

  14. Achieving Rigour and Relevance in Information Systems Studies: Using grounded theory to investigate organizational cases

    Directory of Open Access Journals (Sweden)

    Hans Lehmann, Ph.D.

    2005-11-01

    Full Text Available This paper builds on the belief that rigorous Information Systems (IS research can help practitioners to better understand and to adapt to emerging situations. Contrary to the view seeing rigour and relevance as a dichotomy, it is maintained that IS researchers have a third choice; namely, to be both relevant and rigorous. The paper proposes ways in which IS research can contribute to easing the practitioners’ burden of adapting to changes by providing timely, relevant, and rigorous research. It is argued that synergy between relevance and rigour is possible and that classic grounded theory methodology in combination with case-based data provides a good framework for rigorous and relevant research of emerging phenomena in information systems.

  15. Integrating Information Extraction Agents into a Tourism Recommender System

    Science.gov (United States)

    Esparcia, Sergio; Sánchez-Anguix, Víctor; Argente, Estefanía; García-Fornes, Ana; Julián, Vicente

    Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

  16. Mining knowledge from text repositories using information extraction: A review

    Indian Academy of Sciences (India)

    Sandeep R Sirsat; Dr Vinay Chavan; Dr Shrinivas P Deshpande

    2014-02-01

    There are two approaches to mining text form online repositories. First, when the knowledge to be discovered is expressed directly in the documents to be mined, Information Extraction (IE) alone can serve as an effective tool for such text mining. Second, when the documents contain concrete data in unstructured form rather than abstract knowledge, Information Extraction (IE) can be used to first transform the unstructured data in the document corpus into a structured database, and then use some state-of-the-art data mining algorithms/tools to identify abstract patterns in this extracted data. This paper presents the review of several methods related to these two approaches.

  17. A Parallel Relational Database Management System Approach to Relevance Feedback in Information Retrieval.

    Science.gov (United States)

    Lundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David

    1999-01-01

    Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…

  18. A Parallel Relational Database Management System Approach to Relevance Feedback in Information Retrieval.

    Science.gov (United States)

    Lundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David

    1999-01-01

    Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…

  19. Automatically extracting clinically useful sentences from UpToDate to support clinicians' information needs.

    Science.gov (United States)

    Mishra, Rashmi; Del Fiol, Guilherme; Kilicoglu, Halil; Jonnalagadda, Siddhartha; Fiszman, Marcelo

    2013-01-01

    Clinicians raise several information needs in the course of care. Most of these needs can be met by online health knowledge resources such as UpToDate. However, finding relevant information in these resources often requires significant time and cognitive effort. To design and assess algorithms for extracting from UpToDate the sentences that represent the most clinically useful information for patient care decision making. We developed algorithms based on semantic predications extracted with SemRep, a semantic natural language processing parser. Two algorithms were compared against a gold standard composed of UpToDate sentences rated in terms of clinical usefulness. Clinically useful sentences were strongly correlated with predication frequency (correlation= 0.95). The two algorithms did not differ in terms of top ten precision (53% vs. 49%; p=0.06). Semantic predications may serve as the basis for extracting clinically useful sentences. Future research is needed to improve the algorithms.

  20. The study of the extraction of 3-D informations

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Ki [Korea Univ., Seoul (Korea); Kim, Jin Hun; Kim, Hui Yung; Lee, Gi Sik; Lee, Yung Shin [Sokyung Univ., Seoul (Korea)

    1998-04-01

    To extract three dimensional information in 3 dimensional real world two methods are applied (stereo image method, virtual reality environment method). 1. Stereo image method. From the paris of stereo image matching methods are applied to find the corresponding points in the two images. To solve the problem various methods are applied 2. Virtual reality environment method. As an alternate method to extract 3-D information, virtual reality environment is use. It is very useful to fine 6 DOF for a some given target points in 3-D space. We considered the accuracies and reliability of the 3-D informations. 34 figs., 4 tabs. (Author)

  1. Creation of reliable relevance judgments in information retrieval systems evaluation experimentation through crowdsourcing: a review.

    Science.gov (United States)

    Samimi, Parnia; Ravana, Sri Devi

    2014-01-01

    Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.

  2. Value Relevance of Accounting Information in the Pre- and Post-IFRS Accounting Periods

    OpenAIRE

    2010-01-01

    This paper examines the value relevance of accounting information in the preand post-periods of International Financial Reporting Standards implementation using the models of Easton and Harris (1991) and Feltham and Ohlson (1995) for a sample of Greek companies. The results of the paper indicate that the effects of the IFRS reduced the incremental information content of book values of equity for stock prices. However, earnings’ incremental information content increased for the post-IFRS perio...

  3. OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals.

    Science.gov (United States)

    Ehrenreich, H; Mitjans, M; Van der Auwera, S; Centeno, T P; Begemann, M; Grabe, H J; Bonn, S; Nave, K-A

    2016-12-06

    Despite high heritability of schizophrenia, genome-wide association studies (GWAS) have not yet revealed distinct combinations of single-nucleotide polymorphisms (SNPs), relevant for mental disease-related, quantifiable behavioral phenotypes. Here we propose an individual-based model to use genome-wide significant markers for extracting first genetic signatures of such behavioral continua. 'OTTO' (old Germanic=heritage) marks an individual characterized by a prominent phenotype and a particular load of phenotype-associated risk SNPs derived from GWAS that likely contributed to the development of his personal mental illness. This load of risk SNPs is shared by a small squad of 'similars' scattered under the genetically and phenotypically extremely heterogeneous umbrella of a schizophrenia end point diagnosis and to a variable degree also by healthy subjects. In a discovery sample of >1000 deeply phenotyped schizophrenia patients and several independent replication samples, including the general population, a gradual increase in the severity of 'OTTO's phenotype' expression is observed with an increasing share of 'OTTO's risk SNPs', as exemplified here by autistic and affective phenotypes. These data suggest a model in which the genetic contribution to dimensional behavioral traits can be extracted from combinations of GWAS SNPs derived from individuals with prominent phenotypes. Even though still in the 'model phase' owing to a world-wide lack of sufficiently powered, deeply phenotyped replication samples, the OTTO approach constitutes a conceptually novel strategy to delineate biological subcategories of mental diseases starting from GWAS findings and individual subjects.Molecular Psychiatry advance online publication, 6 December 2016; doi:10.1038/mp.2016.208.

  4. Extraction of Coupling Information From $Z' \\to jj$

    OpenAIRE

    Rizzo, T. G.

    1993-01-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the $Z' \\to jj$ channel in excess of $6\\sigma$ for certain classes of extended electroweak models. We explore the possibility that the data extracted from $Z$ dijet peak will have sufficient statistical power as to supply information on th...

  5. The relevance of music information representation metadata from the perspective of expert users

    Directory of Open Access Journals (Sweden)

    Camila Monteiro de Barros

    Full Text Available The general goal of this research was to verify which metadata elements of music information representation are relevant for its retrieval from the perspective of expert music users. Based on a bibliographical research, a comprehensive metadata set of music information representation was developed and transformed into a questionnaire for data collection, which was applied to students and professors of the Graduate Program in Music at the Federal University of Rio Grande do Sul. The results show that the most relevant information for expert music users is related to identification and authorship responsibilities. The respondents from Composition and Interpretative Practice areas agree with these results, while the respondents from Musicology/Ethnomusicology and Music Education areas also consider the metadata related to the historical context of composition relevant.

  6. PDF text classification to leverage information extraction from publication reports.

    Science.gov (United States)

    Bui, Duy Duc An; Del Fiol, Guilherme; Jonnalagadda, Siddhartha

    2016-06-01

    Data extraction from original study reports is a time-consuming, error-prone process in systematic review development. Information extraction (IE) systems have the potential to assist humans in the extraction task, however majority of IE systems were not designed to work on Portable Document Format (PDF) document, an important and common extraction source for systematic review. In a PDF document, narrative content is often mixed with publication metadata or semi-structured text, which add challenges to the underlining natural language processing algorithm. Our goal is to categorize PDF texts for strategic use by IE systems. We used an open-source tool to extract raw texts from a PDF document and developed a text classification algorithm that follows a multi-pass sieve framework to automatically classify PDF text snippets (for brevity, texts) into TITLE, ABSTRACT, BODYTEXT, SEMISTRUCTURE, and METADATA categories. To validate the algorithm, we developed a gold standard of PDF reports that were included in the development of previous systematic reviews by the Cochrane Collaboration. In a two-step procedure, we evaluated (1) classification performance, and compared it with machine learning classifier, and (2) the effects of the algorithm on an IE system that extracts clinical outcome mentions. The multi-pass sieve algorithm achieved an accuracy of 92.6%, which was 9.7% (pPDF documents. Text classification is an important prerequisite step to leverage information extraction from PDF documents. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Ontology-Based Information Extraction for Business Intelligence

    Science.gov (United States)

    Saggion, Horacio; Funk, Adam; Maynard, Diana; Bontcheva, Kalina

    Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

  8. The Common Body of Knowledge: A Framework to Promote Relevant Information Security Research

    Directory of Open Access Journals (Sweden)

    Kenneth J. Knapp

    2007-03-01

    Full Text Available This study proposes using an established common body of knowledge (CBK as one means of organizing information security literature.  Consistent with calls for more relevant information systems (IS research, this industry-developed framework can motivate future research towards topics that are important to the security practitioner.  In this review, forty-eight articles from ten IS journals from 1995 to 2004 are selected and cross-referenced to the ten domains of the information security CBK.  Further, we distinguish articles as empirical research, frameworks, or tutorials.  Generally, this study identified a need for additional empirical research in every CBK domain including topics related to legal aspects of information security.  Specifically, this study identified a need for additional IS security research relating to applications development, physical security, operations security, and business continuity.  The CBK framework is inherently practitioner oriented and using it will promote relevancy by steering IS research towards topics important to practitioners.  This is important considering the frequent calls by prominent information systems scholars for more relevant research.  Few research frameworks have emerged from the literature that specifically classify the diversity of security threats and range of problems that businesses today face.  With the recent surge of interest in security, the need for a comprehensive framework that also promotes relevant research can be of great value.

  9. Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

    Science.gov (United States)

    Kempler, Steven; Barbieri, Lindsay

    2016-01-01

    Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to

  10. Information bias in contingent valuation: effects of personal relevance, quality of information, and motivational orientation

    Science.gov (United States)

    Icek Ajzen; Thomas C. Brown; Lori H. Rosenthal

    1996-01-01

    A laboratory experiment examined the potential for information bias in contingent valuation (CV). Consistent with the view that information about a public or private good can function as a persuasive communication, willingness to pay (WTP) was found to increase with the quality of arguments used to describe the good, especially under conditions of high personal...

  11. OpenCV-Based Nanomanipulation Information Extraction and the Probe Operation in SEM

    Directory of Open Access Journals (Sweden)

    Dongjie Li

    2015-02-01

    Full Text Available Aimed at the established telenanomanipulation system, the method of extracting location information and the strategies of probe operation were studied in this paper. First, the machine learning algorithm of OpenCV was used to extract location information from SEM images. Thus nanowires and probe in SEM images can be automatically tracked and the region of interest (ROI can be marked quickly. Then the location of nanowire and probe can be extracted from the ROI. To study the probe operation strategy, the Van der Waals force between probe and a nanowire was computed; thus relevant operating parameters can be obtained. With these operating parameters, the nanowire in 3D virtual environment can be preoperated and an optimal path of the probe can be obtained. The actual probe runs automatically under the telenanomanipulation system's control. Finally, experiments were carried out to verify the above methods, and results show the designed methods have achieved the expected effect.

  12. The impact of intangibles on the value relevance of accounting information: Evidence from French companies

    Directory of Open Access Journals (Sweden)

    Bilal Kimouche

    2016-03-01

    Full Text Available Purpose: The paper aims to explore whether intangible items that recognised in financial statements are value-relevant to investors in the French context, and whether these items affect the value relevance of accounting information. Design/methodology/approach: Empirical data were collected from a sample of French listed companies, over the nine-year period of 2005 to 2013. Starting of Ohlson’s (1995 model, the correlation analysis and the linear multiple regressions have been applied. Findings: We find that intangibles and traditional accounting measures as a whole are value relevant. However, the amortization and impairment charges of intangibles and cash flows do not affect the market values of French companies, unlike other variables, which affect positively and substantially the market values. Also goodwill and book values are more associated with market values than intangible assets and earnings respectively. Finally, we find that intangibles have improved the value relevance of accounting information. Practical implications: French legislators must give more interest for intangibles, in order to enrich the financial statements content and increasing the pertinence of accounting information. Auditors must give more attention for intangibles’ examination process, in order to certify the amounts related to intangibles in financial statements, and hence enrich their reliability, what provides adequacy guarantees for investors to use them in decision making. Originality/value: The paper used recently available financial data, and proposed an improvement concerning the measure of incremental value relevance of intangibles items.

  13. Perceived Relevance of an Introductory Information Systems Course to Prospective Business Students

    Directory of Open Access Journals (Sweden)

    Irene Govender

    2013-12-01

    Full Text Available The study is designed to examine students’ perceptions of the introductory Information Systems (IS course. It was an exploratory study in which 67 students participated. A quantitative approach was followed making use of questionnaires for the collection of data. Using the theory of reasoned action as a framework, the study explores the factors that influence non-IS major students’ perceived relevance of the IS introductory course. The analysis of collected data included descriptive and inferential statistics. Using multiple regression analysis, the results suggest that overall, the independent variables, relevance of the content, previous IT knowledge, relevance for professional practice, IT preference in courses and peers’ influence may account for 72% of the explanatory power for the dependent variable, perceived relevance of the IS course. In addition, the results have shown some strong predictors (IT preference and peers’ influence that influence students’ perceived relevance of the IS course. Practical work was found to be a strong mediating variable toward positive perceptions of IS. The results of this study suggest that students do indeed perceive the introductory IS course to be relevant and match their professional needs, but more practical work would enhance their learning. Implications for theory and practice are discussed as a result of the behavioural intention to perceive the IS course to be relevant and eventually to recruit more IS students.

  14. Value Relevance of Earnings Information in Japan -- A Survey: The Empirical Findings by Foreign Researchers --

    OpenAIRE

    大日方, 隆

    2007-01-01

    The purpose of this paper is to confirm how international academicians evaluate the Japanese accounting system. This paper surveys prior studies on the international comparison (including Japan) of accounting information and reexamines the empirical findings on the usefulness of earnings information in Japan, focusing on the value relevance of earnings. Many researchers have pointed out that code law, investor protection in financial regulation environments and Japanese corporate governance, ...

  15. Extracting an entanglement signature from only classical mutual information

    Energy Technology Data Exchange (ETDEWEB)

    Starling, David J.; Howell, John C. [Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627 (United States); Broadbent, Curtis J. [Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627 (United States); Rochester Theory Center, University of Rochester, Rochester, New York 14627 (United States)

    2011-09-15

    We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.

  16. Extracting clinical information to support medical decision based on standards.

    Science.gov (United States)

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  17. Extracting an entanglement signature from only classical mutual information

    Science.gov (United States)

    Starling, David J.; Broadbent, Curtis J.; Howell, John C.

    2011-09-01

    We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.

  18. THE METHODS OF EXTRACTING WATER INFORMATION FROM SPOT IMAGE

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Some techniques and methods for deriving water information from SPOT -4 (XI) image were investigatedand discussed in this paper. An algorithm of decision-tree (DT) classification which includes several classifiers based onthe spectral responding characteristics of water bodies and other objects, was developed and put forward to delineate wa-ter bodies. Another algorithm of decision-tree classification based on both spectral characteristics and auxiliary informa-tion of DEM and slope (DTDS) was also designed for water bodies extraction. In addition, supervised classificationmethod of maximum-likelyhood classification (MLC), and unsupervised method of interactive self-organizing dada analy-sis technique (ISODATA) were used to extract waterbodies for comparison purpose. An index was designed and used toassess the accuracy of different methods adopted in the research. Results have shown that water extraction accuracy wasvariable with respect to the various techniques applied. It was low using ISODATA, very high using DT algorithm andmuch higher using both DTDS and MLC.

  19. Tumor information extraction in radiology reports for hepatocellular carcinoma patients

    Science.gov (United States)

    Yim, Wen-wai; Denman, Tyler; Kwan, Sharon W.; Yetisgen, Meliha

    2016-01-01

    Hepatocellular carcinoma (HCC) is a deadly disease affecting the liver for which there are many available therapies. Targeting treatments towards specific patient groups necessitates defining patients by stage of disease. Criteria for such stagings include information on tumor number, size, and anatomic location, typically only found in narrative clinical text in the electronic medical record (EMR). Natural language processing (NLP) offers an automatic and scale-able means to extract this information, which can further evidence-based research. In this paper, we created a corpus of 101 radiology reports annotated for tumor information. Afterwards we applied machine learning algorithms to extract tumor information. Our inter-annotator partial match agreement scored at 0.93 and 0.90 F1 for entities and relations, respectively. Based on the annotated corpus, our sequential labeling entity extraction achieved 0.87 F1 partial match, and our maximum entropy classification relation extraction achieved scores 0.89 and 0. 74 F1 with gold and system entities, respectively. PMID:27570686

  20. Information Extraction and Linking in a Retrieval Context

    NARCIS (Netherlands)

    Moens, M.F.; Hiemstra, Djoerd

    We witness a growing interest and capabilities of automatic content recognition (often referred to as information extraction) in various media sources that identify entities (e.g. persons, locations and products) and their semantic attributes (e.g., opinions expressed towards persons or products,

  1. Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

    Directory of Open Access Journals (Sweden)

    Mafkereseb Kassahun Bekele

    2016-11-01

    Full Text Available Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description. However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volume historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits (which took place between 1910 and 1926 and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework.

  2. Preparatory information for third molar extraction: does preference for information and behavioral involvement matter?

    NARCIS (Netherlands)

    van Wijk, A.J.; Buchanan, H.; Coulson, N.; Hoogstraten, J.

    2010-01-01

    Objective: The objectives of the present study were to: (1) evaluate the impact of high versus low information provision in terms of anxiety towards third molar extraction (TME) as well as satisfaction with information provision. (2) Investigate how preference for information and behavioral

  3. Access to Attitude-Relevant Information in Memory as a Determinant of Persuasion: The Role of Message and Communicator Attributes.

    Science.gov (United States)

    Wood, Wendy; And Others

    Research literature shows that people with access to attitude-relevant information in memory are able to draw on relevant beliefs and prior experiences when analyzing a persuasive message. This suggests that people who can retrieve little attitude-relevant information should be less able to engage in systematic processing. Two experiments were…

  4. Access to Attitude-Relevant Information in Memory as a Determinant of Persuasion: The Role of Message and Communicator Attributes.

    Science.gov (United States)

    Wood, Wendy; And Others

    Research literature shows that people with access to attitude-relevant information in memory are able to draw on relevant beliefs and prior experiences when analyzing a persuasive message. This suggests that people who can retrieve little attitude-relevant information should be less able to engage in systematic processing. Two experiments were…

  5. Extending a geocoding database by Web information extraction

    Science.gov (United States)

    Wu, Yunchao; Niu, Zheng

    2008-10-01

    Local Search has recently attracted much attention. And the popular architecture of Local Search is map-and-hyperlinks, which links geo-referenced Web content to a map interface. This architecture shows that a good Local Search not only depends on search engine techniques, but also on a perfect geocoding database. The process of building and updating a geocoding database is laborious and time consuming so that it is usually difficult to keep up with the change of the real world. However, the Web provides a rich resource of location related information, which would be a supplementary information source for geocoding. Therefore, this paper introduces how to extract geographic information from Web documents to extend a geocoding database. Our approach involves two major steps. First, geographic named entities are identified and extracted from Web content. Then, named entities are geocoded and put into storage. By this way, we can extend a geocoding database to provide better local Web search services.

  6. The Study on Information Extraction Technology of Seismic Damage

    Directory of Open Access Journals (Sweden)

    Huang Zuo-wei

    2013-01-01

    Full Text Available In order to improve the information extraction technology of seismic damage assessment and information publishing of earthquake damage. Based on past earthquake experience it was constructed technical flow of earthquake damage assessment rapidly, this study, take Yushu earthquake as example, studies the framework and establishment of the information service system by means of Arc IMS and distributed database technology. It analysis some key technologies, build web publishing architecture of massive remote sensing images. The system implements joint application of remote sensing image processing technology, database technology and Web GIS technology, the result could provide the important basis for earthquake damage assessment, emergency management and rescue mission.

  7. Extraction of Information from Images using Dewrapping Techniques

    Directory of Open Access Journals (Sweden)

    Khalid Nazim S. A.

    2010-11-01

    Full Text Available An image containing textual information is called a document image. The textual information in document images is useful in areas like vehicle number plate reading, passport reading and cargo container reading and so on. Thus extracting useful textual information in the document image plays an important role in many applications. One of the major challenges in camera document analysis is to deal with the wrap and perspective distortions. In spite of the prevalence of dewrapping techniques, there is no standard efficient algorithm for the performance evaluation that concentrates on visualization. Wrapping is a common appearance document image before recognition. In order to capture the document images a mobile camera of 2megapixel resolution is used. A database is developed with variations in background, size and colour along with wrapped images, blurred and clean images. This database will be explored and text extraction from those document images is performed. In case of wrapped images no efficient dewrapping techniques have been implemented till date. Thus extracting the text from the wrapped images is done by maintaining a suitable template database. Further, the extracted text from the wrapped or other document images will be converted into an editable form such as Notepad or MS word document. The experimental results were corroborated on various objects of database.

  8. Indexing of Internet resources in order to improve the provision of problem-relevant medical information.

    Science.gov (United States)

    Hoelzer, Simon; Schweiger, Ralf Kurt; Boettcher, Hanno; Rieger, Joerg; Dudeck, Joachim

    2002-01-01

    Due to the information overload and the unstructured access to (medical) information of the internet, it isn't hardly possible to find problem-relevant medical information in an appropriate time (e.g. during a consultation). The web offers a mixture of web pages, forums, newsgroups and databases. The search for problem-relevant information for a certain knowledge area encounters on two basic problems. On the one hand, you have to find in the jungle of the information, relevant resources for your individual clinical case (treatment, diagnosis, therapeutic option etc..). The second problem consists of being able to judge the quality of individual contents of inteernet pages. On the basis of the different informational needs of health care professionals and patients a catalog with inteernet resources was created to tumor diseases such as lung cancer (small cell and non-small cell carcinoma), colorectal cancer and thyroid cancer. Explicit and implicit metainformation, if available, such as the title of the document, language, date or keywords are stored in the database. The database entries are editorially revised, so that further specific metainformation is available for the information retrieval. Our pragmatic approach of searching, editing, and archiving of internet content is still necessary since most of the web documents are based on HTML, which doesn't allow for structuring (medical) information and assigning metainformation sufficiently. The use of specific metainformation is crucial in order to improve the recall and precision of internet searches. In the future, XML and related technologies (RDF) will meet these requirements.

  9. Rapid automatic keyword extraction for information retrieval and analysis

    Science.gov (United States)

    Rose, Stuart J [Richland, WA; Cowley,; E, Wendy [Richland, WA; Crow, Vernon L [Richland, WA; Cramer, Nicholas O [Richland, WA

    2012-03-06

    Methods and systems for rapid automatic keyword extraction for information retrieval and analysis. Embodiments can include parsing words in an individual document by delimiters, stop words, or both in order to identify candidate keywords. Word scores for each word within the candidate keywords are then calculated based on a function of co-occurrence degree, co-occurrence frequency, or both. Based on a function of the word scores for words within the candidate keyword, a keyword score is calculated for each of the candidate keywords. A portion of the candidate keywords are then extracted as keywords based, at least in part, on the candidate keywords having the highest keyword scores.

  10. Extracting Semantic Information from Visual Data: A Survey

    Directory of Open Access Journals (Sweden)

    Qiang Liu

    2016-03-01

    Full Text Available The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

  11. Drama advertisements: moderating effects of self-relevance on the relations among empathy, information processing, and attitudes.

    Science.gov (United States)

    Chebat, Jean-Charles; Vercollier, Sarah Drissi; Gélinas-Chebat, Claire

    2003-06-01

    The effects of drama versus lecture format in public service advertisements are studied in a 2 (format) x 2 (malaria vs AIDS) factorial design. Two structural equation models are built (one for each level of self-relevance), showing two distinct patterns. In both low and high self-relevant situations, empathy plays a key role. Under low self-relevance conditions, drama enhances information processing through empathy. Under high self-relevant conditions, the advertisement format has neither significant cognitive or empathetic effects. The information processing generated by the highly relevant topic affects viewers' empathy, which in turn affects the attitude the advertisement and the behavioral intent. As predicted by the Elaboration Likelihood Model, the advertisement format enhances the attitudes and information processing mostly under low self-relevant conditions. Under low self-relevant conditions, empathy enhances information processing while under high self-relevance, the converse relation holds.

  12. Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

    2015-05-15

    We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements.

  13. Systematic screening of plant extracts from the Brazilian Pantanal with antimicrobial activity against bacteria with cariogenic relevance.

    Science.gov (United States)

    Brighenti, F L; Salvador, M J; Delbem, Alberto Carlos Botazzo; Delbem, Ádina Cleia Bottazzo; Oliveira, M A C; Soares, C P; Freitas, L S F; Koga-Ito, C Y

    2014-01-01

    This study proposes a bioprospection methodology regarding the antimicrobial potential of plant extracts against bacteria with cariogenic relevance. Sixty extracts were obtained from ten plants--(1) Jatropha weddelliana, (2) Attalea phalerata, (3) Buchenavia tomentosa, (4) Croton doctoris, (5) Mouriri elliptica, (6) Mascagnia benthamiana, (7) Senna aculeata, (8) Unonopsis guatterioides, (9) Allagoptera leucocalyx and (10) Bactris glaucescens--using different extraction methods - (A) 70° ethanol 72 h/25°C, (B) water 5 min/100°C, (C) water 1 h/55°C, (D) water 72 h/25°C, (E) hexane 72 h/25°C and (F) 90° ethanol 72 h/25°C. The plants were screened for antibacterial activity at 50 mg/ml using the agar well diffusion test against Actinomyces naeslundii ATCC 19039, Lactobacillus acidophilus ATCC 4356, Streptococcus gordonii ATCC 10558, Streptococcus mutans ATCC 35688, Streptococcus sanguinis ATCC 10556, Streptococcus sobrinus ATCC 33478 and Streptococcus mitis ATCC 9811. The active extracts were tested to determine their minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), cytotoxicity and chemical characterization. Forty-seven extracts (78%) were active against at least one microorganism. Extract 4A demonstrated the lowest MIC and MBC for all microorganisms except S. gordonii and the extract at MIC concentration was non-cytotoxic. The concentrated extracts were slightly cytotoxic. Electrospray ionization with tandem mass spectrometry analyses demonstrated that the extract constituents coincided with the mass of the terpenoids and phenolics. Overall, the best results were obtained for extraction methods A, B and C. The present work proved the antimicrobial activity of several plants. Particularly, extracts from C. doctoris were the most active against bacteria involved in dental caries disease.

  14. Robust Vehicle and Traffic Information Extraction for Highway Surveillance

    Directory of Open Access Journals (Sweden)

    C.-C. Jay Kuo

    2005-08-01

    Full Text Available A robust vision-based traffic monitoring system for vehicle and traffic information extraction is developed in this research. It is challenging to maintain detection robustness at all time for a highway surveillance system. There are three major problems in detecting and tracking a vehicle: (1 the moving cast shadow effect, (2 the occlusion effect, and (3 nighttime detection. For moving cast shadow elimination, a 2D joint vehicle-shadow model is employed. For occlusion detection, a multiple-camera system is used to detect occlusion so as to extract the exact location of each vehicle. For vehicle nighttime detection, a rear-view monitoring technique is proposed to maintain tracking and detection accuracy. Furthermore, we propose a method to improve the accuracy of background extraction, which usually serves as the first step in any vehicle detection processing. Experimental results are given to demonstrate that the proposed techniques are effective and efficient for vision-based highway surveillance.

  15. Task relevance of emotional information affects anxiety-linked attention bias in visual search.

    Science.gov (United States)

    Dodd, Helen F; Vogt, Julia; Turkileri, Nilgun; Notebaert, Lies

    2017-01-01

    Task relevance affects emotional attention in healthy individuals. Here, we investigate whether the association between anxiety and attention bias is affected by the task relevance of emotion during an attention task. Participants completed two visual search tasks. In the emotion-irrelevant task, participants were asked to indicate whether a discrepant face in a crowd of neutral, middle-aged faces was old or young. Irrelevant to the task, target faces displayed angry, happy, or neutral expressions. In the emotion-relevant task, participants were asked to indicate whether a discrepant face in a crowd of middle-aged neutral faces was happy or angry (target faces also varied in age). Trait anxiety was not associated with attention in the emotion-relevant task. However, in the emotion-irrelevant task, trait anxiety was associated with a bias for angry over happy faces. These findings demonstrate that the task relevance of emotional information affects conclusions about the presence of an anxiety-linked attention bias. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. ASPECTS OF COMPANY PERFORMANCE ANALYSIS BASED ON RELEVANT FINANCIAL INFORMATION AND NONFINANCIAL INFORMATION

    Directory of Open Access Journals (Sweden)

    Popa Dorina

    2012-07-01

    Full Text Available The main objective of our work is the conceptual description of the performance of an economic entity in financial and non-financial terms. During our approach we have shown that it is not sufficient to analyze the performance of a company only in financial terms as the performance reflected in financial reports sometimes do not coincide with the real situation of the company. In this case the cause of the differences has to be found among the influences of other nonfinancial information. Mainly following the great financial scandals the distrust in the reliability of financial-accounting information has eroded strongly and thus the business performance measurement cannot be the exclusive domain of the criteria of financial analysis, but must be done in a comprehensive way, based both on financial criteria and on non-financial ones (intangible assets, social responsibility of the company. Using non-financial criteria have led to the occurrence of new types of analysis, namely extra-financial analysis. Thus, enterprise performance is not subject to material and financial resources managed and controlled by the entities, but to the complex of intangible resources that companies created by thier previous work. The extra-financial analysis has to face difficulties arising mainly from the existence of non-financial indicators very little normalized, and from the lack of uniformity of the practice in the field. In determining the extra-financial performance indicators one has to observe the manifestation and the evolution of the company’s relationships with its partners / environment. In order to analyze the performance measurement by financial and nonfinancial indicators we chose as a case study a company in Bihor county, listed on Bucharest Stock Exchange. The results of our study show that the Romanian entities are increasingly interested in measuring performance and after the extra-financial analysis we concluded that the company had set

  17. Enhancing Information Awareness Through Directed Qualification of Semantic Relevancy Scoring Operations

    Science.gov (United States)

    2014-06-01

    Data to Information (D2I), and Quality of Service (QoS) Enabled Dissem- ination (QED). IV. MODELING AND APPLYING DIRECTED QUALIFICATION FOR ANALYTICS ...document or key/value pair stores such as Hadoop or Cassandra. Semantic inferencing can create a form of analytics by applying an ontology relevant...logic analytics within semantic data sets. Many web-oriented popularity, similarity, and clus- tering analytics appear to be well suited for semantic

  18. Relevance of Information Systems Strategic Planning Practices in E-Business Contexts

    OpenAIRE

    Ganesan Kannabiran; Srinivasan Sundar

    2011-01-01

    Increasing global competition and advances in Internet technologies have led organizations to consider e-business strategies. However, evolving e-business strategies have been identified as a critical issue faced by corporate planners. The relevance and the use of IS (Information Systems) strategy planning practices in the context of e-business have been argued among researchers. In this paper, the authors investigate whether organizations can successfully improve the IS value in the e-busine...

  19. Acute and chronic aquatic toxicity of aromatic extracts. Summary of relevant test data

    Energy Technology Data Exchange (ETDEWEB)

    Comber, M.I.H.; Den Haan, K.; Djemel, N.; Eadsforth, C.V.; King, D.; Parkerton, T.; Leon Paumen, M.; Dmytrasz, B.; Del Castillo, F.

    2013-09-15

    This report describes the experimental procedures and the results obtained in acute and chronic ecotoxicity tests on several aromatic extracts samples. The samples were tested for toxicity to the rainbow trout (Oncorhynchus mykiss), the crustacean zooplankter, Daphnia magna and the algae, Selenastrum capricornutum using water accommodated fractions. These results assist in determining the environmental hazard posed by aromatic extracts.

  20. Reference Information Extraction and Processing Using Random Conditional Fields

    Directory of Open Access Journals (Sweden)

    Tudor Groza

    2012-06-01

    Full Text Available Fostering both the creation and the linking of data with the scope of supporting the growth of the Linked Data Web requires us to improve the acquisition and extraction mechanisms of the underlying semantic metadata. This is particularly important for the scientific publishing domain, where currently most of the datasets are being created in an author-driven, manual manner. In addition, such datasets capture only fragments of the complete metadata, omitting usually, important elements such as the references, although they represent valuable information. In this paper we present an approach that aims at dealing with this aspect of extraction and processing of reference information. The experimental evaluation shows that, currently, our solution handles very well diverse types of reference format, thus making it usable for, or adaptable to, any area of scientific publishing.

  1. Information extraction from the GER 63-channel spectrometer data

    Science.gov (United States)

    Kiang, Richard K.

    1993-09-01

    The unprecedented data volume in the era of NASA's Mission to Planet Earth (MTPE) demands innovative information extraction methods and advanced processing techniques. The neural network techniques, which are intrinsic to distributed parallel processings and have shown promising results in analyzing remotely sensed data, could become the essential tools in the MTPE era. To evaluate the information content of data with higher dimension and the usefulness of neural networks in analyzing them, measurements from the GER 63-channel airborne imaging spectrometer data over Cuprite, Nevada, are used. The data are classified with 3-layer Perceptron of various architectures. It is shown that the neural network can achieve a level of performance similar to conventional methods, without the need for an explicit feature extraction step.

  2. Contextual Query Perfection by Affective Features Based Implicit Contextual Semantic Relevance Feedback in Multimedia Information Retrieval

    Directory of Open Access Journals (Sweden)

    Anil K. Tripathi

    2012-09-01

    Full Text Available Multimedia Information may have multiple semantics depending on context, a temporal interest and user preferences. Hence we are exploiting the plausibility of context associated with semantic concept in retrieving relevance information. We are proposing an Affective Feature Based Implicit Contextual Semantic Relevance Feedback (AICSRF to investigate whether audio and speech along with visual could determine the current context in which user wants to retrieve the information and to further investigate whether we could employ Affective Feedback as an implicit source of evidence in CSRF cycle to increase the systems contextual semantic understanding. We introduce an Emotion Recognition Unit (ERU that comprises of spatiotemporal Gabor filter to capture spontaneous facial expression and emotional word recognition system that uses phonemes to recognize the spoken emotional words. We propose Contextual Query Perfection Scheme (CQPS to learn, refine the current context that could be used in query perfection in RF cycle to understand the semantic of query on the basis of relevance judgment taken by ERU. Observations suggest that CQPS in AICSRF incorporating such affective features reduce the search space hence retrieval time and increase the systems contextual semantic understanding.

  3. On the meniscus formation and the negative hydrogen ion extraction from ITER neutral beam injection relevant ion source

    Science.gov (United States)

    Mochalskyy, S.; Wünderlich, D.; Ruf, B.; Fantz, U.; Franzen, P.; Minea, T.

    2014-10-01

    The development of a large area (Asource,ITER = 0.9 × 2 m2) hydrogen negative ion (NI) source constitutes a crucial step in construction of the neutral beam injectors of the international fusion reactor ITER. To understand the plasma behaviour in the boundary layer close to the extraction system the 3D PIC MCC code ONIX is exploited. Direct cross checked analysis of the simulation and experimental results from the ITER-relevant BATMAN source testbed with a smaller area (Asource,BATMAN ≈ 0.32 × 0.59 m2) has been conducted for a low perveance beam, but for a full set of plasma parameters available. ONIX has been partially benchmarked by comparison to the results obtained using the commercial particle tracing code for positive ion extraction KOBRA3D. Very good agreement has been found in terms of meniscus position and its shape for simulations of different plasma densities. The influence of the initial plasma composition on the final meniscus structure was then investigated for NIs. As expected from the Child-Langmuir law, the results show that not only does the extraction potential play a crucial role on the meniscus formation, but also the initial plasma density and its electronegativity. For the given parameters, the calculated meniscus locates a few mm downstream of the plasma grid aperture provoking a direct NI extraction. Most of the surface produced NIs do not reach the plasma bulk, but move directly towards the extraction grid guided by the extraction field. Even for artificially increased electronegativity of the bulk plasma the extracted NI current from this region is low. This observation indicates a high relevance of the direct NI extraction. These calculations show that the extracted NI current from the bulk region is low even if a complete ion-ion plasma is assumed, meaning that direct extraction from surface produced ions should be present in order to obtain sufficiently high extracted NI current density. The calculated extracted currents, both ions

  4. Extracting Firm Information from Administrative Records: The ASSD Firm Panel

    OpenAIRE

    Fink, Martina; Segalla, Esther; Weber, Andrea; Zulehner, Christine

    2010-01-01

    This paper demonstrates how firm information can be extracted from administrative social security records. We use the Austrian Social Security Database (ASSD) and derive firms from employer identifiers in the universe of private sector workers. To correctly pin down entry end exits we use a worker flow approach which follows clusters of workers as they move across administrative entities. This procedure enables us to define different types of entry and exit such as start-ups, spinoffs, closur...

  5. OCR++: A Robust Framework For Information Extraction from Scholarly Articles

    OpenAIRE

    Singh, Mayank; Barua, Barnopriyo; Palod, Priyank; Garg, Manvi; Satapathy, Sidhartha; Bushi, Samuel; Ayush, Kumar; Rohith, Krishna Sai; Gamidi, Tulasi; Goyal, Pawan; Mukherjee, Animesh

    2016-01-01

    This paper proposes OCR++, an open-source framework designed for a variety of information extraction tasks from scholarly articles including metadata (title, author names, affiliation and e-mail), structure (section headings and body text, table and figure headings, URLs and footnotes) and bibliography (citation instances and references). We analyze a diverse set of scientific articles written in English language to understand generic writing patterns and formulate rules to develop this hybri...

  6. A new method for precursory information extraction: Slope-difference information method

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A new method for precursory information extraction, i.e.,slope-difference information method is proposed in the paper for the daily-mean-value precursory data sequence. Taking Tangshan station as an example, the calculation of full-time-domain leveling data is made, which is tested and compared with several other methods. The results indicate that the method is very effective for extracting short-term precursory information from the daily mean values after the optimization is made. Therefore, it is valuable for popularization and application.

  7. Is genetic information relevantly different from other kinds of non-genetic information in the life insurance context?

    Science.gov (United States)

    Malpas, P J

    2008-07-01

    Within the medical, legal and bioethical literature, there has been an increasing concern that the information derived from genetic tests may be used to unfairly discriminate against individuals seeking various kinds of insurance; particularly health and life insurance. Consumer groups, the general public and those with genetic conditions have also expressed these concerns, specifically in the context of life insurance. While it is true that all insurance companies may have an interest in the information obtained from genetic tests, life insurers potentially have a very strong incentive to (want to) use genetic information to rate applicants, as individuals generally purchase their own cover and may want to take out very large policies. This paper critically focuses on genetic information in the context of life insurance. We consider whether genetic information differs in any relevant way from other kinds of non-genetic information required by and disclosed to life insurance companies by potential clients. We will argue that genetic information should not be treated any differently from other types of health information already collected from those wishing to purchase life insurance cover.

  8. Perceived relevance and information needs regarding food topics and preferred information sources among Dutch adults: results of a quantitative consumer study

    NARCIS (Netherlands)

    Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.

    2004-01-01

    Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research.

  9. Extraction of hidden information by efficient community detection in networks

    CERN Document Server

    Lee, Juyong; Lee, Jooyoung

    2012-01-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas.

  10. A Semantic Approach for Geospatial Information Extraction from Unstructured Documents

    Science.gov (United States)

    Sallaberry, Christian; Gaio, Mauro; Lesbegueries, Julien; Loustau, Pierre

    Local cultural heritage document collections are characterized by their content, which is strongly attached to a territory and its land history (i.e., geographical references). Our contribution aims at making the content retrieval process more efficient whenever a query includes geographic criteria. We propose a core model for a formal representation of geographic information. It takes into account characteristics of different modes of expression, such as written language, captures of drawings, maps, photographs, etc. We have developed a prototype that fully implements geographic information extraction (IE) and geographic information retrieval (IR) processes. All PIV prototype processing resources are designed as Web Services. We propose a geographic IE process based on semantic treatment as a supplement to classical IE approaches. We implement geographic IR by using intersection computing algorithms that seek out any intersection between formal geocoded representations of geographic information in a user query and similar representations in document collection indexes.

  11. Multiple automated headspace in-tube extraction for the accurate analysis of relevant wine aroma compounds and for the estimation of their relative liquid-gas transfer rates.

    Science.gov (United States)

    Zapata, Julián; Lopez, Ricardo; Herrero, Paula; Ferreira, Vicente

    2012-11-30

    An automated headspace in-tube extraction (ITEX) method combined with multiple headspace extraction (MHE) has been developed to provide simultaneously information about the accurate wine content in 20 relevant aroma compounds and about their relative transfer rates to the headspace and hence about the relative strength of their interactions with the matrix. In the method, 5 μL (for alcohols, acetates and carbonyl alcohols) or 200 μL (for ethyl esters) of wine sample were introduced in a 2 mL vial, heated at 35°C and extracted with 32 (for alcohols, acetates and carbonyl alcohols) or 16 (for ethyl esters) 0.5 mL pumping strokes in four consecutive extraction and analysis cycles. The application of the classical theory of Multiple Extractions makes it possible to obtain a highly reliable estimate of the total amount of volatile compound present in the sample and a second parameter, β, which is simply the proportion of volatile not transferred to the trap in one extraction cycle, but that seems to be a reliable indicator of the actual volatility of the compound in that particular wine. A study with 20 wines of different types and 1 synthetic sample has revealed the existence of significant differences in the relative volatility of 15 out of 20 odorants. Differences are particularly intense for acetaldehyde and other carbonyls, but are also notable for alcohols and long chain fatty acid ethyl esters. It is expected that these differences, linked likely to sulphur dioxide and some unknown specific compositional aspects of the wine matrix, can be responsible for relevant sensory changes, and may even be the cause explaining why the same aroma composition can produce different aroma perceptions in two different wines. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Relevance of a perchloric acid extraction scheme to determine mineral and organic phosphorus in swine slurry.

    Science.gov (United States)

    Daumer, Marie-Line; Béline, Fabrice; Spérandio, Mathieu; Morel, Christian

    2008-03-01

    To increase the phosphorus recycling potential from swine slurry, mineral phosphorus products which could be used as fertilizers should be obtained and new processes need to be investigated. A routine method is needed to better evaluate the dissolved and solid mineral phosphorus in swine slurry. Cold perchloric acid extraction method previously developed for wastewater or sludge analysis was adapted. Ionic chromatography was used to measure orthophosphate in extracts. Only one extraction step was needed to distinguish between mineral and organic phosphorus in slurry. Reproducibility of the method was high (less than 5% of variation on the measured fractions). Selectivity was assessed by adding several organic and mineral phosphorus sources in the slurry. Cold perchloric extraction followed by ionic chromatography was very selective in quantifying both the mineral and organic forms of phosphorus in swine slurry.

  13. Chemically extracted nanocellulose from sisal fibres by a simple and industrially relevant process

    DEFF Research Database (Denmark)

    Trifol Guzman, Jon; Sillard, Cecile; Plackett, D.

    2017-01-01

    A novel type of acetylated cellulose nanofibre (CNF) was extracted successfully from sisal fibres using chemical methods. Initially, a strong alkali treatment was used to swell the fibres, followed by a bleaching step to remove the residual lignin and finally an acetylation step to reduce...... in the prepared CNF dispersion. Finally, CNF films with alkali extracts were also prepared, resulting in flatter films with an increased mass yield and improved mechanical strength....

  14. Garlic extract exhibits antiamyloidogenic activity on amyloid-beta fibrillogenesis: relevance to Alzheimer's disease.

    Science.gov (United States)

    Gupta, Veer Bala; Indi, S S; Rao, K S J

    2009-01-01

    Alzheimer's disease is characterized pathologically by the deposition of amyloid plaques. Fibrillar Abeta is the principal component of amyloid plaques in the brain of AD patients. The prevention of Abeta aggregation or dissolution of fibrillar Abeta has clinical significance. The present communication examined in vitro the antiamyloidogenic properties of garlic extract. The effects of aqueous garlic extract (both fresh and boiled) on Abeta aggregation and defibrillation were studied by thioflavin-T based fluorescence assay, transmission electron microscopy and SDS-polyacrylamide gel electrophoresis. The aqueous fresh garlic extract not only inhibited Abeta fibril formation in a concentration and time dependent manner but was also able to defibrillate Abeta preformed fibrils. The maximum defibrillization was observed after 2-3 days of incubation. The boiled aqueous garlic extract also retained its antiamyloidogenic activity. This indicated that antiamyloidogenic activity of garlic extract is non-enzymatic, i.e. proteases present in garlic did not degrade Abeta in solution. However, the fibril degrading ability of boiled garlic extract was significantly lost. The findings suggest that consumption of garlic may lead to inhibition of Abeta aggregation in human brain.

  15. Elaboration of a guide including relevant project and logistic information: a case study

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Tchaikowisky M. [Faculdade de Tecnologia e Ciencias (FTC), Itabuna, BA (Brazil); Bresci, Claudio T.; Franca, Carlos M.M. [PETROBRAS, Rio de Janeiro, RJ (Brazil)

    2009-07-01

    For every mobilization of a new enterprise it is necessary to quickly obtain the greatest amount of relative information in regards to location and availability of infra-structure, logistics, and work site amenities. Among this information are reports elaborated for management of the enterprise, (organizational chart, work schedule, objectives, contacts, etc.) as well as geographic anomalies, social-economic and culture of the area to be developed such as territorial extension, land aspects, local population, roads and amenities (fuel stations ,restaurants and hotels), infra-structure of the cities (health, education, entertainment, housing, transport, etc.) and logistically the distance between cities the estimated travel time, ROW access maps and notable points, among other relevant information. With the idea of making this information available for everyone involved in the enterprise, it was elaborated for GASCAC Spread 2A a rapid guide containing all the information mentioned above and made it available for all the vehicles used to transport employees and visitors to the spread. With this, everyone quickly received the majority of information necessary in one place, in a practical, quick, and precise manner, since the information is always used and controlled by the same person. This study includes the model used in the gas pipeline GASCAC Spread 2A project and the methodology used to draft and update the information. Besides the above, a file in the GIS format was prepared containing all necessary planning, execution and tracking information for enterprise activities, from social communication to the execution of the works previously mentioned. Part of the GIS file information was uploaded to Google Earth so as to disclose the information to a greater group of people, bearing in mind that this program is free of charge and easy to use. (author)

  16. THE METHODS OF EXTRACTING WATER INFORMATION FROM SPOT IMAGE

    Institute of Scientific and Technical Information of China (English)

    DUJin-kang; FENGXue-zhi; 等

    2002-01-01

    Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper.An algorithmoif decision-tree(DT) classification which includes several classifiers based on the spectral responding characteristics of water bodies and other objects,was developed and put forward to delineate water bodies.Another algorithm of decision-tree classification based on both spectral characteristics and auxiliary information of DEM and slope(DTDS) was also designed for water bodies extraction.In addition,supervised classification method of maximum-likelyhood classification(MLC),and unsupervised method of interactive self -organizing dada analysis technique(ISODATA) were used to extract waterbodies for comparison purpose.An index was designed and used to assess the accuracy of different methods abopted in the research.Results have shown that water extraction accuracy was variable with respect to the various techniques applied.It was low using ISODATA,very high using DT algorithm and much higher using both DTDS and MLC.

  17. Extraction of spatial information for low-bandwidth telerehabilitation applications

    Directory of Open Access Journals (Sweden)

    Kok Kiong Tan, PhD

    2014-09-01

    Full Text Available Telemedicine applications, based on two-dimensional (2D video conferencing technology, have been around for the past 15 to 20 yr. They have been demonstrated to be acceptable for face-to-face consultations and useful for visual examination of wounds and abrasions. However, certain telerehabilitation assessments need the use of spatial information in order to accurately assess the patient’s condition and sending three-dimensional video data over low-bandwidth networks is extremely challenging. This article proposes an innovative way of extracting the key spatial information from the patient’s movement during telerehabilitation assessment based on 2D video and then presenting the extracted data by using graph plots alongside the video to help physicians in assessments with minimum burden on existing video data transfer. Some common rehabilitation scenarios are chosen for illustrations, and experiments are conducted based on skeletal tracking and color detection algorithms using the Microsoft Kinect sensor. Extracted data are analyzed in detail and their usability discussed.

  18. Transliteration normalization for Information Extraction and Machine Translation

    Directory of Open Access Journals (Sweden)

    Yuval Marton

    2014-12-01

    Full Text Available Foreign name transliterations typically include multiple spelling variants. These variants cause data sparseness and inconsistency problems, increase the Out-of-Vocabulary (OOV rate, and present challenges for Machine Translation, Information Extraction and other natural language processing (NLP tasks. This work aims to identify and cluster name spelling variants using a Statistical Machine Translation method: word alignment. The variants are identified by being aligned to the same “pivot” name in another language (the source-language in Machine Translation settings. Based on word-to-word translation and transliteration probabilities, as well as the string edit distance metric, names with similar spellings in the target language are clustered and then normalized to a canonical form. With this approach, tens of thousands of high-precision name transliteration spelling variants are extracted from sentence-aligned bilingual corpora in Arabic and English (in both languages. When these normalized name spelling variants are applied to Information Extraction tasks, improvements over strong baseline systems are observed. When applied to Machine Translation tasks, a large improvement potential is shown.

  19. Relevant Factors in The Post-Merger Systems Integration and Information Technology in Brazilian Banks

    Directory of Open Access Journals (Sweden)

    Marcel Ginotti Pires

    2017-01-01

    Full Text Available This article discusses the factors present in post-merger integration of Systems and Information Technology (SIT that lead to positive and negative results in mergers and acquisitions (M & A. The research comprised three of the largest acquiring banks in Brazil. We adopted two methods of research, qualitative, to operationalize the theoretical concepts and quantitative, to test the hypotheses. We interviewed six executives of banks that held relevant experience in M & A processes. Subsequently, we applied questionnaires to IT professionals who were involved in the SIT integration processes. The results showed that the quality and expertise of the integration teams and managing the integration were the most relevant factors in the processes, with positive results for increased efficiency and the increased capacity of SIT. Negative results were due to failures in exploiting learning opportunities, the loss of employees and the inexpressive record of integration procedures.

  20. [Study on Information Extraction of Clinic Expert Information from Hospital Portals].

    Science.gov (United States)

    Zhang, Yuanpeng; Dong, Jiancheng; Qian, Danmin; Geng, Xingyun; Wu, Huiqun; Wang, Li

    2015-12-01

    Clinic expert information provides important references for residents in need of hospital care. Usually, such information is hidden in the deep web and cannot be directly indexed by search engines. To extract clinic expert information from the deep web, the first challenge is to make a judgment on forms. This paper proposes a novel method based on a domain model, which is a tree structure constructed by the attributes of search interfaces. With this model, search interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from the returned web pages indexed by search interfaces. To filter the noise information on a web page, a block importance model is proposed. The experiment results indicated that the domain model yielded a precision 10.83% higher than that of the rule-based method, whereas the block importance model yielded an F₁ measure 10.5% higher than that of the XPath method.

  1. Extraction of Coupling Information From $Z' \\to jj$

    CERN Document Server

    Rizzo, T G

    1993-01-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the $Z' \\to jj$ channel in excess of $6\\sigma$ for certain classes of extended electroweak models. We explore the possibility that the data extracted from $Z$ dijet peak will have sufficient statistical power as to supply information on the couplings of the $Z'$ provided it is used in conjunction with complimentary results from the $Z' \\to \\ell^+ \\ell^-$ `discovery' channel. We show, for a 1 TeV $Z'$ produced at the SSC, that this technique can provide a powerful new tool with which to identify the origin of $Z'$'s.

  2. Extraction of coupling information from Z'-->jj

    Science.gov (United States)

    Rizzo, Thomas G.

    1993-11-01

    An analysis by the ATLAS Collaboration has recently shown, contrary to popular belief, that a combination of strategic cuts, excellent mass resolution, and detailed knowledge of the QCD backgrounds from direct measurements can be used to extract a signal in the Z'-->jj channel for certain classes of extended electroweak models. We explore the possibility that the data extracted from Z dijet peak will have sufficient statistical power as to supply information on the couplings of the Z' provided it is used in conjunction with complementary results from the Z'-->l+l- ``discovery'' channel. We show, for a 1 TeV Z' produced at the SSC, that this technique can provide a powerful new tool with which to identify the origin of Z'. Extensions of this analysis to the CERN LHC as well as for a more massive Z' are discussed.

  3. Extracting Backbones from Weighted Complex Networks with Incomplete Information

    Directory of Open Access Journals (Sweden)

    Liqiang Qian

    2015-01-01

    Full Text Available The backbone is the natural abstraction of a complex network, which can help people understand a networked system in a more simplified form. Traditional backbone extraction methods tend to include many outliers into the backbone. What is more, they often suffer from the computational inefficiency—the exhaustive search of all nodes or edges is often prohibitively expensive. In this paper, we propose a backbone extraction heuristic with incomplete information (BEHwII to find the backbone in a complex weighted network. First, a strict filtering rule is carefully designed to determine edges to be preserved or discarded. Second, we present a local search model to examine part of edges in an iterative way, which only relies on the local/incomplete knowledge rather than the global view of the network. Experimental results on four real-life networks demonstrate the advantage of BEHwII over the classic disparity filter method by either effectiveness or efficiency validity.

  4. Knowledge discovery: Extracting usable information from large amounts of data

    Energy Technology Data Exchange (ETDEWEB)

    Whiteson, R.

    1998-12-31

    The threat of nuclear weapons proliferation is a problem of world wide concern. Safeguards are the key to nuclear nonproliferation and data is the key to safeguards. The safeguards community has access to a huge and steadily growing volume of data. The advantages of this data rich environment are obvious, there is a great deal of information which can be utilized. The challenge is to effectively apply proven and developing technologies to find and extract usable information from that data. That information must then be assessed and evaluated to produce the knowledge needed for crucial decision making. Efficient and effective analysis of safeguards data will depend on utilizing technologies to interpret the large, heterogeneous data sets that are available from diverse sources. With an order-of-magnitude increase in the amount of data from a wide variety of technical, textual, and historical sources there is a vital need to apply advanced computer technologies to support all-source analysis. There are techniques of data warehousing, data mining, and data analysis that can provide analysts with tools that will expedite their extracting useable information from the huge amounts of data to which they have access. Computerized tools can aid analysts by integrating heterogeneous data, evaluating diverse data streams, automating retrieval of database information, prioritizing inputs, reconciling conflicting data, doing preliminary interpretations, discovering patterns or trends in data, and automating some of the simpler prescreening tasks that are time consuming and tedious. Thus knowledge discovery technologies can provide a foundation of support for the analyst. Rather than spending time sifting through often irrelevant information, analysts could use their specialized skills in a focused, productive fashion. This would allow them to make their analytical judgments with more confidence and spend more of their time doing what they do best.

  5. Knowledge discovery: Extracting usable information from large amounts of data

    Energy Technology Data Exchange (ETDEWEB)

    Whiteson, R.

    1998-12-31

    The threat of nuclear weapons proliferation is a problem of world wide concern. Safeguards are the key to nuclear nonproliferation and data is the key to safeguards. The safeguards community has access to a huge and steadily growing volume of data. The advantages of this data rich environment are obvious, there is a great deal of information which can be utilized. The challenge is to effectively apply proven and developing technologies to find and extract usable information from that data. That information must then be assessed and evaluated to produce the knowledge needed for crucial decision making. Efficient and effective analysis of safeguards data will depend on utilizing technologies to interpret the large, heterogeneous data sets that are available from diverse sources. With an order-of-magnitude increase in the amount of data from a wide variety of technical, textual, and historical sources there is a vital need to apply advanced computer technologies to support all-source analysis. There are techniques of data warehousing, data mining, and data analysis that can provide analysts with tools that will expedite their extracting useable information from the huge amounts of data to which they have access. Computerized tools can aid analysts by integrating heterogeneous data, evaluating diverse data streams, automating retrieval of database information, prioritizing inputs, reconciling conflicting data, doing preliminary interpretations, discovering patterns or trends in data, and automating some of the simpler prescreening tasks that are time consuming and tedious. Thus knowledge discovery technologies can provide a foundation of support for the analyst. Rather than spending time sifting through often irrelevant information, analysts could use their specialized skills in a focused, productive fashion. This would allow them to make their analytical judgments with more confidence and spend more of their time doing what they do best.

  6. On-matrix derivatization extraction of chemical weapons convention relevant alcohols from soil.

    Science.gov (United States)

    Chinthakindi, Sridhar; Purohit, Ajay; Singh, Varoon; Dubey, D K; Pardasani, Deepak

    2013-10-11

    Present study deals with the on-matrix derivatization-extraction of aminoalcohols and thiodiglycols, which are important precursors and/or degradation products of VX analogues and vesicants class of chemical warfare agents (CWAs). The method involved hexamethyldisilazane (HMDS) mediated in situ silylation of analytes on the soil. Subsequent extraction and gas chromatography-mass spectrometry analysis of derivatized analytes offered better recoveries in comparison to the procedure recommended by the Organization for the Prohibition of Chemical Weapons (OPCW). Various experimental conditions such as extraction solvent, reagent and catalyst amount, reaction time and temperature were optimized. Best recoveries of analytes ranging from 45% to 103% were obtained with DCM solvent containing 5%, v/v HMDS and 0.01%, w/v iodine as catalyst. The limits of detection (LOD) and limit of quantification (LOQ) with selected analytes ranged from 8 to 277 and 21 to 665ngmL(-1), respectively, in selected ion monitoring mode.

  7. In the Dark: Young Men's Stories of Sexual Initiation in the Absence of Relevant Sexual Health Information

    Science.gov (United States)

    Kubicek, Katrina; Beyer, William J.; Weiss, George; Iverson, Ellen; Kipke, Michele D.

    2010-01-01

    A growing body of research has investigated the effectiveness of abstinence-only sexual education. There remains a dearth of research on the relevant sexual health information available to young men who have sex with men (YMSM). Drawing on a mixed-methods study with 526 YMSM, this study explores how and where YMSM receive relevant information on…

  8. In the Dark: Young Men's Stories of Sexual Initiation in the Absence of Relevant Sexual Health Information

    Science.gov (United States)

    Kubicek, Katrina; Beyer, William J.; Weiss, George; Iverson, Ellen; Kipke, Michele D.

    2010-01-01

    A growing body of research has investigated the effectiveness of abstinence-only sexual education. There remains a dearth of research on the relevant sexual health information available to young men who have sex with men (YMSM). Drawing on a mixed-methods study with 526 YMSM, this study explores how and where YMSM receive relevant information on…

  9. Readability, relevance and quality of the information in Spanish on the Web for patients with rheumatoid arthritis.

    Science.gov (United States)

    Castillo-Ortiz, Jose Dionisio; Valdivia-Nuno, Jose de Jesus; Ramirez-Gomez, Andrea; Garagarza-Mariscal, Heber; Gallegos-Rios, Carlos; Flores-Hernandez, Gabriel; Hernandez-Sanchez, Luis; Brambila-Barba, Victor; Castaneda-Sanchez, Jose Juan; Barajas-Ochoa, Zalathiel; Suarez-Rico, Angel; Sanchez-Gonzalez, Jorge Manuel; Ramos-Remus, Cesar

    Education is a major health determinant and one of the main independent outcome predictors in rheumatoid arthritis (RA). The use of the Internet by patients has grown exponentially in the last decade. To assess the characteristics, legibility and quality of the information available in Spanish in the Internet regarding to rheumatoid arthritis. The search was performed in Google using the phrase rheumatoid arthritis. Information from the first 30 pages was evaluated according to a pre-established format (relevance, scope, authorship, type of publication and financial objective). The quality and legibility of the pages were assessed using two validated tools, DISCERN and INFLESZ respectively. Data extraction was performed by senior medical students and evaluation was achieved by consensus. The Google search returned 323 hits but only 63% were considered relevant; 80% of them were information sites (71% discussed exclusively RA, 44% conventional treatment and 12% alternative therapies) and 12.5% had a primary financial interest. 60% of the sites were created by nonprofit organizations and 15% by medical associations. Web sites posted by medical institutions from the United States of America were better positioned in Spanish (Arthritis Foundation 4th position and American College of Rheumatology 10th position) than web sites posted by Spanish speaking countries. There is a risk of disinformation for patients with RA that use the Internet. We identified a window of opportunity for rheumatology medical institutions from Spanish-speaking countries to have a more prominent societal involvement in the education of their patients with RA. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

  10. Linking genes to literature: text mining, information extraction, and retrieval applications for biology.

    Science.gov (United States)

    Krallinger, Martin; Valencia, Alfonso; Hirschman, Lynette

    2008-01-01

    Efficient access to information contained in online scientific literature collections is essential for life science research, playing a crucial role from the initial stage of experiment planning to the final interpretation and communication of the results. The biological literature also constitutes the main information source for manual literature curation used by expert-curated databases. Following the increasing popularity of web-based applications for analyzing biological data, new text-mining and information extraction strategies are being implemented. These systems exploit existing regularities in natural language to extract biologically relevant information from electronic texts automatically. The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance. This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the following: the type of biological information demands being addressed; the level of information granularity of both user queries and results; and the features and methods commonly exploited by these applications. The current trend in biomedical text mining points toward an increasing diversification in terms of application types and techniques, together with integration of domain-specific resources such as ontologies. Additional descriptions of some of the systems discussed here are available on the internet http://zope.bioinfo.cnio.es/bionlp_tools/.

  11. Gaps in policy-relevant information on burden of disease in children: a systematic review.

    Science.gov (United States)

    Rudan, Igor; Lawn, Joy; Cousens, Simon; Rowe, Alexander K; Boschi-Pinto, Cynthia; Tomasković, Lana; Mendoza, Walter; Lanata, Claudio F; Roca-Feltrer, Arantxa; Carneiro, Ilona; Schellenberg, Joanna A; Polasek, Ozren; Weber, Martin; Bryce, Jennifer; Morris, Saul S; Black, Robert E; Campbell, Harry

    Valid information about cause-specific child mortality and morbidity is an essential foundation for national and international health policy. We undertook a systematic review to investigate the geographical dispersion of and time trends in publication for policy-relevant information about children's health and to assess associations between the availability of reliable data and poverty. We identified data available on Jan 1, 2001, and published since 1980, for the major causes of morbidity and mortality in young children. Studies with relevant data were assessed against a set of inclusion criteria to identify those likely to provide unbiased estimates of the burden of childhood disease in the community. Only 308 information units from more than 17,000 papers identified were regarded as possible unbiased sources for estimates of childhood disease burden. The geographical distribution of these information units revealed a pattern of small well-researched populations surrounded by large areas with little available information. No reliable population-based data were identified from many of the world's poorest countries, which account for about a third of all deaths of children worldwide. The number of new studies diminished over the last 10 years investigated. The number of population-based studies yielding estimates of burden of childhood disease from less developed countries was low. The decreasing trend over time suggests reductions in research investment in this sphere. Data are especially sparse from the world's least developed countries with the highest child mortality. Guidelines are needed for the conduct of burden-of-disease studies together with an international research policy that gives increased emphasis to global equity and coverage so that knowledge can be generated from all regions of the world.

  12. Culicoides obsoletus extract relevant for diagnostics of insect bite hypersensitivity in horses

    NARCIS (Netherlands)

    Meide, van der N.M.A.; Meulenbroeks, C.; Altena, van S.E.C.; Schurink, A.; Ducro, B.J.; Wagner, B.; Leibold, W.; Rohwer, J.; Jacobs, F.; Sloet van Oldruitenborgh-Oosterbaan, M.M.; Savelkoul, H.F.J.; Tijhaar, E.

    2012-01-01

    Insect bite hypersensitivity (IBH) is an allergic dermatitis in horses caused by the bites of Culicoides species. The aim of the present study was to evaluate the applicability of whole body extracts of C. obsoletus (the main species found feeding on horses in the Netherlands), C. nubeculosus (rarel

  13. Using XBRL Technology to Extract Competitive Information from Financial Statements

    Directory of Open Access Journals (Sweden)

    Dominik Ditter

    2011-12-01

    Full Text Available The eXtensible Business Reporting Language, or XBRL, is a reporting format for the automatic and electronic exchange of business and financial data. In XBRL every single reported fact is marked with a unique tag, enabling a full computer-based readout of financial data. It has the potential to improve the collection and analysis of financial data for Competitive Intelligence (e.g., the profiling of publicly available financial statements. The article describes how easily information from XBRL reports can be extracted.

  14. A High Accuracy Method for Semi-supervised Information Extraction

    Energy Technology Data Exchange (ETDEWEB)

    Tratz, Stephen C.; Sanfilippo, Antonio P.

    2007-04-22

    Customization to specific domains of dis-course and/or user requirements is one of the greatest challenges for today’s Information Extraction (IE) systems. While demonstrably effective, both rule-based and supervised machine learning approaches to IE customization pose too high a burden on the user. Semi-supervised learning approaches may in principle offer a more resource effective solution but are still insufficiently accurate to grant realistic application. We demonstrate that this limitation can be overcome by integrating fully-supervised learning techniques within a semi-supervised IE approach, without increasing resource requirements.

  15. Geospatial Information Relevant to the Flood Protection Available on The Mainstream Web

    Directory of Open Access Journals (Sweden)

    Kliment Tomáš

    2014-03-01

    Full Text Available Flood protection is one of several disciplines where geospatial data is very important and is a crucial component. Its management, processing and sharing form the foundation for their efficient use; therefore, special attention is required in the development of effective, precise, standardized, and interoperable models for the discovery and publishing of data on the Web. This paper describes the design of a methodology to discover Open Geospatial Consortium (OGC services on the Web and collect descriptive information, i.e., metadata in a geocatalogue. A pilot implementation of the proposed methodology - Geocatalogue of geospatial information provided by OGC services discovered on Google (hereinafter “Geocatalogue” - was used to search for available resources relevant to the area of flood protection. The result is an analysis of the availability of resources discovered through their metadata collected from the OGC services (WMS, WFS, etc. and the resources they provide (WMS layers, WFS objects, etc. within the domain of flood protection.

  16. Autism spectrum disorder updates – relevant information for early interventionists to consider

    Directory of Open Access Journals (Sweden)

    Paula Allen-Meares

    2016-10-01

    Full Text Available Autism spectrum disorder (ASD is a pervasive developmental disorder characterized by deficits in social communication skills as well as repetitive, restricted or stereotyped behaviors (1. Early interventionists are often found at the forefront of assessment, evaluation and early intervention services for children with ASD. The role of an early intervention specialist may include, assessing developmental history, providing group and individual counseling, working in partnership with families on home, school, and community environments, mobilizing school and community resources and assisting in the development of positive early intervention strategies (2, 3. The commonality amongst these roles resides in the importance of providing up-to-date, relevant information to families and children. The purpose of this review is to provide pertinent up-to-date knowledge for early interventionists to help inform practice in working with individuals with ASD, including common behavioral models of intervention.

  17. Autism Spectrum Disorder Updates – Relevant Information for Early Interventionists to Consider

    Science.gov (United States)

    Allen-Meares, Paula; MacDonald, Megan; McGee, Kristin

    2016-01-01

    Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by deficits in social communication skills as well as repetitive, restricted or stereotyped behaviors (1). Early interventionists are often found at the forefront of assessment, evaluation, and early intervention services for children with ASD. The role of an early intervention specialist may include assessing developmental history, providing group and individual counseling, working in partnership with families on home, school, and community environments, mobilizing school and community resources, and assisting in the development of positive early intervention strategies (2, 3). The commonality among these roles resides in the importance of providing up-to-date, relevant information to families and children. The purpose of this review is to provide pertinent up-to-date knowledge for early interventionists to help inform practice in working with individuals with ASD, including common behavioral models of intervention. PMID:27840812

  18. Autism Spectrum Disorder Updates - Relevant Information for Early Interventionists to Consider.

    Science.gov (United States)

    Allen-Meares, Paula; MacDonald, Megan; McGee, Kristin

    2016-01-01

    Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by deficits in social communication skills as well as repetitive, restricted or stereotyped behaviors (1). Early interventionists are often found at the forefront of assessment, evaluation, and early intervention services for children with ASD. The role of an early intervention specialist may include assessing developmental history, providing group and individual counseling, working in partnership with families on home, school, and community environments, mobilizing school and community resources, and assisting in the development of positive early intervention strategies (2, 3). The commonality among these roles resides in the importance of providing up-to-date, relevant information to families and children. The purpose of this review is to provide pertinent up-to-date knowledge for early interventionists to help inform practice in working with individuals with ASD, including common behavioral models of intervention.

  19. Geospatial Information Relevant to the Flood Protection Available on The Mainstream Web

    Science.gov (United States)

    Kliment, Tomáš; Gálová, Linda; Ďuračiová, Renata; Fencík, Róbert; Kliment, Marcel

    2014-03-01

    Flood protection is one of several disciplines where geospatial data is very important and is a crucial component. Its management, processing and sharing form the foundation for their efficient use; therefore, special attention is required in the development of effective, precise, standardized, and interoperable models for the discovery and publishing of data on the Web. This paper describes the design of a methodology to discover Open Geospatial Consortium (OGC) services on the Web and collect descriptive information, i.e., metadata in a geocatalogue. A pilot implementation of the proposed methodology - Geocatalogue of geospatial information provided by OGC services discovered on Google (hereinafter "Geocatalogue") - was used to search for available resources relevant to the area of flood protection. The result is an analysis of the availability of resources discovered through their metadata collected from the OGC services (WMS, WFS, etc.) and the resources they provide (WMS layers, WFS objects, etc.) within the domain of flood protection.

  20. Selective theta-synchronization of choice-relevant information subserves goal-directed behavior

    Directory of Open Access Journals (Sweden)

    Thilo eWomelsdorf

    2010-11-01

    Full Text Available Theta activity reflects a state of rhythmic modulation of excitability at the level of single neuron membranes, within local neuronal groups and between distant nodes of a neuronal network. A wealth of evidence has shown that during theta states distant neuronal groups synchronize, forming networks of spatially confined neuronal clusters at specific time periods during task performance. Here, we show that a functional commonality of networks engaging in theta rhythmic states is that they emerge around decision points, reflecting rhythmic synchronization of choice-relevant information. Decision points characterize a point in time shortly before a subject chooses to select one action over another, i.e. when automatic behavior is terminated and the organism reactivates multiple sources of information to evaluate the evidence for available choices. As such, decision processes require the coordinated retrieval of choice-relevant information including (i the retrieval of stimulus evaluations (stim.-reward associations and reward expectancies about future outcomes, (ii the retrieval of past and prospective memories (e.g. stim.-stim. associations, (iii the reactivation of contextual task rule representations (e.g. stim.-response mappings, along with (iv an ongoing assessment of sensory evidence. An increasing number of studies reveal that retrieval of these multiple types of information proceeds within few theta cycles through synchronized spiking activity across limbic, striatal and cortical processing nodes. The outlined evidence suggests that evolving spatially and temporally specific theta synchronization could serve as the critical correlate underlying the selection of a choice during goal-directed behavior.

  1. Taming Big Data: An Information Extraction Strategy for Large Clinical Text Corpora.

    Science.gov (United States)

    Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gupta, Kalpana; Trautner, Barbara

    2015-01-01

    Concepts of interest for clinical and research purposes are not uniformly distributed in clinical text available in electronic medical records. The purpose of our study was to identify filtering techniques to select 'high yield' documents for increased efficacy and throughput. Using two large corpora of clinical text, we demonstrate the identification of 'high yield' document sets in two unrelated domains: homelessness and indwelling urinary catheters. For homelessness, the high yield set includes homeless program and social work notes. For urinary catheters, concepts were more prevalent in notes from hospitalized patients; nursing notes accounted for a majority of the high yield set. This filtering will enable customization and refining of information extraction pipelines to facilitate extraction of relevant concepts for clinical decision support and other uses.

  2. Seasonal forecasts of impact-relevant climate information indices developed as part of the EUPORIAS project

    Science.gov (United States)

    Spirig, Christoph; Bhend, Jonas

    2015-04-01

    Climate information indices (CIIs) represent a way to communicate climate conditions to specific sectors and the public. As such, CIIs provide actionable information to stakeholders in an efficient way. Due to their non-linear nature, such CIIs can behave differently than the underlying variables, such as temperature. At the same time, CIIs do not involve impact models with different sources of uncertainties. As part of the EU project EUPORIAS (EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale) we have developed examples of seasonal forecasts of CIIs. We present forecasts and analyses of the skill of seasonal forecasts for CIIs that are relevant to a variety of economic sectors and a range of stakeholders: heating and cooling degree days as proxies for energy demand, various precipitation and drought-related measures relevant to agriculture and hydrology, a wild fire index, a climate-driven mortality index and wind-related indices tailored to renewable energy producers. Common to all examples is the finding of limited forecast skill over Europe, highlighting the challenge for providing added-value services to stakeholders operating in Europe. The reasons for the lack of forecast skill vary: often we find little skill in the underlying variable(s) precisely in those areas that are relevant for the CII, in other cases the nature of the CII is particularly demanding for predictions, as seen in the case of counting measures such as frost days or cool nights. On the other hand, several results suggest there may be some predictability in sub-regions for certain indices. Several of the exemplary analyses show potential for skillful forecasts and prospect for improvements by investing in post-processing. Furthermore, those cases for which CII forecasts showed similar skill values as those of the underlying meteorological variables, forecasts of CIIs provide added value from a user perspective.

  3. Automatically extracting clinically useful sentences from UpToDate to support clinicians’ information needs

    Science.gov (United States)

    Mishra, Rashmi; Fiol, Guilherme Del; Kilicoglu, Halil; Jonnalagadda, Siddhartha; Fiszman, Marcelo

    2013-01-01

    Clinicians raise several information needs in the course of care. Most of these needs can be met by online health knowledge resources such as UpToDate. However, finding relevant information in these resources often requires significant time and cognitive effort. Objective: To design and assess algorithms for extracting from UpToDate the sentences that represent the most clinically useful information for patient care decision making. Methods: We developed algorithms based on semantic predications extracted with SemRep, a semantic natural language processing parser. Two algorithms were compared against a gold standard composed of UpToDate sentences rated in terms of clinical usefulness. Results: Clinically useful sentences were strongly correlated with predication frequency (correlation= 0.95). The two algorithms did not differ in terms of top ten precision (53% vs. 49%; p=0.06). Conclusions: Semantic predications may serve as the basis for extracting clinically useful sentences. Future research is needed to improve the algorithms. PMID:24551389

  4. Alveolar dimensional changes relevant to implant placement after minimally traumatic tooth extraction with primary closure.

    Science.gov (United States)

    Carranza, Nelson; Bonta, Hernan; Gualtieri, Ariel F; Rojas, Mariana A; Galli, Federico G; Caride, Facundo

    2016-09-01

    The purpose of this study is to evaluate the dimensional changes that occur in the alveolar ridge after minimally traumatic tooth extraction by means of computed tomography (CT), with special focus on the portion of bone supporting the gingival zenith. Twenty subjects with indication for singlerooted tooth extraction and preserved alveolar walls were selected for this study. After a minimally traumatic extraction, two CT scans were performed; the first within 24 hours postextraction (TC1) and the second 6 months (TC2) later. A radiographic guide with a radiopaque marker was used to obtain references that enabled accurate measurements over time, in both vertical and horizontal directions. The bone crest immediately apical to the gingival zenith was identified and termed "osseous zenith". The displacement of the osseous zenith in horizontal and vertical direction was analyzed and correlated with several alveolar anatomical variables with the aim of identifying possible predictors for bone remodeling. Dimensional changes that occur in postextraction sockets within a 6month period showed significant vertical and horizontal displacement of the osseous zenith (p 3 mm) should be expected. The present study suggests that the width of the alveolar crest at its midlevel, rather than crestal width, may be correlated with the displacement of the osseous zenith. Sociedad Argentina de Investigación Odontológica.

  5. Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

    Science.gov (United States)

    Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

    2003-01-01

    Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used

  6. Karst rocky desertification information extraction with EO-1 Hyperion data

    Science.gov (United States)

    Yue, Yuemin; Wang, Kelin; Zhang, Bing; Jiao, Quanjun; Yu, Yizun

    2008-12-01

    Karst rocky desertification is a special kind of land desertification developed under violent human impacts on the vulnerable eco-geo-environment of karst ecosystem. The process of karst rocky desertification results in simultaneous and complex variations of many interrelated soil, rock and vegetation biogeophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we aimed to use Earth Observing 1 (EO-1) Hyperion hyperspectral data to extract the karst rocky desertification information. A spectral unmixing model based on Monte Carlo approach, was employed to quantify the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare substrates. The results showed that SWIR (1.9-2.35μm) portions of the spectrum were significantly different in PV, NPV and bare rock spectral properties. It has limitations in using full optical range or only SWIR (1.9-2.35μm) region of Hyperion to decompose image into PV, NPV and bare substrates covers. However, when use the tied-SWIR, the sub-pixel fractional covers of PV, NPV and bare substrates were accurately estimated. Our study indicates that the "tied-spectrum" method effectively accentuate the spectral characteristics of materials, while the spectral unmixing model based on Monte Carlo approach is a useful tool to automatically extract mixed ground objects in karst ecosystem. Karst rocky desertification information can be accurately extracted with EO-1 Hyperion. Imaging spectroscopy can provide a powerful methodology toward understanding the extent and spatial pattern of land degradation in karst ecosystem.

  7. Automated extraction of chemical structure information from digital raster images

    Directory of Open Access Journals (Sweden)

    Shedden Kerby A

    2009-02-01

    Full Text Available Abstract Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links

  8. Use and perceptions of information among family physicians: sources considered accessible, relevant, and reliable

    Science.gov (United States)

    Kosteniuk, Julie G.; Morgan, Debra G.; D'Arcy, Carl K.

    2013-01-01

    Objectives: The research determined (1) the information sources that family physicians (FPs) most commonly use to update their general medical knowledge and to make specific clinical decisions, and (2) the information sources FPs found to be most physically accessible, intellectually accessible (easy to understand), reliable (trustworthy), and relevant to their needs. Methods: A cross-sectional postal survey of 792 FPs and locum tenens, in full-time or part-time medical practice, currently practicing or on leave of absence in the Canadian province of Saskatchewan was conducted during the period of January to April 2008. Results: Of 666 eligible physicians, 331 completed and returned surveys, resulting in a response rate of 49.7% (331/666). Medical textbooks and colleagues in the main patient care setting were the top 2 sources for the purpose of making specific clinical decisions. Medical textbooks were most frequently considered by FPs to be reliable (trustworthy), and colleagues in the main patient care setting were most physically accessible (easy to access). Conclusions: When making specific clinical decisions, FPs were most likely to use information from sources that they considered to be reliable and generally physically accessible, suggesting that FPs can best be supported by facilitating easy and convenient access to high-quality information. PMID:23405045

  9. Evaluation of relevant information for optimal reflector modeling through data assimilation procedures

    Directory of Open Access Journals (Sweden)

    Argaud Jean-Philippe

    2015-01-01

    Full Text Available The goal of this study is to look after the amount of information that is mandatory to get a relevant parameters optimisation by data assimilation for physical models in neutronic diffusion calculations, and to determine what is the best information to reach the optimum of accuracy at the cheapest cost. To evaluate the quality of the optimisation, we study the covariance matrix that represents the accuracy of the optimised parameter. This matrix is a classical output of the data assimilation procedure, and it is the main information about accuracy and sensitivity of the parameter optimal determination. From these studies, we present some results collected from the neutronic simulation of nuclear power plants. On the basis of the configuration studies, it has been shown that with data assimilation we can determine a global strategy to optimise the quality of the result with respect to the amount of information provided. The consequence of this is a cost reduction in terms of measurement and/or computing time with respect to the basic approach.

  10. Extraction of hidden information by efficient community detection in networks

    Science.gov (United States)

    Lee, Jooyoung; Lee, Juyong; Gross, Steven

    2013-03-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 20120001222).

  11. The Genomic Scrapheap Challenge; Extracting Relevant Data from Unmapped Whole Genome Sequencing Reads, Including Strain Specific Genomic Segments, in Rats.

    Science.gov (United States)

    van der Weide, Robin H; Simonis, Marieke; Hermsen, Roel; Toonen, Pim; Cuppen, Edwin; de Ligt, Joep

    2016-01-01

    Unmapped next-generation sequencing reads are typically ignored while they contain biologically relevant information. We systematically analyzed unmapped reads from whole genome sequencing of 33 inbred rat strains. High quality reads were selected and enriched for biologically relevant sequences; similarity-based analysis revealed clustering similar to previously reported phylogenetic trees. Our results demonstrate that on average 20% of all unmapped reads harbor sequences that can be used to improve reference genomes and generate hypotheses on potential genotype-phenotype relationships. Analysis pipelines would benefit from incorporating the described methods and reference genomes would benefit from inclusion of the genomic segments obtained through these efforts.

  12. Neodymium(III) Complexes of Dialkylphosphoric and Dialkylphosphonic Acids Relevant to Liquid-Liquid Extraction Systems

    Energy Technology Data Exchange (ETDEWEB)

    Lumetta, Gregg J.; Sinkov, Sergey I.; Krause, Jeanette A.; Sweet, Lucas E.

    2016-01-27

    The complexes formed during the extraction of neodymium(III) into hydrophobic solvents containing acidic organophosphorus extractants were probed by single-crystal X-ray diffractometry, visible spectrophotometry, and Fourier-transform infrared spectroscopy. The crystal structure of the compound Nd(DMP)3 (1, DMP = dimethyl phosphate) revealed a polymeric arrangement in which each Nd(III) center is surrounded by six DMP oxygen atoms in a pseudo-octahedral environment. Adjacent Nd(III) ions are bridged by (MeO)2POO– anions, forming the polymeric network. The diffuse reflectance visible spectrum of 1 is nearly identical to that of the solid that is formed when an n-dodecane solution of di-(2-ethylhexyl)phosphoric acid (HA) is saturated with Nd(III), indicating a similar coordination environment around the Nd center in the NdA3 solid. The visible spectrum of the HA solution fully loaded with Nd(III) is very similar to that of the NdA3 material, both displaying hypersensitive bands characteristic of an pseudo-octahedral coordination environment around Nd. These spectral characteristics persisted across a wide range of organic Nd concentrations, suggesting that the pseudo-octahedral coordination environment is maintained from dilute to saturated conditions.

  13. Classification and Extraction of Urban Land-Use Information from High-Resolution Image Based on Object Multi-features

    Institute of Scientific and Technical Information of China (English)

    Kong Chunfang; Xu Kai; Wu Chonglong

    2006-01-01

    Urban land provides a suitable location for various economic activities which affect the development of surrounding areas. With rapid industrialization and urbanization, the contradictions in land-use become more noticeable. Urban administrators and decision-makers seek modern methods and technology to provide information support for urban growth. Recently, with the fast development of high-resolution sensor technology, more relevant data can be obtained, which is an advantage in studying the sustainable development of urban land-use. However, these data are only information sources and are a mixture of "information" and "noise". Processing, analysis and information extraction from remote sensing data is necessary to provide useful information. This paper extracts urban land-use information from a high-resolution image by using the multi-feature information of the image objects, and adopts an object-oriented image analysis approach and multi-scale image segmentation technology. A classification and extraction model is set up based on the multi-features of the image objects, in order to contribute to information for reasonable planning and effective management. This new image analysis approach offers a satisfactory solution for extracting information quickly and efficiently.

  14. Assessing Hospital Physicians' Acceptance of Clinical Information Systems: A Review of the Relevant Literature

    Directory of Open Access Journals (Sweden)

    Bram Pynoo

    2013-06-01

    Full Text Available In view of the tremendous potential benefits of clinical information systems (CIS for the quality of patient care; it is hard to understand why not every CIS is embraced by its targeted users, the physicians. The aim of this study is to propose a framework for assessing hospital physicians' CIS-acceptance that can serve as a guidance for future research into this area. Hereto, a review of the relevant literature was performed in the ISI Web-of-Science database. Eleven studies were withheld from an initial dataset of 797 articles. Results show that just as in business settings, there are four core groups of variables that influence physicians' acceptance of a CIS: its usefulness and ease of use, social norms, and factors in the working environment that facilitate use of the CIS (such as providing computers/workstations, compatibility between the new and existing system.... We also identified some additional variables as predictors of CIS-acceptance.

  15. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  16. Extraction of neutron spectral information from Bonner-Sphere data

    CERN Document Server

    Haney, J H; Zaidins, C S

    1999-01-01

    We have extended a least-squares method of extracting neutron spectral information from Bonner-Sphere data which was previously developed by Zaidins et al. (Med. Phys. 5 (1978) 42). A pulse-height analysis with background stripping is employed which provided a more accurate count rate for each sphere. Newer response curves by Mares and Schraube (Nucl. Instr. and Meth. A 366 (1994) 461) were included for the moderating spheres and the bare detector which comprise the Bonner spectrometer system. Finally, the neutron energy spectrum of interest was divided using the philosophy of fuzzy logic into three trapezoidal regimes corresponding to slow, moderate, and fast neutrons. Spectral data was taken using a PuBe source in two different environments and the analyzed data is presented for these cases as slow, moderate, and fast neutron fluences. (author)

  17. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...

  18. Domain-independent information extraction in unstructured text

    Energy Technology Data Exchange (ETDEWEB)

    Irwin, N.H. [Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

    1996-09-01

    Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

  19. Querying and Extracting Timeline Information from Road Traffic Sensor Data.

    Science.gov (United States)

    Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

    2016-08-23

    The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system-a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset.

  20. Querying and Extracting Timeline Information from Road Traffic Sensor Data

    Directory of Open Access Journals (Sweden)

    Ardi Imawan

    2016-08-01

    Full Text Available The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset.

  1. Computer-assisted diagnosis of mammographic masses using an information-theoretic image retrieval scheme with BIRADs-based relevance feedback

    Science.gov (United States)

    Tourassi, Georgia D.; Floyd, Carey E., Jr.

    2004-05-01

    The purpose of the study was to develop and evaluate a content-based image retrieval (CBIR) approach for computer-assisted diagnosis of masses detected in screening mammograms. The system follows an information theoretic retrieval scheme with a BIRADS-based relevance feedback (RF) algorithm. Initially, a knowledge databank of 365 mammographic regions of interest (ROIs) was created. They were all 512x512 pixel ROIs extracted from DDSM mammograms digitized using the Lumisys digitizer. The ROIs were extracted around the known locations of the annotated masses. Specifically, there were 177 ROIs depicting a biopsy-proven malignant mass and 188 ROIs with a benign mass. Subsequently, the CBIR algorithm was implemented using mutual information (MI) as the similarity metric for image retrieval. The CBIR algorithm formed the basis of a knowledge-based CAD system. Given a databank of mammographic masses with known pathology, a query mass was evaluated. Based on their information content, all similar masses in the databank were retrieved. A relevance feedback algorithm based on BIRADS findings was implemented to determine the relevance factor of the retrieved masses. Finally, a decision index was calculated using the query's k best matches. The decision index effectively combined the similarity metric of the retrieved cases and their relevance factor into a prediction regarding the malignancy status of the mass depicted in the query ROI. ROC analysis was to evaluate diagnostic performance. Performance improved dramatically with the incorporation of the relevance feedback algorithm. Overall, the CAD system achieved ROC area index AZ= 0.86+/-0.02 for the diagnosis of masses in screening mammograms.

  2. Research of information classification and strategy intelligence extract algorithm based on military strategy hall

    Science.gov (United States)

    Chen, Lei; Li, Dehua; Yang, Jie

    2007-12-01

    Constructing virtual international strategy environment needs many kinds of information, such as economy, politic, military, diploma, culture, science, etc. So it is very important to build an information auto-extract, classification, recombination and analysis management system with high efficiency as the foundation and component of military strategy hall. This paper firstly use improved Boost algorithm to classify obtained initial information, then use a strategy intelligence extract algorithm to extract strategy intelligence from initial information to help strategist to analysis information.

  3. The Determination of Relevant Goals and Criteria Used to Select an Automated Patient Care Information System: A Delphi Approach

    OpenAIRE

    Chocholik, Joan K.; Bouchard, Susan E.; Tan, Joseph K. H.; Ostrow, David N.

    1999-01-01

    Objectives: To determine the relevant weighted goals and criteria for use in the selection of an automated patient care information system (PCIS) using a modified Delphi technique to achieve consensus.

  4. Trend extraction of rail corrugation measured dynamically based on the relevant low-frequency principal components reconstruction

    Science.gov (United States)

    Li, Yanfu; Liu, Hongli; Ma, Ziji

    2016-10-01

    Rail corrugation dynamic measurement techniques are critical to guarantee transport security and guide rail maintenance. During the inspection process, low-frequency trends caused by rail fluctuation are usually superimposed on rail corrugation and seriously affect the assessment of rail maintenance quality. In order to extract and remove the nonlinear and non-stationary trends from original mixed signals, a hybrid model based ensemble empirical mode decomposition (EEMD) and modified principal component analysis (MPCA) is proposed in this paper. Compared with the existing de-trending methods based on EMD, this method first considers low-frequency intrinsic mode functions (IMFs) thought to be underlying trend components that maybe contain some unrelated components, such as white noise and low-frequency signal itself, and proposes to use PCA to accurately extract the pure trends from the IMFs containing multiple components. On the other hand, due to the energy contribution ratio between trends and mixed signals is prior unknown, and the principal components (PCs) decomposed by PCA are arranged in order of energy reduction without considering frequency distribution, the proposed method modifies traditional PCA and just selects relevant low-frequency PCs to reconstruct the trends based on the zero-crossing numbers (ZCN) of each PC. Extensive tests are presented to illustrate the effectiveness of the proposed method. The results show the proposed EEMD-PCA-ZCN is an effective tool for trend extraction of rail corrugation measured dynamically.

  5. Perceived relevance and information needs regarding food topics and preferred information sources among Dutch adults: results of a quantitative consumer study

    NARCIS (Netherlands)

    Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.

    2004-01-01

    Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research. Des

  6. Perceived relevance and information needs regarding food topics and preferred information sources among Dutch adults: results of a quantitative consumer study

    NARCIS (Netherlands)

    Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.

    2004-01-01

    Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research. Des

  7. KneeTex: an ontology-driven system for information extraction from MRI reports.

    Science.gov (United States)

    Spasić, Irena; Zhao, Bo; Jones, Christopher B; Button, Kate

    2015-01-01

    on a test set of 100 MRI reports. A gold standard consisted of 1,259 filled template records with the following slots: finding, finding qualifier, negation, certainty, anatomy and anatomy qualifier. KneeTex extracted information with precision of 98.00 %, recall of 97.63 % and F-measure of 97.81 %, the values of which are in line with human-like performance. KneeTex is an open-source, stand-alone application for information extraction from narrative reports that describe an MRI scan of the knee. Given an MRI report as input, the system outputs the corresponding clinical findings in the form of JavaScript Object Notation objects. The extracted information is mapped onto TRAK, an ontology that formally models knowledge relevant for the rehabilitation of knee conditions. As a result, formally structured and coded information allows for complex searches to be conducted efficiently over the original MRI reports, thereby effectively supporting epidemiologic studies of knee conditions.

  8. Extracting information in spike time patterns with wavelets and information theory.

    Science.gov (United States)

    Lopes-dos-Santos, Vítor; Panzeri, Stefano; Kayser, Christoph; Diamond, Mathew E; Quian Quiroga, Rodrigo

    2015-02-01

    We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information. Copyright © 2015 the American Physiological Society.

  9. Expert versus novice differences in the detection of relevant information during a chess game: Evidence from eye movements

    Directory of Open Access Journals (Sweden)

    Heather eSheridan

    2014-08-01

    Full Text Available The present study explored the ability of expert and novice chess players to rapidly distinguish between regions of a chessboard that were relevant to the best move on the board, and regions of the board that were irrelevant. Accordingly, we monitored the eye movements of expert and novice chess players, while they selected white’s best move for a variety of chess problems. To manipulate relevancy, we constructed two different versions of each chess problem in the experiment, and we counterbalanced these versions across participants. These two versions of each problem were identical except that a single piece was changed from a bishop to a knight. This subtle change reversed the relevancy map of the board, such that regions that were relevant in one version of the board were now irrelevant (and vice versa. Using this paradigm, we demonstrated that both the experts and novices spent more time fixating the relevant relative to the irrelevant regions of the board. However, the experts were faster at detecting relevant information than the novices, as shown by the finding that experts (but not novices were able to distinguish between relevant and irrelevant information during the early part of the trial. These findings further demonstrate the domain-related perceptual processing advantage of chess experts, using an experimental paradigm that allowed us to manipulate relevancy under tightly controlled conditions.

  10. Computations Underlying Social Hierarchy Learning: Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information.

    Science.gov (United States)

    Kumaran, Dharshan; Banino, Andrea; Blundell, Charles; Hassabis, Demis; Dayan, Peter

    2016-12-07

    Knowledge about social hierarchies organizes human behavior, yet we understand little about the underlying computations. Here we show that a Bayesian inference scheme, which tracks the power of individuals, better captures behavioral and neural data compared with a reinforcement learning model inspired by rating systems used in games such as chess. We provide evidence that the medial prefrontal cortex (MPFC) selectively mediates the updating of knowledge about one's own hierarchy, as opposed to that of another individual, a process that underpinned successful performance and involved functional interactions with the amygdala and hippocampus. In contrast, we observed domain-general coding of rank in the amygdala and hippocampus, even when the task did not require it. Our findings reveal the computations underlying a core aspect of social cognition and provide new evidence that self-relevant information may indeed be afforded a unique representational status in the brain. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Public health genomics Relevance of genomics for individual health information management, health policy development and effective health services.

    Directory of Open Access Journals (Sweden)

    Angela Brand

    2006-12-01

    Full Text Available Healthcare delivery systems are facing fundamental challenges. New ways of organising theses systems based on the different needs of stakeholders’ are required to meet these challenges. While medicine is currently undergoing remarkable developments from its morphological and phenotype orientation to a molecular and genotype orientation, promoting the importance of prognosis and prediction, the discussion about the relevance of genome-based information and technologies for the health care system as a whole and especially for public health is still in its infancy. The following article discusses the relevance of genome-based information and technologies for individual health information management, health policy development and effective health services.

  12. Bengali-English Relevant Cross Lingual Information Access Using Finite Automata

    Science.gov (United States)

    Banerjee, Avishek; Bhattacharyya, Swapan; Hazra, Simanta; Mondal, Shatabdi

    2010-10-01

    CLIR techniques searches unrestricted texts and typically extract term and relationships from bilingual electronic dictionaries or bilingual text collections and use them to translate query and/or document representations into a compatible set of representations with a common feature set. In this paper, we focus on dictionary-based approach by using a bilingual data dictionary with a combination to statistics-based methods to avoid the problem of ambiguity also the development of human computer interface aspects of NLP (Natural Language processing) is the approach of this paper. The intelligent web search with regional language like Bengali is depending upon two major aspect that is CLIA (Cross language information access) and NLP. In our previous work with IIT, KGP we already developed content based CLIA where content based searching in trained on Bengali Corpora with the help of Bengali data dictionary. Here we want to introduce intelligent search because to recognize the sense of meaning of a sentence and it has a better real life approach towards human computer interactions.

  13. THE STUDY OF THE RELEVANCE ON THE ESTABLISHMENT OF DRUG INFORMATION CENTRE AT A SECONDARY HOSPITAL IN SOUTH WEST NIGERIA

    Directory of Open Access Journals (Sweden)

    Omole Moses Kayode

    2012-10-01

    Full Text Available This prospective study was carried out in a state hospital, Sokemu, Abeokuta to determine the relevance of Drug Information Centre (DIC to the practice of Health Care Professionals in the Hospital. A total of 120 questionnaires were administered to the hospital health care professionals. Total number of respondents was 107 corresponding to 89.2% of the total population with years of experience in service ranging from 5- 15 years.Eighty five 85 (79.4% believed that Drug Information Centre was relevant to their professional practice, 12 (11.2% believed that it was not relevant to their professional practice, while 10 (9.4% were not sure of the relevance of the DIC to their professional practice.Forty three (43 (19.2% respondents required latest Information on drugs, 25 (11.2% required information on side effects, 29 (12.9% on dosage form, 27 (12.1% on dosage regimen, 12 (5.4% on indications, 27 (12.1% on contra-indications, 19 (8.5% on brand names and 21 (9.4% required drug information on all the listed areas.Forty seven (47 (43.9% claimed that they obtained Drug Information from relevant textbooks, 74 (69.2% from colleagues, 16 (15.0% from internet, 23 (21.5% from journal and largest number 102 (95.3% claimed they obtained information from the Pharmacists who are medical representatives of pharmaceutical companies as well as from hospital pharmacists.Drug Information Centre was found to be relevant to the practice of health care professionals at a state hospital, Sokemu in Abeokuta, Nigeria. Hypothesis testing showed significant relationship of p<0.05.

  14. Analysis of the Relevance of Information Content of the Value Added Statement in the Brazilian Capital Markets

    Directory of Open Access Journals (Sweden)

    Márcio André Veras Machado

    2015-04-01

    Full Text Available The usefulness of financial statements depends, fundamentally, on the degree of relevance of the information they disclose to users. Thus, studies that measure the relevance of accounting information to the users of financial statements are of some importance. One line of research within this subject is in ascertaining the relevance and importance of accounting information for the capital markets: if a particular item of accounting information is minimally reflected in the price of a share, it is because this information has relevance, at least at a certain level of significance, for investors and analysts of the capital markets. This present study aims to analyze the relevance, in the Brazilian capital markets, of the information content of the Value Added Statement (or VAS - referred to in Brazil as the Demonstração do Valor Adicionado, or DVA. It analyzed the ratio between stock price and Wealth created per share (WCPS, using linear regressions, for the period 2005-2011, for non-financial listed companies included in Melhores & Maiores ('Biggest & Best', an annual listing published by Exame Magazine in Brazil. As a secondary objective, this article seeks to establish whether WCPS represents a better indication of a company's result than Net profit per share (in this study, referred to as NPPS. The empirical evidence that was found supports the concept that the VAS has relevant information content, because it shows a capacity to explain a variation in the share price of the companies studied. Additionally, the relationship between WCPS and the stock price was shown to be significant, even after the inclusion of the control variables Stockholders' equity per share (which we abbreviate in this study to SEPS and NPPS. Finally, the evidence found indicates that the market reacts more to WCPS (Wealth created per share than to NPPS. Thus, the results obtained give some indication that, for the Brazilian capital markets, WCPS may be a better proxy

  15. Structural analysis of health-relevant policy-making information exchange networks in Canada.

    Science.gov (United States)

    Contandriopoulos, Damien; Benoît, François; Bryant-Lukosius, Denise; Carrier, Annie; Carter, Nancy; Deber, Raisa; Duhoux, Arnaud; Greenhalgh, Trisha; Larouche, Catherine; Leclerc, Bernard-Simon; Levy, Adrian; Martin-Misener, Ruth; Maximova, Katerina; McGrail, Kimberlyn; Nykiforuk, Candace; Roos, Noralou; Schwartz, Robert; Valente, Thomas W; Wong, Sabrina; Lindquist, Evert; Pullen, Carolyn; Lardeux, Anne; Perroux, Melanie

    2017-09-20

    Health systems worldwide struggle to identify, adopt, and implement in a timely and system-wide manner the best-evidence-informed-policy-level practices. Yet, there is still only limited evidence about individual and institutional best practices for fostering the use of scientific evidence in policy-making processes The present project is the first national-level attempt to (1) map and structurally analyze-quantitatively-health-relevant policy-making networks that connect evidence production, synthesis, interpretation, and use; (2) qualitatively investigate the interaction patterns of a subsample of actors with high centrality metrics within these networks to develop an in-depth understanding of evidence circulation processes; and (3) combine these findings in order to assess a policy network's "absorptive capacity" regarding scientific evidence and integrate them into a conceptually sound and empirically grounded framework. The project is divided into two research components. The first component is based on quantitative analysis of ties (relationships) that link nodes (participants) in a network. Network data will be collected through a multi-step snowball sampling strategy. Data will be analyzed structurally using social network mapping and analysis methods. The second component is based on qualitative interviews with a subsample of the Web survey participants having central, bridging, or atypical positions in the network. Interviews will focus on the process through which evidence circulates and enters practice. Results from both components will then be integrated through an assessment of the network's and subnetwork's effectiveness in identifying, capturing, interpreting, sharing, reframing, and recodifying scientific evidence in policy-making processes. Knowledge developed from this project has the potential both to strengthen the scientific understanding of how policy-level knowledge transfer and exchange functions and to provide significantly improved advice

  16. Medicaid Analytic eXtract (MAX) General Information

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Medicaid Analytic eXtract (MAX) data is a set of person-level data files on Medicaid eligibility, service utilization, and payments. The MAX data are created to...

  17. Medicaid Analytic eXtract (MAX) General Information

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Medicaid Analytic eXtract (MAX) data is a set of person-level data files on Medicaid eligibility, service utilization, and payments. The MAX data are created to...

  18. Providing Decision-Relevant Information for a State Climate Change Action Plan

    Science.gov (United States)

    Wake, C.; Frades, M.; Hurtt, G. C.; Magnusson, M.; Gittell, R.; Skoglund, C.; Morin, J.

    2008-12-01

    Carbon Solutions New England (CSNE), a public-private partnership formed to promote collective action to achieve a low carbon society, has been working with the Governor appointed New Hampshire Climate Change Policy Task Force (NHCCTF) to support the development of a state Climate Change Action Plan. CSNE's role has been to quantify the potential carbon emissions reduction, implementation costs, and cost savings at three distinct time periods (2012, 2025, 2050) for a range of strategies identified by the Task Force. These strategies were developed for several sectors (transportation and land use, electricity generation and use, building energy use, and agriculture, forestry, and waste).New Hampshire's existing and projected economic and population growth are well above the regional average, creating additional challenges for the state to meet regional emission reduction targets. However, by pursuing an ambitious suite of renewable energy and energy efficiency strategies, New Hampshire may be able to continue growing while reducing emissions at a rate close to 3% per year up to 2025. This suite includes efficiency improvements in new and existing buildings, a renewable portfolio standard for electricity generation, avoiding forested land conversion, fuel economy gains in new vehicles, and a reduction in vehicle miles traveled. Most (over 80%) of these emission reduction strategies are projected to provide net economic savings in 2025.A collaborative and iterative process was developed among the key partners in the project. The foundation for the project's success included: a diverse analysis team with leadership that was committed to the project, an open source analysis approach, weekly meetings and frequent communication among the partners, interim reporting of analysis, and an established and trusting relationship among the partners, in part due to collaboration on previous projects.To develop decision-relevant information for the Task Force, CSNE addressed

  19. The Problems in Chinese Government Financial Information Disclosure and Relevant Proposals

    Directory of Open Access Journals (Sweden)

    Zhe Wang

    2016-03-01

    Full Text Available Government financial information is an important part of government information, fully reporting the operational efficiency and the place where government puts tax onto. This paper analyses the problems in Chinese government financial information disclosure and the necessity of reform in detail. It also provides several proposals for the improvement of Chinese governmental financial report and financial information disclosure system.

  20. Transforming a research-oriented dataset for evaluation of tactical information extraction technologies

    Science.gov (United States)

    Roy, Heather; Kase, Sue E.; Knight, Joanne

    2016-05-01

    The most representative and accurate data for testing and evaluating information extraction technologies is real-world data. Real-world operational data can provide important insights into human and sensor characteristics, interactions, and behavior. However, several challenges limit the feasibility of experimentation with real-world operational data. Realworld data lacks the precise knowledge of a "ground truth," a critical factor for benchmarking progress of developing automated information processing technologies. Additionally, the use of real-world data is often limited by classification restrictions due to the methods of collection, procedures for processing, and tactical sensitivities related to the sources, events, or objects of interest. These challenges, along with an increase in the development of automated information extraction technologies, are fueling an emerging demand for operationally-realistic datasets for benchmarking. An approach to meet this demand is to create synthetic datasets, which are operationally-realistic yet unclassified in content. The unclassified nature of these unclassified synthetic datasets facilitates the sharing of data between military and academic researchers thus increasing coordinated testing efforts. This paper describes the expansion and augmentation of two synthetic text datasets, one initially developed through academic research collaborations with the Army. Both datasets feature simulated tactical intelligence reports regarding fictitious terrorist activity occurring within a counterinsurgency (COIN) operation. The datasets were expanded and augmented to create two military relevant datasets. The first resulting dataset was created by augmenting and merging the two to create a single larger dataset containing ground-truth. The second resulting dataset was restructured to more realistically represent the format and content of intelligence reports. The dataset transformation effort, the final datasets, and their

  1. Relevance between the degree of industrial competition and fair value information: Study on the listed companies in China

    Directory of Open Access Journals (Sweden)

    Xuemin Zhuang

    2015-05-01

    Full Text Available Purpose: The purpose of this article is to study whether there exists natural relationship between fair value and corporate external market. A series of special phenomenon in the application of fair value arouses our research interests, which present evidences on how competition affects the correlation of fair value information. Design/methodology/approach: this thesis chooses fair value changes gains and losses and calculate the ratio of DFVPSit as the alternative variable of the fair value. In order to effectively inspect the mutual influence between the degree of industry competition and the value relevance of fair value, and reduce the impact of multi-collinearity, we built a regression model on the hypothesis, which supposes that if other conditions are the same, the fair value information has greater value relevance if the degree of the industry competition is greater. To test the hypothesis, we use the comparison of the DFVPSit coefficient absolute value to judge the value relevance of fair value information, and the greater the absolute value is, the higher relevance between the changes in fair value per share profits and losses with the stock prices. Findings: The higher the degree of competition in the industry is, the more fair value information relevance is. Also, there are evidences representing that fair value information often presents negative correlation with the stock price. Originality/value: The main contribution of the article is to show that not only need we make the formulation and implementation of the high quality of fair value accounting standards to suit for both the national conditions and international practice, but also need we further to improve the company's external governance mechanism to promote fair value’s information correlation.

  2. An Enhanced Text-Mining Framework for Extracting Disaster Relevant Data through Social Media and Remote Sensing Data Fusion

    Science.gov (United States)

    Scheele, C. J.; Huang, Q.

    2016-12-01

    In the past decade, the rise in social media has led to the development of a vast number of social media services and applications. Disaster management represents one of such applications leveraging massive data generated for event detection, response, and recovery. In order to find disaster relevant social media data, current approaches utilize natural language processing (NLP) methods based on keywords, or machine learning algorithms relying on text only. However, these approaches cannot be perfectly accurate due to the variability and uncertainty in language used on social media. To improve current methods, the enhanced text-mining framework is proposed to incorporate location information from social media and authoritative remote sensing datasets for detecting disaster relevant social media posts, which are determined by assessing the textual content using common text mining methods and how the post relates spatiotemporally to the disaster event. To assess the framework, geo-tagged Tweets were collected for three different spatial and temporal disaster events: hurricane, flood, and tornado. Remote sensing data and products for each event were then collected using RealEarthTM. Both Naive Bayes and Logistic Regression classifiers were used to compare the accuracy within the enhanced text-mining framework. Finally, the accuracies from the enhanced text-mining framework were compared to the current text-only methods for each of the case study disaster events. The results from this study address the need for more authoritative data when using social media in disaster management applications.

  3. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus

    OpenAIRE

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Background Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from fre...

  4. Automatic Data Extraction from Websites for Generating Aquatic Product Market Information

    Institute of Scientific and Technical Information of China (English)

    YUAN Hong-chun; CHEN Ying; SUN Yue-fu

    2006-01-01

    The massive web-based information resources have led to an increasing demand for effective automatic retrieval of target information for web applications. This paper introduces a web-based data extraction tool that deploys various algorithms to locate, extract and filter tabular data from HTML pages and to transform them into new web-based representations. The tool has been applied in an aquaculture web application platform for extracting and generating aquatic product market information.Results prove that this tool is very effective in extracting the required data from web pages.

  5. Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

    Science.gov (United States)

    Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

    2016-03-01

    Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

  6. Overview of image processing tools to extract physical information from JET videos

    Science.gov (United States)

    Craciunescu, T.; Murari, A.; Gelfusa, M.; Tiseanu, I.; Zoita, V.; EFDA Contributors, JET

    2014-11-01

    In magnetic confinement nuclear fusion devices such as JET, the last few years have witnessed a significant increase in the use of digital imagery, not only for the surveying and control of experiments, but also for the physical interpretation of results. More than 25 cameras are routinely used for imaging on JET in the infrared (IR) and visible spectral regions. These cameras can produce up to tens of Gbytes per shot and their information content can be very different, depending on the experimental conditions. However, the relevant information about the underlying physical processes is generally of much reduced dimensionality compared to the recorded data. The extraction of this information, which allows full exploitation of these diagnostics, is a challenging task. The image analysis consists, in most cases, of inverse problems which are typically ill-posed mathematically. The typology of objects to be analysed is very wide, and usually the images are affected by noise, low levels of contrast, low grey-level in-depth resolution, reshaping of moving objects, etc. Moreover, the plasma events have time constants of ms or tens of ms, which imposes tough conditions for real-time applications. On JET, in the last few years new tools and methods have been developed for physical information retrieval. The methodology of optical flow has allowed, under certain assumptions, the derivation of information about the dynamics of video objects associated with different physical phenomena, such as instabilities, pellets and filaments. The approach has been extended in order to approximate the optical flow within the MPEG compressed domain, allowing the manipulation of the large JET video databases and, in specific cases, even real-time data processing. The fast visible camera may provide new information that is potentially useful for disruption prediction. A set of methods, based on the extraction of structural information from the visual scene, have been developed for the

  7. Tagline: Information Extraction for Semi-Structured Text Elements in Medical Progress Notes

    Science.gov (United States)

    Finch, Dezon Kile

    2012-01-01

    Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in…

  8. Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art

    NARCIS (Netherlands)

    Habib, Mena B.; Keulen, van Maurice

    2011-01-01

    Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration meth

  9. Semantic Preview Benefit in English: Individual Differences in the Extraction and Use of Parafoveal Semantic Information

    Science.gov (United States)

    Veldre, Aaron; Andrews, Sally

    2016-01-01

    Although there is robust evidence that skilled readers of English extract and use orthographic and phonological information from the parafovea to facilitate word identification, semantic preview benefits have been elusive. We sought to establish whether individual differences in the extraction and/or use of parafoveal semantic information could…

  10. An Effective Approach to Biomedical Information Extraction with Limited Training Data

    Science.gov (United States)

    Jonnalagadda, Siddhartha

    2011-01-01

    In the current millennium, extensive use of computers and the internet caused an exponential increase in information. Few research areas are as important as information extraction, which primarily involves extracting concepts and the relations between them from free text. Limitations in the size of training data, lack of lexicons and lack of…

  11. Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice

    2011-01-01

    Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration meth

  12. LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE.

    Science.gov (United States)

    Krishnan, Ananthanarayan; Gandour, Jackson T

    2014-12-01

    Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long

  13. Towards an information extraction and knowledge formation framework based on Shannon entropy

    Directory of Open Access Journals (Sweden)

    Iliescu Dragoș

    2017-01-01

    Full Text Available Information quantity subject is approached in this paperwork, considering the specific domain of nonconforming product management as information source. This work represents a case study. Raw data were gathered from a heavy industrial works company, information extraction and knowledge formation being considered herein. Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for extraction of specific information and knowledge-that formation. The result of the entropy analysis point out the information needed to be acquired by the involved organisation, this being presented as a specific knowledge type.

  14. Representation of behaviourally relevant information by blowfly motion-sensitive visual interneurons requires precise compensatory head movements

    NARCIS (Netherlands)

    Kern, R.; Hateren, J.H. van; Egelhaaf, M.

    2006-01-01

    Flying blowflies shift their gaze by saccadic turns of body and head, keeping their gaze basically fixed between saccades. For the head, this results in almost pure translational optic flow between saccades, enabling visual interneurons in the fly motion pathway to extract information about translat

  15. Representation of behaviourally relevant information by blowfly motion-sensitive visual interneurons requires precise compensatory head movements

    NARCIS (Netherlands)

    Kern, R.; Hateren, J.H. van; Egelhaaf, M.

    2006-01-01

    Flying blowflies shift their gaze by saccadic turns of body and head, keeping their gaze basically fixed between saccades. For the head, this results in almost pure translational optic flow between saccades, enabling visual interneurons in the fly motion pathway to extract information about

  16. 77 FR 42339 - Improving Contracting Officers' Access to Relevant Integrity Information

    Science.gov (United States)

    2012-07-18

    ... information about contractor business ethics in the Federal Awardee Performance and Integrity Information System (FAPIIS). FAPIIS is designed to facilitate the Government's ability to evaluate the business ethics of prospective contractors and protect the Government from awarding contracts to contractors...

  17. Access to Attitude-Relevant Information in Memory as a Determinant of Attitude-Behavior Consistency.

    Science.gov (United States)

    Kallgren, Carl A.; Wood, Wendy

    Recent reserach has attempted to determine systematically how attitudes influence behavior. This research examined whether access to attitude-relevant beliefs and prior experiences would mediate the relation between attitudes and behavior. Subjects were 49 college students with a mean age of 27 who did not live with their parents or in…

  18. Effects of accessibility and subjective relevance on the use of piecemeal and category information in impression formation.

    Science.gov (United States)

    Köpetz, Catalina; Kruglanski, Arie W

    2008-05-01

    Three studies investigated the process by which categorical and individuating information impacts impression formation. The authors assumed that (a) both types of information are functionally equivalent in serving as evidence for interpersonal judgments and (b) their use is determined by their accessibility and perceived applicability to the impression's target. The first study constituted an extended replication of Pavelchak's experiment, and it showed that its results, initially interpreted to suggest the primacy in impression formation of category over trait information, may have been prompted by differential accessibility of the category versus trait information in some experimental conditions of the original research. Studies 2 and 3 additionally explored the role of informational accessibility manipulated in different ways. Study 3 demonstrated also that the effect of accessibility is qualified by the information's apparent relevance to the judgmental target.

  19. Automated information extraction of key trial design elements from clinical trial publications.

    Science.gov (United States)

    de Bruijn, Berry; Carini, Simona; Kiritchenko, Svetlana; Martin, Joel; Sim, Ida

    2008-11-06

    Clinical trials are one of the most valuable sources of scientific evidence for improving the practice of medicine. The Trial Bank project aims to improve structured access to trial findings by including formalized trial information into a knowledge base. Manually extracting trial information from published articles is costly, but automated information extraction techniques can assist. The current study highlights a single architecture to extract a wide array of information elements from full-text publications of randomized clinical trials (RCTs). This architecture combines a text classifier with a weak regular expression matcher. We tested this two-stage architecture on 88 RCT reports from 5 leading medical journals, extracting 23 elements of key trial information such as eligibility rules, sample size, intervention, and outcome names. Results prove this to be a promising avenue to help critical appraisers, systematic reviewers, and curators quickly identify key information elements in published RCT articles.

  20. Extraction of information of targets based on frame buffer

    Science.gov (United States)

    Han, Litao; Kong, Qiaoli; Zhao, Xiangwei

    2008-10-01

    In all ways of perception, vision is the main channel of getting environmental information for intelligent virtual agent (IVA). Reality and real-time computation of behavior simulation of intelligent objects in interactive virtual environment are required. This paper proposes a new method of getting environmental information. Firstly visual images are generated by setting a second view port in the location of viewpoint of IVA, and then the target location, distance, azimuth, and other basic geometric information and semantic information can be acquired based on the images. Experiments show that the method gives full play to the performance of computer graphic hardware with simple process and higher efficiency.

  1. Extracting local information from crowds through betting markets

    Science.gov (United States)

    Weijs, Steven

    2015-04-01

    In this research, a set-up is considered in which users can bet against a forecasting agency to challenge their probabilistic forecasts. From an information theory standpoint, a reward structure is considered that either provides the forecasting agency with better information, paying the successful providers of information for their winning bets, or funds excellent forecasting agencies through users that think they know better. Especially for local forecasts, the approach may help to diagnose model biases and to identify local predictive information that can be incorporated in the models. The challenges and opportunities for implementing such a system in practice are also discussed.

  2. Extraction of spatio-temporal information of earthquake event based on semantic technology

    Science.gov (United States)

    Fan, Hong; Guo, Dan; Li, Huaiyuan

    2015-12-01

    In this paper a web information extraction method is presented which identifies a variety of thematic events utilizing the event knowledge framework derived from text training, and then further uses the syntactic analysis to extract the event key information. The method which combines the text semantic information and domain knowledge of the event makes the extraction of information people interested more accurate. In this paper, web based earthquake news extraction is taken as an example. The paper firstly briefs the overall approaches, and then details the key algorithm and experiments of seismic events extraction. Finally, this paper conducts accuracy analysis and evaluation experiments which demonstrate that the proposed method is a promising way of hot events mining.

  3. Extracting Coherent Information from Noise Based Correlation Processing

    Science.gov (United States)

    2015-09-30

    LONG-TERM GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios...None PUBLICATIONS [1] “ Monitoring deep-ocean temperatures using acoustic ambinet noise,”K. W. Woolfe, S. Lani, K.G. Sabra, W. A. Kuperman...Geophys. Res. Lett., 42,2878–2884, doi:10.1002/2015GL063438 (2015). [2] “Optimized extraction of coherent arrivals from ambient noise correlations in

  4. Information Retrieval eXperience (IRX): Towards a Human-Centered Personalized Model of Relevance

    NARCIS (Netherlands)

    Sluis, van der Frans; Broek, van den Egon L.; Dijk, van Betsy; Hoeber, O.; Li, Y.; Huang, X.J.

    2010-01-01

    We approach Information Retrieval (IR) from a User eXperience (UX) perspective. Through introducing a model for Information Retrieval eXperience (IRX), this paper operationalizes a perspective on IR that reaches beyond topicality. Based on a document's topicality, complexity, and emotional value, a

  5. Advanced remote sensing terrestrial information extraction and applications

    CERN Document Server

    Liang, Shunlin; Wang, Jindi

    2012-01-01

    Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited application

  6. Spoken Language Understanding Systems for Extracting Semantic Information from Speech

    CERN Document Server

    Tur, Gokhan

    2011-01-01

    Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, usin

  7. [Test Reviews in Child Psychology: Test Users Wish to Obtain Practical Information Relevant to their Respective Field of Work].

    Science.gov (United States)

    Renner, Gerolf; Irblich, Dieter

    2016-11-01

    Test Reviews in Child Psychology: Test Users Wish to Obtain Practical Information Relevant to their Respective Field of Work This study investigated to what extent diagnosticians use reviews of psychometric tests for children and adolescents, how they evaluate their quality, and what they expect concerning content. Test users (n = 323) from different areas of work (notably social pediatrics, early intervention, special education, speech and language therapy) rated test reviews as one of the most important sources of information. Readers of test reviews value practically oriented descriptions and evaluations of tests that are relevant to their respective field of work. They expect independent reviews that critically discuss opportunities and limits of the tests under scrutiny. The results show that authors of test reviews should not only have a background in test theory but should also be familiar with the practical application of tests in various settings.

  8. Which Type of Risk Information to Use for Whom? Moderating Role of Outcome-Relevant Involvement in the Effects of Statistical and Exemplified Risk Information on Risk Perceptions.

    Science.gov (United States)

    So, Jiyeon; Jeong, Se-Hoon; Hwang, Yoori

    2017-04-01

    The extant empirical research examining the effectiveness of statistical and exemplar-based health information is largely inconsistent. Under the premise that the inconsistency may be due to an unacknowledged moderator (O'Keefe, 2002), this study examined a moderating role of outcome-relevant involvement (Johnson & Eagly, 1989) in the effects of statistical and exemplified risk information on risk perception. Consistent with predictions based on elaboration likelihood model (Petty & Cacioppo, 1984), findings from an experiment (N = 237) concerning alcohol consumption risks showed that statistical risk information predicted risk perceptions of individuals with high, rather than low, involvement, while exemplified risk information predicted risk perceptions of those with low, rather than high, involvement. Moreover, statistical risk information contributed to negative attitude toward drinking via increased risk perception only for highly involved individuals, while exemplified risk information influenced the attitude through the same mechanism only for individuals with low involvement. Theoretical and practical implications for health risk communication are discussed.

  9. Extraction of information about periodic orbits from scattering functions

    CERN Document Server

    Bütikofer, T; Seligman, T H; Bütikofer, Thomas; Jung, Christof; Seligman, Thomas H.

    1999-01-01

    As a contribution to the inverse scattering problem for classical chaotic systems, we show that one can select sequences of intervals of continuity, each of which yields the information about period, eigenvalue and symmetry of one unstable periodic orbit.

  10. Social relevance: toward understanding the impact of the individual in an information cascade

    Science.gov (United States)

    Hall, Robert T.; White, Joshua S.; Fields, Jeremy

    2016-05-01

    Information Cascades (IC) through a social network occur due to the decision of users to disseminate content. We define this decision process as User Diffusion (UD). IC models typically describe an information cascade by treating a user as a node within a social graph, where a node's reception of an idea is represented by some activation state. The probability of activation then becomes a function of a node's connectedness to other activated nodes as well as, potentially, the history of activation attempts. We enrich this Coarse-Grained User Diffusion (CGUD) model by applying actor type logics to the nodes of the graph. The resulting Fine-Grained User Diffusion (FGUD) model utilizes prior research in actor typing to generate a predictive model regarding the future influence a user will have on an Information Cascade. Furthermore, we introduce a measure of Information Resonance that is used to aid in predictions regarding user behavior.

  11. The relevance of cartographic scale in interactive and multimedia cartographic information systems

    Directory of Open Access Journals (Sweden)

    Mirjanka Lechthaler

    2004-09-01

    Full Text Available The application of new technologies in the processes of gathering, analysing, transforming, visualizing and communicating of space data and geoinformation offers a great challenge for cartography. Cartographic information provision as described in several cartographic models, which is included in cartographic information systems depend on the graphical presentation/visualization at certain scales. That necessitates a need to define the capacity or content borders (geometry and semantic for cognition and communication. However, currently we need and use maps as a vehicle for transportation of spatial and temporal information. Graphic constructions of geoanalogies, linked with interaction, multimedia sequences and animations, support effective geocommunication, bridging the gaps imposed by having to work at pre-defined scales. This paper illustrates two interactive information systems, which were conceptualised and prototyped at the Institute of Cartography and Geomedia Technique, Vienna University of Technology.

  12. Identifying strategies to improve access to credible and relevant information for public health professionals: a qualitative study

    Directory of Open Access Journals (Sweden)

    Simpson E Hatheway

    2006-04-01

    Full Text Available Abstract Background Movement towards evidence-based practices in many fields suggests that public health (PH challenges may be better addressed if credible information about health risks and effective PH practices is readily available. However, research has shown that many PH information needs are unmet. In addition to reviewing relevant literature, this study performed a comprehensive review of existing information resources and collected data from two representative PH groups, focusing on identifying current practices, expressed information needs, and ideal systems for information access. Methods Nineteen individual interviews were conducted among employees of two domains in a state health department – communicable disease control and community health promotion. Subsequent focus groups gathered additional data on preferences for methods of information access and delivery as well as information format and content. Qualitative methods were used to identify themes in the interview and focus group transcripts. Results Informants expressed similar needs for improved information access including single portal access with a good search engine; automatic notification regarding newly available information; access to best practice information in many areas of interest that extend beyond biomedical subject matter; improved access to grey literature as well as to more systematic reviews, summaries, and full-text articles; better methods for indexing, filtering, and searching for information; and effective ways to archive information accessed. Informants expressed a preference for improving systems with which they were already familiar such as PubMed and listservs rather than introducing new systems of information organization and delivery. A hypothetical ideal model for information organization and delivery was developed based on informants' stated information needs and preferred means of delivery. Features of the model were endorsed by the subjects who

  13. Identifying strategies to improve access to credible and relevant information for public health professionals: a qualitative study.

    Science.gov (United States)

    LaPelle, Nancy R; Luckmann, Roger; Simpson, E Hatheway; Martin, Elaine R

    2006-04-05

    Movement towards evidence-based practices in many fields suggests that public health (PH) challenges may be better addressed if credible information about health risks and effective PH practices is readily available. However, research has shown that many PH information needs are unmet. In addition to reviewing relevant literature, this study performed a comprehensive review of existing information resources and collected data from two representative PH groups, focusing on identifying current practices, expressed information needs, and ideal systems for information access. Nineteen individual interviews were conducted among employees of two domains in a state health department--communicable disease control and community health promotion. Subsequent focus groups gathered additional data on preferences for methods of information access and delivery as well as information format and content. Qualitative methods were used to identify themes in the interview and focus group transcripts. Informants expressed similar needs for improved information access including single portal access with a good search engine; automatic notification regarding newly available information; access to best practice information in many areas of interest that extend beyond biomedical subject matter; improved access to grey literature as well as to more systematic reviews, summaries, and full-text articles; better methods for indexing, filtering, and searching for information; and effective ways to archive information accessed. Informants expressed a preference for improving systems with which they were already familiar such as PubMed and listservs rather than introducing new systems of information organization and delivery. A hypothetical ideal model for information organization and delivery was developed based on informants' stated information needs and preferred means of delivery. Features of the model were endorsed by the subjects who reviewed it. Many critical information needs of PH

  14. Relevance of sampling and DNA extraction techniques for the analysis of salivary evidence from bite marks: a case report.

    Science.gov (United States)

    Chávez-Briones, M L; Hernández-Cortés, R; Jaramillo-Rangel, G; Ortega-Martínez, M

    2015-08-21

    Bite mark evidence has been repeatedly found in criminal cases. Physical comparison of a bite mark to the teeth of available suspects may not always be possible. Experimental studies have shown that the analysis of DNA present in the saliva recovered from bite marks might help in the identification of individuals. However, the application of this approach to an actual criminal case has been reported only once before in forensic literature. Therefore, there is very limited scientific and technical information available on this subject. The current study focuses on a woman found dead in her home; the autopsy ruled the death to be a result of manual strangulation. A bite mark was found on each breast. The single swab technique was used to collect evidence from these bite marks, and an organic extraction method was employed for DNA isolation. Short tandem repeat (STR) sequence typing was performed using a commercially available kit, and the result was compared to the STR profile of a suspect. A full single-source STR profile was obtained from both bite marks, which matched the STR profile of the suspect. To the best of our knowledge, this is the second report on the analysis of DNA isolated from bite marks on the victim used to identify the crime perpetrator. Our results indicated that, contrary to most theoretical indications, a single swab technique for evidence collection and an organic method for DNA isolation could be very useful in solving this class of criminal cases.

  15. NEW METHOD OF EXTRACTING WEAK FAILURE INFORMATION IN GEARBOX BY COMPLEX WAVELET DENOISING

    Institute of Scientific and Technical Information of China (English)

    CHEN Zhixin; XU Jinwu; YANG Debin

    2008-01-01

    Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new signal-denoising method which uses local adaptive algorithm based on dual-tree complex wavelet transform (DT-CWT) is introduced to extract weak failure information in gear, especially to extract impulse components. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking the advantage of near shift-invariance of DT-CWT, the higher signal-to-noise ratio (SNR) than common wavelet denoising methods can be obtained. Experiments of extracting periodic impulses in gearbox vibration signals indicate that the method can extract incipient fault feature and hidden information from heavy noise, and it has an excellent effect on identifying weak feature signals in gearbox vibration signals.

  16. 76 FR 22900 - Request for Information (RFI) To Identify and Obtain Relevant Information From Public or Private...

    Science.gov (United States)

    2011-04-25

    ... strategies to assure safety of the U.S. supply of blood and blood components, tissues, cells, and organs... and public health domains. This RFI is for information and planning purposes only and is not a... areas: Identifying strategies for protecting recipients and living donor health; ] Identifying processes...

  17. A Compilation of Metals and Trace Elements Extracted from Materials Relevant to Pharmaceutical Applications such as Packaging Systems and Devices.

    Science.gov (United States)

    Jenke, Dennis; Rivera, Christine; Mortensen, Tammy; Amin, Parul; Chacko, Molly; Tran, Thang; Chum, James

    2013-01-01

    Nearly 100 individual test articles, representative of materials used in pharmaceutical applications such as packaging and devices, were extracted under exaggerated conditions and the levels of 32 metals and trace elements (Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ge, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Sb, Se, Si, Sn, Sr, Ti, V, Zn, and Zr) were measured in the extracts. The extracting solvents included aqueous mixtures at low and high pH and an organic solvent mixture (40/60 ethanol water). The sealed vessel extractions were performed by placing an appropriate portion of the test articles and an appropriate volume of extracting solution in inert extraction vessels and exposing the extraction units (and associated extraction blanks) to defined conditions of temperature and duration. The levels of extracted target elements were measured by inductively coupled plasma atomic emission spectroscopy. The overall reporting threshold for most of the targeted elements was 0.05 μg/mL, which corresponds to 0.5 μg/g for the most commonly utilized extraction stoichiometry (1 g of material per 10 mL of extracting solvent). The targeted elements could be classified into four major groups depending on the frequency with which they were present in the over 250 extractions reported in this study. Thirteen elements (Ag, As, Be, Cd, Co, Ge, Li, Mo, Ni, Sn, Ti, V, and Zr) were not extracted in reportable quantities from any of the test articles under any of the extraction conditions. Eight additional elements (Bi, Cr, Cu, Mn, Pb, Sb, Se, and Sr) were rarely extracted from the test articles at reportable levels, and three other elements (Ba, Fe, and P) were infrequently extracted from the test articles at reportable levels. The remaining eight elements (Al, B, Ca, Mg, Na, S, Si, and Zn) were more frequently present in the extracts in reportable quantities. These general trends in accumulation behavior were compared to compiled lists of elements of concern as impurities in

  18. The Extraction Model of Paddy Rice Information Based on GF-1 Satellite WFV Images.

    Science.gov (United States)

    Yang, Yan-jun; Huang, Yan; Tian, Qing-jiu; Wang, Lei; Geng, Jun; Yang, Ran-ran

    2015-11-01

    In the present, using the characteristics of paddy rice at different phenophase to identify it by remote sensing images is an efficient way in the information extraction. According to the remarkably properties of paddy rice different from other vegetation, which the surface of paddy fields is with a large number of water in the early stage, NDWI (normalized difference water index) which is used to extract water information can reasonably be applied in the extraction of paddy rice at the early stage of the growth. And using NDWI ratio of two phenophase can expand the difference between paddy rice and other surface features, which is an important part for the extraction of paddy rice with high accuracy. Then using the variation of NDVI (normalized differential vegetation index) in different phenophase can further enhance accuracy of paddy rice information extraction. This study finds that making full advantage of the particularity of paddy rice in different phenophase and combining two indices (NDWI and NDVI) associated with paddy rice can establish a reasonable, accurate and effective extraction model of paddy rice. This is also the main way to improve the accuracy of paddy rice extraction. The present paper takes Lai'an in Anhui Province as the research area, and rice as the research object. It constructs the extraction model of paddy rice information using NDVI and NDWI between tillering stage and heading stage. Then the model was applied to GF1-WFV remote sensing image on July 12, 2013 and August 30, 2013. And it effectively extracted out of paddy rice distribution in Lai'an and carried on the mapping. At last, the result of extraction was verified and evaluated combined with field investigation data in the study area. The result shows that using the extraction model can quickly and accurately obtain the distribution of rice information, and it has the very good universality.

  19. Information extraction from FN plots of tungsten microemitters

    Energy Technology Data Exchange (ETDEWEB)

    Mussa, Khalil O. [Department of Physics, Mu' tah University, Al-Karak (Jordan); Mousa, Marwan S., E-mail: mmousa@mutah.edu.jo [Department of Physics, Mu' tah University, Al-Karak (Jordan); Fischer, Andreas, E-mail: andreas.fischer@physik.tu-chemnitz.de [Institut für Physik, Technische Universität Chemnitz, Chemnitz (Germany)

    2013-09-15

    Tungsten based microemitter tips have been prepared both clean and coated with dielectric materials. For clean tungsten tips, apex radii have been varied ranging from 25 to 500 nm. These tips were manufactured by electrochemical etching a 0.1 mm diameter high purity (99.95%) tungsten wire at the meniscus of two molar NaOH solution. Composite micro-emitters considered here are consisting of a tungsten core coated with different dielectric materials—such as magnesium oxide (MgO), sodium hydroxide (NaOH), tetracyanoethylene (TCNE), and zinc oxide (ZnO). It is worthwhile noting here, that the rather unconventional NaOH coating has shown several interesting properties. Various properties of these emitters were measured including current–voltage (IV) characteristics and the physical shape of the tips. A conventional field emission microscope (FEM) with a tip (cathode)–screen (anode) separation standardized at 10 mm was used to electrically characterize the electron emitters. The system was evacuated down to a base pressure of ∼10{sup −8}mbar when baked at up to ∼180°C overnight. This allowed measurements of typical field electron emission (FE) characteristics, namely the IV characteristics and the emission images on a conductive phosphorus screen (the anode). Mechanical characterization has been performed through a FEI scanning electron microscope (SEM). Within this work, the mentioned experimental results are connected to the theory for analyzing Fowler–Nordheim (FN) plots. We compared and evaluated the data extracted from clean tungsten tips of different radii and determined deviations between the results of different extraction methods applied. In particular, we derived the apex radii of several clean and coated tungsten tips by both SEM imaging and analyzing FN plots. The aim of this analysis is to support the ongoing discussion on recently developed improvements of the theory for analyzing FN plots related to metal field electron emitters, which in

  20. RELEVANCE OF THE ACCOUNTING INFORMATION FOR THE MERGERS AND ACQUISITIONS IN ROMANIA

    Directory of Open Access Journals (Sweden)

    ALIN EMANUEL ARTENE

    2012-11-01

    Full Text Available In the Romanian economic environment entities are operating, we can find a large number of factors that obstruct the development of many economic entities such as: the perpetual economic and financial crisis, bureaucracy, inflation, competition and many others. In our opinion a solution to overcome the difficulties Romanian economic entities are facing is merger or acquisition. The relevance of the advance accounting process such as merger and acquisition can be a support for many small and medium sized enterprises witch in the last year had functioned at the same parameters as the year before. Trough merger this type of entities can harmonize their production process, find ways to develop new and improved products and production processes and last but not least increase the percentage of research and development among Romanian economic entities.

  1. Advanced Extraction of Spatial Information from High Resolution Satellite Data

    Science.gov (United States)

    Pour, T.; Burian, J.; Miřijovský, J.

    2016-06-01

    In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  2. Extraction of Information on the Technical Effect from a Patent Document

    Science.gov (United States)

    Sakai, Hiroyuki; Nonaka, Hirohumi; Masuyama, Shigeru

    We propose a method for extracting information on the technical effect from a patent document. The information on the technical effect extracted by our method is useful for generating patent maps (see e.g., Figure 1.) automatically or analyzing the technical trend from patent documents. Our method extracts expressions containing the information on the technical effect by using frequent expressions and clue expressions effective for extracting them. The frequent expressions and clue expressions are extracted by using statistical information and initial clue expressions automatically. Our method extracts expressions containing the information on the technical effect without predetermined patterns given by hand, and is expected to be applied to other tasks for acquiring expressions that have a particular meaning (e.g., information on the means for solving the problems) not limited to the information on the technical effect. Our method achieves not only high precision (78.0%) but also high recall (77.6%) by acquiring such clue expressions automatically from patent documents.

  3. On Depth Information Extraction from Metal Detector Signals

    NARCIS (Netherlands)

    Schoolderman, A.J.; Wolf, F.J. de; Merlat, L.

    2003-01-01

    Information on the depth of objects detected with the help of a metal detector is useful for safe excavation of these objects in demining operations. Apart from that, depth informatíon may be used in advanced sensor fusion algorithms for a detection system where a metal detector is combíned with eg.

  4. Extracting Conflict-free Information from Multi-labeled Trees

    CERN Document Server

    Deepak, Akshay; McMahon, Michelle M

    2012-01-01

    A multi-labeled tree, or MUL-tree, is a phylogenetic tree where two or more leaves share a label, e.g., a species name. A MUL-tree can imply multiple conflicting phylogenetic relationships for the same set of taxa, but can also contain conflict-free information that is of interest and yet is not obvious. We define the information content of a MUL-tree T as the set of all conflict-free quartet topologies implied by T, and define the maximal reduced form of T as the smallest tree that can be obtained from T by pruning leaves and contracting edges while retaining the same information content. We show that any two MUL-trees with the same information content exhibit the same reduced form. This introduces an equivalence relation in MUL-trees with potential applications to comparing MUL-trees. We present an efficient algorithm to reduce a MUL-tree to its maximally reduced form and evaluate its performance on empirical datasets in terms of both quality of the reduced tree and the degree of data reduction achieved.

  5. THE RELEVANCE OF ACCOUNTING INFORMATION GENERATED BY THE APPLICATION OF IAS 29 RELATED TO SHAREHOLDERS CAPITAL

    Directory of Open Access Journals (Sweden)

    Bunget Ovidiu Constantin

    2013-07-01

    The objective of IAS 29 is to establish specific standards for entities reporting in the currency of a hyperinflationary economy, so that the financial information provided is meaningful. Our empirical analysis encompasses a hyperinflationary economy covering a wide variety of hyperinflationary conditions.

  6. Three subsets of sequence complexity and their relevance to biopolymeric information

    Directory of Open Access Journals (Sweden)

    Trevors Jack T

    2005-08-01

    Full Text Available Abstract Genetic algorithms instruct sophisticated biological organization. Three qualitative kinds of sequence complexity exist: random (RSC, ordered (OSC, and functional (FSC. FSC alone provides algorithmic instruction. Random and Ordered Sequence Complexities lie at opposite ends of the same bi-directional sequence complexity vector. Randomness in sequence space is defined by a lack of Kolmogorov algorithmic compressibility. A sequence is compressible because it contains redundant order and patterns. Law-like cause-and-effect determinism produces highly compressible order. Such forced ordering precludes both information retention and freedom of selection so critical to algorithmic programming and control. Functional Sequence Complexity requires this added programming dimension of uncoerced selection at successive decision nodes in the string. Shannon information theory measures the relative degrees of RSC and OSC. Shannon information theory cannot measure FSC. FSC is invariably associated with all forms of complex biofunction, including biochemical pathways, cycles, positive and negative feedback regulation, and homeostatic metabolism. The algorithmic programming of FSC, not merely its aperiodicity, accounts for biological organization. No empirical evidence exists of either RSC of OSC ever having produced a single instance of sophisticated biological organization. Organization invariably manifests FSC rather than successive random events (RSC or low-informational self-ordering phenomena (OSC.

  7. Two applications of information extraction to biological science journal articles: enzyme interactions and protein structures.

    Science.gov (United States)

    Humphreys, K; Demetriou, G; Gaizauskas, R

    2000-01-01

    Information extraction technology, as defined and developed through the U.S. DARPA Message Understanding Conferences (MUCs), has proved successful at extracting information primarily from newswire texts and primarily in domains concerned with human activity. In this paper we consider the application of this technology to the extraction of information from scientific journal papers in the area of molecular biology. In particular, we describe how an information extraction system designed to participate in the MUC exercises has been modified for two bioinformatics applications: EMPathIE, concerned with enzyme and metabolic pathways; and PASTA, concerned with protein structure. Progress to date provides convincing grounds for believing that IE techniques will deliver novel and effective ways for scientists to make use of the core literature which defines their disciplines.

  8. Financial Information Extraction Using Pre-defined and User-definable Templates in the LOLITA System

    OpenAIRE

    Costantino, Marco; Morgan, Richard G.; Collingham, Russell J.

    1996-01-01

    This paper addresses the issue of information extraction in the financial domain within the framework of a large Natural Language Processing system: LOLITA. The LOLITA system, Large-scale Object-based Linguistic Interactor Translator and Analyser, is a general purpose natural language processing system. Different kinds of applications have been built around the system's core. One of these is the financial information extraction application, which has been designed in close contact with expert...

  9. Extracting information masked by the chaotic signal of a time-delay system.

    Science.gov (United States)

    Ponomarenko, V I; Prokhorov, M D

    2002-08-01

    We further develop the method proposed by Bezruchko et al. [Phys. Rev. E 64, 056216 (2001)] for the estimation of the parameters of time-delay systems from time series. Using this method we demonstrate a possibility of message extraction for a communication system with nonlinear mixing of information signal and chaotic signal of the time-delay system. The message extraction procedure is illustrated using both numerical and experimental data and different kinds of information signals.

  10. Imaged document information location and extraction using an optical correlator

    Science.gov (United States)

    Stalcup, Bruce W.; Dennis, Phillip W.; Dydyk, Robert B.

    1999-12-01

    Today, the paper document is fast becoming a thing of the past. With the rapid development of fast, inexpensive computing and storage devices, many government and private organizations are archiving their documents in electronic form (e.g., personnel records, medical records, patents, etc.). Many of these organizations are converting their paper archives to electronic images, which are then stored in a computer database. Because of this, there is a need to efficiently organize this data into comprehensive and accessible information resources and provide for rapid access to the information contained within these imaged documents. To meet this need, Litton PRC and Litton Data Systems Division are developing a system, the Imaged Document Optical Correlation and Conversion System (IDOCCS), to provide a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provide a means for the search and retrieval of information from imaged documents. IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives and has the potential to determine the types of languages contained within a document. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited, e.g., imaged documents containing an agency's seal or logo can be singled out. In this paper, we present a description of IDOCCS as well as preliminary performance results and theoretical projections.

  11. Using climate information for improved health in Africa: relevance, constraints and opportunities

    Directory of Open Access Journals (Sweden)

    Stephen J. Connor

    2006-11-01

    Full Text Available Good health status is one of the primary aspirations of human social development and, as a consequence, health indicators are key components of the human development indices by which we measure progress toward sustainable development. Certain diseases and ill health are associated with particular environmental and climate conditions. The timeframe of the Millennium Development Goals (MDGs demands that the risks to health associated with current climate variability are more fully understood and acted upon to improve the focus of resources in climate sensitive disease control, especially in sub-Saharan Africa, where good epidemiological surveillance data are lacking. In the absence of high-quality epidemiological data on malaria distribution in Africa, climate information has long been used to develop malaria risk maps illustrating the climatic suitability boundaries for endemic transmission. However, experience to date has shown that it is difficult in terms of availability, timing and cost to obtain meteorological observations from national meteorological services in Africa. National health services generally find the costs of purchasing these data prohibitive given their competing demands for resources across the spectrum of health service requirements. Some national health services have tried to overcome this access problem by using proxies derived from satellites, which tend to be available freely, in 'near-real-time' and therefore offer much promise for monitoring applications. This paper discusses the issues related to climate and health, reviews the current use of climate information for malaria endemic and epidemic surveillance, and presents examples of operational use of climate information for malaria control in Africa based on Geographical Information Systems and Remote Sensing.

  12. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

    Science.gov (United States)

    Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

    2016-01-01

    Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

  13. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

    Directory of Open Access Journals (Sweden)

    Hongchun Zhu

    Full Text Available Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

  14. ADVANCED EXTRACTION OF SPATIAL INFORMATION FROM HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    T. Pour

    2016-06-01

    Full Text Available In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  15. An Effective Approach to Biomedical Information Extraction with Limited Training Data

    CERN Document Server

    Jonnalagadda, Siddhartha

    2011-01-01

    Overall, the two main contributions of this work include the application of sentence simplification to association extraction as described above, and the use of distributional semantics for concept extraction. The proposed work on concept extraction amalgamates for the first time two diverse research areas -distributional semantics and information extraction. This approach renders all the advantages offered in other semi-supervised machine learning systems, and, unlike other proposed semi-supervised approaches, it can be used on top of different basic frameworks and algorithms. http://gradworks.umi.com/34/49/3449837.html

  16. Omnidirectional vision systems calibration, feature extraction and 3D information

    CERN Document Server

    Puig, Luis

    2013-01-01

    This work focuses on central catadioptric systems, from the early step of calibration to high-level tasks such as 3D information retrieval. The book opens with a thorough introduction to the sphere camera model, along with an analysis of the relation between this model and actual central catadioptric systems. Then, a new approach to calibrate any single-viewpoint catadioptric camera is described.  This is followed by an analysis of existing methods for calibrating central omnivision systems, and a detailed examination of hybrid two-view relations that combine images acquired with uncalibrated

  17. On the relevance of Gibson's affordance concept for geographical information science (GISc).

    Science.gov (United States)

    Jonietz, David; Timpf, Sabine

    2015-09-01

    J. J. Gibson's concept of affordances has provided a theoretical basis for various studies in geographical information science (GISc). This paper sets out to explain its popularity from a GISc perspective. Based on a short review of previous work, it will be argued that its main contributions to GISc are twofold, including an action-centered view of spatial entities and the notion of agent-environment mutuality. Using the practical example of pedestrian behavior simulation, new potentials for using and extending affordances are discussed.

  18. CONTEMPORARY APPROACHES OF COMPANY PERFORMANCE ANALYSIS BASED ON RELEVANT FINANCIAL INFORMATION

    OpenAIRE

    Sziki Klara; Kiss Melinda; Popa Dorina

    2012-01-01

    In this paper we chose to present two components of the financial statements: the profit and loss account and the cash flow statement. These summary documents and different indicators calculated based on them allow us to formulate assessments on the performance and profitability on various functions and levels of the company’s activity. This paper aims to support the hypothesis that the accounting information presented in the profit and loss account and in the cash flow statement is an appr...

  19. Data-Driven Information Extraction from Chinese Electronic Medical Records.

    Directory of Open Access Journals (Sweden)

    Dong Xu

    Full Text Available This study aims to propose a data-driven framework that takes unstructured free text narratives in Chinese Electronic Medical Records (EMRs as input and converts them into structured time-event-description triples, where the description is either an elaboration or an outcome of the medical event.Our framework uses a hybrid approach. It consists of constructing cross-domain core medical lexica, an unsupervised, iterative algorithm to accrue more accurate terms into the lexica, rules to address Chinese writing conventions and temporal descriptors, and a Support Vector Machine (SVM algorithm that innovatively utilizes Normalized Google Distance (NGD to estimate the correlation between medical events and their descriptions.The effectiveness of the framework was demonstrated with a dataset of 24,817 de-identified Chinese EMRs. The cross-domain medical lexica were capable of recognizing terms with an F1-score of 0.896. 98.5% of recorded medical events were linked to temporal descriptors. The NGD SVM description-event matching achieved an F1-score of 0.874. The end-to-end time-event-description extraction of our framework achieved an F1-score of 0.846.In terms of named entity recognition, the proposed framework outperforms state-of-the-art supervised learning algorithms (F1-score: 0.896 vs. 0.886. In event-description association, the NGD SVM is superior to SVM using only local context and semantic features (F1-score: 0.874 vs. 0.838.The framework is data-driven, weakly supervised, and robust against the variations and noises that tend to occur in a large corpus. It addresses Chinese medical writing conventions and variations in writing styles through patterns used for discovering new terms and rules for updating the lexica.

  20. Locating relevant patient information in electronic health record data using representations of clinical concepts and database structures.

    Science.gov (United States)

    Pan, Xuequn; Cimino, James J

    2014-01-01

    Clinicians and clinical researchers often seek information in electronic health records (EHRs) that are relevant to some concept of interest, such as a disease or finding. The heterogeneous nature of EHRs can complicate retrieval, risking incomplete results. We frame this problem as the presence of two gaps: 1) a gap between clinical concepts and their representations in EHR data and 2) a gap between data representations and their locations within EHR data structures. We bridge these gaps with a knowledge structure that comprises relationships among clinical concepts (including concepts of interest and concepts that may be instantiated in EHR data) and relationships between clinical concepts and the database structures. We make use of available knowledge resources to develop a reproducible, scalable process for creating a knowledge base that can support automated query expansion from a clinical concept to all relevant EHR data.

  1. Extraction of Left Ventricular Ejection Fraction Information from Various Types of Clinical Reports.

    Science.gov (United States)

    Kim, Youngjun; Garvin, Jennifer H; Goldstein, Mary K; Hwang, Tammy S; Redd, Andrew; Bolton, Dan; Heidenreich, Paul A; Meystre, Stéphane M

    2017-02-02

    Efforts to improve the treatment of congestive heart failure, a common and serious medical condition, include the use of quality measures to assess guideline-concordant care. The goal of this study is to identify left ventricular ejection fraction (LVEF) information from various types of clinical notes, and to then use this information for heart failure quality measurement. We analyzed the annotation differences between a new corpus of clinical notes from the Echocardiography, Radiology, and Text Integrated Utility package and other corpora annotated for natural language processing (NLP) research in the Department of Veterans Affairs. These reports contain varying degrees of structure. To examine whether existing LVEF extraction modules we developed in prior research improve the accuracy of LVEF information extraction from the new corpus, we created two sequence-tagging NLP modules trained with a new data set, with or without predictions from the existing LVEF extraction modules. We also conducted a set of experiments to examine the impact of training data size on information extraction accuracy. We found that less training data is needed when reports are highly structured, and that combining predictions from existing LVEF extraction modules improves information extraction when reports have less structured formats and a rich set of vocabulary.

  2. Abstract Information Extraction From Consumer's Comments On Internet Media

    Directory of Open Access Journals (Sweden)

    Kadriye Ergün

    2013-01-01

    Full Text Available In this study, a system developed to summarize by automatically evaluating comments about product with using text mining techniques will be described. The data has been primarily went through morphological analysis process, because they are texts written in natural language. Words and adjectives meaning positive or negative are determined. They show product features in texts. The tree structure is established according to Turkish grammar rules as subordinate and modified words are designated. The software which uses the depth-first search algorithm on the tree structure is developed. Data from result of software is stored in the SQL database. When any inquiry is made from these data depending on any property of product, numerical information which indicates the degree of satisfaction about this property is obtained.

  3. CONTEMPORARY APPROACHES OF COMPANY PERFORMANCE ANALYSIS BASED ON RELEVANT FINANCIAL INFORMATION

    Directory of Open Access Journals (Sweden)

    Sziki Klara

    2012-12-01

    Full Text Available In this paper we chose to present two components of the financial statements: the profit and loss account and the cash flow statement. These summary documents and different indicators calculated based on them allow us to formulate assessments on the performance and profitability on various functions and levels of the company’s activity. This paper aims to support the hypothesis that the accounting information presented in the profit and loss account and in the cash flow statement is an appropriate source for assessing company performance. The purpose of this research is to answer the question linked to the main hypothesis: Is it the profit and loss statement or the cash flow account that reflects better the performance of a business? Based on the literature of specialty studied we tried a conceptual, analytical and practical approach of the term performance, overviewing some terminological acceptations of the term performance as well as the main indicators of performance analysis on the basis of the profit and loss account and of the cash flow statement: aggregated indicators, also known as intermediary balances of administration, economic rate of return, rate of financial profitability, rate of return through cash flows, operating cash flow rate, rate of generating operating cash out of gross operating result. At the same time we had a comparative approach of the profit and loss account and cash flow statement, outlining the main advantages and disadvantages of these documents. In order to demonstrate the above theoretical assessments, we chose to analyze these indicators based on information from the financial statements of SC Sinteza SA, a company in Bihor county, listed on the Bucharest Stock Exchange.

  4. A study on the relevance and influence of the existing regulation and risk informed/performance based regulation

    Energy Technology Data Exchange (ETDEWEB)

    Cheong, B. J.; Koh, Y. J.; Kim, H. S.; Koh, S. H.; Kang, D. H.; Kang, T. W. [Cheju National Univ., Jeju (Korea, Republic of)

    2004-02-15

    The goal of this study is to estimate the Relevance and Influence of the Existing Regulation and the RI-PBR to the institutionalization of the regulatory system. This study reviews the current regulatory system and the status of the RI-PBR implementation of the US NRC and Korea based upon SECY Papers, Risk Informed Regulation Implementation Plan (RIRIP) of the US NRC and other domestic studies. Also the recent trends of the individual technologies regarding the RI-PBR and RIA are summarized.

  5. Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

    Science.gov (United States)

    Poux, F.; Neuville, R.; Billen, R.

    2017-08-01

    Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

  6. The European Charter for Regional or Minority Languages: Still Relevant in the Information Age?

    Directory of Open Access Journals (Sweden)

    Sarah McMonagle

    2012-12-01

    Full Text Available The impact of new information and communication technologies on European societies could not have been foreseen at the time the European Charter for Regional or Minority Languages (ECRML was adopted two decades ago. Although the text of the ECRML contains no reference to such technologies, they clearly have a role in the context of linguistic communication, given their current social ubiquity. The measures outlined in the ECRML concerning, inter alia, media and cultural facilities, are precisely those being affected by the new media landscape. We can therefore be certain that the internet has some sort of impact on regional and minority languages in Europe, yet detailed assessments of this impact at the policy level are lacking. This article seeks to uncover the extent to which the Committee of Experts of the ECRML assesses the impact of the internet on those languages that have been selected by state parties for protection and promotion under the provisions of the ECRML. Findings show that references to the internet have increased in the reports of the Committee of Experts since monitoring began. However, the role of new technologies in inhibiting or facilitating regional and minority languages is seldom evaluated.

  7. STUDY ON EXTRACTING METHODS OF BURIED GEOLOGICAL INFORMATION IN HUAIBEI COAL FIELD

    Institute of Scientific and Technical Information of China (English)

    王四龙; 赵学军; 凌贻棕; 刘玉荣; 宁书年; 侯德文

    1999-01-01

    It is discussed features and the producing mechanism of buried geological information in geological, geophysical and remote sensing data in Huaibei coal field, and studied the methods extracting buried tectonic and igneous rock information from various geological data using digital image processing techniques.

  8. Analysis of Automated Modern Web Crawling and Testing Tools and Their Possible Employment for Information Extraction

    Directory of Open Access Journals (Sweden)

    Tomas Grigalis

    2012-04-01

    Full Text Available World Wide Web has become an enormously big repository of data. Extracting, integrating and reusing this kind of data has a wide range of applications, including meta-searching, comparison shopping, business intelligence tools and security analysis of information in websites. However, reaching information in modern WEB 2.0 web pages, where HTML tree is often dynamically modified by various JavaScript codes, new data are added by asynchronous requests to the web server and elements are positioned with the help of cascading style sheets, is a difficult task. The article reviews automated web testing tools for information extraction tasks.Article in Lithuanian

  9. Weak characteristic information extraction from early fault of wind turbine generator gearbox

    Science.gov (United States)

    Xu, Xiaoli; Liu, Xiuli

    2017-04-01

    Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.

  10. Weak characteristic information extraction from early fault of wind turbine generator gearbox

    Science.gov (United States)

    Xu, Xiaoli; Liu, Xiuli

    2017-09-01

    Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.

  11. The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

    Science.gov (United States)

    Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

    2016-09-01

    With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

  12. Improving Nigerian health policymakers' capacity to access and utilize policy relevant evidence: outcome of information and communication technology training workshop.

    Science.gov (United States)

    Uneke, Chigozie Jesse; Ezeoha, Abel Ebeh; Uro-Chukwu, Henry; Ezeonu, Chinonyelum Thecla; Ogbu, Ogbonnaya; Onwe, Friday; Edoga, Chima

    2015-01-01

    Information and communication technology (ICT) tools are known to facilitate communication and processing of information and sharing of knowledge by electronic means. In Nigeria, the lack of adequate capacity on the use of ICT by health sector policymakers constitutes a major impediment to the uptake of research evidence into the policymaking process. The objective of this study was to improve the knowledge and capacity of policymakers to access and utilize policy relevant evidence. A modified "before and after" intervention study design was used in which outcomes were measured on the target participants both before the intervention is implemented and after. A 4-point likert scale according to the degree of adequacy; 1 = grossly inadequate, 4 = very adequate was employed. This study was conducted in Ebonyi State, south-eastern Nigeria and the participants were career health policy makers. A two-day intensive ICT training workshop was organized for policymakers who had 52 participants in attendance. Topics covered included: (i). intersectoral partnership/collaboration; (ii). Engaging ICT in evidence-informed policy making; use of ICT for evidence synthesis; (iv) capacity development on the use of computer, internet and other ICT. The pre-workshop mean of knowledge and capacity for use of ICT ranged from 2.19-3.05, while the post-workshop mean ranged from 2.67-3.67 on 4-point scale. The percentage increase in mean of knowledge and capacity at the end of the workshop ranged from 8.3%-39.1%. Findings of this study suggest that policymakers' ICT competence relevant to evidence-informed policymaking can be enhanced through training workshop.

  13. The Technology of Extracting Content Information from Web Page Based on DOM Tree

    Science.gov (United States)

    Yuan, Dingrong; Mo, Zhuoying; Xie, Bing; Xie, Yangcai

    There are huge amounts of information on Web pages, which includes content information and other useless information, such as navigation, advertisement and flash of animation etc. Reducing the toils of Web users, we estabished a thechnique to extract the content information from web page. Fristly, we analyzed the semantic of web documents by V8 engine of Google and parsed the web document into DOM tree. And then, traversed the DOM tree, pruned the DOM tree in the light of the characteristic of Web page's edit language. Finally, we extracted the content information from Web page. Theoretics and experiments showed that the technique could simplify the web page, present the content information to web users and supply clean data for applicable area, such as retrieval, KDD and DM from web.

  14. What do professional forecasters' stock market expectations tell us about herding, information extraction and beauty contests?

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, M.; Schrimpf, A.

    2013-01-01

    We study how professional forecasters form equity market expectations based on a new micro-level dataset which includes rich cross-sectional information about individual characteristics. We focus on testing whether agents rely on the beliefs of others, i.e., consensus expectations, when forming t...... that neither information extraction to incorporate dispersed private information, nor herding for reputational reasons can fully explain these results, leaving Keynes' beauty contest argument as a potential candidate for explaining forecaster behavior....

  15. Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

    OpenAIRE

    Alguliyev, Rasim M.; Ramiz M. Aliguliyev; Irada Y. Alakbarova

    2016-01-01

    Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we ...

  16. Extracting information from the data flood of new solar telescopes. Brainstorming

    CERN Document Server

    Ramos, A Asensio

    2012-01-01

    Extracting magnetic and thermodynamic information from spectropolarimetric observations is a difficult and time consuming task. The amount of science-ready data that will be generated by the new family of large solar telescopes is so large that we will be forced to modify the present approach to inference. In this contribution, I propose several possible ways that might be useful for extracting the thermodynamic and magnetic properties of solar plasmas from such observations quickly.

  17. Extracting Information from the Data Flood of New Solar Telescopes: Brainstorming

    Science.gov (United States)

    Asensio Ramos, A.

    2012-12-01

    Extracting magnetic and thermodynamic information from spectropolarimetric observations is a difficult and time consuming task. The amount of science-ready data that will be generated by the new family of large solar telescopes is so large that we will be forced to modify the present approach to inference. In this contribution, I propose several possible ways that might be useful for extracting the thermodynamic and magnetic properties of solar plasmas from such observations quickly.

  18. Perceived Relevance of Educative Information on Public (Skin Health: Results of a Representative, Population-Based Telephone Survey

    Directory of Open Access Journals (Sweden)

    Daniela Haluza

    2015-11-01

    Full Text Available Individual skin health attitudes are influenced by various factors, including public education campaigns, mass media, family, and friends. Evidence-based, educative information materials assist communication and decision-making in doctor-patient interactions. The present study aims at assessing the prevailing use of skin health information material and sources and their impact on skin health knowledge, motives to tan, and sun protection. We conducted a questionnaire survey among a representative sample of Austrian residents. Print media and television were perceived as the two most relevant sources for skin health information, whereas the source physician was ranked third. Picking the information source physician increased participants’ skin health knowledge (p = 0.025 and sun-protective behavior (p < 0.001. The study results highlight the demand for targeted health messages to attain lifestyle changes towards photo-protective habits. Providing resources that encourage pro-active counseling in every-day doctor-patient communication could increase skin health knowledge and sun-protective behavior, and thus, curb the rise in skin cancer incidence rates.

  19. Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

    Science.gov (United States)

    Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

    2016-09-01

    Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

  20. Extracting important information from Chinese Operation Notes with natural language processing methods.

    Science.gov (United States)

    Wang, Hui; Zhang, Weide; Zeng, Qiang; Li, Zuofeng; Feng, Kaiyan; Liu, Lei

    2014-04-01

    Extracting information from unstructured clinical narratives is valuable for many clinical applications. Although natural Language Processing (NLP) methods have been profoundly studied in electronic medical records (EMR), few studies have explored NLP in extracting information from Chinese clinical narratives. In this study, we report the development and evaluation of extracting tumor-related information from operation notes of hepatic carcinomas which were written in Chinese. Using 86 operation notes manually annotated by physicians as the training set, we explored both rule-based and supervised machine-learning approaches. Evaluating on unseen 29 operation notes, our best approach yielded 69.6% in precision, 58.3% in recall and 63.5% F-score. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. The Colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information

    Directory of Open Access Journals (Sweden)

    Proutski Vitali

    2010-12-01

    Full Text Available Abstract Background To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome. Methods DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information. Results The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance. Conclusions Analysis from our in vitro and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including IGF2BP2, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear

  2. Visualization and Analysis of Geology Word Vectors for Efficient Information Extraction

    Science.gov (United States)

    Floyd, J. S.

    2016-12-01

    allow one to extract information from hundreds of papers or more and find relationships in less time than it would take to read all of the papers. As machine learning tools become more commonly available, more and more scientists will be able to use and refine these tools for their individual needs.

  3. Extraction of Informative Blocks from Deep Web Page Using Similar Layout Feature

    OpenAIRE

    Zeng,Jun; Flanagan, Brendan; Hirokawa, Sachio

    2013-01-01

    Due to the explosive growth and popularity of the deep web, information extraction from deep web page has gained more and more attention. However, the HTML structure of web page has become more complicated, making it difficult to recognize target content by only analyzing the HTML source code. In this paper, we propose a method to extract the informative blocks from a deep web using the layout feature. We consider the visual rectangular region of an HTML element as a visual block in web page....

  4. Information extraction for legal knowledge representation – a review of approaches and trends

    Directory of Open Access Journals (Sweden)

    Denis Andrei de Araujo

    2014-11-01

    Full Text Available This work presents an introduction to Information Extraction systems and a survey of the known approaches of Information Extraction in the legal area. This work analyzes with particular attention the techniques that rely on the representation of legal knowledge as a means to achieve better performance, with emphasis on those techniques including ontologies and linguistic support. Some details of the systems implementations are presented, followed by an analysis of the positive and negative points of each approach, aiming to bring the reader a critical position regarding the solutions studied.

  5. Ultrasonic Signal Processing Algorithm for Crack Information Extraction on the Keyway of Turbine Rotor Disk

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hong Kyu; Seo, Won Chan; Park, Chan [Pukyong National University, Busan (Korea, Republic of); Lee, Jong O; Son, Young Ho [KIMM, Daejeon (Korea, Republic of)

    2009-10-15

    An ultrasonic signal processing algorithm was developed for extracting the information of cracks generated around the keyway of a turbine rotor disk. B-scan images were obtained by using keyway specimens and an ultrasonic scan system with x-y position controller. The B-scan images were used as input images for 2-Dimensional signal processing, and the algorithm was constructed with four processing stages of pre-processing, crack candidate region detection, crack region classification and crack information extraction. It is confirmed by experiments that the developed algorithm is effective for the quantitative evaluation of cracks generated around the keyway of turbine rotor disk

  6. Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

    Directory of Open Access Journals (Sweden)

    Peng Shao

    2014-08-01

    Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

  7. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

    Science.gov (United States)

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single

  8. [Mood-congruent effect in self-relevant information processing: a study using an autobiographical memory recall task].

    Science.gov (United States)

    Itoh, M

    2000-10-01

    The pattern of the mood-congruent effect in an autobiographical memory recall task was investigated. Each subject was randomly assigned to one of three experimental conditions: positive mood, negative mood (induced with music), and control groups (no specific mood). Subjects were then presented with a word at a time from a list of trait words, which were pleasant or unpleasant. They decided whether they could recall any of their autobiographical memories related to the word, and responded with "yes" or "no" buttons as rapidly and accurately as possible. After the task, they were given five minutes for an incidental free recall test. Results indicated that the mood-congruent effect was found regardless of whether there was an autobiographical memory related to the word or not in both positive and negative mood states. The effect of moods on self-relevant information processing was discussed.

  9. Information retrieval and terminology extraction in online resources for patients with diabetes.

    Science.gov (United States)

    Seljan, Sanja; Baretić, Maja; Kucis, Vlasta

    2014-06-01

    Terminology use, as a mean for information retrieval or document indexing, plays an important role in health literacy. Specific types of users, i.e. patients with diabetes need access to various online resources (on foreign and/or native language) searching for information on self-education of basic diabetic knowledge, on self-care activities regarding importance of dietetic food, medications, physical exercises and on self-management of insulin pumps. Automatic extraction of corpus-based terminology from online texts, manuals or professional papers, can help in building terminology lists or list of "browsing phrases" useful in information retrieval or in document indexing. Specific terminology lists represent an intermediate step between free text search and controlled vocabulary, between user's demands and existing online resources in native and foreign language. The research aiming to detect the role of terminology in online resources, is conducted on English and Croatian manuals and Croatian online texts, and divided into three interrelated parts: i) comparison of professional and popular terminology use ii) evaluation of automatic statistically-based terminology extraction on English and Croatian texts iii) comparison and evaluation of extracted terminology performed on English manual using statistical and hybrid approaches. Extracted terminology candidates are evaluated by comparison with three types of reference lists: list created by professional medical person, list of highly professional vocabulary contained in MeSH and list created by non-medical persons, made as intersection of 15 lists. Results report on use of popular and professional terminology in online diabetes resources, on evaluation of automatically extracted terminology candidates in English and Croatian texts and on comparison of statistical and hybrid extraction methods in English text. Evaluation of automatic and semi-automatic terminology extraction methods is performed by recall

  10. [An improved N-FINDR endmember extraction algorithm based on manifold learning and spatial information].

    Science.gov (United States)

    Tang, Xiao-yan; Gao, Kun; Ni, Guo-qiang; Zhu, Zhen-yu; Cheng, Hao-bo

    2013-09-01

    An improved N-FINDR endmember extraction algorithm by combining manifold learning and spatial information is presented under nonlinear mixing assumptions. Firstly, adaptive local tangent space alignment is adapted to seek potential intrinsic low-dimensional structures of hyperspectral high-diemensional data and reduce original data into a low-dimensional space. Secondly, spatial preprocessing is used by enhancing each pixel vector in spatially homogeneous areas, according to the continuity of spatial distribution of the materials. Finally, endmembers are extracted by looking for the largest simplex volume. The proposed method can increase the precision of endmember extraction by solving the nonlinearity of hyperspectral data and taking advantage of spatial information. Experimental results on simulated and real hyperspectral data demonstrate that the proposed approach outperformed the geodesic simplex volume maximization (GSVM), vertex component analysis (VCA) and spatial preprocessing N-FINDR method (SPPNFINDR).

  11. A method of building information extraction based on mathematical morphology and multiscale

    Science.gov (United States)

    Li, Jing-wen; Wang, Ke; Zhang, Zi-ping; Xue, Long-li; Yin, Shou-qiang; Zhou, Song

    2015-12-01

    In view of monitoring the changes of buildings on Earth's surface ,by analyzing the distribution characteristics of building in remote sensing image, combined with multi-scale in image segmentation and the advantages of mathematical morphology, this paper proposes a multi-scale combined with mathematical morphology of high resolution remote sensing image segmentation method, and uses the multiple fuzzy classification method and the shadow of auxiliary method to extract information building, With the comparison of k-means classification, and the traditional maximum likelihood classification method, the results of experiment object based on multi-scale combined with mathematical morphology of image segmentation and extraction method, can accurately extract the structure of the information is more clear classification data, provide the basis for the intelligent monitoring of earth data and theoretical support.

  12. Extraction and Network Sharing of Forest Vegetation Information based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Hannv

    2013-05-01

    Full Text Available The support vector machine (SVM is a new method of data mining, which can deal with regression problems (time series analysis, pattern recognition (classification, discriminant analysis and many other issues very well. In recent years, SVM has been widely used in computer classification and recognition of remote sensing images. This paper is based on Landsat TM image data, using a classification method which is based on support vector machine to extract the forest cover information of Dahuanggou tree farm of Changbai Mountain area, and compare with the conventional maximum likelihood classification. The results show that extraction accuracy of forest information based on support vector machine, Kappa values are 0.9810, 0.9716, 0.9753, which are exceeding the extraction accuracy of maximum likelihood method (MLC and Kappa value of 0.9634, the method has good maneuverability and practicality.

  13. Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies

    Science.gov (United States)

    Zheng, Shuai; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A

    2017-01-01

    Background Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Objective Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. Methods A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Results Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports—each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. Conclusions IDEAL-X adopts a unique online machine learning–based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. PMID:28487265

  14. Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies.

    Science.gov (United States)

    Zheng, Shuai; Lu, James J; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A; Wang, Fusheng

    2017-05-09

    Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports-each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. IDEAL-X adopts a unique online machine learning-based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable.

  15. A construction scheme of web page comment information extraction system based on frequent subtree mining

    Science.gov (United States)

    Zhang, Xiaowen; Chen, Bingfeng

    2017-08-01

    Based on the frequent sub-tree mining algorithm, this paper proposes a construction scheme of web page comment information extraction system based on frequent subtree mining, referred to as FSM system. The entire system architecture and the various modules to do a brief introduction, and then the core of the system to do a detailed description, and finally give the system prototype.

  16. An Information Extraction Core System for Real World German Text Processing

    CERN Document Server

    Neumann, G; Baur, J; Becker, M; Braun, C

    1997-01-01

    This paper describes SMES, an information extraction core system for real world German text processing. The basic design criterion of the system is of providing a set of basic powerful, robust, and efficient natural language components and generic linguistic knowledge sources which can easily be customized for processing different tasks in a flexible manner.

  17. User-centered evaluation of Arizona BioPathway: an information extraction, integration, and visualization system.

    Science.gov (United States)

    Quiñones, Karin D; Su, Hua; Marshall, Byron; Eggers, Shauna; Chen, Hsinchun

    2007-09-01

    Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This paper presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature-viewing method. Relation aggregation significantly contributes to knowledge-acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multiview, relation-based interface that supports user-controlled exploration of pathway information across multiple granularities.

  18. Information Extraction to Generate Visual Simulations of Car Accidents from Written Descriptions

    NARCIS (Netherlands)

    Nugues, P.; Dupuy, S.; Egges, A.

    2003-01-01

    This paper describes a system to create animated 3D scenes of car accidents from written reports. The text-to-scene conversion process consists of two stages. An information extraction module creates a tabular description of the accident and a visual simulator generates and animates the scene. We

  19. Information extraction with object based support vector machines and vegetation indices

    Science.gov (United States)

    Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

    2016-07-01

    Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

  20. Web信息抽取系统的设计%Design of Web Information Extraction System

    Institute of Scientific and Technical Information of China (English)

    刘斌; 张晓婧

    2013-01-01

    In order to obtain the scattered information hidden in Web pages,Web information extraction system design.The system first uses a modified HITS algorithm for topic selection information collection; then the Web page's HTML document structure of the data pre-processing; Finally,based on the XPath DOM tree generation algorithm to obtain the absolute path is an XPath node marked expression,and use the XPath language with XSLT technology to write extraction rules,resulting in a structured database or XML file,to achieve the positioning and Web information extraction.Extraction through a shopping site experiments show that the extraction system works well,can achieve similar batch extract Web page.%为了获取分散Web页面中隐含信息,设计了Web信息抽取系统.该系统首先使用一种改进的HITS主题精选算法进行信息采集;然后对Web页面的HTML结构进行文档的数据预处理;最后,基于DOM树的XPath绝对路径生成算法来获取被标注结点的XPath表达式,并使用XPath语言结合XSLT技术来编写抽取规则,从而得到结构化的数据库或XML文件,实现了Web信息的定位和抽取.通过一个购物网站的抽取实验证明,该系统的抽取效果良好,可以实现相似Web页面的批量抽取.

  1. A study on the relevance and influence of the existing regulation and risk informed/performance based regulation

    Energy Technology Data Exchange (ETDEWEB)

    Cheong, B. J.; Kang, J. M.; Kim, H. S.; Koh, S. H.; Kang, D. H.; Park, C. H. [Cheju Univ., Jeju (Korea, Republic of)

    2003-02-15

    The goal of this study is to estimate the relevance and Influence of the Existing Regulation and the RI-PBR to the institutionalization of the regulatory system. This study reviews the current regulatory system and the status of the RI-PBR implementation of the US NRC and Korea based upon SECY Papers, Risk Informed Regulation Implementation Plan (RIRIP) of the US NRC and other domestic studies. In order to investigate the perceptions, knowledge level, ground for the regulatory change, a survey was performed to Korean nuclear utilities, researchers and regulators on the perception on the RIR. The questionnaire was composed of 50 questions regarding personal details on work experience, level of education and specific field of work ; level of knowledge on the risk informed performance based regulation (RI-PBR); the perception of the current regulation, the effectiveness, level of procedure, flexibility, dependency on the regulator and personal view, and the perception of the RI-PBR such as flexibility of regulation, introduction time and the effect of RI-PBR, safety improvement, public perception, parts of the existing regulatory system that should be changed, etc. 515 answered from all sectors of the nuclear field; utilities, engineering companies, research institutes, and regulatory bodies.

  2. Information Extraction for System-Software Safety Analysis: Calendar Year 2008 Year-End Report

    Science.gov (United States)

    Malin, Jane T.

    2009-01-01

    This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

  3. A Framework For Extracting Information From Web Using VTD-XML‘s XPath

    Directory of Open Access Journals (Sweden)

    C. Subhashini

    2012-03-01

    Full Text Available The exponential growth of WWW (World Wide Web is the cause for vast pool of information as well as several challenges posed by it, such as extracting potentially useful and unknown information from WWW. Many websites are built with HTML, because of its unstructured layout, it is difficult to obtain effective and precise data from web using HTML. The advent of XML (Extensible Markup Language proposes a better solution to extract useful knowledge from WWW. Web Data Extraction based on XML Technology solves this problem because XML is a general purpose specification for exchanging data over the Web. In this paper, a framework is suggested to extract the data from the web.Here the semi-structured data in the web page is transformed into well-structured data using standard XML technologies and the new parsing technique called extended VTD-XML (Virtual Token Descriptorfor XML along with Xpath implementation has been used to extract data from the well-structured XML document.

  4. Framework for automatic information extraction from research papers on nanocrystal devices

    Directory of Open Access Journals (Sweden)

    Thaer M. Dieb

    2015-09-01

    Full Text Available To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called “ NaDev” (Nanocrystal Device Development for this purpose. We also proposed an automatic information extraction system called “NaDevEx” (Nanocrystal Device Automatic Information Extraction Framework. NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms, the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material. However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39–73%; however, precision is better (75–97%. The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for

  5. Framework for automatic information extraction from research papers on nanocrystal devices.

    Science.gov (United States)

    Dieb, Thaer M; Yoshioka, Masaharu; Hara, Shinjiro; Newton, Marcus C

    2015-01-01

    To support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called " NaDev" (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called "NaDevEx" (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39-73%); however, precision is better (75-97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for characterization papers

  6. Clinic expert information extraction based on domain model and block importance model.

    Science.gov (United States)

    Zhang, Yuanpeng; Wang, Li; Qian, Danmin; Geng, Xingyun; Yao, Dengfu; Dong, Jiancheng

    2015-11-01

    To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method.

  7. Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2016-03-01

    Full Text Available Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we create social network of wiki-users. For clustering of the conflict articles a hybrid weighted fuzzy-c-means method is proposed.

  8. Extraction of spatial information from remotely sensed image data - an example: gloria sidescan sonar images

    Science.gov (United States)

    Chavez, Pat S.; Gardner, James V.

    1994-01-01

    A method to extract spatial amplitude and variability information from remotely sensed digital imaging data is presented. High Pass Filters (HPFs) are used to compute both a Spatial Amplitude Image/Index (SAI) and Spatial Variability Image/Index (SVI) at the local, intermediate, and regional scales. Used as input to principal component analysis and automatic clustering classification, the results indicate that spatial information at scales other than local is useful in the analysis of remotely sensed data. The resultant multi-spatial data set allows the user to study and analyze an image based more on the complete spatial characteristics of an image than only local textural information.

  9. Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

    Directory of Open Access Journals (Sweden)

    Lishuang Li

    Full Text Available Protein-Protein Interaction (PPI extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH. We evaluate our method with Support Vector Machine (SVM and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

  10. Orchard spatial information extraction from SPOT-5 image based on CART model

    Science.gov (United States)

    Li, Deyi; Zhang, Shuwen

    2009-07-01

    Orchard is an important agricultural industry and typical land use type in Shandong peninsula of China. This article focused on the automatic information extraction of orchard using SPOT-5 image. After analyzing every object's spectrum, we proposed a CART model based on sub-region and hierarchy theory by exploring spectrum, texture and topography attributes. The whole area was divided into coastal plain region and hill region based on SRTM data and extracted respectively. The accuracy reached to 86.40%, which was much higher than supervised classification method.

  11. Extracting directed information flow networks: an application to genetics and semantics

    CERN Document Server

    Masucci, A P; Hernández-García, E; Kalampokis, A

    2010-01-01

    We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two applications: first extracting the network of genetic flow between the meadows of the seagrass Poseidonia Oceanica, where the meadow elements are specified by sets of microsatellite markers, then we extract the semantic flow network from a set of Wikipedia pages, showing the semantic channels between different areas of knowledge.

  12. A theoretical extraction scheme of transport information based on exclusion models

    Institute of Scientific and Technical Information of China (English)

    Chen Hua; Du Lei; Qu Cheng-Li; Li Wei-Hua; He Liang; Chen Wen-Hao; Sun Peng

    2010-01-01

    In order to explore how to extract more transport information from current fluctuation, a theoretical extraction scheme is presented in a single barrier structure based on exclusion models, which include counter-flows model and tunnel model. The first four cumulants of these two exclusion models are computed in a single barrier structure, and their characteristics are obtained. A scheme with the help of the first three cumulants is devised to check a transport process to follow the counter-flows model, the tunnel model or neither of them. Time series generated by Monte Carlo techniques is adopted to validate the abstraction procedure, and the result is reasonable.

  13. Breast cancer and quality of life: medical information extraction from health forums.

    Science.gov (United States)

    Opitz, Thomas; Aze, Jérome; Bringay, Sandra; Joutard, Cyrille; Lavergne, Christian; Mollevi, Caroline

    2014-01-01

    Internet health forums are a rich textual resource with content generated through free exchanges among patients and, in certain cases, health professionals. We tackle the problem of retrieving clinically relevant information from such forums, with relevant topics being defined from clinical auto-questionnaires. Texts in forums are largely unstructured and noisy, calling for adapted preprocessing and query methods. We minimize the number of false negatives in queries by using a synonym tool to achieve query expansion of initial topic keywords. To avoid false positives, we propose a new measure based on a statistical comparison of frequent co-occurrences in a large reference corpus (Web) to keep only relevant expansions. Our work is motivated by a study of breast cancer patients' health-related quality of life (QoL). We consider topics defined from a breast-cancer specific QoL-questionnaire. We quantify and structure occurrences in posts of a specialized French forum and outline important future developments.

  14. 3D local feature BKD to extract road information from mobile laser scanning point clouds

    Science.gov (United States)

    Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

    2017-08-01

    Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

  15. Extraction of palaeochannei information from remote sensing imagery in the east of Chaohu Lake, China

    Institute of Scientific and Technical Information of China (English)

    Xinyuan WANG; Zhenya GUO; Li WU; Cheng ZHU; Hui HE

    2012-01-01

    Palaeochannels are deposits of unconsolidated sediments or semi-consolidated sedimentary rocks deposited in ancient,currently inactive fiver and stream channel systems.It is distinct from the overbank deposits of currently active river channels,including ephemeral water courses which do not regularly flow.We have introduced a spectral characteristics-based palaeochannel information extraction model from SPOT-5 imagery with special time phase,which has been built by virtue of an analysis of remote sensing mechanism and spectral characteristics of the palaeochannel,combined with its distinction from the spatial distribution and spectral features of currently active river channels,also with the establishment of remote sensing judging features of the palaeochannel in remote sensing image.This model follows the process of supervised classification → farmland masking and primary component analysis → underground palaeochannel information extractioninformation combination → palaeochannel system image.The Zhegao River Valley in the east of Chaohu Lake was selected as a study area,and SPOT-5 imagery was used as a source of data.The result was satisfactory when this method has been successfully applied to extract the palaeochannel information,which can provide good reference for regional remote sensing archeology and neotectonic research.However,the applicability of this method needs to be tested further in other areas as the spatial characteristics and spectral response of palaeochannel might be different.

  16. A study of extraction of petal region on flower picture using HSV color information

    Science.gov (United States)

    Yanagihara, Yoshio; Nakayama, Ryo

    2014-01-01

    It is one of useful and interesting applications to discriminate the kind of the flower or recognize the name of the flower, as example of retrieving flower database. As its contour line of the petal region of flower is useful for such problems, it is important to extract the precise region of the petal of a flower picture. In this paper, the method which extracts petal regions on a flower picture using HSV color information is proposed, such to discriminate the kind of the flower. The experiments show that the proposed method can extract petal regions at the success rate of about 90%, which is thought to be satisfied. In detail, the success rates of one-colored flower, plural-colored flower, and white flower are about 98%, 85%, and 83%, respectively.

  17. Web Page Information Extraction Technology%网页信息提取技术

    Institute of Scientific and Technical Information of China (English)

    邵振凯

    2013-01-01

    With the rapid development of the Internet,the amount of information in the Web page has become very large,how to quickly and efficiently search and find valuable information has become an important aspect of Web research. In this regard a tag extraction meth-od is proposed. Optimize the Web page into good HTML format documents with JTidy,and resolve to a DOM tree. Then use tag extrac-tion approach to extract the tags contain the text message content from DOM tree,remove the tags used to control the Web interaction and display,and use the method based on the punctuation information extraction method to remove the copyright notice and other informa-tion. The results on a number of different sites extraction show that the tags extraction methods not only have a great generality but also can accurately extract site theme.%随着互联网的快速发展,Web页面上的信息量已变得非常巨大,面对网页上海量的信息资源,如何快速有效地检索及发现有价值的信息已成为Web研究的一个重要方面。对此提出了一种标签提取方法。利用JTidy将网页优化为格式良好的HTML文档并解析为DOM树,然后用标签提取方法对该DOM树中包含有文本信息内容的叶子节点标签进行提取,把用于控制网页交互性和显示的标签删除掉,并运用基于标点符号的信息提取方法去除版权说明等信息。对不同网站的网页进行抽取实验,结果表明标签提取方法不但通用性强,而且能够准确地提取网页的主题信息。

  18. Multilevel spatial semantic model for urban house information extraction automatically from QuickBird imagery

    Science.gov (United States)

    Guan, Li; Wang, Ping; Liu, Xiangnan

    2006-10-01

    Based on the introduction to the characters and constructing flow of space semantic model, the feature space and context of house information in high resolution remote sensing image are analyzed, and the house semantic network model of Quick Bird image is also constructed. Furthermore, the accuracy and practicability of space semantic model are checked up through extracting house information automatically from Quick Bird image after extracting candidate semantic nodes to the image by taking advantage of grey division method, window threshold value method and Hough transformation. Sample result indicates that its type coherence, shape coherence and area coherence are 96.75%, 89.5 % and 88 % respectively. Thereinto the effect of the extraction of the houses with rectangular roof is the best and that with herringbone and the polygonal roofs is just ideal. However, the effect of the extraction of the houses with round roof is not satisfied and thus they need the further perfection to the semantic model to make them own higher applied value.

  19. Extraction of Remote Sensing Information Ofbanana Under Support of 3S Technology Inguangxi Province

    Science.gov (United States)

    Yang, Xin; Sun, Han; Tan, Zongkun; Ding, Meihua

    This paper presents an automatic approach to planting areas extraction for mixed vegetation and hilly region, more cloud using moderate spatial resolution and high temporal resolution MODIS data around Guangxi province, south of China. According to banana growth lasting more 9 to 11 months, and the areas are reduced during crush season, the Maximum likelihood was used to extract the information of banana planting and their spatial distribution through the calculation of multiple-phase MODIS-NDVI in Guangxi and stylebook training regions of banana of being selected by GPS. Compared with the large and little regions of banana planting in monitoring image and the investigation of on the spot with GPS, the resolute shows that the banana planting information in remote sensing image are true. In this research, multiple-phase MODIS data were received during banana main growing season and preprocessed; NDVI temporal profiles of banana were generated;models for planting areas extraction were developed based on the analysis of temporal NDVI curves; and spatial distribution map of planting areas of banana in Guangxi in 2006 were created. The study suggeststhat it is possible to extract planting areas automatically from MODIS data for large areas.

  20. An Useful Information Extraction using Image Mining Techniques from Remotely Sensed Image (RSI

    Directory of Open Access Journals (Sweden)

    Dr. C. Jothi Venkateswaran,

    2010-11-01

    Full Text Available Information extraction using mining techniques from remote sensing image (RSI is rapidly gaining attention among researchers and decision makers because of its potential in application oriented studies. Knowledge discovery from image poses many interesting challenges such as preprocessing the image data set, training the data and discovering useful image patterns applicable to many newapplication frontiers. In the image rich domain of RSI, image mining implies the synergy of data mining and image processing technology. Such culmination of techniques renders a valuable tool in information extraction. Also, this encompasses the problem of handling a larger data base of varied image data formats representing various levels ofinformation such as pixel, local and regional. In the present paper, various preprocessing corrections and techniques of image mining are discussed.

  1. Information Problem Solving: Analysis of a Complex Cognitive Skill

    NARCIS (Netherlands)

    S. Brand-Gruwel; I. Wopereis; Y. Vermetten

    2004-01-01

    textabstractIn (higher) education students are often faced with information problems: tasks or assignments which require the student to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a

  2. Information Problem Solving: Analysis of a Complex Cognitive Skill

    NARCIS (Netherlands)

    S. Brand-Gruwel; I. Wopereis; Y. Vermetten

    2004-01-01

    textabstractIn (higher) education students are often faced with information problems: tasks or assignments which require the student to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a

  3. Information extraction and transmission techniques for spaceborne synthetic aperture radar images

    Science.gov (United States)

    Frost, V. S.; Yurovsky, L.; Watson, E.; Townsend, K.; Gardner, S.; Boberg, D.; Watson, J.; Minden, G. J.; Shanmugan, K. S.

    1984-01-01

    Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.

  4. An Useful Information Extraction using Image Mining Techniques from Remotely Sensed Image (RSI)

    OpenAIRE

    Dr. C. Jothi Venkateswaran,; Murugan, S.; Dr. N. Radhakrishnan

    2010-01-01

    Information extraction using mining techniques from remote sensing image (RSI) is rapidly gaining attention among researchers and decision makers because of its potential in application oriented studies. Knowledge discovery from image poses many interesting challenges such as preprocessing the image data set, training the data and discovering useful image patterns applicable to many newapplication frontiers. In the image rich domain of RSI, image mining implies the synergy of data mining and ...

  5. Monadic datalog and the expressive power of languages for Web information extraction

    OpenAIRE

    Gottlob, Georg; Koch, Christoph

    2004-01-01

    Research on information extraction from Web pages (wrapping) has seen much activity recently (particularly systems implementations), but little work has been done on formally studying the expressiveness of the formalisms proposed or on the theoretical foundations of wrapping. In this paper, we first study monadic datalog over trees as a wrapping language. We show that this simple language is equivalent to monadic second order logic (MSO) in its ability to specify wrappers. We believe that MSO...

  6. Road Extraction from High-resolution Remote Sensing Images Based on Multiple Information Fusion

    Directory of Open Access Journals (Sweden)

    LI Xiao-feng

    2016-02-01

    Full Text Available Road extraction from high-resolution remote sensing images has been considered to be a significant but very difficult task.Especially the spectrum of some buildings is similar with that of roads,which makes the surfaces being connect with each other after classification and difficult to be distinguished.Based on the cooperation between road surfaces and edges,this paper presents an approach to purify roads from high-resolution remote sensing images.Firstly,we try to improve the extraction accuracy of road surfaces and edges respectively.The logic cooperation between these two binary images is used to separate road and non-road objects.Then the road objects are confirmed by the cooperation between surfaces and edges.And the effective shape indices(e.g.polar moment of inertia and narrow extent index are applied to eliminate non-road objects.So the road information is refined.The experiments indicate that the proposed approach is efficient for eliminating non-road information and extracting road information from high-resolution remote sensing image.

  7. Feature extraction and learning using context cue and Rényi entropy based mutual information

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2015-01-01

    Feature extraction and learning play a critical role for visual perception tasks. We focus on improving the robustness of the kernel descriptors (KDES) by embedding context cues and further learning a compact and discriminative feature codebook for feature reduction using Rényi entropy based mutual...... improving the robustness of CKD. For feature learning and reduction, we propose a novel codebook learning method, based on a Rényi quadratic entropy based mutual information measure called Cauchy-Schwarz Quadratic Mutual Information (CSQMI), to learn a compact and discriminative CKD codebook. Projecting...

  8. Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2015-11-01

    Full Text Available Prognostics is necessary to ensure the reliability and safety of lithium-ion batteries for hybrid electric vehicles or satellites. This process can be achieved by capacity estimation, which is a direct fading indicator for assessing the state of health of a battery. However, the capacity of a lithium-ion battery onboard is difficult to monitor. This paper presents a data-driven approach for online capacity estimation. First, six novel features are extracted from cyclic charge/discharge cycles and used as indirect health indicators. An adaptive multi-kernel relevance machine (MKRVM based on accelerated particle swarm optimization algorithm is used to determine the optimal parameters of MKRVM and characterize the relationship between extracted features and battery capacity. The overall estimation process comprises offline and online stages. A supervised learning step in the offline stage is established for model verification to ensure the generalizability of MKRVM for online application. Cross-validation is further conducted to validate the performance of the proposed model. Experiment and comparison results show the effectiveness, accuracy, efficiency, and robustness of the proposed approach for online capacity estimation of lithium-ion batteries.

  9. BioDARA: Data Summarization Approach to Extracting Bio-Medical Structuring Information

    Directory of Open Access Journals (Sweden)

    Chung S. Kheau

    2011-01-01

    Full Text Available Problem statement: Due to the ever growing amount of biomedical datasets stored in multiple tables, Information Extraction (IE from these datasets is increasingly recognized as one of the crucial technologies in bioinformatics. However, for IE to be practically applicable, adaptability of a system is crucial, considering extremely diverse demands in biomedical IE application. One should be able to extract a set of hidden patterns from these biomedical datasets at low cost. Approach: In this study, a new method is proposed, called Bio-medical Data Aggregation for Relational Attributes (BioDARA, for automatic structuring information extraction for biomedical datasets. BioDARA summarizes biomedical data stored in multiple tables in order to facilitate data modeling efforts in a multi-relational setting. BioDARA has the advantages or capabilities to transform biomedical data stored in multiple tables or databases into a Vector Space model, summarize biomedical data using the Information Retrieval theory and finally extract frequent patterns that describe the characteristics of these biomedical datasets. Results: the results show that data summarization performed by DARA, can be beneficial in summarizing biomedical datasets in a complex multi-relational environment, in which biomedical datasets are stored in a multi-level of one-to-many relationships and also in the case of datasets stored in more than one one-to-many relationships with non-target tables. Conclusion: This study concludes that data summarization performed by BioDARA, can be beneficial in summarizing biomedical datasets in a complex multi-relational environment, in which biomedical datasets are stored in a multi-level of one-to-many relationships.

  10. EXTRACT

    DEFF Research Database (Denmark)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/....

  11. Information extraction and CT reconstruction of liver images based on diffraction enhanced imaging

    Institute of Scientific and Technical Information of China (English)

    Chunhong Hu; Tao Zhao; Lu Zhang; Hui Li; Xinyan Zhao; Shuqian Luo

    2009-01-01

    X-ray phase-contrast imaging (PCI) is a new emerging imaging technique that generates a high spatial resolution and high contrast of biological soft tissues compared to conventional radiography. Herein a biomedical application of diffraction enhanced imaging (DEI) is presented. As one of the PCI methods, DEI derives contrast from many different kinds of sample information, such as the sample's X-ray absorption, refraction gradient and ultra-small-angle X-ray scattering (USAXS) properties, and the sample information is expressed by three parametric images. Combined with computed tomography (CT), DEI-CT can produce 3D volumetric images of the sample and can be used for investigating micro-structures of biomedical samples. Our DEI experiments for fiver samples were implemented at the topog-raphy station of Beijing Synchrotron Radiation Facility (BSRF). The results show that by using our provided information extraction method and DEI-CT reconstruction approach, the obtained parametric images clearly display the inner structures of liver tissues and the morphology of blood vessels. Furthermore, the reconstructed 3D view of the fiver blood vessels exhibits the micro blood vessels whose minimum diameter is on the order of about tens of microns, much better than its conventional CT reconstruction at a millimeter resolution.In conclusion, both the information extraction method and DEI-CT have the potential for use in biomedical micro-structures analysis.

  12. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    Science.gov (United States)

    Wang, Huaqing; Chen, Peng

    2009-01-01

    This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

  13. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    Directory of Open Access Journals (Sweden)

    Huaqing Wang

    2009-04-01

    Full Text Available This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to.

  14. Choice reaching with a LEGO arm robot (CoRLEGO): The motor system guides visual attention to movement-relevant information.

    Science.gov (United States)

    Strauss, Soeren; Woodgate, Philip J W; Sami, Saber A; Heinke, Dietmar

    2015-12-01

    We present an extension of a neurobiologically inspired robotics model, termed CoRLEGO (Choice reaching with a LEGO arm robot). CoRLEGO models experimental evidence from choice reaching tasks (CRT). In a CRT participants are asked to rapidly reach and touch an item presented on the screen. These experiments show that non-target items can divert the reaching movement away from the ideal trajectory to the target item. This is seen as evidence attentional selection of reaching targets can leak into the motor system. Using competitive target selection and topological representations of motor parameters (dynamic neural fields) CoRLEGO is able to mimic this leakage effect. Furthermore if the reaching target is determined by its colour oddity (i.e. a green square among red squares or vice versa), the reaching trajectories become straighter with repetitions of the target colour (colour streaks). This colour priming effect can also be modelled with CoRLEGO. The paper also presents an extension of CoRLEGO. This extension mimics findings that transcranial direct current stimulation (tDCS) over the motor cortex modulates the colour priming effect (Woodgate et al., 2015). The results with the new CoRLEGO suggest that feedback connections from the motor system to the brain's attentional system (parietal cortex) guide visual attention to extract movement-relevant information (i.e. colour) from visual stimuli. This paper adds to growing evidence that there is a close interaction between the motor system and the attention system. This evidence contradicts the traditional conceptualization of the motor system as the endpoint of a serial chain of processing stages. At the end of the paper we discuss CoRLEGO's predictions and also lessons for neurobiologically inspired robotics emerging from this work.

  15. Bounds on the entropy generated when timing information is extracted from microscopic systems

    CERN Document Server

    Janzing, D; Janzing, Dominik; Beth, Thomas

    2003-01-01

    We consider Hamiltonian quantum systems with energy bandwidth \\Delta E and show that each measurement that determines the time up to an error \\Delta t generates at least the entropy (\\hbar/(\\Delta t \\Delta E))^2/2. Our result describes quantitatively to what extent all timing information is quantum information in systems with limited energy. It provides a lower bound on the dissipated energy when timing information of microscopic systems is converted to classical information. This is relevant for low power computation since it shows the amount of heat generated whenever a band limited signal controls a classical bit switch. Our result provides a general bound on the information-disturbance trade-off for von-Neumann measurements that distinguish states on the orbits of continuous unitary one-parameter groups with bounded spectrum. In contrast, information gain without disturbance is possible for some completely positive semi-groups. This shows that readout of timing information can be possible without entropy ...

  16. Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information

    Directory of Open Access Journals (Sweden)

    Curt H. Davis

    2005-08-01

    Full Text Available High-resolution satellite imagery provides an important new data source for building extraction. We demonstrate an integrated strategy for identifying buildings in 1-meter resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. First, a series of geodesic opening and closing operations are used to build a differential morphological profile (DMP that provides image structural information. Building hypotheses are generated and verified through shape analysis applied to the DMP. Second, shadows are extracted using the DMP to provide reliable contextual information to hypothesize position and size of adjacent buildings. Seed building rectangles are verified and grown on a finely segmented image. Next, bright buildings are extracted using spectral information. The extraction results from the different information sources are combined after independent extraction. Performance evaluation of the building extraction on an urban test site using IKONOS satellite imagery of the City of Columbia, Missouri, is reported. With the combination of structural, contextual, and spectral information, 72.7% of the building areas are extracted with a quality percentage 58.8%.

  17. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

    Directory of Open Access Journals (Sweden)

    Kun-Ching Wang

    2014-09-01

    Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.

  18. A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

    Science.gov (United States)

    Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

    2017-05-01

    Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction

    Directory of Open Access Journals (Sweden)

    Yong Zhu

    2015-01-01

    Full Text Available After summarizing the advantages and disadvantages of current integral methods, a novel vibration signal integral method based on feature information extraction was proposed. This method took full advantage of the self-adaptive filter characteristic and waveform correction feature of ensemble empirical mode decomposition in dealing with nonlinear and nonstationary signals. This research merged the superiorities of kurtosis, mean square error, energy, and singular value decomposition on signal feature extraction. The values of the four indexes aforementioned were combined into a feature vector. Then, the connotative characteristic components in vibration signal were accurately extracted by Euclidean distance search, and the desired integral signals were precisely reconstructed. With this method, the interference problem of invalid signal such as trend item and noise which plague traditional methods is commendably solved. The great cumulative error from the traditional time-domain integral is effectively overcome. Moreover, the large low-frequency error from the traditional frequency-domain integral is successfully avoided. Comparing with the traditional integral methods, this method is outstanding at removing noise and retaining useful feature information and shows higher accuracy and superiority.

  20. Note: Sound recovery from video using SVD-based information extraction.

    Science.gov (United States)

    Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Chang'an

    2016-08-01

    This note reports an efficient singular value decomposition (SVD)-based vibration extraction approach that recovers sound information in silent high-speed video. A high-speed camera of which frame rates are in the range of 2 kHz-10 kHz is applied to film the vibrating objects. Sub-images cut from video frames are transformed into column vectors and then reconstructed to a new matrix. The SVD of the new matrix produces orthonormal image bases (OIBs) and image projections onto specific OIB can be recovered as understandable acoustical signals. Standard frequencies of 256 Hz and 512 Hz tuning forks are extracted offline from their vibrating surfaces and a 3.35 s speech signal is recovered online from a piece of paper that is stimulated by sound waves within 1 min.

  1. Note: Sound recovery from video using SVD-based information extraction

    Science.gov (United States)

    Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Chang'an

    2016-08-01

    This note reports an efficient singular value decomposition (SVD)-based vibration extraction approach that recovers sound information in silent high-speed video. A high-speed camera of which frame rates are in the range of 2 kHz-10 kHz is applied to film the vibrating objects. Sub-images cut from video frames are transformed into column vectors and then reconstructed to a new matrix. The SVD of the new matrix produces orthonormal image bases (OIBs) and image projections onto specific OIB can be recovered as understandable acoustical signals. Standard frequencies of 256 Hz and 512 Hz tuning forks are extracted offline from their vibrating surfaces and a 3.35 s speech signal is recovered online from a piece of paper that is stimulated by sound waves within 1 min.

  2. National information service in mining, mineral processing and extractive metallurgy. [MINTEC

    Energy Technology Data Exchange (ETDEWEB)

    Romaniuk, A.S.; MacDonald, R.J.C.

    1979-03-01

    More than a dedade ago, CANMET management recognized the need to make better use of existing technological information in mining and extractive metallurgy, two fields basic to the economic well-being of Canada. There were at that time no indexes or files didicated to disseminating technical information for the many minerals mined and processed in Canada, including coal. CANMET, with the nation's largest research and library resources in the minerals field, was in a unique position to fill this need. Initial efforts were concentrated on building a mining file beginning with identification of world sources of published information, development of a special thesaurus of terms for language control and adoption of a manual indexing/retrieval system. By early 1973, this file held 8,300 references, with source, abstract and keywords given for each reference. In mid-1973, operations were computerized. Software for indexing and retrieval by batch mode was written by CANMET staff to utilize the hardware facilities of EMR's Computer Science Center. The resulting MINTEC file, one of the few files of technological information produced in Canada, is the basis for the national literature search service in mining offered by CANMET. Attention is now focussed on building a sister-file in extractive metallurgy using the system already developed. Published information sources have been identified and a thesaurus of terms is being compiled and tested. The software developed for CANMET's file-building operations has several features, including the selective dissemination of information and production from magnetic tape of photoready copy for publication, as in a bi-monthly abstracts journal.

  3. Exploring the information and communication technology competence and confidence of nursing students and their perception of its relevance to clinical practice.

    Science.gov (United States)

    Levett-Jones, Tracy; Kenny, Raelene; Van der Riet, Pamela; Hazelton, Michael; Kable, Ashley; Bourgeois, Sharon; Luxford, Yoni

    2009-08-01

    This paper profiles a study that explored nursing students' information and communication technology competence and confidence. It presents selected findings that focus on students' attitudes towards information and communication technology as an educational methodology and their perceptions of its relevance to clinical practice. Information and communication technology is integral to contemporary nursing practice. Development of these skills is important to ensure that graduates are 'work ready' and adequately prepared to practice in increasingly technological healthcare environments. This was a mixed methods study. Students (n=971) from three Australian universities were surveyed using an instrument designed specifically for the study, and 24 students participated in focus groups. The focus group data revealed that a number of students were resistant to the use of information and communication technology as an educational methodology and lacked the requisite skills and confidence to engage successfully with this educational approach. Survey results indicated that 26 per cent of students were unsure about the relevance of information and communication technology to clinical practice and only 50 per cent felt 'very confident' using a computer. While the importance of information and communication technology to student's learning and to their preparedness for practice has been established, it is evident that students' motivation is influenced by their level of confidence and competence, and their understanding of the relevance of information and communication technology to their future careers.

  4. Perioperative Temperature Measurement Considerations Relevant to Reporting Requirements for National Quality Programs Using Data From Anesthesia Information Management Systems.

    Science.gov (United States)

    Epstein, Richard H; Dexter, Franklin; Hofer, Ira S; Rodriguez, Luis I; Schwenk, Eric S; Maga, Joni M; Hindman, Bradley J

    2017-06-08

    Perioperative hypothermia may increase the incidences of wound infection, blood loss, transfusion, and cardiac morbidity. U.S. national quality programs for perioperative normothermia specify the presence of at least 1 "body temperature" ≥35.5°C during the interval from 30 minutes before to 15 minutes after the anesthesia end time. Using data from 4 academic hospitals, we evaluated timing and measurement considerations relevant to the current requirements to guide hospitals wishing to report perioperative temperature measures using electronic data sources. Anesthesia information management system databases from 4 hospitals were queried to obtain intraoperative temperatures and intervals to the anesthesia end time from discontinuation of temperature monitoring, end of surgery, and extubation. Inclusion criteria included age >16 years, use of a tracheal tube or supraglottic airway, and case duration ≥60 minutes. The end-of-case temperature was determined as the maximum intraoperative temperature recorded within 30 minutes before the anesthesia end time (ie, the temperature that would be used for reporting purposes). The fractions of cases with intervals >30 minutes between the last intraoperative temperature and the anesthesia end time were determined. Among the hospitals, averages (binned by quarters) of 34.5% to 59.5% of cases had intraoperative temperature monitoring discontinued >30 minutes before the anesthesia end time. Even if temperature measurement had been continued until extubation, averages of 5.9% to 20.8% of cases would have exceeded the allowed 30-minute window. Averages of 8.9% to 21.3% of cases had end-of-case intraoperative temperatures <35.5°C (ie, a quality measure failure). Because of timing considerations, a substantial fraction of cases would have been ineligible to use the end-of-case intraoperative temperature for national quality program reporting. Thus, retrieval of postanesthesia care unit temperatures would have been necessary. A

  5. Automated DICOM metadata and volumetric anatomical information extraction for radiation dosimetry

    Science.gov (United States)

    Papamichail, D.; Ploussi, A.; Kordolaimi, S.; Karavasilis, E.; Papadimitroulas, P.; Syrgiamiotis, V.; Efstathopoulos, E.

    2015-09-01

    Patient-specific dosimetry calculations based on simulation techniques have as a prerequisite the modeling of the modality system and the creation of voxelized phantoms. This procedure requires the knowledge of scanning parameters and patients’ information included in a DICOM file as well as image segmentation. However, the extraction of this information is complicated and time-consuming. The objective of this study was to develop a simple graphical user interface (GUI) to (i) automatically extract metadata from every slice image of a DICOM file in a single query and (ii) interactively specify the regions of interest (ROI) without explicit access to the radiology information system. The user-friendly application developed in Matlab environment. The user can select a series of DICOM files and manage their text and graphical data. The metadata are automatically formatted and presented to the user as a Microsoft Excel file. The volumetric maps are formed by interactively specifying the ROIs and by assigning a specific value in every ROI. The result is stored in DICOM format, for data and trend analysis. The developed GUI is easy, fast and and constitutes a very useful tool for individualized dosimetry. One of the future goals is to incorporate a remote access to a PACS server functionality.

  6. Information extraction approaches to unconventional data sources for "Injury Surveillance System": the case of newspapers clippings.

    Science.gov (United States)

    Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Rahim, Yousif; Gregori, Dario

    2012-04-01

    Injury Surveillance Systems based on traditional hospital records or clinical data have the advantage of being a well established, highly reliable source of information for making an active surveillance on specific injuries, like choking in children. However, they suffer the drawback of delays in making data available to the analysis, due to inefficiencies in data collection procedures. In this sense, the integration of clinical based registries with unconventional data sources like newspaper articles has the advantage of making the system more useful for early alerting. Usage of such sources is difficult since information is only available in the form of free natural-language documents rather than structured databases as required by traditional data mining techniques. Information Extraction (IE) addresses the problem of transforming a corpus of textual documents into a more structured database. In this paper, on a corpora of Italian newspapers articles related to choking in children due to ingestion/inhalation of foreign body we compared the performance of three IE algorithms- (a) a classical rule based system which requires a manual annotation of the rules; (ii) a rule based system which allows for the automatic building of rules; (b) a machine learning method based on Support Vector Machine. Although some useful indications are extracted from the newspaper clippings, this approach is at the time far from being routinely implemented for injury surveillance purposes.

  7. Extraction of depth information for 3D imaging using pixel aperture technique

    Science.gov (United States)

    Choi, Byoung-Soo; Bae, Myunghan; Kim, Sang-Hwan; Lee, Jimin; Oh, Chang-Woo; Chang, Seunghyuk; Park, JongHo; Lee, Sang-Jin; Shin, Jang-Kyoo

    2017-02-01

    A 3dimensional (3D) imaging is an important area which can be applied to face detection, gesture recognition, and 3D reconstruction. In this paper, extraction of depth information for 3D imaging using pixel aperture technique is presented. An active pixel sensor (APS) with in-pixel aperture has been developed for this purpose. In the conventional camera systems using a complementary metal-oxide-semiconductor (CMOS) image sensor, an aperture is located behind the camera lens. However, in our proposed camera system, the aperture implemented by metal layer of CMOS process is located on the White (W) pixel which means a pixel without any color filter on top of the pixel. 4 types of pixels including Red (R), Green (G), Blue (B), and White (W) pixels were used for pixel aperture technique. The RGB pixels produce a defocused image with blur, while W pixels produce a focused image. The focused image is used as a reference image to extract the depth information for 3D imaging. This image can be compared with the defocused image from RGB pixels. Therefore, depth information can be extracted by comparing defocused image with focused image using the depth from defocus (DFD) method. Size of the pixel for 4-tr APS is 2.8 μm × 2.8 μm and the pixel structure was designed and simulated based on 0.11 μm CMOS image sensor (CIS) process. Optical performances of the pixel aperture technique were evaluated using optical simulation with finite-difference time-domain (FDTD) method and electrical performances were evaluated using TCAD.

  8. Why relevance theory is relevant for lexicography

    DEFF Research Database (Denmark)

    Bothma, Theo; Tarp, Sven

    2014-01-01

    , socio-cognitive and affective relevance. It then shows, at the hand of examples, why relevance is important from a user perspective in the extra-lexicographical pre- and post-consultation phases and in the intra-lexicographical consultation phase. It defines an additional type of subjective relevance...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...

  9. Analysis on health information extracted from an urban professional population in Beijing

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tie-mei; ZHANG Yan; LIU Bin; JIA Hong-bo; LIU Yun-jie; ZHU Ling; LUO Sen-lin; HAN Yi-wen; ZHANG Yan; YANG Shu-wen; LIU An-nan; MA Lan-jun; ZHAO Yan-yan

    2011-01-01

    Background The assembled data from a population could provide information on health trends within the population.The aim of this research was to extract and know basic health information from an urban professional population in Beijing.Methods Data analysis was carried out in a population who underwent a routine medical check-up and aged >20 years,including 30 058 individuals.General information,data from physical examinations and blood samples were collected in the same method.The health status was separated into three groups by the criteria generated in this study,i.e.,people with common chronic diseases,people in a sub-clinic situation,and healthy people.The proportion of both common diseases suffered and health risk distribution of different age groups were also analyzed.Results The proportion of people with common chronic diseases,in the sub-clinic group and in the healthy group was 28.6%,67.8% and 3.6% respectively.There were significant differences in the health situation in different age groups.Hypertension was on the top of list of self-reported diseases.The proportion of chronic diseases increased significantly in people after 35 years of age.Meanwhile,the proportion of sub-clinic conditions was decreasing at the same rate.The complex risk factors to health in this population were metabolic disturbances (61.3%),risk for tumor (2.7%),abnormal results of morphological examination (8.2%) and abnormal results of lab tests of serum (27.8%).Conclusions Health information could be extracted from a complex data set from the heath check-ups of the general population.The information should be applied to support prevention and control chronic diseases as well as for directing intervention for patients with risk factors for disease.

  10. Red Tide Information Extraction Based on Multi-source Remote Sensing Data in Haizhou Bay

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment mon...

  11. The method of earthquake landslide information extraction with high-resolution remote sensing

    Science.gov (United States)

    Wu, Jian; Chen, Peng; Liu, Yaolin; Wang, Jing

    2014-05-01

    As a kind of secondary geological disaster caused by strong earthquake, the earthquake-induced landslide has drawn much attention in the world due to the severe hazard. The high-resolution remote sensing, as a new technology for investigation and monitoring, has been widely applied in landslide susceptibility and hazard mapping. The Ms 8.0 Wenchuan earthquake, occurred on 12 May 2008, caused many buildings collapse and half million people be injured. Meanwhile, damage caused by earthquake-induced landslides, collapse and debris flow became the major part of total losses. By analyzing the property of the Zipingpu landslide occurred in the Wenchuan earthquake, the present study advanced a quick-and-effective way for landslide extraction based on NDVI and slope information, and the results were validated with pixel-oriented and object-oriented methods. The main advantage of the idea lies in the fact that it doesn't need much professional knowledge and data such as crustal movement, geological structure, fractured zone, etc. and the researchers can provide the landslide monitoring information for earthquake relief as soon as possible. In pixel-oriented way, the NDVI-differential image as well as slope image was analyzed and segmented to extract the landslide information. When it comes to object-oriented method, the multi-scale segmentation algorithm was applied in order to build up three-layer hierarchy. The spectral, textural, shape, location and contextual information of individual object classes, and GLCM (Grey Level Concurrence Matrix homogeneity, shape index etc. were extracted and used to establish the fuzzy decision rule system of each layer for earthquake landslide extraction. Comparison of the results generated from the two methods, showed that the object-oriented method could successfully avoid the phenomenon of NDVI-differential bright noise caused by the spectral diversity of high-resolution remote sensing data and achieved better result with an overall

  12. Multi-Paradigm and Multi-Lingual Information Extraction as Support for Medical Web Labelling Authorities

    Directory of Open Access Journals (Sweden)

    Martin Labsky

    2010-10-01

    Full Text Available Until recently, quality labelling of medical web content has been a pre-dominantly manual activity. However, the advances in automated text processing opened the way to computerised support of this activity. The core enabling technology is information extraction (IE. However, the heterogeneity of websites offering medical content imposes particular requirements on the IE techniques to be applied. In the paper we discuss these requirements and describe a multi-paradigm approach to IE addressing them. Experiments on multi-lingual data are reported. The research has been carried out within the EU MedIEQ project.

  13. The information extraction of Gannan citrus orchard based on the GF-1 remote sensing image

    Science.gov (United States)

    Wang, S.; Chen, Y. L.

    2017-02-01

    The production of Gannan oranges is the largest in China, which occupied an important part in the world. The extraction of citrus orchard quickly and effectively has important significance for fruit pathogen defense, fruit production and industrial planning. The traditional spectra extraction method of citrus orchard based on pixel has a lower classification accuracy, difficult to avoid the “pepper phenomenon”. In the influence of noise, the phenomenon that different spectrums of objects have the same spectrum is graveness. Taking Xunwu County citrus fruit planting area of Ganzhou as the research object, aiming at the disadvantage of the lower accuracy of the traditional method based on image element classification method, a decision tree classification method based on object-oriented rule set is proposed. Firstly, multi-scale segmentation is performed on the GF-1 remote sensing image data of the study area. Subsequently the sample objects are selected for statistical analysis of spectral features and geometric features. Finally, combined with the concept of decision tree classification, a variety of empirical values of single band threshold, NDVI, band combination and object geometry characteristics are used hierarchically to execute the information extraction of the research area, and multi-scale segmentation and hierarchical decision tree classification is implemented. The classification results are verified with the confusion matrix, and the overall Kappa index is 87.91%.

  14. A Draft Conceptual Framework of Relevant Theories to Inform Future Rigorous Research on Student Service-Learning Outcomes

    Science.gov (United States)

    Whitley, Meredith A.

    2014-01-01

    While the quality and quantity of research on service-learning has increased considerably over the past 20 years, researchers as well as governmental and funding agencies have called for more rigor in service-learning research. One key variable in improving rigor is using relevant existing theories to improve the research. The purpose of this…

  15. The Relevance Voxel Machine (RVoxM): A Self-Tuning Bayesian Model for Informative Image-Based Prediction

    DEFF Research Database (Denmark)

    Sabuncu, Mert R.; Van Leemput, Koen

    2012-01-01

    This paper presents the relevance voxel machine (RVoxM), a dedicated Bayesian model for making predictions based on medical imaging data. In contrast to the generic machine learning algorithms that have often been used for this purpose, the method is designed to utilize a small number of spatially...

  16. 75 FR 20843 - Notice of Workshop To Discuss Policy-Relevant Science to Inform EPA's Integrated Plan for the...

    Science.gov (United States)

    2010-04-21

    ... regarding workshop registration or logistics to ICF staff at 919-293-1621 or EPA_Lead_Wksp@icfi.com , or... highlight key policy issues around which EPA would structure the Pb NAAQS review. In workshop discussions... workshop is to ensure that this review focuses on the key policy-relevant issues and considers the most...

  17. Foreground and Background Lexicons and Word Sense Disambiguation for Information Extraction

    CERN Document Server

    Kilgarriff, A

    1999-01-01

    Lexicon acquisition from machine-readable dictionaries and corpora is currently a dynamic field of research, yet it is often not clear how lexical information so acquired can be used, or how it relates to structured meaning representations. In this paper I look at this issue in relation to Information Extraction (hereafter IE), and one subtask for which both lexical and general knowledge are required, Word Sense Disambiguation (WSD). The analysis is based on the widely-used, but little-discussed distinction between an IE system's foreground lexicon, containing the domain's key terms which map onto the database fields of the output formalism, and the background lexicon, containing the remainder of the vocabulary. For the foreground lexicon, human lexicography is required. For the background lexicon, automatic acquisition is appropriate. For the foreground lexicon, WSD will occur as a by-product of finding a coherent semantic interpretation of the input. WSD techniques as discussed in recent literature are suit...

  18. Non-linear correlation of content and metadata information extracted from biomedical article datasets.

    Science.gov (United States)

    Theodosiou, Theodosios; Angelis, Lefteris; Vakali, Athena

    2008-02-01

    Biomedical literature databases constitute valuable repositories of up to date scientific knowledge. The development of efficient machine learning methods in order to facilitate the organization of these databases and the extraction of novel biomedical knowledge is becoming increasingly important. Several of these methods require the representation of the documents as vectors of variables forming large multivariate datasets. Since the amount of information contained in different datasets is voluminous, an open issue is to combine information gained from various sources to a concise new dataset, which will efficiently represent the corpus of documents. This paper investigates the use of the multivariate statistical approach, called Non-Linear Canonical Correlation Analysis (NLCCA), for exploiting the correlation among the variables of different document representations and describing the documents with only one new dataset. Experiments with document datasets represented by text words, Medical Subject Headings (MeSH) and Gene Ontology (GO) terms showed the effectiveness of NLCCA.

  19. Solution of Multiple——Point Statistics to Extracting Information from Remotely Sensed Imagery

    Institute of Scientific and Technical Information of China (English)

    Ge Yong; Bai Hexiang; Cheng Qiuming

    2008-01-01

    Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information.Therefore,there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery.In the current article,a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification.The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese YeHow River delta on August 8,1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier (MLC)

  20. Detailed design specification for the ALT Shuttle Information Extraction Subsystem (SIES)

    Science.gov (United States)

    Clouette, G. L.; Fitzpatrick, W. N.

    1976-01-01

    The approach and landing test (ALT) shuttle information extraction system (SIES) is described in terms of general requirements and system characteristics output products and processing options, output products and data sources, and system data flow. The ALT SIES is a data reduction system designed to satisfy certain data processing requirements for the ALT phase of the space shuttle program. The specific ALT SIES data processing requirements are stated in the data reduction complex approach and landing test data processing requirements. In general, ALT SIES must produce time correlated data products as a result of standardized data reduction or special purpose analytical processes. The main characteristics of ALT SIES are: (1) the system operates in a batch (non-interactive) mode; (2) the processing is table driven; (3) it is data base oriented; (4) it has simple operating procedures; and (5) it requires a minimum of run time information.

  1. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Iwano Koji

    2007-01-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  2. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Koji Iwano

    2007-03-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  3. Learning and Relevance in Information Retrieval: A Study in the Application of Exploration and User Knowledge to Enhance Performance

    Science.gov (United States)

    Hyman, Harvey

    2012-01-01

    This dissertation examines the impact of exploration and learning upon eDiscovery information retrieval; it is written in three parts. Part I contains foundational concepts and background on the topics of information retrieval and eDiscovery. This part informs the reader about the research frameworks, methodologies, data collection, and…

  4. In-vitro estimation of bioaccessibility of chlorinated organophosphate flame retardants in indoor dust by fasting and fed physiologically relevant extraction tests.

    Science.gov (United States)

    Quintana, José Benito; Rosende, María; Montes, Rosa; Rodríguez-Álvarez, Tania; Rodil, Rosario; Cela, Rafael; Miró, Manuel

    2017-02-15

    This paper reports the evaluation of in-vitro physiologically relevant extraction tests for ascertainment of the bioaccessible fractions of emerging flame retardants from indoor dust in the gastric and gastrointestinal compartments. Standardized bioaccessibility tests under both fasting (UBM-like test) and fed (FOREhST test) conditions simulating the macronutrient composition of an average child diet were harnessed for investigation of the oral bioaccessibility of chlorinated organophosphate esters, namely, tris(2-chloroethyl) phosphate (TCEP), tris(1-chloro-2-propyl) phosphate (TCPP) and tris(1,3-dichloro-2-propyl) phosphate (TDCP), in household and automobile cabin dust samples with varying concentration levels of contaminants. Minimal processing of the biomimetic extracts (only protein precipitation using acetonitrile) was proven feasible by analysis with liquid chromatography-mass spectrometric detection (LC-MS/MS). An inversely proportional relationship was identified between log Kow and oral bioaccessibility concentrations for TCEP, TCPP and TDCP in both dust samples with maximum bioaccessibility fractions for TCEP within the range of 50-103%. Non-bioaccessible fractions were determined by matrix-solid phase dispersion. Limits of quantification of LC-MS/MS in surrogate digestive fluids ranging from 0.4-0.8ng/mL suffice for determination of freely dissolved fractions of the two less hydrophobic species. Our results indicate that lipophilic food commodities used under fed-state gastrointestinal extraction conditions do not increase availability of TCEP, TCPP and TDCP in body fluids, and therefore conservative conditions in human health risk explorations for the target moderately polar flame retardants might be obtained with simplified tests under fasting conditions. This also holds true for the UBM/FOREhST bioaccessibility data for SRM 2585 (organic contaminants in house dust). Estimated average daily intake doses for toddlers incorporating oral

  5. [An object-based information extraction technology for dominant tree species group types].

    Science.gov (United States)

    Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

    2015-06-01

    Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

  6. Extracting Urban Ground Object Information from Images and LiDAR Data

    Science.gov (United States)

    Yi, Lina; Zhao, Xuesheng; Li, Luan; Zhang, Guifeng

    2016-06-01

    To deal with the problem of urban ground object information extraction, the paper proposes an object-oriented classification method using aerial image and LiDAR data. Firstly, we select the optimal segmentation scales of different ground objects and synthesize them to get accurate object boundaries. Then, this paper uses ReliefF algorithm to select the optimal feature combination and eliminate the Hughes phenomenon. Eventually, the multiple classifier combination method is applied to get the outcome of the classification. In order to validate the feasible of this method, this paper selects two experimental regions in Stuttgart and Germany (Region A and B, covers 0.21 km2 and 1.1 km2 respectively). The aim of the first experiment on the Region A is to get the optimal segmentation scales and classification features. The overall accuracy of the classification reaches to 93.3 %. The purpose of the experiment on region B is to validate the application-ability of this method for a large area, which is turned out to be reaches 88.4 % overall accuracy. In the end of this paper, the conclusion shows that the proposed method can be performed accurately and efficiently in terms of urban ground information extraction and be of high application value.

  7. Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

    Science.gov (United States)

    Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

    2017-05-01

    This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

  8. High-resolution multispectral satellite imagery for extracting bathymetric information of Antarctic shallow lakes

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

    High-resolution pansharpened images from WorldView-2 were used for bathymetric mapping around Larsemann Hills and Schirmacher oasis, east Antarctica. We digitized the lake features in which all the lakes from both the study areas were manually extracted. In order to extract the bathymetry values from multispectral imagery we used two different models: (a) Stumpf model and (b) Lyzenga model. Multiband image combinations were used to improve the results of bathymetric information extraction. The derived depths were validated against the in-situ measurements and root mean square error (RMSE) was computed. We also quantified the error between in-situ and satellite-estimated lake depth values. Our results indicated a high correlation (R = 0.60 0.80) between estimated depth and in-situ depth measurements, with RMSE ranging from 0.10 to 1.30 m. This study suggests that the coastal blue band in the WV-2 imagery could retrieve accurate bathymetry information compared to other bands. To test the effect of size and dimension of lake on bathymetry retrieval, we distributed all the lakes on the basis of size and depth (reference data), as some of the lakes were open, some were semi frozen and others were completely frozen. Several tests were performed on open lakes on the basis of size and depth. Based on depth, very shallow lakes provided better correlation (≈ 0.89) compared to shallow (≈ 0.67) and deep lakes (≈ 0.48). Based on size, large lakes yielded better correlation in comparison to medium and small lakes.

  9. MS(E) based multiplex protein analysis quantified important allergenic proteins and detected relevant peptides carrying known epitopes in wheat grain extracts.

    Science.gov (United States)

    Uvackova, Lubica; Skultety, Ludovit; Bekesova, Slavka; McClain, Scott; Hajduch, Martin

    2013-11-01

    The amount of clinically relevant, allergy-related proteins in wheat grain is still largely unknown. The application of proteomics may create a platform not only for identification and characterization, but also for quantitation of these proteins. The aim of this study was to evaluate the data-independent quantitative mass spectrometry (MS(E)) approach in combination with 76 wheat allergenic sequences downloaded from the AllergenOnline database ( www.allergenonline.org ) as a starting point. Alcohol soluble extracts of gliadin and glutenin proteins were analyzed. This approach has resulted in identification and quantification of 15 allergenic protein isoforms that belong to amylase/trypsin inhibitors, γ-gliadins, and high or low molecular weight glutenins. Additionally, several peptides carrying four previously discovered epitopes of γ-gliadin B precursor have been detected. These data were validated against the UniProt database, which contained 11764 Triticeae protein sequences. The identified allergens are discussed in relation to Baker's asthma, food allergy, wheat dependent exercise induced anaphylaxis, atopic dermatitis, and celiac disease (i.e., gluten-sensitive enteropathy). In summary, the results showed that the MS(E) approach is suitable for quantitative analysis and allergens profiling in wheat varieties and/or other food matrices.

  10. Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery.

    Science.gov (United States)

    Drawnel, Faye Marie; Zhang, Jitao David; Küng, Erich; Aoyama, Natsuyo; Benmansour, Fethallah; Araujo Del Rosario, Andrea; Jensen Zoffmann, Sannah; Delobel, Frédéric; Prummer, Michael; Weibel, Franziska; Carlson, Coby; Anson, Blake; Iacone, Roberto; Certa, Ulrich; Singer, Thomas; Ebeling, Martin; Prunotto, Marco

    2017-05-18

    Today, novel therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping was applicable to compounds with a range of binding specificities and triaged false positives derived from high-content screening assays. The technique identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. Our results advocate for application of molecular phenotyping in early drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Extracting duration information in a picture category decoding task using hidden Markov Models

    Science.gov (United States)

    Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

    2016-04-01

    Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

  12. The Study on Height Information Extraction of Cultural Features in Remote Sensing Images Based on Shadow Areas

    Science.gov (United States)

    Bao-Ming, Z.; Hai-Tao, G.; Jun, L.; Zhi-Qing, L.; Hong, H.

    2011-09-01

    Cultural feature is important element in geospatial information library and the height information is important information of cultural features. The existences of the height information and its precision have direct influence over topographic map, especially the quality of large-scale and medium-scale topographic map, and the level of surveying and mapping support. There are a lot of methods about height information extraction, in which the main methods are ground survey (field direct measurement) spatial sensor and photogrammetric ways. However, automatic extraction is very tough. This paper has had an emphasis on segmentation algorithm on shadow areas under multiple constraints and realized automatic extraction of height information by using shadow. Binarization image can be obtained using gray threshold estimated under the multiple constraints. On the interesting area, spot elimination and region splitting are made. After region labeling and non-shadowed regions elimination, shadow area of cultural features can be found. Then height of the cultural features can be calculated using shadow length, sun altitude angle, azimuth angle, and sensor altitude angle, azimuth angle. A great many of experiments have shown that mean square error of the height information of cultural features extraction is close to 2 meter and automatic extraction rate is close to 70%.

  13. THE STUDY ON HEIGHT INFORMATION EXTRACTION OF CULTURAL FEATURES IN REMOTE SENSING IMAGES BASED ON SHADOW AREAS

    Directory of Open Access Journals (Sweden)

    Z. Bao-Ming

    2012-09-01

    Full Text Available Cultural feature is important element in geospatial information library and the height information is important information of cultural features. The existences of the height information and its precision have direct influence over topographic map, especially the quality of large-scale and medium-scale topographic map, and the level of surveying and mapping support. There are a lot of methods about height information extraction, in which the main methods are ground survey (field direct measurement spatial sensor and photogrammetric ways. However, automatic extraction is very tough. This paper has had an emphasis on segmentation algorithm on shadow areas under multiple constraints and realized automatic extraction of height information by using shadow. Binarization image can be obtained using gray threshold estimated under the multiple constraints. On the interesting area, spot elimination and region splitting are made. After region labeling and non-shadowed regions elimination, shadow area of cultural features can be found. Then height of the cultural features can be calculated using shadow length, sun altitude angle, azimuth angle, and sensor altitude angle, azimuth angle. A great many of experiments have shown that mean square error of the height information of cultural features extraction is close to 2 meter and automatic extraction rate is close to 70%.

  14. Comparing the Influence of Title and URL in Information Retrieval Relevance in Search Engines Results between Human Science and Agriculture Science

    Directory of Open Access Journals (Sweden)

    Parisa Allami

    2012-12-01

    Full Text Available When the World Wide Web provides suitable methods for producing and publishing information to scientists, the Web has become a mediator to publishing information. This environment has been formed billions of web pages that each of them has a special title, special content, special address and special purpose. Search engines provide a variety of facilities limit search results to raise the possibility of relevance in the retrieval results. One of these facilities is the limitation of the keywords and search terms to the title or URL. It can increase the possibility of results relevance significantly. Search engines claim what are limited to title and URL is most relevant. This research tried to compare the results relevant between results limited in title and URL in agricultural and Humanities areas from their users sights also it notice to Comparison of the presence of keywords in the title and URL between two areas and the relationship between search query numbers and matching keywords in title and their URLs. For this purpose, the number of 30 students in each area whom were in MA process and in doing their thesis was chosen. There was a significant relevant of the results that they limited their information needs to title and URL. There was significantly relevance in URL results in agricultural area, but there was not any significant difference between title and URL results in the humanities. For comparing the number of keywords in title and URL in two areas, 30 keywords in each area were chosen. There was not any significantly difference between the number of keywords in the title and URL of websites in two areas. To show relationship between number of search keyword and the matching of title and URL 45 keywords in each area were chosen. They were divided to three parts (one keyword, two keywords and three keywords. It was determined that if search keyword was less, the amount of matching between title and URL was more and if the matching

  15. You had me at "Hello": Rapid extraction of dialect information from spoken words.

    Science.gov (United States)

    Scharinger, Mathias; Monahan, Philip J; Idsardi, William J

    2011-06-15

    Research on the neuronal underpinnings of speaker identity recognition has identified voice-selective areas in the human brain with evolutionary homologues in non-human primates who have comparable areas for processing species-specific calls. Most studies have focused on estimating the extent and location of these areas. In contrast, relatively few experiments have investigated the time-course of speaker identity, and in particular, dialect processing and identification by electro- or neuromagnetic means. We show here that dialect extraction occurs speaker-independently, pre-attentively and categorically. We used Standard American English and African-American English exemplars of 'Hello' in a magnetoencephalographic (MEG) Mismatch Negativity (MMN) experiment. The MMN as an automatic change detection response of the brain reflected dialect differences that were not entirely reducible to acoustic differences between the pronunciations of 'Hello'. Source analyses of the M100, an auditory evoked response to the vowels suggested additional processing in voice-selective areas whenever a dialect change was detected. These findings are not only relevant for the cognitive neuroscience of language, but also for the social sciences concerned with dialect and race perception.

  16. Information problem solving by experts and novices: Analysis of a complex cognitive skill.

    NARCIS (Netherlands)

    Brand-Gruwel, Saskia; Wopereis, Iwan; Vermetten, Yvonne

    2007-01-01

    In (higher) education students are often faced with information problems: tasks or assignments that require them to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a variety of sources.

  17. Information problem solving by experts and novices: Analysis of a complex cognitive skill.

    NARCIS (Netherlands)

    Brand-Gruwel, Saskia; Wopereis, Iwan; Vermetten, Yvonne

    2007-01-01

    In (higher) education students are often faced with information problems: tasks or assignments that require them to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a variety of sources.

  18. Information-problem solving: a review of problems students encounter and instructional solutionsstar, open

    NARCIS (Netherlands)

    Walraven, Amber; Brand-Gruwel, Saskia; Boshuizen, Henny P.A.

    2008-01-01

    Searching and processing information is a complex cognitive process that requires students to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a variety of sources. This process is called

  19. Research of the Information Literacy Education on Relevance theory MOOC%关联主义MOOC的信息素养教育探究

    Institute of Scientific and Technical Information of China (English)

    卜冰华

    2015-01-01

    By trying to In-depth analysis and research of the characteristics of relevance theory MOOC, This article constructs the content frame about information literacy that relevance theory MOOC learner should have and explored the education model for information literacy education that the MOOC platform carried on.%文章试图通过对关联主义MOOC的学习特点进行深入分析与研究,构建出关联主义MOOC学习者应具备的信息素养内容框架,并对MOOC平台开展信息素养的教育模式进行了探究。

  20. 40 CFR 86.1862-04 - Maintenance of records and submittal of information relevant to compliance with fleet average NOX...

    Science.gov (United States)

    2010-07-01

    ... each LDV/T or MDPV subject to this subpart: (i) Model year; (ii) Applicable fleet average NOX standard... which the LDV/T or MDPV is certified; and (vii) Information on the point of first sale, including the...

  1. Enriching a document collection by integrating information extraction and PDF annotation

    Science.gov (United States)

    Powley, Brett; Dale, Robert; Anisimoff, Ilya

    2009-01-01

    Modern digital libraries offer all the hyperlinking possibilities of the World Wide Web: when a reader finds a citation of interest, in many cases she can now click on a link to be taken to the cited work. This paper presents work aimed at providing the same ease of navigation for legacy PDF document collections that were created before the possibility of integrating hyperlinks into documents was ever considered. To achieve our goal, we need to carry out two tasks: first, we need to identify and link citations and references in the text with high reliability; and second, we need the ability to determine physical PDF page locations for these elements. We demonstrate the use of a high-accuracy citation extraction algorithm which significantly improves on earlier reported techniques, and a technique for integrating PDF processing with a conventional text-stream based information extraction pipeline. We demonstrate these techniques in the context of a particular document collection, this being the ACL Anthology; but the same approach can be applied to other document sets.

  2. Face Contour Extraction of Information%人脸轮廓信息的提取

    Institute of Scientific and Technical Information of China (English)

    原瑾

    2011-01-01

    边缘提取在模式识别、机器视觉、图像分析及图像编码等领域都有着重要的研究价值。人脸检测技术是一种人脸识别技术的前提。文章针对人脸检测中人脸定位提出了人脸轮廓信息提取技术,确定人脸检测的主要区域。首先介绍了几种边缘检测算子,然后提出了动态阈值方法来改进图像阈值,提高了边缘检测精度。%Edge extraction has important research value in the fields of pattern recognition, machine vision, image analysis and image coding. Face detection technology is prerequisite of face recognition technology. In view of person face localization in person face detection, the dissertation proposes an extraction technology of face outline information to identify the main regional of face. This article first introduced several edge detection operators, and then proposed the method of dynamic threshold value to improves the image threshold value, which increased the edge detection accuracy.

  3. Information asymmetries and the value-relevance of cash flow and accounting figures: empirical analysis and implications for managerial accounting

    OpenAIRE

    Rapp, Marc Steffen

    2010-01-01

    While some of the modern performance measures used in managerial accounting rely on cash flow based figures others try to take advantage of the information content of accounting figures. However, whether the additional information content in the accrual components of earnings improves the internal performance measurement is an open empirical question. To shed light on this question, I examine the correlation between operating cash flows and earnings with firm's total shareholder returns. Usin...

  4. Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities.

    Science.gov (United States)

    Abraham, Paul E; Giannone, Richard J; Xiong, Weili; Hettich, Robert L

    2014-06-17

    Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

  5. Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities

    Energy Technology Data Exchange (ETDEWEB)

    Abraham, Paul E [ORNL; Giannone, Richard J [ORNL; Xiong, Weili [ORNL; Hettich, Robert {Bob} L [ORNL

    2014-01-01

    Contemporary microbial ecology studies usually employ one or more omics approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other meta-omic approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

  6. Optimal Extraction of Cosmological Information from Supernova Datain the Presence of Calibration Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Alex G.; Miquel, Ramon

    2005-09-26

    We present a new technique to extract the cosmological information from high-redshift supernova data in the presence of calibration errors and extinction due to dust. While in the traditional technique the distance modulus of each supernova is determined separately, in our approach we determine all distance moduli at once, in a process that achieves a significant degree of self-calibration. The result is a much reduced sensitivity of the cosmological parameters to the calibration uncertainties. As an example, for a strawman mission similar to that outlined in the SNAP satellite proposal, the increased precision obtained with the new approach is roughly equivalent to a factor of five decrease in the calibration uncertainty.

  7. Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

    Science.gov (United States)

    Malin, Jane T.

    2008-01-01

    This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set.

  8. Developing a Process Model for the Forensic Extraction of Information from Desktop Search Applications

    Directory of Open Access Journals (Sweden)

    Timothy Pavlic

    2008-03-01

    Full Text Available Desktop search applications can contain cached copies of files that were deleted from the file system. Forensic investigators see this as a potential source of evidence, as documents deleted by suspects may still exist in the cache. Whilst there have been attempts at recovering data collected by desktop search applications, there is no methodology governing the process, nor discussion on the most appropriate means to do so. This article seeks to address this issue by developing a process model that can be applied when developing an information extraction application for desktop search applications, discussing preferred methods and the limitations of each. This work represents a more structured approach than other forms of current research.

  9. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared......What if Information Retrieval (IR) systems did not just retrieve relevant information that is stored in their indices, but could also "understand" it and synthesise it into a single document? We present a preliminary study that makes a first step towards answering this question. Given a query, we...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  10. ANALYSIS OF THE IMPACT OF THE CONVERGENCE PROCESS TO THE INTERNATIONAL ACCOUNTING STANDARDS IN BRAZIL: A STUDY BASED ON THE VALUE RELEVANCE OF ACCOUNTING INFORMATION

    OpenAIRE

    2014-01-01

    Recently, a lot of changes in the legislation governing the Brazilian accounting practices initiated the alignment of Brazil to the internationalization process of accounting. In this context, this article aims to verify if the process of convergence to international accounting standards impacted the value relevance of accounting information such as Earnings per Share (LPA) and Equity per Share (PLPA), of the non-financial companies most traded on BM&FBOVESPA. This is done by testing the ...

  11. EnvMine: A text-mining system for the automatic extraction of contextual information

    Directory of Open Access Journals (Sweden)

    de Lorenzo Victor

    2010-06-01

    Full Text Available Abstract Background For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles. So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations from textual sources of any kind. Results EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings. Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude, thus allowing the calculation of distance between the individual locations. Conclusion EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical

  12. Intelligent information extraction to aid science decision making in autonomous space exploration

    Science.gov (United States)

    Merényi, Erzsébet; Tasdemir, Kadim; Farrand, William H.

    2008-04-01

    Effective scientific exploration of remote targets such as solar system objects increasingly calls for autonomous data analysis and decision making on-board. Today, robots in space missions are programmed to traverse from one location to another without regard to what they might be passing by. By not processing data as they travel, they can miss important discoveries, or will need to travel back if scientists on Earth find the data warrant backtracking. This is a suboptimal use of resources even on relatively close targets such as the Moon or Mars. The farther mankind ventures into space, the longer the delay in communication, due to which interesting findings from data sent back to Earth are made too late to command a (roving, floating, or orbiting) robot to further examine a given location. However, autonomous commanding of robots in scientific exploration can only be as reliable as the scientific information extracted from the data that is collected and provided for decision making. In this paper, we focus on the discovery scenario, where information extraction is accomplished with unsupervised clustering. For high-dimensional data with complicated structure, detailed segmentation that identifies all significant groups and discovers the small, surprising anomalies in the data, is a challenging task at which conventional algorithms often fail. We approach the problem with precision manifold learning using self-organizing neural maps with non-standard features developed in the course of our research. We demonstrate the effectiveness and robustness of this approach on multi-spectral imagery from the Mars Exploration Rovers Pancam, and on synthetic hyperspectral imagery.

  13. HIV pre-test information, discussion or counselling? A review of guidance relevant to the WHO European Region.

    Science.gov (United States)

    Bell, Stephen A; Delpech, Valerie; Raben, Dorthe; Casabona, Jordi; Tsereteli, Nino; de Wit, John

    2016-02-01

    In the context of a shift from exceptionalism to normalisation, this study examines recommendations/evidence in current pan-European/global guidelines regarding pre-test HIV testing and counselling practices in health care settings. It also reviews new research not yet included in guidelines. There is consensus that verbal informed consent must be gained prior to testing, individually, in private, confidentially, in the presence of a health care provider. All guidelines recommend pre-test information/discussion delivered verbally or via other methods (information sheet). There is agreement about a minimum standard of information to be provided before a test, but guidelines differ regarding discussion about issues encouraging patients to think about implications of the result. There is heavy reliance on expert consultation in guideline development. Referenced scientific evidence is often more than ten years old and based on US/UK research. Eight new papers are reviewed. Current HIV testing and counselling guidelines have inconsistencies regarding the extent and type of information that is recommended during pre-test discussions. The lack of new research underscores a need for new evidence from a range of European settings to support the process of expert consultation in guideline development.

  14. The Persistence of the Pamphlet: On the Continued Relevance of the Health Information Pamphlet in the Digital Age.

    Science.gov (United States)

    Sium, Aman; Giuliani, Meredith; Papadakos, Janet

    2015-11-18

    Since the early 2000s, web and digital health information and education has progressed in both volume and innovation (Dutta-Bergman 2006; Mano, Computers in Human Behavior 39 404 412, 2014). A growing number of leading Canadian health institutions (e.g., hospitals, community health centers, and health ministries) are migrating much of their vital public health information and education, once restricted to pamphlets and other physically distributed materials, to online platforms. Examples of these platforms are websites and web pages, eLearning modules, eBooks, streamed classrooms, audiobooks, and online health videos. The steady migration of health information to online platforms is raising important questions for fields of patient education, such as cancer education. These questions include, but are not limited to (a) are pamphlets still a useful modality for patient information and education when so much is available on the Internet? (b) If so, what should be the relationship between print-based and online health information and education, and when should one modality take precedence over the other? This article responds to these questions within the Canadian health care context.

  15. Matching Office Information Systems (OIS Curriculum To Relevant Standards: Students, School Mission, Regional Business Needs, and National Curriculum

    Directory of Open Access Journals (Sweden)

    Arlene August

    1998-01-01

    Full Text Available This paper examines the process and outcome of a major curriculum update for the Office Information Systems (OIS major in the Office Information Systems Department in the School of Computer Science and Information Systems (CSIS at Pace University. The curriculum was updated to better prepare our students for success as end-user specialists in today’s flattened organizations. The changes made were based on modules recommended from the Office Systems Research Association (OSRA--recommendations that were both reliable and valid. OSRA’s national curriculum was flexible enough to allow us to incorporate regional business demands as well as adhere to CSIS’s mission statement. The success of this curriculum, now two years old, is measured by the success of our graduates (B.Sc. degree in obtaining meaningful employment.

  16. Inhibitory effect on key enzymes relevant to acute type-2 diabetes and antioxidative activity of ethanolic extract of Artocarpus heterophyllus stem bark

    Institute of Scientific and Technical Information of China (English)

    Basiru Olaitan Ajiboye; Oluwafemi Adeleke Ojo; Oluwatosin Adeyonu; Oluwatosin Imiere; Isreal Olayide; Adewale Fadaka; Babatunji Emmanuel Oyinloye

    2016-01-01

    Objective: To investigate the in vitro antioxidant activity of ethanolic extract of Arto-carpus heterophyllus (A. heterophyllus) stem bark and its inhibitory effect on a-amylase and a-glucosidase. Methods: The A. heterophyllus stem bark was extracted using methanol and tested for antioxidative activity. Results: The results revealed that the ethanolic extract has polyphenolics and free radical scavenging compounds which were significantly higher (P Conclusions: Therefore, it can be inferred from this study that ethanolic extract of A. heterophyllus stem bark may be useful in the management of diabetes mellitus probably due to bioactive compounds observed in the extract.

  17. Benchmarking and Its Relevance to the Library and Information Sector. Interim Findings of "Best Practice Benchmarking in the Library and Information Sector," a British Library Research and Development Department Project.

    Science.gov (United States)

    Kinnell, Margaret; Garrod, Penny

    This British Library Research and Development Department study assesses current activities and attitudes toward quality management in library and information services (LIS) in the academic sector as well as the commercial/industrial sector. Definitions and types of benchmarking are described, and the relevance of benchmarking to LIS is evaluated.…

  18. A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies

    Science.gov (United States)

    Hook, Simon J.; Gabell, A. R.; Green, A. A.; Kealy, P. S.

    1992-01-01

    This article evaluates three techniques developed to extract emissivity information from multispectral thermal infrared data. The techniques are the assumed Channel 6 emittance model, thermal log residuals, and alpha residuals. These techniques were applied to calibrated, atmospherically corrected thermal infrared multispectral scanner (TIMS) data acquired over Cuprite, Nevada in September 1990. Results indicate that the two new techniques (thermal log residuals and alpha residuals) provide two distinct advantages over the assumed Channel 6 emittance model. First, they permit emissivity information to be derived from all six TIMS channels. The assumed Channel 6 emittance model only permits emissivity values to be derived from five of the six TIMS channels. Second, both techniques are less susceptible to noise than the assumed Channel 6 emittance model. The disadvantage of both techniques is that laboratory data must be converted to thermal log residuals or alpha residuals to facilitate comparison with similarly processed image data. An additional advantage of the alpha residual technique is that the processed data are scene-independent unlike those obtained with the other techniques.

  19. Information Management Processes for Extraction of Student Dropout Indicators in Courses in Distance Mode

    Directory of Open Access Journals (Sweden)

    Renata Maria Abrantes Baracho

    2016-04-01

    Full Text Available This research addresses the use of information management processes in order to extract student dropout indicators in distance mode courses. Distance education in Brazil aims to facilitate access to information. The MEC (Ministry of Education announced, in the second semester of 2013, that the main obstacles faced by institutions offering courses in this mode were students dropping out and the resistance of both educators and students to this mode. The research used a mixed methodology, qualitative and quantitative, to obtain student dropout indicators. The factors found and validated in this research were: the lack of interest from students, insufficient training in the use of the virtual learning environment for students, structural problems in the schools that were chosen to offer the course, students without e-mail, incoherent answers to activities to the course, lack of knowledge on the part of the student when using the computer tool. The scenario considered was a course offered in distance mode called Aluno Integrado (Integrated Student

  20. Relevance between the degree of industrial competition and fair value information: Study on the listed companies in China

    OpenAIRE

    Xuemin Zhuang; Yonggen Luo

    2015-01-01

    Purpose: The purpose of this article is to study whether there exists natural relationship between fair value and corporate external market. A series of special phenomenon in the application of fair value arouses our research interests, which present evidences on how competition affects the correlation of fair value information. Design/methodology/approach: this thesis chooses fair value changes gains and losses and calculate the ratio of DFVPSit as the alternative variable of the fair value....

  1. Culturally-Relevant Online Cancer Education Modules Empower Alaska's Community Health Aides/Practitioners to Disseminate Cancer Information and Reduce Cancer Risk.

    Science.gov (United States)

    Cueva, Katie; Revels, Laura; Cueva, Melany; Lanier, Anne P; Dignan, Mark; Viswanath, K; Fung, Teresa T; Geller, Alan C

    2017-04-12

    To address a desire for timely, medically accurate cancer education in rural Alaska, ten culturally relevant online learning modules were developed with, and for, Alaska's Community Health Aides/Practitioners (CHA/Ps). The project was guided by the framework of Community-Based Participatory Action Research, honored Indigenous Ways of Knowing, and was informed by Empowerment Theory. A total of 428 end-of-module evaluation surveys were completed by 89 unique Alaska CHA/Ps between January and December 2016. CHA/Ps shared that as a result of completing the modules, they were empowered to share cancer information with their patients, families, friends, and communities, as well as engage in cancer risk reduction behaviors such as eating healthier, getting cancer screenings, exercising more, and quitting tobacco. CHA/Ps also reported the modules were informative and respectful of their diverse cultures. These results from end-of-module evaluation surveys suggest that the collaboratively developed, culturally relevant, online cancer education modules have empowered CHA/Ps to reduce cancer risk and disseminate cancer information. "brought me to tears couple of times, and I think it will help in destroying the silence that surrounds cancer".

  2. Information Extraction and Dependency on Open Government Data (ogd) for Environmental Monitoring

    Science.gov (United States)

    Abdulmuttalib, Hussein

    2016-06-01

    Environmental monitoring practices support decision makers of different government / private institutions, besides environmentalists and planners among others. This support helps them act towards the sustainability of our environment, and also take efficient measures for protecting human beings in general, but it is difficult to explore useful information from 'OGD' and assure its quality for the purpose. On the other hand, Monitoring itself comprises detecting changes as happens, or within the mitigation period range, which means that any source of data, that is to be used for monitoring, should replicate the information related to the period of environmental monitoring, or otherwise it's considered almost useless or history. In this paper the assessment of information extraction and structuring from Open Government Data 'OGD', that can be useful to environmental monitoring is performed, looking into availability, usefulness to environmental monitoring of a certain type, checking its repetition period and dependences. The particular assessment is being performed on a small sample selected from OGD, bearing in mind the type of the environmental change monitored, such as the increase and concentrations of built up areas, and reduction of green areas, or monitoring the change of temperature in a specific area. The World Bank mentioned in its blog that Data is open if it satisfies both conditions of, being technically open, and legally open. The use of Open Data thus, is regulated by published terms of use, or an agreement which implies some conditions without violating the above mentioned two conditions. Within the scope of the paper I wish to share the experience of using some OGD for supporting an environmental monitoring work, that is performed to mitigate the production of carbon dioxide, by regulating energy consumption, and by properly designing the test area's landscapes, thus using Geodesign tactics, meanwhile wish to add to the results achieved by many

  3. Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks

    Directory of Open Access Journals (Sweden)

    Nathan Paula M

    2010-06-01

    Full Text Available Abstract Background Mathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective for obtaining contact data relevant to the determination of these mixing patterns. Methods 65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA. Participants were randomised to first prospective recording method. Results Both methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77. Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22, P P Conclusions The study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners.

  4. Urban Built-Up Area Extraction from Landsat TM/ETM+ Images Using Spectral Information and Multivariate Texture

    Directory of Open Access Journals (Sweden)

    Jun Zhang

    2014-08-01

    Full Text Available Urban built-up area information is required by various applications. However, urban built-up area extraction using moderate resolution satellite data, such as Landsat series data, is still a challenging task due to significant intra-urban heterogeneity and spectral confusion with other land cover types. In this paper, a new method that combines spectral information and multivariate texture is proposed. The multivariate textures are separately extracted from multispectral data using a multivariate variogram with different distance measures, i.e., Euclidean, Mahalanobis and spectral angle distances. The multivariate textures and the spectral bands are then combined for urban built-up area extraction. Because the urban built-up area is the only target class, a one-class classifier, one-class support vector machine, is used. For comparison, the classical gray-level co-occurrence matrix (GLCM is also used to extract image texture. The proposed method was evaluated using bi-temporal Landsat TM/ETM+ data of two megacity areas in China. Results demonstrated that the proposed method outperformed the use of spectral information alone and the joint use of the spectral information and the GLCM texture. In particular, the inclusion of multivariate variogram textures with spectral angle distance achieved the best results. The proposed method provides an effective way of extracting urban built-up areas from Landsat series images and could be applicable to other applications.

  5. Perception and processing of information relevant to critical incidents and emergencies; Wahrnehmung und Verarbeitung stoer- und unfallrelevanter Informationen

    Energy Technology Data Exchange (ETDEWEB)

    Dombrowsky, W.R. [Kiel Univ. (Germany). Katastrophenforschungsstelle

    1997-12-31

    Based on the results of empirical research, which implemented and evaluated information to the public requested by law (HIO-Paragraph-11a) and based on the general findings of crisis- and risk-communication research, some disturbing elements in the relationship between entrepreneurs, administration and the public will be described in terms of cognitive dissonance, prejudice, fears and false expectations. The empirical example of public information in emergencies will evidence the conflicting views on types, styles, size and profoundity of such information as well as the differences in perception, motivation and interest of all parties involved. Finally, the cultural context of risk perception and of coping capabilities will be interrelated with historical changes of risk-management to prepare for the understanding that risk- and crisis communication has to be more than talking about safety. (orig.) [Deutsch] Am Beispiel einer Implementations- und Evaluationsforschung zur Erstellung von Stoerfallinformationen nach Paragraph 11a BimSchG fuer zwei Unternehmen und auf Basis des Kenntnisstandes der internationalen Forschung zur Krisen- und Risikokommunikation wird verdeutlicht, welche kognitiven Dissonanzen zwischen Anlagenbetreibern, Behoerden und Bevoelkerung ueber Art, Umfang und Gestaltung von Gefahrinformationen bestehen, welche Vorurteile und Aengste eine sachliche Kommunikation behindern, welche gesellschaftlichen Faktoren bislang weitgehend uebersehen wurden, was von wem fuer `stoer- und unfallrelevant` gehalten wird und welche gesellschaftlichen, sozialen `settings`, d.h. welche menschlichen Bedingungen die Wahrnehmung und Verarbeitung welcher Informationen beeinflussen. Darin liegt die empirische Bestaetigung der Hypothese, dass sich die Wahrnehmung von Risiken und Bedrohungen historisch kurzfristig (bereits innerhalb einer Generation) veraendert und es keine `one-for-all`-Strategie der Risiko- und Krisenkommunikation geben kann, wohl aber allgemeine

  6. [Evidence-based medicine. 2. Research of clinically relevant biomedical information. Gruppo Italiano per la Medicina Basata sulle Evidenze--GIMBE].

    Science.gov (United States)

    Cartabellotta, A

    1998-05-01

    Evidence-based Medicine is a product of the electronic information age and there are several databases useful for practice it--MEDLINE, EMBASE, specialized compendiums of evidence (Cochrane Library, Best Evidence), practice guidelines--most of them free available through Internet, that offers a growing number of health resources. Because searching best evidence is a basic step to practice Evidence-based Medicine, this second review (the first one has been published in the issue of March 1998) has the aim to provide physicians tools and skills for retrieving relevant biomedical information. Therefore, we discuss about strategies for managing information overload, analyze characteristics, usefulness and limits of medical databases and explain how to use MEDLINE in day-to-day clinical practice.

  7. Identifying relevant components to include in a parenting intervention for homeless families in transitional housing: Using parent input to inform adaptation efforts.

    Science.gov (United States)

    Holtrop, Kendal; Chaviano, Casey L; Scott, Jenna C; McNeil Smith, Shardé

    2015-11-01

    Homeless families in transitional housing face a number of distinct challenges, yet there is little research seeking to guide prevention and intervention work with homeless parents. Informed by the tenets of community-based participatory research, the purpose of this study was to identify relevant components to include in a parenting intervention for this population. Data were gathered from 40 homeless parents through semistructured individual interviews and were analyzed using qualitative content analysis. The resulting 15 categories suggest several topics, approach considerations, and activities that can inform parenting intervention work with homeless families in transitional housing. Study findings are discussed within the context of intervention fidelity versus adaptation, and implications for practice, research, and policy are suggested. This study provides important insights for informing parenting intervention adaptation and implementation efforts with homeless families in transitional housing. (PsycINFO Database Record

  8. Omnibus Weights of Evidence Method Implemented in GeoDAS GIS for Information Extraction and Integration

    Institute of Scientific and Technical Information of China (English)

    Zhang Shengyuan; Cheng Qiuming; Chen Zhijun

    2008-01-01

    Weights of evidence (WofE) is an artificial intelligent method for integration of information from diverse sources for predictive purpose in supporting decision making. This method has been commonly used to predict point events by integrating point training layer and binary or ternary evidential layers (multiclass evidence less commonly used). Omnibus weights of evidence integrates fuzzy training layer and diverse evidential layers. This method provides new features in comparison with the ordinary WofE method. This new method has been implemented in a geographic information system-geophysical data analysis system and the method includes the following contents: (1) dual fuzzy weights of evidence (DFWofE), in which training layer and evidential layers can be treated as fuzzy sets. DFWofE can be used to predict not only point events but also area or line events. In this model a fuzzy training layer can be defined based on point, line, and areas using fuzzy membership function; and (2) degree-of-exploration model for WofE is implemented through building a degree of exploration map. This method can be used to assess possible spatial correlations between the degree of exploration and potential evidential layers. Importantly, it would also make it possible to estimate undiscovered resources, if the degree of exploration map is combined with other models that predict where such resources are most likely to occur. These methods and relevant systems were validated using a case study of mineral potential prediction in Gejiu (个旧) mineral district, Yunnan (云南), China.

  9. Inhibitor y effect on key enzymes relevant to acute type-2 diabetes and antioxidative activity of ethanolic extract of Artocarpus heterophyllus stem bark

    Directory of Open Access Journals (Sweden)

    Basiru Olaitan Ajiboye

    2016-09-01

    Full Text Available Objective: To investigate the in vitro antioxidant activity of ethanolic extract of Artocarpus heterophyllus (A. heterophyllus stem bark and its inhibitory effect on a-amylase and a-glucosidase. Methods: The A. heterophyllus stem bark was extracted using methanol and tested for antioxidative activity. Results: The results revealed that the ethanolic extract has polyphenolics and free radical scavenging compounds which were significantly higher (P < 0.05 than their respective standard, at concentration dependent manner. The ethanolic extract of A. heterophyllus stem bark was observed to show inhibitory activities on a-amylase and a-glucosidase with IC50 of (4.18 ± 0.01 and (3.53 ± 0.03 mg/mL, respectively. The Lineweaver-Burk plot revealed that ethanolic extract of A. heterophyllus stem bark exhibited non-competitive inhibition for a-amylase and uncompetitive inhibition for a-glucosidase activities. Also, gas chromatography–mass spectrometry showed the presence of different bioactive compounds in extract. Conclusions: Therefore, it can be inferred from this study that ethanolic extract of A. heterophyllus stem bark may be useful in the management of diabetes mellitus probably due to bioactive compounds observed in the extract.

  10. Extracting information on urban impervious surface from GF-1 data in Tianjin City of China

    Science.gov (United States)

    Li, Bin; Meng, Qingyan; Wu, Jun; Gu, Xingfa

    2015-09-01

    The urban impervious surface, an important part in the city system, has a great influence on theecologicalenvironment in urban areas. The coverage of it is an important indicator for the evaluation ofurbanization. TheRemotesensing data has prominent features such as information-rich and accurate and it can provide data basis for large area extraction of impervious surface. GF-1 satellite is the first satellite of high-resolution earth observation system in China. With the homemade GF-1 satellite remote sensing image date as a resolution, this research, by the combination of V-I-S model and linear spectral mixture model, has first made estimation on the impervious surface of Tianjin City and then employed the remote sensingimage date with high resolution to test the precision of the estimated results. The results not only show that this method will make high precision available, but also reveal that Tianjin City has a wide coverage of impervious surface in general level, especially a high coverage rate both in the center and the coastal areas. The average coverage of impervious surface of the Tianjin city is very high and the coverage of impervious surface in the center and the coastal areas of Tianjin city reach seventy percent.City managers can use these data to guide city management and city planning.

  11. Extracting conformational structure information of benzene molecules via laser-induced electron diffraction

    Directory of Open Access Journals (Sweden)

    Yuta Ito

    2016-05-01

    Full Text Available We have measured the angular distributions of high energy photoelectrons of benzene molecules generated by intense infrared femtosecond laser pulses. These electrons arise from the elastic collisions between the benzene ions with the previously tunnel-ionized electrons that have been driven back by the laser field. Theory shows that laser-free elastic differential cross sections (DCSs can be extracted from these photoelectrons, and the DCS can be used to retrieve the bond lengths of gas-phase molecules similar to the conventional electron diffraction method. From our experimental results, we have obtained the C-C and C-H bond lengths of benzene with a spatial resolution of about 10 pm. Our results demonstrate that laser induced electron diffraction (LIED experiments can be carried out with the present-day ultrafast intense lasers already. Looking ahead, with aligned or oriented molecules, more complete spatial information of the molecule can be obtained from LIED, and applying LIED to probe photo-excited molecules, a “molecular movie” of the dynamic system may be created with sub-Ångström spatial and few-ten femtosecond temporal resolutions.

  12. 基于DOM模型扩展的Web信息提取%Extraction of Information from Web Pages Based on Extended DOM Tree

    Institute of Scientific and Technical Information of China (English)

    顾韵华; 田伟

    2009-01-01

    A method of information extraction from Web pages was presented, and it is based on extended DOM tree.Web pages were firstly transformed to DOM tree, then the DOM tree was extended by adding semantic expression to node and influence degree was calculated for each node.According to influence degree of nodes, the DOM tree was pruned,and it can automatically extract the useful relevant content from Web pages.This approach is a universal me-thod,which does not require to pre-know the structure of the Web page.The results of the information extraction are used not only for browsing but also for further Web information process, such as internet data mining, topic-based search engine.%提出了一种基于DOM模型扩展的Web信息提取方法.将Web页面表示为DOM树结构,对DOM树结点进行语义扩展并计算其影响度因子,依据结点的影响度因子进行剪枝,进而提取Web页面信息内容.该方法不要求对网页的结构有预先认识,具有自动和通用的特点.提取结果除可以直接用于Web浏览外,还可用于互联网数据挖掘、基于主题的搜索引擎等应用中.

  13. Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II

    Directory of Open Access Journals (Sweden)

    Peng-yuan Liu

    2016-01-01

    Full Text Available A novel feature extraction and selection scheme is presented for intelligent engine fault diagnosis by utilizing two-dimensional nonnegative matrix factorization (2DNMF, mutual information, and nondominated sorting genetic algorithms II (NSGA-II. Experiments are conducted on an engine test rig, in which eight different engine operating conditions including one normal condition and seven fault conditions are simulated, to evaluate the presented feature extraction and selection scheme. In the phase of feature extraction, the S transform technique is firstly utilized to convert the engine vibration signals to time-frequency domain, which can provide richer information on engine operating conditions. Then a novel feature extraction technique, named two-dimensional nonnegative matrix factorization, is employed for characterizing the time-frequency representations. In the feature selection phase, a hybrid filter and wrapper scheme based on mutual information and NSGA-II is utilized to acquire a compact feature subset for engine fault diagnosis. Experimental results by adopted three different classifiers have demonstrated that the proposed feature extraction and selection scheme can achieve a very satisfying classification performance with fewer features for engine fault diagnosis.

  14. Extracting structural information from the polarization dependence of one- and two-dimensional sum frequency generation spectra.

    Science.gov (United States)

    Laaser, Jennifer E; Zanni, Martin T

    2013-07-25

    We present ways in which pulse sequences and polarizations can be used to extract structural information from one- and two-dimensional vibrational sum frequency generation (2D SFG) spectra. We derive analytic expressions for the polarization dependence of systems containing coupled vibrational modes, and we present simulated spectra to identify the features of different molecular geometries. We discuss several useful polarization combinations for suppressing strong diagonal peaks and emphasizing weaker cross-peaks. We investigate unique capabilities of 2D SFG spectra for obtaining structural information about SFG-inactive modes and for identifying coupled achiral chromophores. This work builds on techniques that have been developed for extracting structural information from 2D IR spectra. This paper discusses how to utilize these concepts in 2D SFG experiments to probe multioscillator systems at interfaces. The sample code for calculating polarization dependence of 1D and 2D SFG spectra is provided in the Supporting Information .

  15. Stable isotope analysis provides new information on winter habitat use of declining avian migrants that is relevant to their conservation.

    Directory of Open Access Journals (Sweden)

    Karl L Evans

    Full Text Available Winter habitat use and the magnitude of migratory connectivity are important parameters when assessing drivers of the marked declines in avian migrants. Such information is unavailable for most species. We use a stable isotope approach to assess these factors for three declining African-Eurasian migrants whose winter ecology is poorly known: wood warbler Phylloscopus sibilatrix, house martin Delichon urbicum and common swift Apus apus. Spatially segregated breeding wood warbler populations (sampled across a 800 km transect, house martins and common swifts (sampled across a 3,500 km transect exhibited statistically identical intra-specific carbon and nitrogen isotope ratios in winter grown feathers. Such patterns are compatible with a high degree of migratory connectivity, but could arise if species use isotopically similar resources at different locations. Wood warbler carbon isotope ratios are more depleted than typical for African-Eurasian migrants and are compatible with use of moist lowland forest. The very limited variance in these ratios indicates specialisation on isotopically restricted resources, which may drive the similarity in wood warbler populations' stable isotope ratios and increase susceptibility to environmental change within its wintering grounds. House martins were previously considered to primarily use moist montane forest during the winter, but this seems unlikely given the enriched nature of their carbon isotope ratios. House martins use a narrower isotopic range of resources than the common swift, indicative of increased specialisation or a relatively limited wintering range; both factors could increase house martins' vulnerability to environmental change. The marked variance in isotope ratios within each common swift population contributes to the lack of population specific signatures and indicates that the species is less vulnerable to environmental change in sub-Saharan Africa than our other focal species. Our findings

  16. Evaluation of a simple protein extraction method for species identification of clinically relevant staphylococci by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

    Science.gov (United States)

    Matsuda, Naoto; Matsuda, Mari; Notake, Shigeyuki; Yokokawa, Hirohide; Kawamura, Yoshiaki; Hiramatsu, Keiichi; Kikuchi, Ken

    2012-12-01

    In clinical microbiology, bacterial identification is labor-intensive and time-consuming. A solution for this problem is the use of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this study, we evaluated a modified protein extraction method of identification performed on target plates (on-plate extraction method) with MALDI-TOF (Bruker Microflex LT with Biotyper version 3.0) and compared it to 2 previously described methods: the direct colony method and a standard protein extraction method (standard extraction method). We evaluated the species of 273 clinical strains and 14 reference strains of staphylococci. All isolates were characterized using the superoxide dismutase A sequence as a reference. For the species identification, the on-plate, standard extraction, and direct colony methods identified 257 isolates (89.5%), 232 isolates (80.8%), and 173 isolates (60.2%), respectively, with statistically significant differences among the three methods (P extraction method is at least as good as standard extraction in identification rate and has the advantage of a shorter processing time.

  17. In-shore ship extraction from HR optical remote sensing image via salience structure and GIS information

    Science.gov (United States)

    Ren, Xiaoyuan; Jiang, Libing; Tang, Xiao-an

    2015-12-01

    In order to solve the problem of in-shore ship extraction from remote sensing image, a novel method for in-shore ship extraction from high resolution (HR) optical remote sensing image is proposed via salience structure feature and GIS information. Firstly, the berth ROI is located in the image with the aid of the prior GIS auxiliary information. Secondly, the salient corner features at ship bow are extracted from the berth ROI precisely. Finally, a recursive algorithm concerning the symmetric geometry of the ship target is conducted to discriminate the multi docked in-shore targets into mono in-shore ships. The results of the experiments show that the method proposed in this paper can detect the majority of large and medium scale in-shore ships from the optical remote sensing image, including both the mono and the multi adjacent docked in-shore ship cases.

  18. Antioxidant and inhibitory properties of Clerodendrum volubile leaf extracts on key enzymes relevant to non-insulin dependent diabetes mellitus and hypertension

    Directory of Open Access Journals (Sweden)

    Stephen A. Adefegha

    2016-07-01

    Conclusion: The inhibitory properties of phenolic rich extracts on α-amylase, α-glucosidase, ACE, and Fe2+- and sodium nitroprusside-induced lipid peroxidation in the pancreas could be attributed to the antioxidant properties of the extracts and their phenolic composition. The stronger action of the bound phenolic extract on α-glucosidase may provide the possible bioactivity at the brush border end of the intestinal wall. This study may thus suggest that leaves represent a functional food and nutraceutical in the management of non-insulin dependent diabetes mellitus and hypertension.

  19. Perceptions of document relevance

    Directory of Open Access Journals (Sweden)

    Peter eBruza

    2014-07-01

    Full Text Available This article presents a study of how humans perceive the relevance of documents.Humans are adept at making reasonably robust and quick decisions about what information is relevant to them, despite the ever increasing complexity and volume of their surrounding information environment. The literature on document relevance has identified various dimensions of relevance (e.g., topicality, novelty, etc., however little is understood about how these dimensions may interact.We performed a crowdsourced study of how human subjects judge two relevance dimensions in relation to document snippets retrieved from an internet search engine.The order of the judgement was controlled.For those judgements exhibiting an order effect, a q-test was performed to determine whether the order effects can be explained by a quantum decision model based on incompatible decision perspectives.Some evidence of incompatibility was found which suggests incompatible decision perspectives is appropriate for explaining interacting dimensions of relevance.

  20. Inhibitory effect of dates-extract on α-Amylase and β-glucosidase enzymes relevant to non-insulin dependent diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Sulaiman Al-Zuhair

    2010-04-01

    the NIDDM treatment potential of DE. Keywords: Diabetes, dates-extract, α-amylase, α-glucosidase, enzyme inhibition Received: 4 April 2010 / Received in revised form: 9 June 2010, Accepted: 9 June 2010, Published online: 7 July 2010

  1. Extracting key information from historical data to quantify the transmission dynamics of smallpox

    Directory of Open Access Journals (Sweden)

    Brockmann Stefan O

    2008-08-01

    Full Text Available Abstract Background Quantification of the transmission dynamics of smallpox is crucial for optimizing intervention strategies in the event of a bioterrorist attack. This article reviews basic methods and findings in mathematical and statistical studies of smallpox which estimate key transmission parameters from historical data. Main findings First, critically important aspects in extracting key information from historical data are briefly summarized. We mention different sources of heterogeneity and potential pitfalls in utilizing historical records. Second, we discuss how smallpox spreads in the absence of interventions and how the optimal timing of quarantine and isolation measures can be determined. Case studies demonstrate the following. (1 The upper confidence limit of the 99th percentile of the incubation period is 22.2 days, suggesting that quarantine should last 23 days. (2 The highest frequency (61.8% of secondary transmissions occurs 3–5 days after onset of fever so that infected individuals should be isolated before the appearance of rash. (3 The U-shaped age-specific case fatality implies a vulnerability of infants and elderly among non-immune individuals. Estimates of the transmission potential are subsequently reviewed, followed by an assessment of vaccination effects and of the expected effectiveness of interventions. Conclusion Current debates on bio-terrorism preparedness indicate that public health decision making must account for the complex interplay and balance between vaccination strategies and other public health measures (e.g. case isolation and contact tracing taking into account the frequency of adverse events to vaccination. In this review, we summarize what has already been clarified and point out needs to analyze previous smallpox outbreaks systematically.

  2. Inhibitory activity of a standardized elderberry liquid extract against clinically-relevant human respiratory bacterial pathogens and influenza A and B viruses

    Directory of Open Access Journals (Sweden)

    Domann Eugen

    2011-02-01

    Full Text Available Abstract Background Black elderberries (Sambucus nigra L. are well known as supportive agents against common cold and influenza. It is further known that bacterial super-infection during an influenza virus (IV infection can lead to severe pneumonia. We have analyzed a standardized elderberry extract (Rubini, BerryPharma AG for its antimicrobial and antiviral activity using the microtitre broth micro-dilution assay against three Gram-positive bacteria and one Gram-negative bacteria responsible for infections of the upper respiratory tract, as well as cell culture experiments for two different strains of influenza virus. Methods The antimicrobial activity of the elderberry extract was determined by bacterial growth experiments in liquid cultures using the extract at concentrations of 5%, 10%, 15% and 20%. The inhibitory effects were determined by plating the bacteria on agar plates. In addition, the inhibitory potential of the extract on the propagation of human pathogenic H5N1-type influenza A virus isolated from a patient and an influenza B virus strain was investigated using MTT and focus assays. Results For the first time, it was shown that a standardized elderberry liquid extract possesses antimicrobial activity against both Gram-positive bacteria of Streptococcus pyogenes and group C and G Streptococci, and the Gram-negative bacterium Branhamella catarrhalis in liquid cultures. The liquid extract also displays an inhibitory effect on the propagation of human pathogenic influenza viruses. Conclusion Rubini elderberry liquid extract is active against human pathogenic bacteria as well as influenza viruses. The activities shown suggest that additional and alternative approaches to combat infections might be provided by this natural product.

  3. Delayed effects of environmentally relevant concentrations of 3,3',4,4'-tetrachlorobiphenyl (PCB-77) and non-polar sediment extracts detected in the prolonged-FETAX

    NARCIS (Netherlands)

    Gutleb, A.C.; Mossink, L.; Schriks, M.; Berg, van den J.H.J.; Murk, A.J.

    2007-01-01

    In the prolonged-FETAX (prolonged-Frog Embryo Teratogenic Assay-Xenopus) tadpoles are allowed to develop until metamorphosis after an initial 4 day early life-stage exposure (FETAX). PCB 77 (3,4,3¿,4¿-tetrachlorobiphenyl) and sediment extracts were used in the presented experiments. Concentrations o

  4. A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION

    Directory of Open Access Journals (Sweden)

    J. Sharmila

    2016-01-01

    Full Text Available Web mining related exploration is getting the chance to be more essential these days in view of the reason that a lot of information is overseen through the web. Web utilization is expanding in an uncontrolled way. A particular framework is required for controlling such extensive measure of information in the web space. Web mining is ordered into three noteworthy divisions: Web content mining, web usage mining and web structure mining. Tak-Lam Wong has proposed a web content mining methodology in the exploration with the aid of Bayesian Networks (BN. In their methodology, they were learning on separating the web data and characteristic revelation in view of the Bayesian approach. Roused from their investigation, we mean to propose a web content mining methodology, in view of a Deep Learning Algorithm. The Deep Learning Algorithm gives the interest over BN on the basis that BN is not considered in any learning architecture planning like to propose system. The main objective of this investigation is web document extraction utilizing different grouping algorithm and investigation. This work extricates the data from the web URL. This work shows three classification algorithms, Deep Learning Algorithm, Bayesian Algorithm and BPNN Algorithm. Deep Learning is a capable arrangement of strategies for learning in neural system which is connected like computer vision, speech recognition, and natural language processing and biometrics framework. Deep Learning is one of the simple classification technique and which is utilized for subset of extensive field furthermore Deep Learning has less time for classification. Naive Bayes classifiers are a group of basic probabilistic classifiers in view of applying Bayes hypothesis with concrete independence assumptions between the features. At that point the BPNN algorithm is utilized for classification. Initially training and testing dataset contains more URL. We extract the content presently from the dataset. The

  5. Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report.

    Energy Technology Data Exchange (ETDEWEB)

    Kegelmeyer, W. Philip,; Shead, Timothy M. [Sandia National Laboratories, Albuquerque, NM; Dunlavy, Daniel M. [Sandia National Laboratories, Albuquerque, NM

    2013-09-01

    This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods. Conditional random fields (CRFs) are powerful, flexible probabilistic graphical models often used in supervised machine learning prediction tasks associated with sequence data. Specifically, they are currently the best known option for named entity recognition (NER) in text. NER is the process of labeling words in sentences with semantic identifiers such as %E2%80%9Cperson%E2%80%9D, %E2%80%9Cdate%E2%80%9D, or %E2%80%9Corganization%E2%80%9D. Ensembles are a powerful statistical inference meta-method that can make most supervised machine learning methods more accurate, faster, or both. Ensemble methods are normally best suited to %E2%80%9Cunstable%E2%80%9D classification methods with high variance error. CRFs applied to NER are very stable classifiers, and as such, would initially seem to be resistant to the benefits of ensembles. The NEEEEIT project nonetheless worked out how to generalize ensemble methods to CRFs, demonstrated that accuracy can indeed be improved by proper use of ensemble techniques, and generated a new CRF code, %E2%80%9CpyCrust%E2%80%9D and a surrounding application environment, %E2%80%9CNEEEEIT%E2%80%9D, which implement those improvements. The summary practical advice that results from this work, then, is: When making use of CRFs for label prediction tasks in machine learning, use the pyCrust CRF base classifier with NEEEEIT's bagging ensemble implementation. (If those codes are not available, then de-stablize your CRF code via every means available, and generate the bagged training sets by hand.) If you have ample pre-processing computational time, do %E2%80%9Cforward feature selection%E2%80%9D to find and remove counter-productive feature classes. Conversely

  6. Different approaches for extracting information from the co-occurrence matrix.

    Directory of Open Access Journals (Sweden)

    Loris Nanni

    Full Text Available In 1979 Haralick famously introduced a method for analyzing the texture of an image: a set of statistics extracted from the co-occurrence matrix. In this paper we investigate novel sets of texture descriptors extracted from the co-occurrence matrix; in addition, we compare and combine different strategies for extending these descriptors. The following approaches are compared: the standard approach proposed by Haralick, two methods that consider the co-occurrence matrix as a three-dimensional shape, a gray-level run-length set of features and the direct use of the co-occurrence matrix projected onto a lower dimensional subspace by principal component analysis. Texture descriptors are extracted from the co-occurrence matrix evaluated at multiple scales. Moreover, the descriptors are extracted not only from the entire co-occurrence matrix but also from subwindows. The resulting texture descriptors are used to train a support vector machine and ensembles. Results show that our novel extraction methods improve the performance of standard methods. We validate our approach across six medical datasets representing different image classification problems using the Wilcoxon signed rank test. The source code used for the approaches tested in this paper will be available at: http://www.dei.unipd.it/wdyn/?IDsezione=3314&IDgruppo_pass=124&preview=.

  7. Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducability for use in research/quality assurance

    DEFF Research Database (Denmark)

    Kent, Peter; Briggs, Andrew M; Albert, Hanne Birgit;

    2011-01-01

    Background Although reproducibility in reading MRI images amongst radiologists and clinicians has been studied previously, no studies have examined the reproducibility of inexperienced clinicians in extracting pathoanatomic information from magnetic resonance imaging (MRI) narrative reports...... pathoanatomic information from radiologist-generated MRI narrative reports. Methods Twenty MRI narrative reports were randomly extracted from an institutional database. A group of three physiotherapy students independently reviewed the reports and coded the presence of 14 common pathoanatomic findings using...... a categorical electronic coding matrix. Decision rules were developed after initial coding in an effort to resolve ambiguities in narrative reports. This process was repeated a further three times using separate samples of 20 MRI reports until no further ambiguities were identified (total n=80). Reproducibility...

  8. Extracting Information from the Atom-Laser Wave Function UsingInterferometric Measurement with a Laser Standing-Wave Grating

    Institute of Scientific and Technical Information of China (English)

    刘正东; 武强; 曾亮; 林宇; 朱诗尧

    2001-01-01

    The reconstruction of the atom-laser wave function is performed using an interferometric measurement with a standing-wave grating, and the results of this scheme are studied. The relations between the measurement data and the atomic wave function are also presented. This scheme is quite applicable and effectively avoids the initial random phase problem of the method that employs the laser running wave. The information which is encoded in the atom-laser wave is extracted.

  9. INFO ANAV, a channel that is consolidated in the communication of information relevant to plant safety; INO ANAV, un canal que se consolida en la comunicacion de informacion relevante para la seguridad en las plantas

    Energy Technology Data Exchange (ETDEWEB)

    Lopera Broto, A. J.; Balbas Gomez, S.

    2012-07-01

    This weekly publication intended to make it to all the people who work at the sites of Asco and Vandellos relevant information for security since we are all responsible for the safe and reliable operation of our plants.

  10. Cross-scale modelling of alien and native vascular plant species richness in Great Britain: where is geodiversity information most relevant?

    Science.gov (United States)

    Bailey, Joseph; Field, Richard; Boyd, Doreen

    2016-04-01

    We assess the scale-dependency of the relationship between biodiversity and novel geodiversity information by studying spatial patterns of native and alien (archaeophytes and neophytes) vascular plant species richness at varying spatial scales across Great Britain. Instead of using a compound geodiversity metric, we study individual geodiversity components (GDCs) to advance our understanding of which aspects of 'geodiversity' are most important and at what scale. Terrestrial native (n = 1,490) and alien (n = 1,331) vascular plant species richness was modelled across the island of Great Britain at two grain sizes and several extent radii. Various GDCs (landforms, hydrology, geology) were compiled from existing national datasets and automatically extracted landform coverage information (e.g. hollows, valleys, peaks), the latter using a digital elevation model (DEM) and geomorphometric techniques. More traditional predictors of species richness (climate, widely-used topography metrics, land cover diversity, and human population) were also incorporated. Boosted Regression Tree (BRT) models were produced at all grain sizes and extents for each species group and the dominant predictors were assessed. Models with and without geodiversity data were compared. Overarching patterns indicated a clear dominance of geodiversity information at the smallest study extent (12.5km radius) and finest grain size (1x1km), which substantially decreased for each increase in extent as the contribution of climatic variables increased. The contribution of GDCs to biodiversity models was chiefly driven by landform information from geomorphometry, but hydrology (rivers and lakes), and to a lesser extent materials (soil, superficial deposits, and geology), were important, also. GDCs added significantly to vascular plant biodiversity models in Great Britain, independently of widely-used topographic metrics, particularly for native species. The wider consideration of geodiversity alongside

  11. A New Paradigm for the Extraction of Information:Application to Enhancement of Visual Information in a Medical Application

    Institute of Scientific and Technical Information of China (English)

    V. Courboulay; A. Histace; M. Ménard; C.Cavaro-Menard

    2004-01-01

    The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium displacement on both Short-Axis (SA) and Long-Axis (LA) frames in a time sequence. Visual evaluation of the grid deformation allows the estimation of the displacement inside the myocardium. The work described in this paper aims to make robust and reliable the visual enhancement of the grid tags on cardiac MRI sequences, thanks to an informational formalism based on Extreme Physical Informational (EPI). This approach leads to the development of an original diffusion pre-processing allowing us to make better the robustness of the visual detection and the following of the grid of tags.

  12. Optimization of a multilayer neural network by using minimal redundancy maximal relevance-partial mutual information clustering with least square regression.

    Science.gov (United States)

    Chen, Chao; Yan, Xuefeng

    2015-06-01

    In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation learning algorithm, minimal redundancy maximal relevance-partial mutual information clustering (mPMIc) integrated with least square regression (LSR) is proposed to optimize the MLFN. The mPMIc can determine the location of hidden layer nodes using information in the hidden and output layers, as well as remove redundant hidden layer nodes. These selected nodes are highly related to output data, but are minimally correlated with other hidden layer nodes. The weights between the selected hidden layer nodes and output layer are then updated through LSR. When the redundant nodes from the hidden layer are removed, the ideal MLFN structure can be obtained according to the test error results. In actual applications, the naphtha dry point must be controlled accurately because it strongly affects the production yield and the stability of subsequent operational processes. The mPMIc-LSR MLFN with a simple network size performs better than other improved MLFN variants and existing efficient models.

  13. Road Extraction and Network Building from Synthetic Aperture Radar Images using A-Priori Information

    NARCIS (Netherlands)

    Dekker, R.J.

    2008-01-01

    This paper describes a method for the extraction of road networks from radar images. Three phases can be distinguished: (1) detection of road lines, (2) network building, and (3) network fusion. The method has been demonstrated on two radar images, one urban and one rural. Despite the differences,

  14. Road Extraction and Network Building from Synthetic Aperture Radar Images using A-Priori Information

    NARCIS (Netherlands)

    Dekker, R.J.

    2008-01-01

    This paper describes a method for the extraction of road networks from radar images. Three phases can be distinguished: (1) detection of road lines, (2) network building, and (3) network fusion. The method has been demonstrated on two radar images, one urban and one rural. Despite the differences, t

  15. Comparison of Qinzhou bay wetland landscape information extraction by three methods

    Directory of Open Access Journals (Sweden)

    X. Chang

    2014-04-01

    and OO is 219 km2, 193.70 km2, 217.40 km2 respectively. The result indicates that SC is in the f irst place, followed by OO approach, and the third DT method when used to extract Qingzhou Bay coastal wetland.

  16. A defocus-information-free autostereoscopic three-dimensional (3D) digital reconstruction method using direct extraction of disparity information (DEDI)

    Science.gov (United States)

    Li, Da; Cheung, Chifai; Zhao, Xing; Ren, Mingjun; Zhang, Juan; Zhou, Liqiu

    2016-10-01

    Autostereoscopy based three-dimensional (3D) digital reconstruction has been widely applied in the field of medical science, entertainment, design, industrial manufacture, precision measurement and many other areas. The 3D digital model of the target can be reconstructed based on the series of two-dimensional (2D) information acquired by the autostereoscopic system, which consists multiple lens and can provide information of the target from multiple angles. This paper presents a generalized and precise autostereoscopic three-dimensional (3D) digital reconstruction method based on Direct Extraction of Disparity Information (DEDI) which can be used to any transform autostereoscopic systems and provides accurate 3D reconstruction results through error elimination process based on statistical analysis. The feasibility of DEDI method has been successfully verified through a series of optical 3D digital reconstruction experiments on different autostereoscopic systems which is highly efficient to perform the direct full 3D digital model construction based on tomography-like operation upon every depth plane with the exclusion of the defocused information. With the absolute focused information processed by DEDI method, the 3D digital model of the target can be directly and precisely formed along the axial direction with the depth information.

  17. Identification of "pathologs" (disease-related genes from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

    Directory of Open Access Journals (Sweden)

    Socha Luis A

    2004-04-01

    Full Text Available Abstract Background A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term "patholog" to mean a homolog of a human disease-related gene encoding a product (transcript, anti-sense or protein potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity (70–85% identity to known human-disease genes. Using a newly developed biological information extraction and annotation tool (FACTS in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic (53%, hereditary (24%, immunological (5%, cardio-vascular (4%, or other (14%, disorders. Conclusions Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

  18. Extracting Information about the Initial State from the Black Hole Radiation.

    Science.gov (United States)

    Lochan, Kinjalk; Padmanabhan, T

    2016-02-05

    The crux of the black hole information paradox is related to the fact that the complete information about the initial state of a quantum field in a collapsing spacetime is not available to future asymptotic observers, belying the expectations from a unitary quantum theory. We study the imprints of the initial quantum state contained in a specific class of distortions of the black hole radiation and identify the classes of in states that can be partially or fully reconstructed from the information contained within. Even for the general in state, we can uncover some specific information. These results suggest that a classical collapse scenario ignores this richness of information in the resulting spectrum and a consistent quantum treatment of the entire collapse process might allow us to retrieve much more information from the spectrum of the final radiation.

  19. Towards Evidence-based Precision Medicine: Extracting Population Information from Biomedical Text using Binary Classifiers and Syntactic Patterns

    Science.gov (United States)

    Raja, Kalpana; Dasot, Naman; Goyal, Pawan; Jonnalagadda, Siddhartha R

    2016-01-01

    Precision Medicine is an emerging approach for prevention and treatment of disease that considers individual variability in genes, environment, and lifestyle for each person. The dissemination of individualized evidence by automatically identifying population information in literature is a key for evidence-based precision medicine at the point-of-care. We propose a hybrid approach using natural language processing techniques to automatically extract the population information from biomedical literature. Our approach first implements a binary classifier to classify sentences with or without population information. A rule-based system based on syntactic-tree regular expressions is then applied to sentences containing population information to extract the population named entities. The proposed two-stage approach achieved an F-score of 0.81 using a MaxEnt classifier and the rule- based system, and an F-score of 0.87 using a Nai've-Bayes classifier and the rule-based system, and performed relatively well compared to many existing systems. The system and evaluation dataset is being released as open source. PMID:27570671

  20. Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis

    Energy Technology Data Exchange (ETDEWEB)

    Petrie, G.M.; Perry, E.M.; Kirkham, R.R.; Slator, D.E. [and others

    1997-09-01

    This report describes the work performed at the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy`s Office of Nonproliferation and National Security, Office of Research and Development (NN-20). The work supports the NN-20 Broad Area Search and Analysis, a program initiated by NN-20 to improve the detection and classification of undeclared weapons facilities. Ongoing PNNL research activities are described in three main components: image collection, information processing, and change analysis. The Multispectral Airborne Imaging System, which was developed to collect georeferenced imagery in the visible through infrared regions of the spectrum, and flown on a light aircraft platform, will supply current land use conditions. The image information extraction software (dynamic clustering and end-member extraction) uses imagery, like the multispectral data collected by the PNNL multispectral system, to efficiently generate landcover information. The advanced change detection uses a priori (benchmark) information, current landcover conditions, and user-supplied rules to rank suspect areas by probable risk of undeclared facilities or proliferation activities. These components, both separately and combined, provide important tools for improving the detection of undeclared facilities.

  1. Study on extraction of crop information using time-series MODIS data in the Chao Phraya Basin of Thailand

    Science.gov (United States)

    Tingting, Lv; Chuang, Liu

    2010-03-01

    In order to acquire the crop-related information in Chao Phraya Basin, time-series MODIS data were used in this paper. Although the spatial resolution of MODIS data is not very high, it is still useful for detecting very large-scale phenomenon, such as changes in seasonal vegetation patterns. After the data processing a general crop-related LULC (land use and land cover) map, cropping intensity map and cropping patterns map were produced. Analysis of these maps showed that the main land use type in the study area was farmland, most of which was dominated by rice. Rice fields mostly concentrated in the flood plains and double or triple rice-cropping system was commonly employed in this area. Maize, cassava, sugarcane and other upland crops were mainly distributed in the high alluvial terraces. Because these area often have water shortage problem particularly in the dry season which can support only one crop in a year, the cropping intensity was very low. However, some upland areas can be cultivated twice a year with crops which have short growing seasons. The crop information extracted from MODIS data sets were assessed by CBERS data, statistic data and so on. It was shown that MODIS derived crop information coincided well with the statistic data at the provincial level. At the same time, crop information extracted by MODIS data sets and CBERS were compared with each other which also showed similar spatial patterns.

  2. Keyword Extraction from a Document using Word Co-occurrence Statistical Information

    Science.gov (United States)

    Matsuo, Yutaka; Ishizuka, Mitsuru

    We present a new keyword extraction algorithm that applies to a single document without using a large corpus. Frequent terms are extracted first, then a set of co-occurrence between each term and the frequent terms, i.e., occurrences in the same sentences, is generated. The distribution of co-occurrence shows the importance of a term in the document as follows. If the probability distribution of co-occurrence between term a and the frequent terms is biased to a particular subset of the frequent terms, then term a is likely to be a keyword. The degree of the biases of the distribution is measured by χ²-measure. We show our algorithm performs well for indexing technical papers.

  3. Rapid Training of Information Extraction with Local and Global Data Views

    Science.gov (United States)

    2012-05-01

    Proceedings of the COLING, 1996. [35] Ralph Grishman, David Westbrook and Adam Meyers. NYUs English ACE 2005 System Description. ACE 2005 Evaluation...Conference on Artificial Intelligence. 2000. 93 [61] David Nadeau and Satoshi Sekine. A Survey of Named Entity Recognition and Classification. In: Sekine...relation extraction. In Proc. of COLING. 2008. [64] John Ross Quinlan . Induction of decision trees. Machine Learning, 1(1), 81- 106. 1986. [65] Lev

  4. Analysis of a Probabilistic Model of Redundancy in Unsupervised Information Extraction

    Science.gov (United States)

    2010-08-25

    noise. Example A in Figure 4 has strong evidence for a functional relation. 66 out of 70 extractions for was born in ( Mozart , PLACE) have the same y...unambiguous. 19 A. was born in( Mozart , PLACE): Salzburg(66), Germany(3), Vienna(1) B. was born in(John Adams, PLACE): Braintree(12), Quincy(10), Worcester(8...C. lived in( Mozart , PLACE): Vienna(20), Prague(13), Salzburg(5) Figure 4: Functional relations such as example A have a different distribution of y

  5. A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

    Science.gov (United States)

    Guo, H., II

    2016-12-01

    Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

  6. Extracting principles for information management adaptability during crisis response: A dynamic capability view

    NARCIS (Netherlands)

    Bharosa, N.; Janssen, M.F.W.H.A.

    2010-01-01

    During crises, relief agency commanders have to make decisions in a complex and uncertain environment, requiring them to continuously adapt to unforeseen environmental changes. In the process of adaptation, the commanders depend on information management systems for information. Yet there are still

  7. Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

    Science.gov (United States)

    Zhang, Rui

    2013-01-01

    The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

  8. Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

    Science.gov (United States)

    Zhang, Rui

    2013-01-01

    The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

  9. Extracting depth information of 3-dimensional structures from a single-view X-ray Fourier-transform hologram.

    Science.gov (United States)

    Geilhufe, J; Tieg, C; Pfau, B; Günther, C M; Guehrs, E; Schaffert, S; Eisebitt, S

    2014-10-20

    We demonstrate how information about the three-dimensional structure of an object can be extracted from a single Fourier-transform X-ray hologram. In contrast to lens-based 3D imaging approaches that provide depth information of a specimen utilizing several images from different angles or via adjusting the focus to different depths, our method capitalizes on the use of the holographically encoded phase and amplitude information of the object's wavefield. It enables single-shot measurements of 3D objects at coherent X-ray sources. As the ratio of longitudinal resolution over transverse resolution scales proportional to the diameter of the reference beam aperture over the X-ray wavelength, we expect the approach to be particularly useful in the extreme ultraviolet and soft-X-ray regime.

  10. BioSimplify: an open source sentence simplification engine to improve recall in automatic biomedical information extraction

    CERN Document Server

    Jonnalagadda, Siddhartha

    2011-01-01

    BioSimplify is an open source tool written in Java that introduces and facilitates the use of a novel model for sentence simplification tuned for automatic discourse analysis and information extraction (as opposed to sentence simplification for improving human readability). The model is based on a "shot-gun" approach that produces many different (simpler) versions of the original sentence by combining variants of its constituent elements. This tool is optimized for processing biomedical scientific literature such as the abstracts indexed in PubMed. We tested our tool on its impact to the task of PPI extraction and it improved the f-score of the PPI tool by around 7%, with an improvement in recall of around 20%. The BioSimplify tool and test corpus can be downloaded from https://biosimplify.sourceforge.net.

  11. Robust Multivariable Estimation of the Relevant Information Coming from a Wheel Speed Sensor and an Accelerometer Embedded in a Car under Performance Tests

    Directory of Open Access Journals (Sweden)

    Wilmar Hernandez

    2005-11-01

    Full Text Available In the present paper, in order to estimate the response of both a wheel speedsensor and an accelerometer placed in a car under performance tests, robust and optimalmultivariable estimation techniques are used. In this case, the disturbances and noisescorrupting the relevant information coming from the sensors’ outputs are so dangerous thattheir negative influence on the electrical systems impoverish the general performance of thecar. In short, the solution to this problem is a safety related problem that deserves our fullattention. Therefore, in order to diminish the negative effects of the disturbances and noiseson the car’s electrical and electromechanical systems, an optimum observer is used. Theexperimental results show a satisfactory improvement in the signal-to-noise ratio of therelevant signals and demonstrate the importance of the fusion of several intelligent sensordesign techniques when designing the intelligent sensors that today’s cars need.

  12. A Target Sound Extraction via 2ch Microphone Array Using Phase Information

    Science.gov (United States)

    Suyama, Kenji; Takahashi, Kota

    In this paper, we propose a novel learning method of linear filters for a target sound extraction in a non—stationary noisy environment via a microphone array with 2 elements. The method is based on a phase difference between two microphones, which is detected from outputs of the Hilbert transformer whose length is corresponding to a fundamental period of vowel parts of speech signals. The cue signal, which has a correlation with a power envelop of target sound, is generated using a mean square of phase difference and applied to the learning. A superior performance of the proposed method is presented by several computer simulation results.

  13. Functional network and its application to extract information from chaotic communication

    Institute of Scientific and Technical Information of China (English)

    李卫斌; 焦李成

    2004-01-01

    In chaotic communication system, the useful signal is hidden in chaotic signal, so the general method does not work well. Due to the random feature of chaotic signal, a functional network-based method is presented. In this method,the neural functions are selected from some complete function set for the functional network to reconstruct the chaotic signal, so the useful signal hidden in chaotic background is extracted. In addition, its learning algorithm is presented here and the example proves its good preformance.

  14. Recent advancements in information extraction methodology and hardware for earth resources survey systems

    Science.gov (United States)

    Erickson, J. D.; Thomson, F. J.

    1974-01-01

    The present work discusses some recent developments in preprocessing and extractive processing techniques and hardware and in user applications model development for earth resources survey systems. The Multivariate Interactive Digital Analysis System (MIDAS) is currently being developed, and is an attempt to solve the problem of real time multispectral data processing in an operational system. The main features and design philosophy of this system are described. Examples of wetlands mapping and land resource inventory are presented. A user model developed for predicting the yearly production of mallard ducks from remote sensing and ancillary data is described.

  15. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Directory of Open Access Journals (Sweden)

    Hui Wang

    Full Text Available We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs in 29 individuals with autism spectrum disorders (ASD, and 29 individuals with typical development (TD while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  16. Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders.

    Science.gov (United States)

    Wang, Hui; Chen, Chen; Fushing, Hsieh

    2012-01-01

    We employed a multi-scale clustering methodology known as "data cloud geometry" to extract functional connectivity patterns derived from functional magnetic resonance imaging (fMRI) protocol. The method was applied to correlation matrices of 106 regions of interest (ROIs) in 29 individuals with autism spectrum disorders (ASD), and 29 individuals with typical development (TD) while they completed a cognitive control task. Connectivity clustering geometry was examined at both "fine" and "coarse" scales. At the coarse scale, the connectivity clustering geometry produced 10 valid clusters with a coherent relationship to neural anatomy. A supervised learning algorithm employed fine scale information about clustering motif configurations and prevalence, and coarse scale information about intra- and inter-regional connectivity; the algorithm correctly classified ASD and TD participants with sensitivity of 82.8% and specificity of 82.8%. Most of the predictive power of the logistic regression model resided at the level of the fine-scale clustering geometry, suggesting that cellular versus systems level disturbances are more prominent in individuals with ASD. This article provides validation for this multi-scale geometric approach to extracting brain functional connectivity pattern information and for its use in classification of ASD.

  17. Extraction of structural and chemical information from high angle annular dark-field image by an improved peaks finding method.

    Science.gov (United States)

    Yin, Wenhao; Huang, Rong; Qi, Ruijuan; Duan, Chungang

    2016-09-01

    With the development of spherical aberration (Cs) corrected scanning transmission electron microscopy (STEM), high angle annular dark filed (HAADF) imaging technique has been widely applied in the microstructure characterization of various advanced materials with atomic resolution. However, current qualitative interpretation of the HAADF image is not enough to extract all the useful information. Here a modified peaks finding method was proposed to quantify the HAADF-STEM image to extract structural and chemical information. Firstly, an automatic segmentation technique including numerical filters and watershed algorithm was used to define the sub-areas for each atomic column. Then a 2D Gaussian fitting was carried out to determine the atomic column positions precisely, which provides the geometric information at the unit-cell scale. Furthermore, a self-adaptive integration based on the column position and the covariance of statistical Gaussian distribution were performed. The integrated intensities show very high sensitivity on the mean atomic number with improved signal-to-noise (S/N) ratio. Consequently, the polarization map and strain distributions were rebuilt from a HAADF-STEM image of the rhombohedral and tetragonal BiFeO3 interface and a MnO2 monolayer in LaAlO3 /SrMnO3 /SrTiO3 heterostructure was discerned from its neighbor TiO2 layers. Microsc. Res. Tech. 79:820-826, 2016. © 2016 Wiley Periodicals, Inc.

  18. Wavelet analysis of molecular dynamics: Efficient extraction of time-frequency information in ultrafast optical processes

    Energy Technology Data Exchange (ETDEWEB)

    Prior, Javier; Castro, Enrique [Departamento de Física Aplicada, Universidad Politécnica de Cartagena, Cartagena 30202 (Spain); Chin, Alex W. [Theory of Condensed Matter Group, University of Cambridge, J J Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Almeida, Javier; Huelga, Susana F.; Plenio, Martin B. [Institut für Theoretische Physik, Albert-Einstein-Allee 11, Universität Ulm, D-89069 Ulm (Germany)

    2013-12-14

    New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet “complete” spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport.

  19. Wavelet analysis of molecular dynamics: efficient extraction of time-frequency information in ultrafast optical processes.

    Science.gov (United States)

    Prior, Javier; Castro, Enrique; Chin, Alex W; Almeida, Javier; Huelga, Susana F; Plenio, Martin B

    2013-12-14

    New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet "complete" spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport.

  20. Investigation of the Impact of Extracting and Exchanging Health Information by Using Internet and Social Networks

    Science.gov (United States)

    Pistolis, John; Zimeras, Stelios; Chardalias, Kostas; Roupa, Zoe; Fildisis, George; Diomidous, Marianna

    2016-01-01

    Introduction: Social networks (1) have been embedded in our daily life for a long time. They constitute a powerful tool used nowadays for both searching and exchanging information on different issues by using Internet searching engines (Google, Bing, etc.) and Social Networks (Facebook, Twitter etc.). In this paper, are presented the results of a research based on the frequency and the type of the usage of the Internet and the Social Networks by the general public and the health professionals. Objectives: The objectives of the research were focused on the investigation of the frequency of seeking and meticulously searching for health information in the social media by both individuals and health practitioners. The exchanging of information is a procedure that involves the issues of reliability and quality of information. Methods: In this research, by using advanced statistical techniques an effort is made to investigate the participant’s profile in using social networks for searching and exchanging information on health issues. Results: Based on the answers 93 % of the people, use the Internet to find information on health-subjects. Considering principal component analysis, the most important health subjects were nutrition (0.719 %), respiratory issues (0.79 %), cardiological issues (0.777%), psychological issues (0.667%) and total (73.8%). Conclusions: The research results, based on different statistical techniques revealed that the 61.2% of the males and 56.4% of the females intended to use the social networks for searching medical information. Based on the principal components analysis, the most important sources that the participants mentioned, were the use of the Internet and social networks for exchanging information on health issues. These sources proved to be of paramount importance to the participants of the study. The same holds for nursing, medical and administrative staff in hospitals. PMID:27482135