WorldWideScience

Sample records for extract meaningful information

  1. Information and perception of meaningful patterns.

    Directory of Open Access Journals (Sweden)

    Maria M Del Viva

    Full Text Available The visual system needs to extract the most important elements of the external world from a large flux of information in a short time for survival purposes. It is widely believed that in performing this task, it operates a strong data reduction at an early stage, by creating a compact summary of relevant information that can be handled by further levels of processing. In this work we formulate a model of early vision based on a pattern-filtering architecture, partly inspired by high-speed digital data reduction in experimental high-energy physics (HEP. This allows a much stronger data reduction than models based just on redundancy reduction. We show that optimizing this model for best information preservation under tight constraints on computational resources yields surprisingly specific a-priori predictions for the shape of biologically plausible features, and for experimental observations on fast extraction of salient visual features by human observers. Interestingly, applying the same optimized model to HEP data acquisition systems based on pattern-filtering architectures leads to specific a-priori predictions for the relevant data patterns that these devices extract from their inputs. These results suggest that the limitedness of computing resources can play an important role in shaping the nature of perception, by determining what is perceived as "meaningful features" in the input data.

  2. Beyond noise: using temporal ICA to extract meaningful information from high-frequency fMRI signal fluctuations during rest

    Directory of Open Access Journals (Sweden)

    Roland Norbert Boubela

    2013-05-01

    Full Text Available Analysis of resting-state networks using fMRI usually ignores high-frequencyfluctuations in the BOLD signal – be it because of low TR prohibiting the analysis offluctuations with frequencies higher than 0.25 Hz (for a typical TR of 2 s, or becauseof the application of a bandpass filter (commonly restricting the signal to frequencieslower than 0.1 Hz. While the standard model of convolving neuronal activity with ahemodynamic response function suggests that the signal of interest in fMRI is characterized by slow fluctuation, it is in fact unclear whether the high-frequency dynamics of the signal consists of noise only. In this study, 10 subjects were scanned at 3 T during 6 minutes of rest using a multiband EPI sequence with a TR of 354 ms to critically sample fluctuations of up to 1.4 Hz. Preprocessed data were high-pass filtered to include only frequencies above 0.25 Hz, and voxelwise whole-brain temporal ICA (tICA was used to identify consistent high-frequency signals. The resulting components include physiological background signal sources, most notably pulsation and heartbeat components, that can be specifically identified and localized with the method presented here. Perhaps more surprisingly, common resting-state networks like the default-mode network also emerge as separate tICA components. This means that high frequency oscillations sampled with a rather T1-weighted contrast still contain specific information on these resting-state networks to consistently identify them, not consistent with the commonly held view that these networks operate on low-frequency fluctuations alone. Consequently, the use of bandpass filters in resting-state data analysis should be reconsidered, since this step eliminates potentially relevant information. Instead, more specific methods for the elimination of physiological background signals, for example by regression of physiological noise components, might prove to be viable alternatives.

  3. A Primer on Data Logging to Support Extraction of Meaningful Information from Educational Games: An Example from Save Patch. CRESST Report 814

    Science.gov (United States)

    Chung, Gregory K. W. K.; Kerr, Deirdre S.

    2012-01-01

    In this primer we briefly describe our perspective and experience in using data logging to support measurement of student learning in a game testbed ("Save Patch") we developed for research purposes. The goal of data logging is to support the derivation of cognitively meaningful measures and affectively meaningful measures from a combination of…

  4. Between order and chaos: The quest for meaningful information

    NARCIS (Netherlands)

    P. Adriaans

    2009-01-01

    The notion of meaningful information seems to be associated with the sweet spot between order and chaos. This form of meaningfulness of information, which is primarily what science is interested in, is not captured by both Shannon information and Kolmogorov complexity. In this paper I develop a theo

  5. Readiness for Meaningful Use of Health Information Tech...

    Data.gov (United States)

    U.S. Department of Health & Human Services — According to findings reported in Readiness for Meaningful Use of Health Information Technology and Patient Centered Medical Home Recognition Survey Results,...

  6. 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

  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. Meaningful auditory information enhances perception of visual biological motion.

    Science.gov (United States)

    Arrighi, Roberto; Marini, Francesco; Burr, David

    2009-04-30

    Robust perception requires efficient integration of information from our various senses. Much recent electrophysiology points to neural areas responsive to multisensory stimulation, particularly audiovisual stimulation. However, psychophysical evidence for functional integration of audiovisual motion has been ambiguous. In this study we measure perception of an audiovisual form of biological motion, tap dancing. The results show that the audio tap information interacts with visual motion information, but only when in synchrony, demonstrating a functional combination of audiovisual information in a natural task. The advantage of multimodal combination was better than the optimal maximum likelihood prediction.

  9. Collect Meaningful Information about Stock Markets from the Web

    Directory of Open Access Journals (Sweden)

    Saleem Abuleil

    2015-02-01

    Full Text Available Events represent a significant source of information on the web; they deliver information about events that occur around the world in all subjects and areas. These events can be collected and organized to provide valuable and useful information for decision makers, researchers, as well as for any person seeking knowledge. In this paper, we discuss an ongoing research to target stock markets domain to observe and record changes (events when they happen, collect them, understand the meaning of each one of them, and organize the information along with meaning in a well-structured format. By using Semantic Role Labeling (SRL technique, we have identified four factors for each event in this paper: verb of action and three roles associated with it, entity name, attribute, and attribute value. We have generated a set of rules and techniques to support our approach to analyze and understand the meaning of the events that take place in stock markets.

  10. The generation of meaningful information in molecular systems.

    Science.gov (United States)

    Wills, Peter R

    2016-03-13

    The physico-chemical processes occurring inside cells are under the computational control of genetic (DNA) and epigenetic (internal structural) programming. The origin and evolution of genetic information (nucleic acid sequences) is reasonably well understood, but scant attention has been paid to the origin and evolution of the molecular biological interpreters that give phenotypic meaning to the sequence information that is quite faithfully replicated during cellular reproduction. The near universality and age of the mapping from nucleotide triplets to amino acids embedded in the functionality of the protein synthetic machinery speaks to the early development of a system of coding which is still extant in every living organism. We take the origin of genetic coding as a paradigm of the emergence of computation in natural systems, focusing on the requirement that the molecular components of an interpreter be synthesized autocatalytically. Within this context, it is seen that interpreters of increasing complexity are generated by series of transitions through stepped dynamic instabilities (non-equilibrium phase transitions). The early phylogeny of the amino acyl-tRNA synthetase enzymes is discussed in such terms, leading to the conclusion that the observed optimality of the genetic code is a natural outcome of the processes of self-organization that produced it.

  11. 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

  12. Meaningful Informed Consent with Young Children: Looking Forward through an Interactive Narrative Approach

    Science.gov (United States)

    Mayne, Fiona; Howitt, Christine; Rennie, Léonie

    2016-01-01

    Ideas about ethical research with young children are evolving at a rapid rate. Not only can young children participate in the informed consent process, but researchers now also recognize that the process must be meaningful for them. As part of a larger study, this article reviews children's rights and informed consent literature as the foundation…

  13. Meaningful Informed Consent with Young Children: Looking Forward through an Interactive Narrative Approach

    Science.gov (United States)

    Mayne, Fiona; Howitt, Christine; Rennie, Léonie

    2016-01-01

    Ideas about ethical research with young children are evolving at a rapid rate. Not only can young children participate in the informed consent process, but researchers now also recognize that the process must be meaningful for them. As part of a larger study, this article reviews children's rights and informed consent literature as the foundation…

  14. Achieving meaningful learning in health information management students: the importance of professional experience.

    Science.gov (United States)

    Marks, Anne; McIntosh, Jean

    2006-01-01

    Learning is a complex process, not merely a transfer of information from teacher to student. for learning to be meaningful, students need to adopt a deep approach, and in the case of vocational students, to be given the opportunity to learn experientially. Health information management is a practice profession for which students are educated through theory at university and professional experience in the workplace. This article discusses how, through the process of experiential learning, professional experience can promote reflective thinking and thus deep learning, that is, the ability to integrate theory and practice, as well as professional and personal development in health information management students.

  15. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a qualitative systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Bjerrum, Merete; Sørensen, Erik Elgaard;

    Background: Support groups are considered an effective way to care for informal caregivers of older adults with dementia and relieve their feelings of stress and burden. Research shows, that participating in support groups seems to be beneficial for the informal caregivers, but with no significant...... the future through virtual configurations of group meetings Conclusion: Peer support is meaningful and beneficial for informal caregivers. The support groups provide a source for obtaining positive emotional support, venting negative feeling and gaining help to deal with the everyday life of caring for older...... improvements in feelings of stress and burden. It is unclear how support groups can produce a meaningful outcome for the informal caregivers. Aim: To identify the meaningfulness of participating in support groups for informal caregivers of older adults with dementia living in their own home. Method...

  16. The meaningfulness of participating in Support Groups for informal caregives of older adults with dementia: A Systematic Review Protocol

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Bjerrum, Merete

    2013-01-01

    Review question/objective The objective of this review is to identify the meaningfulness of participating in support groups for informal caregivers of older adults with dementia living in their own home. More specifically, the review question is: How do informal caregivers of older adults...... with dementia, living in urban and rural settings, perceive the meaningfulness of participating in support groups? Inclusion Criteria Types of participant(s) This review will consider studies that include informal caregivers of older adults aged 65 years and older with dementia, regardless of the severity...... that investigate how the informal caregivers of older adults with dementia, living in urban or rural settings perceive the meaningfulness of participating in support groups. The phenomenon of interest will consider studies that include informal caregivers, aged 18 years and older, who are caring for an older adult...

  17. From Big Data to Meaningful Information with SAS High-Performance Analytics

    Directory of Open Access Journals (Sweden)

    Silvia BOLOHAN

    2013-10-01

    Full Text Available This paper is about the importance of Big Data and What You Can Accomplish with the data that counts. Until recently, organizations have been limited to using subsets of their data, or they were constrained to simplistic analyses because the sheer volumes of data overwhelmed their processing platforms. But, what is the point of collecting and storing terabytes of data if you can't analyze it in full context, or if you have to wait hours or days to get results? On the other hand, not all business questions are better answered by bigger data. How can you make the most of all that data, now and in the future? It is a twofold proposition. You can only optimize your success if you weave analytics into your solution. But you also need analytics to help you manage the data itself. There are several key technologies that can help you get a handle on your big data, and more importantly, extract meaningful value from it.

  18. A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.

    Directory of Open Access Journals (Sweden)

    Daniel H Rapoport

    Full Text Available Automated microscopy is currently the only method to non-invasively and label-free observe complex multi-cellular processes, such as cell migration, cell cycle, and cell differentiation. Extracting biological information from a time-series of micrographs requires each cell to be recognized and followed through sequential microscopic snapshots. Although recent attempts to automatize this process resulted in ever improving cell detection rates, manual identification of identical cells is still the most reliable technique. However, its tedious and subjective nature prevented tracking from becoming a standardized tool for the investigation of cell cultures. Here, we present a novel method to accomplish automated cell tracking with a reliability comparable to manual tracking. Previously, automated cell tracking could not rival the reliability of manual tracking because, in contrast to the human way of solving this task, none of the algorithms had an independent quality control mechanism; they missed validation. Thus, instead of trying to improve the cell detection or tracking rates, we proceeded from the idea to automatically inspect the tracking results and accept only those of high trustworthiness, while rejecting all other results. This validation algorithm works independently of the quality of cell detection and tracking through a systematic search for tracking errors. It is based only on very general assumptions about the spatiotemporal contiguity of cell paths. While traditional tracking often aims to yield genealogic information about single cells, the natural outcome of a validated cell tracking algorithm turns out to be a set of complete, but often unconnected cell paths, i.e. records of cells from mitosis to mitosis. This is a consequence of the fact that the validation algorithm takes complete paths as the unit of rejection/acceptance. The resulting set of complete paths can be used to automatically extract important biological parameters

  19. A Narrative Review of Meaningful Use and Anesthesia Information Management Systems.

    Science.gov (United States)

    Gálvez, Jorge A; Rothman, Brian S; Doyle, Christine A; Morgan, Sherry; Simpao, Allan F; Rehman, Mohamed A

    2015-09-01

    The US federal government has enacted legislation for a federal incentive program for health care providers and hospitals to implement electronic health records. The primary goal of the Meaningful Use (MU) program is to drive adoption of electronic health records nationwide and set the stage to monitor and guide efforts to improve population health and outcomes. The MU program provides incentives for the adoption and use of electronic health record technology and, in some cases, penalties for hospitals or providers not using the technology. The MU program is administrated by the Department of Health and Human Services and is divided into 3 stages that include specific reporting and compliance metrics. The rationale is that increased use of electronic health records will improve the process of delivering care at the individual level by improving the communication and allow for tracking population health and quality improvement metrics at a national level in the long run. The goal of this narrative review is to describe the MU program as it applies to anesthesiologists in the United States. This narrative review will discuss how anesthesiologists can meet the eligible provider reporting criteria of MU by applying anesthesia information management systems (AIMS) in various contexts in the United States. Subsequently, AIMS will be described in the context of MU criteria. This narrative literature review also will evaluate the evidence supporting the electronic health record technology in the operating room, including AIMS, independent of certification requirements for the electronic health record technology under MU in the United States.

  20. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a qualitative systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    Introduction: Support groups are considered an effective and economical way to relieve informal caregivers stress and burden. Research shows, that participating in support groups seems to be beneficial for the informal caregivers, but there are no significant improvements in feelings of stress an...... that through comparison and sharing positive and negative emotions, the members of the support group are able to take on and maintain the role as caregiver.......Introduction: Support groups are considered an effective and economical way to relieve informal caregivers stress and burden. Research shows, that participating in support groups seems to be beneficial for the informal caregivers, but there are no significant improvements in feelings of stress...... and burden. It is unclear how support groups can produce a meaningful and optimal outcome for the informal caregivers. Aim: To identify the meaningfulness of participating in support groups for informal caregivers of older adults with dementia living in their own home. Method: A systematic literature review...

  1. 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...

  2. 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.

  3. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    2015-01-01

    BACKGROUND Informal caregivers who perform at-home care of older people with dementia might have feelings of a meaningless existence, burden, anxiety, stress and fatigue. Support groups are considered an especially effective and economical way to relieve informal caregivers’ stress and burden...... of participants: Informal caregivers of older adults aged 65 years and over with dementia. The informal caregiver was a family member, and care was performed at home. Phenomena of interest: How the informal caregivers perceived the meaningfulness of participating in support groups. The setting was all locations...

  4. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a qualitative systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    . The support groups provide a source for obtaining positive emotional support, venting negative feeling and gaining help to deal with the everyday life of caring for older adults with dementia. Dementia coordinators and primary health care nurses should play an active role as facilitators at the group meetings......Background: Support groups are considered an especially effective and economical way to relieve informal caregiver’s stress and burden, although it is unclear if participating in group meetings produces a meaningful outcome for the informal caregiver. Aim: To identify the meaningfulness...... of participating in support groups for informal caregivers of older adults with dementia living in their own home. Method: A systematic literature review was conducted based on a peer-reviewed and published review protocol. 233 full-text papers were assessed for eligibility. Five qualitative papers met...

  5. A Framework for Picture Extraction on Search Engine Improved and Meaningful Result

    CERN Document Server

    Sharma, Anamika

    2011-01-01

    Searching is an important tool of information gathering, if information is in the form of picture than it play a major role to take quick action and easy to memorize. This is a human tendency to retain more picture than text. The complexity and the occurrence of variety of query can give variation in result and provide the humans to learn something new or get confused. This paper presents a development of a framework that will focus on recourse identification for the user so that they can get faster access with accurate & concise results on time and analysis of the change that is evident as the scenario changes from text to picture retrieval. This paper also provides a glimpse how to get accurate picture information in advance and extended technologies searching framework. The new challenges and design techniques of picture retrieval systems are also suggested in this paper.

  6. 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.

  7. 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.

  8. The meaningfulness of participating in Support Groups for informal caregives of older adults with dementia: A Systematic Review Protocol

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Bjerrum, Merete Bender

    2013-01-01

    of the disease and the duration of care. The informal caregiver is mainly seen as a family member and care must be performed at home. The review will not differentiate between studies involving subsets of informal caregivers (e.g. based on specific ethnicity, gender and/or specific morbidities of dementia among...... with dementia, aged 65 years and older, living in their own home. The setting will be all locations where support groups for informal caregivers have been held and studied. Types of outcomes The outcomes of interest include, but are not restricted to the following: 1. Subjective accounts of the informal......Review question/objective The objective of this review is to identify the meaningfulness of participating in support groups for informal caregivers of older adults with dementia living in their own home. More specifically, the review question is: How do informal caregivers of older adults...

  9. 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.

  10. 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...

  11. 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.

  12. Social spaces, casual interactions, meaningful exchanges: 'information ground' characteristics based on the college student experience.

    Directory of Open Access Journals (Sweden)

    K.E. Fisher

    2007-01-01

    Full Text Available Introduction. In the late 1990s Fisher (writing as Pettigrew proposed information grounds to describe social settings in which people share everyday information while attending to a focal activity. Method. This study was conducted at a major research university, home to 45,000 students. Data were collected by seventy-two Master of Library and Information Science (MLIS students as part of an information behaviour class. Trained in interviewing techniques, each MLIS student interviewed ten students in public places, including the campus and the university commercial district. The survey, comprising twenty-seven primarily open-ended questions, was conducted from October 14-21, 2004. Data were collected from 729 college students and entered, along with extensive field notes, into an in-house Web form. Analysis. Qualitative and quantitative analyses were supplemented by mini-reports prepared by the student researchers along with full-team debriefings. Results. Using a 'people, place, information-related trichotomy', characteristics are discussed in terms of how they can be manipulated to optimize information flow in social settings. Conclusion. . By understanding better the characteristics of information grounds and the interactions among these characteristics, we may be able to develop social spaces in support of information flow and human interaction. Our college student and other studies suggest that information grounds play an intrinsic role in facilitating communication among people and that by building an in-depth typology, beginning with basic categorical characteristics, we may develop new methods for facilitating information exchange.

  13. 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.

  14. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    2015-01-01

    where support groups for informal caregivers were held and studied. Types of studies Studies that focused on qualitative data including, but not limited to, designs such as phenomenology, grounded theory, ethnography, action research and feminist research. Types of outcomes Subjective accounts...... quality of the qualitative papers was assessed independently by two reviewers using standardized critical appraisal instruments from the Joanna Briggs Institute Qualitative Assessment and Review Instrument. Data extraction Qualitative data were extracted from papers included in the review using...

  15. Meaningful, Authentic and Place-Based Informal Science Education for 6-12 Students

    Science.gov (United States)

    Ito, E.; Dalbotten, D. M.

    2014-12-01

    American Indians are underrepresented in STEM and especially in Earth sciences. They have the lowest high school graduation rate and highest unemployment. On the other hand, tribes are in search of qualified young people to work in geo- and hydro-technical fields to manage reservations' natural resources. Dalbotten and her collaborators at the Fond du Lac Band of Lake Superior Chippewa and local 6-12 teachers ran a place-based but non-themed informal monthly science camps (gidakiimanaaniwigamig) for 7 years starting 2003. Camps were held on reservation and some activities focused on observing seasonal changes. The students enjoyed coming to the camps but the camp activities went largely unnoticed by the reservation itself. For the last 5 years, we and the same cast of characters from the gidakiimanaaniwigamig camps ran a very place-based, research-based camp program, manoomin. The research was focused on manoomin (wild rice) which is a culturally important plant and food that grows in local lakes and wetlands. Manmade changes in hydrology, toxic metals from mining, and changing weather patterns due to climate change threaten this precious resource. Our plan was for 6-12 students to investigate the past, the present and the future conditions of manoomin on and around the reservation. It became clear by 3rd year that the research project, as conceived, was overly ambitious and could not be completed at the level we hoped in a camp setting (6 weekend camps = 6 full days per year). However, students felt that they were involved in research that was beneficial to their reservation, reported gaining self-confidence to pursue a career in science, and stated a desired to obtain a college degree. They also became aware of STEM employment opportunities on reservation that they could aim for. The camps also fostered a trusting relationship between researchers at Fond du Lac resource managers and the U. of MN. Based on these experiences, we proposed a new format for these

  16. Improvement of workflow and processes to ease and enrich meaningful use of health information technology

    Directory of Open Access Journals (Sweden)

    Singh R

    2013-11-01

    Full Text Available Ranjit Singh,1 Ashok Singh,2 Devan R Singh,3 Gurdev Singh1 1Department of Family Medicine, UB Patient Safety Research Center, School of Medicine and Management, State University of NY at Buffalo, NY, USA; 2Niagara Family Medicine Associates, Niagara Falls, NY, USA; 3SaferPatients LLC, Lewiston, NY, USA Abstract: The introduction of health information technology (HIT can have unexpected and unintended patient safety and/or quality consequences. This highly desirable but complex intervention requires workflow changes in order to be effective. Workflow is often cited by providers as the number one 'pain point'. Its redesign needs to be tailored to the organizational context, current workflow, HIT system being introduced, and the resources available. Primary care practices lack the required expertise and need external assistance. Unfortunately, the current methods of using esoteric charts or software are alien to health care workers and are, therefore, perceived to be barriers. Most importantly and ironically, these do not readily educate or enable staff to inculcate a common vision, ownership, and empowerment among all stakeholders. These attributes are necessary for creating highly reliable organizations. We present a tool that addresses US Accreditation Council for Graduate Medical (ACGME competency requirements. Of the six competencies called for by the ACGME, the two that this tool particularly addresses are 'system-based practice' and 'practice-based learning and continuing improvement'. This toolkit is founded on a systems engineering approach. It includes a motivational and orientation presentation, 128 magnetic pictorial and write-erase icons of 40 designs, dry-erase magnetic board, and five visual aids for reducing cognitive and emotive biases in staff. Pilot tests were carried out in practices in Western New York and Colorado, USA. In addition, the toolkit was presented at the 2011 North American Primary Care Research Group (NAPCRG

  17. 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.

  18. 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.

  19. 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.

  20. Does kinematics add meaningful information to clinical assessment in post-stroke upper limb rehabilitation? A case report

    Science.gov (United States)

    Bigoni, Matteo; Baudo, Silvia; Cimolin, Veronica; Cau, Nicola; Galli, Manuela; Pianta, Lucia; Tacchini, Elena; Capodaglio, Paolo; Mauro, Alessandro

    2016-01-01

    [Purpose] The aims of this case study were to: (a) quantify the impairment and activity restriction of the upper limb in a hemiparetic patient; (b) quantitatively evaluate rehabilitation program effectiveness; and (c) discuss whether more clinically meaningful information can be gained with the use of kinematic analysis in addition to clinical assessment. The rehabilitation program consisted of the combined use of different traditional physiotherapy techniques, occupational therapy sessions, and the so-called task-oriented approach. [Subject and Methods] Subject was a one hemiplegic patient. The patient was assessed at the beginning and after 1 month of daily rehabilitation using the Medical Research Council scale, Nine Hole Peg Test, Motor Evaluation Scale for Upper Extremity in Stroke Patients, and Hand Grip Dynamometer test as well as a kinematic analysis using an optoelectronic system. [Results] After treatment, significant improvements were evident in terms of total movement duration, movement completion velocity, and some smoothness parameters. [Conclusion] Our case report showed that the integration of clinical assessment with kinematic evaluation appears to be useful for quantitatively assessing performance changes. PMID:27630445

  1. Understanding the factors that influence the adoption and meaningful use of social media by physicians to share medical information.

    Science.gov (United States)

    McGowan, Brian S; Wasko, Molly; Vartabedian, Bryan Steven; Miller, Robert S; Freiherr, Desirae D; Abdolrasulnia, Maziar

    2012-09-24

    attitudes toward the use of social media were more likely to use social media and to share medical information with other physicians through social media. Neither age nor gender had a significant impact on adoption or usage of social media. Based on the results of this study, the use of social media applications may be seen as an efficient and effective method for physicians to keep up-to-date and to share newly acquired medical knowledge with other physicians within the medical community and to improve the quality of patient care. Future studies are needed to examine the impact of the meaningful use of social media on physicians' knowledge, attitudes, skills, and behaviors in practice.

  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. 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.

  4. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a qualitative systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    : A systematic literature review was conducted based on a peer-reviewed and published review protocol. 233 full-text papers were assessed for eligibility. Five qualitative papers were selected and assessed for methodological quality prior to inclusion using The Joanna Briggs Institute Qualitative Assessment...... and Review Instrument. Qualitative research data were extracted and the findings were pooled. This process involved the aggregation of findings to generate a set of statements that represent that aggregation, through assembling the findings rated according to their quality, and categorizing these findings......Background: Support groups are considered an effective way to care for informal caregivers of older adults with dementia and relieve their feelings of stress and burden. Research shows, that participating in support groups seems to be beneficial for the informal caregivers, but with no significant...

  5. 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.

  6. 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...

  7. 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....

  8. 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.

  9. 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 ...

  10. 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

  11. 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.

  12. 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...

  13. Making Meaningful Improvements to Direct Care Worker Training Through Informed Policy: Understanding How Care Setting Structure and Culture Matter.

    Science.gov (United States)

    Kemeny, M Elizabeth; Mabry, J Beth

    2015-10-09

    Well-intentioned policy governing the training of direct care workers (DCWs) who serve older persons, in practice, may become merely a compliance issue for organizations rather than a meaningful way to improve quality of care. This study investigates the relationships between best practices in DCW training and the structure and culture of long term support service (LTSS) organizations. Using a mixed-methods approach to analyzing data from 328 licensed LTSS organizations in Pennsylvania, the findings suggest that public policy should address methods of training, not just content, and consider organizational variations in size, training evaluation practices, DCW integration, and DCW input into care planning. Effective training also incorporates support for organizations and supervisors as key aspects of DCWs' learning and working environment.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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...

  19. Cybersemiotics: A New Foundation for Transdisciplinary Theory of Information, Cognition, Meaningful Communication and the Interaction Between Nature and Culture

    Directory of Open Access Journals (Sweden)

    Søren Brier

    2013-06-01

    Full Text Available Cybersemiotics constructs a non-reductionist framework in order to integrate third person knowledge from the exact sciences and the life sciences with first person knowledge described as the qualities of feeling in humanities and second person intersubjective knowledge of the partly linguistic communicative interactions, on which the social and cultural aspects of reality are based. The modern view of the universe as made through evolution in irreversible time, forces us to view man as a product of evolution and therefore an observer from inside the universe. This changes the way we conceptualize the problem and the role of consciousness in nature and culture. The theory of evolution forces us to conceive the natural and social sciences as well as the humanities together in one theoretical framework of unrestricted or absolute naturalism, where consciousness as well as culture is part of nature. But the theories of the phenomenological life world and the hermeneutics of the meaning of communication seem to defy classical scientific explanations. The humanities therefore send another insight the opposite way down the evolutionary ladder, with questions like: What is the role of consciousness, signs and meaning in the development of our knowledge about evolution? Phenomenology and hermeneutics show the sciences that their prerequisites are embodied living conscious beings imbued with meaningful language and with a culture. One can see the world view that emerges from the work of the sciences as a reconstruction back into time of our present ecological and evolutionary self-understanding as semiotic intersubjective conscious cultural and historical creatures, but unable to handle the aspects of meaning and conscious awareness and therefore leaving it out of the story. Cybersemiotics proposes to solve the dualistic paradox by starting in the middle with semiotic cognition and communication as a basic sort of reality in which all our knowledge is

  20. The meaningfulness of participating in support groups for informal caregivers of older adults with dementia: a qualitative systematic review

    DEFF Research Database (Denmark)

    Lauritzen, Jette; Pedersen, Preben Ulrich; Sørensen, Erik Elgaard;

    2015-01-01

    quality prior to inclusion using The Joanna Briggs Institute Qualitative Assessment and Review Instrument. Qualitative research data were extracted and the findings were pooled. This process involved the aggregation of findings to generate a set of statements that represent that aggregation, through...... assembling the findings rated according to their quality, and categorizing these findings based on similarity in meaning. These categories were subjected to a meta-synthesis that produced a comprehensive set of synthesized findings. Result: The meta-synthesis produced three synthesized findings: 1. Emotional......, venting negative feeling and gaining help to deal with the everyday life of caring for older adults with dementia....

  1. 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.

  2. From Raw Data to Meaningful Information: A Representational Approach to Cadastral Databases in Relation to Urban Planning

    Directory of Open Access Journals (Sweden)

    Francesc Valls Dalmau

    2014-10-01

    Full Text Available Digesting the data hose that cities are constantly producing is complex; data is usually structured with different criteria, which makes comparative analysis of multiple cities challenging. However, the publicly available data from the Spanish cadaster contains urban information in a documented format with common semantics for the whole territory, which makes these analyses possible. This paper uses the information about the 3D geometry of buildings, their use and their year of construction, stored in cadastral databases, to study the relation between the built environment (what the city is and the urban plan (what the city wants to become, translating the concepts of the cadastral data into the semantics of the urban plan. Different representation techniques to better understand the city from the pedestrians’ point of view and to communicate this information more effectively are also discussed.

  3. 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.

  4. 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.

  5. 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. ...

  6. 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

  7. What Makes Learning Meaningful?

    Science.gov (United States)

    Wilson, Arthur L.; Burket, Lee

    This document examines the work of Dewey, Kolb, Jarvis, Mezirow, Freire, Rogers, and Houle to find out what these experiential learning theorists have to say about the role experience plays in making learning meaningful. The first section addresses each writer's work for specific ideas of how experience is related to making learning meaningful,…

  8. Making Fractions Meaningful

    Science.gov (United States)

    McCormick, Kelly K.

    2015-01-01

    To be able to support meaningful mathematical experiences, preservice elementary school teachers (PSTs) must learn mathematics in deep and meaningful ways (Ma 1999). They need to experience investigating and making sense of the mathematics they will be called on to teach. To expand their own--often limited--views of what it means to teach and…

  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. 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

  11. Concept maps and the meaningful learning of science

    Directory of Open Access Journals (Sweden)

    José Antonio C. S. Valadares

    2013-03-01

    Full Text Available The foundations of the Meaningful Learning Theory (MLT were laid by David Ausubel. The MLT was highly valued by the contributions of Joseph Novak and D. B. Gowin. Unlike other learning theories, the MLT has an operational component, since there are some instruments based on it and with the meaningful learning facilitation as aim. These tools were designated graphic organizers by John Trowbridge and James Wandersee (2000, pp. 100-129. One of them is the concept map created by Novak to extract meanings from an amalgam of information, having currently many applications. The other one is the Vee diagram or knowledge Vee, also called epistemological Vee or heuristic Vee. It was created by Gowin, and is an excellent organizer, for example to unpack and make transparent the unclear information from an information source. Both instruments help us in processing and becoming conceptually transparent the information, to facilitate the cognitive process of new meanings construction. In this work, after a brief introduction, it will be developed the epistemological and psychological grounds of MLT, followed by a reference to constructivist learning environments facilitators of the meaningful learning, the characterization of concept maps and exemplification of its use in various applications that have proved to be very effective from the standpoint of meaningful learning.

  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. Towards formulating an accounting theory of meaningfulness

    OpenAIRE

    S. Wedzerai ,Musvoto; Gouws, Daan G

    2012-01-01

    This study highlights the need for a theory of meaningfulness for accounting information. A theory of meaningfulness determines the theoretical position that may be taken about the scientific content of information. The need for such a theory in accounting arises from the perspective that users of accounting information have not been able to take a firm theoretical position about the scientific content of accounting information in the financial statements. This has caused users of accounting ...

  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. 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

  16. 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.

  17. 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.

  18. 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...

  19. 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…

  20. 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…

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. From Mindless to Meaningful

    Science.gov (United States)

    Billings, Laura; Roberts, Terry

    2014-01-01

    Despite teachers' best intentions, traditional whole-class discussions sometimes end up sounding like the monotonous drone of Charlie Brown's teacher. But with careful planning, teachers can structure discussions that encourage meaningful student interaction and collaborative thinking, write Laura Billings and Terry Roberts of the…

  8. Meaningful and Purposeful Practice

    Science.gov (United States)

    Clementi, Donna

    2014-01-01

    This article describes a graphic, designed by Clementi and Terrill, the authors of "Keys to Planning for Learning" (2013), visually representing the components that contribute to meaningful and purposeful practice in learning a world language, practice that leads to greater proficiency. The entire graphic is centered around the letter…

  9. 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...

  10. 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)

  11. Characteristics of patient portals developed in the context of health information exchanges: Early policy effects of incentives in the meaningful use program in the United States

    NARCIS (Netherlands)

    E.T. Otte-Trojel (Eva Terese); A.A. de Bont (Antoinette); J.J. van de Klundert (Joris); T.G. Rundall (Thomas)

    2014-01-01

    textabstractBackground: In 2014, the Centers for Medicare & Medicaid Services in the United States launched the second stage of its Electronic Health Record (EHR) Incentive Program, providing financial incentives to providers to meaningfully use their electronic health records to engage patients onl

  12. Characteristics of patient portals developed in the context of health information exchanges: Early policy effects of incentives in the meaningful use program in the United States

    NARCIS (Netherlands)

    E.T. Otte-Trojel (Eva Terese); A.A. de Bont (Antoinette); J.J. van de Klundert (Joris); T.G. Rundall (Thomas)

    2014-01-01

    markdownabstract__Background:__ In 2014, the Centers for Medicare & Medicaid Services in the United States launched the second stage of its Electronic Health Record (EHR) Incentive Program, providing financial incentives to providers to meaningfully use their electronic health records to engage

  13. 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...

  14. 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.

  15. Life seems pretty meaningful.

    Science.gov (United States)

    Jeffery, Austin John; Shackelford, Todd K

    2015-09-01

    Comments on the original article "Life is pretty meaningful," by S. J. Heintzelman and L. A. King (see record 2014-03265-001). Heintzelman and King argue that, contrary to popular perception, our lives hold a great deal of meaning. The study of perceived meaning is an interesting and fruitful avenue. The current authors are concerned, however, that Heintzelman and King may have misrepresented and exploited the philosophical debate surrounding meaning to generate interest in their topic. Unless Heintzelman and King wish to argue that life truly is meaningful and that the perception of meaning is evidence enough, the current authors recommend that for the sake of clarity they make the explicit distinction between the widespread perception of meaning and its intrinsic existence. Unfortunately, once this distinction is made clear, these findings are less compelling to individuals who seek confirmation that intrinsic meaning exists. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  16. Life is pretty meaningful.

    Science.gov (United States)

    Heintzelman, Samantha J; King, Laura A

    2014-09-01

    The human experience of meaning in life is widely viewed as a cornerstone of well-being and a central human motivation. Self-reports of meaning in life relate to a host of important functional outcomes. Psychologists have portrayed meaning in life as simultaneously chronically lacking in human life as well as playing an important role in survival. Examining the growing literature on meaning in life, we address the question "How meaningful is life, in general?" We review possible answers from various psychological sources, some of which anticipate that meaning in life should be low and others that it should be high. Summaries of epidemiological data and research using two self-report measures of meaning in life suggest that life is pretty meaningful. Diverse samples rate themselves significantly above the midpoint on self-reports of meaning in life. We suggest that if meaning in life plays a role in adaptation, it must be commonplace, as our analysis suggests.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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,

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  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. 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...

  12. 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.

  13. Making metrics meaningful

    Directory of Open Access Journals (Sweden)

    Linda Bennett

    2013-07-01

    Full Text Available Continuing purchase of AHSS resources is threatened more by library budget squeezes than that of STM resources. Librarians must justify all expenditure, but quantitative metrical analysis to assess the value to the institution of journals and specialized research databases for AHSS subjects can be inconclusive; often the number of recorded transactions is lower than for STM, as the resource may be relevant to a smaller number of users. This paper draws on a literature review and extensive primary research, including a survey of 570 librarians and academics across the Anglophone countries, findings from focus group meetings and the analysis of user behaviour at a UK university before and after the installation of the Summon discovery system. It concludes that providing a new approach to metrics can help to develop resources strategies that meet changing user needs; and that usage statistics can be complemented with supplementary ROI measures to make them more meaningful.

  14. 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.

  15. 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.

  16. 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...

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. [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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. Fishing for meaningful units in connected speech

    DEFF Research Database (Denmark)

    Henrichsen, Peter Juel; Christiansen, Thomas Ulrich

    2009-01-01

    was far lower than for phonemic recognition. Our findings show that it is possible to automatically characterize a linguistic message, without detailed spectral information or presumptions about the target units. Further, fishing for simple meaningful cues and enhancing these selectively would potentially...... be a more effective way of achieving intelligibility transfer, which is the end goal for speech transducing technologies....

  12. 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.

  13. 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.

  14. Creating Meaningful Multimedia Presentations

    NARCIS (Netherlands)

    Hardman, L.; Ossenbruggen, J.R. van

    2006-01-01

    Finding relevant information is one step in the chain of understanding information. Presenting material to a user in a suitable way is a further step. Our research focuses on using semantic annotations of multimedia elements to increase the ”presentability” of retrieved info

  15. 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

  16. 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.

  17. 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

  18. 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).

  19. Engaging Scientists in Meaningful E/PO: How the NASA SMD E/PO Community Addresses Informal Educators' Preferences for PD and Materials

    Science.gov (United States)

    Bartolone, Lindsay; Nelson, Andi; Smith, Denise A.; NASA SMD Astrophysics E/PO Community

    2015-01-01

    The NASA Astrophysics Science Education and Public Outreach Forum (SEPOF) coordinates the work of NASA Science Mission Directorate (SMD) Astrophysics EPO projects. These teams work together to capitalize on the cutting-edge discoveries of NASA Astrophysics missions to support educators in Science, Technology, Engineering, and Math (STEM) and to enable youth to engage in doing STEM inside and outside of school. The Astrophysics Forum assists scientists and educators with becoming involved in SMD E/PO, which is uniquely poised to foster collaboration between scientists with content expertise and educators with pedagogy expertise, and makes SMD E/PO resources and expertise accessible to the science and education communities. Informal educators participated in a recent nationally-distributed survey from the NASA SMD SEPOF Informal Education Working Group. The results show the preferences of staff from museums, parks, public libraries, community/afterschool centers, and others with regard to professional development and material resources. The results of the survey will be presented during this session.In addition, we present opportunities for the astronomy community to participate in collaborations supporting the NASA SMD efforts in K-12 Formal Education, Informal Science Education, and Outreach. These efforts focus on enhancing instruction, as well as youth and public engagement, in STEM via use of research-based best practices, collaborations with libraries, partnerships with local and national organizations, and remote engagement of audiences. The Forums' efforts for the Formal, Informal Science Education and Outreach communities include a literature review, appraisal of informal educators' needs, coordination of audience-based NASA resources and opportunities, professional development, plus support with the Next Generation Science Standards. Learn how to join in our collaborative efforts to support the K-12 Formal Education community and to reach the informal

  20. 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.

  1. 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)

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Meaningful CSR Communication via Digital Media

    OpenAIRE

    Osborne, N.; Bolat, Elvira; Memery, Juliet

    2016-01-01

    It has regularly been stated that consumer demand for CSR is larger than ever, but do consumers really want to be informed about the ethical behaviour of brands? Does digital media have an impact on meaningful CSR communication? A research analysing consumer reaction to social media posts about CSR is limited. Using mixed method, this study examined the UK consumer attitudes towards CSR and its communication in digital media plus its consequent effect on purchasing intentions. Results indicat...

  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. Ritual, meaningfulness, and interstellar message construction

    Science.gov (United States)

    Traphagan, John W.

    2010-10-01

    In this paper, I am interested in exploring the potential of ritual performance as a means of communication with ETI. I argue that the study of ritual and ritualized behavior, understood as a technique for representation of meaning and meaningfulness about the world, has potential to inform how scientists think about the construction and interpretation of interstellar messages. I do not suggest that ritual activities themselves provide more than limited potential for communication with ETI. However, the structural elements of ritual and the manner in which meaning is conveyed through the formality and repetition of ritual is at least to some extent decipherable cross-culturally and provides one way to think about how to express important aspects of humans and their cultures to ETI and to represent, if not specific meanings themselves, the fact that a message is meaningful.

  10. MapReduce Functions to Analyze Sentiment Information from Social Big Data

    OpenAIRE

    Ilkyu Ha; Bonghyun Back; Byoungchul Ahn

    2015-01-01

    Opinion mining, which extracts meaningful opinion information from large amounts of social multimedia data, has recently arisen as a research area. In particular, opinion mining has been used to understand the true meaning and intent of social networking site users. It requires efficient techniques to collect a large amount of social multimedia data and extract meaningful information from them. Therefore, in this paper, we propose a method to extract sentiment information from various types o...

  11. Psychological context of work meaningfulness

    Directory of Open Access Journals (Sweden)

    Karel Paulík

    2014-12-01

    Full Text Available There is a significant shift of approach to the management of organizations and workers in recent decades. This shift in management philosophy is characterized by converting from traditional, conventional (rather bureaucratic management models to rather humanistic/existential oriented models. This transition comes partly from the understanding that human resources are the most promising and effective way for organization development, partly from a shift in the understanding of the role of organizations in society. The key point of these approaches has become a "meaning" or "meaningfulness" in relation to the work and organization. The importance of work meaningfulness is not only in its potential to increase the competitiveness of organizations, but especially in its major (mostly positive impacts on the employee himself and his work (and by that the organization and its performance. Work meaningfulness is strongly connected to the work engagement, which represents the active personal participation in the work process, manifested by vigor, active cooperation, willingness to contribute to the company's success and dedication to work. Work engagement seems to be next important factor affecting work attitudes and achievements of employees. The paper gives an overview of various approaches to work meaningfulness and work engagement, on the basis of which authors propose new model of work meaningfulness with overlap to work engagement. The work meaningfulness is not seen as one-dimensional variable, but consists of complex of interacting factors and processes that define an individual perceived meaning and importance of the work. Meaningful work is influenced by three areas. The first is the organizational culture. This is defined as a specific pattern of values, norms, beliefs, attitudes and assumptions that are often not clearly expressed, but affect the way individuals behave in an organization and how things are done. The second area is the work

  12. When "no" might not quite mean "no"; the importance of informed and meaningful non-consent: results from a survey of individuals refusing participation in a health-related research project

    Directory of Open Access Journals (Sweden)

    McMurdo Marion ET

    2007-04-01

    -consent does not necessarily mean that a fully informed evaluation of the pros and cons of participation and non-participation has taken place. The meaningfulness of expressions of non-consent may therefore be a cause for concern and should be subject to further research. Many reasons for non-participation may be specific to a particular research topic or population. Information sheets should reflect this by going beyond standardised guidelines for their design and instead proactively seek out and address areas of concern or potential misunderstanding. The use of established behavioural theory in their design could also be considered.

  13. 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...

  14. 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...

  15. 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...

  16. 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.

  17. 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.

  18. 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…

  19. 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

  20. 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…

  1. 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…

  2. 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

  3. Towards a mathematical theory of meaningful communication

    Science.gov (United States)

    Corominas-Murtra, Bernat; Fortuny, Jordi; Solé, Ricard V.

    2014-04-01

    Meaning has been left outside most theoretical approaches to information in biology. Functional responses based on an appropriate interpretation of signals have been replaced by a probabilistic description of correlations between emitted and received symbols. This assumption leads to potential paradoxes, such as the presence of a maximum information associated to a channel that creates completely wrong interpretations of the signals. Game-theoretic models of language evolution and other studies considering embodied communicating agents show that the correct (meaningful) match resulting from agent-agent exchanges is always achieved and natural systems obviously solve the problem correctly. Inspired by the concept of duality of the communicative sign stated by the swiss linguist Ferdinand de Saussure, here we present a complete description of the minimal system necessary to measure the amount of information that is consistently decoded. Several consequences of our developments are investigated, such as the uselessness of a certain amount of information properly transmitted for communication among autonomous agents.

  4. Towards a mathematical theory of meaningful communication.

    Science.gov (United States)

    Corominas-Murtra, Bernat; Fortuny, Jordi; Solé, Ricard V

    2014-04-04

    Meaning has been left outside most theoretical approaches to information in biology. Functional responses based on an appropriate interpretation of signals have been replaced by a probabilistic description of correlations between emitted and received symbols. This assumption leads to potential paradoxes, such as the presence of a maximum information associated to a channel that creates completely wrong interpretations of the signals. Game-theoretic models of language evolution and other studies considering embodied communicating agents show that the correct (meaningful) match resulting from agent-agent exchanges is always achieved and natural systems obviously solve the problem correctly. Inspired by the concept of duality of the communicative sign stated by the swiss linguist Ferdinand de Saussure, here we present a complete description of the minimal system necessary to measure the amount of information that is consistently decoded. Several consequences of our developments are investigated, such as the uselessness of a certain amount of information properly transmitted for communication among autonomous agents.

  5. Towards a mathematical theory of meaningful communication

    Science.gov (United States)

    Corominas-Murtra, Bernat; Fortuny, Jordi; Solé, Ricard V.

    2014-01-01

    Meaning has been left outside most theoretical approaches to information in biology. Functional responses based on an appropriate interpretation of signals have been replaced by a probabilistic description of correlations between emitted and received symbols. This assumption leads to potential paradoxes, such as the presence of a maximum information associated to a channel that creates completely wrong interpretations of the signals. Game-theoretic models of language evolution and other studies considering embodied communicating agents show that the correct (meaningful) match resulting from agent-agent exchanges is always achieved and natural systems obviously solve the problem correctly. Inspired by the concept of duality of the communicative sign stated by the swiss linguist Ferdinand de Saussure, here we present a complete description of the minimal system necessary to measure the amount of information that is consistently decoded. Several consequences of our developments are investigated, such as the uselessness of a certain amount of information properly transmitted for communication among autonomous agents. PMID:24699312

  6. 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.

  7. Healthcare BI: a tool for meaningful analysis.

    Science.gov (United States)

    Rohloff, Rose

    2011-05-01

    Implementing an effective business intelligence (BI) system requires organizationwide preparation and education to allow for meaningful analysis of information. Hospital executives should take steps to ensure that: Staff entering data are proficient in how the data are to be used for decision making, and integration is based on clean data from primary sources of entry. Managers have the business acumen required for effective data analysis. Decision makers understand how multidimensional BI offers new ways of analysis that represent significant improvements over historical approaches using static reporting.

  8. The Use of Meaningful Reception Learning in Lesson on Classification

    OpenAIRE

    2013-01-01

    This paper begins with a learning theory of instruction. It describes how Meaningful Reception Learning can be used to teach in classification of items. Meaningful Reception Learning is a learning theory of instruction proposed by Ausubel who believed that learners can learn best when the new material being taught can be anchored into existing cognitive information in the learners. He also proposed the use of advance organizers as representations of the facts of the lesson. ...

  9. Providing meaningful care for families experiencing stillbirth: a meta-synthesis of qualitative evidence.

    Science.gov (United States)

    Peters, M D J; Lisy, K; Riitano, D; Jordan, Z; Aromataris, E

    2016-01-01

    The objective of this study was to explore the meaningfulness of non-pharmacological care experienced by families throughout the experience of stillbirth from diagnosis onwards. A comprehensive systematic review was conducted. Multiple sources were searched for relevant studies including gray literature. Studies were included if they reported the experiences of families with the care they received throughout the experience of stillbirth, from diagnosis onwards. Studies were assessed for methodological quality prior to inclusion. Qualitative findings were extracted from included studies and pooled using a meta-aggregative approach. This paper reports the results of one meta-synthesis from the systematic review. Ten qualitative studies of moderate to high quality informed this meta-synthesis. The meta-aggregative synthesis included 69 findings that informed the development of 10 categories and one final, synthesized finding. Emerging themes that underpinned the meaningfulness of care provided to parents experiencing stillbirth included: information provision, the need for emotional support and appropriate maternity ward environments and systems. The results of this meta-synthesis revealed the elements of care that were experienced as meaningful from the perspective of parents who had experienced stillbirth. Exploration of these elements has provided important detail to underpin a growing understanding of how parents experience care and what may help or hinder parents' experience of distress, anxiety and grief throughout the experience of stillbirth.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  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. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Field homology: a meaningful definition.

    Science.gov (United States)

    Cookson, K

    2001-02-01

    Field homology refers to populations of cells that derive from evolutionarily conserved regions of embryos but are distributed across sets of adult morphological structures that cannot be placed in one-to-one correspondance. The concept of field homology has proven especially attractive to comparative neurologists because it allows them to deal with the fact that sets of nuclei or nuclear subdivisions often cannot be compared on a one-to-one basis across phyletic groups. However, the concept of field homology has recently come under criticism. It has been argued that field homology is theoretically impossible because it requires sequences of developmental stages to be both evolutionarily conserved and evolutionarily modified. It has also been argued that field homology allows overly vague comparisons of adult morphological structures, fails to account for homologous structures that derive from non-homologous embryonic sources, and establishes overly rigid links between embryonic and adult morphology. All of these criticisms may be adequately addressed by explaining field homology in terms of differentiation. The present paper explains field homology in terms of differentiation using the amniote dorsal thalamus to illustrate major points. It is concluded that field homology is a meaningful concept when defined in terms of differentiation, applied to appropriate cases, and properly limited in its comparisons of adult structures.

  1. 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

  2. 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.

  3. 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.

  4. 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%.

  5. 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.

  6. 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....

  7. 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 ...

  8. 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.

  9. 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.

  10. VLSI architecture of NEO spike detection with noise shaping filter and feature extraction using informative samples.

    Science.gov (United States)

    Hoang, Linh; Yang, Zhi; Liu, Wentai

    2009-01-01

    An emerging class of multi-channel neural recording systems aims to simultaneously monitor the activity of many neurons by miniaturizing and increasing the number of recording channels. Vast volume of data from the recording systems, however, presents a challenge for processing and transmitting wirelessly. An on-chip neural signal processor is needed for filtering uninterested recording samples and performing spike sorting. This paper presents a VLSI architecture of a neural signal processor that can reliably detect spike via a nonlinear energy operator, enhance spike signal over noise ratio by a noise shaping filter, and select meaningful recording samples for clustering by using informative samples. The architecture is implemented in 90-nm CMOS process, occupies 0.2 mm(2), and consumes 0.5 mW of power.

  11. 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

  12. 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.

  13. 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.

  14. An algorithm for encryption of secret images into meaningful images

    Science.gov (United States)

    Kanso, A.; Ghebleh, M.

    2017-03-01

    Image encryption algorithms typically transform a plain image into a noise-like cipher image, whose appearance is an indication of encrypted content. Bao and Zhou [Image encryption: Generating visually meaningful encrypted images, Information Sciences 324, 2015] propose encrypting the plain image into a visually meaningful cover image. This improves security by masking existence of encrypted content. Following their approach, we propose a lossless visually meaningful image encryption scheme which improves Bao and Zhou's algorithm by making the encrypted content, i.e. distortions to the cover image, more difficult to detect. Empirical results are presented to show high quality of the resulting images and high security of the proposed algorithm. Competence of the proposed scheme is further demonstrated by means of comparison with Bao and Zhou's scheme.

  15. 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....

  16. 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.

  17. 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...

  18. 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

  19. 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.

  20. 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

  1. 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

  2. [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).

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Meaningful work, work engagement and organisational commitment

    Directory of Open Access Journals (Sweden)

    Madelyn Geldenhuys

    2014-02-01

    Full Text Available Orientation: Meaningful work can yield benefits for organisations and lead to positive work outcomes such as satisfied, engaged and committed employees, individual and organisational fulfilment, productivity, retention and loyalty.Research purpose: The aim of the study was to investigate the relationships amongst psychological meaningfulness, work engagement and organisational commitment and to test for a possible mediation effect of work engagement on the relationship between psychological meaningfulness and organisational commitment.Motivation for the study: Managers have to rethink ways of improving productivity and performance at work, due to the diverse, and in some instances escalating, needs of employees (e.g. financial support to uphold their interest in and enjoyment of working.Research approach, design and method: A quantitative approach was employed to gather the data for the study, utilising a cross-sectional survey design. The sample (n = 415 consisted of working employees from various companies and positions in Gauteng, South Africa.Main findings: The results confirmed a positive relationship between psychological meaningfulness, work engagement and organisational commitment. Further, psychological meaningfulness predicts work engagement, whilst psychological meaningfulness and work engagement predict organisational commitment.Practical/managerial implications: Employers identifying their employees’ commitment patterns and mapping out strategies for enhancing those that are relevant to organisational goals will yield positive work outcomes (e.g. employees who are creative, seek growth or challenges for themselves.Contribution/value-add: This study contributes to the literature through highlighting the impact that meaningful work has on sustaining employee commitment to the organisation.

  15. Reflections on Meaningfulness and its Social Relevance

    Directory of Open Access Journals (Sweden)

    Nicole Note

    2010-06-01

    Full Text Available Philosophers who write about the meaning of life are few nowadays. Thesubject has lost its attractiveness. Perceived from a viewpoint of logical positivism or language philosophy, the whole issue of meaningfulness seems rather pointless. It is often considered to be related to metaphysics, making it less suitable for philosophical inquiry. The topic of meaningfulness seems too intangible. Indeed, the few philosophers that have embarked on examining meaningfulness have proven to be well aware of the challenges this poses. At times they acknowledge that the more they concentrate on the subject, the more it seems to fall apart into unintelligible pieces about whichnothing of philosophical value can be said.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Sense of Life Meaningfulness in Drug Addicts

    Directory of Open Access Journals (Sweden)

    Kaczyńska Marta

    2017-07-01

    Full Text Available The article presents results of studies concerning the assessment of changes taking place in the existential sphere (the sense of life meaningfulness in persons addicted to drugs and subjected to therapy. The studies were conducted in MONAR – Addictions Prophylaxis and Treatment Center in Lublin. 25 patients of the Center, aged 17 to 58 years, were examined. In the first part, concerning the sense of life meaningfulness the control group consisted of persons without addictions. In the second part of the studies, in examining differences between levels of addiction and the sense of life meaningfulness in addicts from various therapeutic- rehabilitation centers, the control group consisted of patients from MONAR Center in Głoskowo. We used the method of diagnostic sounding with the application of Screening Test Questionnaire concerning drug addiction, based on ICD-10 criteria and Life Meaningfulness Scale (PIL. On the basis of study results the level of the sense of life meaningfulness in persons addicted to drugs was determined. The performed analysis of empirical study results revealed that the persons strongly addicted to drugs demonstrate a lower level of the sense of life meaningfulness.

  8. 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.

  9. 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.

  10. 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.

  11. 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。

  12. 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/.

  13. 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.

  14. 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.

  15. 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.

  16. A meaningful workplace: Framework, space and context

    Directory of Open Access Journals (Sweden)

    Petrus L. Steenkamp

    2013-01-01

    Full Text Available An attempt was made to describe and to eventually implement work space that can be defined as psychologically meaningful and which has increased during the past 5−10 years. Indications are that various researchers on different continents have embarked on a journey to describe the meaningful workplace. Such a workplace is more than a geographical location, it is psychological space; space where the individual employee performs tasks that construe his or her work role, in collaboration with other individuals, within a framework of predetermined time frames, according to certain procedures, based on identified needs and within a formal workflow structure that is normally referred to as the organisation. Within this framework employees become alienated as a result of which the organisation as well as the individual suffer. The organisation experiences a loss of productivity, quality, innovation, et cetera, and the employee a loss of meaning in life and work. Yet, the workplace remains the space where meaning can be gained. It is both the framework and context for meaningfulness at work. Within this framework certain factors and constitutive elements play a facilitating role in experiencing meaningfulness. Various factors including values, and imbedded therein, the Protestant Ethic (PE, (and various other factors, such as for instance spirituality, culture, leadership and management style, etc., play an important role as facilitating factors towards the experience of meaningfulness at work. Developing a framework and context, on a conceptual level for the positioning of these factors as contributories towards the meaningful workplace, is a first priority. This is what this article is about: to conceptualise the workplace as psychological space, framework and context for understanding the contributory role of PE (and other factors towards the experience of meaningfulness at work. The positioning of values and the PE as Max Weber understood the

  17. 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.

  18. 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 ...

  19. 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...

  20. 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

    In the realm of knee pathology, magnetic resonance imaging (MRI) has the advantage of visualising all structures within the knee joint, which makes it a valuable tool for increasing diagnostic accuracy and planning surgical treatments. Therefore, clinical narratives found in MRI reports convey valuable diagnostic information. A range of studies have proven the feasibility of natural language processing for information extraction from clinical narratives. However, no study focused specifically on MRI reports in relation to knee pathology, possibly due to the complexity of knee anatomy and a wide range of conditions that may be associated with different anatomical entities. In this paper we describe KneeTex, an information extraction system that operates in this domain. As an ontology-driven information extraction system, KneeTex makes active use of an ontology to strongly guide and constrain text analysis. We used automatic term recognition to facilitate the development of a domain-specific ontology with sufficient detail and coverage for text mining applications. In combination with the ontology, high regularity of the sublanguage used in knee MRI reports allowed us to model its processing by a set of sophisticated lexico-semantic rules with minimal syntactic analysis. The main processing steps involve named entity recognition combined with coordination, enumeration, ambiguity and co-reference resolution, followed by text segmentation. Ontology-based semantic typing is then used to drive the template filling process. We adopted an existing ontology, TRAK (Taxonomy for RehAbilitation of Knee conditions), for use within KneeTex. The original TRAK ontology expanded from 1,292 concepts, 1,720 synonyms and 518 relationship instances to 1,621 concepts, 2,550 synonyms and 560 relationship instances. This provided KneeTex with a very fine-grained lexico-semantic knowledge base, which is highly attuned to the given sublanguage. Information extraction results were evaluated

  1. 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.

  2. 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

  3. 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...

  4. Work engagement and meaningful work across generational cohorts

    Directory of Open Access Journals (Sweden)

    Crystal Hoole

    2015-03-01

    261 participants across several financial institutions in Gauteng, including three generational cohorts (Baby Boomers, Generation X and Generation Y. Main findings: A moderate relationship was found to exist between work engagement and meaningful work. The Baby Boomer generation experiences the highest levels of engagement and meaningful work. Significant differences were found between Baby Boomers and Generation X and Baby Boomers and Generation Y. No significant difference were noted between Generation X and Generation Y.Practical/managerial implications: A one-size-fits-all strategy to improve work engagement and the sense of meaning in work does not exist. Results of this study suggest that various approaches based on the needs of each cohort may be required in order to sustain engagement. Older workers in particular prove to be far more valuable and productive and should be treated with care.Contribution: Whilst a large amount of information exists in terms of generational cohorts, not all findings are supported by empirical research to link the concept of work engagement to the different generational cohorts. The conventional belief that older people are less engaged and do not find meaning in their work has been proven to be a misconception, which highlights the danger of stereotypical beliefs. The findings suggest that older employees are still very valuable resources and can contribute significantly to the organisation’s success, but have different needs and values than other age groups. Customised engagement strategies tailored towards different generational cohorts might be more beneficial.

  5. 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.

  6. 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/....

  7. The challenge of a meaningful job

    DEFF Research Database (Denmark)

    Jepsen, Ingrid

    2015-01-01

    and the feeling of doing high quality care generate job satisfaction. The obligation and pressure to perform well and the disadvantages on the midwives’ private lives is counterbalanced by the feeling of doing a meaningful and important job. Working in caseload midwifery creates a feeling of working in a self...... is a work form with an embedded and inevitable commitment and obligation that brings forward the midwife’s desire to do her utmost and in return receive appreciation, social recognition and a meaningful job with great job satisfaction. There is a balance between the advantages of a meaningful job......-form. The number of women per full time midwife, as well as the succession rate, has to be surveilled as job-satisfaction is dependent on the midwives’ capability of still fulfilling expectations....

  8. Antecedents and outcomes of meaningful work among school teachers

    National Research Council Canada - National Science Library

    Elmari Fouché; Sebastiaan (Snr) Rothmann; Corne van der Vyver

    2017-01-01

    .... Meaningful work might affect these employee and organisational outcomes. Research purpose: The aim of this study was to investigate antecedents and outcomes of meaningful work among school teachers...

  9. 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.

  10. 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

  11. 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.

  12. Meaningful Interaction in a Local Context

    DEFF Research Database (Denmark)

    Holck, Ulla

    2006-01-01

    This keynote is based on a Ph.D. thesis on development of socially meaningful interaction in music therapy with children with very poor communication skills (Holck 2002). The aim was to identify some of the conditions, whereby actions can be understood as meaningful - that is, whereby the child a...... Music Therapy Congress, June 16-20, 2004 Jyväskylä, Finland. P. 1094-1110. eBook (PDF) available at MusicTherapyToday.com Vol.6. Issue 4 (November 2005)....

  13. Meaningful Interaction in a Local Context

    DEFF Research Database (Denmark)

    Holck, Ulla

    2006-01-01

    This keynote is based on a Ph.D. thesis on development of socially meaningful interaction in music therapy with children with very poor communication skills (Holck 2002). The aim was to identify some of the conditions, whereby actions can be understood as meaningful - that is, whereby the child a...... Music Therapy Congress, June 16-20, 2004 Jyväskylä, Finland. P. 1094-1110. eBook (PDF) available at MusicTherapyToday.com Vol.6. Issue 4 (November 2005)....

  14. 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%.

  15. Students' Meaningful Learning Orientation and Their Meaningful Understandings of Meiosis and Genetics.

    Science.gov (United States)

    Cavallo, Ann Liberatore

    This 1-week study explored the extent to which high school students (n=140) acquired meaningful understanding of selected biological topics (meiosis and the Punnett square method) and the relationship between these topics. This study: (1) examined "mental modeling" as a technique for measuring students' meaningful understanding of the…

  16. 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.

  17. 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.

  18. 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.

  19. Visually Meaningful Histopathological Features for Automatic Grading of Prostate Cancer.

    Science.gov (United States)

    Niazi, M Khalid Khan; Keluo Yao; Zynger, Debra L; Clinton, Steven K; Chen, James; Koyuturk, Mehmet; LaFramboise, Thomas; Gurcan, Metin

    2017-07-01

    Histopathologic features, particularly Gleason grading system, have contributed significantly to the diagnosis, treatment, and prognosis of prostate cancer for decades. However, prostate cancer demonstrates enormous heterogeneity in biological behavior, thus establishing improved prognostic and predictive markers is particularly important to personalize therapy of men with clinically localized and newly diagnosed malignancy. Many automated grading systems have been developed for Gleason grading but acceptance in the medical community has been lacking due to poor interpretability. To overcome this problem, we developed a set of visually meaningful features to differentiate between low- and high-grade prostate cancer. The visually meaningful feature set consists of luminal and architectural features. For luminal features, we compute: 1) the shortest path from the nuclei to their closest luminal spaces; 2) ratio of the epithelial nuclei to the total number of nuclei. A nucleus is considered an epithelial nucleus if the shortest path between it and the luminal space does not contain any other nucleus; 3) average shortest distance of all nuclei to their closest luminal spaces. For architectural features, we compute directional changes in stroma and nuclei using directional filter banks. These features are utilized to create two subspaces; one for prostate images histopathologically assessed as low grade and the other for high grade. The grade associated with a subspace, which results in the minimum reconstruction error is considered as the prediction for the test image. For training, we utilized 43 regions of interest (ROI) images, which were extracted from 25 prostate whole slide images of The Cancer Genome Atlas (TCGA) database. For testing, we utilized an independent dataset of 88 ROIs extracted from 30 prostate whole slide images. The method resulted in 93.0% and 97.6% training and testing accuracies, respectively, for the spectrum of cases considered. The

  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. 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. 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.

  3. 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.

  4. Literature as a Meaningful Life Laboratory

    NARCIS (Netherlands)

    Kurakin, Dmitry

    2010-01-01

    Meaningful life is emotionally marked off. That's the general point that Johansen (IPBS: Integrative Psychological & Behavioral Science 44, 2010) makes which is of great importance. Fictional abstractions use to make the point even more salient. As an example I've examined Borges' famous fiction sto

  5. Fishing for meaningful units in connected speech

    DEFF Research Database (Denmark)

    Henrichsen, Peter Juel; Christiansen, Thomas Ulrich

    2009-01-01

    In many branches of spoken language analysis including ASR, the set of smallest meaningful units of speech is taken to coincide with the set of phones or phonemes. However, fishing for phones is difficult, error-prone, and computationally expensive. We present an experiment, based on machine...

  6. Meaningful Use of School Health Data

    Science.gov (United States)

    Johnson, Kathleen Hoy; Bergren, Martha Dewey

    2011-01-01

    Meaningful use (MU) of Electronic Health Records (EHRs) is an important development in the safety and security of health care delivery in the United States. Advancement in the use of EHRs occurred with the passage of the American Recovery and Reinvestment Act of 2009, which provides incentives for providers to support adoption and use of EHRs.…

  7. A meaningful workplace: Framework, space and context

    African Journals Online (AJOL)

    2013-02-14

    Feb 14, 2013 ... at work. Within this framework certain factors and constitutive elements play a facilitating ... The original study identified the dimensions (on a conceptual level) that ... Workplace'; to expand the theoretical base of the construct. 'Meaningful .... The experience of meaninglessness has major effects such.

  8. Meaningful Experiences in the Counseling Process

    Science.gov (United States)

    Sackett, Corrine; Lawson, Gerard; Burge, Penny L.

    2012-01-01

    Researchers examined the experiences of a counseling session from the perspectives of counselors-intraining (CITs) and clients. Post-session phenomenological interviews were conducted to elicit participants' meaningful experiences, and the analysis revealed both similarities and differences. Researchers found the following themes most meaningful…

  9. Extracting Primary Objects by Video Co-Segmentation

    NARCIS (Netherlands)

    Lou, Z.; Gevers, T.

    2014-01-01

    Video object segmentation is a challenging problem. Without human annotation or other prior information, it is hard to select a meaningful primary object from a single video, so extracting the primary object across videos is a more promising approach. However, existing algorithms consider the proble

  10. 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.

  11. 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.

  12. Ocean Thermal Extractable Energy Visualization

    Energy Technology Data Exchange (ETDEWEB)

    Ascari, Matthew [Lockheed Martin Corporation, Bethesda, MD (United States)

    2012-10-28

    The Ocean Thermal Extractable Energy Visualization (OTEEV) project focuses on assessing the Maximum Practicably Extractable Energy (MPEE) from the world’s ocean thermal resources. MPEE is defined as being sustainable and technically feasible, given today’s state-of-the-art ocean energy technology. Under this project the OTEEV team developed a comprehensive Geospatial Information System (GIS) dataset and software tool, and used the tool to provide a meaningful assessment of MPEE from the global and domestic U.S. ocean thermal resources.

  13. 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.

  14. 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.

  15. 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...

  16. 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

  17. 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.

  18. Are students ready for meaningful use?

    Science.gov (United States)

    Ferenchick, Gary S.; Solomon, David; Mohmand, Asad; Towfiq, Basim; Kavanaugh, Kevin; Warbasse, Larry; Addison, James; Chames, Frances

    2013-01-01

    Background The meaningful use (MU) of electronic medical records (EMRs) is being implemented in three stages. Key objectives of stage one include electronic analysis of data entered into structured fields, using decision-support tools (e.g., checking drug–drug interactions [DDI]) and electronic information exchange. Objective The authors assessed the performance of medical students on 10 stage-one MU tasks and measured the correlation between students’ MU performance and subsequent end-of-clerkship professionalism assessments and their grades on an end-of-year objective structured clinical examination. Participants Two-hundred and twenty-two third-year medical students on the internal medicine (IM) clerkship. Design/main measures From July 2010 to February 2012, all students viewed 15 online tutorials covering MU competencies. The authors measured student MU documentation and performance in the chart of a virtual patient using a fully functional training EMR. Specific MU measurements included, adding: a new problem, a new medication, an advanced directive, smoking status, the results of screening tests; and performing a DDI (in which a major interaction was probable), and communicating a plan for this interaction. Key results A total of 130 MU errors were identified. Sixty-eight (30.6%) students had at least one error, and 30 (13.5%) had more than one (range 2–6). Of the 130 errors, 90 (69.2%) were errors in structured data entry. Errors occurred in medication dosing and instructions (18%), DDI identification (12%), documenting smoking status (15%), and colonoscopy results (23%). Students with MU errors demonstrated poorer performance on end-of-clerkship professionalism assessments (r =−0.112, p=0.048) and lower observed structured clinical examination (OSCE) history-taking skills (r =−0.165, p=0.008) and communication scores (r= − 0.173, p=0.006). Conclusions MU errors among medical students are common and correlate with subsequent poor performance in

  19. Are students ready for meaningful use?

    Directory of Open Access Journals (Sweden)

    Gary S. Ferenchick

    2013-11-01

    Full Text Available Background: The meaningful use (MU of electronic medical records (EMRs is being implemented in three stages. Key objectives of stage one include electronic analysis of data entered into structured fields, using decision-support tools (e.g., checking drug–drug interactions [DDI] and electronic information exchange. Objective: The authors assessed the performance of medical students on 10 stage-one MU tasks and measured the correlation between students’ MU performance and subsequent end-of-clerkship professionalism assessments and their grades on an end-of-year objective structured clinical examination. Participants: Two-hundred and twenty-two third-year medical students on the internal medicine (IM clerkship. Design/main measures: From July 2010 to February 2012, all students viewed 15 online tutorials covering MU competencies. The authors measured student MU documentation and performance in the chart of a virtual patient using a fully functional training EMR. Specific MU measurements included, adding: a new problem, a new medication, an advanced directive, smoking status, the results of screening tests; and performing a DDI (in which a major interaction was probable, and communicating a plan for this interaction. Key results: A total of 130 MU errors were identified. Sixty-eight (30.6% students had at least one error, and 30 (13.5% had more than one (range 2–6. Of the 130 errors, 90 (69.2% were errors in structured data entry. Errors occurred in medication dosing and instructions (18%, DDI identification (12%, documenting smoking status (15%, and colonoscopy results (23%. Students with MU errors demonstrated poorer performance on end-of-clerkship professionalism assessments (r=−0.112, p=0.048 and lower observed structured clinical examination (OSCE history-taking skills (r=−0.165, p=0.008 and communication scores (r=− 0.173, p=0.006. Conclusions: MU errors among medical students are common and correlate with subsequent poor

  20. 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%.

  1. 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...

  2. 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.

  3. 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)

  4. 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.

  5. 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.

  6. 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.

  7. [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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. Geographical origin: meaningful reference or marketing tool?

    DEFF Research Database (Denmark)

    Hedegaard, Liselotte

    2015-01-01

    origin was the result of a crisis in French wine-production in the early 20th century. Labelling was intended to protect the reputation of a product in terms of quality and taste by referring to parcels of land where specific traditions are maintained and the resulting products embedded in collective....... In this respect, the place of origin becomes more than a point on a map. It becomes representations of the past and expectations of taste in the sense of re-tasting It is likely that the differences in consumer-perceptions reside in the interplay between origin and provenance. In France, geographical origin...... constitutes a meaningful reference to a link between food and place that represents expectations of taste and quality. In Denmark, this link is not attributed similar meaning and, hence, the difference between meaningful references and images formed through the language of marketing is less discernible...

  13. 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.

  14. 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

  15. 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%.

  16. 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%.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Situated Cognition and Strategies for Meaningful Learning

    Directory of Open Access Journals (Sweden)

    Frida Díaz Barriga Arceo

    2003-11-01

    Full Text Available The paper describes the principles underlying situated cognition linked to the Vygotskian sociocultural perspective, which state that situated cognition is both a part and the result of activity, context and culture. It highlights the importance of mediation, the joint construction of meaning and the mechanism of adapted assistance. There are examples of instructional approaches which vary in cultural relevance and the type of social activity they elicit. It also presents a number of meaningful learning strategies based on situated experiential teaching (authentic problem solving, learning while in service, case studies, projects, situated simulation, among others. Finally, the paper deals with the potentiality of empowerment.

  8. Meaningful learning of cell division and genetics

    OpenAIRE

    Hung, Yuen-mang, Venus; 洪婉萌

    2014-01-01

    Meaningful learning is where the learner actively integrates new knowledge to his or her existing knowledge base. It involves the use of cognitive strategies and self-regulation. What motivates a learner to do so is found to be related to variables like the motivational beliefs, personal goal orientation and affect as well as the perception towards the teacher and his or her classroom context. The study surveyed a group of S6 biology students to examine the correlations between some of the di...

  9. Making a meaningful contribution to theory

    DEFF Research Database (Denmark)

    Boer, Harry; Holweg, Matthias; Kilduff, Martin

    2015-01-01

    discussed in the “OM Theory” workshop in Dublin in 2011 and the special sessions at the 2011 and the 2013 EurOMA Conferences in Cambridge and Dublin. Design/methodology/approach – This paper presents six short essays that explore the role and use of theory in management research, and specifically ask what...... is a good or meaningful contribution to theory. The authors comment on the current state of theory in OperationsManagement (OM) (Harry Boer), the type of theories the authors have in OM (Chris Voss), the role of theory in increasing the general understanding of OM problems (Roger Schmenner), whether...

  10. 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.

  11. 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

  12. Callings, work role fit, psychological meaningfulness and work ...

    African Journals Online (AJOL)

    Scale, Work-Life Questionnaire, Psychological Meaningfulness Scale, and Work Engagement. Scale were .... their work life meaningful and 82% would continue to work even if they could receive ..... A proposed model of lifestyle balance.

  13. 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

  14. The Retention of Meaningful Understanding of Meiosis and Genetics.

    Science.gov (United States)

    Cavallo, Ann Liberatore

    This study investigated the retention of meaningful understanding of the biological topics of meiosis, the Punnett square method and the relations between these two topics. This study also explored the predictive influence of students' general tendency to learn meaningfully or by rote (meaningful learning orientation), prior knowledge of meiosis,…

  15. 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.

  16. Spectral embedding finds meaningful (relevant structure in image and microarray data

    Directory of Open Access Journals (Sweden)

    Solka Jeffrey L

    2006-02-01

    Full Text Available Abstract Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA is a linear dimensionality reduction (DR method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method. This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent

  17. A meaningful expansion around detailed balance

    CERN Document Server

    Colangeli, Matteo; Wynants, Bram

    2011-01-01

    We consider Markovian dynamics modeling open mesoscopic systems which are driven away from detailed balance by a nonconservative force. A systematic expansion is obtained of the stationary distribution around an equilibrium reference, in orders of the nonequilibrium forcing. The first order around equilibrium has been known since the work of McLennan (1959), and involves the transient irreversible entropy flux. The expansion generalizes the McLennan formula to higher orders, complementing the entropy flux with the dynamical activity. The latter is more kinetic than thermodynamic and is a possible realization of Landauer's insight (1975) that, for nonequilibrium, the relative occupation of states also depends on the noise along possible escape routes. In that way nonlinear response around equilibrium can be meaningfully discussed in terms of two main quantities only, the entropy flux and the dynamical activity. The expansion makes mathematical sense as shown in the simplest cases from exponential ergodicity.

  18. Meaningful Academic Work as Praxis in Emergence

    Directory of Open Access Journals (Sweden)

    Keijo Räsänen

    2008-01-01

    Full Text Available The managerial form of university governance has changed the conditions of academic work in many countries. While some academics consider this a welcome development, others experience it as a threat to their autonomy and to the meaningfulness of their work. This essay suggests a stance in response to the current conditions that should serve especially the latter group of academics. The claim is that by approaching academic work as a potential praxis in emergence, it is possible to appreciate local, autonomous activity in renewing academic work. Even if such efforts remain difficult, dispersed in space, discontinuous in time, and incomplete, they may provide a sense of direction and keep up hope. The conception of praxis is a way of articulating the mission of such efforts; simultaneously, it is also a way of defining an epistemic object for research on academic work.

  19. The Structures of Meaningful Life Stories

    Directory of Open Access Journals (Sweden)

    Owen Flanagan

    2008-12-01

    Full Text Available Life’s meaning is a matter of how we live in this life. Whatever meaning a life has for the creature whose life itis ends when bodily death occurs. When someone dies the meaning of their life is over for them, in first person.But the meaning of a life for others, for those in relation with the dead person, does not end when a person dies.Our lives, be they good or bad, leave effects, ripples – memories – on others who are different because of us,and future generations who will feel the effects of our being – certainly after long enough time, without everknowing that we existed. This is all the meaning we can reasonably expect a human life to have. But manypeople think that this much meaning is not enough, that for life to be truly meaningful there must be somethingthat makes for eternal or transcendent meaning.

  20. 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.

  1. 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.

  2. Spatial anomaly detection in sensor networks using neighborhood information

    NARCIS (Netherlands)

    Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

    2016-01-01

    The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capabil- ity, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

  3. 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.

  4. 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 .

  5. 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.

  6. Large datasets: Segmentation, feature extraction, and compression

    Energy Technology Data Exchange (ETDEWEB)

    Downing, D.J.; Fedorov, V.; Lawkins, W.F.; Morris, M.D.; Ostrouchov, G.

    1996-07-01

    Large data sets with more than several mission multivariate observations (tens of megabytes or gigabytes of stored information) are difficult or impossible to analyze with traditional software. The amount of output which must be scanned quickly dilutes the ability of the investigator to confidently identify all the meaningful patterns and trends which may be present. The purpose of this project is to develop both a theoretical foundation and a collection of tools for automated feature extraction that can be easily customized to specific applications. Cluster analysis techniques are applied as a final step in the feature extraction process, which helps make data surveying simple and effective.

  7. The measurement of water scarcity: Defining a meaningful indicator.

    Science.gov (United States)

    Damkjaer, Simon; Taylor, Richard

    2017-09-01

    Metrics of water scarcity and stress have evolved over the last three decades from simple threshold indicators to holistic measures characterising human environments and freshwater sustainability. Metrics commonly estimate renewable freshwater resources using mean annual river runoff, which masks hydrological variability, and quantify subjectively socio-economic conditions characterising adaptive capacity. There is a marked absence of research evaluating whether these metrics of water scarcity are meaningful. We argue that measurement of water scarcity (1) be redefined physically in terms of the freshwater storage required to address imbalances in intra- and inter-annual fluxes of freshwater supply and demand; (2) abandons subjective quantifications of human environments and (3) be used to inform participatory decision-making processes that explore a wide range of options for addressing freshwater storage requirements beyond dams that include use of renewable groundwater, soil water and trading in virtual water. Further, we outline a conceptual framework redefining water scarcity in terms of freshwater storage.

  8. 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.

  9. Meaningful use of pharmacogenomics in health records: semantics should be made explicit.

    Science.gov (United States)

    Shabo Shvo, Amnon

    2010-01-01

    The recent emphasis on 'meaningful use' of electronic health records in health information technology reforms (e.g., as in the US stimulus package) can leverage the pharmacogenomics field. In order for clinical trials outcomes, based on pharmacogenomics research, to be meaningfully and effectively used in clinical practice there is a need to make health semantics explicit. Often, semantics is merely implicit in both the research and practice worlds and is buried in unstructured and disconnected descriptions of the data or just in the heads of human experts. Meaningful semantics includes rich metadata, but more importantly, the context of each discrete data item and how it relates to other data items in a specific dataset, as well as how it fits within the entire health record of an individual and how it references up-to-date clinical knowledge. Properly-built electronic health records systems based on standards could provide meaningful semantics on the healthcare side, while the fields of research and clinical trials need to come closer to healthcare in its data and knowledge representations in a way that lends itself to personalized medicine. The purpose of this review is to explore how evidence created by pharmacogenomics can be meaningfully delivered to healthcare through new approaches, such as electronic health records systems and information models.

  10. A meaningful MESS (Medical Education Scholarship Support

    Directory of Open Access Journals (Sweden)

    Shari A. Whicker

    2016-07-01

    Full Text Available Background: Graduate medical education faculty bear the responsibility of demonstrating active research and scholarship; however, faculty who choose education-focused careers may face unique obstacles related to the lack of promotion tracks, funding, career options, and research opportunities. Our objective was to address education research and scholarship barriers by providing a collaborative peer-mentoring environment and improve the production of research and scholarly outputs. Methods: We describe a Medical Education Scholarship Support (MESS group created in 2013. MESS is an interprofessional, multidisciplinary peer-mentoring education research community that now spans multiple institutions. This group meets monthly to address education research and scholarship challenges. Through this process, we develop new knowledge, research, and scholarly products, in addition to meaningful collaborations. Results: MESS originated with eight founding members, all of whom still actively participate. MESS has proven to be a sustainable unfunded local community of practice, encouraging faculty to pursue health professions education (HPE careers and fostering scholarship. We have met our original objectives that involved maintaining 100% participant retention; developing increased knowledge in at least seven content areas; and contributing to the development of 13 peer-reviewed publications, eight professional presentations, one Masters of Education project, and one educational curriculum. Discussion: The number of individuals engaged in HPE research continues to rise. The MESS model could be adapted for use at other institutions, thereby reducing barriers HPE researchers face, providing an effective framework for trainees interested in education-focused careers, and having a broader impact on the education research landscape.

  11. Science Faculty Improving Teaching Practice: Identifying Needs and Finding Meaningful Professional Development

    Science.gov (United States)

    Bouwma-Gearhart, Jana

    2012-01-01

    While research into the effectiveness of teaching professional development for postsecondary educators has increased over the last 40 years, little is known about science faculty members' teaching professional development needs and their perceptions regarding what constitutes meaningful teaching professional development. Informed by an extensive…

  12. Does (Non-)Meaningful Sensori-Motor Engagement Promote Learning With Animated Physical Systems?

    NARCIS (Netherlands)

    Pouw, Wim T J L; Eielts, Charly; van Gog, Tamara; Zwaan, Rolf A.; Paas, Fred

    2016-01-01

    Previous research indicates that sensori-motor experience with physical systems can have a positive effect on learning. However, it is not clear whether this effect is caused by mere bodily engagement or the intrinsically meaningful information that such interaction affords in performing the learnin

  13. 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

  14. 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

  15. 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.

  16. WHATSAPP CONTRIBUTIONS IN SPANISH TEACHING: A PERSPECTIVE OF MEANINGFUL AND COLLABORATIVE LEARNING

    Directory of Open Access Journals (Sweden)

    Iandra Maria Weirich da Silva Coelho

    2017-08-01

    Full Text Available This article describes a didactic proposal, mediated by the use of WhatsApp as a potential tool for the teaching of Spanish as an additional language. Activities are drawn from collaborative and meaningful practice with authentic situations of the language usage, taking by reference the theoretical construct of the Theory of Meaningful Learning (AUSUBEL, 2003 and Collaborative Practice of Writing. The results identify positive contributions about the increased interest and motivation of students, promotion of discursive competence, interactivity, autonomy, about actions involving the authorship and collaborative construction in information network for knowledge sharing.

  17. Stimulus set meaningfulness and neurophysiological differentiation: a functional magnetic resonance imaging study.

    Directory of Open Access Journals (Sweden)

    Melanie Boly

    Full Text Available A meaningful set of stimuli, such as a sequence of frames from a movie, triggers a set of different experiences. By contrast, a meaningless set of stimuli, such as a sequence of 'TV noise' frames, triggers always the same experience--of seeing 'TV noise'--even though the stimuli themselves are as different from each other as the movie frames. We reasoned that the differentiation of cortical responses underlying the subject's experiences, as measured by Lempel-Ziv complexity (incompressibility of functional MRI images, should reflect the overall meaningfulness of a set of stimuli for the subject, rather than differences among the stimuli. We tested this hypothesis by quantifying the differentiation of brain activity patterns in response to a movie sequence, to the same movie scrambled in time, and to 'TV noise', where the pixels from each movie frame were scrambled in space. While overall cortical activation was strong and widespread in all conditions, the differentiation (Lempel-Ziv complexity of brain activation patterns was correlated with the meaningfulness of the stimulus set, being highest in the movie condition, intermediate in the scrambled movie condition, and minimal for 'TV noise'. Stimulus set meaningfulness was also associated with higher information integration among cortical regions. These results suggest that the differentiation of neural responses can be used to assess the meaningfulness of a given set of stimuli for a given subject, without the need to identify the features and categories that are relevant to the subject, nor the precise location of selective neural responses.

  18. 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=.

  19. 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...

  20. 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.

  1. Meaningful Literacy: Writing Poetry in the Language Classroom

    Science.gov (United States)

    Hanauer, David I.

    2012-01-01

    This paper develops the concept of meaningful literacy and offers a classroom methodology--poetry writing--that manifests this approach to ESL/EFL literacy instruction. The paper is divided into three sections. The first deals with the concept of meaningful literacy learning in second and foreign language pedagogy; the second summarizes empirical…

  2. Self-Determination and Meaningful Work: Exploring Socioeconomic Constraints

    Directory of Open Access Journals (Sweden)

    Blake A Allan

    2016-02-01

    Full Text Available This study examined a model of meaningful work among a diverse sample of working adults. From the perspectives of Self-Determination Theory and the Psychology of Working Framework, we tested a structural model with social class and work volition predicting SDT motivation variables, which in turn predicted meaningful work. Partially supporting hypotheses, work volition was positively related to internal regulation and negatively related to amotivation, whereas social class was positively related to external regulation and amotivation. In turn, internal regulation was positively related to meaningful work, whereas external regulation and amotivation were negatively related to meaningful work. Indirect effects from work volition to meaningful work via internal regulation and amotivation were significant, and indirect effects from social class to meaningful work via external regulation and amotivaiton were significant. This study highlights the important relations between SDT motivation variables and meaningful work, especially the large positive relation between internal regulation and meaningful work. However, results also reveal that work volition and social class may play critical roles in predicting internal regulation, external regulation, and amotivation.

  3. Self-Determination and Meaningful Work: Exploring Socioeconomic Constraints.

    Science.gov (United States)

    Allan, Blake A; Autin, Kelsey L; Duffy, Ryan D

    2016-01-01

    This study examined a model of meaningful work among a diverse sample of working adults. From the perspectives of Self-Determination Theory and the Psychology of Working Framework, we tested a structural model with social class and work volition predicting SDT motivation variables, which in turn predicted meaningful work. Partially supporting hypotheses, work volition was positively related to internal regulation and negatively related to amotivation, whereas social class was positively related to external regulation and amotivation. In turn, internal regulation was positively related to meaningful work, whereas external regulation and amotivation were negatively related to meaningful work. Indirect effects from work volition to meaningful work via internal regulation and amotivation were significant, and indirect effects from social class to meaningful work via external regulation and amotivation were significant. This study highlights the important relations between SDT motivation variables and meaningful work, especially the large positive relation between internal regulation and meaningful work. However, results also reveal that work volition and social class may play critical roles in predicting internal regulation, external regulation, and amotivation.

  4. Developing Meaningfulness at Work through Emotional Intelligence Training

    Science.gov (United States)

    Thory, Kathryn

    2016-01-01

    To date, there remains a significant gap in the human resource development (HRD) literature in understanding how training and development contributes to meaningful work. In addition, little is known about how individuals proactively make their work more meaningful. This article shows how emotional intelligence (EI) training promotes learning about…

  5. Meaningful Literacy: Writing Poetry in the Language Classroom

    Science.gov (United States)

    Hanauer, David I.

    2012-01-01

    This paper develops the concept of meaningful literacy and offers a classroom methodology--poetry writing--that manifests this approach to ESL/EFL literacy instruction. The paper is divided into three sections. The first deals with the concept of meaningful literacy learning in second and foreign language pedagogy; the second summarizes empirical…

  6. Characteristics of meaningful chemistry education - The case of water quality

    NARCIS (Netherlands)

    Westbroek, Hanna Barbara

    2005-01-01

    This thesis addresses the question of how to involve students in meaningful chemistry education by a proper implementation of three characteristics of meaningful: a context, a need-to-know approach and attention for student input. The characteristics were adopted as solution strategies for

  7. 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.

  8. 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,

  9. 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

  10. 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.

  11. A Study of the Meaningful Construction of Mental Schema in English Reading Comprehension

    Institute of Scientific and Technical Information of China (English)

    张静

    2014-01-01

    Schemata are abstract structures that represent what one holds to be generally true about the world. What people know exists in schemata hierarchies and this prior knowledge is activated when they encounter new information. Schema theory asserts that reading is an interactive process between the text and the reader. Such interaction involves the readers ’prior knowledge of schemata and the actual information in the text. Only be constructing appropriate and meaningful schemata, can readers compre-hend the text.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Improving Personal Characterization of Meaningful Activity in Adults with Chronic Conditions Living in a Low-Income Housing Community

    Directory of Open Access Journals (Sweden)

    Carrie A. Ciro

    2015-09-01

    Full Text Available Purpose: To understand how adults living in a low-income, public housing community characterize meaningful activity (activity that gives life purpose and if through short-term intervention, could overcome identified individual and environmental barriers to activity engagement. Methods: We used a mixed methods design where Phase 1 (qualitative informed the development of Phase 2 (quantitative. Focus groups were conducted with residents of two low-income, public housing communities to understand their characterization of meaningful activity and health. From these results, we developed a theory-based group intervention for overcoming barriers to engagement in meaningful activity. Finally, we examined change in self-report scores from the Meaningful Activity Participation Assessment (MAPA and the Engagement in Meaningful Activity Survey (EMAS. Results: Health literacy appeared to impact understanding of the questions in Phase 1. Activity availability, transportation, income and functional limitations were reported as barriers to meaningful activity. Phase 2 within group analysis revealed a significant difference in MAPA pre-post scores (p =0.007, but not EMAS (p =0.33. Discussion: Health literacy should be assessed and addressed in this population prior to intervention. After a group intervention, participants had a change in characterization of what is considered healthy, meaningful activity but reported fewer changes to how their activities aligned with their values.

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. The Omaha system and meaningful use: applications for practice, education, and research.

    Science.gov (United States)

    Martin, Karen S; Monsen, Karen A; Bowles, Kathryn H

    2011-01-01

    Meaningful use has become ubiquitous in the vocabulary of health information technology. It suggests that better healthcare does not result from the adoption of technology and electronic health records, but by increasing interoperability and informing clinical decisions at the point of care. Although the initial application of meaningful use was limited to eligible professionals and hospitals, it incorporates complex processes and workflow that involve all nurses, other healthcare practitioners, and settings. The healthcare community will become more integrated, and interdisciplinary practitioners will provide enhanced patient-centered care if electronic health records adopt the priorities of meaningful use. Standardized terminologies are a necessary component of such electronic health records. The Omaha System is an exemplar of a standardized terminology that enables meaningful use of clinical data to support and improve patient-centered clinical practice, education, and research. It is user-friendly, generates data that can be shared with patients and their families, and enables healthcare providers to analyze and exchange patient-centered coded data. Use of the Omaha System is increasing steadily in diverse practice, education, and research settings nationally and internationally.

  3. 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.

  4. 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

  5. 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…

  6. 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…

  7. 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.

  8. 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.

  9. Noun-Phrase Analysis in Unrestricted Text for Information Retrieval

    OpenAIRE

    Evans, David A.; Zhai, Chengxiang

    1996-01-01

    Information retrieval is an important application area of natural-language processing where one encounters the genuine challenge of processing large quantities of unrestricted natural-language text. This paper reports on the application of a few simple, yet robust and efficient noun-phrase analysis techniques to create better indexing phrases for information retrieval. In particular, we describe a hybrid approach to the extraction of meaningful (continuous or discontinuous) subcompounds from ...

  10. 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 ...

  11. 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.

  12. 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.

  13. 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.

  14. Redefining meaningful age groups in the context of disease.

    Science.gov (United States)

    Geifman, Nophar; Cohen, Raphael; Rubin, Eitan

    2013-12-01

    Age is an important factor when considering phenotypic changes in health and disease. Currently, the use of age information in medicine is somewhat simplistic, with ages commonly being grouped into a small number of crude ranges reflecting the major stages of development and aging, such as childhood or adolescence. Here, we investigate the possibility of redefining age groups using the recently developed Age-Phenome Knowledge-base (APK) that holds over 35,000 literature-derived entries describing relationships between age and phenotype. Clustering of APK data suggests 13 new, partially overlapping, age groups. The diseases that define these groups suggest that the proposed divisions are biologically meaningful. We further show that the number of different age ranges that should be considered depends on the type of disease being evaluated. This finding was further strengthened by similar results obtained from clinical blood measurement data. The grouping of diseases that share a similar pattern of disease-related reports directly mirrors, in some cases, medical knowledge of disease-age relationships. In other cases, our results may be used to generate new and reasonable hypotheses regarding links between diseases.

  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

  1. Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Konuma, Tsuyoshi [Icahn School of Medicine at Mount Sinai, Department of Structural and Chemical Biology (United States); Harada, Erisa [Suntory Foundation for Life Sciences, Bioorganic Research Institute (Japan); Sugase, Kenji, E-mail: sugase@sunbor.or.jp, E-mail: sugase@moleng.kyoto-u.ac.jp [Kyoto University, Department of Molecular Engineering, Graduate School of Engineering (Japan)

    2015-12-15

    Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

  2. A proposal of Potentially Meaningful Teaching Unit using concept maps

    Directory of Open Access Journals (Sweden)

    Thaís Rafaela Hilger

    2013-12-01

    Full Text Available This paper presents preliminary results from the implementation of a Potentially Meaningful Teaching Unit in four classes of third grade of secondary educational from a public school in the city of Bagé (Rio Grande do Sul. The proposed content deals with concepts related to Quantum Physics (quantization, uncertainty principle, state and superposition of states, presented in accordance with the sequence of eight steps of Potentially Meaningful Teaching Unit, seeking meaningful learning of these concepts. Are analyzed in this work mental maps and concept maps produced in pairs, as well as the comparison between them. Also presented are some comments from students about their development in the understanding of the concepts covered in the proposal. The proposal was a well received and, although the study is still in progress and part of a broader research, already provide evidence of significant learning, which is the goal of a Potentially Meaningful Teaching Unit.

  3. Meaningful work and secondary school teachers' intention to leave

    African Journals Online (AJOL)

    Hennie

    regarded as a key factor in low teacher morale and motivation. If incentives in ... the performance of the organisation negatively due ... influence meaningfulness at the workplace, namely ...... plemented to improve work-role fit of teachers and.

  4. PROMOTING MEANINGFUL LEARNING THROUGH CREATE-SHARE-COLLABORATE

    OpenAIRE

    Sailin, Siti Nazuar; Mahmor, Noor Aida

    2017-01-01

    Students in this 21st century are required to acquire these 4C skills: Critical thinking, Communication, Collaboration and Creativity. These skills can be integrated in the teaching and learning through innovative teaching that promotes active and meaningful learning. One way of integrating these skills is through collaborative knowledge creation and sharing. This paper providesan example of meaningful teaching and learning activities designed within the Create-Share-Collaborate instructional...

  5. To learn meaningfully and to classify in chemistry

    OpenAIRE

    María Victoria Alzate Cano

    2006-01-01

    In our context, the teaching of chemistry does not make enough emphasis on the chemical criteria of substances classification and the chances that these they for a meaningful learning of several kind of substances based on functional groups and on the differentiation between pure substances and homogeneous mixtures as well as and among other chemical and physical modifications. This teaching situation implies a devaluation of the relevance that meaningful comprehension has on c...

  6. Extracting information about the initial state from the black hole radiation

    CERN Document Server

    Lochan, Kinjalk

    2015-01-01

    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 the distortions of the black hole radiation from the thermal spectrum, which can be detected by the asymptotic observers. We identify the class of in-states which can be fully reconstructed from the information contained in the distortions at the semiclassical level. Even for the general in-state, we can uncover a specific amount of information about the initial state. For a large class of initial states, some specific observables defined in the initial Hilbert space are completely determined from the resulting final spectrum. These results suggest that a \\textit{classical} collapse scenario ignores this richness of information in the resulting spectrum and a consistent quantu...

  7. The effect of occupational meaningfulness on occupational commitment

    Directory of Open Access Journals (Sweden)

    Itai Ivtzan

    2014-11-01

    Full Text Available Existing research lacks a scholarly consensus on how to define and validly measure ‘meaningful work’ (e.g., Rosso, Dekas & Wrzesniewski, 2010. The following correlational study highlights the value of investigating meaningfulness in the context of occupational commitment. The study hypothesizes that occupational commitment is positively correlated with occupational meaningfulness, where meaningfulness is defined as the extent to which people’s occupations contribute to personal meaning in life. One-hundred and fifty-six full-time office based UK workers completed an online questionnaire including 18 questions measuring levels of occupational commitment (Meyer, Allen & Smith, 1993, in addition to six novel items measuring occupational meaningfulness. The results supported the hypothesis and also showed that the affective sub-type of occupational commitment had the highest correlation with occupational meaningfulness. Such results exhibit the importance of finding meaning at work, as well as the relevance of this to one’s level of commitment to his or her job. This paper argues that individuals should consider OM before choosing to take a specific role, whereas organizations ought to consider the OM of their potential candidates before recruiting them into a role. Possible directions for future research directions are also discussed.

  8. Meaningful work and mental health: job satisfaction as a moderator.

    Science.gov (United States)

    Allan, Blake A; Dexter, Chelsea; Kinsey, Rebecca; Parker, Shelby

    2016-11-12

    Depression, anxiety and stress are common problems for modern workers. Although having meaningful work, or work that is significant, facilitates personal growth, and contributes to the greater good, has been linked to better mental health, people's work might also need to be satisfying or enjoyable to improve outcomes. The purpose of the present study was to examine meaningful work's relation to mental health (i.e. depression, anxiety and stress) and investigate job satisfaction as a moderator of this relation. The study hypotheses were tested with a large, diverse sample recruited from an online source. Partially supporting hypotheses, when controlling for job satisfaction, meaningful work negatively correlated with depression but did not have a significant relation with anxiety and stress. Similarly, job satisfaction negatively predicted depression and stress. Furthermore, the relations between meaningful work and both anxiety and stress were moderated by job satisfaction. Specifically, only people perceiving their work as meaningful and satisfying reported less anxiety and stress. Although continued research is needed, employers and employees may have to target both the meaningfulness and job satisfaction to address the issues of stress and anxiety among working adults.

  9. A Novel Approach for Text Categorization of Unorganized data based with Information Extraction

    Directory of Open Access Journals (Sweden)

    Suneetha Manne,

    2011-07-01

    Full Text Available Internet has made a profound change in the lives of many enthusiastic innovators and researchers. The information available on the web has knocked the doors of Knowledge Discovery leading to a new Information era. Unfortunately, most Search Engines provide web content which is irrelevant to the information intended to the browser. Many Text Categorization techniques for web content have been developed, to recognize the given document’s category but failed to make trust worthy results. This paper primarily focuses on web content categorization based on classic summarization technique by enabling the classification at word level. The web document is preprocessed first which involves filtering the content with classical techniques and then is converted into organized data. The organized data is then treated with predefined hierarchical categorical set to identify theexact category.

  10. Amplitude extraction in pseudoscalar-meson photoproduction: towards a situation of complete information

    CERN Document Server

    Nys, Jannes; Ryckebusch, Jan

    2015-01-01

    A complete set for pseudoscalar-meson photoproduction is a minimum set of observables from which one can determine the underlying reaction amplitudes unambiguously. The complete sets considered in this work involve single- and double-polarization observables. It is argued that for extracting amplitudes from data, the transversity representation of the reaction amplitudes offers advantages over alternate representations. It is shown that with the available single-polarization data for the p({\\gamma},K^+)\\Lambda reaction, the energy and angular dependence of the moduli of the normalized transversity amplitudes in the resonance region can be determined to a fair accuracy. Determining the relative phases of the amplitudes from double-polarization observables is far less evident.

  11. Adaptive extraction of emotion-related EEG segments using multidimensional directed information in time-frequency domain.

    Science.gov (United States)

    Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

    2010-01-01

    Emotion discrimination from electroencephalogram (EEG) has gained attention the last decade as a user-friendly and effective approach to EEG-based emotion recognition (EEG-ER) systems. Nevertheless, challenging issues regarding the emotion elicitation procedure, especially its effectiveness, raise. In this work, a novel method, which not only evaluates the degree of emotion elicitation but localizes the emotion information in the time-frequency domain, as well, is proposed. The latter, incorporates multidimensional directed information at the time-frequency EEG representation, extracted using empirical mode decomposition, and introduces an asymmetry index for adaptive emotion-related EEG segment selection. Experimental results derived from 16 subjects visually stimulated with pictures from the valence/arousal space drawn from the International Affective Picture System database, justify the effectiveness of the proposed approach and its potential contribution to the enhancement of EEG-ER systems.

  12. Extracting DC bus current information for optimal phase correction and current ripple in sensorless brushless DC motor drive

    Institute of Scientific and Technical Information of China (English)

    Zu-sheng HO; Chii-maw UANG; Ping-chieh WANG

    2014-01-01

    Brushless DC motor (BLDCM) sensorless driving technology is becoming increasingly established. However, op-timal phase correction still relies on complex calculations or algorithms. In finding the correct commutation point, the problem of phase lag is introduced. In this paper, we extract DC bus current information for auto-calibrating the phase shift to obtain the correct commutation point and optimize the control of BLDC sensorless driving. As we capture only DC bus current information, the original shunt resistor is used in the BLDCM driver and there is no need to add further current sensor components. Software processing using only simple arithmetic operations successfully accomplishes the phase correction. Experimental results show that the proposed method can operate accurately and stably at low or high speed, with light or heavy load, and is suitable for practical applications. This approach will not increase cost but will achieve the best performance/cost ratio and meet market expectations.

  13. Analysis Methods for Extracting Knowledge from Large-Scale WiFi Monitoring to Inform Building Facility Planning

    DEFF Research Database (Denmark)

    Ruiz-Ruiz, Antonio; Blunck, Henrik; Prentow, Thor Siiger

    2014-01-01

    realistic data to inform facility planning. In this paper, we propose analysis methods to extract knowledge from large sets of network collected WiFi traces to better inform facility management and planning in large building complexes. The analysis methods, which build on a rich set of temporal and spatial...... features, include methods for noise removal, e.g., labeling of beyond building-perimeter devices, and methods for quantification of area densities and flows, e.g., building enter and exit events, and for classifying the behavior of people, e.g., into user roles such as visitor, hospitalized or employee...... noise removal of beyond building perimeter devices. We furthermore present detailed statistics from our analysis regarding people’s presence, movement and roles, and example types of visualizations that both highlight their potential as inspection tools for planners and provide interesting insights...

  14. Extracting additional risk managers information from a risk assessment of Listeria monocytogenes in deli meats

    NARCIS (Netherlands)

    Pérez-Rodríguez, F.; Asselt, van E.D.; García-Gimeno, R.M.; Zurera, G.; Zwietering, M.H.

    2007-01-01

    The risk assessment study of Listeria monocytogenes in ready-to-eat foods conducted by the U.S. Food and Drug Administration is an example of an extensive quantitative microbiological risk assessment that could be used by risk analysts and other scientists to obtain information and by managers and s

  15. The Promise of Information and Communication Technology in Healthcare: Extracting Value From the Chaos.

    Science.gov (United States)

    Mamlin, Burke W; Tierney, William M

    2016-01-01

    Healthcare is an information business with expanding use of information and communication technologies (ICTs). Current ICT tools are immature, but a brighter future looms. We examine 7 areas of ICT in healthcare: electronic health records (EHRs), health information exchange (HIE), patient portals, telemedicine, social media, mobile devices and wearable sensors and monitors, and privacy and security. In each of these areas, we examine the current status and future promise, highlighting how each might reach its promise. Steps to better EHRs include a universal programming interface, universal patient identifiers, improved documentation and improved data analysis. HIEs require federal subsidies for sustainability and support from EHR vendors, targeting seamless sharing of EHR data. Patient portals must bring patients into the EHR with better design and training, greater provider engagement and leveraging HIEs. Telemedicine needs sustainable payment models, clear rules of engagement, quality measures and monitoring. Social media needs consensus on rules of engagement for providers, better data mining tools and approaches to counter disinformation. Mobile and wearable devices benefit from a universal programming interface, improved infrastructure, more rigorous research and integration with EHRs and HIEs. Laws for privacy and security need updating to match current technologies, and data stewards should share information on breaches and standardize best practices. ICT tools are evolving quickly in healthcare and require a rational and well-funded national agenda for development, use and assessment.

  16. An Approach for Comparative Research Between Ontology Building & Learning Tools for Information Extraction & Retrieval

    Directory of Open Access Journals (Sweden)

    Dr Suresh Jain C. S. Bhatia Dharmendra Gupta Sumit Jain Bharat Pahadiya

    2012-02-01

    Full Text Available Information available on the web is huge & it covers diversified fields. Nowadays most of search engines use essentially keyword based search techniques. We simply specify a set of keywords or query as a request and a reference we get a list of pages, ranked based on similarity of query. Currently searching web face with one problem that many times outcome is not satisfactory because of irrelevance of the information. Searching the exact information from such a huge repository of unstructured web data is still main area of research interest. One solution to achieve this is Semantic Web. Ontology is an effective concept commonly used for the Semantic Web. Ontology is “an explicit specification of a conceptualization”. There are two main pillars of semantic Web one is Problem Solving Methods & another is Ontology. Ontology building is a tedious job and a time consuming task for user. The quality of ontology plays an important role in information retrieval application .This paper deals with features & familiarity with different Ontology building & learning tools. After all the preliminary knowledge about all tools & software we have made research about specific features & services provided by some tools & identified the optimum tool in all respect for particularly for our further research project.

  17. The Exponentially Embedded Family of Distributions for Effective Data Representation, Information Extraction, and Decision Making

    Science.gov (United States)

    2013-03-01

    unlimited. This is equivalent to Gram-Schmidt orthogonalization for Gaussian PDFs (see Figure 2). Pt (true PDF) Pr(t; Ho) -~- · Prr (best...approximation) additional information of T2 Figure 2: Best Approximation For one sensor we construct and for two sensors we construct Prr = Pryi ,7]2

  18. Named entity extraction and disambiguation for informal text: the missing link

    NARCIS (Netherlands)

    Badieh Habib Morgan, Mena

    2014-01-01

    Social media content represents a large portion of all textual content appearing on the Internet. These streams of user generated content (UGC) provide an opportunity and challenge for media analysts to analyze huge amount of new data and use them to infer and reason with new information. An example

  19. Creating meaningful business continuity management programme metrics.

    Science.gov (United States)

    Strong, Brian

    2010-11-01

    The popular axiom, 'what gets measured gets done', is often applied in the quality management and continuous improvement disciplines. This truism is also useful to business continuity practitioners as they continually strive to prove the value of their organisation's investment in a business continuity management (BCM) programme. BCM practitioners must also remain relevant to their organisations as executives focus on the bottom line and maintaining stakeholder confidence. It seems that executives always find a way, whether in a hallway or elevator, to ask BCM professionals about the company's level of readiness. When asked, they must be ready with an informed response. The establishment of a process to measure business continuity programme performance and organisational readiness has emerged as a key component of US Department of Homeland Security 'Voluntary Private Sector Preparedness (PS-Prep) Program' standards where the overarching goal is to improve private sector preparedness for disasters and emergencies. The purpose of this paper is two-fold: to introduce continuity professionals to best practices that should be considered when developing a BCM metrics programme as well as providing a case study of how a large health insurance company researched, developed and implemented a process to measure BCM programme performance and company readiness.

  20. Antecedents and outcomes of meaningful work among school teachers

    Directory of Open Access Journals (Sweden)

    Elmari Fouché

    2017-01-01

    Full Text Available Orientation: Quality education is dependent on the well-being, engagement, performance and retention of teachers. Meaningful work might affect these employee and organisational outcomes.Research purpose: The aim of this study was to investigate antecedents and outcomes of meaningful work among school teachers.Motivation for the study: Meaningful work underpins people’s motivation and affects their well-being and job satisfaction. Furthermore, it is a significant pathway to healthy and authentic organisations. However, a research gap exists regarding the effects of different antecedents and outcomes of meaningful work.Research approach, design and method: A cross-sectional survey was used with a convenience sample of 513 teachers. The Work-Life Questionnaire, Revised Job Diagnostic Survey, Co-worker Relations Scale, Work and Meaning Inventory, Personal Resources Scale, Work Engagement Scale, Turnover Intention Scale and a measure of self-rated performance were administered.Main findings: A calling orientation, job design and co-worker relations were associated with meaningful work. A low calling orientation and poor co-worker relationships predicted burnout. A calling orientation, a well-designed job, good co-worker relationships and meaningful work predicted work engagement. Job design was moderately associated with self-ratings of performance. The absence of a calling orientation predicted teachers’ intention to leave the organisation.Practical/managerial implications: Educational managers should consider implementing interventions to affect teachers’ calling orientation (through job crafting, perceptions of the nature of their jobs (by allowing autonomy and co-worker relations (through teambuilding to promote perceptions of meaningful work. Promoting perceptions of meaningful work might contribute to lower burnout, higher work engagement, better self-ratings of performance and retention of teachers.Contribution/value-add: This study

  1. Extracting Feature Information and its Visualization Based on the Characteristic Defect Octave Frequencies in a Rolling Element Bearing

    Directory of Open Access Journals (Sweden)

    Jianyu Lei

    2007-10-01

    Full Text Available Monitoring the condition of rolling element bearings and defect diagnosis has received considerable attention for many years because the majority of problems in rotating machines are caused by defective bearings. In order to monitor conditions and diagnose defects in a rolling element bearing, a new approach is developed, based on the characteristic defect octave frequencies. The characteristic defect frequencies make it possible to detect the presence of a defect and diagnose in what part of the bearing the defect appears. However, because the characteristic defect frequencies vary with rotational speed, it is difficult to extract feature information from data at variable rotational speeds. In this paper, the characteristic defect octave frequencies, which do not vary with rotation speed, are introduced to replace the characteristic defect frequencies. Therefore feature information can be easily extracted. Moreover, based on characteristic defect octave frequencies, an envelope spectrum array, which associates 3-D visualization technology with extremum envelope spectrum technology, is established. This method has great advantages in acquiring the characteristics and trends of the data and achieves a straightforward and creditable result.

  2. Evaluation of an Automated Information Extraction Tool for Imaging Data Elements to Populate a Breast Cancer Screening Registry.

    Science.gov (United States)

    Lacson, Ronilda; Harris, Kimberly; Brawarsky, Phyllis; Tosteson, Tor D; Onega, Tracy; Tosteson, Anna N A; Kaye, Abby; Gonzalez, Irina; Birdwell, Robyn; Haas, Jennifer S

    2015-10-01

    Breast cancer screening is central to early breast cancer detection. Identifying and monitoring process measures for screening is a focus of the National Cancer Institute's Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) initiative, which requires participating centers to report structured data across the cancer screening continuum. We evaluate the accuracy of automated information extraction of imaging findings from radiology reports, which are available as unstructured text. We present prevalence estimates of imaging findings for breast imaging received by women who obtained care in a primary care network participating in PROSPR (n = 139,953 radiology reports) and compared automatically extracted data elements to a "gold standard" based on manual review for a validation sample of 941 randomly selected radiology reports, including mammograms, digital breast tomosynthesis, ultrasound, and magnetic resonance imaging (MRI). The prevalence of imaging findings vary by data element and modality (e.g., suspicious calcification noted in 2.6% of screening mammograms, 12.1% of diagnostic mammograms, and 9.4% of tomosynthesis exams). In the validation sample, the accuracy of identifying imaging findings, including suspicious calcifications, masses, and architectural distortion (on mammogram and tomosynthesis); masses, cysts, non-mass enhancement, and enhancing foci (on MRI); and masses and cysts (on ultrasound), range from 0.8 to1.0 for recall, precision, and F-measure. Information extraction tools can be used for accurate documentation of imaging findings as structured data elements from text reports for a variety of breast imaging modalities. These data can be used to populate screening registries to help elucidate more effective breast cancer screening processes.

  3. Architecture and data processing alternatives for the TSE computer. Volume 2: Extraction of topological information from an image by the Tse computer

    Science.gov (United States)

    Jones, J. R.; Bodenheimer, R. E.

    1976-01-01

    A simple programmable Tse processor organization and arithmetic operations necessary for extraction of the desired topological information are described. Hardware additions to this organization are discussed along with trade-offs peculiar to the tse computing concept. An improved organization is presented along with the complementary software for the various arithmetic operations. The performance of the two organizations is compared in terms of speed, power, and cost. Software routines developed to extract the desired information from an image are included.

  4. Analysis of space-borne data for coastal zone information extraction of Goa Coast, India

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.; Wagle, B.G.

    pan Estuary island Mangrove vegetation Fig. 2. Photo-geomorphological map o[ study area. Analysis of space-borne data for coastal zone information 193 I Fluvial I Coastal Features I I) Estuary islands 2) River terraces 3) Tidal flats.... These projects result in tidal flooding, further accelerating the erosion of river banks, which ultimately has adverse impacts on fish nurseries and salt pans. These revelations demonstrate that remote sensing with spatial, spectral, and temporal capabilities...

  5. Resource Conservation and Recovery Information System extract tape. Data tape documentation

    Energy Technology Data Exchange (ETDEWEB)

    1990-12-31

    Within the Environmental Protection Agency (EPA), the Office of Solid Waste and Emergency Response (OSWER) is responsible for the development and management of a national program to safely handle solid and hazardous waste. The national program, for the most part, is authorized by the Resource Conservation and Recovery Act (RCRA). The Hazardous Waste Data Management System (HWDMS) was developed to automatically track the status of permits, reports, inspections, enforcement activities, and financial data to assist EPA in managing the data generated by RCRA. As with many computer systems, HWDMS has outgrown its capabilities, so a new system is needed. The new system is called the Resource Conservation and Recovery Information System (RCRIS). The goal of the RCRIS system is to provide a more effective means for tracking hazardous waste handlers regulated under RCRA. RCRA Notification, Permitting, and Compliance Monitoring and Evaluation data is available through the National Technical Information Service (NTIS) on IBM compatible tapes. From now until HWDMS is completely archived, there will be two data tapes from NTIS. There will be a tape for HWDMS and a separate one for RCRIS. The HWDMS tape will include data from all States and Territories, except for Mississippi. The RCRIS tape will only contain the data from Mississippi and general enforcement data, sensitive information is not included.

  6. Optimal Extraction of Geothermal Energy

    Energy Technology Data Exchange (ETDEWEB)

    Golabi, Kamal; Scherer, Charles, R.

    1977-06-01

    This study is concerned with the optimal extraction of energy from a hot water geothermal field. In view of the relative "commercial" availability of the many energy sources alternative to geothermal, it is possible that a socially "best" extraction policy may not include producing geothermal energy as fast as the current technology will permit. Rather, a truly "optimal" policy will depend on, among other things, the costs and value of geothermal energy in the future and the analogous values of other energy sources. Hence, a general approach to this problem would make the policy contingent on pertinent information on alternative sources. A good example of this approach is given in Manne's (1976) Energy Technology Assessment Model, where he points out that "Each energy source has its own cost parameters and introduction date, but is interdependent with other components of the energy sector." (Manne (1976), p. 379). But by their large dimensions, such relativity macro-analyses tend to preclude a close look at the specific technology of a process is important in developing meaningful resource management models, we substitute for a macro model the increasing value over time of the energy extracted. In this contact we seek an extraction rate (and an economic life) that maximizes the net discounted value of the energy extracted. [DJE-2005

  7. Identifying and extracting patient smoking status information from clinical narrative texts in Spanish.

    Science.gov (United States)

    Figueroa, Rosa L; Soto, Diego A; Pino, Esteban J

    2014-01-01

    In this work we present a system to identify and extract patient's smoking status from clinical narrative text in Spanish. The clinical narrative text was processed using natural language processing techniques, and annotated by four people with a biomedical background. The dataset used for classification had 2,465 documents, each one annotated with one of the four smoking status categories. We used two feature representations: single word token and bigrams. The classification problem was divided in two levels. First recognizing between smoker (S) and non-smoker (NS); second recognizing between current smoker (CS) and past smoker (PS). For each feature representation and classification level, we used two classifiers: Support Vector Machines (SVM) and Bayesian Networks (BN). We split our dataset as follows: a training set containing 66% of the available documents that was used to build classifiers and a test set containing the remaining 34% of the documents that was used to test and evaluate the model. Our results show that SVM together with the bigram representation performed better in both classification levels. For S vs NS classification level performance measures were: ACC=85%, Precision=85%, and Recall=90%. For CS vs PS classification level performance measures were: ACC=87%, Precision=91%, and Recall=94%.

  8. 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.

  9. Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducibility for use in research/quality assurance

    Directory of Open Access Journals (Sweden)

    Kent Peter

    2011-07-01

    Full Text Available Abstract 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 and transforming that information into quantitative data. However, this process is frequently required in research and quality assurance contexts. The purpose of this study was to examine inter-rater reproducibility (agreement and reliability among an inexperienced group of clinicians in extracting spinal 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 between trainee clinicians and two highly trained raters was examined in an arbitrary coding round, with agreement measured using percentage agreement and reliability measured using unweighted Kappa (k. Reproducibility was then examined in another group of three trainee clinicians who had not participated in the production of the decision rules, using another sample of 20 MRI reports. Results The mean percentage agreement for paired comparisons between the initial trainee clinicians improved over the four coding rounds (97.9-99.4%, although the greatest improvement was observed after the first introduction of coding rules. High inter-rater reproducibility was observed between trainee clinicians across 14 pathoanatomic categories over the

  10. Case study on the extraction of land cover information from the SAR image of a coal mining area

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-ling; LI Hai-quan; DU Pei-jun

    2009-01-01

    In this study, analyses are conducted on the information features of a construction site, a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area, on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image, we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next, a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis, a classification is conducted selectively on three principal component bands with the most information. Finally, through training and experimenting with the samples, a better three-layered BP neural network was established to classify the SAR image. The results show that, assisted by texture information, the neural network classification improved the accuracy of SAR image clas-sification by 14.6%, compared with a classification by maximum likelihood estimation without texture information.

  11. Classification of Informal Settlements Through the Integration of 2d and 3d Features Extracted from Uav Data

    Science.gov (United States)

    Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

    2016-06-01

    Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  12. CLASSIFICATION OF INFORMAL SETTLEMENTS THROUGH THE INTEGRATION OF 2D AND 3D FEATURES EXTRACTED FROM UAV DATA

    Directory of Open Access Journals (Sweden)

    C. M. Gevaert

    2016-06-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  13. Hospital IT adoption strategies associated with implementation success: implications for achieving meaningful use.

    Science.gov (United States)

    Ford, Eric W; Menachemi, Nir; Huerta, Timothy R; Yu, Feliciano

    2010-01-01

    Health systems are facing significant pressure to either implement health information technology (HIT) systems that have "certified" electronic health record applications and that fulfill the federal government's definition of "meaningful use" or risk substantial financial penalties in the near future. To this end, hospitals have adopted one of three strategies, described as "best of breed," "best of suite," and "single vendor," to meet organizational and regulatory demands. The single-vendor strategy is used by the simple majority of U.S. hospitals, but is it the most effective mode for achieving full implementation? Moreover, what are the implications of adopting this strategy for achieving meaningful use? The simple answer to the first question is that the hospitals using the hybrid best of suite strategy had fully implemented HIT systems in significantly greater proportions than did hospitals employing either of the other strategies. Nonprofit and system-affiliated hospitals were more likely to have fully implemented their HIT systems. In addition, increased health maintenance organization market penetration rates were positively correlated with complete implementation rates. These results have ongoing implications for achieving meaningful use in the near term. The federal government's rewards and incentives program related to the meaningful use of HIT in hospitals has created an organizational imperative to implement such systems. For hospitals that have not begun systemwide implementation, pursuing a best of suite strategy may provide the greatest chance for achieving all or some of the meaningful use targets in the near term or at least avoiding future penalties scheduled to begin in 2015.

  14. Toward a comprehensive drug ontology: extraction of drug-indication relations from diverse information sources.

    Science.gov (United States)

    Sharp, Mark E

    2017-01-10

    Drug ontologies could help pharmaceutical researchers overcome information overload and speed the pace of drug discovery, thus benefiting the industry and patients alike. Drug-disease relations, specifically drug-indication relations, are a prime candidate for representation in ontologies. There is a wealth of available drug-indication information, but structuring and integrating it is challenging. We created a drug-indication database (DID) of data from 12 openly available, commercially available, and proprietary information sources, integrated by terminological normalization to UMLS and other authorities. Across sources, there are 29,964 unique raw drug/chemical names, 10,938 unique raw indication "target" terms, and 192,008 unique raw drug-indication pairs. Drug/chemical name normalization to CAS numbers or UMLS concepts reduced the unique name count to 91 or 85% of the raw count, respectively, 84% if combined. Indication "target" normalization to UMLS "phenotypic-type" concepts reduced the unique term count to 57% of the raw count. The 12 sources of raw data varied widely in coverage (numbers of unique drug/chemical and indication concepts and relations) generally consistent with the idiosyncrasies of each source, but had strikingly little overlap, suggesting that we successfully achieved source/raw data diversity. The DID is a database of structured drug-indication relations intended to facilitate building practical, comprehensive, integrated drug ontologies. The DID itself is not an ontology, but could be converted to one more easily than the contributing raw data. Our methodology could be adapted to the creation of other structured drug-disease databases such as for contraindications, precautions, warnings, and side effects.

  15. The Pediatrix BabySteps Data Warehouse and the Pediatrix QualitySteps improvement project system--tools for "meaningful use" in continuous quality improvement.

    Science.gov (United States)

    Spitzer, Alan R; Ellsbury, Dan L; Handler, Darren; Clark, Reese H

    2010-03-01

    The Pediatrix BabySteps Clinical Data Warehouse (CDW) is a rich and novel tool allowing unbiased extraction of information from an entire neonatal population care by physicians and advanced practice nurses in Pediatrix Medical Group. Because it represents the practice of newborn medicine ranging from small community intensive care units to some of the largest neonatal intensive care units in the United States, it is highly representative of scope of practice in this country. Its value in defining outcome measures, quality improvement projects, and research continues to grow annually. Now coupled with the BabySteps QualitySteps program for defined clinical quality improvement projects, it represents a robust methodology for meaningful use of an electronic health care record, as designated during this era of health care reform. Continued growth of the CDW should result in continued important observations and improvements in neonatal care.

  16. 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

  17. COSEBIs: Extracting the full E-/B-mode information from cosmic shear correlation functions

    CERN Document Server

    Schneider, Peter; Krause, Elisabeth

    2010-01-01

    Cosmic shear is considered one of the most powerful methods for studying the properties of Dark Energy in the Universe. As a standard method, the two-point correlation functions $xi_\\pm(theta)$ of the cosmic shear field are used as statistical measures for the shear field. In order to separate the observed shear into E- and B-modes, the latter being most likely produced by remaining systematics in the data set and/or intrinsic alignment effects, several statistics have been defined before. Here we aim at a complete E-/B-mode decomposition of the cosmic shear information contained in the $xi_\\pm$ on a finite angular interval. We construct two sets of such E-/B-mode measures, namely Complete Orthogonal Sets of E-/B-mode Integrals (COSEBIs), characterized by weight functions between the $xi_\\pm$ and the COSEBIs which are polynomials in $theta$ or polynomials in $ln(theta)$, respectively. Considering the likelihood in cosmological parameter space, constructed from the COSEBIs, we study their information contents....

  18. Textpresso: an ontology-based information retrieval and extraction system for biological literature.

    Directory of Open Access Journals (Sweden)

    Hans-Michael Müller

    2004-11-01

    Full Text Available We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc. and classes that relate two objects (e.g., association, regulation, etc. or describe one (e.g., biological process, etc.. Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other

  19. Textpresso: an ontology-based information retrieval and extraction system for biological literature.

    Science.gov (United States)

    Müller, Hans-Michael; Kenny, Eimear E; Sternberg, Paul W

    2004-11-01

    We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism

  20. Extracting change information of land-use and soil-erosion based on RS & GIS technology

    Institute of Scientific and Technical Information of China (English)

    LI Zhong-feng; LI You-cai

    2007-01-01

    Rapid land-use change has taken place in many arid regions of China such as Yulin prefecture over the last decade due to rehabilitation measures. Land-use change and soil erosion dynamics were investigated by the combined use of remote sensing and geographic information systems (GIS). The objectives were to determine land-use transition rates and soil erosion change in Yulin prefecture over 15 years from 1986 to 2000. Significant changes in land-use and soil erosion occurred in the area over the study period. The results show the significant decrease in barren land mainly due to conversion to grassland. Agricultural land increased associated with conversions from grassland and barren land. The area of water erosion and wind erosion declined. The study demonstrates that the integration of satellite remote sensing and GIS is an effective approach for analyzing the direction, rate, and spatial pattern of land-use and soil erosion change.

  1. Extracting Time-Resolved Information from Time-Integrated Laser-Induced Breakdown Spectra

    Directory of Open Access Journals (Sweden)

    Emanuela Grifoni

    2014-01-01

    Full Text Available Laser-induced breakdown spectroscopy (LIBS data are characterized by a strong dependence on the acquisition time after the onset of the laser plasma. However, time-resolved broadband spectrometers are expensive and often not suitable for being used in portable LIBS instruments. In this paper we will show how the analysis of a series of LIBS spectra, taken at different delays after the laser pulse, allows the recovery of time-resolved spectral information. The comparison of such spectra is presented for the analysis of an aluminium alloy. The plasma parameters (electron temperature and number density are evaluated, starting from the time-integrated and time-resolved spectra, respectively. The results are compared and discussed.

  2. 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.

  3. Extraction of Benthic Cover Information from Video Tows and Photographs Using Object-Based Image Analysis

    Science.gov (United States)

    Estomata, M. T. L.; Blanco, A. C.; Nadaoka, K.; Tomoling, E. C. M.

    2012-07-01

    Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES) was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU), which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA), which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05).

  4. EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

    Full Text Available Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU, which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA, which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, α = 0.05.

  5. 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.

  6. Automatic Extraction System of Webpage Information%全自动网页信息采集系统

    Institute of Scientific and Technical Information of China (English)

    徐春凤; 王艳春; 翟宏宇

    2015-01-01

    With the rapid development of the internet age, users have put forward more requirements for search en-gines,content of webpage and large data processing etc. Selecting the required information from the internet information with mass data has become a new hotspot. In this paper, extensible webcrawler project- Heritrix, which is an open source and developed by Java, is extended to capture user webpage. The information collection technology is further studied. Extendibility of Heritrix is used to realize a user’s capture. Through the analysis of the working process of Heritrix, module allocation and source code design, based on webpage extraction facing product information with Heri-trix extendibility and webpage content analysis with HtmlParser, key product information is extracted effectively, which is stored in the database for retrieval.%随着网络时代的快速发展,用户对搜索引擎、网页的内容和大数据处理等有了更多的要求。从海量的互联网信息中选取最符合要求的信息成为了新的热点。基于一个开源的、Java开发的、可扩展的Web爬虫项目—Heritrix,进行扩展抓取用户需要的网页,深入研究了信息采集技术。利用Heritrix的可扩展性,来实现用户的抓取。通过分析Heritrix的工作流程,模块划分以及源码设计,基于Heritrix扩展抽取面向商品信息的网页,配合HtmlParser对网页内容进行解析,有效的提取商品关键信息后存入数据库以供检索。

  7. The Developing of Meaningful Activity in Artificial Environment

    DEFF Research Database (Denmark)

    Holsbæk, Jonas

    is Ambient Assisted Living (ALL). ALL is often focused on the institutional and societal needs (saving man power eg.) as primary objectives, and the user needs as secondary. Physical activity as well as meaningful activity and experience of Flow, has a positive influence on health for all humans....... The experience of Flow can be hard to achieve or maintain for people with Dementia due to their loss of skills over time. Objectives: The purpose of this project was to develop a platform that supports People with Dementia in performing physical activity, meaningfulness and the experience of Flow. Method...... developing. Results/Discussion: Data from the observation suggested that the moch up could support the participants with Dementia in experiencing flow, and that the physical activity was experienced as meaningful for the participants. Conclusion: An artificial environment can support the experience of Flow...

  8. Meaningful learning: theoretical support for concept-based teaching.

    Science.gov (United States)

    Getha-Eby, Teresa J; Beery, Theresa; Xu, Yin; O'Brien, Beth A

    2014-09-01

    Novice nurses’ inability to transfer classroom knowledge to the bedside has been implicated in adverse patient outcomes, including death. Concept-based teaching is a pedagogy found to improve knowledge transfer. Concept-based teaching emanates from a constructivist paradigm of teaching and learning and can be implemented most effectively when the underlying theory and principles are applied. Ausubel’s theory of meaningful learning and its construct of substantive knowledge integration provides a model to help educators to understand, implement, and evaluate concept-based teaching. Contemporary findings from the fields of cognitive psychology, human development, and neurobiology provide empirical evidence of the relationship between concept-based teaching, meaningful learning, and knowledge transfer. This article describes constructivist principles and meaningful learning as they apply to nursing pedagogy.

  9. Citizen-Centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm

    Directory of Open Access Journals (Sweden)

    Bernd Resch

    2016-07-01

    Full Text Available Traditional urban planning processes typically happen in offices and behind desks. Modern types of civic participation can enhance those processes by acquiring citizens’ ideas and feedback in participatory sensing approaches like “People as Sensors”. As such, citizen-centric planning can be achieved by analysing Volunteered Geographic Information (VGI data such as Twitter tweets and posts from other social media channels. These user-generated data comprise several information dimensions, such as spatial and temporal information, and textual content. However, in previous research, these dimensions were generally examined separately in single-disciplinary approaches, which does not allow for holistic conclusions in urban planning. This paper introduces TwEmLab, an interdisciplinary approach towards extracting citizens’ emotions in different locations within a city. More concretely, we analyse tweets in three dimensions (space, time, and linguistics, based on similarities between each pair of tweets as defined by a specific set of functional relationships in each dimension. We use a graph-based semi-supervised learning algorithm to classify the data into discrete emotions (happiness, sadness, fear, anger/disgust, none. Our proposed solution allows tweets to be classified into emotion classes in a multi-parametric approach. Additionally, we created a manually annotated gold standard that can be used to evaluate TwEmLab’s performance. Our experimental results show that we are able to identify tweets carrying emotions and that our approach bears extensive potential to reveal new insights into citizens’ perceptions of the city.

  10. 一种表单Ajax信息项提取方法%Extraction Method of Form Ajax Information Item

    Institute of Scientific and Technical Information of China (English)

    段青玲; 杨仁刚; 朱杨

    2011-01-01

    This paper presents an extraction method of form Ajax information item. The method embeds JavaScript engine into the running programs which is independent of the browser, reconstructs the DOM and Ajax objects locally. It simulates the user operation in using the browser with the JavaScript engine tracking and executing the script to automatic gain form Ajax information item data. Experimental results show that the method can completely obtain form information of Deep Web query interface, and it can improve search accuracy.%提出一种表单Ajax信息项提取方法.该方法在独立于浏览器运行的程序中嵌入JavaScript引擎,本地化构建DOM对象和Ajax应用对象,利用JavaScript引擎跟踪执行脚本代码,模拟执行用户在浏览器下的操作,从而自动获取表单Ajax信息项数据.实验结果表明,该方法可以完整获取Deep Web查询接口的表单信息,提高搜索准确率.

  11. Meaningful improvement in gait speed in hip fracture recovery.

    Science.gov (United States)

    Alley, Dawn E; Hicks, Gregory E; Shardell, Michelle; Hawkes, William; Miller, Ram; Craik, Rebecca L; Mangione, Kathleen K; Orwig, Denise; Hochberg, Marc; Resnick, Barbara; Magaziner, Jay

    2011-09-01

    To estimate meaningful improvements in gait speed observed during recovery from hip fracture and to evaluate the sensitivity and specificity of gait speed changes in detecting change in self-reported mobility. Secondary longitudinal data analysis from two randomized controlled trials Twelve hospitals in the Baltimore, Maryland, area. Two hundred seventeen women admitted with hip fracture. Usual gait speed and self-reported mobility (ability to walk 1 block and climb 1 flight of stairs) measured 2 and 12 months after fracture. Effect size-based estimates of meaningful differences were 0.03 for small differences and 0.09 for substantial differences. Depending on the anchor (stairs vs walking) and method (mean difference vs regression), anchor-based estimates ranged from 0.10 to 0.17 m/s for small meaningful improvements and 0.17 to 0.26 m/s for substantial meaningful improvement. Optimal gait speed cutpoints yielded low sensitivity (0.39-0.62) and specificity (0.57-0.76) for improvements in self-reported mobility. Results from this sample of women recovering from hip fracture provide only limited support for the 0.10-m/s cut point for substantial meaningful change previously identified in community-dwelling older adults experiencing declines in walking abilities. Anchor-based estimates and cut points derived from receiver operating characteristic curve analysis suggest that greater improvements in gait speed may be required for substantial perceived mobility improvement in female hip fracture patients. Furthermore, gait speed change performed poorly in discriminating change in self-reported mobility. Estimates of meaningful change in gait speed may differ based on the direction of change (improvement vs decline) or between patient populations. © 2011, Copyright the Authors. Journal compilation © 2011, The American Geriatrics Society.

  12. Is it Possible to Extract Brain Metabolic Pathways Information from In Vivo H Nuclear Magnetic Resonance Spectroscopy Data?

    CERN Document Server

    de Lara, Alejandro Chinea Manrique

    2010-01-01

    In vivo H nuclear magnetic resonance (NMR) spectroscopy is an important tool for performing non-invasive quantitative assessments of brain tumour glucose metabolism. Brain tumours are considered as fast-growth tumours because of their high rate of proliferation. In addition, tumour cells exhibit profound genetic, biochemical and histological differences with respect to the original non-transformed cellular types. Therefore, there is a strong interest from the clinical investigator point of view in understanding the role of brain metabolites in normal and pathological conditions and especially on the development of early tumour detection techniques. Unfortunately, current diagnosis techniques ignore the dynamic aspects of these signals. It is largely believed that temporal variations of NMR Spectra are noisy or just simply do not carry enough information to be exploited by any reliable diagnosis procedure. Thus, current diagnosis procedures are mainly based on empirical observations extracted from single avera...

  13. Designing Meaningful Game Experiences for Rehabilitation and Sustainable Mobility Settings

    Directory of Open Access Journals (Sweden)

    Silvia Gabrielli

    2014-03-01

    Full Text Available This paper presents the approach followed in two ongoing research projects aimed to designing meaningful game-based experiences to support home rehabilitation, eco-sustainable mobility goals and more in general better daily lifestyles. We first introduce the need for designing meaningful game-based experiences that are well-connected to the relevant non-game settings and can be customized by/for users, then, we show examples of how this approach can be realized in the rehabilitation and sustainable mobility contexts.

  14. Combining information preserved in fluvial topography and strath terraces to extract rock uplift rates in the Apennines

    Science.gov (United States)

    Fox, M.; Brandon, M. T.

    2015-12-01

    Longitudinal river profiles respond to changes in tectonic uplift rates through climate-modulated erosion. Therefore, rock uplift rate information should be recorded in fluvial topography and extracting this information provides crucial constraints on tectonic processes. In addition to the shape of the modern river profile, paleo-river profiles can often be mapped in the field by connecting strath terraces. These strath terraces act as markers that record complex incision histories in response to rock uplift rates that vary in space and time. We exploit an analytical linear solution to the linear version (n=1) of the stream-power equation to efficiently extract uplift histories from river networks and strath terraces. The analytical solution is based on the transient solution to the linear version (n=1) of the stream-power equation. The general solution to this problem states that the elevation of a point in a river channel is equal to the time integral of its uplift history, where integration is carried out over the time required for an uplift signal to propagate from the baselevel of the river network to the point of interest. A similar expression can be written for each strath terrace in the dataset. Through discretization of these expressions into discrete timesteps and spatial nodes, a linear system of equations can be solved using linear inverse methods. In this way, strath terraces and river profiles can be interpreted in an internally consistent framework, without the requirement that the river profile is in a steady state. We apply our approach to the Northern Apennines where strath terraces have been extensively mapped and dated. Comparison of our inferred rock uplift rate history with modern rock uplift rates enables us to distinguish short-term deformation on a buried thrust fault with long-term mountain building processes.

  15. Dementia care: using empathic curiosity to establish the common ground that is necessary for meaningful communication.

    Science.gov (United States)

    McEvoy, P; Plant, R

    2014-08-01

    Over the past two decades the advocates of person-centred approaches to dementia care have consistently argued that some of the negative impacts of dementia can be ameliorated in supportive social environments and they have given lie to the common but unfounded, nihilistic belief that meaningful engagement with people with dementia is impossible. This discussion paper contributes to this welcome trend by exploring how carers can use empathic curiosity to establish the common ground that is necessary to sustain meaningful engagement with people who have mild to moderate dementia. The first section of the paper gives a brief theoretical introduction to the concept of empathic curiosity, which is informed by perceptual control theory and applied linguistics. Three case examples taken from the literature on dementia care are then used to illustrate what empathic curiosity may look like in practice and to explore the potential impact that adopting an empathic and curious approach may have.

  16. Meaningful Peer Review in Radiology: A Review of Current Practices and Potential Future Directions.

    Science.gov (United States)

    Moriarity, Andrew K; Hawkins, C Matthew; Geis, J Raymond; Dreyer, Keith J; Kamer, Aaron P; Khandheria, Paras; Morey, Jose; Whitfill, James; Wiggins, Richard H; Itri, Jason N

    2016-12-01

    The current practice of peer review within radiology is well developed and widely implemented compared with other medical specialties. However, there are many factors that limit current peer review practices from reducing diagnostic errors and improving patient care. The development of "meaningful peer review" requires a transition away from compliance toward quality improvement, whereby the information and insights gained facilitate education and drive systematic improvements that reduce the frequency and impact of diagnostic error. The next generation of peer review requires significant improvements in IT functionality and integration, enabling features such as anonymization, adjudication by multiple specialists, categorization and analysis of errors, tracking, feedback, and easy export into teaching files and other media that require strong partnerships with vendors. In this article, the authors assess various peer review practices, with focused discussion on current limitations and future needs for meaningful peer review in radiology.

  17. Extraction of orientation-and-scale-dependent information from GPR B-scans with tunable two-dimensional wavelet filters

    Science.gov (United States)

    Tzanis, A.

    2012-04-01

    GPR is an invaluable tool for civil and geotechnical engineering applications. One of the most significant objectives of such applications is the detection of fractures, inclined interfaces, empty or filled cavities frequently associated with jointing/faulting and a host of other oriented features. These types of target, especially fractures, are usually not good reflectors and are spatially localized. Their scale is therefore a factor significantly affecting their detectability. Quite frequently, systemic or extraneous noise, or other significant structural characteristics swamp the data with information which blurs, or even masks reflections from such targets, rendering their recognition difficult. This paper reports a method of extracting information (isolating) oriented and scale-dependent structural characteristics, based on oriented two-dimensional B-spline wavelet filters and Gabor wavelet filters. In addition to their advantageous properties (e.g. compact support, orthogonality etc), B-spline wavelets comprise a family with a broad spectrum of frequency localization properties and frequency responses that mimic, more or less, the shape of the radar source wavelet. For instance, the Ricker wavelet is also approximated by derivatives of Cardinal B-splines. An oriented two-dimensional B-spline filter is built by sidewise arranging a number of identical one-dimensional wavelets to create a matrix, tapering the edge-parallel direction with an orthogonal window function and rotating the resulting matrix to the desired orientation. The length of the one-dimensional wavelet (edge-normal direction) determines the width of the topographic features to be isolated. The number of parallel wavelets (edge-parallel direction) determines the feature length over which to smooth. The Gabor wavelets were produced by a Gabor kernel that is a product of an elliptical Gaussian and a complex plane wave: it is two-dimensional by definition. Their applications have hitherto focused

  18. Using Meaningful Contexts to Promote Understanding of Pronumerals

    Science.gov (United States)

    Linsell, Chris; Cavanagh, Michael; Tahir, Salma

    2013-01-01

    Developing a conceptual understanding of elementary algebra has been the focus of a number of recent articles in this journal. Baroudi (2006) advocated problem solving to assist students' transition from arithmetic to algebra, and Shield (2008) described the use of meaningful contexts for developing the concept of function. Samson (2011, 2012)…

  19. Concept Maps: An Instructional Tool to Facilitate Meaningful Learning

    Science.gov (United States)

    Safdar, Muhammad; Hussain, Azhar; Shah, Iqbal; Rifat, Qudsia

    2012-01-01

    This paper describes the procedure of developing an instructional tool, "concept mapping" and its effectiveness in making the material meaningful to the students. In Pakistan, the traditional way of teaching science subjects at all levels at school relies heavily on memorization. The up-to-date data obtained from qualitative and…

  20. Meaningful Gamification in an Industrial/Organizational Psychology Course

    Science.gov (United States)

    Stansbury, Jessica A.; Earnest, David R.

    2017-01-01

    Motivation and game research continue to demonstrate that the implementation of game design characteristics in the classroom can be engaging and intrinsically motivating. The present study assessed the extent to which an industrial organizational psychology course designed learning environment created with meaningful gamification elements can…

  1. Facilitating Meaningful Discussion Groups in the Primary Grades

    Science.gov (United States)

    Moses, Lindsey; Ogden, Meridith; Kelly, Laura Beth

    2015-01-01

    This Teaching Tips describes a yearlong process of facilitating meaningful discussion groups about literature with first-grade students in an urban Title I school. At the beginning of the year, the teacher provided explicit instruction in speaking and listening skills to support students with the social skills needed for thoughtful discussion. She…

  2. Making "Professionalism" Meaningful to Students in Higher Education

    Science.gov (United States)

    Wilson, Anna; Åkerlind, Gerlese; Walsh, Barbara; Stevens, Bruce; Turner, Bethany; Shield, Alison

    2013-01-01

    With rising vocational expectations of higher education, universities are increasingly promoting themselves as preparing students for future professional lives. This makes it timely to ask what makes professionalism meaningful to students. In addressing this question, we first identify aspects of professionalism that might represent appropriate…

  3. Meaningful civicness for the many : A comment on Erik Claes

    NARCIS (Netherlands)

    Dekker, P.

    2016-01-01

    This comment on Erik Claes values his treatment of in-depth interviews to gain a better understanding of how volunteers make sense of their activities, but it questions the representativeness, meaningfulness and civicness of what is found. Meaning as deep personal commitment to an objective value (S

  4. How Do Novice Art Teachers Define and Implement Meaningful Curriculum?

    Science.gov (United States)

    Bain, Christina; Newton, Connie; Kuster, Deborah; Milbrandt, Melody

    2010-01-01

    Four researchers collaborated on this qualitative case study that examined 11 first-year novice art teachers' understanding and implementation of meaningful curriculum. Participants were selected through a criterion method sampling strategy; the subjects were employed in rural, urban, and suburban public school districts. In order to conduct a…

  5. Meaningful Gamification in an Industrial/Organizational Psychology Course

    Science.gov (United States)

    Stansbury, Jessica A.; Earnest, David R.

    2017-01-01

    Motivation and game research continue to demonstrate that the implementation of game design characteristics in the classroom can be engaging and intrinsically motivating. The present study assessed the extent to which an industrial organizational psychology course designed learning environment created with meaningful gamification elements can…

  6. The Role of Meaningful Dialogue in Early Childhood Education Leadership

    Science.gov (United States)

    Deakins, Eric

    2007-01-01

    Action research was used to study the effectiveness of Learning Organisation and Adaptive Enterprise theories for promoting organisation-wide learning and creating a more effective early childhood education organisation. This article describes the leadership steps taken to achieve shared vision via meaningful dialogue between board, management and…

  7. Meaningful work in supportive environments: experiences with the recovery process.

    Science.gov (United States)

    Strong, S

    1998-01-01

    This ethnographic study examined what makes work meaningful for persons with persistent mental illness and how this meaningfulness relates to their recovery. Twelve persons between 32 and 58 years of age who had been involved an average of 19 years with a formal mental health system participated in in-depth interviews and a focus group. Thematic analysis and case studies were understood in the context of the investigator's 15 months of participant observation of 35 persons with psychiatric disabilities working at an affirmative business. The meaning of work varied with participants perception of their illness and their self-concept. Changes in their self-efficacy and self-concept were driven by their participation in work activities to operate the affirmative business. Findings suggest that therapists could potentially facilitate these changes in clients' sense of self-efficacy and self-concept by helping them make connections with meaningful occupations and contributions to organizations in the community and to experience challenges and successes in the context of meaningful work.

  8. Meaningful Learning with Digital and Online Videos: Theoretical Perspectives

    Science.gov (United States)

    Karppinen, Paivi

    2005-01-01

    In this paper theoretical perspectives for analyzing the pedagogical meaningfulness of using videos in teaching, studying and learning are presented and discussed with a special focus on using digital and online video materials. The theoretical arguments were applied in the international Joint Inserts Bank (JIBS) for Schools project. Out of…

  9. Types of Meaningfulness of Life and Values of Future Teachers

    Science.gov (United States)

    Salikhova, Nailia R.

    2016-01-01

    The leading role of meaning of life in regulation of human's activity of all types provides the relevance of the research. The goal of the paper is to identify and describe types of meaningfulness of life in future teachers, and to reveal the specificity of values hierarchy indicative of each type. The leading approach applied in the research was…

  10. Today's 'meaningful use' standard for medication orders by hospitals may save few lives; later stages may do more.

    NARCIS (Netherlands)

    Jones, S.S.; Heaton, P.; Friedberg, M.W.; Schneider, E.C.

    2011-01-01

    The federal government is currently offering bonus payments through Medicare and Medicaid to hospitals, physicians, and other eligible health professionals who meet new standards for "meaningful use" of health information technology. Whether these incentives will improve care, reduce errors, and imp

  11. Today's 'meaningful use' standard for medication orders by hospitals may save few lives; later stages may do more.

    NARCIS (Netherlands)

    Jones, S.S.; Heaton, P.; Friedberg, M.W.; Schneider, E.C.

    2011-01-01

    The federal government is currently offering bonus payments through Medicare and Medicaid to hospitals, physicians, and other eligible health professionals who meet new standards for "meaningful use" of health information technology. Whether these incentives will improve care, reduce errors, and imp

  12. A Study of the Relative Effectiveness of a Meaningful Concrete and a Meaningful Symbolic Model in Learning a Selected Mathematical Principle.

    Science.gov (United States)

    Fennema, Elizabeth

    Reported is a study to determine the relative effectiveness of a meaningful concrete and a meaningful symbolic model in learning a selected mathematics principle. Subjects were from a second grade population and they were assigned to three treatments. Students assigned to Treatment 1 received instruction in the principle with a meaningful symbolic…

  13. Open Information Extraction

    Science.gov (United States)

    2010-12-31

    cxtraction http://www.cs.washington.edu/rcscarch/tcxtrunnci/ http://reverb.cs.washington.edu/ http://turingc.cs.washington.edu: 1234/lda sp demo v3/lda sp/rclations/ http://abstract.cs.washington.edu/~tlin/ leibniz /

  14. Web Information Extraction Research Based on Page Classification%基于页面分类的 Web 信息抽取方法研究

    Institute of Scientific and Technical Information of China (English)

    成卫青; 于静; 杨晶; 杨龙

    2013-01-01

    By means of analysis of existing Web information extraction and the current Web page characteristics,current extraction tech-niques are found to have problems that the types of extract page fixed and the extract results are not accurate. In order to make up for the deficiency mentioned above,propose a Web information extraction method based on page classification. This method is able to complete the extraction of the mainstream of information on the Internet page. By classifying the Web page and extracting the main body of the page,it overcomes the two problems existing in traditional method respectively. A complete model of the Web information extraction is designed and the details of each functional module are provided. The unique features of the model are containing modules of Web page principle part extraction and Web page classification,as well as using regular expression to generate extraction rules automatically that promote the generality and precision of the extraction method. Experimental results have verified the validity and accuracy of the method.%  通过对现有 Web 信息抽取方法和当前 Web 网页特点的分析,发现现有抽取技术存在抽取页面类型固定和抽取结果不准确的问题,为了弥补以上两个不足,文中提出了一种基于页面分类的 Web 信息抽取方法,此方法能够完成对互联网上主流信息的提取。通过对页面进行分类和对页面主体的提取,分别克服传统方法抽取页面类型固定和抽取结果不够准确的问题。文中设计了一个完整的 Web 信息抽取模型,并给出了各功能模块的实现方法。该模型包含页面主体提取、页面分类和信息抽取等模块,并利用正则表达式自动生成抽取规则,提高了抽取方法的通用性和准确性。最后用实验证实了文中方法的有效性与正确性。

  15. Residuals of autoregressive model providing additional information for feature extraction of pattern recognition-based myoelectric control.

    Science.gov (United States)

    Pan, Lizhi; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

    2015-01-01

    Myoelectric control based on pattern recognition has been studied for several decades. Autoregressive (AR) features are one of the mostly used feature extraction methods among myoelectric control studies. Almost all previous studies only used the AR coefficients without the residuals of AR model for classification. However, the residuals of AR model contain important amplitude information of the electromyography (EMG) signals. In this study, we added the residuals to the AR features (AR+re) and compared its performance with the classical sixth-order AR coefficients. We tested six unilateral transradial amputees and eight able-bodied subjects for eleven hand and wrist motions. The classification accuracy (CA) of the intact side for amputee subjects and the right hand for able-bodied subjects showed that the CA of AR+re features was slightly but significantly higher than that of classical AR features (p = 0.009), which meant that residuals could provide additional information to classical AR features for classification. Interestingly, the CA of the affected side for amputee subjects showed that there was no significant difference between the CA of AR+re features and classical AR features (p > 0.05). We attributed this to the fact that the amputee subjects could not use their affected side to produce consistent EMG patterns as their intact side or the dominant hand of the able-bodied subjects. Since the residuals were already available when the AR coefficients were computed, the results of this study suggested adding the residuals to classical AR features to potentially improve the performance of pattern recognition-based myoelectric control.

  16. Urban vegetation cover extraction from hyperspectral imagery and geographic information system spatial analysis techniques: case of Athens, Greece

    Science.gov (United States)

    Petropoulos, George P.; Kalivas, Dionissios P.; Georgopoulou, Iro A.; Srivastava, Prashant K.

    2015-01-01

    The present study aimed at evaluating the performance of two different pixel-based classifiers [spectral angle mapper (SAM) and support vector machines (SVMs)] in discriminating different land-cover classes in a typical urban setting, focusing particularly on urban vegetation cover by utilizing hyperspectral (EO-1 Hyperion) data. As a case study, the city of Athens, Greece, was used. Validation of urban vegetation predictions was based on the error matrix statistics. Additionally, the final urban vegetation cover maps were compared at a municipality level against reference urban vegetation cover estimates derived from the digitization of very high-resolution imagery. To ensure consistency and comparability of the results, the same training and validation points dataset were used to compare the different classifiers. The results showed that SVMs outperformed SAM in terms of both classification and urban vegetation cover mapping with an overall accuracy of 86.53% and Kappa coefficient 0.823, whereas for SAM classification, the accuracy statistics obtained were 75.13% and 0.673, respectively. Our results confirmed the ability of both techniques, when combined with Hyperion imagery, to extract urban vegetation cover for the case of a densely populated city with complex urban features, such as Athens. Our findings offer significant information at the local scale as regards to the presence of open green spaces in the urban environment of Athens. Such information is vital for successful infrastructure development, urban landscape planning, and improvement of urban environment. More widely, this study also contributes significantly toward an objective assessment of Hyperion in detecting and mapping urban vegetation cover.

  17. The Developing of Meaningful Activity in Artificial Environment

    DEFF Research Database (Denmark)

    Holsbæk, Jonas

    Abstract: The Developing of Meaningful Activity in Artificial Environment Subtheme: Innovations and Challenges in Occupational Therapy Category: Live stage: Elderly Area of Practice: Technology and Medical Science Keywords: Innovations and challenges, Occupational balance Introduction: Due....... The experience of Flow can be hard to achieve or maintain for people with Dementia due to their loss of skills over time. Objectives: The purpose of this project was to develop a platform that supports People with Dementia in performing physical activity, meaningfulness and the experience of Flow. Method......: Innovative methods such as: Workshops, Observations, Focus Groups and Interviews of; spouses, formal careers, Occupational Therapists students, Technical engineer students and people with Dementia. The data was put together with specialized qualification and the innovative method Living lab/user panel...

  18. Concept Mapping Using Cmap Tools to Enhance Meaningful Learning

    Science.gov (United States)

    Cañas, Alberto J.; Novak, Joseph D.

    Concept maps are graphical tools that have been used in all facets of education and training for organizing and representing knowledge. When learners build concept maps, meaningful learning is facilitated. Computer-based concept mapping software such as CmapTools have further extended the use of concept mapping and greatly enhanced the potential of the tool, facilitating the implementation of a concept map-centered learning environment. In this chapter, we briefly present concept mapping and its theoretical foundation, and illustrate how it can lead to an improved learning environment when it is combined with CmapTools and the Internet. We present the nationwide “Proyecto Conéctate al Conocimiento” in Panama as an example of how concept mapping, together with technology, can be adopted by hundreds of schools as a means to enhance meaningful learning.

  19. Politics of place: the meaningfulness of resisting spaces

    OpenAIRE

    Courpasson, David; Dany, F.; Delbridge, Rick

    2016-01-01

    The meaningfulness of the physical place within which resistance is nurtured and enacted has not been carefully considered in research on space and organizations. In this article, we offer two stories of middle managers developing resistance to managerial policies and decisions. We show that the appropriation and reconstruction of specific places by middle managers helps them to build autonomous resisting work thanks to the meanings that resisters attribute to the place in which they undertak...

  20. To learn meaningfully and to classify in chemistry

    Directory of Open Access Journals (Sweden)

    María Victoria Alzate Cano

    2006-08-01

    Full Text Available In our context, the teaching of chemistry does not make enough emphasis on the chemical criteria of substances classification and the chances that these they for a meaningful learning of several kind of substances based on functional groups and on the differentiation between pure substances and homogeneous mixtures as well as and among other chemical and physical modifications. This teaching situation implies a devaluation of the relevance that meaningful comprehension has on chemical language. In general, the later comprise the formulation of substances and the formulated representation of chemical transformations. These formulated representations are a bridge between the world of substances, their chemical transformations and their conceptualization. The periodic system of chemical elements as a basic classificatory system for substances according to their elemental composition is a conceptual tool for meaningful teaching and learning of substance groups in relation with their common functional groups. This leads to the development of substances classificatory systems, which allow the students to interact with the diversity of substances, to work with previous knowledge and concepts formation processes and to make explicit their knowledge through natural language and the way they use and signify the language of relative and molecular chemical formulas.

  1. To learn meaningfully and to classify in chemistry

    Directory of Open Access Journals (Sweden)

    María Victoria Alzate Cano

    2006-12-01

    Full Text Available In our context, the teaching of chemistry does not make enough emphasis on the chemical criteria of substances classification and the chances that these they for a meaningful learning of several kind of substances based on functional groups and on the differentiation between pure substances and homogeneous mixtures as well as and among other chemical and physical modifications. This teaching situation implies a devaluation of the relevance that meaningful comprehension has on chemical language. In general, the later comprise the formulation of substances and the formulated representation of chemical transformations. These formulated representations are a bridge between the world of substances, their chemical transformations and their conceptualization. The periodic system of chemical elements as a basic classificatory system for substances according to their elemental composition is a conceptual tool for meaningful teaching and learning of substance groups in relation with their common functional groups. This leads to the development of substances classificatory systems, which allow the students to interact with the diversity of substances, to work with previous knowledge and concepts formation processes and to make explicit their knowledge through natural language and the way they use and signify the language of relative and molecular chemical formulas.

  2. Extracting tag hierarchies.

    Directory of Open Access Journals (Sweden)

    Gergely Tibély

    Full Text Available Tagging items with descriptive annotations or keywords is a very natural way to compress and highlight information about the properties of the given entity. Over the years several methods have been proposed for extracting a hierarchy between the tags for systems with a "flat", egalitarian organization of the tags, which is very common when the tags correspond to free words given by numerous independent people. Here we present a complete framework for automated tag hierarchy extraction based on tag occurrence statistics. Along with proposing new algorithms, we are also introducing different quality measures enabling the detailed comparison of competing approaches from different aspects. Furthermore, we set up a synthetic, computer generated benchmark providing a versatile tool for testing, with a couple of tunable parameters capable of generating a wide range of test beds. Beside the computer generated input we also use real data in our studies, including a biological example with a pre-defined hierarchy between the tags. The encouraging similarity between the pre-defined and reconstructed hierarchy, as well as the seemingly meaningful hierarchies obtained for other real systems indicate that tag hierarchy extraction is a very promising direction for further research with a great potential for practical applications. Tags have become very prevalent nowadays in various online platforms ranging from blogs through scientific publications to protein databases. Furthermore, tagging systems dedicated for voluntary tagging of photos, films, books, etc. with free words are also becoming popular. The emerging large collections of tags associated with different objects are often referred to as folksonomies, highlighting their collaborative origin and the "flat" organization of the tags opposed to traditional hierarchical categorization. Adding a tag hierarchy corresponding to a given folksonomy can very effectively help narrowing or broadening the scope of

  3. Extracting tag hierarchies.

    Science.gov (United States)

    Tibély, Gergely; Pollner, Péter; Vicsek, Tamás; Palla, Gergely

    2013-01-01

    Tagging items with descriptive annotations or keywords is a very natural way to compress and highlight information about the properties of the given entity. Over the years several methods have been proposed for extracting a hierarchy between the tags for systems with a "flat", egalitarian organization of the tags, which is very common when the tags correspond to free words given by numerous independent people. Here we present a complete framework for automated tag hierarchy extraction based on tag occurrence statistics. Along with proposing new algorithms, we are also introducing different quality measures enabling the detailed comparison of competing approaches from different aspects. Furthermore, we set up a synthetic, computer generated benchmark providing a versatile tool for testing, with a couple of tunable parameters capable of generating a wide range of test beds. Beside the computer generated input we also use real data in our studies, including a biological example with a pre-defined hierarchy between the tags. The encouraging similarity between the pre-defined and reconstructed hierarchy, as well as the seemingly meaningful hierarchies obtained for other real systems indicate that tag hierarchy extraction is a very promising direction for further research with a great potential for practical applications. Tags have become very prevalent nowadays in various online platforms ranging from blogs through scientific publications to protein databases. Furthermore, tagging systems dedicated for voluntary tagging of photos, films, books, etc. with free words are also becoming popular. The emerging large collections of tags associated with different objects are often referred to as folksonomies, highlighting their collaborative origin and the "flat" organization of the tags opposed to traditional hierarchical categorization. Adding a tag hierarchy corresponding to a given folksonomy can very effectively help narrowing or broadening the scope of search. Moreover

  4. Extracting Tag Hierarchies

    Science.gov (United States)

    Tibély, Gergely; Pollner, Péter; Vicsek, Tamás; Palla, Gergely

    2013-01-01

    Tagging items with descriptive annotations or keywords is a very natural way to compress and highlight information about the properties of the given entity. Over the years several methods have been proposed for extracting a hierarchy between the tags for systems with a "flat", egalitarian organization of the tags, which is very common when the tags correspond to free words given by numerous independent people. Here we present a complete framework for automated tag hierarchy extraction based on tag occurrence statistics. Along with proposing new algorithms, we are also introducing different quality measures enabling the detailed comparison of competing approaches from different aspects. Furthermore, we set up a synthetic, computer generated benchmark providing a versatile tool for testing, with a couple of tunable parameters capable of generating a wide range of test beds. Beside the computer generated input we also use real data in our studies, including a biological example with a pre-defined hierarchy between the tags. The encouraging similarity between the pre-defined and reconstructed hierarchy, as well as the seemingly meaningful hierarchies obtained for other real systems indicate that tag hierarchy extraction is a very promising direction for further research with a great potential for practical applications. Tags have become very prevalent nowadays in various online platforms ranging from blogs through scientific publications to protein databases. Furthermore, tagging systems dedicated for voluntary tagging of photos, films, books, etc. with free words are also becoming popular. The emerging large collections of tags associated with different objects are often referred to as folksonomies, highlighting their collaborative origin and the “flat” organization of the tags opposed to traditional hierarchical categorization. Adding a tag hierarchy corresponding to a given folksonomy can very effectively help narrowing or broadening the scope of search

  5. Improving the user experience through practical data analytics gain meaningful insight and increase your bottom line

    CERN Document Server

    Fritz, Mike

    2015-01-01

    Improving the User Experience through Practical Data Analytics is your must-have resource for making UX design decisions based on data, rather than hunches. Authors Fritz and Berger help the UX professional recognize and understand the enormous potential of the ever-increasing user data that is often accumulated as a by-product of routine UX tasks, such as conducting usability tests, launching surveys, or reviewing clickstream information. Then, step-by-step, they explain how to utilize both descriptive and predictive statistical techniques to gain meaningful insight with that data. You'll be

  6. 事件信息抽取中的数据预处理方法研究%STUDY ON DATA PREPROCESSING METHODS IN EVENT INFORMATION EXTRACTION

    Institute of Scientific and Technical Information of China (English)

    孙中友; 李培峰; 朱巧明

    2011-01-01

    Event extraction is an important area in information extraction research. Due to such problems as incomplete information, unclear semanteme, diversified elementary expression and obvious event redundancy with event extraction, the thesis proposes both missing data filling algorithm based on statistics to perfect events with missing information, and event element standardisation based on rules and dictionaries to unify events which are expressed differently. By authenticating events it solves the problem of semantic ambiguity, fixes incorrect event extraction, at the mean time filters out events with obvious redundant information.%事件抽取是信息抽取领域的一个重要研究方向.针对事件抽取获得的信息不完整、语义不明确、元素表达多样性及明显事件冗余等问题,提出基于统计的缺失数据填充算法,使丢失信患的事件完备化;同时提出基于规则和词典的事件元素规格化将不同表述的事件统一化,通过事件真伪辨别解决了语义不明确问题,修正抽取不正确的事件,并过滤掉明显冗余信息的事件.

  7. Remote Sensing Image Feature Extracting Based Multiple Ant Colonies Cooperation

    Directory of Open Access Journals (Sweden)

    Zhang Zhi-long

    2014-02-01

    Full Text Available This paper presents a novel feature extraction method for remote sensing imagery based on the cooperation of multiple ant colonies. First, multiresolution expression of the input remote sensing imagery is created, and two different ant colonies are spread on different resolution images. The ant colony in the low-resolution image uses phase congruency as the inspiration information, whereas that in the high-resolution image uses gradient magnitude. The two ant colonies cooperate to detect features in the image by sharing the same pheromone matrix. Finally, the image features are extracted on the basis of the pheromone matrix threshold. Because a substantial amount of information in the input image is used as inspiration information of the ant colonies, the proposed method shows higher intelligence and acquires more complete and meaningful image features than those of other simple edge detectors.

  8. Aging, culture, and memory for socially meaningful item-context associations: an East-West cross-cultural comparison study.

    Directory of Open Access Journals (Sweden)

    Lixia Yang

    Full Text Available Research suggests that people in Eastern interdependent cultures process information more holistically and attend more to contextual information than do people in Western independent cultures. The current study examined the effects of culture and age on memory for socially meaningful item-context associations in 71 Canadians of Western European descent (35 young and 36 older and 72 native Chinese citizens (36 young and 36 older. All participants completed two blocks of context memory tasks. During encoding, participants rated pictures of familiar objects. In one block, objects were rated either for their meaningfulness in the independent living context or their typicality in daily life. In the other block, objects were rated for their meaningfulness in the context of fostering relationships with others or for their typicality in daily life. The encoding in each block was followed by a recognition test in which participants identified pictures and their associated contexts. The results showed that Chinese outperformed Canadians in context memory, though both culture groups showed similar age-related deficits in item and context memory. The results suggest that Chinese are at an advantage in memory for socially meaningful item-context associations, an advantage that continues from young adulthood into old age.

  9. Aging, culture, and memory for socially meaningful item-context associations: an East-West cross-cultural comparison study.

    Science.gov (United States)

    Yang, Lixia; Li, Juan; Spaniol, Julia; Hasher, Lynn; Wilkinson, Andrea J; Yu, Jing; Niu, Yanan

    2013-01-01

    Research suggests that people in Eastern interdependent cultures process information more holistically and attend more to contextual information than do people in Western independent cultures. The current study examined the effects of culture and age on memory for socially meaningful item-context associations in 71 Canadians of Western European descent (35 young and 36 older) and 72 native Chinese citizens (36 young and 36 older). All participants completed two blocks of context memory tasks. During encoding, participants rated pictures of familiar objects. In one block, objects were rated either for their meaningfulness in the independent living context or their typicality in daily life. In the other block, objects were rated for their meaningfulness in the context of fostering relationships with others or for their typicality in daily life. The encoding in each block was followed by a recognition test in which participants identified pictures and their associated contexts. The results showed that Chinese outperformed Canadians in context memory, though both culture groups showed similar age-related deficits in item and context memory. The results suggest that Chinese are at an advantage in memory for socially meaningful item-context associations, an advantage that continues from young adulthood into old age.

  10. Investigation of the methods of extracting information from IKONOS image in Qixia district of Nanjing land cover

    Science.gov (United States)

    Rami, Badawi; Feng, Xuezhi

    2007-06-01

    Qixia District is located in the north east of Nanjing City in China. The most beautiful mountain in Nanjing is located in this district. The District serves communication of Nanjing city. There are a total of 70 ports and harbors of different types, Highways extend in all directions and radiate to all parts of Jiangsu Province (whereas Nanjing is the capital of Jiangsu). The Shanghai-Nanjing highway, Yangtze River Bridge of Nanjing passes through the District. The District is a major area with concentrated modern industry in Nanjing and has formed four pillar industries, such as medicine and electronics, machine manufacture, new building materials and petrochemistry. The District has more than 30 universities, colleges and research institutes within. Recently the IKONOS satellite is to collect images with one-meter resolution. There was a need to acquire high spatial resolution images to classify the land use and land cover in the urban sites. This district has agriculture and an important base of farming. There are historic sites of cultural. Four methods has been used to extract the information from IKONOS image, the texture algorithm for this test are represent the vegetation are depend on normalized differences and normalized difference vegetations indices NDVI the unsupervised classification has been adopted to calcified the land cover in Qixia district while a new equation used to eliminated the non -vegetation pixel depending on the reflectance spectrum of Items in the image. This investigation shows that the urban vegetation cover in this district is contributing to mitigate the climate and decrease the pollution. This study probably help Qixia District to rebuilt into a modern riverside new district with beautiful landscape, to give more favorable social environment and a more wealthy life for its people.

  11. An analytical framework for extracting hydrological information from time series of small reservoirs in a semi-arid region

    Science.gov (United States)

    Annor, Frank; van de Giesen, Nick; Bogaard, Thom; Eilander, Dirk

    2013-04-01

    small reservoirs in the Upper East Region of Ghana. Reservoirs without obvious large seepage losses (field survey) were selected. To verify this, stable water isotopic samples are collected from groundwater upstream and downstream from the reservoir. By looking at possible enrichment of downstream groundwater, a good estimate of seepage can be made in addition to estimates on evaporation. We estimated the evaporative losses and compared those with field measurements using eddy correlation measurements. Lastly, we determined the cumulative surface runoff curves for the small reservoirs .We will present this analytical framework for extracting hydrological information from time series of small reservoirs and show the first results for our study region of northern Ghana.

  12. A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION

    OpenAIRE

    J. Sharmila; Subramani, A.

    2016-01-01

    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 methodolog...

  13. 流域不透水面及其变化信息提取%Extracting Impervious Surface and Its Change Information Using Satellite Remote Sensing Data

    Institute of Scientific and Technical Information of China (English)

    马雪梅; 李希峰

    2008-01-01

    Impervious surface is one of the important parameters of valley water circular simulation, scientific estimation for which has significant and practical value for the urban water quantity and process simulation, diffuse pollution estimating and the forecast of climate changes. The objective of this research is to get the information of impervious surface and its dynamic change. Through the computer-assisted field method, the technologies of decision tree and data mining were applied to withdraw the impervious surface information in research region by the Landsat TM data in 1988, 1994 and 2002. The results suggested that the accuracy of impervious surface information extraction in the study area arrived above 94.4% in 2002 image. On this basis, the mixed method was used to extract the location and the types of the impervious surface change. The overall accuracy of monitoring reached 89%, which meets the demand of the hydrological models.

  14. Information Extraction for Strategic Intelligence Research%信息抽取在战略情报研究中的应用

    Institute of Scientific and Technical Information of China (English)

    袁林

    2012-01-01

    Information extraction is an applied technology for language processing. It can improve the efficiency of obtaining information. Aiming at strategic intelligence research area, several typical methods of information extraction are introduced based on exploratory research on the technology. The technology can he used to solve the bottlenecks problems ot! intelligence analyses in strategic intelligence research.%信息抽取是一种可提高信息获取效率的应用性语言处理技术。针对战略情报研究,介绍了信息抽取技术的3种典型应用方法,并对该技术进行了探索性研究,以解决战略情报研究中面临的情报智能分析瓶颈问题。

  15. Information Extraction Method for Chinese Text Messages%面向中文短信的信息抽取方法

    Institute of Scientific and Technical Information of China (English)

    吴中彪; 刘椿年

    2011-01-01

    In the application domain of mobile phone 3D animation automatic generation system, resesrches the information extraction method for Chinese text messages. It proposes a method to do the information extraction on Chinese text messages. A domain template definition method based on the limited context-free grammar is defined. After that designs and implements a template base with the corresponding template parser. The template parser uses the left-first deduction algorithm to ensure the efficiency. Experimental results show that this method can expand the extracted range and improve the accuracy of information extraction.%在手机3D动画自动生成系统中,研究面向中文短信的信息抽取方法.设计一种基于上下文无关文法的模板定义方式,以及对应的模板知识库与模板解析器.在模板解析器处理数据的过程中,通过最左规约算法保证中文短信的信息抽取效率.实验结果表明,该方法在扩展抽取内容范围的同时,能提高信息抽取的准确性.

  16. Topic information extraction from Web pages based on tree comparison%基于树比较的Web页面主题信息抽取

    Institute of Scientific and Technical Information of China (English)

    朱梦麟; 李光耀; 周毅敏

    2011-01-01

    为了从具有海量信息的Internet上自动抽取Web页面的信息,提出了一种基于树比较的Web页面主题信息抽取方法。通过目标页面与其相似页面所构建的树之间的比较,简化了目标页面,并在此基础上生成抽取规则,完成了页面主题信息的抽取。对国内主要的一些网站页面进行的抽取检测表明,该方法可以准确、有效地抽取Web页面的主题信息。%In order to automatically extract Web page information from Internet that contains magnanimous information, this paper presented an approach based on tree comparison. This approach compared tree built from the target page with that ones built from its similar pages to simplify the target page. Extraction rules were generated on this basis, and then we used the rules to extract topic information from the target Web page. Experiment result shows this extraction method is precise and efficient.

  17. Genetic and conservation of Araucaria angustifolia: III DNA extraction protocol and informative capacity of RAPD markers for the analysis of genetic diversity in natural population

    OpenAIRE

    2004-01-01

    This study was aimed at adapting a DNA extraction protocol by Araucaria angustifolia leaves, and testing the informative capacity of RAPD markers for genetics diversity analysis in natural populations of this species. The extraction method was standardized by eight tested protocols and it was possible to obtain good quality DNA for RAPD reactions. The OD260/OD280 ratio ranged from 1.7 to 2.0 in 80% of the samples, indicating that they had a low level of protein contamination. The RAPD markers...

  18. Measuring meaningful learning in the undergraduate chemistry laboratory

    Science.gov (United States)

    Galloway, Kelli R.

    The undergraduate chemistry laboratory has been an essential component in chemistry education for over a century. The literature includes reports on investigations of singular aspects laboratory learning and attempts to measure the efficacy of reformed laboratory curriculum as well as faculty goals for laboratory learning which found common goals among instructors for students to learn laboratory skills, techniques, experimental design, and to develop critical thinking skills. These findings are important for improving teaching and learning in the undergraduate chemistry laboratory, but research is needed to connect the faculty goals to student perceptions. This study was designed to explore students' ideas about learning in the undergraduate chemistry laboratory. Novak's Theory of Meaningful Learning was used as a guide for the data collection and analysis choices for this research. Novak's theory states that in order for meaningful learning to occur the cognitive, affective, and psychomotor domains must be integrated. The psychomotor domain is inherent in the chemistry laboratory, but the extent to which the cognitive and affective domains are integrated is unknown. For meaningful learning to occur in the laboratory, students must actively integrate both the cognitive domain and the affective domains into the "doing" of their laboratory work. The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' cognitive and affective expectations and experiences within the context of conducting experiments in the undergraduate chemistry laboratory. Evidence for the validity and reliability of the data generated by the MLLI were collected from multiple quantitative studies: a one semester study at one university, a one semester study at 15 colleges and universities across the United States, and a longitudinal study where the MLLI was administered 6 times during two years of general and organic chemistry laboratory courses. Results from

  19. 网络舆情信息提取技术研究与实现%Research and Implementation of Information Extraction Technology in Network Public Opinion

    Institute of Scientific and Technical Information of China (English)

    刘华春; 王星捷

    2016-01-01

    Internet public opinion information extraction is the most critical part of public opinion analysis system,which is also a data base of the public opinion analysis and statistics. For this reason,a public opinion information extraction method based on clues topic is designed and implemented. In the method,pages of public opinion as one topic clue is divided to logical region,and the breadth-first search methods based on DOM tree is applied to design extraction algorithm of public opinion information. By setting a minimum repeat topic thresholdƟ,customized extraction format,removed duplicate and noise of information,public opinion extraction is realized effec-tively. By experiment of the public opinion of multiple forums,the results show that this scheme has good extract performance,and the re-call,the correct rate and F measure are higher,which is able to well extract forum and reviews and other public opinion information.%网络舆情信息提取是舆情分析系统中最为关键的部分,是实现舆情分析、舆情统计的数据基础。为此,设计和实现了一个基于话题线索的舆情信息提取方案。该方案将舆情页面以话题为线索进行逻辑划分;采用基于DOM树的广度优先搜索方法,设计了舆情信息提取算法;通过设置最低重复话题阈值兹,用户定制提取格式,信息去重去噪措施,实现了舆情信息的有效提取。通过对多个论坛舆情信息的提取实验,结果表明,所设计的方案有很好的提取性能,召回率、正确率、F指数都较高,能够很好地提取出论坛、评论等舆情信息。

  20. Extraction of yarn positional information from three-dimensional CT image of textile fabric using a yarn model for its structure analysis

    Institute of Scientific and Technical Information of China (English)

    Toshihiro Shinohara; Jun-ya Takayama; Shinji Ohyama; Akira Kobayashi

    2008-01-01

    This paper proposes a novel method for analyzing a textile fabric structure to extract positional information regarding each yarn using three-dimensional X-ray computed tomography (3D CT) image. Positional relationship among the yarns can be reconstructed using the extracted yarn positional information. In this paper, a sequence of points on the center line of each yarn of the sample is defined as the yarn positional information, since the sequence can be regarded as the representative position of the yarn. The sequence is extracted by tracing the yarn. The yarn is traced by estimating the yarn center and direction and correlating the yarn part of the 3D CT image with a 3D yarn model, which is moved along the estimated yarn direction. The trajectory of the center of the yarn model corresponds to the positional information of the yarn. The application of the proposed method is shown by experimentally applying the proposed method to a 3D CT image of a double-layered woven fabric. Furthermore, the experimental results for a plain knitted fabric show that this method can be applied to even knitted fabrics.