WorldWideScience

Sample records for knowledge discovery object

  1. Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

    Science.gov (United States)

    Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

    Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object

  2. A knowledge discovery object model API for Java

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2003-10-01

    Full Text Available Abstract Background Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. Results This work describes an application programming interface (API that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. Conclusions The Knowledge Discovery Object Model (KDOM API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at http://www.bcgsc.ca/bioinfo/software.

  3. Discovery simulations and the assessment of intuitive knowledge

    NARCIS (Netherlands)

    Swaak, Janine; de Jong, Anthonius J.M.

    2001-01-01

    The objective of the present work is to have a closer look at the relations between the features of discovery simulations, the learning processes elicited, the knowledge that results, and the methods used to measure this acquired knowledge. It is argued that discovery simulations are ‘rich’, have a

  4. Object-graphs for context-aware visual category discovery.

    Science.gov (United States)

    Lee, Yong Jae; Grauman, Kristen

    2012-02-01

    How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

  5. Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

    Science.gov (United States)

    Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

    2000-01-01

    These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

  6. Rough – Granular Computing knowledge discovery models

    Directory of Open Access Journals (Sweden)

    Mohammed M. Eissa

    2016-11-01

    Full Text Available Medical domain has become one of the most important areas of research in order to richness huge amounts of medical information about the symptoms of diseases and how to distinguish between them to diagnose it correctly. Knowledge discovery models play vital role in refinement and mining of medical indicators to help medical experts to settle treatment decisions. This paper introduces four hybrid Rough – Granular Computing knowledge discovery models based on Rough Sets Theory, Artificial Neural Networks, Genetic Algorithm and Rough Mereology Theory. A comparative analysis of various knowledge discovery models that use different knowledge discovery techniques for data pre-processing, reduction, and data mining supports medical experts to extract the main medical indicators, to reduce the misdiagnosis rates and to improve decision-making for medical diagnosis and treatment. The proposed models utilized two medical datasets: Coronary Heart Disease dataset and Hepatitis C Virus dataset. The main purpose of this paper was to explore and evaluate the proposed models based on Granular Computing methodology for knowledge extraction according to different evaluation criteria for classification of medical datasets. Another purpose is to make enhancement in the frame of KDD processes for supervised learning using Granular Computing methodology.

  7. Energy-Water Nexus Knowledge Discovery Framework

    Science.gov (United States)

    Bhaduri, B. L.; Foster, I.; Chandola, V.; Chen, B.; Sanyal, J.; Allen, M.; McManamay, R.

    2017-12-01

    As demand for energy grows, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. An integrated data driven modeling, analysis, and visualization capability is needed to understand, design, and develop efficient local and regional practices for the energy-water infrastructure components that can be guided with strategic (federal) policy decisions to ensure national energy resilience. To meet this need of the energy-water nexus (EWN) community, an Energy-Water Knowledge Discovery Framework (EWN-KDF) is being proposed to accomplish two objectives: Development of a robust data management and geovisual analytics platform that provides access to disparate and distributed physiographic, critical infrastructure, and socioeconomic data, along with emergent ad-hoc sensor data to provide a powerful toolkit of analysis algorithms and compute resources to empower user-guided data analysis and inquiries; and Demonstration of knowledge generation with selected illustrative use cases for the implications of climate variability for coupled land-water-energy systems through the application of state-of-the art data integration, analysis, and synthesis. Oak Ridge National Laboratory (ORNL), in partnership with Argonne National Laboratory (ANL) and researchers affiliated with the Center for International Earth Science Information Partnership (CIESIN) at Columbia University and State University of New York-Buffalo (SUNY), propose to develop this Energy-Water Knowledge Discovery Framework to generate new, critical insights regarding the complex dynamics of the EWN and its interactions with climate variability and change. An overarching

  8. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    OpenAIRE

    Chen, Qipeng; Fan, Zhong; Kaleshi, Dritan; Armour, Simon M D

    2015-01-01

    Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induct...

  9. Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data

    International Nuclear Information System (INIS)

    Rubel, Oliver; Ahern, Sean; Bethel, E. Wes; Biggin, Mark D.; Childs, Hank; Cormier-Michel, Estelle; DePace, Angela; Eisen, Michael B.; Fowlkes, Charless C.; Geddes, Cameron G.R.; Hagen, Hans; Hamann, Bernd; Huang, Min-Yu; Keranen, Soile V.E.; Knowles, David W.; Hendriks, Chris L. Luengo; Malik, Jitendra; Meredith, Jeremy; Messmer, Peter; Prabhat; Ushizima, Daniela; Weber, Gunther H.; Wu, Kesheng

    2010-01-01

    Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies 'such as efficient data management' supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

  10. Knowledge discovery in the prediction of bankruptcy

    NARCIS (Netherlands)

    Almeida, R.J.; Vieira, S.M.; Milea, D.V.; Kaymak, U.; Costa Sousa, da J.M.; Carvalho, J.P.; Dubois, D.; Kaymak, U.

    2009-01-01

    Knowledge discovery in databases (KDD) is the process of discovering interesting knowledge from large amounts of data. However, real-world datasets have problems such as incompleteness, redundancy, inconsistency, noise, etc. All these problems affect the performance of data mining algorithms. Thus,

  11. Knowledge discovery with classification rules in a cardiovascular dataset.

    Science.gov (United States)

    Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

    2005-12-01

    In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

  12. A collaborative filtering-based approach to biomedical knowledge discovery.

    Science.gov (United States)

    Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

    2018-02-15

    The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  13. Evaluating the inverse reasoning account of object discovery.

    Science.gov (United States)

    Carroll, Christopher D; Kemp, Charles

    2015-06-01

    People routinely make inferences about unobserved objects. A hotel guest with welts on his arms, for example, will often worry about bed bugs. The discovery of unobserved objects almost always involves a backward inference from some observed effects (e.g., welts) to unobserved causes (e.g., bed bugs). The inverse reasoning account, which is typically formalized as Bayesian inference, posits that the strength of a backward inference is closely connected to the strength of the corresponding forward inference from the unobserved causes to the observed effects. We evaluated the inverse reasoning account of object discovery in three experiments where participants were asked to discover the unobserved "attractors" and "repellers" that controlled a "particle" moving within an arena. Experiments 1 and 2 showed that participants often failed to provide the best explanations for various particle motions, even when the best explanations were simple and when participants enthusiastically endorsed these explanations when presented with them. This failure demonstrates that object discovery is critically dependent on the processes that support hypothesis generation-processes that the inverse reasoning account does not explain. Experiment 3 demonstrated that people sometimes generate explanations that are invalid even according to their own forward inferences, suggesting that the psychological processes that support forward and backward inference are less intertwined than the inverse reasoning account suggests. The experimental findings support an alternative account of object discovery in which people rely on heuristics to generate possible explanations. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Knowledge discovery from data streams

    CERN Document Server

    Gama, Joao

    2010-01-01

    Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams.The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks,

  15. Knowledge management and Discovery for advanced Enterprise Knowledge Engineering

    OpenAIRE

    Novi, Daniele

    2014-01-01

    2012 - 2013 The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. Th...

  16. 08471 Report -- Geographic Privacy-Aware Knowledge Discovery and Delivery

    OpenAIRE

    Kuijpers, Bart; Pedreschi, Dino; Saygin, Yucel; Spaccapietra, Stefano

    2009-01-01

    The Dagstuhl-Seminar on Geographic Privacy-Aware Knowledge Discovery and Delivery was held during 16 - 21 November, 2008, with 37 participants registered from various countries from Europe, as well as other parts of the world such as United States, Canada, Argentina, and Brazil. Issues in the newly emerging area of geographic knowledge discovery with a privacy perspective were discussed in a week to consolidate some of the research questions. The Dagstuhl program included...

  17. The relation between prior knowledge and students' collaborative discovery learning processes.

    NARCIS (Netherlands)

    Gijlers, Aaltje H.; de Jong, Anthonius J.M.

    2005-01-01

    In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication

  18. Concept Formation in Scientific Knowledge Discovery from a Constructivist View

    Science.gov (United States)

    Peng, Wei; Gero, John S.

    The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called "first-person" knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer's first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing

  19. Knowledge Discovery and Data Mining in Iran's Climatic Researches

    Science.gov (United States)

    Karimi, Mostafa

    2013-04-01

    Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for

  20. Engineering Application Way of Faults Knowledge Discovery Based on Rough Set Theory

    International Nuclear Information System (INIS)

    Zhao Rongzhen; Deng Linfeng; Li Chao

    2011-01-01

    For the knowledge acquisition puzzle of intelligence decision-making technology in mechanical industry, to use the Rough Set Theory (RST) as a kind of tool to solve the puzzle was researched. And the way to realize the knowledge discovery in engineering application is explored. A case extracting out the knowledge rules from a concise data table shows out some important information. It is that the knowledge discovery similar to the mechanical faults diagnosis is an item of complicated system engineering project. In where, first of all-important tasks is to preserve the faults knowledge into a table with data mode. And the data must be derived from the plant site and should also be as concise as possible. On the basis of the faults knowledge data obtained so, the methods and algorithms to process the data and extract the knowledge rules from them by means of RST can be processed only. The conclusion is that the faults knowledge discovery by the way is a process of rising upward. But to develop the advanced faults diagnosis technology by the way is a large-scale knowledge engineering project for long time. Every step in which should be designed seriously according to the tool's demands firstly. This is the basic guarantees to make the knowledge rules obtained have the values of engineering application and the studies have scientific significance. So, a general framework is designed for engineering application to go along the route developing the faults knowledge discovery technology.

  1. 4th International conference on Knowledge Discovery and Data Mining

    CERN Document Server

    Knowledge Discovery and Data Mining

    2012-01-01

    The volume includes a set of selected papers extended and revised from the 4th International conference on Knowledge Discovery and Data Mining, March 1-2, 2011, Macau, Chin.   This Volume is to provide a forum for researchers, educators, engineers, and government officials involved in the general areas of knowledge discovery and data mining and learning to disseminate their latest research results and exchange views on the future research directions of these fields. 108 high-quality papers are included in the volume.

  2. SemaTyP: a knowledge graph based literature mining method for drug discovery.

    Science.gov (United States)

    Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

    2018-05-30

    Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

  3. Bioenergy Knowledge Discovery Framework Fact Sheet

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-07-01

    The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

  4. Network-based approaches to climate knowledge discovery

    Science.gov (United States)

    Budich, Reinhard; Nyberg, Per; Weigel, Tobias

    2011-11-01

    Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

  5. Object Knowledge Modulates Colour Appearance

    Directory of Open Access Journals (Sweden)

    Christoph Witzel

    2011-01-01

    Full Text Available We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis.

  6. Object knowledge modulates colour appearance

    Science.gov (United States)

    Witzel, Christoph; Valkova, Hanna; Hansen, Thorsten; Gegenfurtner, Karl R

    2011-01-01

    We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective) colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis. PMID:23145224

  7. 13 CFR 142.25 - Can a party or witness object to discovery?

    Science.gov (United States)

    2010-01-01

    ... discovery? 142.25 Section 142.25 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION PROGRAM FRAUD CIVIL REMEDIES ACT REGULATIONS Hearing Provisions § 142.25 Can a party or witness object to discovery? Any party or prospective witness may file a motion to quash a subpoena or to limit discovery or the...

  8. Developing integrated crop knowledge networks to advance candidate gene discovery.

    Science.gov (United States)

    Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

    2016-12-01

    The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

  9. Enhancing Big Data Value Using Knowledge Discovery Techniques

    OpenAIRE

    Mai Abdrabo; Mohammed Elmogy; Ghada Eltaweel; Sherif Barakat

    2016-01-01

    The world has been drowned by floods of data due to technological development. Consequently, the Big Data term has gotten the expression to portray the gigantic sum. Different sorts of quick data are doubling every second. We have to profit from this enormous surge of data to convert it to knowledge. Knowledge Discovery (KDD) can enhance detecting the value of Big Data based on some techniques and technologies like Hadoop, MapReduce, and NoSQL. The use of Big D...

  10. Drive Cost Reduction, Increase Innovation and Mitigate Risk with Advanced Knowledge Discovery Tools Designed to Unlock and Leverage Prior Knowledge

    International Nuclear Information System (INIS)

    Mitchell, I.

    2016-01-01

    Full text: The nuclear industry is knowledge-intensive and includes a diverse number of stakeholders. Much of this knowledge is at risk as engineers, technicians and project professionals retire, leaving a widening skills and information gap. This knowledge is critical in an increasingly complex environment with information from past projects often buried in decades-old, non-integrated systems enterprise. Engineers can spend 40% or more of their time searching for answers across the enterprise instead of solving problems. The inability to access trusted industry knowledge results in increased risk and expense. Advanced knowledge discovery technologies slash research times by as much as 75% and accelerate innovation and problem solving by giving technical professionals access to the information they need, in the context of the problems they are trying to solve. Unlike traditional knowledge management approaches, knowledge discovery tools powered by semantic search technologies are adept at uncovering answers in unstructured data and require no tagging, organization or moving of data, meaning a smaller IT footprint and faster time-to-knowledge. This session will highlight best-in-class knowledge discovery technologies, content, and strategies to give nuclear industry organizations the ability to leverage the corpus of enterprise knowledge into the future. (author

  11. Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

    DEFF Research Database (Denmark)

    Wilkowski, Bartlomiej

    This thesis discusses potential applications of semantics to the recent literaturebased informatics systems to facilitate knowledge discovery, hypothesis generation, and literature retrieval in the domain of biomedicine. The approaches presented herein make use of semantic information extracted...

  12. Knowledge Discovery in Data in Construction Projects

    Directory of Open Access Journals (Sweden)

    Szelka J.

    2016-06-01

    Full Text Available Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones, the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. It has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones, allowing for the use of this knowledge in the area under consideration.

  13. Data-Centric Knowledge Discovery Strategy for a Safety-Critical Sensor Application

    Directory of Open Access Journals (Sweden)

    Nilamadhab Mishra

    2014-01-01

    Full Text Available In an indoor safety-critical application, sensors and actuators are clustered together to accomplish critical actions within a limited time constraint. The cluster may be controlled by a dedicated programmed autonomous microcontroller device powered with electricity to perform in-network time critical functions, such as data collection, data processing, and knowledge production. In a data-centric sensor network, approximately 3–60% of the sensor data are faulty, and the data collected from the sensor environment are highly unstructured and ambiguous. Therefore, for safety-critical sensor applications, actuators must function intelligently within a hard time frame and have proper knowledge to perform their logical actions. This paper proposes a knowledge discovery strategy and an exploration algorithm for indoor safety-critical industrial applications. The application evidence and discussion validate that the proposed strategy and algorithm can be implemented for knowledge discovery within the operational framework.

  14. Advances in knowledge discovery in databases

    CERN Document Server

    Adhikari, Animesh

    2015-01-01

    This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis.  

  15. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  16. Asymmetric threat data mining and knowledge discovery

    Science.gov (United States)

    Gilmore, John F.; Pagels, Michael A.; Palk, Justin

    2001-03-01

    Asymmetric threats differ from the conventional force-on- force military encounters that the Defense Department has historically been trained to engage. Terrorism by its nature is now an operational activity that is neither easily detected or countered as its very existence depends on small covert attacks exploiting the element of surprise. But terrorism does have defined forms, motivations, tactics and organizational structure. Exploiting a terrorism taxonomy provides the opportunity to discover and assess knowledge of terrorist operations. This paper describes the Asymmetric Threat Terrorist Assessment, Countering, and Knowledge (ATTACK) system. ATTACK has been developed to (a) data mine open source intelligence (OSINT) information from web-based newspaper sources, video news web casts, and actual terrorist web sites, (b) evaluate this information against a terrorism taxonomy, (c) exploit country/region specific social, economic, political, and religious knowledge, and (d) discover and predict potential terrorist activities and association links. Details of the asymmetric threat structure and the ATTACK system architecture are presented with results of an actual terrorist data mining and knowledge discovery test case shown.

  17. Service-oriented discovery of knowledge : foundations, implementations and applications

    NARCIS (Netherlands)

    Bruin, Jeroen Sebastiaan de

    2010-01-01

    In this thesis we will investigate how a popular new way of distributed computing called service orientation can be used within the field of Knowledge Discovery. We critically investigate its principles and present models for developing withing this paradigm. We then apply this model to create a web

  18. Knowledge Discovery from Vibration Measurements

    Directory of Open Access Journals (Sweden)

    Jun Deng

    2014-01-01

    Full Text Available The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM. However, as a part of the overall process of knowledge discovery from data bases (KDD, the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques.

  19. An Object-oriented Knowledge Link Model for General Knowledge Management

    OpenAIRE

    Xiao-hong, CHEN; Bang-chuan, LAI

    2005-01-01

    The knowledge link is the basic on knowledge share and the indispensable part in knowledge standardization management. In this paper, a object-oriented knowledge link model is proposed for general knowledge management by using objectoriented representation based on knowledge levels system. In the model, knowledge link is divided into general knowledge link and integrated knowledge with corresponding link properties and methods. What’s more, its BNF syntax is described and designed.

  20. A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective

    OpenAIRE

    Mishra, Nilamadhab; Lin, Chung-Chih; Chang, Hsien-Tsung

    2015-01-01

    In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propos...

  1. Mandolin: A Knowledge Discovery Framework for the Web of Data

    OpenAIRE

    Soru, Tommaso; Esteves, Diego; Marx, Edgard; Ngomo, Axel-Cyrille Ngonga

    2017-01-01

    Markov Logic Networks join probabilistic modeling with first-order logic and have been shown to integrate well with the Semantic Web foundations. While several approaches have been devised to tackle the subproblems of rule mining, grounding, and inference, no comprehensive workflow has been proposed so far. In this paper, we fill this gap by introducing a framework called Mandolin, which implements a workflow for knowledge discovery specifically on RDF datasets. Our framework imports knowledg...

  2. Data Mining in Education : A Review on the Knowledge Discovery Perspective

    OpenAIRE

    Pratiyush Guleria; Manu Sood

    2014-01-01

    Knowledge Discovery in Databases is the process of finding knowledge in massive amount of data where data mining is the core of this process. Data minin g can be used to mine understandable meaningful patterns from large databases and these patterns ma y then be converted into knowledge.Data mining is t he process of extracting the information and patterns derived by the KDD process which helps in crucial decision-making.Data mining works with data warehou se and...

  3. Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

    Science.gov (United States)

    Fox, P.

    2012-04-01

    The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

  4. Knowledge Discovery and Data Mining (KDDM) survey report.

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, Laurence R.; Jordan, Danyelle N.; Bauer, Travis L.; Elmore, Mark T. (Oak Ridge National Laboratory, Oak Ridge, TN); Treadwell, Jim N. (Oak Ridge National Laboratory, Oak Ridge, TN); Homan, Rossitza A.; Chapman, Leon Darrel; Spires, Shannon V.

    2005-02-01

    The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.

  5. KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

    Science.gov (United States)

    Holzinger, Andreas; Zupan, Mario

    2013-06-13

    Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

  6. Machine Learning Methods for Knowledge Discovery in Medical Data on Atherosclerosis

    Czech Academy of Sciences Publication Activity Database

    Serrano, J.I.; Tomečková, Marie; Zvárová, Jana

    2006-01-01

    Roč. 1, - (2006), s. 6-33 ISSN 1801-5603 Institutional research plan: CEZ:AV0Z10300504 Keywords : knowledge discovery * supervised machine learning * biomedical data mining * risk factors of atherosclerosis Subject RIV: BB - Applied Statistics, Operational Research

  7. Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2017-12-01

    Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

  8. Methodologies of Knowledge Discovery from Data and Data Mining Methods in Mechanical Engineering

    Directory of Open Access Journals (Sweden)

    Rogalewicz Michał

    2016-12-01

    Full Text Available The paper contains a review of methodologies of a process of knowledge discovery from data and methods of data exploration (Data Mining, which are the most frequently used in mechanical engineering. The methodologies contain various scenarios of data exploring, while DM methods are used in their scope. The paper shows premises for use of DM methods in industry, as well as their advantages and disadvantages. Development of methodologies of knowledge discovery from data is also presented, along with a classification of the most widespread Data Mining methods, divided by type of realized tasks. The paper is summarized by presentation of selected Data Mining applications in mechanical engineering.

  9. Knowledge discovery from models of soil properties developed through data mining

    NARCIS (Netherlands)

    Bui, E.N.; Henderson, B.L.; Viergever, K.

    2006-01-01

    We modelled the distribution of soil properties across the agricultural zone on the Australian continent using data mining and knowledge discovery from databases (DM&KDD) tools. Piecewise linear tree models were built choosing from 19 climate variables, digital elevation model (DEM) and derived

  10. The Role of Knowledge Objects in Participatory Ergonomics Simulation

    DEFF Research Database (Denmark)

    Andersen, Simone Nyholm

    2015-01-01

    Participatory ergonomics simulations, taking place in simulation labs, have the tendency to get detached from the surrounding design process, resulting in a knowledge gap. Few studies in the human factors and ergonomics field have applied knowledge management based object concepts in the study...... of knowledge generation and transfer over such gaps. This paper introduces the concept of knowledge object to identify the roles of objects in an exploratory case study of five participatory simulation activities. The simulations had the purpose of contributing to room design of a new Danish hospital....... The analysis showed sequences and transitions of the knowledge objects revealing the process behind the knowledge interpretations and development of the future hospital rooms. Practitioner Summary: When planning participatory simulation in a lab context, the ergonomist should consider the role of objects...

  11. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.

    Science.gov (United States)

    Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

    2016-12-15

    With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM³ ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

  12. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management

    Science.gov (United States)

    Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

    2016-01-01

    With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs. PMID:27983713

  13. Topical video object discovery from key frames by modeling word co-occurrence prior.

    Science.gov (United States)

    Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

    2015-12-01

    A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

  14. Knowledge-based simulation using object-oriented programming

    Science.gov (United States)

    Sidoran, Karen M.

    1993-01-01

    Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.

  15. Knowledge discovery in variant databases using inductive logic programming.

    Science.gov (United States)

    Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

    2013-01-01

    Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

  16. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA for Environmental Risk Management

    Directory of Open Access Journals (Sweden)

    Yan Li

    2016-12-01

    Full Text Available With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity and the degree of Socio-Economic Deprivation (SED at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

  17. Participative Knowledge Production of Learning Objects for E-Books.

    Science.gov (United States)

    Dodero, Juan Manuel; Aedo, Ignacio; Diaz, Paloma

    2002-01-01

    Defines a learning object as any digital resource that can be reused to support learning and thus considers electronic books as learning objects. Highlights include knowledge management; participative knowledge production, i.e. authoring electronic books by a distributed group of authors; participative knowledge production architecture; and…

  18. Knowledge transfer objects and innovation performance

    DEFF Research Database (Denmark)

    Sajadirad, Solmaz; Lassen, Astrid Heidemann

    2016-01-01

    Local knowledge of globally distributed subsidiaries may be a valuable source of innovation for headquarters. However, acquiring local knowledge of subsidiaries and transforming it into innovation performance remains a challenge for many multinational companies. In this paper, based on analysis...... of eleven multinational companies present in Danish industry, we characterize different approaches to the use of knowledge transfer objects (static vs. dynamic), and discuss the respective effect on innovation performance. A conceptual framework is proposed to classify such different approaches on the basis...

  19. Privacy-aware knowledge discovery novel applications and new techniques

    CERN Document Server

    Bonchi, Francesco

    2010-01-01

    Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover well-established results-they also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development. Divided into seve

  20. Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2016-12-01

    Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

  1. Reconstructing Sessions from Data Discovery and Access Logs to Build a Semantic Knowledge Base for Improving Data Discovery

    Directory of Open Access Journals (Sweden)

    Yongyao Jiang

    2016-04-01

    Full Text Available Big geospatial data are archived and made available through online web discovery and access. However, finding the right data for scientific research and application development is still a challenge. This paper aims to improve the data discovery by mining the user knowledge from log files. Specifically, user web session reconstruction is focused upon in this paper as a critical step for extracting usage patterns. However, reconstructing user sessions from raw web logs has always been difficult, as a session identifier tends to be missing in most data portals. To address this problem, we propose two session identification methods, including time-clustering-based and time-referrer-based methods. We also present the workflow of session reconstruction and discuss the approach of selecting appropriate thresholds for relevant steps in the workflow. The proposed session identification methods and workflow are proven to be able to extract data access patterns for further pattern analyses of user behavior and improvement of data discovery for more relevancy data ranking, suggestion, and navigation.

  2. The Initial Development of Object Knowledge by a Learning Robot.

    Science.gov (United States)

    Modayil, Joseph; Kuipers, Benjamin

    2008-11-30

    We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. We evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks including object recognition and achieving goals that require both planning and continuous control.

  3. ForEx++: A New Framework for Knowledge Discovery from Decision Forests

    Directory of Open Access Journals (Sweden)

    Md Nasim Adnan

    2017-11-01

    Full Text Available Decision trees are popularly used in a wide range of real world problems for both prediction and classification (logic rules discovery. A decision forest is an ensemble of decision trees and it is often built for achieving better predictive performance compared to a single decision tree. Besides improving predictive performance, a decision forest can be seen as a pool of logic rules (rules with great potential for knowledge discovery. However, a standard-sized decision forest usually generates a large number of rules that a user may not able to manage for effective knowledge analysis. In this paper, we propose a new, data set independent framework for extracting those rules that are comparatively more accurate, generalized and concise than others. We apply the proposed framework on rules generated by two different decision forest algorithms from some publicly available medical related data sets on dementia and heart disease. We then compare the quality of rules extracted by the proposed framework with rules generated from a single J48 decision tree and rules extracted by another recent method. The results reported in this paper demonstrate the effectiveness of the proposed framework.

  4. Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

    Science.gov (United States)

    Matthews, Bryan

    2018-01-01

    This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

  5. Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System

    Directory of Open Access Journals (Sweden)

    Donghua Chen

    2018-06-01

    Full Text Available Patient-reported posts in Online Health Communities (OHCs contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate that our proposed method outperforms existing methods in terms of providing knowledge support. Our method enhances knowledge support for online patients and can help develop intelligent OHCs in the future.

  6. OKBL: A language for representing object oriented knowledge

    International Nuclear Information System (INIS)

    Matsumoto, Y.; Sugiyai, I.; Ishikawa, K.

    1984-01-01

    Industrial system is operated by using numerous ''operator's knowledge'' about the system. Each knowledge can be regarded as an object and is represented and maintained as an 'ACTOR' and written in a language based on the actor concept. OKBL (Object Oriented Operational KnowledgeBase Management Language) is the language proposed here for this purpose and used in OKBS (a system based on OKBL). The OKBS inference mechanism on the knowledgebase written in OKBL is implemented by message passings among ACTORs. OKBS has been applied to the guidance system for the operators of electric power dispatch control stations

  7. Data Mining and Knowledge Discovery via Logic-Based Methods

    CERN Document Server

    Triantaphyllou, Evangelos

    2010-01-01

    There are many approaches to data mining and knowledge discovery (DM&KD), including neural networks, closest neighbor methods, and various statistical methods. This monograph, however, focuses on the development and use of a novel approach, based on mathematical logic, that the author and his research associates have worked on over the last 20 years. The methods presented in the book deal with key DM&KD issues in an intuitive manner and in a natural sequence. Compared to other DM&KD methods, those based on mathematical logic offer a direct and often intuitive approach for extracting easily int

  8. Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

    Science.gov (United States)

    Hassani-Pak, Keywan; Rawlings, Christopher

    2017-06-13

    Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

  9. A knowledge discovery in databases approach for industrial microgrid planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.; Montero, Eduardo

    2016-01-01

    The progressive application of Information and Communication Technologies to industrial processes has increased the amount of data gathered by manufacturing companies during last decades. Nowadays some standardized management systems, such as ISO 50.001 and ISO 14.001, exploit these data in order...... sustainable and proactive microgrid which allows identifying, designing and developing energy efficiency strategies at supply, management and energy use levels. In this context, the expansion of Internet of Things and Knowledge Discovery in Databases techniques will drive changes in current microgrid planning...

  10. Knowledge discovery from structured mammography reports using inductive logic programming.

    Science.gov (United States)

    Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

    2005-01-01

    The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

  11. How does non-formal marine education affect student attitude and knowledge? A case study using SCDNR's Discovery program

    Science.gov (United States)

    McGovern, Mary Francis

    Non-formal environmental education provides students the opportunity to learn in ways that would not be possible in a traditional classroom setting. Outdoor learning allows students to make connections to their environment and helps to foster an appreciation for nature. This type of education can be interdisciplinary---students not only develop skills in science, but also in mathematics, social studies, technology, and critical thinking. This case study focuses on a non-formal marine education program, the South Carolina Department of Natural Resources' (SCDNR) Discovery vessel based program. The Discovery curriculum was evaluated to determine impact on student knowledge about and attitude toward the estuary. Students from two South Carolina coastal counties who attended the boat program during fall 2014 were asked to complete a brief survey before, immediately after, and two weeks following the program. The results of this study indicate that both student knowledge about and attitude significantly improved after completion of the Discovery vessel based program. Knowledge and attitude scores demonstrated a positive correlation.

  12. Accelerating knowledge discovery through community data sharing and integration.

    Science.gov (United States)

    Yip, Y L

    2009-01-01

    To summarize current excellent research in the field of bioinformatics. Synopsis of the articles selected for the IMIA Yearbook 2009. The selection process for this yearbook's section on Bioinformatics results in six excellent articles highlighting several important trends First, it can be noted that Semantic Web technology continues to play an important role in heterogeneous data integration. Novel applications also put more emphasis on its ability to make logical inferences leading to new insights and discoveries. Second, translational research, due to its complex nature, increasingly relies on collective intelligence made available through the adoption of community-defined protocols or software architectures for secure data annotation, sharing and analysis. Advances in systems biology, bio-ontologies and text-ming can also be noted. Current biomedical research gradually evolves towards an environment characterized by intensive collaboration and more sophisticated knowledge processing activities. Enabling technologies, either Semantic Web or other solutions, are expected to play an increasingly important role in generating new knowledge in the foreseeable future.

  13. Semi-automated knowledge discovery: identifying and profiling human trafficking

    Science.gov (United States)

    Poelmans, Jonas; Elzinga, Paul; Ignatov, Dmitry I.; Kuznetsov, Sergei O.

    2012-11-01

    We propose an iterative and human-centred knowledge discovery methodology based on formal concept analysis. The proposed approach recognizes the important role of the domain expert in mining real-world enterprise applications and makes use of specific domain knowledge, including human intelligence and domain-specific constraints. Our approach was empirically validated at the Amsterdam-Amstelland police to identify suspects and victims of human trafficking in 266,157 suspicious activity reports. Based on guidelines of the Attorney Generals of the Netherlands, we first defined multiple early warning indicators that were used to index the police reports. Using concept lattices, we revealed numerous unknown human trafficking and loverboy suspects. In-depth investigation by the police resulted in a confirmation of their involvement in illegal activities resulting in actual arrestments been made. Our human-centred approach was embedded into operational policing practice and is now successfully used on a daily basis to cope with the vastly growing amount of unstructured information.

  14. Semantically-enabled Knowledge Discovery in the Deep Carbon Observatory

    Science.gov (United States)

    Wang, H.; Chen, Y.; Ma, X.; Erickson, J. S.; West, P.; Fox, P. A.

    2013-12-01

    The Deep Carbon Observatory (DCO) is a decadal effort aimed at transforming scientific and public understanding of carbon in the complex deep earth system from the perspectives of Deep Energy, Deep Life, Extreme Physics and Chemistry, and Reservoirs and Fluxes. Over the course of the decade DCO scientific activities will generate a massive volume of data across a variety of disciplines, presenting significant challenges in terms of data integration, management, analysis and visualization, and ultimately limiting the ability of scientists across disciplines to make insights and unlock new knowledge. The DCO Data Science Team (DCO-DS) is applying Semantic Web methodologies to construct a knowledge representation focused on the DCO Earth science disciplines, and use it together with other technologies (e.g. natural language processing and data mining) to create a more expressive representation of the distributed corpus of DCO artifacts including datasets, metadata, instruments, sensors, platforms, deployments, researchers, organizations, funding agencies, grants and various awards. The embodiment of this knowledge representation is the DCO Data Science Infrastructure, in which unique entities within the DCO domain and the relations between them are recognized and explicitly identified. The DCO-DS Infrastructure will serve as a platform for more efficient and reliable searching, discovery, access, and publication of information and knowledge for the DCO scientific community and beyond.

  15. A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.

    Science.gov (United States)

    Kothari, Cartik R; Payne, Philip R O

    2015-01-01

    In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.

  16. Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

    Science.gov (United States)

    Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

    2009-01-01

    In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

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

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

  18. The objectivity of local knowledge. Lessons from ethnobiology

    NARCIS (Netherlands)

    Ludwig, David

    2017-01-01

    This article develops an account of local epistemic practices on the basis of case studies from ethnobiology. I argue that current debates about objectivity often stand in the way of a more adequate understanding of local knowledge and ethnobiological practices in general. While local knowledge

  19. The Objectivity of Local Knowledge: Lessons From Ethnobiology

    NARCIS (Netherlands)

    Ludwig, D.J.

    2017-01-01

    This article develops an account of local epistemic practices on the basis of case studies from ethnobiology. I argue that current debates about objectivity often stand in the way of a more adequate understanding of local knowledge and ethnobiological practices in general. While local knowledge

  20. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

    Directory of Open Access Journals (Sweden)

    Tom L. Blundell

    2017-07-01

    Full Text Available The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called `linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  1. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry.

    Science.gov (United States)

    Blundell, Tom L

    2017-07-01

    The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein-protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called 'linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  2. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

    Science.gov (United States)

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

  3. KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    F. Boochs

    2012-07-01

    Full Text Available Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL, used for formulating the knowledge base and the Semantic Web Rule Language (SWRL with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.

  4. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    Science.gov (United States)

    Boochs, F.; Karmacharya, A.; Marbs, A.

    2012-07-01

    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

  5. NEOview: Near Earth Object Data Discovery and Query

    Science.gov (United States)

    Tibbetts, M.; Elvis, M.; Galache, J. L.; Harbo, P.; McDowell, J. C.; Rudenko, M.; Van Stone, D.; Zografou, P.

    2013-10-01

    Missions to Near Earth Objects (NEOs) figure prominently in NASA's Flexible Path approach to human space exploration. NEOs offer insight into both the origins of the Solar System and of life, as well as a source of materials for future missions. With NEOview scientists can locate NEO datasets, explore metadata provided by the archives, and query or combine disparate NEO datasets in the search for NEO candidates for exploration. NEOview is a software system that illustrates how standards-based interfaces facilitate NEO data discovery and research. NEOview software follows a client-server architecture. The server is a configurable implementation of the International Virtual Observatory Alliance (IVOA) Table Access Protocol (TAP), a general interface for tabular data access, that can be deployed as a front end to existing NEO datasets. The TAP client, seleste, is a graphical interface that provides intuitive means of discovering NEO providers, exploring dataset metadata to identify fields of interest, and constructing queries to retrieve or combine data. It features a powerful, graphical query builder capable of easing the user's introduction to table searches. Through science use cases, NEOview demonstrates how potential targets for NEO rendezvous could be identified by combining data from complementary sources. Through deployment and operations, it has been shown that the software components are data independent and configurable to many different data servers. As such, NEOview's TAP server and seleste TAP client can be used to create a seamless environment for data discovery and exploration for tabular data in any astronomical archive.

  6. ESIP's Earth Science Knowledge Graph (ESKG) Testbed Project: An Automatic Approach to Building Interdisciplinary Earth Science Knowledge Graphs to Improve Data Discovery

    Science.gov (United States)

    McGibbney, L. J.; Jiang, Y.; Burgess, A. B.

    2017-12-01

    Big Earth observation data have been produced, archived and made available online, but discovering the right data in a manner that precisely and efficiently satisfies user needs presents a significant challenge to the Earth Science (ES) community. An emerging trend in information retrieval community is to utilize knowledge graphs to assist users in quickly finding desired information from across knowledge sources. This is particularly prevalent within the fields of social media and complex multimodal information processing to name but a few, however building a domain-specific knowledge graph is labour-intensive and hard to keep up-to-date. In this work, we update our progress on the Earth Science Knowledge Graph (ESKG) project; an ESIP-funded testbed project which provides an automatic approach to building a dynamic knowledge graph for ES to improve interdisciplinary data discovery by leveraging implicit, latent existing knowledge present within across several U.S Federal Agencies e.g. NASA, NOAA and USGS. ESKG strengthens ties between observations and user communities by: 1) developing a knowledge graph derived from various sources e.g. Web pages, Web Services, etc. via natural language processing and knowledge extraction techniques; 2) allowing users to traverse, explore, query, reason and navigate ES data via knowledge graph interaction. ESKG has the potential to revolutionize the way in which ES communities interact with ES data in the open world through the entity, spatial and temporal linkages and characteristics that make it up. This project enables the advancement of ESIP collaboration areas including both Discovery and Semantic Technologies by putting graph information right at our fingertips in an interactive, modern manner and reducing the efforts to constructing ontology. To demonstrate the ESKG concept, we will demonstrate use of our framework across NASA JPL's PO.DAAC, NOAA's Earth Observation Requirements Evaluation System (EORES) and various USGS

  7. Deconstructing Human Papillomavirus (HPV) Knowledge: Objective and Perceived Knowledge in Males' Intentions to Receive the HPV Vaccine

    Science.gov (United States)

    Krawczyk, Andrea; Stephenson, Ellen; Perez, Samara; Lau, Elsa; Rosberger, Zeev

    2013-01-01

    Background: The human papillomavirus (HPV) vaccine was recently approved for men. To effectively tailor HPV education efforts toward men, it is important to understand what men know about HPV and how this knowledge relates to their decision to receive the vaccine. This study examines how objective HPV knowledge, objective HPV vaccine knowledge,…

  8. Electrophysiological evidence for effects of color knowledge in object recognition.

    Science.gov (United States)

    Lu, Aitao; Xu, Guiping; Jin, Hua; Mo, Lei; Zhang, Jijia; Zhang, John X

    2010-01-29

    Knowledge about the typical colors associated with familiar everyday objects (i.e., strawberries are red) is well-known to be represented in the conceptual semantic system. Evidence that such knowledge may also play a role in early perceptual processes for object recognition is scant. In the present ERP study, participants viewed a list of object pictures and detected infrequent stimulus repetitions. Results show that shortly after stimulus onset, ERP components indexing early perceptual processes, including N1, P2, and N2, differentiated between objects in their appropriate or congruent color from these objects in an inappropriate or incongruent color. Such congruence effect also occurred in N3 associated with semantic processing of pictures but not in N4 for domain-general semantic processing. Our results demonstrate a clear effect of color knowledge in early object recognition stages and support the following proposal-color as a surface property is stored in a multiple-memory system where pre-semantic perceptual and semantic conceptual representations interact during object recognition. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

  9. A knowledge discovery approach to urban analysis: Beyoglu Preservation Area as a data mine

    Directory of Open Access Journals (Sweden)

    Ahu Sokmenoglu Sohtorik

    2017-11-01

    Full Text Available Enhancing our knowledge of the complexities of cities in order to empower ourselves to make more informed decisions has always been a challenge for urban research. Recent developments in large-scale computing, together with the new techniques and automated tools for data collection and analysis are opening up promising opportunities for addressing this problem. The main motivation that served as the driving force behind this research is how these developments may contribute to urban data analysis. On this basis, the thesis focuses on urban data analysis in order to search for findings that can enhance our knowledge of urban environments, using the generic process of knowledge discovery using data mining. A knowledge discovery process based on data mining is a fully automated or semi-automated process which involves the application of computational tools and techniques to explore the “previously unknown, and potentially useful information” (Witten & Frank, 2005 hidden in large and often complex and multi-dimensional databases. This information can be obtained in the form of correlations amongst variables, data groupings (classes and clusters or more complex hypotheses (probabilistic rules of co-occurrence, performance vectors of prediction models etc.. This research targets researchers and practitioners working in the field of urban studies who are interested in quantitative/ computational approaches to urban data analysis and specifically aims to engage the interest of architects, urban designers and planners who do not have a background in statistics or in using data mining methods in their work. Accordingly, the overall aim of the thesis is the development of a knowledge discovery approach to urban analysis; a domain-specific adaptation of the generic process of knowledge discovery using data mining enabling the analyst to discover ‘relational urban knowledge’. ‘Relational urban knowledge’ is a term employed in this thesis to refer

  10. Knowledge discovery in traditional Chinese medicine: state of the art and perspectives.

    Science.gov (United States)

    Feng, Yi; Wu, Zhaohui; Zhou, Xuezhong; Zhou, Zhongmei; Fan, Weiyu

    2006-11-01

    As a complementary medical system to Western medicine, traditional Chinese medicine (TCM) provides a unique theoretical and practical approach to the treatment of diseases over thousands of years. Confronted with the increasing popularity of TCM and the huge volume of TCM data, historically accumulated and recently obtained, there is an urgent need to explore these resources effectively by the techniques of knowledge discovery in database (KDD). This paper aims at providing an overview of recent KDD studies in TCM field. A literature search was conducted in both English and Chinese publications, and major studies of knowledge discovery in TCM (KDTCM) reported in these materials were identified. Based on an introduction to the state of the art of TCM data resources, a review of four subfields of KDTCM research was presented, including KDD for the research of Chinese medical formula, KDD for the research of Chinese herbal medicine, KDD for TCM syndrome research, and KDD for TCM clinical diagnosis. Furthermore, the current state and main problems in each subfield were summarized based on a discussion of existing studies, and future directions for each subfield were also proposed accordingly. A series of KDD methods are used in existing KDTCM researches, ranging from conventional frequent itemset mining to state of the art latent structure model. Considerable interesting discoveries are obtained by these methods, such as novel TCM paired drugs discovered by frequent itemset analysis, functional community of related genes discovered under syndrome perspective by text mining, the high proportion of toxic plants in the botanical family Ranunculaceae disclosed by statistical analysis, the association between M-cholinoceptor blocking drug and Solanaceae revealed by association rule mining, etc. It is particularly inspiring to see some studies connecting TCM with biomedicine, which provide a novel top-down view for functional genomics research. However, further developments

  11. Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

    Directory of Open Access Journals (Sweden)

    Di Feng

    2018-02-01

    Full Text Available Reusing the tactile knowledge of some previously-explored objects (prior objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT, and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10 % when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20 % . The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer.

  12. Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

    Science.gov (United States)

    Espinoza Molina, D.; Datcu, M.

    2015-04-01

    The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

  13. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  14. RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

    Science.gov (United States)

    Tilton, James C.; Cook, Diane J.

    2008-01-01

    Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

  15. Informing child welfare policy and practice: using knowledge discovery and data mining technology via a dynamic Web site.

    Science.gov (United States)

    Duncan, Dean F; Kum, Hye-Chung; Weigensberg, Elizabeth Caplick; Flair, Kimberly A; Stewart, C Joy

    2008-11-01

    Proper management and implementation of an effective child welfare agency requires the constant use of information about the experiences and outcomes of children involved in the system, emphasizing the need for comprehensive, timely, and accurate data. In the past 20 years, there have been many advances in technology that can maximize the potential of administrative data to promote better evaluation and management in the field of child welfare. Specifically, this article discusses the use of knowledge discovery and data mining (KDD), which makes it possible to create longitudinal data files from administrative data sources, extract valuable knowledge, and make the information available via a user-friendly public Web site. This article demonstrates a successful project in North Carolina where knowledge discovery and data mining technology was used to develop a comprehensive set of child welfare outcomes available through a public Web site to facilitate information sharing of child welfare data to improve policy and practice.

  16. Knowledge discovery from seismic data using neural networks; Descoberta de conhecimento a partir de dados sismicos utilizando redes neurais

    Energy Technology Data Exchange (ETDEWEB)

    Paula, Wesley R. de; Costa, Bruno A.D.; Gomes, Herman M. [Universidade Federal de Campina Grande (UFCG), PB (Brazil)

    2004-07-01

    The analysis and interpretation of seismic data is of fundamental importance to the Oil Industry, since it helps discover geologic formations that are conducive to hydrocarbon accumulation. The use of seismic data in reservoir characterization may be performed through localized data inspections and clustering based on features of common seismic responses. This clustering or classification can be performed in two basic ways: visually, with the help of graphical tools; or using automatic classification techniques, such as statistical models and artificial neural networks. Neural network based methods are generally superior to rule- or knowledge-based systems, since they have a better generalization capability and are fault tolerant. Within this context, the main objective of this work is to describe methods that employ the two main neural network based approaches (supervised and unsupervised) in knowledge discovery from seismic data. Initially, the implementation and experiments were focused on the problem of seismic facies recognition using the unsupervised approach, but in future works, the implementation of the supervised approach, an application to fault detection and a parallel implementation of the proposed methods are planned. (author)

  17. Learning object repositories as knowledge management systems

    Directory of Open Access Journals (Sweden)

    Demetrios G. Sampson

    2013-06-01

    Full Text Available Over the past years, a number of international initiatives that recognize the importance of sharing and reusing digital educational resources among educational communities through the use of Learning Object Repositories (LORs have emerged. Typically, these initiatives focus on collecting digital educational resources that are offered by their creators for open access and potential reuse. Nevertheless, most of the existing LORs are designed more as digital repositories, rather than as Knowledge Management Systems (KMS. By exploiting KMSs functionalities in LORs would bare the potential to support the organization and sharing of educational communities’ explicit knowledge (depicted in digital educational resources constructed by teachers and/or instructional designers and tacit knowledge (depicted in teachers’ and students’ experiences and interactions of using digital educational resources available in LORs. Within this context, in this paper we study the design and the implementation of fourteen operating LORs from the KMSs’ perspective, so as to identify additional functionalities that can support the management of educational communities’ explicit and tacit knowledge. Thus, we propose a list of essential LORs’ functionalities, which aim to facilitate the organization and sharing of educational communities’ knowledge. Finally, we present the added value of these functionalities by identifying their importance towards addressing the current demands of web-facilitated educational communities, as well as the knowledge management activities that they execute.

  18. The development of object function and manipulation knowledge: evidence from a semantic priming study

    Directory of Open Access Journals (Sweden)

    Cynthia Collette

    2016-08-01

    Full Text Available Object semantics include object function and manipulation knowledge. Function knowledge refers to the goal attainable by using an object (e.g. the function of a key is to open or close a door while manipulation knowledge refers to gestures one has to execute to use an object appropriately (e.g. a key is held between the thumb and the index, inserted into the door lock and then turned.To date, several studies have assessed function and manipulation knowledge in brain lesion patients as well as in healthy adult populations. In patients with left brain damage, a double dissociation between these two types of knowledge has been reported; on the other hand, behavioral studies in healthy adults show that function knowledge is processed faster than manipulation knowledge. Empirical evidence has shown that object interaction in children differs from that in adults, suggesting that the access to function and manipulation knowledge in children might also differ.To investigate the development of object function and manipulation knowledge, 51 typically developing 8-9-10 year-old children and 17 healthy young adults were tested on a naming task associated with a semantic priming paradigm (190-ms SOA; prime duration: 90 ms in which a series of line drawings of manipulable objects were used. Target objects could be preceded by three priming contexts: related (e.g. knife-scissors for function; key-screwdriver for manipulation, unrelated but visually similar (e.g. glasses-scissors; baseball bat-screwdriver, and purely unrelated (e.g. die-scissors; tissue-screwdriver.Results showed a different developmental pattern of function and manipulation priming effects. Function priming effects were not present in children and emerged only in adults, with faster naming responses for targets preceded by objects sharing the same function. In contrast, manipulation priming effects were already present in 8-year-olds with faster naming responses for targets preceded by objects

  19. Text mining for traditional Chinese medical knowledge discovery: a survey.

    Science.gov (United States)

    Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

    2010-08-01

    Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

  20. From Data to Knowledge to Discoveries: Artificial Intelligence and Scientific Workflows

    Directory of Open Access Journals (Sweden)

    Yolanda Gil

    2009-01-01

    Full Text Available Scientific computing has entered a new era of scale and sharing with the arrival of cyberinfrastructure facilities for computational experimentation. A key emerging concept is scientific workflows, which provide a declarative representation of complex scientific applications that can be automatically managed and executed in distributed shared resources. In the coming decades, computational experimentation will push the boundaries of current cyberinfrastructure in terms of inter-disciplinary scope and integrative models of scientific phenomena under study. This paper argues that knowledge-rich workflow environments will provide necessary capabilities for that vision by assisting scientists to validate and vet complex analysis processes and by automating important aspects of scientific exploration and discovery.

  1. A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

    Science.gov (United States)

    Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

    2003-01-01

    Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

  2. [Objective and subjective knowledge of HIV/AIDS as predictor of condom use in adolescents].

    Science.gov (United States)

    Villaseñor-Sierra, Alberto; Caballero-Hoyos, Ramiro; Hidalgo-San Martín, Alfredo; Santos-Preciado, José Ignacio

    2003-01-01

    To evaluate the association between objective and subjective knowledge on HIV/AIDS and condom use. Analysis of a database from an anonymous, self-applied, randomized survey conducted between 1995 and 1996. Study subjects were 1,410 adolescents of four socioeconomic strata from Guadalajara, Mexico. Objective knowledge was assessed with 24 questions regarding HIV/AIDS, and subjective knowledge with the question "how much do you think you know about HIV/AIDS?" The variables associated with condom use were identified using logistic regression analysis and by calculating odds ratios with a 95% confidence interval. The degree of objective knowledge was "average", differentiated by socioeconomic strata (p subjective knowledge, adolescents from the low, medium, and high socioeconomic strata claimed to know "a little", and the ones from the lowest stratum claimed to know "very little". Condom use was higher in males (35.4%), and in adolescents from high socioeconomic strata (p objective and subjective knowledge (r = 0.37, p subjective knowledge was associated with condom use (p Subjective knowledge, belonging to medium and high socioeconomic strata and being male, were predictors of condom use.

  3. Usability of Discovery Portals

    OpenAIRE

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals are not spatial data experts but professionals with limited spatial knowledge, and a focus outside the spatial domain. An exploratory usability experiment was carried out in which three discovery p...

  4. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

    Science.gov (United States)

    Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

    2010-01-01

    Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

  5. The biological knowledge discovery by PCCF measure and PCA-F projection.

    Science.gov (United States)

    Jia, Xingang; Zhu, Guanqun; Han, Qiuhong; Lu, Zuhong

    2017-01-01

    In the process of biological knowledge discovery, PCA is commonly used to complement the clustering analysis, but PCA typically gives the poor visualizations for most gene expression data sets. Here, we propose a PCCF measure, and use PCA-F to display clusters of PCCF, where PCCF and PCA-F are modeled from the modified cumulative probabilities of genes. From the analysis of simulated and experimental data sets, we demonstrate that PCCF is more appropriate and reliable for analyzing gene expression data compared to other commonly used distances or similarity measures, and PCA-F is a good visualization technique for identifying clusters of PCCF, where we aim at such data sets that the expression values of genes are collected at different time points.

  6. An Object-Oriented Approach to Knowledge Representation in a Biomedical Domain

    NARCIS (Netherlands)

    Ensing, M.; Paton, R.; Speel, P.H.W.M.; Speel, P.H.W.M.; Rada, R.

    1994-01-01

    An object-oriented approach has been applied to the different stages involved in developing a knowledge base about insulin metabolism. At an early stage the separation of terminological and assertional knowledge was made. The terminological component was developed by medical experts and represented

  7. Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

    Directory of Open Access Journals (Sweden)

    Jing Kong

    2007-09-01

    Full Text Available This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery.

  8. Knowledge discovery for pancreatic cancer using inductive logic programming.

    Science.gov (United States)

    Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh

    2014-08-01

    Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.

  9. A Systematic Knowledge Management Approach Using Object-Oriented Theory in Customer Complaint Management

    Directory of Open Access Journals (Sweden)

    Wusheng Zhang

    2010-12-01

    Full Text Available Research into the effectiveness of customer complaint management has attracted researchers, yet there has been little discussion on customer complaint management in the context of systematic knowledge management approach particularly in the domain of hotel industry. This paper aims to address such gap through the application of object-oriented theory for which the notation of unified modelling language has been adopted for the representation of the concepts, objects, relationships and vocabularies in the domain. The paper used data from forty seven hotel management staff and academics in hospitalitymanagement to investigate lessons learned and best practices in customer complaint management and knowledge management. By providing insights into the potential of a knowledge management approach using object oriented theory, this study advances our understanding on how a knowledge management approach can systematically support the management of hotel customer complaints.

  10. The discovery of radioactivity: the centenary

    International Nuclear Information System (INIS)

    Patil, S.K.

    1995-01-01

    In the last decade of the nineteenth century, a number of fundamental discoveries of outstanding importance were made unexpectedly which marked the beginning of a new era in physics. A cascade of spectacular discoveries began with the announcement of the discovery of x-rays by Roentgen followed by the discoveries, in quick succession, of radioactivity by Becquerel, of Zeeman effect, of electron by J.J. Thomson, and of polonium and radium by the Curies. Both x-rays and radioactivity have wide applications in scientific, medical and industrial fields and have made outstanding contribution to the advancement of human knowledge and welfare. Radioactivity is well known and no other discovery in the field of physics or chemistry has had a more profound effect on our fundamental knowledge of nature. Present article, on the occasion of the centenary of the discovery of radioactivity, makes an attempt to describe some glimpses of the history of radioactivity. (author). 59 refs

  11. Discovery of an Unidentified Fermi Object as a Black Widow-Like Millisecond Pulsar

    Science.gov (United States)

    Kong, A. K. H.; Huang, R. H. H.; Cheng, K. S.; Takata, J.; Yatsu, Y.; Cheung, C. C.; Donato, D.; Lin, L. C. C.; Kataoka, J.; Takahashi, Y.; hide

    2012-01-01

    The Fermi Gamma-ray Space Telescope has revolutionized our knowledge of the gamma-ray pulsar population, leading to the discovery of almost 100 gamma-ray pulsars and dozens of gamma-ray millisecond pulsars (MSPs). Although the outer-gap model predicts different sites of emission for the radio and gamma-ray pulsars, until now all of the known gamma-ray MSPs have been visible in the radio. Here we report the discovery of a radio-quiet" gamma-ray emitting MSP candidate by using Fermi, Chandra, Swift, and optical observations. The X-ray and gamma-ray properties of the source are consistent with known gamma-ray pulsars. We also found a 4.63-hr orbital period in optical and X-ray data. We suggest that the source is a black widow-like MSP with a approx. 0.1 Stellar Mass late-type companion star. Based on the profile of the optical and X-ray light-curves, the companion star is believed to be heated by the pulsar while the X-ray emissions originate from pulsar magnetosphere and/or from intra-binary shock. No radio detection of the source has been reported yet and although no gamma-ray/radio pulsation has been found, we estimated that the spin period of the MSP is approx. 3-5 ms based on the inferred gamma-ray luminosity.

  12. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  13. A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

    Science.gov (United States)

    Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

    2015-01-01

    User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service. PMID:26393609

  14. A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

    Directory of Open Access Journals (Sweden)

    Muhammad Golam Kibria

    2015-09-01

    Full Text Available User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

  15. A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment.

    Science.gov (United States)

    Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

    2015-09-18

    User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

  16. From static to dynamic use of knowledge transfer objects and its effect on innovation performance

    DEFF Research Database (Denmark)

    Sajadirad, Solmaz; Lassen, Astrid Heidemann; Wæhrens, Brian Vejrum

    2016-01-01

    Many different tools (objects) are applied by companies to transfer knowledge to globally distributed subsidiaries. Nevertheless, tapping into the local knowledge of subsidiaries and transforming this into innovation capabilities remains a challenge for many multinational companies. In this paper......, we aim to discuss how different approach to the use of knowledge transfer objects can affect companies’ abilities to obtain the subsidiaries’ knowledge and utilize it to different degrees of innovation performance. For this purpose, we adopted a multiple case study approach consisting of ten...... multinational companies located in Denmark. Based on literature review and empirical evidence, we discuss that inter-firm objects can be considered as boundary objects if they support specific circumstances, i.e., interactions and negotiations, collaboration, shared understanding and identity...

  17. GrandBase: generating actionable knowledge from Big Data

    Directory of Open Access Journals (Sweden)

    Xiu Susie Fang

    2017-08-01

    Full Text Available Purpose – This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB, called GrandBase. Design/methodology/approach – In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase. In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed. Findings – Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed. Originality/value – To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem. Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

  18. Advances in Knowledge Discovery and Data Mining 21st Pacific Asia Conference, PAKDD 2017 Held in Jeju, South Korea, May 23 26, 2017. Proceedings Part I, Part II.

    Science.gov (United States)

    2017-06-27

    Data Mining 21’’ Pacific-Asia Conference, PAKDD 2017Jeju, South Korea, May 23-26, Sb. GRANT NUMBER 2017 Proceedings, Part I, Part II Sc. PROGRAM...Springer; Switzerland. 14. ABSTRACT The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference...in the areas of knowledge discovery and data mining (KDD). We had three keynote speeches, delivered by Sang Cha from Seoul National University

  19. Using concepts in literature-based discovery : Simulating Swanson's Raynaud-fish oil and migraine-magnesium discoveries

    NARCIS (Netherlands)

    Weeber, M; Klein, Henny; de Jong-van den Berg, LTW; Vos, R

    Literature-based discovery has resulted in new knowledge. In the biomedical context, Don R. Swanson has generated several literature-based hypotheses that have been corroborated experimentally and clinically. In this paper, we propose a two-step model of the discovery process in which hypotheses are

  20. Knowledge sharing in construction partnering projects - redundancy, boundary objects and brokers

    DEFF Research Database (Denmark)

    Koch, Christian; Thuesen, Christian

    2013-01-01

    is on two dialogue excerpts, one on process, and one on product knowledge exchanges. The diversity and disjunctive feature of the practices form a condition of possibility for knowledge handling and synthesis into the built construct. Relation-based interaction is necessary with boundary objects and brokers......This article adopts practice-based theory for understanding inter-organisational knowledge work and extends it with a discussion of the role of redundancy. In this view, a constellation of firms is a multiple configuration of communities of practices, characterised by overlapping practises......, multiple memberships and different levels of participation, and accompanied by a governance frame. The paper discusses central mechanisms for coordinating knowledge in such a complex construction project. The knowledge relations are conceptualised through focusing on redundancy, understood as negotiated...

  1. Exploiting core knowledge for visual object recognition.

    Science.gov (United States)

    Schurgin, Mark W; Flombaum, Jonathan I

    2017-03-01

    Humans recognize thousands of objects, and with relative tolerance to variable retinal inputs. The acquisition of this ability is not fully understood, and it remains an area in which artificial systems have yet to surpass people. We sought to investigate the memory process that supports object recognition. Specifically, we investigated the association of inputs that co-occur over short periods of time. We tested the hypothesis that human perception exploits expectations about object kinematics to limit the scope of association to inputs that are likely to have the same token as a source. In several experiments we exposed participants to images of objects, and we then tested recognition sensitivity. Using motion, we manipulated whether successive encounters with an image took place through kinematics that implied the same or a different token as the source of those encounters. Images were injected with noise, or shown at varying orientations, and we included 2 manipulations of motion kinematics. Across all experiments, memory performance was better for images that had been previously encountered with kinematics that implied a single token. A model-based analysis similarly showed greater memory strength when images were shown via kinematics that implied a single token. These results suggest that constraints from physics are built into the mechanisms that support memory about objects. Such constraints-often characterized as 'Core Knowledge'-are known to support perception and cognition broadly, even in young infants. But they have never been considered as a mechanism for memory with respect to recognition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery

    Directory of Open Access Journals (Sweden)

    Isabel Cristina Siqueira da Silva

    2017-05-01

    Full Text Available The evolution of technology has changed the face of education, especially when combined with appropriate pedagogical bases. This combination has created innovation opportunities in order to add quality to teaching through new perspectives for traditional methods applied in the classroom. In the Health field, particularly, augmented reality and interaction design techniques can assist the teacher in the exposition of theoretical concepts and/or concepts that need of training at specific medical procedures. Besides, visualization and interaction with Health data, from different sources and in different formats, helps to identify hidden patterns or anomalies, increases the flexibility in the search for certain values, allows the comparison of different units to obtain relative difference in quantities, provides human interaction in real time, etc. At this point, it is noted that the use of interactive visualization techniques such as augmented reality and virtual can collaborate with the process of knowledge discovery in medical and biomedical databases. This work discuss aspects related to the use of augmented reality and interaction design as a tool for teaching anatomy and knowledge discovery, with the proposition of an case study based on mobile application that can display targeted anatomical parts in high resolution and with detail of its parts.

  3. The Large Synoptic Survey Telescope as a Near-Earth Object discovery machine

    Science.gov (United States)

    Jones, R. Lynne; Slater, Colin T.; Moeyens, Joachim; Allen, Lori; Axelrod, Tim; Cook, Kem; Ivezić, Željko; Jurić, Mario; Myers, Jonathan; Petry, Catherine E.

    2018-03-01

    Using the most recent prototypes, design, and as-built system information, we test and quantify the capability of the Large Synoptic Survey Telescope (LSST) to discover Potentially Hazardous Asteroids (PHAs) and Near-Earth Objects (NEOs). We empirically estimate an expected upper limit to the false detection rate in LSST image differencing, using measurements on DECam data and prototype LSST software and find it to be about 450 deg-2. We show that this rate is already tractable with current prototype of the LSST Moving Object Processing System (MOPS) by processing a 30-day simulation consistent with measured false detection rates. We proceed to evaluate the performance of the LSST baseline survey strategy for PHAs and NEOs using a high-fidelity simulated survey pointing history. We find that LSST alone, using its baseline survey strategy, will detect 66% of the PHA and 61% of the NEO population objects brighter than H = 22 , with the uncertainty in the estimate of ± 5 percentage points. By generating and examining variations on the baseline survey strategy, we show it is possible to further improve the discovery yields. In particular, we find that extending the LSST survey by two additional years and doubling the MOPS search window increases the completeness for PHAs to 86% (including those discovered by contemporaneous surveys) without jeopardizing other LSST science goals (77% for NEOs). This equates to reducing the undiscovered population of PHAs by additional 26% (15% for NEOs), relative to the baseline survey.

  4. Translational Research 2.0: a framework for accelerating collaborative discovery.

    Science.gov (United States)

    Asakiewicz, Chris

    2014-05-01

    The world wide web has revolutionized the conduct of global, cross-disciplinary research. In the life sciences, interdisciplinary approaches to problem solving and collaboration are becoming increasingly important in facilitating knowledge discovery and integration. Web 2.0 technologies promise to have a profound impact - enabling reproducibility, aiding in discovery, and accelerating and transforming medical and healthcare research across the healthcare ecosystem. However, knowledge integration and discovery require a consistent foundation upon which to operate. A foundation should be capable of addressing some of the critical issues associated with how research is conducted within the ecosystem today and how it should be conducted for the future. This article will discuss a framework for enhancing collaborative knowledge discovery across the medical and healthcare research ecosystem. A framework that could serve as a foundation upon which ecosystem stakeholders can enhance the way data, information and knowledge is created, shared and used to accelerate the translation of knowledge from one area of the ecosystem to another.

  5. Integrating traditional knowledge when it appears to conflict with conservation: lessons from the discovery and protection of sitatunga in Ghana

    Directory of Open Access Journals (Sweden)

    Jana M. McPherson

    2016-03-01

    Full Text Available Cultural traditions can conflict with modern conservation goals when they promote damage to fragile environments or the harvest of imperiled species. We explore whether and how traditional, culturally motivated species exploitation can nonetheless aid conservation by examining the recent "discovery" in Avu Lagoon, Ghana, of sitatunga (Tragelaphus spekii gratus, a species familiar to locals, but not previously scientifically recorded in Ghana and regionally assumed extinct. Specifically, we investigate what role traditional beliefs, allied hunting practices, and the associated traditional ecological knowledge have played in the species' discovery and subsequent community-based conservation; how they might influence future conservation outcomes; and how they may themselves be shaped by conservation efforts. Our study serves to exemplify the complexities, risks, and benefits associated with building conservation efforts around traditional ecological knowledge and beliefs. Complexities arise from localized variation in beliefs (with cultural significance of sitatunga much stronger in one village than others, progressive dilution of traditional worldviews by mainstream religions, and the context dependence, both culturally and geographically, of the reliability of traditional ecological knowledge. Among the benefits, we highlight (1 information on the distribution and habitat needs of species that can help to discover, rediscover, or manage imperiled taxa if appropriately paired with scientific data collection; and (2 enhanced sustainability of conservation efforts given the cultivation of mutual trust, respect, and understanding between researchers and local communities. In turn, conservation attention to traditional ecological knowledge and traditionally important species can help reinvigorate cultural diversity by promoting the persistence of traditional belief and knowledge systems alongside mainstream worldviews and religions.

  6. Predicting future discoveries from current scientific literature.

    Science.gov (United States)

    Petrič, Ingrid; Cestnik, Bojan

    2014-01-01

    Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

  7. Socratic Questioning-Guided Discovery

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2012-04-01

    Full Text Available “Socratic Method” is a way of teaching philosophical thinking and knowledge by asking questions which was used by antique period greek philosopher Socrates. Socrates was teaching knowledge to his followers by asking questions and the conversation between them was named “Socratic Dialogues”. In this meaning, no novel knowledge is taught to the individual but only what is formerly known is reminded and rediscovered. The form of socratic questioning which is used during the process of cognitive behavioral therapy is known as Guided Discovery. In this method it is aimed to make the client notice the piece of knowledge which he could notice but is not aware with a series of questions. Socratic method or guided discovery consists of several steps which are: Identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly found information and questioning the old distorted belief and reaching to a conclusion and applying it. Question types used during these procedures are, questions for gaining information, questions revealing the meanings, questions revealing the beliefs, questions about behaviours during the similar past experiences, analyse questions and analytic synthesis questions. In order to make the patient feel understood it is important to be empathetic and summarising the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues after eachstep. [JCBPR 2012; 1(1.000: 15-20

  8. An Ontology-supported Approach for Automatic Chaining of Web Services in Geospatial Knowledge Discovery

    Science.gov (United States)

    di, L.; Yue, P.; Yang, W.; Yu, G.

    2006-12-01

    Recent developments in geospatial semantic Web have shown promise for automatic discovery, access, and use of geospatial Web services to quickly and efficiently solve particular application problems. With the semantic Web technology, it is highly feasible to construct intelligent geospatial knowledge systems that can provide answers to many geospatial application questions. A key challenge in constructing such intelligent knowledge system is to automate the creation of a chain or process workflow that involves multiple services and highly diversified data and can generate the answer to a specific question of users. This presentation discusses an approach for automating composition of geospatial Web service chains by employing geospatial semantics described by geospatial ontologies. It shows how ontology-based geospatial semantics are used for enabling the automatic discovery, mediation, and chaining of geospatial Web services. OWL-S is used to represent the geospatial semantics of individual Web services and the type of the services it belongs to and the type of the data it can handle. The hierarchy and classification of service types are described in the service ontology. The hierarchy and classification of data types are presented in the data ontology. For answering users' geospatial questions, an Artificial Intelligent (AI) planning algorithm is used to construct the service chain by using the service and data logics expressed in the ontologies. The chain can be expressed as a graph with nodes representing services and connection weights representing degrees of semantic matching between nodes. The graph is a visual representation of logical geo-processing path for answering users' questions. The graph can be instantiated to a physical service workflow for execution to generate the answer to a user's question. A prototype system, which includes real world geospatial applications, is implemented to demonstrate the concept and approach.

  9. 10 CFR 205.198 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 3 2010-01-01 2010-01-01 false Discovery. 205.198 Section 205.198 Energy DEPARTMENT OF... of Proposed Disallowance, and Order of Disallowance § 205.198 Discovery. (a) If a person intends to file a Motion for Discovery, he must file it at the same time that he files his Statement of Objections...

  10. Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.

    Science.gov (United States)

    Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F

    2016-04-01

    To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Integrating GIS components with knowledge discovery technology for environmental health decision support.

    Science.gov (United States)

    Bédard, Yvan; Gosselin, Pierre; Rivest, Sonia; Proulx, Marie-Josée; Nadeau, Martin; Lebel, Germain; Gagnon, Marie-France

    2003-04-01

    This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a SOLAP application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for GKD and decision-making in public health. The SOLAP concept is also described and a comparison is made with traditional GIS applications.

  12. An interactive visualization tool for mobile objects

    Science.gov (United States)

    Kobayashi, Tetsuo

    Recent advancements in mobile devices---such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID)---have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data

  13. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  14. View discovery in OLAP databases through statistical combinatorial optimization

    Energy Technology Data Exchange (ETDEWEB)

    Hengartner, Nick W [Los Alamos National Laboratory; Burke, John [PNNL; Critchlow, Terence [PNNL; Joslyn, Cliff [PNNL; Hogan, Emilie [PNNL

    2009-01-01

    OnLine Analytical Processing (OLAP) is a relational database technology providing users with rapid access to summary, aggregated views of a single large database, and is widely recognized for knowledge representation and discovery in high-dimensional relational databases. OLAP technologies provide intuitive and graphical access to the massively complex set of possible summary views available in large relational (SQL) structured data repositories. The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of 'views' of an OLAP database as a combinatorial object of all projections and subsets, and 'view discovery' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline 'hop-chaining' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a 'spiraling' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.

  15. Assessing College Student Subjective and Objective Knowledge in an Online Financial Education Program

    Science.gov (United States)

    Bowles, Charity

    2017-01-01

    Purpose: This purpose of this correlational study using Joo's (2008) financial wellness framework was to determine the impact of an online financial literacy workshop on student subjective knowledge, dependent on indicators of stress, behavior, and objective knowledge, when controlling for demographic differences at a large public university.…

  16. Network Structures in a Society Composed of Individuals with Utilities DependingStudy of Object-Oriented Model for the Knowledge Base System

    OpenAIRE

    Mingwei, Zhao; Yanzhong, Dang

    2005-01-01

    Based on the analysis of object-oriented model, knowledge base and knowledge base system by using theories on object-oriented and knowledge base, the relationships between object-oriented model and knowledge base are discussed in this paper. The architecture of object-oriented knowledge system is proposed and the Rule-Case-Based Reasoning knowledge base system is designed.

  17. PKDE4J: Entity and relation extraction for public knowledge discovery.

    Science.gov (United States)

    Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

    2015-10-01

    Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD

    Directory of Open Access Journals (Sweden)

    Stefania Pasanisi

    2018-04-01

    Full Text Available The healthcare ambit is usually perceived as “information rich” yet “knowledge poor”. Nowadays, an unprecedented effort is underway to increase the use of business intelligence techniques to solve this problem. Heart disease (HD is a major cause of mortality in modern society. This paper analyzes the risk factors that have been identified in cardiovascular disease (CVD surveillance systems. The Heart Care study identifies attributes related to CVD risk (gender, age, smoking habit, etc. and other dependent variables that include a specific form of CVD (diabetes, hypertension, cardiac disease, etc.. In this paper, we combine Clustering, Association Rules, and Neural Networks for the assessment of heart-event-related risk factors, targeting the reduction of CVD risk. With the use of the K-means algorithm, significant groups of patients are found. Then, the Apriori algorithm is applied in order to understand the kinds of relations between the attributes within the dataset, first looking within the whole dataset and then refining the results through the subsets defined by the clusters. Finally, both results allow us to better define patients’ characteristics in order to make predictions about CVD risk with a Multilayer Perceptron Neural Network. The results obtained with the hybrid information mining approach indicate that it is an effective strategy for knowledge discovery concerning chronic diseases, particularly for CVD risk.

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

    International Nuclear Information System (INIS)

    Whiteson, R.

    1998-01-01

    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

  20. Multi-agent system for Knowledge-based recommendation of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea RODRÍGUEZ MARÍN

    2015-12-01

    Full Text Available Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.

  1. Discovery of a Satellite of the Large Trans-Neptunian Object (225088) 2007 OR{sub 10}

    Energy Technology Data Exchange (ETDEWEB)

    Kiss, Csaba; Marton, Gábor; Farkas-Takács, Anikó; Vinkó, József; Pál, András [Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences, Konkoly Thege 15-17, H-1121 Budapest (Hungary); Stansberry, John [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Müller, Thomas [Max-Planck-Institut für extraterrestrische Physik, Postfach 1312, Giessenbachstr., D-85741 Garching (Germany); Balog, Zoltán [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Ortiz, Jose-Luis, E-mail: kiss.csaba@csfk.mta.hu [Instituto de Astrofísica de Andalucía—CSIC, Apt 3004, E-18080 Granada (Spain)

    2017-03-20

    2007 OR{sub 10} is currently the third largest known dwarf planet in the trans-Neptunian region, with an effective radiometric diameter of ∼1535 km. It has a slow rotation period of ∼45 hr that was suspected to be caused by tidal interactions with a satellite undetected at that time. Here, we report on the discovery of a likely moon of 2007 OR{sub 10}, identified on archival Hubble Space Telescope WFC3/UVIS system images. Although the satellite is detected at two epochs, this does not allow an unambiguous determination of the orbit and the orbital period. A feasible 1.5–5.8 · 10{sup 21} kg estimate for the system mass leads to a likely 35–100 day orbital period. The moon is about 4.ͫ2 fainter than 2007 OR{sub 10} in HST images that corresponds to a diameter of 237 km assuming equal albedos with the primary. Due to the relatively small size of the moon, the previous size and albedo estimates for the primary remains unchanged. With this discovery all trans-Neptunian objects larger than 1000 km are now known to harbor satellites, an important constraint for moon formation theories in the young solar system.

  2. A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY GLOBAL WARMING SCENARIOS

    Data.gov (United States)

    National Aeronautics and Space Administration — A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY...

  3. Microlensing discovery of a tight, low-mass-ratio planetary-mass object around an old field brown dwarf

    Energy Technology Data Exchange (ETDEWEB)

    Han, C.; Jung, Y. K. [Department of Physics, Chungbuk National University, Cheongju 371-763 (Korea, Republic of); Udalski, A.; Szymański, M. K.; Kubiak, M.; Pietrzyński, G.; Soszyński, I.; Skowron, J.; Kozłowski, S.; Poleski, R.; Ulaczyk, K.; Wyrzykowski, Ł.; Pietrukowicz, P. [Warsaw University Observatory, Al. Ujazdowskie 4, 00-478 Warszawa (Poland); Sumi, T. [Department of Earth and Space Science, Osaka University, Osaka 560-0043 (Japan); Gaudi, B. S.; Gould, A. [Department of Astronomy, Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States); Bennett, D. P. [University of Notre Dame, Department of Physics, 225 Nieuwland Science Hall, Notre Dame, IN 46556-5670 (United States); Tsapras, Y. [Las Cumbres Observatory Global Telescope Network, 6740B Cortona Dr, Goleta, CA 93117 (United States); Abe, F. [Solar-Terrestrial Environment Laboratory, Nagoya University, Nagoya 464-8601 (Japan); Bond, I. A. [Institute of Information and Mathematical Sciences, Massey University, Private Bag 102-904, North Shore Mail Centre, Auckland (New Zealand); Collaboration: OGLE Collaboration; MOA Collaboration; μFUN Collaboration; RoboNet Collaboration; and others

    2013-11-20

    Observations of accretion disks around young brown dwarfs (BDs) have led to the speculation that they may form planetary systems similar to normal stars. While there have been several detections of planetary-mass objects around BDs (2MASS 1207-3932 and 2MASS 0441-2301), these companions have relatively large mass ratios and projected separations, suggesting that they formed in a manner analogous to stellar binaries. We present the discovery of a planetary-mass object orbiting a field BD via gravitational microlensing, OGLE-2012-BLG-0358Lb. The system is a low secondary/primary mass ratio (0.080 ± 0.001), relatively tightly separated (∼0.87 AU) binary composed of a planetary-mass object with 1.9 ± 0.2 Jupiter masses orbiting a BD with a mass 0.022 M {sub ☉}. The relatively small mass ratio and separation suggest that the companion may have formed in a protoplanetary disk around the BD host in a manner analogous to planets.

  4. Subjective and objective knowledge and decisional role preferences in cerebrovascular patients compared to controls

    Directory of Open Access Journals (Sweden)

    Riechel C

    2016-08-01

    Full Text Available Christina Riechel,1,* Anna Christina Alegiani,1,* Sascha Köpke,2 Jürgen Kasper,3,4 Michael Rosenkranz,1,5 Götz Thomalla,1 Christoph Heesen1,4 1Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 2Nursing Research Unit, Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany; 3Department of Health and Caring Sciences, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway; 4Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 5Department of Neurology, Albertinen-Krankenhaus, Hamburg, Germany *These authors contributed equally to this work Background: Risk knowledge and active role preferences are important for patient involvement in treatment decision-making and adherence. Although knowledge about stroke warning signs and risk factors has received considerable attention, objective knowledge on secondary prevention and further self-esteem subjective knowledge have rarely been studied. The aim of our study was to investigate knowledge and treatment decisional role preferences in cerebrovascular patients compared to controls. Methods: We performed a survey on subjective and objective stroke risk knowledge and autonomy preferences in cerebrovascular patients from our stroke outpatient clinic (n=262 and from pedestrians on the street taken as controls during a “World Stroke Day” (n=274. The questionnaire includes measures for knowledge and decisional role preferences from previously published questionnaires and newly developed measures, for example, subjective knowledge, revealed on a visual analog scale. Results: The overall stroke knowledge was low to moderate, with no differences between patients and controls. Knowledge about secondary prevention was particularly low. Only 10%–15% of participants correctly estimated the stroke absolute risk reduction potential of aspirin. The medical data

  5. Inhibitory Control Interacts with Core Knowledge in Toddlers' Manual Search for an Occluded Object

    Science.gov (United States)

    Baker, Sara T.; Gjersoe, Nathalia L.; Sibielska-Woch, Kasia; Leslie, Alan M.; Hood, Bruce M.

    2011-01-01

    Core knowledge theories advocate the primacy of fundamental principles that constrain cognitive development from early infancy. However, there is concern that core knowledge of object properties does not constrain older preschoolers' reasoning during manual search. Here we address in detail both failure and success on two well-established search…

  6. Computational methods in drug discovery

    Directory of Open Access Journals (Sweden)

    Sumudu P. Leelananda

    2016-12-01

    Full Text Available The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

  7. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian; Paulson, Olaf B

    2002-01-01

    Functional imaging studies have demonstrated that processing of man-made objects activate the left ventral premotor cortex, which is known to be concerned with motor function. This has led to the suggestion that the comprehension of man-made objects may rely on motor-based knowledge of object uti...

  8. Radioactivity. Centenary of radioactivity discovery

    International Nuclear Information System (INIS)

    Charpak, G.; Tubiana, M.; Bimbot, R.

    1997-01-01

    This small booklet was edited for the occasion of the exhibitions of the celebration of the centenary of radioactivity discovery which took place in various locations in France from 1996 to 1998. It recalls some basic knowledge concerning radioactivity and its applications: history of discovery, atoms and isotopes, radiations, measurement of ionizing radiations, natural and artificial radioactivity, isotope dating and labelling, radiotherapy, nuclear power and reactors, fission and fusion, nuclear wastes, dosimetry, effects and radioprotection. (J.S.)

  9. Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

    Science.gov (United States)

    Juandi, D.; Priatna, N.

    2018-05-01

    The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

  10. Children's Comprehension of Object Relative Sentences: It's Extant Language Knowledge That Matters, Not Domain-General Working Memory.

    Science.gov (United States)

    Rusli, Yazmin Ahmad; Montgomery, James W

    2017-10-17

    The aim of this study was to determine whether extant language (lexical) knowledge or domain-general working memory is the better predictor of comprehension of object relative sentences for children with typical development. We hypothesized that extant language knowledge, not domain-general working memory, is the better predictor. Fifty-three children (ages 9-11 years) completed a word-level verbal working-memory task, indexing extant language (lexical) knowledge; an analog nonverbal working-memory task, representing domain-general working memory; and a hybrid sentence comprehension task incorporating elements of both agent selection and cross-modal picture-priming paradigms. Images of the agent and patient were displayed at the syntactic gap in the object relative sentences, and the children were asked to select the agent of the sentence. Results of general linear modeling revealed that extant language knowledge accounted for a unique 21.3% of variance in the children's object relative sentence comprehension over and above age (8.3%). Domain-general working memory accounted for a nonsignificant 1.6% of variance. We interpret the results to suggest that extant language knowledge and not domain-general working memory is a critically important contributor to children's object relative sentence comprehension. Results support a connectionist view of the association between working memory and object relative sentence comprehension. https://doi.org/10.23641/asha.5404573.

  11. Reporting Astronomical Discoveries: Past, Now, and Future

    Science.gov (United States)

    Yamaoka, Hitoshi; Green, Daniel W. E.; Samus, Nikolai N.; West, Richard

    2015-08-01

    Many new astronomical objects have been discovered over the years by amateur astronomers, and this continues to be the case. They have traditionally reported them (as have professional astronomers) to the Central Bureau for Astronomical Telegrams (CBAT), which was established in the 19th century. This procedure has worked very well throughout the 20th century, moving under the umbrella of the newly established IAU in 1920. The discoverers have been honored by the formal announcement of their discoveries in the publications of the CBAT.In recent years, some professional research groups have established other ways of announcing their discoveries of explosive objects such as novae and supernovae; some do not now report their discoveries or spectroscopic confirmations of the transients to the CBAT, including often spectroscopic reports of objects posted to the CBAT "Transient Objects Confirmation Page" -- the highly successful TOCP webpage, which assigns official positional designations to new transients posted there by approved, registered users. This leads to a delay in formal announcements of discoveries by amateur astronomers in many cases, as well as inconsistent designations being put into use by individual groups. Amateur astronomers are feeling frustrated about this situation, and they hope that the IAU will help to settle the situation.We have proposed the new IAU commission NC-52, which will treat these phenomena in a continuation of Commission 6, through the CBAT. We hope to continuously support the reporting of the discoveries by amateur astronomers, as well as professional astronomers, who all deserve and desire proper recognition. Our strategy will maintain the firm trust between the amateur and professional astronomers, which is necessary for true collaboration. The plan is for the CBAT to work with collaborators to assure that discoveries posted on the TOCP are promptly designated and announced by the CBAT, even when confirmations are made elsewhere

  12. Stored object knowledge and the production of referring expressions: The case of color typicality

    Directory of Open Access Journals (Sweden)

    Hans eWesterbeek

    2015-07-01

    Full Text Available When speakers describe objects with atypical properties, do they include these properties in their referring expressions, even when that is not strictly required for unique referent identification? Based on previous work, we predict that speakers mention the color of a target object more often when the object is atypically colored, compared to when it is typical. Taking literature from object recognition and visual attention into account, we further hypothesize that this behavior is proportional to the degree to which a color is atypical, and whether color is a highly diagnostic feature in the referred-to object's identity. We investigate these expectations in two language production experiments, in which participants referred to target objects in visual contexts. In Experiment 1, we find a strong effect of color typicality: less typical colors for target objects predict higher proportions of referring expressions that include color. In Experiment 2 we manipulated objects with more complex shapes, for which color is less diagnostic, and we find that the color typicality effect is moderated by color diagnosticity: it is strongest for high-color-diagnostic objects (i.e., objects with a simple shape. These results suggest that the production of atypical color attributes results from a contrast with stored knowledge, an effect which is stronger when color is more central to object identification. Our findings offer evidence for models of reference production that incorporate general object knowledge, in order to be able to capture these effects of typicality on determining the content of referring expressions.

  13. Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

    Directory of Open Access Journals (Sweden)

    Kristopher J. L. Irizarry

    2016-01-01

    Full Text Available Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

  14. Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

    Science.gov (United States)

    Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

    2016-01-01

    Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

  15. The role of boundary objects in the facilitation of dynamic knowledge transfer

    DEFF Research Database (Denmark)

    Sajadirad, Solmaz; Wæhrens, Brian Vejrum; Lassen, Astrid Heidemann

    2015-01-01

    As industrial companies expand in size and number of locations, new means for organizing the knowledge flows need to be developed to support the efficiency and effectiveness of the global operations of multinational companies (MNCs). Most perspectives on boundary objects tend to highlight the bou...

  16. Prior knowledge about objects determines neural color representation in human visual cortex

    NARCIS (Netherlands)

    Vandenbroucke, A.R.E.; Fahrenfort, J.J.; Meuwese, J.D.I.; Scholte, H.S.; Lamme, V.A.F.

    2016-01-01

    To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and

  17. Effective Online Group Discovery in Trajectory Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    2013-01-01

    GPS-enabled devices are pervasive nowadays. Finding movement patterns in trajectory data stream is gaining in importance. We propose a group discovery framework that aims to efficiently support the online discovery of moving objects that travel together. The framework adopts a sampling-independen......GPS-enabled devices are pervasive nowadays. Finding movement patterns in trajectory data stream is gaining in importance. We propose a group discovery framework that aims to efficiently support the online discovery of moving objects that travel together. The framework adopts a sampling......-independent approach that makes no assumptions about when positions are sampled, gives no special importance to sampling points, and naturally supports the use of approximate trajectories. The framework's algorithms exploit state-of-the-art, density-based clustering (DBScan) to identify groups. The groups are scored...

  18. A Technique Socratic Questioning-Guided Discovery

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2012-03-01

    Full Text Available “Socratic Method” is a way of teaching philosophical thinking and knowledge by asking questions which was used by antique period greek philosopher Socrates. Socrates was teaching knowledge to his followers by asking questions and the conversation between them was named “Socratic Dialogues”. In this meaning, no novel knowledge is taught to the individual but only what is formerly known is reminded and rediscovered. The form of socratic questioning which is used during the process of cognitive behavioral therapy is known as Guided Discovery. In this method it is aimed to make the client notice the piece of knowledge which he could notice but is not aware with a series of questions. Socratic method or guided discovery consists of several steps which are: Identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly found information and questioning the old distorted belief and reaching to a conclusion and applying it. Question types used during these procedures are, questions for gaining information, questions revealing the meanings, questions revealing the beliefs, questions about behaviours during the similar past experiences, analyse questions and analytic synthesis questions. In order to make the patient feel understood it is important to be empathetic and summarising the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues after each step

  19. Looking at anything that is green when hearing "frog": how object surface colour and stored object colour knowledge influence language-mediated overt attention.

    Science.gov (United States)

    Huettig, Falk; Altmann, Gerry T M

    2011-01-01

    Three eye-tracking experiments investigated the influence of stored colour knowledge, perceived surface colour, and conceptual category of visual objects on language-mediated overt attention. Participants heard spoken target words whose concepts are associated with a diagnostic colour (e.g., "spinach"; spinach is typically green) while their eye movements were monitored to (a) objects associated with a diagnostic colour but presented in black and white (e.g., a black-and-white line drawing of a frog), (b) objects associated with a diagnostic colour but presented in an appropriate but atypical colour (e.g., a colour photograph of a yellow frog), and (c) objects not associated with a diagnostic colour but presented in the diagnostic colour of the target concept (e.g., a green blouse; blouses are not typically green). We observed that colour-mediated shifts in overt attention are primarily due to the perceived surface attributes of the visual objects rather than stored knowledge about the typical colour of the object. In addition our data reveal that conceptual category information is the primary determinant of overt attention if both conceptual category and surface colour competitors are copresent in the visual environment.

  20. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  1. An historic discovery around the corner from school: Ceres, a solar system object with an uncertain identity.

    Science.gov (United States)

    Stira, Salvatore

    2016-04-01

    Ceres is the largest object in the asteroid belt between Mars and Jupiter, and it was discovered on January 1, 1801, by the Italian astronomer Giuseppe Piazzi. The study of Ceres is especially relevant to my students because this celestial body was discovered in Palermo, in the astronomic observatory located in the UNESCO world heritage site "Palazzo dei Normanni", around 500 meters away from the institute where I teach, and because Ceres was considered the patron goddess of Sicily. Moreover, it received scientists and media attention recently because it was explored by the NASA Dawn spacecraft in 2015. The categorization of Ceres has changed more than once and has been the subject of some disagreement. It was originally considered a planet, but was reclassified as an asteroid in the 1850s when many other objects in similar orbits were discovered. Its status changed again in 2006 when it was promoted to dwarf planet, a classification it shares with Pluto and other Kuiper belt objects. The study of this celestial body has a notable educational value, since the uncertain identity of Ceres constitutes an occasion to reflect on the criterions of classification of the natural objects. The history of its discovery allows the students to understand as the scientific method doesn't always consist in the verification of hypothesis through experiments but it sometimes asks for the forecast of facts through mathematical calculations, repeated and methodic observations, the collaboration between scientists of different sectors and nationality. Furthermore, it is a particularly suitable topic for interdisciplinary connections, as regards both scientific and humanistic matters. In order to promote the scientific competences of my first class students, I have developed a learning unit on Ceres, thanks to good cooperation with the Palermo Observatory scientists, particularly active in the astronomic dissemination towards the schools and the citizens. The most meaningful activities

  2. Strategies for discovery and optimization of thermoelectric materials: Role of real objects and local fields

    Science.gov (United States)

    Zhu, Hao; Xiao, Chong

    2018-06-01

    Thermoelectric materials provide a renewable and eco-friendly solution to mitigate energy shortages and to reduce environmental pollution via direct heat-to-electricity conversion. Discovery of the novel thermoelectric materials and optimization of the state-of-the-art material systems lie at the core of the thermoelectric society, the basic concept behind these being comprehension and manipulation of the physical principles and transport properties regarding thermoelectric materials. In this mini-review, certain examples for designing high-performance bulk thermoelectric materials are presented from the perspectives of both real objects and local fields. The highlights of this topic involve the Rashba effect, Peierls distortion, local magnetic field, and local stress field, which cover several aspects in the field of thermoelectric research. We conclude with an overview of future developments in thermoelectricity.

  3. Resource Discovery within the Networked "Hybrid" Library.

    Science.gov (United States)

    Leigh, Sally-Anne

    This paper focuses on the development, adoption, and integration of resource discovery, knowledge management, and/or knowledge sharing interfaces such as interactive portals, and the use of the library's World Wide Web presence to increase the availability and usability of information services. The introduction addresses changes in library…

  4. Data mining and knowledge discovery technologies

    National Research Council Canada - National Science Library

    Taniar, David

    2008-01-01

    "This book presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data...

  5. Indigenous Past Climate Knowledge as Cultural Built-in Object and Its Accuracy

    Directory of Open Access Journals (Sweden)

    Christian Leclerc

    2013-12-01

    Full Text Available In studying indigenous climate knowledge, two approaches can be envisioned. In the first, traditional knowledge is a cultural built-in object; conceived as a whole, its relevance can be assessed by referring to other cultural, economic, or technical components at work within an indigenous society. In the second, the accuracy of indigenous climate knowledge is assessed with western science knowledge used as an external reference. However, assessing the accuracy of indigenous climate knowledge remains a largely untapped area. We aim to show how accurate the culturally built indigenous climate knowledge of extreme climatic events is, and how amenable it is to fuzzy logic. A retrospective survey was carried out individually and randomly among 195 Eastern African farmers on climatic reasons for loss of on-farm crop diversity from 1961 to 2006. More than 3000 crop loss events were recorded, and reasons given by farmers were mainly related to droughts or heavy rainfall. Chi-square statistics computed by Monte Carlo simulations based on 999 replicates clearly rejected independence between indigenous knowledge of drought and heavy rainfall that occurred in the past and rainfall records. The fuzzy logic nature of indigenous climatic knowledge appears in the clear association of drought or heavy rainfall events, as perceived by farmers, with corresponding extreme rainfall values, contrasting with a fuzzy picture in the intermediate climatic situations. We discuss how the cultural built-in knowledge helps farmers in perceiving and remembering past climate variations, considering the specificity of the contexts where extreme climatic events were experienced. The integration of indigenous and scientific climate knowledge could allow development of drought monitoring that considers both climatic and contextual data.

  6. BayesMD: flexible biological modeling for motif discovery

    DEFF Research Database (Denmark)

    Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

    2008-01-01

    We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

  7. Swift: 10 Years of Discovery

    Science.gov (United States)

    2014-12-01

    The conference Swift: 10 years of discovery was held in Roma at La Sapienza University on Dec. 2-5 2014 to celebrate 10 years of Swift successes. Thanks to a large attendance and a lively program, it provided the opportunity to review recent advances of our knowledge of the high-energy transient Universe both from the observational and theoretical sides. When Swift was launched on November 20, 2004, its prime objective was to chase Gamma-Ray Bursts and deepen our knowledge of these cosmic explosions. And so it did, unveiling the secrets of long and short GRBs. However, its multi-wavelength instrumentation and fast scheduling capabilities made it the most versatile mission ever flown. Besides GRBs, Swift has observed, and contributed to our understanding of, an impressive variety of targets including AGNs, supernovae, pulsars, microquasars, novae, variable stars, comets, and much more. Swift is continuously discovering rare and surprising events distributed over a wide range of redshifts, out to the most distant transient objects in the Universe. Such a trove of discoveries has been addressed during the conference with sessions dedicated to each class of events. Indeed, the conference in Rome was a spectacular celebration of the Swift 10th anniversary. It included sessions on all types of transient and steady sources. Top scientists from around the world gave invited and contributed talks. There was a large poster session, sumptuous lunches, news interviews and a glorious banquet with officials attending from INAF and ASI. All the presentations, as well as several conference pictures, can be found in the conference website (http://www.brera.inaf.it/Swift10/Welcome.html). These proceedings have been collected owing to the efforts of Paolo D’Avanzo who has followed each paper from submission to final acceptance. Our warmest thanks to Paolo for all his work. The Conference has been made possible by the support from La Sapienza University as well as from the ARAP

  8. Birth of the Object: Detection of Objectness and Extraction of Object Shape through Object Action Complexes

    DEFF Research Database (Denmark)

    Kraft, Dirk; Pugeault, Nicolas; Baseski, Emre

    2008-01-01

    We describe a process in which the segmentation of objects as well as the extraction of the object shape becomes realized through active exploration of a robot vision system. In the exploration process, two behavioral modules that link robot actions to the visual and haptic perception of objects...... interact. First, by making use of an object independent grasping mechanism, physical control over potential objects can be gained. Having evaluated the initial grasping mechanism as being successful, a second behavior extracts the object shape by making use of prediction based on the motion induced...... system, knowledge about its own embodiment as well as knowledge about geometric relationships such as rigid body motion. This prior knowledge allows the extraction of representations that are semantically richer compared to many other approaches....

  9. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  10. Integration of World Knowledge and Temporary Information about Changes in an Object's Environmental Location during Different Stages of Sentence Comprehension.

    Science.gov (United States)

    Chen, Xuqian; Yang, Wei; Ma, Lijun; Li, Jiaxin

    2018-01-01

    Recent findings have shown that information about changes in an object's environmental location in the context of discourse is stored in working memory during sentence comprehension. However, in these studies, changes in the object's location were always consistent with world knowledge (e.g., in "The writer picked up the pen from the floor and moved it to the desk," the floor and the desk are both common locations for a pen). How do people accomplish comprehension when the object-location information in working memory is inconsistent with world knowledge (e.g., a pen being moved from the floor to the bathtub)? In two visual world experiments, with a "look-and-listen" task, we used eye-tracking data to investigate comprehension of sentences that described location changes under different conditions of appropriateness (i.e., the object and its location were typically vs. unusually coexistent, based on world knowledge) and antecedent context (i.e., contextual information that did vs. did not temporarily normalize unusual coexistence between object and location). Results showed that listeners' retrieval of the critical location was affected by both world knowledge and working memory, and the effect of world knowledge was reduced when the antecedent context normalized unusual coexistence of object and location. More importantly, activation of world knowledge and working memory seemed to change during the comprehension process. These results are important because they demonstrate that interference between world knowledge and information in working memory, appears to be activated dynamically during sentence comprehension.

  11. New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

    Science.gov (United States)

    Brescia, Massimo

    2012-11-01

    Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to

  12. Biomarker Gene Signature Discovery Integrating Network Knowledge

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  13. Rethinking infant knowledge: toward an adaptive process account of successes and failures in object permanence tasks.

    Science.gov (United States)

    Munakata, Y; McClelland, J L; Johnson, M H; Siegler, R S

    1997-10-01

    Infants seem sensitive to hidden objects in habituation tasks at 3.5 months but fail to retrieve hidden objects until 8 months. The authors first consider principle-based accounts of these successes and failures, in which early successes imply knowledge of principles and failures are attributed to ancillary deficits. One account is that infants younger than 8 months have the object permanence principle but lack means-ends abilities. To test this, 7-month-olds were trained on means-ends behaviors and were tested on retrieval of visible and occluded toys. Means-ends demands were the same, yet infants made more toy-guided retrievals in the visible case. The authors offer an adaptive process account in which knowledge is graded and embedded in specific behavioral processes. Simulation models that learn gradually to represent occluded objects show how this approach can account for success and failure in object permanence tasks without assuming principles and ancillary deficits.

  14. Integration of knowledge to support automatic object reconstruction from images and 3D data

    International Nuclear Information System (INIS)

    Boochs, F.; Truong, H; Marbs, A.; Karmacharya, A.; Cruz, C.; Habed, A.; Nicolle, C.; Voisin, Y.

    2011-01-01

    Object reconstruction is a important task in many fields of application as it allows to generate digital representations of our physical world used as base for analysis, planning, construction, visualization or other aims. A reconstruction itself normally is based on reliable data (images, 3D point clouds for example) expressing the object in his complete extension. This data then has to be compiled and analyzed in order to extract all necessary geometrical elements, which represent the object and form a digital copy of it. Traditional strategies are largely based on manual interaction and interpretation, because with increasing complexity of objects human understanding is inevitable to achieve acceptable and reliable results. But human interaction is time consuming and expensive, why many research has already been invested to integrate algorithmic support, what allows to speed up the process and reduce manual work load. Presently most such algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. By means of these models, which normally will represent geometrical (flatness, roughness, for example) or physical features (color, texture), the data is classified and analyzed. This is succesful for objects with a limited complexity, but gets to its limits with increasing complexity of objects. Then purely numerical strategies are not able to sufficiently model the reality. Therefore, the intention of our approach is to take human cogni-tive strategy as an example, and to simulate extraction processes based on available knowledge for the objects of interest. Such processes will introduce a semantic structure for the objects and guide the algorithms used to detect and recognize objects, which will yield a higher effectiveness. Hence, our research proposes an approach using knowledge to guide the algorithms in 3D point cloud and image processing.

  15. Automated cell type discovery and classification through knowledge transfer

    Science.gov (United States)

    Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E.

    2017-01-01

    Abstract Motivation: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. Results: We present a new algorithm called Automated Cell-type Discovery and Classification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. Availability and Implementation: A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc. Contact: brian.kidd@mssm.edu or joel.dudley@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28158442

  16. Research on an Agricultural Knowledge Fusion Method for Big Data

    Directory of Open Access Journals (Sweden)

    Nengfu Xie

    2015-05-01

    Full Text Available The object of our research is to develop an ontology-based agricultural knowledge fusion method that can be used as a comprehensive basis on which to solve agricultural information inconsistencies, analyze data, and discover new knowledge. A recent survey has provided a detailed comparison of various fusion methods used with Deep Web data (Li, 2013. In this paper, we propose an effective agricultural ontology-based knowledge fusion method by leveraging recent advances in data fusion, such as the semantic web and big data technologies, that will enhance the identification and fusion of new and existing data sets to make big data analytics more possible. We provide a detailed fusion method that includes agricultural ontology building, fusion rule construction, an evaluation module, etc. Empirical results show that this knowledge fusion method is useful for knowledge discovery.

  17. Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge.

    Science.gov (United States)

    van Elk, Michiel; van Schie, Hein; Bekkering, Harold

    2014-06-01

    Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Integration of World Knowledge and Temporary Information about Changes in an Object's Environmental Location during Different Stages of Sentence Comprehension

    Directory of Open Access Journals (Sweden)

    Xuqian Chen

    2018-02-01

    Full Text Available Recent findings have shown that information about changes in an object's environmental location in the context of discourse is stored in working memory during sentence comprehension. However, in these studies, changes in the object's location were always consistent with world knowledge (e.g., in “The writer picked up the pen from the floor and moved it to the desk,” the floor and the desk are both common locations for a pen. How do people accomplish comprehension when the object-location information in working memory is inconsistent with world knowledge (e.g., a pen being moved from the floor to the bathtub? In two visual world experiments, with a “look-and-listen” task, we used eye-tracking data to investigate comprehension of sentences that described location changes under different conditions of appropriateness (i.e., the object and its location were typically vs. unusually coexistent, based on world knowledge and antecedent context (i.e., contextual information that did vs. did not temporarily normalize unusual coexistence between object and location. Results showed that listeners' retrieval of the critical location was affected by both world knowledge and working memory, and the effect of world knowledge was reduced when the antecedent context normalized unusual coexistence of object and location. More importantly, activation of world knowledge and working memory seemed to change during the comprehension process. These results are important because they demonstrate that interference between world knowledge and information in working memory, appears to be activated dynamically during sentence comprehension.

  19. [Objective assessment of transfusion-related knowledge of nurses using modern test theory].

    Science.gov (United States)

    Rajki, Veronika; Deutsch, Tibor; Csóka, Mária; Mészáros, Judit

    2015-09-13

    Clinical practice requires knowledge of health professionals for the application of problem solving of different tasks in various clinical settings. Therefore, a set of reliable measurement tools is required to assess various components of the professional knowledge including factual knowledge, skills and competence as outcomes of nursing education and training. Traditional questionnaires and test methods do not allow the measurement of these characteristics properly, as these tools typically provide overall scores without relevant insight into areas in which nurses perform well, and those where their knowledge and/or skills should be improved substantially. The aim of this nationwide survey conducted among nurses between November 2014 and February 2015 was to determine how the teaching/training objectives have been achieved in the nurses' transfusion practice. The authors attempted to exceed the capabilities of classical test theory and acquire a detailed picture about what the nurses know about transfusion therapy and how they are involved and behave in routine clinical practice. The knowledge and skills of 657 participants were assessed using a validated instrument consisting of a set of questions covering every aspects of transfusion therapy. The answers to these items were evaluated on a binary (good or bad) scale. Recorded answers of the participants were analysed using hierarchical cluster analysis and item response theory tools such as the one-parametric Rasch model suitable for dichotomous data. Data analysis was performed with the SPSS program and the ltm module of the R statistical program. The paper presents the distribution of correct and incorrect answers to various questions about transfusion therapy along with the corresponding logit values and odds ratios, respectively. The characteristic curves of each item were determined on the basis of the number of correct answers that have been recorded. These curves highlight which questions were answered

  20. Accounting for discovery bias in genomic prediction

    Science.gov (United States)

    Our objective was to evaluate an approach to mitigating discovery bias in genomic prediction. Accuracy may be improved by placing greater emphasis on regions of the genome expected to be more influential on a trait. Methods emphasizing regions result in a phenomenon known as “discovery bias” if info...

  1. On the role of object knowledge in reference production : Effects of color typicality on content determination

    NARCIS (Netherlands)

    Westerbeek, H.G.W.; Koolen, R.M.F.; Maes, A.A.; Bello, Paul; Guarini, Marcello; McShane, Marjorie; Scassellati, Brian

    2014-01-01

    In two language production experiments, we investigated whether stored knowledge of the typical color of objects affects spoken reference. In experiment 1, human speakers referred to objects with colors ranging from very typical (e.g., red tomato) to very atypical (e.g., blue pepper). The

  2. The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition.

    Science.gov (United States)

    Gudde, Harmen B; Griffiths, Debra; Coventry, Kenny R

    2018-02-19

    The memory game paradigm is a behavioral procedure to explore the relationship between language, spatial memory, and object knowledge. Using two different versions of the paradigm, spatial language use and memory for object location are tested under different, experimentally manipulated conditions. This allows us to tease apart proposed models explaining the influence of object knowledge on spatial language (e.g., spatial demonstratives), and spatial memory, as well as understanding the parameters that affect demonstrative choice and spatial memory more broadly. Key to the development of the method was the need to collect data on language use (e.g., spatial demonstratives: "this/that") and spatial memory data under strictly controlled conditions, while retaining a degree of ecological validity. The language version (section 3.1) of the memory game tests how conditions affect language use. Participants refer verbally to objects placed at different locations (e.g., using spatial demonstratives: "this/that red circle"). Different parameters can be experimentally manipulated: the distance from the participant, the position of a conspecific, and for example whether the participant owns, knows, or sees the object while referring to it. The same parameters can be manipulated in the memory version of the memory game (section 3.2). This version tests the effects of the different conditions on object-location memory. Following object placement, participants get 10 seconds to memorize the object's location. After the object and location cues are removed, participants verbally direct the experimenter to move a stick to indicate where the object was. The difference between the memorized and the actual location shows the direction and strength of the memory error, allowing comparisons between the influences of the respective parameters.

  3. Guided Discovery with Socratic Questioning

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2015-04-01

    Full Text Available “The Socratic method” is a way of teaching philosophical thinking and knowledge by asking questions. It was first used by in ancient times by the Greek philosopher Socrates who taught his followers by asking questions; these conversations between them are known as “Socratic dialogues”. In this methodology, no new knowledge is taught to the individual; rather, the individual is guided to remember and rediscover what was formerly known through this process. The main method used in cognitive therapy is guided discovery. There are various methods of guided discovery in cognitive therapy. The form of verbal exchange between the therapist and client which is used during the process of cognitive behavioral therapy is known as “socratic questioning”. In this method the goal is to make the client rediscover, with a series of questions, a piece of knowledge which he could otherwise know but is not presently conscious of. The Socratic Questioning consists of several steps, including: identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly rediscovered information and questioning the old distorted belief, and reaching a new conclusion and applying it. Question types used during these procedures are: questions for collecting information, questions revealing meanings, questions revealing beliefs, questions about behaviours during similar past experiences, analytic questions and analytic synthesis questions. In order to make the patient feel understood, it is important to be empathetic and summarize the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues provided for each step. [JCBPR 2015; 4(1.000: 47-53

  4. Designing the Object Game

    DEFF Research Database (Denmark)

    Filip, Diane; Lindegaard, Hanne

    2016-01-01

    The Object Game is an exploratory design game and an experiment of developing a tangible object that can spark dialogue and retrospection between collaborative partners and act as a boundary object. The objective of this article is to show and elaborate on the development of the Object Game......, and to provide case examples of the game in action. The Object Game has two parts – Story-building and Co-rating of objects – with the aim of stimulating a collaborative reflection on knowledge sharing with different objects. In Story-building, the participants visualize their knowledge sharing process...... these facilitated knowledge transfer, knowledge exchange, knowledge generation, and knowledge integration. The participants collaborative reflected on their use of different objects for knowledge sharing and learn which objects have been effective (and which have not been effective) in their collaborative...

  5. Evolution of the clinical and epidemiological knowledge about Chagas disease 90 years after its discovery

    Directory of Open Access Journals (Sweden)

    Prata Aluízio

    1999-01-01

    Full Text Available Three different periods may be considered in the evolution of knowledge about the clinical and epidemiological aspects of Chagas disease since its discovery: (a early period concerning the studies carried out by Carlos Chagas in Lassance with the collaboration of other investigators of the Manguinhos School. At that time the disease was described and the parasite, transmitters and reservoirs were studied. The coexistence of endemic goiter in the same region generated some confusion about the clinical forms of the disease; (b second period involving uncertainty and the description of isolated cases, which lasted until the 1940 decade. Many acute cases were described during this period and the disease was recognized in many Latin American countries. Particularly important were the studies of the Argentine Mission of Regional Pathology Studies, which culminated with the description of the Romaña sign in the 1930 decade, facilitating the diagnosis of the early phase of the disease. However, the chronic phase, which was the most important, continued to be difficult to recognize; (c period of consolidation of knowledge and recognition of the importance of Chagas disease. Studies conducted by Laranja, Dias and Nóbrega in Bambuí updated the description of Chagas heart disease made by Carlos Chagas and Eurico Villela. From then on, the disease was more easily recognized, especially with the emphasis on the use of a serologic diagnosis; (d period of enlargement of knowledges on the disease. The studies on denervation conducted in Ribeirão Preto by Fritz Köberle starting in the 1950 decade led to a better understanding of the relations between Chagas disease and megaesophagus and other visceral megas detected in endemic areas.

  6. Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Sapna Kumari

    Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

  7. A Knowledge Discovery Approach to Diagnosing Intracranial Hematomas on Brain CT: Recognition, Measurement and Classification

    Science.gov (United States)

    Liao, Chun-Chih; Xiao, Furen; Wong, Jau-Min; Chiang, I.-Jen

    Computed tomography (CT) of the brain is preferred study on neurological emergencies. Physicians use CT to diagnose various types of intracranial hematomas, including epidural, subdural and intracerebral hematomas according to their locations and shapes. We propose a novel method that can automatically diagnose intracranial hematomas by combining machine vision and knowledge discovery techniques. The skull on the CT slice is located and the depth of each intracranial pixel is labeled. After normalization of the pixel intensities by their depth, the hyperdense area of intracranial hematoma is segmented with multi-resolution thresholding and region-growing. We then apply C4.5 algorithm to construct a decision tree using the features of the segmented hematoma and the diagnoses made by physicians. The algorithm was evaluated on 48 pathological images treated in a single institute. The two discovered rules closely resemble those used by human experts, and are able to make correct diagnoses in all cases.

  8. Pinocchio: Geppetto's transitional object

    Directory of Open Access Journals (Sweden)

    Gabriele Zeloni

    2015-01-01

    Full Text Available The literature has been considered by Freud and others after him, a form of unaware exploration of mind that can leads to discoveries similar to psychoanalysis’s discoveries. From this perspective, the author puts forward the following hypothesis: Pinocchio is a puppet who comes to life and is therefore, from a child's perception, a transitional object according to Winnicott. Consequently Geppetto is nothing more than the involuntary representation of any child interacting with the transitional object. The author explains the results of the analysis of the text in support of the hypothesis and reflects on the impact of The adventure of Pinocchio on the reader.

  9. Incremental Knowledge Discovery in Social Media

    Science.gov (United States)

    Tang, Xuning

    2013-01-01

    In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge. This dissertation centers on the issue of modeling the dynamics of user communities, trending…

  10. A Knowledge-Based System For Analysis, Intervention Planning and Prevention of Defects in Immovable Cultural Heritage Objects and Monuments

    Science.gov (United States)

    Valach, J.; Cacciotti, R.; Kuneš, P.; ČerÅanský, M.; Bláha, J.

    2012-04-01

    The paper presents a project aiming to develop a knowledge-based system for documentation and analysis of defects of cultural heritage objects and monuments. The MONDIS information system concentrates knowledge on damage of immovable structures due to various causes, and preventive/remedial actions performed to protect/repair them, where possible. The currently built system is to provide for understanding of causal relationships between a defect, materials, external load, and environment of built object. Foundation for the knowledge-based system will be the systemized and formalized knowledge on defects and their mitigation acquired in the process of analysis of a representative set of cases documented in the past. On the basis of design comparability, used technologies, materials and the nature of the external forces and surroundings, the developed software system has the capacity to indicate the most likely risks of new defect occurrence or the extension of the existing ones. The system will also allow for a comparison of the actual failure with similar cases documented and will propose a suitable technical intervention plan. The system will provide conservationists, administrators and owners of historical objects with a toolkit for defect documentation for their objects. Also, advanced artificial intelligence methods will offer accumulated knowledge to users and will also enable them to get oriented in relevant techniques of preventive interventions and reconstructions based on similarity with their case.

  11. Discovery of a probable galaxy with a redshift of 3.218

    International Nuclear Information System (INIS)

    Djorgovski, S.; Spinard, H.; McCarthy, P.; Strauss, M.A.

    1985-01-01

    We report the discovery of a narrow emission line object, probably a galaxy, with a redshift of 3.218. The object is a companion to the quasar PKS 1614+051, which is at a redshift of 3.209. This is the most distant non--QSO, non--gravitationally lensed object presently known by a large margin. Its properties are consistent with those expected of a high-redshift galaxy. This object has an age of only a few percent of the present age of the universe. The object was discovered with a novel technique, which promises to push studies of distant galaxies to redshifts as high as those of the most distant quasars known, and which may eventually lead to the discovery of primeval galaxies. This discovery opens the way for studies of galaxies beyond z = 3, which should prove invaluable for observational cosmology

  12. Development of the IAEA’s Knowledge Preservation Portals for Fast Reactors and Gas-Cooled Reactors Knowledge Preservation

    International Nuclear Information System (INIS)

    Batra, C.; Menahem, D. Beraha; Kriventsev, V.; Monti, S.; Reitsma, F.; Grosbois, J. de; Khoroshev, M.; Gladyshev, M.

    2016-01-01

    Full text: The IAEA has been carrying out a dedicated initiative on fast reactor knowledge preservation since 2003. The main objectives of the Fast Reactor Knowledge Portal (FRKP) initiative are to, a) halt the on-going loss of information related to fast reactors (FR), and b) collect, retrieve, preserve and make accessible existing data and information on FR. This portal will help in knowledge sharing, development, search and discovery, collaboration and communication of fast reactor related information. On similar lines a Gas Cooled Fast Reactor Knowledge Preservation portal project also started in 2013. Knowledge portals are capable to control and manage both publicly available as well as controlled information. The portals will not only incorporate existing set of knowledge and information, but will also provide a systemic platform for further preservation of new developments. It will include fast reactor and gas cooled reactor document repositories, project workspaces for the IAEA’s Coordinated Research Projects (CRPs), Technical Meetings (TMs), forums for discussion, etc. The portal will also integrate a taxonomy based search tool, which will help using new semantic search capabilities for improved conceptual retrieve of documents. The taxonomy complies with international web standards as defined by the W3C (World Wide Web Consortium). (author

  13. FluKB: A Knowledge-Based System for Influenza Vaccine Target Discovery and Analysis of the Immunological Properties of Influenza Viruses

    DEFF Research Database (Denmark)

    Simon, Christian; Kudahl, Ulrich Johan; Sun, Jing

    2015-01-01

    FluKB is a knowledge-based system focusing on data and analytical tools for influenza vaccine discovery. The main goal of FluKB is to provide access to curated influenza sequence and epitope data and enhance the analysis of influenza sequence diversity and the analysis of targets of immune...... responses. FluKB consists of more than 400,000 influenza protein sequences, known epitope data (357 verified T-cell epitopes, 685 HLA binders, and 16 naturally processed MHC ligands), and a collection of 28 influenza antibodies and their structurally defined B-cell epitopes. FluKB was built using amodular...

  14. Knowledge discovery in databases of biomechanical variables: application to the sit to stand motor task

    Directory of Open Access Journals (Sweden)

    Benvenuti Francesco

    2004-10-01

    Full Text Available Abstract Background The interpretation of data obtained in a movement analysis laboratory is a crucial issue in clinical contexts. Collection of such data in large databases might encourage the use of modern techniques of data mining to discover additional knowledge with automated methods. In order to maximise the size of the database, simple and low-cost experimental set-ups are preferable. The aim of this study was to extract knowledge inherent in the sit-to-stand task as performed by healthy adults, by searching relationships among measured and estimated biomechanical quantities. An automated method was applied to a large amount of data stored in a database. The sit-to-stand motor task was already shown to be adequate for determining the level of individual motor ability. Methods The technique of search for association rules was chosen to discover patterns as part of a Knowledge Discovery in Databases (KDD process applied to a sit-to-stand motor task observed with a simple experimental set-up and analysed by means of a minimum measured input model. Selected parameters and variables of a database containing data from 110 healthy adults, of both genders and of a large range of age, performing the task were considered in the analysis. Results A set of rules and definitions were found characterising the patterns shared by the investigated subjects. Time events of the task turned out to be highly interdependent at least in their average values, showing a high level of repeatability of the timing of the performance of the task. Conclusions The distinctive patterns of the sit-to-stand task found in this study, associated to those that could be found in similar studies focusing on subjects with pathologies, could be used as a reference for the functional evaluation of specific subjects performing the sit-to-stand motor task.

  15. Effect of knowledge of APOE genotype on subjective and objective memory performance in healthy older adults.

    Science.gov (United States)

    Lineweaver, Tara T; Bondi, Mark W; Galasko, Douglas; Salmon, David P

    2014-02-01

    The knowledge that one carries the apolipoprotein E (APOE) ε4 allele risk factor for Alzheimer's disease was recently found to have little short-term psychological risk. The authors investigated the impact of knowledge of carrying the risk allele on subjective ratings of memory and objective memory test performance of older adults. Using a nested case-control design, the authors administered objective verbal and visual memory tests and self-rating scales of memory function to 144 cognitively normal older adults (ages 52-89) with known APOE genotype who knew (ε4+, N=25; ε4-, N=49) or did not know (ε4+, N=25; ε4-, N=45) their genotype and genetic risk for Alzheimer's disease prior to neuropsychological evaluation. Significant genotype-by-disclosure interaction effects were observed on several memory rating scales and tests of immediate and delayed verbal recall. Older adults who knew their ε4+ genotype judged their memory more harshly and performed worse on an objective verbal memory test than did ε4+ adults who did not know. In contrast, older adults who knew their ε4- genotype judged their memory more positively than did ε4- adults who did not know, but these groups did not differ in objective memory test performance. Informing older adults that they have an APOE genotype associated with an increased risk of Alzheimer's disease can have adverse consequences on their perception of their memory abilities and their performance on objective memory tests. The patient's knowledge of his or her genotype and risk of Alzheimer's disease should be considered when evaluating cognition in the elderly.

  16. Computer-Aided Drug Discovery in Plant Pathology.

    Science.gov (United States)

    Shanmugam, Gnanendra; Jeon, Junhyun

    2017-12-01

    Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides .

  17. Microbial Dark Matter Investigations: How Microbial Studies Transform Biological Knowledge and Empirically Sketch a Logic of Scientific Discovery

    Science.gov (United States)

    Bernard, Guillaume; Pathmanathan, Jananan S; Lannes, Romain; Lopez, Philippe; Bapteste, Eric

    2018-01-01

    Abstract Microbes are the oldest and most widespread, phylogenetically and metabolically diverse life forms on Earth. However, they have been discovered only 334 years ago, and their diversity started to become seriously investigated even later. For these reasons, microbial studies that unveil novel microbial lineages and processes affecting or involving microbes deeply (and repeatedly) transform knowledge in biology. Considering the quantitative prevalence of taxonomically and functionally unassigned sequences in environmental genomics data sets, and that of uncultured microbes on the planet, we propose that unraveling the microbial dark matter should be identified as a central priority for biologists. Based on former empirical findings of microbial studies, we sketch a logic of discovery with the potential to further highlight the microbial unknowns. PMID:29420719

  18. HISTORICAL CRITICAL PEDAGOGY AND OBJECTIVE KNOWLEDGE VERSUS THE MULTICULTURALISM AND RELATIVISM CURRENT ACADEMIC DEBATE

    Directory of Open Access Journals (Sweden)

    Julia Malanchen

    2015-06-01

    Full Text Available The article discusses the existing antagonistic understanding among the authors who discuss curriculum from the multiculturalist perspective and the authors of the Historical-Critical Pedagogy. The aim is to explain the postmodern relativists bases and multiculturalism, which opposes the defense of objective knowledge as central to the organization of a curriculum. Finally we point out what content should integrate an academic, with the objective, human development, human emancipation and social transformation, which allow the human being aim to provide social and consciously so increasingly free and universal.

  19. Looking at anything that is green when hearing ‘frog’: How object surface colour and stored object colour knowledge influence language-mediated overt attention

    OpenAIRE

    Huettig, F.; Altmann, G.

    2011-01-01

    Three eye-tracking experiments investigated the influence of stored colour knowledge, perceived surface colour, and conceptual category of visual objects on language-mediated overt attention. Participants heard spoken target words whose concepts are associated with a diagnostic colour (e.g., "spinach"; spinach is typically green) while their eye movements were monitored to (a) objects associated with a diagnostic colour but presented in black and white (e.g., a black-and-white line drawing of...

  20. Context-aware pattern discovery for moving object trajectories

    Science.gov (United States)

    Sharif, Mohammad; Asghar Alesheikh, Ali; Kaffash Charandabi, Neda

    2018-05-01

    Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.

  1. IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

    Science.gov (United States)

    Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

    2015-07-14

    In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to

  2. Resource-estimation models and predicted discovery

    International Nuclear Information System (INIS)

    Hill, G.W.

    1982-01-01

    Resources have been estimated by predictive extrapolation from past discovery experience, by analogy with better explored regions, or by inference from evidence of depletion of targets for exploration. Changes in technology and new insights into geological mechanisms have occurred sufficiently often in the long run to form part of the pattern of mature discovery experience. The criterion, that a meaningful resource estimate needs an objective measure of its precision or degree of uncertainty, excludes 'estimates' based solely on expert opinion. This is illustrated by development of error measures for several persuasive models of discovery and production of oil and gas in USA, both annually and in terms of increasing exploration effort. Appropriate generalizations of the models resolve many points of controversy. This is illustrated using two USA data sets describing discovery of oil and of U 3 O 8 ; the latter set highlights an inadequacy of available official data. Review of the oil-discovery data set provides a warrant for adjusting the time-series prediction to a higher resource figure for USA petroleum. (author)

  3. Intelligent Discovery for Learning Objects Using Semantic Web Technologies

    Science.gov (United States)

    Hsu, I-Ching

    2012-01-01

    The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

  4. Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

    Science.gov (United States)

    Honavar, Vasant

    2015-01-01

    New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

  5. Open Knowledge Maps: Creating a Visual Interface to the World’s Scientific Knowledge Based on Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Peter Kraker

    2016-11-01

    Full Text Available The goal of Open Knowledge Maps is to create a visual interface to the world’s scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps. Das Ziel von Open Knowledge Map ist es, ein visuelles Interface zum wissenschaftlichen Wissen der Welt bereitzustellen. Die Basis für die dieses Interface sind sogenannte “knowledge maps”, zu deutsch Wissenslandkarten. Wissenslandkarten ermöglichen die Exploration bestehenden Wissens und die Entdeckung neuen Wissens. Unsere Open Source Software wendet für die Erstellung der Wissenslandkarten eine Reihe von Text Mining Verfahren iterativ auf die Metadaten wissenschaftlicher Artikel an. Die daraus resultierende Repräsentation wird in einer Datenbank für die Anzeige in einer Web-Visualisierung abgespeichert. In Zukunft wollen wir einen Raum für das kollektive Erstellen von Wissenslandkarten schaffen, der die Personen und Communities, welche sich mit der Exploration und Entdeckung wissenschaftlichen Wissens beschäftigen, zusammenbringt. Wir wollen es den NutzerInnen ermöglichen, einander in der Literatursuche durch kollaboratives Annotieren und Modifizieren von automatisch erstellten Wissenslandkarten zu unterstützen.

  6. Incremental discovery of hidden structure: Applications in theory of elementary particles

    International Nuclear Information System (INIS)

    Zytkow, J.M.; Fischer, P.J.

    1996-01-01

    Discovering hidden structure is a challenging, universal research task in Physics, Chemistry, Biology, and other disciplines. Not only must the elements of hidden structure be postulated by the discoverer, but they can only be verified by indirect evidence, at the level of observable objects. In this paper we describe a framework for hidden structure discovery, built on a constructive definition of hidden structure. This definition leads to operators that build models of hidden structure step by step, postulating hidden objects, their combinations and properties, reactions described in terms of hidden objects, and mapping between the hidden and the observed structure. We introduce the operator dependency diagram, which shows the order of operator application and model evaluation. Different observational knowledge supports different evaluation criteria, which lead to different search systems with verifiable sequences of operator applications. Isomorph-free structure generation is another issue critical for efficiency of search. We apply our framework in the system GELL-MANN, that hypothesizes hidden structure for elementary particles and we present the results of a large scale search for quark models

  7. Building Scalable Knowledge Graphs for Earth Science

    Science.gov (United States)

    Ramachandran, Rahul; Maskey, Manil; Gatlin, Patrick; Zhang, Jia; Duan, Xiaoyi; Miller, J. J.; Bugbee, Kaylin; Christopher, Sundar; Freitag, Brian

    2017-01-01

    Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

  8. 75 FR 66766 - NIAID Blue Ribbon Panel Meeting on Adjuvant Discovery and Development

    Science.gov (United States)

    2010-10-29

    ..., identifies gaps in knowledge and capabilities, and defines NIAID's goals for the continued discovery...), will convene a Blue Ribbon Panel to provide expertise in developing a strategic plan and research... vaccines. NIAID has developed a draft Strategic Plan and Research Agenda for Adjuvant Discovery and...

  9. PRE-DISCOVERY OBSERVATIONS OF DISRUPTING ASTEROID P/2010 A2

    International Nuclear Information System (INIS)

    Jewitt, David; Stuart, Joseph S.; Li Jing

    2011-01-01

    Solar system object P/2010 A2 is the first-noticed example of the aftermath of a recently disrupted asteroid, probably resulting from a collision. Nearly a year elapsed between its inferred initiation in early 2009 and its eventual detection in early 2010. Here, we use new observations to assess the factors underlying the visibility, especially to understand the delayed discovery. We present pre-discovery observations from the LINEAR telescope and set limits to the early-time brightness from SOHO and STEREO satellite coronagraphic images. Consideration of the circumstances of discovery of P/2010 A2 suggests that similar objects must be common, and that future all-sky surveys will reveal them in large numbers.

  10. Discovery Mondays

    CERN Multimedia

    2003-01-01

    Many people don't realise quite how much is going on at CERN. Would you like to gain first-hand knowledge of CERN's scientific and technological activities and their many applications? Try out some experiments for yourself, or pick the brains of the people in charge? If so, then the «Lundis Découverte» or Discovery Mondays, will be right up your street. Starting on May 5th, on every first Monday of the month you will be introduced to a different facet of the Laboratory. CERN staff, non-scientists, and members of the general public, everyone is welcome. So tell your friends and neighbours and make sure you don't miss this opportunity to satisfy your curiosity and enjoy yourself at the same time. You won't have to listen to a lecture, as the idea is to have open exchange with the expert in question and for each subject to be illustrated with experiments and demonstrations. There's no need to book, as Microcosm, CERN's interactive museum, will be open non-stop from 7.30 p.m. to 9 p.m. On the first Discovery M...

  11. Chirality - The forthcoming 160th Anniversary of Pasteur's Discovery

    OpenAIRE

    Molčanov, K.; Kojić-Prodić., B.

    2007-01-01

    The presented review on chirality is dedicated to the centennial birth anniversary of Nobel laureate Vladimir Prelog and 160 years of Pasteur's discovery of chirality on tartrates. Chirality has been recognized in nature by artists and architects, who have used it for decorations and basic constructions, as shown in the Introduction. The progress of science through history has enabled the gathering of knowledge on chirality and its many ways of application. The key historical discoveries abou...

  12. Mining the Quantified Self: Personal Knowledge Discovery as a Challenge for Data Science.

    Science.gov (United States)

    Fawcett, Tom

    2015-12-01

    The last several years have seen an explosion of interest in wearable computing, personal tracking devices, and the so-called quantified self (QS) movement. Quantified self involves ordinary people recording and analyzing numerous aspects of their lives to understand and improve themselves. This is now a mainstream phenomenon, attracting a great deal of attention, participation, and funding. As more people are attracted to the movement, companies are offering various new platforms (hardware and software) that allow ever more aspects of daily life to be tracked. Nearly every aspect of the QS ecosystem is advancing rapidly, except for analytic capabilities, which remain surprisingly primitive. With increasing numbers of qualified self participants collecting ever greater amounts and types of data, many people literally have more data than they know what to do with. This article reviews the opportunities and challenges posed by the QS movement. Data science provides well-tested techniques for knowledge discovery. But making these useful for the QS domain poses unique challenges that derive from the characteristics of the data collected as well as the specific types of actionable insights that people want from the data. Using a small sample of QS time series data containing information about personal health we provide a formulation of the QS problem that connects data to the decisions of interest to the user.

  13. Simultaneously Discovering and Localizing Common Objects in Wild Images.

    Science.gov (United States)

    Wang, Zhenzhen; Yuan, Junsong

    2018-09-01

    Motivated by the recent success of supervised and weakly supervised common object discovery, in this paper, we move forward one step further to tackle common object discovery in a fully unsupervised way. Generally, object co-localization aims at simultaneously localizing objects of the same class across a group of images. Traditional object localization/detection usually trains specific object detectors which require bounding box annotations of object instances, or at least image-level labels to indicate the presence/absence of objects in an image. Given a collection of images without any annotations, our proposed fully unsupervised method is to simultaneously discover images that contain common objects and also localize common objects in corresponding images. Without requiring to know the total number of common objects, we formulate this unsupervised object discovery as a sub-graph mining problem from a weighted graph of object proposals, where nodes correspond to object proposals, and edges represent the similarities between neighbouring proposals. The positive images and common objects are jointly discovered by finding sub-graphs of strongly connected nodes, with each sub-graph capturing one object pattern. The optimization problem can be efficiently solved by our proposed maximal-flow-based algorithm. Instead of assuming that each image contains only one common object, our proposed solution can better address wild images where each image may contain multiple common objects or even no common object. Moreover, our proposed method can be easily tailored to the task of image retrieval in which the nodes correspond to the similarity between query and reference images. Extensive experiments on PASCAL VOC 2007 and Object Discovery data sets demonstrate that even without any supervision, our approach can discover/localize common objects of various classes in the presence of scale, view point, appearance variation, and partial occlusions. We also conduct broad

  14. Exhibiting Epistemic Objects

    DEFF Research Database (Denmark)

    Tybjerg, Karin

    2017-01-01

    of exhibiting epistemic objects that utilize their knowledge-generating potential and allow them to continue to stimulate curiosity and generate knowledge in the exhibition. The epistemic potential of the objects can then be made to work together with the function of the exhibition as a knowledge-generating set...

  15. Exploring relation types for literature-based discovery.

    Science.gov (United States)

    Preiss, Judita; Stevenson, Mark; Gaizauskas, Robert

    2015-09-01

    Literature-based discovery (LBD) aims to identify "hidden knowledge" in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of unrelated concepts that are implicitly related via a shared concept to which both are explicitly related. Many LBD approaches use simple techniques to identify semantically weak relations between concepts, for example, document co-occurrence. These generate huge numbers of hypotheses, difficult for humans to assess. More complex techniques rely on linguistic analysis, for example, shallow parsing, to identify semantically stronger relations. Such approaches generate fewer hypotheses, but may miss hidden knowledge. The authors investigate this trade-off in detail, comparing techniques for identifying related concepts to discover which are most suitable for LBD. A generic LBD system that can utilize a range of relation types was developed. Experiments were carried out comparing a number of techniques for identifying relations. Two approaches were used for evaluation: replication of existing discoveries and the "time slicing" approach.(1) RESULTS: Previous LBD discoveries could be replicated using relations based either on document co-occurrence or linguistic analysis. Using relations based on linguistic analysis generated many fewer hypotheses, but a significantly greater proportion of them were candidates for hidden knowledge. The use of linguistic analysis-based relations improves accuracy of LBD without overly damaging coverage. LBD systems often generate huge numbers of hypotheses, which are infeasible to manually review. Improving their accuracy has the potential to make these systems significantly more usable. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  16. On the threshold of discovery

    International Nuclear Information System (INIS)

    Cherenkov, P.A.

    1986-01-01

    The author, the discoverer of the Cherenkov radiation, recalls some interesting circumstances of his discoery 50 years ago and puts it into the context of the knowledge of the period. The discovery of Cherenkov radiation which today is in practice used especially for the detection of charged particles, was correctly understood and appreciated somewhat belatedly. At first the discovery was met with distrust and the original article announcing it was rejected by the magazine Nature. In effect, the discovery was not the result of any planned experiment but was the by-product of another research. It was, of course, allowed by previous achievements in various fields of physics, namely progress reached in the study of luminescence by S.I. Vavilov and his pupils. The discovery was made during an experimental study of luminescence induced in liquids by the β and γ radiations of uranyl salts. During his attempts to suppress the background radiation from vessel walls the autor found a ''background'' from pure solvent which differed from luminescence by being independent of the concentration, temperature and viscosity of the liquid. A closer examination of the phenomenon more or less by accident revealed its marked spatial asymmetry which had major importance for the development of the theory of the new phenomenon by I.V. Tamm and I.M. Frank. (A.K.)

  17. Concept relation discovery and innovation enabling technology (CORDIET)

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Neznanov, A.; Viaene, S.; Kuznetsov, S.O.; Ignatov, D.; Dedene, G.

    2011-01-01

    Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self

  18. Automated discovery systems and the inductivist controversy

    Science.gov (United States)

    Giza, Piotr

    2017-09-01

    The paper explores possible influences that some developments in the field of branches of AI, called automated discovery and machine learning systems, might have upon some aspects of the old debate between Francis Bacon's inductivism and Karl Popper's falsificationism. Donald Gillies facetiously calls this controversy 'the duel of two English knights', and claims, after some analysis of historical cases of discovery, that Baconian induction had been used in science very rarely, or not at all, although he argues that the situation has changed with the advent of machine learning systems. (Some clarification of terms machine learning and automated discovery is required here. The key idea of machine learning is that, given data with associated outcomes, software can be trained to make those associations in future cases which typically amounts to inducing some rules from individual cases classified by the experts. Automated discovery (also called machine discovery) deals with uncovering new knowledge that is valuable for human beings, and its key idea is that discovery is like other intellectual tasks and that the general idea of heuristic search in problem spaces applies also to discovery tasks. However, since machine learning systems discover (very low-level) regularities in data, throughout this paper I use the generic term automated discovery for both kinds of systems. I will elaborate on this later on). Gillies's line of argument can be generalised: thanks to automated discovery systems, philosophers of science have at their disposal a new tool for empirically testing their philosophical hypotheses. Accordingly, in the paper, I will address the question, which of the two philosophical conceptions of scientific method is better vindicated in view of the successes and failures of systems developed within three major research programmes in the field: machine learning systems in the Turing tradition, normative theory of scientific discovery formulated by Herbert Simon

  19. Model-driven discovery of underground metabolic functions in Escherichia coli

    DEFF Research Database (Denmark)

    Guzmán, Gabriela I.; Utrilla, José; Nurk, Sergey

    2015-01-01

    -scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence......E, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations....

  20. A Knowledge-Informed and Pareto-Based Artificial Bee Colony Optimization Algorithm for Multi-Objective Land-Use Allocation

    Directory of Open Access Journals (Sweden)

    Lina Yang

    2018-02-01

    Full Text Available Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front reflecting different tradeoffs in several objectives. However, obtaining a Pareto front is a challenging task, and the Pareto front obtained by state-of-the-art algorithms is still not sufficient. To achieve better Pareto solutions, taking the grid-representative land-use allocation problem with two objectives as an example, an artificial bee colony optimization algorithm for multi-objective land-use allocation (ABC-MOLA is proposed. In this algorithm, the traditional ABC’s search direction guiding scheme and solution maintaining process are modified. In addition, a knowledge-informed neighborhood search strategy, which utilizes the auxiliary knowledge of natural geography and spatial structures to facilitate the neighborhood spatial search around each solution, is developed to further improve the Pareto front’s quality. A series of comparison experiments (a simulated experiment with small data volume and a real-world data experiment for a large area shows that all the Pareto fronts obtained by ABC-MOLA totally dominate the Pareto fronts by other algorithms, which demonstrates ABC-MOLA’s effectiveness in achieving Pareto fronts of high quality.

  1. Unifying Learning Object Repositories in MACE

    NARCIS (Netherlands)

    Prause, Christian; Ternier, Stefaan; De Jong, Tim; Apelt, Stefan; Scholten, Marius; Wolpers, Martin; Eisenhauer, Markus; Vandeputte, Bram; Specht, Marcus; Duval, Erik

    2007-01-01

    Prause, C., Ternier, S., De Jong, T., Apelt, S., Scholten, M., Wolpers, M., et al. (2007). Unifying Learning Object Repositories in MACE. In D. Massart, J.-N. Colin & F. V. Assche (Eds.). Proceedings of the First International Workshop on Learning Object Discovery & Exchange (LODE'07). September,

  2. Automatic Discovery and Geotagging of Objects from Street View Imagery

    Directory of Open Access Journals (Sweden)

    Vladimir A. Krylov

    2018-04-01

    Full Text Available Many applications, such as autonomous navigation, urban planning, and asset monitoring, rely on the availability of accurate information about objects and their geolocations. In this paper, we propose the automatic detection and computation of the coordinates of recurring stationary objects of interest using street view imagery. Our processing pipeline relies on two fully convolutional neural networks: the first segments objects in the images, while the second estimates their distance from the camera. To geolocate all the detected objects coherently we propose a novel custom Markov random field model to estimate the objects’ geolocation. The novelty of the resulting pipeline is the combined use of monocular depth estimation and triangulation to enable automatic mapping of complex scenes with the simultaneous presence of multiple, visually similar objects of interest. We validate experimentally the effectiveness of our approach on two object classes: traffic lights and telegraph poles. The experiments report high object recall rates and position precision of approximately 2 m, which is approaching the precision of single-frequency GPS receivers.

  3. Personal optical disk library (PODL) for knowledge engineering

    Science.gov (United States)

    Wang, Hong; Jia, Huibo; Xu, Duanyi

    2001-02-01

    This paper describes the structure of Personal Optical Disk Library (PODL), a kind of large capacity (40 GB) optical storage equipment for personal usage. With the knowledge engineering technology integrated in the PODL, it can be used on knowledge query, knowledge discovery, Computer-Aided Instruction (CAI) and Online Analysis Process (OLAP).

  4. Knowledge driven discovery for opportunistic IoT networking.

    OpenAIRE

    Pozza, Riccardo

    2015-01-01

    So far, the Internet of Things (IoT) has been concerned with the objective of connecting every-thing, or any object to the Internet world. By collaborating towards the creation of new services, the IoT has introduced the opportunity to add smartness to our cities, homes, buildings and healthcare systems, as well as businesses and products. In many scenarios, objects or IoT devices are not always statically deployed, but they may be free to move around being carried by people or vehicles, whil...

  5. Top-down modulation of visual processing and knowledge after 250 ms supports object constancy of category decisions

    Directory of Open Access Journals (Sweden)

    Haline E. Schendan

    2015-09-01

    Full Text Available People categorize objects slowly when visual input is highly impoverished instead of optimal. While bottom-up models may explain a decision with optimal input, perceptual hypothesis testing (PHT theories implicate top-down processes with impoverished input. Brain mechanisms and the time course of PHT are largely unknown. This event-related potential study used a neuroimaging paradigm that implicated prefrontal cortex in top-down modulation of occipitotemporal cortex. Subjects categorized more impoverished and less impoverished real and pseudo objects. PHT theories predict larger impoverishment effects for real than pseudo objects because top-down processes modulate knowledge only for real objects, but different PHT variants predict different timing. Consistent with parietal-prefrontal PHT variants, around 250 ms, the earliest impoverished real object interaction started on an N3 complex, which reflects interactive cortical activity for object cognition. N3 impoverishment effects localized to both prefrontal and occipitotemporal cortex for real objects only. The N3 also showed knowledge effects by 230 ms that localized to occipitotemporal cortex. Later effects reflected (a word meaning in temporal cortex during the N400, (b internal evaluation of prior decision and memory processes and secondary higher-order memory involving anterotemporal parts of a default mode network during posterior positivity (P600, and (c response related activity in posterior cingulate during an anterior slow wave (SW after 700 ms. Finally, response activity in supplementary motor area during a posterior SW after 900 ms showed impoverishment effects that correlated with RTs. Convergent evidence from studies of vision, memory, and mental imagery which reflects purely top-down inputs, indicates that the N3 reflects the critical top-down processes of PHT. A hybrid multiple-state interactive, PHT and decision theory best explains the visual constancy of object cognition.

  6. Top-down modulation of visual processing and knowledge after 250 ms supports object constancy of category decisions.

    Science.gov (United States)

    Schendan, Haline E; Ganis, Giorgio

    2015-01-01

    People categorize objects more slowly when visual input is highly impoverished instead of optimal. While bottom-up models may explain a decision with optimal input, perceptual hypothesis testing (PHT) theories implicate top-down processes with impoverished input. Brain mechanisms and the time course of PHT are largely unknown. This event-related potential study used a neuroimaging paradigm that implicated prefrontal cortex in top-down modulation of occipitotemporal cortex. Subjects categorized more impoverished and less impoverished real and pseudo objects. PHT theories predict larger impoverishment effects for real than pseudo objects because top-down processes modulate knowledge only for real objects, but different PHT variants predict different timing. Consistent with parietal-prefrontal PHT variants, around 250 ms, the earliest impoverished real object interaction started on an N3 complex, which reflects interactive cortical activity for object cognition. N3 impoverishment effects localized to both prefrontal and occipitotemporal cortex for real objects only. The N3 also showed knowledge effects by 230 ms that localized to occipitotemporal cortex. Later effects reflected (a) word meaning in temporal cortex during the N400, (b) internal evaluation of prior decision and memory processes and secondary higher-order memory involving anterotemporal parts of a default mode network during posterior positivity (P600), and (c) response related activity in posterior cingulate during an anterior slow wave (SW) after 700 ms. Finally, response activity in supplementary motor area during a posterior SW after 900 ms showed impoverishment effects that correlated with RTs. Convergent evidence from studies of vision, memory, and mental imagery which reflects purely top-down inputs, indicates that the N3 reflects the critical top-down processes of PHT. A hybrid multiple-state interactive, PHT and decision theory best explains the visual constancy of object cognition.

  7. The pillar of metropolitan greatness: The long making of archeological objects in Paris (1711-2001).

    Science.gov (United States)

    Van Damme, Stéphane

    2017-09-01

    Over three centuries after the 1711 discovery in the choir of Notre-Dame in Paris of a square-section stone bas-relief (the Pillar of the Boatmen) with depictions of several deities, both Gaulish and Roman, the blocks comprising it were analyzed as a symbol of Parisian power, if not autonomy, vis-à-vis the Roman Empire. Variously considered as local, national, or imperial representations, the blocks were a constant object of admiration, interrogation, and speculation among antiquarians of the Republic of Letters. They were also boundary objects - products of the emergence of a Parisian archeology dated from 1711. If this science reflected the tensions and ambiguities of a local regime of knowledge situated in a national context, it also helped to coordinate archeological work between different institutions and actors. This paper would like to assess the specific role played by the Pillar of the Boatmen as a fetish object in this process. To what extent could an archeological artifact influence this reshaping of urban representation, this change of scales? By following the three-century career of the pillar's blocks as composite objects, which some have identified as merely stones or a column, it is possible to understand the multiple dimensions that defined the object as archeological - as an artifact that contributed to the relocating of the historical city center - and the multiple approaches that transform existing remains into knowledgeable objects.

  8. Does scientism undermine other forms of knowledge?

    Directory of Open Access Journals (Sweden)

    Ndubuisi C. Ani

    2016-03-01

    Full Text Available Science has continually bridged the gaps in knowledge about reality by exerting its prowess in explanation, discovery and invention. Astonished by the successes of science coupled with the demonstrability and (purported objectivity of scientific knowledge, scholars are lured to nurse the impression that science is the answer to all questions that need to be asked about reality. This has led to an intellectual fanaticism called scientism where science is seen as the only bona fide way of attaining any true knowledge whatsoever. Consequently, other fields of knowledge suffer grievously from being abandoned, belittled or modified to operate using the scientific method of inquiry. Against this backdrop, this paper argues that science is not the only way of knowing reality. Other fields of knowledge and their traditional methods of inquiry are vital in the understanding of reality that abandoning or constructing them in the scientific light is tantamount to having a parochial view of reality. Through its arguments, the research advances pluralistic, inclusive and complementary approaches.Intradisciplinary and/or interdisciplinary implications: This research challenges the claims and influence of scientism, which holds that science has the answer to every question about reality. The paper contends that other epistemological methods of philosophical, religious, mythical and artistic forms are essential epistemological methods. Hence, the research advances a pluralistic and complementary approach in epistemology.

  9. Semantic Data Integration and Knowledge Management to Represent Biological Network Associations.

    Science.gov (United States)

    Losko, Sascha; Heumann, Klaus

    2017-01-01

    The vast quantities of information generated by academic and industrial research groups are reflected in a rapidly growing body of scientific literature and exponentially expanding resources of formalized data, including experimental data, originating from a multitude of "-omics" platforms, phenotype information, and clinical data. For bioinformatics, the challenge remains to structure this information so that scientists can identify relevant information, to integrate this information as specific "knowledge bases," and to formalize this knowledge across multiple scientific domains to facilitate hypothesis generation and validation. Here we report on progress made in building a generic knowledge management environment capable of representing and mining both explicit and implicit knowledge and, thus, generating new knowledge. Risk management in drug discovery and clinical research is used as a typical example to illustrate this approach. In this chapter we introduce techniques and concepts (such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers) that are used to represent complex biomedical networks. The BioXM™ Knowledge Management Environment is used as an example to demonstrate how a domain such as oncology is represented and how this representation is utilized for research.

  10. Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop.

    Science.gov (United States)

    Jagodnik, Kathleen M; Koplev, Simon; Jenkins, Sherry L; Ohno-Machado, Lucila; Paten, Benedict; Schurer, Stephan C; Dumontier, Michel; Verborgh, Ruben; Bui, Alex; Ping, Peipei; McKenna, Neil J; Madduri, Ravi; Pillai, Ajay; Ma'ayan, Avi

    2017-07-01

    The volume and diversity of data in biomedical research have been rapidly increasing in recent years. While such data hold significant promise for accelerating discovery, their use entails many challenges including: the need for adequate computational infrastructure, secure processes for data sharing and access, tools that allow researchers to find and integrate diverse datasets, and standardized methods of analysis. These are just some elements of a complex ecosystem that needs to be built to support the rapid accumulation of these data. The NIH Big Data to Knowledge (BD2K) initiative aims to facilitate digitally enabled biomedical research. Within the BD2K framework, the Commons initiative is intended to establish a virtual environment that will facilitate the use, interoperability, and discoverability of shared digital objects used for research. The BD2K Commons Framework Pilots Working Group (CFPWG) was established to clarify goals and work on pilot projects that address existing gaps toward realizing the vision of the BD2K Commons. This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Knowledge discovery based on experiential learning corporate culture management

    Science.gov (United States)

    Tu, Kai-Jan

    2014-10-01

    A good corporate culture based on humanistic theory can make the enterprise's management very effective, all enterprise's members have strong cohesion and centripetal force. With experiential learning model, the enterprise can establish an enthusiastic learning spirit corporate culture, have innovation ability to gain the positive knowledge growth effect, and to meet the fierce global marketing competition. A case study on Trend's corporate culture can offer the proof of industry knowledge growth rate equation as the contribution to experiential learning corporate culture management.

  12. The discovery and history of knowledge of natural atmospheric radioactivity

    International Nuclear Information System (INIS)

    Renoux, A.

    1996-01-01

    Everybody knows that the radioactivity was discovered, 100 years ago, by the Frenchman Henri Becquerel at Paris, in Feb. 1896, stemmed from the discovery of X-rays by Roentgen in the preceding year. In 1899, Rutherford was able to show the existence of α and β rays, and in 1900 Villard showed the presence of a third class of rays, the γ rays. The discovery of the rare radioactive gas radon is attributed to P. and M. Curie in 1898 and F. Dorn in 1900. Thoron ( 220 Rn) was discovered by Rutherford and Owens in 1899-1900 and Actinon ( 219 Rn) by Debierne and Geisel about the same time. The radon's radiotoxicity was studied in France since 1904 by Bouchard and Balthazard and in 1924 it was formulated the hypothesis that the great mortality observed in the uranium miners of Schneeberg in Germany and Joachimsthal in Czechoslovakia was maybe due to the radon. But, in fact, Elster and Geitel were the first to see that the radioactivity is present in the atmosphere in about 1901. After this date, many investigations were made (M. Curie, for example), but it is during the fifties and, of course, until today that the most numerous works were developed. In this paper, we speak about the researches of the after second war pioneers: Evans, Wilkening, Kawano, Israel, Junge, Schuman, Bricard... Renoux, Madelaine, Blanc, Fontan, Siksna, Chamberlain, Dyson, Nolan, etc. and the works developed later. Finally, we reach to the nineties, period where the works are particularly directed in the aim of radon and radon progeny indoor, with in particular, many works effectuated in France. (author). 78 refs., 17 figs., 2 tabs

  13. Causality discovery technology

    Science.gov (United States)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  14. Introduction to fragment-based drug discovery.

    Science.gov (United States)

    Erlanson, Daniel A

    2012-01-01

    Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

  15. Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

    Science.gov (United States)

    Agrafiotis, Dimitris K; Alex, Simson; Dai, Heng; Derkinderen, An; Farnum, Michael; Gates, Peter; Izrailev, Sergei; Jaeger, Edward P; Konstant, Paul; Leung, Albert; Lobanov, Victor S; Marichal, Patrick; Martin, Douglas; Rassokhin, Dmitrii N; Shemanarev, Maxim; Skalkin, Andrew; Stong, John; Tabruyn, Tom; Vermeiren, Marleen; Wan, Jackson; Xu, Xiang Yang; Yao, Xiang

    2007-01-01

    We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, data systems, and cultures using modern information technology and to provide scientists with tools that allow them to analyze multifactorial SAR and make informed, data-driven decisions. The system consists of three major components: (1) a data warehouse, which combines data from multiple chemical and pharmacological transactional databases, designed for supreme query performance; (2) a state-of-the-art application suite, which facilitates data upload, retrieval, mining, and reporting, and (3) a workspace, which facilitates collaboration and data sharing by allowing users to share queries, templates, results, and reports across project teams, campuses, and other organizational units. Chemical intelligence, performance, and analytical sophistication lie at the heart of the new system, which was developed entirely in-house. ABCD is used routinely by more than 1000 scientists around the world and is rapidly expanding into other functional areas within the J&J organization.

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

    Science.gov (United States)

    Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

    2013-10-01

    Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Mathematical modeling for novel cancer drug discovery and development.

    Science.gov (United States)

    Zhang, Ping; Brusic, Vladimir

    2014-10-01

    Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

  18. A New Universe of Discoveries

    Science.gov (United States)

    Córdova, France A.

    2016-01-01

    The convergence of emerging advances in astronomical instruments, computational capabilities and talented practitioners (both professional and civilian) is creating an extraordinary new environment for making numerous fundamental discoveries in astronomy, ranging from the nature of exoplanets to understanding the evolution of solar systems and galaxies. The National Science Foundation is playing a critical role in supporting, stimulating, and shaping these advances. NSF is more than an agency of government or a funding mechanism for the infrastructure of science. The work of NSF is a sacred trust that every generation of Americans makes to those of the next generation, that we will build on the body of knowledge we inherit and continue to push forward the frontiers of science. We never lose sight of NSF's obligation to "explore the unexplored" and inspire all of humanity with the wonders of discovery. As the only Federal agency dedicated to the support of basic research and education in all fields of science and engineering, NSF has empowered discoveries across a broad spectrum of scientific inquiry for more than six decades. The result is fundamental scientific research that has had a profound impact on our nation's innovation ecosystem and kept our nation at the very forefront of the world's science-and-engineering enterprise.

  19. Formal concept analysis in knowledge discovery: A survey

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Viaene, S.; Dedene, G.; Croitoru, M.; Ferré, S.; Lukose, D.

    2010-01-01

    In this paper, we analyze the literature on Formal Concept Analysis (FCA) using FCA. We collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in the abstract. We developed a knowledge browsing environment to support our literature analysis process. The pdf-files

  20. Discovery stories in the science classroom

    Science.gov (United States)

    Arya, Diana Jaleh

    when the readers have little prior knowledge of a given topic. Further, ethnic minority groups of lower socio-economic level (i.e., Latin and African-American origins) demonstrated an even greater benefit from the SDN texts, suggesting that a scientist's story of discovery can help to close the gap in academic performance in science.

  1. Knowledge Discovery and Pavement Performance : Intelligent Data Mining

    NARCIS (Netherlands)

    Miradi, M.

    2009-01-01

    The main goal of the study was to discover knowledge from data about asphalt road pavement problems to achieve a better understanding of the behavior of them and via this understanding improve pavement quality and enhance its lifespan. Four pavement problems were chosen to be investigated; raveling

  2. State of the Art in Tumor Antigen and Biomarker Discovery

    International Nuclear Information System (INIS)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

    2011-01-01

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology

  3. Knowledge deficit, attitude and behavior scales association to objective measures of sun exposure and sunburn in a Danish population based sample.

    Science.gov (United States)

    Køster, Brian; Søndergaard, Jens; Nielsen, Jesper Bo; Christensen, Karl Bang; Allen, Martin; Olsen, Anja; Bentzen, Joan

    2017-01-01

    The objective of this study was to develop new scales measuring knowledge and attitude about UVR and sun related behavior, and to examine their association to sun related behavior objectively measured by personal dosimetry. During May-August 2013, 664 Danes wore a personal electronic UV-dosimeter for one week that measured their UVR exposure. Afterwards, they answered a questionnaire on sun-related items. We applied descriptive analysis, linear and logistic regression analysis to evaluate the associations between the questionnaire scales and objective UVR measures. Perceiving protection as routine and important were positively correlated with protective behavior. Knowledge deficit of UV and risk of melanoma, perceived benefits and importance of protection behavior was also correlated with use of protection. 'Knowledge deficit of UV and risk of melanoma and Perceived barrier towards sun avoidance between 12 and 15' were both associated with increased risk of sunburn. Attitude towards tan was associated to both outdoor time and exposure as well as use of protection, but not to sunburn. The results regarding Knowledge deficit of UV and risk of melanoma associated to UVR exposure and Perceived barrier towards sun avoidance between 12 and 15 emphasize the importance of awareness of melanoma risk and the priority of the skin cancer prevention advice. Shifting activities to outside the suns peak-hours could be an approach for structural and campaign preventive measures. Knowledge of items predicting exposure to UVR, use of protection and sunburn are important for planning of preventive interventions and melanoma research.

  4. Managing knowledge management

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    2016-01-01

    today is that knowledge about health and health care is generated from a multitude of sources and circulated rapidly across professional and Karin Knorr Cetina (2006, 2007) stresses that to understand knowledge management practices we need to magnify the space of knowledge in action and consider......This work-in-progress focuses on the management of knowledge management and its socio-material implications. More specifically, it focuses on the management of epistemic objects and objectives in professional health care organisations. One of the main characteristics of professional health care...... the presentation and circulation of epistemic objects in extended contexts. In other words, we need to consider that the routes from research to practice – and the relation between knowledge and management – is not straightforward. First epistemic objects and objectives may lead to contrasting results...

  5. The limits of de novo DNA motif discovery.

    Directory of Open Access Journals (Sweden)

    David Simcha

    Full Text Available A major challenge in molecular biology is reverse-engineering the cis-regulatory logic that plays a major role in the control of gene expression. This program includes searching through DNA sequences to identify "motifs" that serve as the binding sites for transcription factors or, more generally, are predictive of gene expression across cellular conditions. Several approaches have been proposed for de novo motif discovery-searching sequences without prior knowledge of binding sites or nucleotide patterns. However, unbiased validation is not straightforward. We consider two approaches to unbiased validation of discovered motifs: testing the statistical significance of a motif using a DNA "background" sequence model to represent the null hypothesis and measuring performance in predicting membership in gene clusters. We demonstrate that the background models typically used are "too null," resulting in overly optimistic assessments of significance, and argue that performance in predicting TF binding or expression patterns from DNA motifs should be assessed by held-out data, as in predictive learning. Applying this criterion to common motif discovery methods resulted in universally poor performance, although there is a marked improvement when motifs are statistically significant against real background sequences. Moreover, on synthetic data where "ground truth" is known, discriminative performance of all algorithms is far below the theoretical upper bound, with pronounced "over-fitting" in training. A key conclusion from this work is that the failure of de novo discovery approaches to accurately identify motifs is basically due to statistical intractability resulting from the fixed size of co-regulated gene clusters, and thus such failures do not necessarily provide evidence that unfound motifs are not active biologically. Consequently, the use of prior knowledge to enhance motif discovery is not just advantageous but necessary. An implementation of

  6. Sigmund Freud (1856-1939) and Karl Köller (1857-1944) and the discovery of local anesthesia.

    Science.gov (United States)

    dos Reis, Almiro

    2009-01-01

    The understanding, occasionally recognized, that Sigmund Freud had the intuition to use cocaine as local anesthetic for surgical procedures, or even that he played any role in the discovery of local anesthesia is not true. The objective of Freud's studies were different, and based in irrefutable evidence, Karl Köller was the real inventor of local anesthesia. In face of those facts, proper knowledge of this historically important subject is due. This report refers to the long-known properties of cocaine. It also remembers personal data, and the professional and scientific activities of Sigmund Freud and Karl Köller. It presents Freud's researches on the pathophysiological effects of cocaine. It exposes the reasons for the harsh criticism of Freud's concepts. It describes the sudden, but conscious and justified, idea of Karl Köller to study scientifically the use of cocaine as a local anesthetic in animals and humans. It indicates how those pioneering studies, that culminated with the discovery of local anesthesia by Köller and two presentations in Vienna on the subject, were done. It also reports the first ophthalmologic surgery under local anesthesia. It shows the immediate dissemination throughout the world of the discovery that marked the beginning of regional blocks. It comments several documents corroborating the role of Köller in this discovery. And, finally, it mentions the numerous homages received by Köller in different areas of the world. COCLUSIONS: Regional block was introduced by Karl Köller in 1884, when he demonstrated the feasibility of performing painless ophthalmologic surgeries by using cocaine as a local anesthetic. Sigmund Freud studied cocaine extensively, but he did not have direct participation in this important discovery.

  7. A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

    Directory of Open Access Journals (Sweden)

    Asma Adala

    2011-01-01

    Full Text Available As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that enables semantic Web service discovery based on keywords written in natural language. We describe a novel approach for automatic discovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in natural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to compute the semantic distance between ontological concepts.

  8. Discovery: Under the Microscope at Kennedy Space Center

    Science.gov (United States)

    Howard, Philip M.

    2013-01-01

    The National Aeronautics & Space Administration (NASA) is known for discovery, exploration, and advancement of knowledge. Since the days of Leeuwenhoek, microscopy has been at the forefront of discovery and knowledge. No truer is that statement than today at Kennedy Space Center (KSC), where microscopy plays a major role in contamination identification and is an integral part of failure analysis. Space exploration involves flight hardware undergoing rigorous "visually clean" inspections at every step of processing. The unknown contaminants that are discovered on these inspections can directly impact the mission by decreasing performance of sensors and scientific detectors on spacecraft and satellites, acting as micrometeorites, damaging critical sealing surfaces, and causing hazards to the crew of manned missions. This talk will discuss how microscopy has played a major role in all aspects of space port operations at KSC. Case studies will highlight years of analysis at the Materials Science Division including facility and payload contamination for the Navigation Signal Timing and Ranging Global Positioning Satellites (NA VST AR GPS) missions, quality control monitoring of monomethyl hydrazine fuel procurement for launch vehicle operations, Shuttle Solids Rocket Booster (SRB) foam processing failure analysis, and Space Shuttle Main Engine Cut-off (ECO) flight sensor anomaly analysis. What I hope to share with my fellow microscopists is some of the excitement of microscopy and how its discoveries has led to hardware processing, that has helped enable the successful launch of vehicles and space flight missions here at Kennedy Space Center.

  9. Participative knowledge management to empower manufacturing workers

    DEFF Research Database (Denmark)

    Campatelli, Gianni; Richter, Alexander; Stocker, Alexander

    2016-01-01

    skills. In this paper, the authors suggest a participative knowledge management approach to empower manufacturing workers. Starting from a comprehensive empirical analysis of the existing work practices in a manufacturing company, the authors have developed and validated a knowledge management system...... prototype. The prototype is aimed for training, problem solving, and facilitating the discovery, acquisition, and sharing of manufacturing knowledge. The conducted evaluation of the prototype indicates that workers' skills and level of work satisfaction will increase since the knowledge management system...

  10. Volatility Discovery

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

    The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

  11. Children's level of word knowledge predicts their exclusion of familiar objects as referents of novel words

    Directory of Open Access Journals (Sweden)

    Susanne eGrassmann

    2015-08-01

    Full Text Available When children are learning a novel object label, they tend to exclude as possible referents familiar objects for which they already have a name. In the current study, we wanted to know if children would behave in this same way regardless of how well they knew the name of potential referent objects, specifically, whether they could only comprehend it or they could both comprehend and produce it. Sixty-six monolingual German-speaking 2-, 3-, and 4-year-old children participated in two experimental sessions. In one session the familiar objects were chosen such that their labels were in the children's productive vocabularies, and in the other session the familiar objects were chosen such that their labels were only in the children's receptive vocabularies. Results indicated that children at all three ages were more likely to exclude a familiar object as the potential referent of the novel word if they could comprehend and produce its name rather than comprehend its name only. Indeed, level of word knowledge as operationalized in this way was a better predictor than was age. These results are discussed in the context of current theories of word learning by exclusion.

  12. Children's Comprehension of Object Relative Sentences: It's Extant Language Knowledge That Matters, Not Domain-General Working Memory

    Science.gov (United States)

    Rusli, Yazmin Ahmad; Montgomery, James W.

    2017-01-01

    Purpose: The aim of this study was to determine whether extant language (lexical) knowledge or domain-general working memory is the better predictor of comprehension of object relative sentences for children with typical development. We hypothesized that extant language knowledge, not domain-general working memory, is the better predictor. Method:…

  13. Integration of asynchronous knowledge sources in a novel speech recognition framework

    OpenAIRE

    Van hamme, Hugo

    2008-01-01

    Van hamme H., ''Integration of asynchronous knowledge sources in a novel speech recognition framework'', Proceedings ITRW on speech analysis and processing for knowledge discovery, 4 pp., June 2008, Aalborg, Denmark.

  14. 40 CFR 300.300 - Phase I-Discovery or notification.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 27 2010-07-01 2010-07-01 false Phase I-Discovery or notification. 300.300 Section 300.300 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND... person in charge of a vessel or a facility shall, as soon as he or she has knowledge of any discharge...

  15. Recent advances in inkjet dispensing technologies: applications in drug discovery.

    Science.gov (United States)

    Zhu, Xiangcheng; Zheng, Qiang; Yang, Hu; Cai, Jin; Huang, Lei; Duan, Yanwen; Xu, Zhinan; Cen, Peilin

    2012-09-01

    Inkjet dispensing technology is a promising fabrication methodology widely applied in drug discovery. The automated programmable characteristics and high-throughput efficiency makes this approach potentially very useful in miniaturizing the design patterns for assays and drug screening. Various custom-made inkjet dispensing systems as well as specialized bio-ink and substrates have been developed and applied to fulfill the increasing demands of basic drug discovery studies. The incorporation of other modern technologies has further exploited the potential of inkjet dispensing technology in drug discovery and development. This paper reviews and discusses the recent developments and practical applications of inkjet dispensing technology in several areas of drug discovery and development including fundamental assays of cells and proteins, microarrays, biosensors, tissue engineering, basic biological and pharmaceutical studies. Progression in a number of areas of research including biomaterials, inkjet mechanical systems and modern analytical techniques as well as the exploration and accumulation of profound biological knowledge has enabled different inkjet dispensing technologies to be developed and adapted for high-throughput pattern fabrication and miniaturization. This in turn presents a great opportunity to propel inkjet dispensing technology into drug discovery.

  16. Investigation of objective evaluation system of anatomical knowledge and operative techniques in education for rhinologic surgery

    International Nuclear Information System (INIS)

    Ishimasa, Hiroshi; Murata, Hideyuki

    2006-01-01

    Operative technique and approach method for the nasal and paranasal sinuses, areas of anatomical complexity and high individual variation, have been transformed dramatically in recent years with the introduction of the endoscope. However, due to surgeons' unfamiliarity with the technique and anatomical misidentification, medical errors show no sign of significant decline. As endoscopic sinus surgery (ESS) is an indirect operating procedure, conducted while watching a video monitor, it is necessary for the surgeon to become accustomed to the special properties of the endoscope, namely, the lack of perspective projection. Until now, surgical training has made repetitive use of video material and donated cadavers for skill practice, and a system of one-to-one instruction whereby instruction is received from a lead surgeon while the learner joins the actual procedure as an assistant. That is to say, there has been no objective method of evaluating individual proficiency until now. In our study, evaluation of individual anatomical knowledge and thought process until task completion, objective evaluation of surgical instrument handling and technique, and evaluation of knowledge required in actual surgeries are discussed Then an individually responsive method of surgical instruction with self-evaluation and self-cognition will be sought. (author)

  17. The fragile x mental retardation syndrome 20 years after the FMR1 gene discovery: an expanding universe of knowledge.

    Science.gov (United States)

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-08-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations.

  18. The Fragile X Mental Retardation Syndrome 20 Years After the FMR1 Gene Discovery: an Expanding Universe of Knowledge

    Science.gov (United States)

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-01-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations. PMID:21912443

  19. The Discovery of the Existence of the Absolute in Existential Metaphysics

    Directory of Open Access Journals (Sweden)

    Andrzej Maryniarczyk

    2016-12-01

    Full Text Available The article shows the way in which the discovery of the existence of the Absolute is made in existential metaphysics. This existential metaphysics provides us with knowledge about reality. It shows the content of the experience of being, the content given to us in the transcendentals. It also unveils the foundation of the rational order, which is given to us in the discovery of the first principles of the existence of being and of cognition. Metaphysics provides us also with knowledge concerning the structure of being. It shows us being as composite and plural; being which is “insufficient” in its structure and calls for an explanation. That being—that is problematized in existence, given to us in experience, and incompletely intelligible in itself—lifts us toward its ultimate “complement” and understanding, to the Absolute.

  20. Discovery of the leinamycin family of natural products by mining actinobacterial genomes.

    Science.gov (United States)

    Pan, Guohui; Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Yang, Dong; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen; Shen, Ben

    2017-12-26

    Nature's ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF-SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF-SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm -type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature's rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature's biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

  1. Development of Scientific Approach Based on Discovery Learning Module

    Science.gov (United States)

    Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

    2018-04-01

    Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on

  2. Knowledge extraction from evolving spiking neural networks with rank order population coding.

    Science.gov (United States)

    Soltic, Snjezana; Kasabov, Nikola

    2010-12-01

    This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

  3. Chemogenomic discovery of allosteric antagonists at the GPRC6A receptor

    DEFF Research Database (Denmark)

    Gloriam, David E.; Wellendorph, Petrine; Johansen, Lars Dan

    2011-01-01

    and pharmacological character: (1) chemogenomic lead identification through the first, to our knowledge, ligand inference between two different GPCR families, Families A and C; and (2) the discovery of the most selective GPRC6A allosteric antagonists discovered to date. The unprecedented inference of...... pharmacological activity across GPCR families provides proof-of-concept for in silico approaches against Family C targets based on Family A templates, greatly expanding the prospects of successful drug design and discovery. The antagonists were tested against a panel of seven Family A and C G protein-coupled receptors...

  4. The ambiguous and bewitching power of knowledge, skills and attitudes leads to confusing statements of learning objectives.

    Science.gov (United States)

    Guilbert, J-J

    2002-01-01

    The words "knowledge", "skills" and "attitudes" are given different meanings by health personnel when discussing educational issues. Ambiguity is known as a handicap to efficient communication. In the design of a curriculum the quality of the definition of learning objectives plays a fundamental role. If learning objectives lack clarity, learners and teachers will face operational difficulties. As Robert Mager said, "If you are not certain of where you are going you may very well end up somewhere else and not even know it". Knowledge is not only memory of facts but what you do with it. The complexity of human behaviour should not be underestimated. This is why educational objectives need active non-ambiguous verbs in order to achieve better communication between teachers and learners and to assess that complexity. This is why I suggest using the expression intellectual skill (or competence) as meaning "a rational decision or act". Sensomotor skill (or competence) would replace "skills" as presently used and cover only "acts which require a neuromuscular coordination". Interpersonal communication skill (or competence) would replace "attitude(s)" and be limited to "verbal and non-verbal relation between persons". As the level of validity of assessment of learners' competencies is linked to the clarity of learning objectives, it is hoped that the above suggestions will raise the overall level of validity of the evaluation system. This is why it is important that everybody understands, in the same manner, the meaning of a learning objective. It will help learners to focus their learning efforts on the right target. It will help teachers to ensure the relevance to health needs of their teaching and the validity of assessment instruments. In both cases it will be beneficial to the health of the population.

  5. Design and implementation of the object-oriented fast simulation program for the ATLAS experiment and its use to determine the discovery potential of the Higgs Boson via the channel h- > ZZ- > bbl+l-

    CERN Document Server

    Steward, Richard M

    2004-01-01

    The design and implementation of the object-oriented fast simulation program Atlfast is described for the ATLAS experiment at the CERN particle physics laboratory in Switzerland. Fast simulations use parametrised energy and momentum smearing in order to recreate the detection efficiency and particle identification of a real experimental detector, without the time-consuming computation required for full detector simulation. Additionally, an object-oriented program for performing user-defined physics analyses is described. This program is released for general use by the ATLAS collaboration and is designed for use with, but not restricted to, physics output from the Atlfast fast simulation program. These programs are demonstrated in a physics study of the feasibility of discovering the Higgs boson at the ATLAS experiment, using the discovery channel ho > Z Z * > bb l+l via weak vector boson fusion in the mass range 150 GeV - 200 GeV. It is found that this channel does not significantly increase the discovery pot...

  6. Near-Earth Object Survey Simulation Software

    Science.gov (United States)

    Naidu, Shantanu P.; Chesley, Steven R.; Farnocchia, Davide

    2017-10-01

    There is a significant interest in Near-Earth objects (NEOs) because they pose an impact threat to Earth, offer valuable scientific information, and are potential targets for robotic and human exploration. The number of NEO discoveries has been rising rapidly over the last two decades with over 1800 being discovered last year, making the total number of known NEOs >16000. Pan-STARRS and the Catalina Sky Survey are currently the most prolific NEO surveys, having discovered >1600 NEOs between them in 2016. As next generation surveys such as Large Synoptic Survey Telescope (LSST) and the proposed Near-Earth Object Camera (NEOCam) become operational in the next decade, the discovery rate is expected to increase tremendously. Coordination between various survey telescopes will be necessary in order to optimize NEO discoveries and create a unified global NEO discovery network. We are collaborating on a community-based, open-source software project to simulate asteroid surveys to facilitate such coordination and develop strategies for improving discovery efficiency. Our effort so far has focused on development of a fast and efficient tool capable of accepting user-defined asteroid population models and telescope parameters such as a list of pointing angles and camera field-of-view, and generating an output list of detectable asteroids. The software takes advantage of the widely used and tested SPICE library and architecture developed by NASA’s Navigation and Ancillary Information Facility (Acton, 1996) for saving and retrieving asteroid trajectories and camera pointing. Orbit propagation is done using OpenOrb (Granvik et al. 2009) but future versions will allow the user to plug in a propagator of their choice. The software allows the simulation of both ground-based and space-based surveys. Performance is being tested using the Grav et al. (2011) asteroid population model and the LSST simulated survey “enigma_1189”.

  7. Distributed Service Discovery for Heterogeneous Wireless Sensor Networks

    NARCIS (Netherlands)

    Marin Perianu, Raluca; Scholten, Johan; Havinga, Paul J.M.

    Service discovery in heterogeneous Wireless Sensor Networks is a challenging research objective, due to the inherent limitations of sensor nodes and their extensive and dense deployment. The protocols proposed for ad hoc networks are too heavy for sensor environments. This paper presents a

  8. Knowledge categorization affects popularity and quality of Wikipedia articles.

    Science.gov (United States)

    Lerner, Jürgen; Lomi, Alessandro

    2018-01-01

    The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia-an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system.

  9. Knowledge categorization affects popularity and quality of Wikipedia articles

    Science.gov (United States)

    Lomi, Alessandro

    2018-01-01

    The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia—an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system. PMID:29293627

  10. Improve Data Mining and Knowledge Discovery through the use of MatLab

    Science.gov (United States)

    Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

    2011-01-01

    Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and

  11. Targeting cysteine proteases in trypanosomatid disease drug discovery.

    Science.gov (United States)

    Ferreira, Leonardo G; Andricopulo, Adriano D

    2017-12-01

    Chagas disease and human African trypanosomiasis are endemic conditions in Latin America and Africa, respectively, for which no effective and safe therapy is available. Efforts in drug discovery have focused on several enzymes from these protozoans, among which cysteine proteases have been validated as molecular targets for pharmacological intervention. These enzymes are expressed during the entire life cycle of trypanosomatid parasites and are essential to many biological processes, including infectivity to the human host. As a result of advances in the knowledge of the structural aspects of cysteine proteases and their role in disease physiopathology, inhibition of these enzymes by small molecules has been demonstrated to be a worthwhile approach to trypanosomatid drug research. This review provides an update on drug discovery strategies targeting the cysteine peptidases cruzain from Trypanosoma cruzi and rhodesain and cathepsin B from Trypanosoma brucei. Given that current chemotherapy for Chagas disease and human African trypanosomiasis has several drawbacks, cysteine proteases will continue to be actively pursued as valuable molecular targets in trypanosomatid disease drug discovery efforts. Copyright © 2017. Published by Elsevier Inc.

  12. Panorama 2014 - New oil and gas discoveries

    International Nuclear Information System (INIS)

    Vially, Roland; Hureau, Geoffroy

    2013-12-01

    Spending on exploration increased significantly in 2012, and this growth should continue into 2013. Over a period of ten years, exploration budgets have increased five-fold, leading to major discoveries in regions as yet unexplored. In 2012, 25 billion barrels of oil equivalent (Gboe) were revealed. This is more than the average for the whole decade, but less than the amount for the previous year. Although knowledge of the volumes that have been discovered is still very fragmented, they should continue to fall into 2013. The main reason lies in the fact that spending on exploration is being shifted towards assessing discoveries made in previous years in the particularly prolific basins of Brazil and East Africa, while the exploration of border regions - such as the West African pre-salt formation - is still only in its early stages. (authors)

  13. Improving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker index

    Directory of Open Access Journals (Sweden)

    Zomaya Albert Y

    2006-12-01

    Full Text Available Abstract Background Knowledge of protein domain boundaries is critical for the characterisation and understanding of protein function. The ability to identify domains without the knowledge of the structure – by using sequence information only – is an essential step in many types of protein analyses. In this present study, we demonstrate that the performance of DomainDiscovery is improved significantly by including the inter-domain linker index value for domain identification from sequence-based information. Improved DomainDiscovery uses a Support Vector Machine (SVM approach and a unique training dataset built on the principle of consensus among experts in defining domains in protein structure. The SVM was trained using a PSSM (Position Specific Scoring Matrix, secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results Improved DomainDiscovery is compared with other methods by benchmarking against a structurally non-redundant dataset and also CASP5 targets. Improved DomainDiscovery achieves 70% accuracy for domain boundary identification in multi-domains proteins. Conclusion Improved DomainDiscovery compares favourably to the performance of other methods and excels in the identification of domain boundaries for multi-domain proteins as a result of introducing support vector machine with benchmark_2 dataset.

  14. A role for physicians in ethnopharmacology and drug discovery.

    Science.gov (United States)

    Raza, Mohsin

    2006-04-06

    Ethnopharmacology investigations classically involved traditional healers, botanists, anthropologists, chemists and pharmacologists. The role of some groups of researchers but not of physician has been highlighted and well defined in ethnopharmacological investigations. Historical data shows that discovery of several important modern drugs of herbal origin owe to the medical knowledge and clinical expertise of physicians. Current trends indicate negligible role of physicians in ethnopharmacological studies. Rising cost of modern drug development is attributed to the lack of classical ethnopharmacological approach. Physicians can play multiple roles in the ethnopharmacological studies to facilitate drug discovery as well as to rescue authentic traditional knowledge of use of medicinal plants. These include: (1) Ethnopharmacological field work which involves interviewing healers, interpreting traditional terminologies into their modern counterparts, examining patients consuming herbal remedies and identifying the disease for which an herbal remedy is used. (2) Interpretation of signs and symptoms mentioned in ancient texts and suggesting proper use of old traditional remedies in the light of modern medicine. (3) Clinical studies on herbs and their interaction with modern medicines. (4) Advising pharmacologists to carryout laboratory studies on herbs observed during field studies. (5) Work in collaboration with local healers to strengthen traditional system of medicine in a community. In conclusion, physician's involvement in ethnopharmacological studies will lead to more reliable information on traditional use of medicinal plants both from field and ancient texts, more focused and cheaper natural product based drug discovery, as well as bridge the gap between traditional and modern medicine.

  15. A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

    2013-10-01

    Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.

  16. The discovery of radioactivity: a bend in sciences history

    International Nuclear Information System (INIS)

    Dautray, R.

    1997-01-01

    One hundred years after the discovery of radioactivity, it is possible to see what are the consequences of this discovery for the science. Four consequences are studied in this article: the acquisition of a new knowledge about matter and universe. Secondly, the observation that the radioactivity has given a clock of world history and open to us the past and how this past forged the present world. Thirdly, the fact that radioactivity gave tracers, markers which allow to sound the internal structure of the human body as well as these one of earth and solar system and to unveil the mechanisms. The fourth consequence, is all the applications, electro-nuclear energy, national defence, nuclear medicine. (N.C.)

  17. Impaired integration of object knowledge and visual input in a case of ventral simultanagnosia with bilateral damage to area V4.

    Science.gov (United States)

    Leek, E Charles; d'Avossa, Giovanni; Tainturier, Marie-Josèphe; Roberts, Daniel J; Yuen, Sung Lai; Hu, Mo; Rafal, Robert

    2012-01-01

    This study examines how brain damage can affect the cognitive processes that support the integration of sensory input and prior knowledge during shape perception. It is based on the first detailed study of acquired ventral simultanagnosia, which was found in a patient (M.T.) with posterior occipitotemporal lesions encompassing V4 bilaterally. Despite showing normal object recognition for single items in both accuracy and response times (RTs), and intact low-level vision assessed across an extensive battery of tests, M.T. was impaired in object identification with overlapping figures displays. Task performance was modulated by familiarity: Unlike controls, M.T. was faster with overlapping displays of abstract shapes than with overlapping displays of common objects. His performance with overlapping common object displays was also influenced by both the semantic relatedness and visual similarity of the display items. These findings challenge claims that visual perception is driven solely by feedforward mechanisms and show how brain damage can selectively impair high-level perceptual processes supporting the integration of stored knowledge and visual sensory input.

  18. On the growth of scientific knowledge: yeast biology as a case study.

    Directory of Open Access Journals (Sweden)

    Xionglei He

    2009-03-01

    Full Text Available The tempo and mode of human knowledge expansion is an enduring yet poorly understood topic. Through a temporal network analysis of three decades of discoveries of protein interactions and genetic interactions in baker's yeast, we show that the growth of scientific knowledge is exponential over time and that important subjects tend to be studied earlier. However, expansions of different domains of knowledge are highly heterogeneous and episodic such that the temporal turnover of knowledge hubs is much greater than expected by chance. Familiar subjects are preferentially studied over new subjects, leading to a reduced pace of innovation. While research is increasingly done in teams, the number of discoveries per researcher is greater in smaller teams. These findings reveal collective human behaviors in scientific research and help design better strategies in future knowledge exploration.

  19. Process Knowledge Discovery Using Sparse Principal Component Analysis

    DEFF Research Database (Denmark)

    Gao, Huihui; Gajjar, Shriram; Kulahci, Murat

    2016-01-01

    As the goals of ensuring process safety and energy efficiency become ever more challenging, engineers increasingly rely on data collected from such processes for informed decision making. During recent decades, extracting and interpreting valuable process information from large historical data sets...... SPCA approach that helps uncover the underlying process knowledge regarding variable relations. This approach systematically determines the optimal sparse loadings for each sparse PC while improving interpretability and minimizing information loss. The salient features of the proposed approach...

  20. Engaging Scientists in Meaningful E/PO: The Universe Discovery Guides

    Science.gov (United States)

    Meinke, B. K.; Lawton, B.; Gurton, S.; Smith, D. A.; Manning, J. G.

    2014-12-01

    For the 2009 International Year of Astronomy, the then-existing NASA Origins Forum collaborated with the Astronomical Society of the Pacific (ASP) to create a series of monthly "Discovery Guides" for informal educator and amateur astronomer use in educating the public about featured sky objects and associated NASA science themes. Today's NASA Astrophysics Science Education and Public Outreach Forum (SEPOF), one of a new generation of forums coordinating the work of NASA Science Mission Directorate (SMD) EPO efforts—in collaboration with the ASP and NASA SMD missions and programs--has adapted the Discovery Guides into "evergreen" educational resources suitable for a variety of audiences. The Guides focus on "deep sky" objects and astrophysics themes (stars and stellar evolution, galaxies and the universe, and exoplanets), showcasing EPO resources from more than 30 NASA astrophysics missions and programs in a coordinated and cohesive "big picture" approach across the electromagnetic spectrum, grounded in best practices to best serve the needs of the target audiences. Each monthly guide features a theme and a representative object well-placed for viewing, with an accompanying interpretive story, finding charts, strategies for conveying the topics, and complementary supporting NASA-approved education activities and background information from a spectrum of NASA missions and programs. The Universe Discovery Guides are downloadable from the NASA Night Sky Network web site at nightsky.jpl.nasa.gov. We will share the Forum-led Collaborative's experience in developing the guides, how they place individual science discoveries and learning resources into context for audiences, and how the Guides can be readily used in scientist public outreach efforts, in college and university introductory astronomy classes, and in other engagements between scientists, students and the public.

  1. Semantic memory in object use.

    Science.gov (United States)

    Silveri, Maria Caterina; Ciccarelli, Nicoletta

    2009-10-01

    We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

  2. Classification and Comparison of Architecture Evolution Reuse Knowledge - A Systematic Review

    DEFF Research Database (Denmark)

    Ahmad, Aakash; Jamshidi, Pooyan; Pahl, Claus

    2014-01-01

    patterns (34% of selected studies) represent a predominant solution, followed by evolution styles (25%) and adaptation strategies and policies (22%) to enable application of reuse knowledge. Empirical methods for acquisition of reuse knowledge represent 19% including pattern discovery, configuration...

  3. A projection and density estimation method for knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Adam Stanski

    Full Text Available A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features.

  4. Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities

    Directory of Open Access Journals (Sweden)

    Yu-Chi Lin

    2011-02-01

    Full Text Available Due to the implicit characteristics of learning disabilities (LDs, the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN and support vector machine (SVM have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST, which can not only perform as a classifier, but may also produce meaningful explanations or rules, to the LD diagnosis application. Our experiments indicate that the RST approach is competitive as a tool for feature selection, and it performs better in term of prediction accuracy than other rulebased algorithms such as decision tree and ripper algorithms. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with simple and readily available clustering algorithms, we are able to improve the quality and support of rules generated by the RST. Overall, our study shows that the rough set approach, as a classification and knowledge discovery tool, may have great potential in playing an essential role in LD diagnosis.

  5. On the Limitations of Biological Knowledge

    Science.gov (United States)

    Dougherty, Edward R; Shmulevich, Ilya

    2012-01-01

    Scientific knowledge is grounded in a particular epistemology and, owing to the requirements of that epistemology, possesses limitations. Some limitations are intrinsic, in the sense that they depend inherently on the nature of scientific knowledge; others are contingent, depending on the present state of knowledge, including technology. Understanding limitations facilitates scientific research because one can then recognize when one is confronted by a limitation, as opposed to simply being unable to solve a problem within the existing bounds of possibility. In the hope that the role of limiting factors can be brought more clearly into focus and discussed, we consider several sources of limitation as they apply to biological knowledge: mathematical complexity, experimental constraints, validation, knowledge discovery, and human intellectual capacity. PMID:23633917

  6. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  7. Astronomers Detect Powerful Bursting Radio Source Discovery Points to New Class of Astronomical Objects

    Science.gov (United States)

    2005-03-01

    Astronomers at Sweet Briar College and the Naval Research Laboratory (NRL) have detected a powerful new bursting radio source whose unique properties suggest the discovery of a new class of astronomical objects. The researchers have monitored the center of the Milky Way Galaxy for several years and reveal their findings in the March 3, 2005 edition of the journal, “Nature”. This radio image of the central region of the Milky Way Galaxy holds a new radio source, GCRT J1745-3009. The arrow points to an expanding ring of debris expelled by a supernova. CREDIT: N.E. Kassim et al., Naval Research Laboratory, NRAO/AUI/NSF Principal investigator, Dr. Scott Hyman, professor of physics at Sweet Briar College, said the discovery came after analyzing some additional observations from 2002 provided by researchers at Northwestern University. “"We hit the jackpot!” Hyman said referring to the observations. “An image of the Galactic center, made by collecting radio waves of about 1-meter in wavelength, revealed multiple bursts from the source during a seven-hour period from Sept. 30 to Oct. 1, 2002 — five bursts in fact, and repeating at remarkably constant intervals.” Hyman, four Sweet Briar students, and his NRL collaborators, Drs. Namir Kassim and Joseph Lazio, happened upon transient emission from two radio sources while studying the Galactic center in 1998. This prompted the team to propose an ongoing monitoring program using the National Science Foundation’s Very Large Array (VLA) radio telescope in New Mexico. The National Radio Astronomy Observatory, which operates the VLA, approved the program. The data collected, laid the groundwork for the detection of the new radio source. “Amazingly, even though the sky is known to be full of transient objects emitting at X- and gamma-ray wavelengths,” NRL astronomer Dr. Joseph Lazio pointed out, “very little has been done to look for radio bursts, which are often easier for astronomical objects to produce

  8. Topology Discovery Using Cisco Discovery Protocol

    OpenAIRE

    Rodriguez, Sergio R.

    2009-01-01

    In this paper we address the problem of discovering network topology in proprietary networks. Namely, we investigate topology discovery in Cisco-based networks. Cisco devices run Cisco Discovery Protocol (CDP) which holds information about these devices. We first compare properties of topologies that can be obtained from networks deploying CDP versus Spanning Tree Protocol (STP) and Management Information Base (MIB) Forwarding Database (FDB). Then we describe a method of discovering topology ...

  9. Mining knowledge from text repositories using information extraction ...

    Indian Academy of Sciences (India)

    Information extraction (IE); text mining; text repositories; knowledge discovery from .... general purpose English words. However ... of precision and recall, as extensive experimentation is required due to lack of public tagged corpora. 4. Mining ...

  10. 41. DISCOVERY, SEARCH, AND COMMUNICATION OF TEXTUAL KNOWLEDGE RESOURCES IN DISTRIBUTED SYSTEMS a. Discovering and Utilizing Knowledge Sources for Metasearch Knowledge Systems

    Energy Technology Data Exchange (ETDEWEB)

    Zamora, Antonio

    2008-03-18

    Advanced Natural Language Processing Tools for Web Information Retrieval, Content Analysis, and Synthesis. The goal of this SBIR was to implement and evaluate several advanced Natural Language Processing (NLP) tools and techniques to enhance the precision and relevance of search results by analyzing and augmenting search queries and by helping to organize the search output obtained from heterogeneous databases and web pages containing textual information of interest to DOE and the scientific-technical user communities in general. The SBIR investigated 1) the incorporation of spelling checkers in search applications, 2) identification of significant phrases and concepts using a combination of linguistic and statistical techniques, and 3) enhancement of the query interface and search retrieval results through the use of semantic resources, such as thesauri. A search program with a flexible query interface was developed to search reference databases with the objective of enhancing search results from web queries or queries of specialized search systems such as DOE's Information Bridge. The DOE ETDE/INIS Joint Thesaurus was processed to create a searchable database. Term frequencies and term co-occurrences were used to enhance the web information retrieval by providing algorithmically-derived objective criteria to organize relevant documents into clusters containing significant terms. A thesaurus provides an authoritative overview and classification of a field of knowledge. By organizing the results of a search using the thesaurus terminology, the output is more meaningful than when the results are just organized based on the terms that co-occur in the retrieved documents, some of which may not be significant. An attempt was made to take advantage of the hierarchy provided by broader and narrower terms, as well as other field-specific information in the thesauri. The search program uses linguistic morphological routines to find relevant entries regardless of

  11. THE METHDOLOGICAL WAYS OF FORM OF THE KNOWLEDGE BASE OF THE AUTOMATIC SYSTEM DIAGNOSTICS OF THE COMPLEX AIRCRAFT OBJECT

    Directory of Open Access Journals (Sweden)

    Ю. Чоха

    2012-04-01

    Full Text Available Development of the Systems provides reception of the multitude of information and improvement of theiranalysis for diagnostics of aviation techniques. However theoretical bases deficiently are motivated forstructure and analysis of information. On modern stage of evolution of the artificial intelligence the trend istracked the outrun of technological (practical of the facilities of the development of the intellectual systemscomparatively their theoretical developments. In this connection in article the idea is emphasized thatclassical approaches to the analytical bases of the cybernetics have grown old. Accordingly by the base forensuring of functioning of the automatic diagnostics systems requisite to consider the ways (the strategies ofdecompositions and creature structure of the knowledge base in relation to of the concrete aviation object.However use of the syntheses of the deductive and of inductive strategy shaping the structure of theknowledge’s can be insufficient in some cases of making of the diagnostics system of the complex object ofthe aviation techniques with depth diagnosis at the constructive node. For this case on each of levels ofstructurization of the knowledge base, authors offer to apply also strategy of parallel (horizontaldecomposition of object of diagnosing concerning its behaviour at transition from one stationary operationalregimen on another. As a base paradigm of methodology of the structural analysis and formation of a field ofknowledge by authors are proffered to use generalised objective - the structural approach, which developedto technological and program realisation.

  12. Managing knowledge management

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    ) and colleagues, who stresses that to understand knowledge management practices we need to magnify the space of knowledge in action and consider the presentation and circulation of epistemic objects in extended contexts. In other words, we need to consider that the routes from research to practice......The work-in-progress that I would like to present and discuss in the workshop focuses on the management of knowledge management and its socio-material implications. More specifically, my work focuses on how epistemic objects and objectives are managed in professional health care organisations. One...... of the characteristics of professional health care today is that knowledge is generated from a multitude of sources and circulated rapidly across organizational boundaries. This derives not only from a growth in knowledge production within many organizations, but also from the emergence of agencies that specialize...

  13. Enhancing knowledge discovery from cancer genomics data with Galaxy.

    Science.gov (United States)

    Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

    2017-05-01

    The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

  14. Empirical study using network of semantically related associations in bridging the knowledge gap.

    Science.gov (United States)

    Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

    2014-11-27

    The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

  15. Discovery Mondays - The detectors: tracking particles

    CERN Multimedia

    2005-01-01

    View of a module from the LHCb vertex detector, which will be presented at the next Discovery Monday. How do you observe the invisible? In order to deepen still further our knowledge of the infinitely small, physicists accelerate beams of particles and generate collisions between them at extraordinary energies. The collisions give birth to showers of new particles. What are they? In order to find out, physicists slip into the role of detectives thanks to the detectors. At the next Discovery Monday you will find out about the different methods used at CERN to detect particles. A cloud chamber will allow you to see the tracks of cosmic particles live. You will also be given the chance to see real modules for the ATLAS and for the LHCb experiments. Strange materials will be on hand, such as crystals that are heavier than iron and yet as transparent as glass... Come to the Microcosm and become a top detective yourself! This event will take place in French. Join us at the Microcosm (Reception Building 33, M...

  16. Discovery Mondays - The detectors: tracking particles

    CERN Multimedia

    2005-01-01

    View of a module from the LHCb vertex detector, which will be presented at the next Discovery Monday. How do you observe the invisible? In order to deepen still further our knowledge of the infinitely small, physicists accelerate beams of particles at close to the speed of light, then generate collisions between them at extraordinary energies, giving birth to showers of new particles. What are these particles? In order to find out, physicists transform themselves into detectives with the help of the detectors. Located around the collision area, these exceptional machines are made up of various layers, each of which detects and measures specific properties of the particles that travel through them. Powerful computers then reconstruct their trajectory and record their charge, mass and energy in order to build up a kind of particle ID card. At the next Discovery Monday you will be able to find out about the different methods used at CERN to detect particles. A cloud chamber will provide live images of the trac...

  17. Business Model Discovery by Technology Entrepreneurs

    Directory of Open Access Journals (Sweden)

    Steven Muegge

    2012-04-01

    Full Text Available Value creation and value capture are central to technology entrepreneurship. The ways in which a particular firm creates and captures value are the foundation of that firm's business model, which is an explanation of how the business delivers value to a set of customers at attractive profits. Despite the deep conceptual link between business models and technology entrepreneurship, little is known about the processes by which technology entrepreneurs produce successful business models. This article makes three contributions to partially address this knowledge gap. First, it argues that business model discovery by technology entrepreneurs can be, and often should be, disciplined by both intention and structure. Second, it provides a tool for disciplined business model discovery that includes an actionable process and a worksheet for describing a business model in a form that is both concise and explicit. Third, it shares preliminary results and lessons learned from six technology entrepreneurs applying a disciplined process to strengthen or reinvent the business models of their own nascent technology businesses.

  18. Designing discovery learning environments: process analysis and implications for designing an information system

    NARCIS (Netherlands)

    Pieters, Julius Marie; Limbach, R.; de Jong, Anthonius J.M.

    2004-01-01

    A systematic analysis of the design process of authors of (simulation based) discovery learning environments was carried out. The analysis aimed at identifying the design activities of authors and categorising knowledge gaps that they experience. First, five existing studies were systematically

  19. Augmented Reality-Based Simulators as Discovery Learning Tools: An Empirical Study

    Science.gov (United States)

    Ibáñez, María-Blanca; Di-Serio, Ángela; Villarán-Molina, Diego; Delgado-Kloos, Carlos

    2015-01-01

    This paper reports empirical evidence on having students use AR-SaBEr, a simulation tool based on augmented reality (AR), to discover the basic principles of electricity through a series of experiments. AR-SaBEr was enhanced with knowledge-based support and inquiry-based scaffolding mechanisms, which proved useful for discovery learning in…

  20. Knowledge ecologies, "supple" objects, and different priorities across women's and gender studies programs and departments in the United States, 1970-2010.

    Science.gov (United States)

    Wood, Christine Virginia

    2015-01-01

    This article examines the evolving connections between local conditions and knowledge processes in women's and gender studies, a research field in the social sciences and humanities. Data are historical records from five early-adopting women's and gender studies units in the United States and interviews with affiliated professors. In their formative years, these programs were consistent in their intellectual content. Scholars across sites defined the purpose of women's studies similarly: to address the lack of research on women and social problems of sex inequality. Gradually, scholars incorporated a range of analytic categories into women's studies' agenda, including gender identities and masculinities, leading to diverse understandings and redefinitions of the central objects of analysis. Analytic shifts are reflected in differences in the institutional and intellectual composition of programs and departments. To explain how local departmental conditions affect the conception of core objects of study in gender research, the author builds on the literature on knowledge ecologies and introduces the concept of the "supple object." © 2015 Wiley Periodicals, Inc.

  1. 14 CFR 406.143 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  2. OntoWeaver S: supporting the design of knowledge portals

    OpenAIRE

    Lei, Yuangui; Motta, Enrico; Domingue, John

    2004-01-01

    This paper presents OntoWeaver-S, an ontology-based infrastructure for building knowledge portals. In particular, OntoWeaver-S is integrated with a comprehensive web service platform, IRS-II, for the publication, discovery, and execution of web services. In this way, OntoWeaver-S supports the access and provision of remote web services for knowledge portals. Moreover, it provides a set of comprehensive site ontologies to model and represent knowledge portals, and thus is able to offer high le...

  3. Pacific Research Platform - Creation of a West Coast Big Data Freeway System Applied to the CONNected objECT (CONNECT) Data Mining Framework for Earth Science Knowledge Discovery

    Science.gov (United States)

    Sellars, S. L.; Nguyen, P.; Tatar, J.; Graham, J.; Kawsenuk, B.; DeFanti, T.; Smarr, L.; Sorooshian, S.; Ralph, M.

    2017-12-01

    A new era in computational earth sciences is within our grasps with the availability of ever-increasing earth observational data, enhanced computational capabilities, and innovative computation approaches that allow for the assimilation, analysis and ability to model the complex earth science phenomena. The Pacific Research Platform (PRP), CENIC and associated technologies such as the Flash I/O Network Appliance (FIONA) provide scientists a unique capability for advancing towards this new era. This presentation reports on the development of multi-institutional rapid data access capabilities and data pipeline for applying a novel image characterization and segmentation approach, CONNected objECT (CONNECT) algorithm to study Atmospheric River (AR) events impacting the Western United States. ARs are often associated with torrential rains, swollen rivers, flash flooding, and mudslides. CONNECT is computationally intensive, reliant on very large data transfers, storage and data mining techniques. The ability to apply the method to multiple variables and datasets located at different University of California campuses has previously been challenged by inadequate network bandwidth and computational constraints. The presentation will highlight how the inter-campus CONNECT data mining framework improved from our prior download speeds of 10MB/s to 500MB/s using the PRP and the FIONAs. We present a worked example using the NASA MERRA data to describe how the PRP and FIONA have provided researchers with the capability for advancing knowledge about ARs. Finally, we will discuss future efforts to expand the scope to additional variables in earth sciences.

  4. Higgs Discovery

    DEFF Research Database (Denmark)

    Sannino, Francesco

    2013-01-01

    has been challenged by the discovery of a not-so-heavy Higgs-like state. I will therefore review the recent discovery \\cite{Foadi:2012bb} that the standard model top-induced radiative corrections naturally reduce the intrinsic non-perturbative mass of the composite Higgs state towards the desired...... via first principle lattice simulations with encouraging results. The new findings show that the recent naive claims made about new strong dynamics at the electroweak scale being disfavoured by the discovery of a not-so-heavy composite Higgs are unwarranted. I will then introduce the more speculative......I discuss the impact of the discovery of a Higgs-like state on composite dynamics starting by critically examining the reasons in favour of either an elementary or composite nature of this state. Accepting the standard model interpretation I re-address the standard model vacuum stability within...

  5. Integrated approach to e-learning enhanced both subjective and objective knowledge of aEEG in a neonatal intensive care unit.

    Science.gov (United States)

    Poon, W B; Tagamolila, V; Toh, Y P; Cheng, Z R

    2015-03-01

    Various meta-analyses have shown that e-learning is as effective as traditional methods of continuing professional education. However, there are some disadvantages to e-learning, such as possible technical problems, the need for greater self-discipline, cost involved in developing programmes and limited direct interaction. Currently, most strategies for teaching amplitude-integrated electroencephalography (aEEG) in neonatal intensive care units (NICUs) worldwide depend on traditional teaching methods. We implemented a programme that utilised an integrated approach to e-learning. The programme consisted of three sessions of supervised protected time e-learning in an NICU. The objective and subjective effectiveness of the approach was assessed through surveys administered to participants before and after the programme. A total of 37 NICU staff (32 nurses and 5 doctors) participated in the study. 93.1% of the participants appreciated the need to acquire knowledge of aEEG. We also saw a statistically significant improvement in the subjective knowledge score (p = 0.041) of the participants. The passing rates for identifying abnormal aEEG tracings (defined as ≥ 3 correct answers out of 5) also showed a statistically significant improvement (from 13.6% to 81.8%, p e-learning can help improve subjective and objective knowledge of aEEG.

  6. Knowledge Exchange and Management Research

    DEFF Research Database (Denmark)

    Bager, Torben

    2018-01-01

    for ‘interesting’ discoveries has a potential to lift off papers with a high level of scientific rigor as well as a high level of relevance for practice. Originality: An outcome focus on the relationship between knowledge exchange activities and management research is to our knowledge new in the debate about......Purpose: The growing involvement of management researchers in knowledge exchange activities and collaborative research does not seem to be reflected in a growing academic output. The purpose of this paper is to explore barriers for academic output from these activities as well as the potential...... derived from knowledge exchange activities and Mode 2 research into academic papers such as low priority of case study research in leading management journals, a growing practice orientation in the research funding systems, methodological challenges due to limited researcher control, and disincentives...

  7. A knowledge base architecture for distributed knowledge agents

    Science.gov (United States)

    Riedesel, Joel; Walls, Bryan

    1990-01-01

    A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

  8. Conhecimento objetivo e percebido sobre contraceptivos hormonais orais entre adolescentes com antecedentes gestacionais Objective and perceived knowledge of oral contraceptive methods among adolescent mothers

    Directory of Open Access Journals (Sweden)

    Michelle Chintia Rodrigues de Sousa

    2009-03-01

    Full Text Available A elevada freqüência de gestação precoce no Brasil e, particularmente, em Teresina (21,5%, Piauí, motivou o presente estudo, cuja meta foi identificar os níveis de conhecimento objetivo e percebido sobre contraceptivos hormonais orais, bem como variáveis reprodutivas e sócio-demográficas preditoras de elevado conhecimento. Realizou-se estudo transversal com 278 adolescentes com idade de 15 a 19 anos de idade, com antecedentes reprodutivos, internadas em quatro maternidades de Teresina, em 2006. Regressão logística foi a base da análise estatística. Quase 98% das adolescentes apresentaram baixo conhecimento tanto objetivo quanto percebido. Apenas o maior número de gestações foi preditor de elevado conhecimento objetivo para anticoncepcionais orais. Os baixos níveis de conhecimento objetivo e percebido das adolescentes sobre o uso de anticoncepcionais orais revelam a suscetibilidade das jovens ao comportamento sexual de risco. Sugere-se a utilização de abordagem mais interativa com os adolescentes para elevar o nível de conhecimento tanto objetivo quanto percebido deles, e assim reduzir a incidência e reincidência da gravidez indesejada na adolescência e suas conseqüências negativas na vida destas jovens e de sua prole.The high rate of early pregnancy in Brazil and particularly in Teresina (21.5%, Piauí State, motivated the current study, the aim of which was to identify levels of objective and perceived knowledge on oral contraceptives, as well as predictive reproductive and socio-demographic variables for high knowledge. A cross-sectional study was performed including 278 teenage mothers (15-19 years, with their childbearing history, admitted to four maternity hospitals in Teresina in 2006. Logistic regression provided the basis for the statistical analysis. Nearly 98% of the adolescent mothers showed low objective and perceived knowledge of oral contraceptives. High parity was the only predictor of increased objective

  9. "Structured Discovery": A Modified Inquiry Approach to Teaching Social Studies.

    Science.gov (United States)

    Lordon, John

    1981-01-01

    Describes structured discovery approach to inquiry teaching which encourages the teacher to select instructional objectives, content, and questions to be answered. The focus is on individual and group activities. A brief outline using this approach to analyze Adolf Hitler is presented. (KC)

  10. The discovery of the periodic table as a case of simultaneous discovery.

    Science.gov (United States)

    Scerri, Eric

    2015-03-13

    The article examines the question of priority and simultaneous discovery in the context of the discovery of the periodic system. It is argued that rather than being anomalous, simultaneous discovery is the rule. Moreover, I argue that the discovery of the periodic system by at least six authors in over a period of 7 years represents one of the best examples of a multiple discovery. This notion is supported by a new view of the evolutionary development of science through a mechanism that is dubbed Sci-Gaia by analogy with Lovelock's Gaia hypothesis. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  11. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2017-01-01

    In this chapter we explore four alternatives to the dominant discovery view of entrepreneurship; the development view, the construction view, the evolutionary view, and the Neo-Austrian view. We outline the main critique points of the discovery presented in these four alternatives, as well...

  12. Knowledge Factors and Their Impact on the Organisation

    Directory of Open Access Journals (Sweden)

    Domen Kozjek

    2016-12-01

    Full Text Available Research Question (RQ: The research question is whether managers in organisations recognize the benefits of knowledge management. Purpose: The purpose of this research is to identify the factors of knowledge which have a significant impact on the organisation. Method: We reviewed the relevant literature in the field of knowledge management. On this basis, we summarized the factors of knowledge. We performed a survey among the 69 biggest Slovenian commercial companies (public and banking sectors were excluded. Results: Research has shown that managers recognize the positive effects of knowledge. Factor analysis, with the discovery of latent variables, additionally confirmed already established facts from the research literature. This led us to the discovery that knowledge is the common denominator of all companies, regardless of the business in which they operate. Organisation: From the examined literature, we can conclude that knowledge management has a positive impact on the company's results. Identification of knowledge factors allows a more efficient use of company’s resources and enables further development of the organisation. Society: Knowledge has become a highly appreciated "resource", therefore it is necessary to be able to manage it. Knowledge is the foundation of progress, not only for the development of the company but for the entire civilization. Originality: We see the original contribution in the identification of dilemmas in building connections between knowledge management and the company's success. Limitations / further research: The research matter is extremely difficult because the evidence that knowledge is the most influencing matter of a company’s success can not be easily confirmed. The connection (we remain inside the topic of human capital between knowledge and company's result is also manifested with other elements of the business, such as organisational culture, public relations, etc. Additional question is

  13. "Eureka, Eureka!" Discoveries in Science

    Science.gov (United States)

    Agarwal, Pankaj

    2011-01-01

    Accidental discoveries have been of significant value in the progress of science. Although accidental discoveries are more common in pharmacology and chemistry, other branches of science have also benefited from such discoveries. While most discoveries are the result of persistent research, famous accidental discoveries provide a fascinating…

  14. Operational knowledge management: identification of knowledge objects, operation methods, and goals and means for the support function

    NARCIS (Netherlands)

    Wijnhoven, Alphonsus B.J.M.

    2003-01-01

    Though much has been written about knowledge management, this field has not been described extensively from an operational management perspective. Consequently, knowledge management seems difficult to implement at the operational levels of the organisations. To solve this problem, the abstract

  15. 30 CFR 44.24 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  16. 19 CFR 356.20 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  17. Chemical Discovery

    Science.gov (United States)

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  18. 24 CFR 180.500 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  19. 22 CFR 224.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  20. The Prehistory of Discovery: Precursors of Representational Change in Solving Gear System Problems.

    Science.gov (United States)

    Dixon, James A.; Bangert, Ashley S.

    2002-01-01

    This study investigated whether the process of representational change undergoes developmental change or different processes occupy different niches in the course of knowledge acquisition. Subjects--college, third-, and sixth-grade students--solved gear system problems over two sessions. Findings indicated that for all grades, discovery of the…

  1. 19 CFR 207.109 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  2. 15 CFR 25.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  3. Development of Object and Grasping Knowledge by Robot Exploration

    DEFF Research Database (Denmark)

    Kraft, Dirk; Detry, Renaud; Pugeault, Nicolas

    2010-01-01

    We describe a bootstrapping cognitive robot system that—mainly based on pure exploration—acquires rich object representations and associated object-specific grasp affordances. Such bootstrapping becomes possible by combining innate competences and behaviours by which the system gradually enriches...

  4. 39 CFR 963.14 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  5. Discovery of convoys in trajectory databases

    DEFF Research Database (Denmark)

    Jeung, Hoyoung; Yiu, Man Lung; Zhou, Xiaofang

    2008-01-01

    a group of objects that have traveled together for some time. More specifically, this paper formalizes the concept of a convoy query using density-based notions, in order to capture groups of arbitrary extents and shapes. Convoy discovery is relevant for real-life applications in throughput planning...... convoys are further processed to obtain the actual convoys. Our comprehensive empirical study offers insight into the properties of the paper's proposals and demonstrates that the proposals are effective and efficient on real-world trajectory data....

  6. Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

    International Nuclear Information System (INIS)

    Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

    2008-01-01

    Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. This work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic

  7. Leveraging ecological theory to guide natural product discovery.

    Science.gov (United States)

    Smanski, Michael J; Schlatter, Daniel C; Kinkel, Linda L

    2016-03-01

    Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery.

  8. Equation Discovery for Model Identification in Respiratory Mechanics of the Mechanically Ventilated Human Lung

    Science.gov (United States)

    Ganzert, Steven; Guttmann, Josef; Steinmann, Daniel; Kramer, Stefan

    Lung protective ventilation strategies reduce the risk of ventilator associated lung injury. To develop such strategies, knowledge about mechanical properties of the mechanically ventilated human lung is essential. This study was designed to develop an equation discovery system to identify mathematical models of the respiratory system in time-series data obtained from mechanically ventilated patients. Two techniques were combined: (i) the usage of declarative bias to reduce search space complexity and inherently providing the processing of background knowledge. (ii) A newly developed heuristic for traversing the hypothesis space with a greedy, randomized strategy analogical to the GSAT algorithm. In 96.8% of all runs the applied equation discovery system was capable to detect the well-established equation of motion model of the respiratory system in the provided data. We see the potential of this semi-automatic approach to detect more complex mathematical descriptions of the respiratory system from respiratory data.

  9. Data Linkage Graph: computation, querying and knowledge discovery of life science database networks

    Directory of Open Access Journals (Sweden)

    Lange Matthias

    2007-12-01

    Full Text Available To support the interpretation of measured molecular facts, like gene expression experiments or EST sequencing, the functional or the system biological context has to be considered. Doing so, the relationship to existing biological knowledge has to be discovered. In general, biological knowledge is worldwide represented in a network of databases. In this paper we present a method for knowledge extraction in life science databases, which prevents the scientists from screen scraping and web clicking approaches.

  10. Beyond the International Year of Astronomy: The Universe Discovery Guides

    Science.gov (United States)

    Lawton, B.; Berendsen, M.; Gurton, S.; Smith, D.; NASA SMD Astrophysics EPO Community

    2014-07-01

    Developed for informal educators and their audiences, the 12 Universe Discovery Guides (UDGs, one per month) are adapted from the Discovery Guides that were developed for the International Year of Astronomy in 2009. The UDGs showcase education and public outreach resources from across more than 30 NASA astrophysics missions and programs. Via collaboration through scientist and educator partnerships, the UDGs aim to increase the impact of individual missions and programs, put their efforts into context, and extend their reach to new audiences. Each of the UDGs has a science topic, an interpretive story, a sky object to view with finding charts, hands-on activities, and connections to recent NASA science discoveries. The UDGs are modular; informal educators can take resources from the guides that they find most useful for their audiences. Attention is being given to audience needs, and field-testing is ongoing. The UDGs are available via downloadable PDFs.

  11. Making the Long Tail Visible: Social Networking Sites and Independent Music Discovery

    Science.gov (United States)

    Gaffney, Michael; Rafferty, Pauline

    2009-01-01

    Purpose: The purpose of this paper is to investigate users' knowledge and use of social networking sites and folksonomies to discover if social tagging and folksonomies, within the area of independent music, aid in its information retrieval and discovery. The sites examined in this project are MySpace, Lastfm, Pandora and Allmusic. In addition,…

  12. NASA Reverb: Standards-Driven Earth Science Data and Service Discovery

    Science.gov (United States)

    Cechini, M. F.; Mitchell, A.; Pilone, D.

    2011-12-01

    NASA's Earth Observing System Data and Information System (EOSDIS) is a core capability in NASA's Earth Science Data Systems Program. NASA's EOS ClearingHOuse (ECHO) is a metadata catalog for the EOSDIS, providing a centralized catalog of data products and registry of related data services. Working closely with the EOSDIS community, the ECHO team identified a need to develop the next generation EOS data and service discovery tool. This development effort relied on the following principles: + Metadata Driven User Interface - Users should be presented with data and service discovery capabilities based on dynamic processing of metadata describing the targeted data. + Integrated Data & Service Discovery - Users should be able to discovery data and associated data services that facilitate their research objectives. + Leverage Common Standards - Users should be able to discover and invoke services that utilize common interface standards. Metadata plays a vital role facilitating data discovery and access. As data providers enhance their metadata, more advanced search capabilities become available enriching a user's search experience. Maturing metadata formats such as ISO 19115 provide the necessary depth of metadata that facilitates advanced data discovery capabilities. Data discovery and access is not limited to simply the retrieval of data granules, but is growing into the more complex discovery of data services. These services include, but are not limited to, services facilitating additional data discovery, subsetting, reformatting, and re-projecting. The discovery and invocation of these data services is made significantly simpler through the use of consistent and interoperable standards. By utilizing an adopted standard, developing standard-specific adapters can be utilized to communicate with multiple services implementing a specific protocol. The emergence of metadata standards such as ISO 19119 plays a similarly important role in discovery as the 19115 standard

  13. View Discovery in OLAP Databases through Statistical Combinatorial Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Burke, Edward J.; Critchlow, Terence J.

    2009-05-01

    The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of ``views'' of an OLAP database as a combinatorial object of all projections and subsets, and ``view discovery'' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline ``hop-chaining'' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a ``spiraling'' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.

  14. Polar Domain Discovery with Sparkler

    Science.gov (United States)

    Duerr, R.; Khalsa, S. J. S.; Mattmann, C. A.; Ottilingam, N. K.; Singh, K.; Lopez, L. A.

    2017-12-01

    The scientific web is vast and ever growing. It encompasses millions of textual, scientific and multimedia documents describing research in a multitude of scientific streams. Most of these documents are hidden behind forms which require user action to retrieve and thus can't be directly accessed by content crawlers. These documents are hosted on web servers across the world, most often on outdated hardware and network infrastructure. Hence it is difficult and time-consuming to aggregate documents from the scientific web, especially those relevant to a specific domain. Thus generating meaningful domain-specific insights is currently difficult. We present an automated discovery system (Figure 1) using Sparkler, an open-source, extensible, horizontally scalable crawler which facilitates high throughput and focused crawling of documents pertinent to a particular domain such as information about polar regions. With this set of highly domain relevant documents, we show that it is possible to answer analytical questions about that domain. Our domain discovery algorithm leverages prior domain knowledge to reach out to commercial/scientific search engines to generate seed URLs. Subject matter experts then annotate these seed URLs manually on a scale from highly relevant to irrelevant. We leverage this annotated dataset to train a machine learning model which predicts the `domain relevance' of a given document. We extend Sparkler with this model to focus crawling on documents relevant to that domain. Sparkler avoids disruption of service by 1) partitioning URLs by hostname such that every node gets a different host to crawl and by 2) inserting delays between subsequent requests. With an NSF-funded supercomputer Wrangler, we scaled our domain discovery pipeline to crawl about 200k polar specific documents from the scientific web, within a day.

  15. Drawbacks and benefits associated with inter-organizational collaboration along the discovery-development-delivery continuum: a cancer research network case study.

    Science.gov (United States)

    Harris, Jenine K; Provan, Keith G; Johnson, Kimberly J; Leischow, Scott J

    2012-07-25

    The scientific process around cancer research begins with scientific discovery, followed by development of interventions, and finally delivery of needed interventions to people with cancer. Numerous studies have identified substantial gaps between discovery and delivery in health research. Team science has been identified as a possible solution for closing the discovery to delivery gap; however, little is known about effective ways of collaborating within teams and across organizations. The purpose of this study was to determine benefits and drawbacks associated with organizational collaboration across the discovery-development-delivery research continuum. Representatives of organizations working on cancer research across a state answered a survey about how they collaborated with other cancer research organizations in the state and what benefits and drawbacks they experienced while collaborating. We used exponential random graph modeling to determine the association between these benefits and drawbacks and the presence of a collaboration tie between any two network members. Different drawbacks and benefits were associated with discovery, development, and delivery collaborations. The only consistent association across all three was with the drawback of difficulty due to geographic differences, which was negatively associated with collaboration, indicating that those organizations that had collaborated were less likely to perceive a barrier related to geography. The benefit, enhanced access to other knowledge, was positive and significant in the development and delivery networks, indicating that collaborating organizations viewed improved knowledge exchange as a benefit of collaboration. 'Acquisition of additional funding or other resources' and 'development of new tools and methods' were negatively significantly related to collaboration in these networks. So, although improved knowledge access was an outcome of collaboration, more tangible outcomes were not being

  16. The history of aerobic ammonia oxidizers: from the first discoveries to today.

    Science.gov (United States)

    Monteiro, Maria; Séneca, Joana; Magalhães, Catarina

    2014-07-01

    Nitrification, the oxidation of ammonia to nitrite and nitrate, has long been considered a central biological process in the global nitrogen cycle, with its first description dated 133 years ago. Until 2005, bacteria were considered the only organisms capable of nitrification. However, the recent discovery of a chemoautotrophic ammonia-oxidizing archaeon, Nitrosopumilus maritimus, changed our concept of the range of organisms involved in nitrification, highlighting the importance of ammonia-oxidizing archaea (AOA) as potential players in global biogeochemical nitrogen transformations. The uniqueness of these archaea justified the creation of a novel archaeal phylum, Thaumarchaeota. These recent discoveries increased the global scientific interest within the microbial ecology society and have triggered an analysis of the importance of bacterial vs archaeal ammonia oxidation in a wide range of natural ecosystems. In this mini review we provide a chronological perspective of the current knowledge on the ammonia oxidation pathway of nitrification, based on the main physiological, ecological and genomic discoveries.

  17. The Universe Discovery Guides: A Collaborative Approach to Educating with NASA Science

    Science.gov (United States)

    Manning, James G.; Lawton, Brandon L.; Gurton, Suzanne; Smith, Denise Anne; Schultz, Gregory; Astrophysics Community, NASA

    2015-08-01

    For the 2009 International Year of Astronomy, the then-existing NASA Origins Forum collaborated with the Astronomical Society of the Pacific (ASP) to create a series of monthly “Discovery Guides” for informal educator and amateur astronomer use in educating the public about featured sky objects and associated NASA science themes. Today’s NASA Astrophysics Science Education and Public Outreach Forum (SEPOF), one of the current generation of forums coordinating the work of NASA Science Mission Directorate (SMD) EPO efforts—in collaboration with the ASP and NASA SMD missions and programs--has adapted the Discovery Guides into “evergreen” educational resources suitable for a variety of audiences. The Guides focus on “deep sky” objects and astrophysics themes (stars and stellar evolution, galaxies and the universe, and exoplanets), showcasing EPO resources from more than 30 NASA astrophysics missions and programs in a coordinated and cohesive “big picture” approach across the electromagnetic spectrum, grounded in best practices to best serve the needs of the target audiences.Each monthly guide features a theme and a representative object well-placed for viewing, with an accompanying interpretive story, finding charts, strategies for conveying the topics, and complementary supporting NASA-approved education activities and background information from a spectrum of NASA missions and programs. The Universe Discovery Guides are downloadable from the NASA Night Sky Network web site at nightsky.jpl.nasa.gov and specifically from http://nightsky.jpl.nasa.gov/news-display.cfm?News_ID=611.The presentation will describe the collaborative’s experience in developing the guides, how they place individual science discoveries and learning resources into context for audiences, and how the Guides can be readily used in scientist public outreach efforts, in college and university introductory astronomy classes, and in other engagements between scientists, instructors

  18. Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

    Science.gov (United States)

    Emond, Bruno; Buffett, Scott

    2015-01-01

    This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

  19. Logical knowledge representation of regulatory relations in biomedical pathways

    DEFF Research Database (Denmark)

    Zambach, Sine; Hansen, Jens Ulrik

    2010-01-01

    Knowledge on regulatory relations, in for example regulatory pathways in biology, is used widely in experiment design by biomedical researchers and in systems biology. The knowledge has typically either been represented through simple graphs or through very expressive differential equation...... simulations of smaller parts of a pathway. In this work we suggest a knowledge representation of the most basic relations in regulatory processes regulates, positively regulates and negatively regulates in logics based on a semantic analysis. We discuss the usage of these relations in biology and in articial...... intelligence for hypothesis development in drug discovery....

  20. Performance Evaluation of Frequent Subgraph Discovery Techniques

    Directory of Open Access Journals (Sweden)

    Saif Ur Rehman

    2014-01-01

    Full Text Available Due to rapid development of the Internet technology and new scientific advances, the number of applications that model the data as graphs increases, because graphs have highly expressive power to model a complicated structure. Graph mining is a well-explored area of research which is gaining popularity in the data mining community. A graph is a general model to represent data and has been used in many domains such as cheminformatics, web information management system, computer network, and bioinformatics, to name a few. In graph mining the frequent subgraph discovery is a challenging task. Frequent subgraph mining is concerned with discovery of those subgraphs from graph dataset which have frequent or multiple instances within the given graph dataset. In the literature a large number of frequent subgraph mining algorithms have been proposed; these included FSG, AGM, gSpan, CloseGraph, SPIN, Gaston, and Mofa. The objective of this research work is to perform quantitative comparison of the above listed techniques. The performances of these techniques have been evaluated through a number of experiments based on three different state-of-the-art graph datasets. This novel work will provide base for anyone who is working to design a new frequent subgraph discovery technique.

  1. Insect-Specific Virus Discovery: Significance for the Arbovirus Community

    Directory of Open Access Journals (Sweden)

    Bethany G. Bolling

    2015-09-01

    Full Text Available Arthropod-borne viruses (arboviruses, especially those transmitted by mosquitoes, are a significant cause of morbidity and mortality in humans and animals worldwide. Recent discoveries indicate that mosquitoes are naturally infected with a wide range of other viruses, many within taxa occupied by arboviruses that are considered insect-specific. Over the past ten years there has been a dramatic increase in the literature describing novel insect-specific virus detection in mosquitoes, which has provided new insights about viral diversity and evolution, including that of arboviruses. It has also raised questions about what effects the mosquito virome has on arbovirus transmission. Additionally, the discovery of these new viruses has generated interest in their potential use as biological control agents as well as novel vaccine platforms. The arbovirus community will benefit from the growing database of knowledge concerning these newly described viral endosymbionts, as their impacts will likely be far reaching.

  2. Teaching object concepts for XML-based representations.

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R. L. (Robert L.)

    2002-01-01

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

  3. Neptune's Discovery: Le Verrier, Adams, and the Assignment of Credit

    Science.gov (United States)

    Sheehan, William

    2011-01-01

    As one of the most significant achievements of 19th century astronomy, the discovery of Neptune has been the subject of a vast literature. A large part of this literature--beginning with the period immediately after the optical discovery in Berlin--has been the obsession with assigning credit to the two men who attempted to calculate the planet's position (and initially this played out against the international rivalry between France and England). Le Verrier and Adams occupied much different positions in the Scientific Establishments of their respective countries; had markedly different personalities; and approached the investigation using different methods. A psychiatrist and historian of astronomy tries to provide some new contexts to the familiar story of the discovery of Neptune, and argues that the personalities of these two men played crucial roles in their approaches to the problem they set themselves and the way others reacted to their stimuli. Adams had features of high-functioning autism, while Le Verrier's domineering, obsessive, orderly personality--though it allowed him to be immensely productive--eventually led to serious difficulties with his peers (and an outright revolt). Though it took extraordinary smarts to calculate the position of Neptune, the discovery required social skills that these men lacked--and thus the process to discovery was more bumbling and adventitious than it might have been. The discovery of Neptune occurred at a moment when astronomy was changing from that of heroic individuals to team collaborations involving multiple experts, and remains an object lesson in the sociological aspects of scientific endeavor.

  4. 19 CFR 354.10 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  5. 36 CFR 1150.63 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  6. 37 CFR 11.52 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  7. An object memory bias induced by communicative reference

    OpenAIRE

    Marno, Hanna; Davelaar, Eddy J.; Csibra, Gergely

    2015-01-01

    In humans, a good proportion of knowledge, including knowledge about objects and object kinds, is acquired via social learning by direct communication from others. If communicative signals raise the expectation of social learning about objects, intrinsic (permanent) features that support object recognition are relevant to store into memory, while extrinsic (accidental) object properties can be ignored. We investigated this hypothesis by instructing participants to memorise shape-colour associ...

  8. Usability of Discovery Portals

    NARCIS (Netherlands)

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals

  9. Bringing home methylmercury: The construction of an authoritative object of knowledge for a Cree community in northern Quebec

    International Nuclear Information System (INIS)

    Scott, R.T.

    1993-01-01

    Aspects of the construction of methylmercury as an authoritative object of knowledge is examined for the case of Chisasibi, a Cree community on the James Bay coast in northern Quebec. The community is located near large hydroelectric projects, and an extensive institutional apparatus has been established in the Chisasibi area to provide research and education about the resulting contamination of water and fish by methylmercury released by flooding of lands by hydro reservoirs. The historical development of the Cree community is reviewed and the evolution of a particular set of spheres of exchange which mediate economic relations in the region is described. Such relations occur between the Cree communities, the federal and provincial governments, and state and corporate structures tied to the state. Knowledge claims about mercury can be seen as situated among claims of injury in a moral economy which is based on conflict over the James Bay hydroelectric project. The politicization and subsequent medicalization of these knowledge claims are described. Finally, the emergence of particular concepts of normality, risk, and risk group are traced in medical and technocratic discourses about the effects of methylmercury on Canadian aboriginal populations. 122 refs., 2 figs., 3 tabs

  10. 14 CFR 16.213 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Discovery. 16.213 Section 16.213... PRACTICE FOR FEDERALLY-ASSISTED AIRPORT ENFORCEMENT PROCEEDINGS Hearings § 16.213 Discovery. (a) Discovery... discovery permitted by this section if a party shows that— (1) The information requested is cumulative or...

  11. 28 CFR 76.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Discovery. 76.21 Section 76.21 Judicial... POSSESSION OF CERTAIN CONTROLLED SUBSTANCES § 76.21 Discovery. (a) Scope. Discovery under this part covers... as a general guide for discovery practices in proceedings before the Judge. However, unless otherwise...

  12. Discovery of an infrared nucleus in Cygnus A - An obscured quasar revealed?

    International Nuclear Information System (INIS)

    Djorgovski, S.; Weir, N.; Matthews, K.; Graham, J.R.

    1991-01-01

    This paper reports on the discovery of a compact, unresolved infrared nucleus, coincident with the radio core, in the prototypical powerful radio galaxy Cygnus A (3C 405). The infrared colors and magnitudes of the nucleus can be explained as a highly reddened extension of the radio continuum. The implied restframe extinction is A(V) equal to about 50 + or - 30 magnitudes. The extinction-corrected luminosity of the object is in the quasar range. This discovery gives some support to the unification models for quasars and powerful radio galaxies. 35 refs

  13. Text mining patents for biomedical knowledge.

    Science.gov (United States)

    Rodriguez-Esteban, Raul; Bundschus, Markus

    2016-06-01

    Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. 40 CFR 27.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Discovery. 27.21 Section 27.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

  15. 37 CFR 41.150 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Discovery. 41.150 Section 41... COMMERCE PRACTICE BEFORE THE BOARD OF PATENT APPEALS AND INTERFERENCES Contested Cases § 41.150 Discovery. (a) Limited discovery. A party is not entitled to discovery except as authorized in this subpart. The...

  16. 14 CFR 13.220 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Discovery. 13.220 Section 13.220... INVESTIGATIVE AND ENFORCEMENT PROCEDURES Rules of Practice in FAA Civil Penalty Actions § 13.220 Discovery. (a) Initiation of discovery. Any party may initiate discovery described in this section, without the consent or...

  17. 49 CFR 604.38 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 7 2010-10-01 2010-10-01 false Discovery. 604.38 Section 604.38 Transportation... TRANSPORTATION CHARTER SERVICE Hearings. § 604.38 Discovery. (a) Permissible forms of discovery shall be within the discretion of the PO. (b) The PO shall limit the frequency and extent of discovery permitted by...

  18. 15 CFR 719.10 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Discovery. 719.10 Section 719.10... Discovery. (a) General. The parties are encouraged to engage in voluntary discovery regarding any matter... the Federal Rules of Civil Procedure relating to discovery apply to the extent consistent with this...

  19. 24 CFR 26.18 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 26.18 Section 26.18... PROCEDURES Hearings Before Hearing Officers Discovery § 26.18 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery procedures, which may commence at any time after an answer has...

  20. 42 CFR 426.532 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 3 2010-10-01 2010-10-01 false Discovery. 426.532 Section 426.532 Public Health... § 426.532 Discovery. (a) General rule. If the Board orders discovery, the Board must establish a reasonable timeframe for discovery. (b) Protective order—(1) Request for a protective order. Any party...

  1. 49 CFR 1503.633 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 9 2010-10-01 2010-10-01 false Discovery. 1503.633 Section 1503.633... Rules of Practice in TSA Civil Penalty Actions § 1503.633 Discovery. (a) Initiation of discovery. Any party may initiate discovery described in this section, without the consent or approval of the ALJ, at...

  2. 14 CFR 1264.120 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Discovery. 1264.120 Section 1264.120... PENALTIES ACT OF 1986 § 1264.120 Discovery. (a) The following types of discovery are authorized: (1..., discovery is available only as ordered by the presiding officer. The presiding officer shall regulate the...

  3. 22 CFR 128.6 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 128.6 Section 128.6 Foreign... Discovery. (a) Discovery by the respondent. The respondent, through the Administrative Law Judge, may... discovery if the interests of national security or foreign policy so require, or if necessary to comply with...

  4. 24 CFR 26.42 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 26.42 Section 26.42... PROCEDURES Hearings Pursuant to the Administrative Procedure Act Discovery § 26.42 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery procedures, which may commence at any time...

  5. 49 CFR 386.37 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 5 2010-10-01 2010-10-01 false Discovery. 386.37 Section 386.37 Transportation... and Hearings § 386.37 Discovery. (a) Parties may obtain discovery by one or more of the following...; and requests for admission. (b) Discovery may not commence until the matter is pending before the...

  6. 29 CFR 1955.32 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 9 2010-07-01 2010-07-01 false Discovery. 1955.32 Section 1955.32 Labor Regulations...) PROCEDURES FOR WITHDRAWAL OF APPROVAL OF STATE PLANS Preliminary Conference and Discovery § 1955.32 Discovery... allow discovery by any other appropriate procedure, such as by interrogatories upon a party or request...

  7. 42 CFR 426.432 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 3 2010-10-01 2010-10-01 false Discovery. 426.432 Section 426.432 Public Health... § 426.432 Discovery. (a) General rule. If the ALJ orders discovery, the ALJ must establish a reasonable timeframe for discovery. (b) Protective order—(1) Request for a protective order. Any party receiving a...

  8. 10 CFR 13.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 1 2010-01-01 2010-01-01 false Discovery. 13.21 Section 13.21 Energy NUCLEAR REGULATORY COMMISSION PROGRAM FRAUD CIVIL REMEDIES § 13.21 Discovery. (a) The following types of discovery are...) Unless mutually agreed to by the parties, discovery is available only as ordered by the ALJ. The ALJ...

  9. 49 CFR 1121.2 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 8 2010-10-01 2010-10-01 false Discovery. 1121.2 Section 1121.2 Transportation... TRANSPORTATION RULES OF PRACTICE RAIL EXEMPTION PROCEDURES § 1121.2 Discovery. Discovery shall follow the procedures set forth at 49 CFR part 1114, subpart B. Discovery may begin upon the filing of the petition for...

  10. 38 CFR 42.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 2 2010-07-01 2010-07-01 false Discovery. 42.21 Section... IMPLEMENTING THE PROGRAM FRAUD CIVIL REMEDIES ACT § 42.21 Discovery. (a) The following types of discovery are... creation of a document. (c) Unless mutually agreed to by the parties, discovery is available only as...

  11. 22 CFR 521.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 2 2010-04-01 2010-04-01 true Discovery. 521.21 Section 521.21 Foreign... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for... interpreted to require the creation of a document. (c) Unless mutually agreed to by the parties, discovery is...

  12. 31 CFR 10.71 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false Discovery. 10.71 Section 10.71 Money... SERVICE Rules Applicable to Disciplinary Proceedings § 10.71 Discovery. (a) In general. Discovery may be... relevance, materiality and reasonableness of the requested discovery and subject to the requirements of § 10...

  13. 39 CFR 955.15 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 955.15 Section 955.15 Postal Service... APPEALS § 955.15 Discovery. (a) The parties are encouraged to engage in voluntary discovery procedures. In connection with any deposition or other discovery procedure, the Board may issue any order which justice...

  14. 43 CFR 35.21 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Discovery. 35.21 Section 35.21 Public... AND STATEMENTS § 35.21 Discovery. (a) The following types of discovery are authorized: (1) Requests...) Unless mutually agreed to by the parties, discovery is available only as ordered by the ALJ. The ALJ...

  15. 15 CFR 766.9 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Discovery. 766.9 Section 766.9... PROCEEDINGS § 766.9 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery... provisions of the Federal Rules of Civil Procedure relating to discovery apply to the extent consistent with...

  16. "Discoveries in Planetary Sciences": Slide Sets Highlighting New Advances for Astronomy Educators

    Science.gov (United States)

    Brain, D. A.; Schneider, N. M.; Beyer, R. A.

    2010-12-01

    Planetary science is a field that evolves rapidly, motivated by spacecraft mission results. Exciting new mission results are generally communicated rather quickly to the public in the form of press releases and news stories, but it can take several years for new advances to work their way into college textbooks. Yet it is important for students to have exposure to these new advances for a number of reasons. In some cases, new work renders older textbook knowledge incorrect or incomplete. In some cases, new discoveries make it possible to emphasize older textbook knowledge in a new way. In all cases, new advances provide exciting and accessible examples of the scientific process in action. To bridge the gap between textbooks and new advances in planetary sciences we have developed content on new discoveries for use by undergraduate instructors. Called 'Discoveries in Planetary Sciences', each new discovery is summarized in a 3-slide PowerPoint presentation. The first slide describes the discovery, the second slide discusses the underlying planetary science concepts, and the third presents the big picture implications of the discovery. A fourth slide includes links to associated press releases, images, and primary sources. This effort is generously sponsored by the Division for Planetary Sciences of the American Astronomical Society, and the slide sets are available at http://dps.aas.org/education/dpsdisc/. Sixteen slide sets have been released so far covering topics spanning all sub-disciplines of planetary science. Results from the following spacecraft missions have been highlighted: MESSENGER, the Spirit and Opportunity rovers, Cassini, LCROSS, EPOXI, Chandrayan, Mars Reconnaissance Orbiter, Mars Express, and Venus Express. Additionally, new results from Earth-orbiting and ground-based observing platforms and programs such as Hubble, Keck, IRTF, the Catalina Sky Survey, HARPS, MEarth, Spitzer, and amateur astronomers have been highlighted. 4-5 new slide sets are

  17. On Discovery of Gathering Patterns from Trajectories

    DEFF Research Database (Denmark)

    Zheng, Kai; Zheng, Yu; Yuan, Jing

    2013-01-01

    The increasing pervasiveness of location-acquisition technologies has enabled collection of huge amount of trajectories for almost any kind of moving objects. Discovering useful patterns from their movement behaviours can convey valuable knowledge to a variety of critical applications. In this li......The increasing pervasiveness of location-acquisition technologies has enabled collection of huge amount of trajectories for almost any kind of moving objects. Discovering useful patterns from their movement behaviours can convey valuable knowledge to a variety of critical applications...

  18. Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 2.

    Science.gov (United States)

    McBride, Christopher; Cheruvallath, Zacharia; Komandla, Mallareddy; Tang, Mingnam; Farrell, Pamela; Lawson, J David; Vanderpool, Darin; Wu, Yiqin; Dougan, Douglas R; Plonowski, Artur; Holub, Corine; Larson, Chris

    2016-06-15

    Methionine aminopeptidase-2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. This step is required before they will fold or function correctly. Pre-clinical and clinical studies with a MetAP2 inhibitor suggest that they could be used as a novel treatment for obesity. Herein we describe the discovery of a series of pyrazolo[4,3-b]indoles as reversible MetAP2 inhibitors. A fragment-based drug discovery (FBDD) approach was used, beginning with the screening of fragment libraries to generate hits with high ligand-efficiency (LE). An indazole core was selected for further elaboration, guided by structural information. SAR from the indazole series led to the design of a pyrazolo[4,3-b]indole core and accelerated knowledge-based fragment growth resulted in potent and efficient MetAP2 inhibitors, which have shown robust and sustainable body weight loss in DIO mice when dosed orally. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Get Involved in Planetary Discoveries through New Worlds, New Discoveries

    Science.gov (United States)

    Shupla, Christine; Shipp, S. S.; Halligan, E.; Dalton, H.; Boonstra, D.; Buxner, S.; SMD Planetary Forum, NASA

    2013-01-01

    "New Worlds, New Discoveries" is a synthesis of NASA’s 50-year exploration history which provides an integrated picture of our new understanding of our solar system. As NASA spacecraft head to and arrive at key locations in our solar system, "New Worlds, New Discoveries" provides an integrated picture of our new understanding of the solar system to educators and the general public! The site combines the amazing discoveries of past NASA planetary missions with the most recent findings of ongoing missions, and connects them to the related planetary science topics. "New Worlds, New Discoveries," which includes the "Year of the Solar System" and the ongoing celebration of the "50 Years of Exploration," includes 20 topics that share thematic solar system educational resources and activities, tied to the national science standards. This online site and ongoing event offers numerous opportunities for the science community - including researchers and education and public outreach professionals - to raise awareness, build excitement, and make connections with educators, students, and the public about planetary science. Visitors to the site will find valuable hands-on science activities, resources and educational materials, as well as the latest news, to engage audiences in planetary science topics and their related mission discoveries. The topics are tied to the big questions of planetary science: how did the Sun’s family of planets and bodies originate and how have they evolved? How did life begin and evolve on Earth, and has it evolved elsewhere in our solar system? Scientists and educators are encouraged to get involved either directly or by sharing "New Worlds, New Discoveries" and its resources with educators, by conducting presentations and events, sharing their resources and events to add to the site, and adding their own public events to the site’s event calendar! Visit to find quality resources and ideas. Connect with educators, students and the public to

  20. 13 CFR 134.213 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Discovery. 134.213 Section 134.213... OFFICE OF HEARINGS AND APPEALS Rules of Practice for Most Cases § 134.213 Discovery. (a) Motion. A party may obtain discovery only upon motion, and for good cause shown. (b) Forms. The forms of discovery...

  1. 31 CFR 16.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false Discovery. 16.21 Section 16.21 Money... FRAUD CIVIL REMEDIES ACT OF 1986 § 16.21 Discovery. (a) The following types of discovery are authorized... to require the creation of a document. (c) Unless mutually agreed to by the parties, discovery is...

  2. The University of New Mexico Center for Molecular Discovery

    Science.gov (United States)

    Edwards, Bruce S.; Gouveia, Kristine; Oprea, Tudor I.; Sklar, Larry A.

    2015-01-01

    The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as “up-front” services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH’s Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of “smart” oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise. PMID:24409953

  3. Subjective knowledge of AIDS and use of HIV testing.

    Science.gov (United States)

    Phillips, K A

    1993-10-01

    Increasing knowledge is an important goal of human immunodeficiency virus (HIV) prevention strategies, although increased knowledge may not be associated with increased preventive behaviors. This study examines the association of (1) objective and subjective acquired immunodeficiency syndrome (AIDS) knowledge, and (2) both objective and subjective AIDS knowledge with HIV testing use. Data are from the 1988 National Health Interview Survey. Objective and subjective knowledge were only moderately correlated. In regression analyses, higher subjective knowledge was significantly associated with higher testing use, but objective knowledge was not. The results are relevant to other preventive behaviors for which knowledge is an important factor.

  4. The Southern HII Region Discovery Survey

    Science.gov (United States)

    Wenger, Trey; Miller Dickey, John; Jordan, Christopher; Bania, Thomas M.; Balser, Dana S.; Dawson, Joanne; Anderson, Loren D.; Armentrout, William P.; McClure-Griffiths, Naomi

    2016-01-01

    HII regions are zones of ionized gas surrounding recently formed high-mass (OB-type) stars. They are among the brightest objects in the sky at radio wavelengths. HII regions provide a useful tool in constraining the Galactic morphological structure, chemical structure, and star formation rate. We describe the Southern HII Region Discovery Survey (SHRDS), an Australia Telescope Compact Array (ATCA) survey that discovered ~80 new HII regions (so far) in the Galactic longitude range 230 degrees to 360 degrees. This project is an extension of the Green Bank Telescope HII Region Discovery Survey (GBT HRDS), Arecibo HRDS, and GBT Widefield Infrared Survey Explorer (WISE) HRDS, which together discovered ~800 new HII regions in the Galactic longitude range -20 degrees to 270 degrees. Similar to those surveys, candidate HII regions were chosen from 20 micron emission (from WISE) coincident with 10 micron (WISE) and 20 cm (SGPS) emission. By using the ATCA to detect radio continuum and radio recombination line emission from a subset of these candidates, we have added to the population of known Galactic HII regions.

  5. Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data.

    Science.gov (United States)

    Mamykina, Lena; Heitkemper, Elizabeth M; Smaldone, Arlene M; Kukafka, Rita; Cole-Lewis, Heather J; Davidson, Patricia G; Mynatt, Elizabeth D; Cassells, Andrea; Tobin, Jonathan N; Hripcsak, George

    2017-12-01

    To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum. The study included observations of class sessions, and interviews and focus groups with the educator and attendees of the program (n = 14). The main discovery in diabetes self-management evolved around discovering patterns of association between characteristics of individuals' activities and changes in their blood glucose levels that the participants referred to as "cause and effect". This discovery empowered individuals to actively engage in self-management and provided a desired flexibility in selection of personalized self-management strategies. We show that discovery of cause and effect involves four essential phases: (1) feature selection, (2) hypothesis generation, (3) feature evaluation, and (4) goal specification. Further, we identify opportunities to support discovery at each stage with informatics and data visualization solutions by providing assistance with: (1) active manipulation of collected data (e.g., grouping, filtering and side-by-side inspection), (2) hypotheses formulation (e.g., using natural language statements or constructing visual queries), (3) inference evaluation (e.g., through aggregation and visual comparison, and statistical analysis of associations), and (4) translation of discoveries into actionable goals (e.g., tailored selection from computable knowledge sources of effective diabetes self-management behaviors). The study suggests that discovery of cause and effect in diabetes can be a powerful approach to helping individuals to improve their self-management strategies, and that self-monitoring data can

  6. 100 years poliovirus: from discovery to eradication. A meeting report.

    Science.gov (United States)

    Skern, Tim

    2010-09-01

    Just over hundred years ago, Karl Landsteiner and Erwin Popper identified a virus, later termed poliovirus, as the causative agent of poliomyelitis. This groundbreaking discovery simultaneously provided the basis for the measures that today prevent the outbreaks of the terrible epidemics caused by poliovirus. In 1988, the WHO started its eradication program to eliminate the virus from the planet. The symposium celebrated the discovery of poliovirus and discussed our current state of knowledge of poliovirus biology. Prospects for the eradication program were evaluated, with particular emphasis being placed on why certain countries still have not succeeding in interrupting wild-type transmission of poliovirus. Discussion also centred on the role of inactivated poliovirus vaccines in the eradication program and the maintenance of a poliovirus-free world, whenever this goal should be achieved.

  7. A SEARCH FOR HERBIG-HARO OBJECTS IN NGC 7023 AND BARNARD 175

    International Nuclear Information System (INIS)

    Rector, T. A.; Schweiker, H.

    2013-01-01

    Wide-field optical imaging was obtained of the cluster and reflection nebula NGC 7023 and the Bok globule B175. We report the discovery of four new Herbig-Haro (HH) objects in NGC 7023, the first HH objects to be found in this region. They were first detected by their Hα and [S II] emission but are also visible at 3.6 and 4.5 μm in archival Spitzer observations of this field. These HH objects are part of at least two distinct outflows. Both outflows are aligned with embedded 'Class I' young stellar objects in a tight group on the western edge of the nebula. One of the outflows may have a projected distance of 0.75 pc, which is a notable length for an embedded source. No new HH objects were discovered in B175. However, we reclassify the knot HH450X, in B175, as a background galaxy. The discovery that HH 450X is not a shock front weakens the argument that HH 450 and SNR G110.3+11.3 are co-located and interacting.

  8. Knowledge-based public health situation awareness

    Science.gov (United States)

    Mirhaji, Parsa; Zhang, Jiajie; Srinivasan, Arunkumar; Richesson, Rachel L.; Smith, Jack W.

    2004-09-01

    There have been numerous efforts to create comprehensive databases from multiple sources to monitor the dynamics of public health and most specifically to detect the potential threats of bioterrorism before widespread dissemination. But there are not many evidences for the assertion that these systems are timely and dependable, or can reliably identify man made from natural incident. One must evaluate the value of so called 'syndromic surveillance systems' along with the costs involved in design, development, implementation and maintenance of such systems and the costs involved in investigation of the inevitable false alarms1. In this article we will introduce a new perspective to the problem domain with a shift in paradigm from 'surveillance' toward 'awareness'. As we conceptualize a rather different approach to tackle the problem, we will introduce a different methodology in application of information science, computer science, cognitive science and human-computer interaction concepts in design and development of so called 'public health situation awareness systems'. We will share some of our design and implementation concepts for the prototype system that is under development in the Center for Biosecurity and Public Health Informatics Research, in the University of Texas Health Science Center at Houston. The system is based on a knowledgebase containing ontologies with different layers of abstraction, from multiple domains, that provide the context for information integration, knowledge discovery, interactive data mining, information visualization, information sharing and communications. The modular design of the knowledgebase and its knowledge representation formalism enables incremental evolution of the system from a partial system to a comprehensive knowledgebase of 'public health situation awareness' as it acquires new knowledge through interactions with domain experts or automatic discovery of new knowledge.

  9. The role of internet of things (IOT in knowledge management systems (Case study: Performance management of Yazd municipality staff

    Directory of Open Access Journals (Sweden)

    Hamid Reza Khedmatgozar

    2015-09-01

    Full Text Available With the development of Internet of things (IOT technologies in recent years, the development of knowledge management systems based on them, as well as the role of these systems in different organizational areas such as staff performance management should be considered. The objective of this study is to design an application based on the IOT, and analysis of its role in staff performance improvement. The methodology of this study is action research based on the design of information systems with RAD approach and prototyping design method, and focus on one of the performance indicators of the Yazd municipality staff, namely daily working time. The proposed knowledge management based structure to control the entry and exit of staff in the case of study, and implementation of its prototype indicated that IOT can play roles in improving staff performance in six specific areas in two parts of data collection and management of entry and exit. In general, IOT could be used as a reliable basis to generate required data for knowledge management in knowledge based processes, especially knowledge discovery in physical and digital environments.

  10. Decades of Discovery

    Science.gov (United States)

    2011-06-01

    For the past two-and-a-half decades, the Office of Science at the U.S. Department of Energy has been at the forefront of scientific discovery. Over 100 important discoveries supported by the Office of Science are represented in this document.

  11. Automatic cumulative sums contour detection of FBP-reconstructed multi-object nuclear medicine images.

    Science.gov (United States)

    Protonotarios, Nicholas E; Spyrou, George M; Kastis, George A

    2017-06-01

    The problem of determining the contours of objects in nuclear medicine images has been studied extensively in the past, however most of the analysis has focused on a single object as opposed to multiple objects. The aim of this work is to develop an automated method for determining the contour of multiple objects in positron emission tomography (PET) and single photon emission computed tomography (SPECT) filtered backprojection (FBP) reconstructed images. These contours can be used for computing body edges for attenuation correction in PET and SPECT, as well as for eliminating streak artifacts outside the objects, which could be useful in compressive sensing reconstruction. Contour detection has been accomplished by applying a modified cumulative sums (CUSUM) scheme in the sinogram. Our approach automatically detects all objects in the image, without requiring a priori knowledge of the number of distinct objects in the reconstructed image. This method has been tested in simulated phantoms, such as an image-quality (IQ) phantom and two digital multi-object phantoms, as well as a real NEMA phantom and a clinical thoracic study. For this purpose, a GE Discovery PET scanner was employed. The detected contours achieved root mean square accuracy of 1.14 pixels, 1.69 pixels and 3.28 pixels and a Hausdorff distance of 3.13, 3.12 and 4.50 pixels, for the simulated image-quality phantom PET study, the real NEMA phantom and the clinical thoracic study, respectively. These results correspond to a significant improvement over recent results obtained in similar studies. Furthermore, we obtained an optimal sub-pattern assignment (OSPA) localization error of 0.94 and 1.48, for the two-objects and three-objects simulated phantoms, respectively. Our method performs efficiently for sets of convex objects and hence it provides a robust tool for automatic contour determination with precise results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Discovery and the atom

    International Nuclear Information System (INIS)

    1989-01-01

    ''Discovery and the Atom'' tells the story of the founding of nuclear physics. This programme looks at nuclear physics up to the discovery of the neutron in 1932. Animation explains the science of the classic experiments, such as the scattering of alpha particles by Rutherford and the discovery of the nucleus. Archive film shows the people: Lord Rutherford, James Chadwick, Marie Curie. (author)

  13. Biomimicry as a basis for drug discovery.

    Science.gov (United States)

    Kolb, V M

    1998-01-01

    Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.

  14. Featured Article: Genotation: Actionable knowledge for the scientific reader.

    Science.gov (United States)

    Nagahawatte, Panduka; Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

    2016-06-01

    We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug-gene relationships, 5981 gene-disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. © 2016 by the Society for Experimental Biology and

  15. Reuse-oriented common structure discovery in assembly models

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Pan; Zhang Jie; Li, Yuan; Yu, Jian Feng [The Ministry of Education Key Lab of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, Xian (China)

    2017-01-15

    Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach.

  16. Reuse-oriented common structure discovery in assembly models

    International Nuclear Information System (INIS)

    Wang, Pan; Zhang Jie; Li, Yuan; Yu, Jian Feng

    2017-01-01

    Discovering the common structures in assembly models provides designers with the commonalities that carry significant design knowledge across multiple products, which helps to improve design efficiency and accelerate the design process. In this paper, a discovery method has been developed to obtain the common structure in assembly models. First, this work proposes a graph descriptor that captures both the geometrical and topological information of the assembly model, in which shape vectors and link vectors quantitatively describe the part models and mating relationships, respectively. Then, a clustering step is introduced into the discovery, which clusters the similar parts by comparing the similarities between them. In addition, some rules are also provided to filter the frequent subgraphs in order to obtain the expected results. Compared with the existing method, the proposed approach could overcome the disadvantages by providing an independent description of the part model and taking into consideration the similar parts in assemblies, which leads to a more reasonable result. Finally, some experiments have been carried out and the experimental results demonstrate the effectiveness of the proposed approach

  17. Approaching socio-technical issues in Knowledge Communication

    DEFF Research Database (Denmark)

    Kampf, Constance; Islas Sedano, Carolina

    2008-01-01

    This paper looks at the connection between technology, knowledge management and knowledge communication theory from a process perspective. Knowledge management and knowledge communication processes are examined through the iterations in creating project goals and objectives which connect the social...... and objectives with respect to knowledge communication theory, demonstrating the potential of knowledge communication concepts for socio-technical design processes, as well as the implications of socio-technical design processes in extending our understanding of knowledge communication....

  18. DISCOVERY OF TWO RARE RIGIDLY ROTATING MAGNETOSPHERE STARS IN THE APOGEE SURVEY

    Energy Technology Data Exchange (ETDEWEB)

    Eikenberry, Stephen S.; Garner, Alan [Department of Astronomy, University of Florida, 211 Bryant Space Science Center, Gainesville, FL 32611 (United States); Chojnowski, S. Drew; Majewski, Steven R.; Whelan, David G.; Borish, H. Jacob; Hearty, Fred; Li, Zhi-Yun; Nidever, David L.; Skrutskie, Michael [Department of Astronomy, University of Virginia, 530 McCormick Rd, Charlottesville, VA 22904 (United States); Wisniewski, John [Department of Astronomy, University of Oklahoma, 440 W. Brooks St., Norman, OK 73019 (United States); Shetrone, Matthew [University of Texas, McDonald Observatory, 3640 Dark Sky Drive, Fort Davis, TX (United States); Bizyaev, Dmitry; Ebelke, Garrett [Apache Point Observatory, 2001 Apache Point Rd, Sunspot, NM 88349 (United States); Davenport, James R. A. [Department of Astronomy, University of Washington, Box 351580, U.W., Seattle, WA 98195-1580 (United States); Feuillet, Diane; Holtzman, Jon [Department of Astronomy, New Mexico State University, 1780 E University Ave, Las Cruces, NM 88003 (United States); Frinchaboy, Peter M. [Department of Physics and Astronomy, Texas Christian University, Box 298840, Fort Worth, TX 76129 (United States); Mészáros, Sz. [Instituto de Astrofísica de Canarias (IAC), E-38200 La Laguna, Tenerife (Spain); Schneider, Donald P. [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Lab, University Park, PA 16802 (United States); and others

    2014-04-01

    The Apache Point Observatory Galactic Evolution Experiment (APOGEE)—one of the Sloan Digital Sky Survey III programs—is using near-infrared (NIR) spectra of ∼100,000 red giant branch star candidates to study the structure of the Milky Way. In the course of the survey, APOGEE also acquires spectra of hot field stars to serve as telluric calibrators for the primary science targets. We report the serendipitous discovery of two rare, fast-rotating B-stars of the σ Ori E type among those blue field stars observed during the first year of APOGEE operations. Both of the discovered stars display the spectroscopic signatures of rigidly rotating magnetospheres (RRM) common to this class of highly magnetized (B ∼ 10 kGauss) stars, increasing the number of known RRM stars by ∼10%. One (HD 345439) is a main-sequence B-star with unusually strong He absorption (similar to σ Ori E), while the other (HD 23478) fits a ''He-normal'' B3IV classification. We combine the APOGEE discovery spectra with other optical and NIR spectra of these two stars, and of σ Ori E itself, to show how NIR spectroscopy can be a uniquely powerful tool for discovering more of these rare objects, which may show little/no RRM signatures in their optical spectra. We discuss the potential for further discovery of σ Ori E type stars, as well as the implications of our discoveries for the population of these objects and insights into their origin and evolution.

  19. DISCOVERY OF TWO RARE RIGIDLY ROTATING MAGNETOSPHERE STARS IN THE APOGEE SURVEY

    International Nuclear Information System (INIS)

    Eikenberry, Stephen S.; Garner, Alan; Chojnowski, S. Drew; Majewski, Steven R.; Whelan, David G.; Borish, H. Jacob; Hearty, Fred; Li, Zhi-Yun; Nidever, David L.; Skrutskie, Michael; Wisniewski, John; Shetrone, Matthew; Bizyaev, Dmitry; Ebelke, Garrett; Davenport, James R. A.; Feuillet, Diane; Holtzman, Jon; Frinchaboy, Peter M.; Mészáros, Sz.; Schneider, Donald P.

    2014-01-01

    The Apache Point Observatory Galactic Evolution Experiment (APOGEE)—one of the Sloan Digital Sky Survey III programs—is using near-infrared (NIR) spectra of ∼100,000 red giant branch star candidates to study the structure of the Milky Way. In the course of the survey, APOGEE also acquires spectra of hot field stars to serve as telluric calibrators for the primary science targets. We report the serendipitous discovery of two rare, fast-rotating B-stars of the σ Ori E type among those blue field stars observed during the first year of APOGEE operations. Both of the discovered stars display the spectroscopic signatures of rigidly rotating magnetospheres (RRM) common to this class of highly magnetized (B ∼ 10 kGauss) stars, increasing the number of known RRM stars by ∼10%. One (HD 345439) is a main-sequence B-star with unusually strong He absorption (similar to σ Ori E), while the other (HD 23478) fits a ''He-normal'' B3IV classification. We combine the APOGEE discovery spectra with other optical and NIR spectra of these two stars, and of σ Ori E itself, to show how NIR spectroscopy can be a uniquely powerful tool for discovering more of these rare objects, which may show little/no RRM signatures in their optical spectra. We discuss the potential for further discovery of σ Ori E type stars, as well as the implications of our discoveries for the population of these objects and insights into their origin and evolution

  20. Integrating ergonomics into engineering design: the role of objects.

    Science.gov (United States)

    Hall-Andersen, Lene Bjerg; Broberg, Ole

    2014-05-01

    The objective of this study was to explore the role of objects in integrating ergonomic knowledge in engineering design processes. An engineering design case was analyzed using the theoretical concepts of boundary objects and intermediary objects: Boundary objects facilitate collaboration between different knowledge domains, while the aim of an intermediary object is to circulate knowledge and thus produce a distant effect. Adjustable layout drawings served as boundary objects and had a positive impact on the dialog between an ergonomist and designers. An ergonomic guideline document was identified as an intermediary object. However, when the ergonomic guidelines were circulated in the design process, only some of the guidelines were transferred to the design of the sterile processing plant. Based on these findings, recommendations for working with objects in design processes are included. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  1. 29 CFR 2700.56 - Discovery; general.

    Science.gov (United States)

    2010-07-01

    ...(c) or 111 of the Act has been filed. 30 U.S.C. 815(c) and 821. (e) Completion of discovery... 29 Labor 9 2010-07-01 2010-07-01 false Discovery; general. 2700.56 Section 2700.56 Labor... Hearings § 2700.56 Discovery; general. (a) Discovery methods. Parties may obtain discovery by one or more...

  2. Harnessing the potential of natural products in drug discovery from a cheminformatics vantage point.

    Science.gov (United States)

    Rodrigues, Tiago

    2017-11-15

    Natural products (NPs) present a privileged source of inspiration for chemical probe and drug design. Despite the biological pre-validation of the underlying molecular architectures and their relevance in drug discovery, the poor accessibility to NPs, complexity of the synthetic routes and scarce knowledge of their macromolecular counterparts in phenotypic screens still hinder their broader exploration. Cheminformatics algorithms now provide a powerful means of circumventing the abovementioned challenges and unlocking the full potential of NPs in a drug discovery context. Herein, I discuss recent advances in the computer-assisted design of NP mimics and how artificial intelligence may accelerate future NP-inspired molecular medicine.

  3. Early investigations of Ceres and the discovery of Pallas historical studies in asteroid research

    CERN Document Server

    Cunningham, Clifford

    2016-01-01

    An asteroid scholar, Cunningham in this book picks up where his Discovery of the First Asteroid, Ceres left off in telling the story of the impact created by the discovery of this new class of object in the early 1800s. The best and brightest minds of mathematics, science, and philosophy were fascinated by Ceres, and figures as diverse as Gauss, Herschel, Brougham, Kant, and Laplace all contributed something to the conversation. The first few chapters deal with the mathematical and philosophical aspects of the discovery, and the rivalry between Germany and France that so affected science and astronomy of that era. The jockeying for glory over the discovery of Ceres by both Piazzi and Bode is examined in detail, as is the reception given to Herschel’s use of the word 'asteroid.' Archival research that reveals the creator of the word 'asteroid' is presented in this book. Astronomy was a truly cosmopolitan field at the time, spanning across various disciplines, and the discovery of Pallas, a story completely t...

  4. Evaluating Music Discovery Tools on Spotify: The Role of User Preference Characteristics

    Directory of Open Access Journals (Sweden)

    Muh-Chyun Tang

    2017-06-01

    Full Text Available An experimental study was conducted to assess the effectiveness of the four music discovery tools available on Spotify, a popular music streaming service, namely: radio recommendation, regional charts, genres and moods, as well as following Facebook friends. Both subjective judgment of user experience and objective measures of search effectiveness were used as the performance criteria. Other than comparison of these four tools, we also compared how consistent are these performance measures. The results show that user experience criteria were not necessarily corresponded to search effectiveness. Furthermore, three user preference characteristics: preference diversity, preference insight, and openness to novelty were introduced as mediating variables, with an aim to investigating how these attributes might interact with these four music discovery tools on performance. The results suggest that users’ preference characteristics did have an impact on the performance of these music discovery tools.

  5. Is it SUSY? -first steps after an LHC discovery

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    A missing energy discovery is possible at the LHC in the first year of running. The origin of such a signal could be any of a huge number of models of supersymmetry, or non-supersymmetric models with extra dimensions or "little Higgs". Recently we have developed a realistic strategy to rapidly narrow the list of candidate theories at, or close to, the moment of discovery. The strategy is based on robust ratios of inclusive counts of simple physics objects. We studied specific cases showing discrimination of look- alike models in simulated data sets that are at least 10 to 100 times smaller than used in previous studies. We discriminate supersymmetry models from non-supersymmetric look-alikes with only 100 pb-1 of simulated data, using combinations of observables that trace back to differences in spin.

  6. Software patterns, knowledge maps, and domain analysis

    CERN Document Server

    Fayad, Mohamed E; Hegde, Srikanth GK; Basia, Anshu; Vakil, Ashka

    2014-01-01

    Preface AcknowledgmentsAuthors INTRODUCTIONAn Overview of Knowledge MapsIntroduction: Key Concepts-Software Stable Models, Knowledge Maps, Pattern Language, Goals, Capabilities (Enduring Business Themes + Business Objects) The Motivation The Problem The Objectives Overview of Software Stability Concepts Overview of Knowledge Maps Pattern Languages versus Knowledge Maps: A Brief ComparisonThe Solution Knowledge Maps Methodology or Concurrent Software Development ModelWhy Knowledge Maps? Research Methodology Undertaken Research Verification and Validation The Stratification of This Book Summary

  7. Rediscovering Don Swanson: The Past, Present and Future of Literature-based Discovery

    Directory of Open Access Journals (Sweden)

    Neil R. Smalheiser

    2017-12-01

    Full Text Available Purpose: The late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the American Society for Information Science Award of Merit for 2000, and as author of many seminal articles. In this informal essay, I will give my personal perspective on Don’s contributions to science, and outline some current and future directions in literature-based discovery that are rooted in concepts that he developed. Design/methodology/approach: Personal recollections and literature review. Findings: The Swanson A-B-C model of literature-based discovery has been successfully used by laboratory investigators analyzing their findings and hypotheses. It continues to be a fertile area of research in a wide range of application areas including text mining, drug repurposing, studies of scientific innovation, knowledge discovery in databases, and bioinformatics. Recently, additional modes of discovery that do not follow the A-B-C model have also been proposed and explored (e.g. so-called storytelling, gaps, analogies, link prediction, negative consensus, outliers, and revival of neglected or discarded research questions. Research limitations: This paper reflects the opinions of the author and is not a comprehensive nor technically based review of literature-based discovery. Practical implications: The general scientific public is still not aware of the availability of tools for literature-based discovery. Our Arrowsmith project site maintains a suite of discovery tools that are free and open to the public (http://arrowsmith.psych.uic.edu, as does BITOLA which is maintained by Dmitar Hristovski (http:// http://ibmi.mf.uni-lj.si/bitola, and Epiphanet which is maintained by Trevor Cohen (http://epiphanet.uth.tmc.edu/. Bringing user-friendly tools to the public should be a high priority, since even more than advancing basic research in informatics, it is vital that we ensure that scientists

  8. A Revenue Analysis on Taiwan’s Publishing Industries from the Prospective of Knowledge Discovery Using Government’s Financial Database

    Directory of Open Access Journals (Sweden)

    Ming-Ju Hsu

    2017-07-01

    Full Text Available This research focused on retrieving and analyzing data and information from the “Financial Database” established by the Ministry of Finance of Republic of China (Taiwan, carrying out a Knowledge Discovery from the Financial Database (KDFD 2013~2015, primarily on Taiwan’s Nine(9-subclass Publishing Industries. The results of the research showed that: a. the sales revenues of Taiwan’s Publishing Industries have declined year after year from 2013 to 2015; b. within the year there was a wave of steep drop in sales from May to June, then the sales revenues gradually recovered and reached the peak in November to December and c. Newspapers, magazines and books publishing were still the dominate part of the sales for the Publishing Industries (82.1%. While the Digital Publishing Industries accounted for an average of 16% of total sales revenues from 2013 to 2015, the growth spurs from 11% in 2013 to 16% in 2014, then to 20% in 2015 were quite impressive, indicating a potential growth for Digital Publishing Industries. The definition of the publishing industries categorized by the government of Taiwan included nine subclasses in the whole division, further study could be conducted for each subclass of the publishing division to obtain its actual sales revenues for a more realistic comparison with surveyed data.

  9. Knowledge, attitudes and practices of mothers and knowledge of ...

    African Journals Online (AJOL)

    Objective: To determine the knowledge, attitudes and practices (KAP) of mothers and the knowledge of health workers regarding care of the newborn umbilical cord. Design: Cross-sectional survey. Subjects: Mothers with infants less than three months of age attending well child clinics and health workers (HW) in the clinics, ...

  10. GENESI-DR: Discovery, Access and on-Demand Processing in Federated Repositories

    Science.gov (United States)

    Cossu, Roberto; Pacini, Fabrizio; Parrini, Andrea; Santi, Eliana Li; Fusco, Luigi

    2010-05-01

    GENESI-DR (Ground European Network for Earth Science Interoperations - Digital Repositories) is a European Commission (EC)-funded project, kicked-off early 2008 lead by ESA; partners include Space Agencies (DLR, ASI, CNES), both space and no-space data providers such as ENEA (I), Infoterra (UK), K-SAT (N), NILU (N), JRC (EU) and industry as Elsag Datamat (I), CS (F) and TERRADUE (I). GENESI-DR intends to meet the challenge of facilitating "time to science" from different Earth Science disciplines in discovery, access and use (combining, integrating, processing, …) of historical and recent Earth-related data from space, airborne and in-situ sensors, which are archived in large distributed repositories. In fact, a common dedicated infrastructure such as the GENESI-DR one permits the Earth Science communities to derive objective information and to share knowledge in all environmental sensitive domains over a continuum of time and a variety of geographical scales so addressing urgent challenges such as Global Change. GENESI-DR federates data, information and knowledge for the management of our fragile planet in line with one of the major goals of the many international environmental programmes such as GMES, GEO/GEOSS. As of today, 12 different Digital Repositories hosting more than 60 heterogeneous dataset series are federated in GENESI-DR. Series include satellite data, in situ data, images acquired by airborne sensors, digital elevation models and model outputs. ESA has started providing access to: Category-1 data systematically available on Internet; level 3 data (e.g., GlobCover map, MERIS Global Vegetation Index); ASAR products available in ESA Virtual Archive and related to the Supersites initiatives. In all cases, existing data policies and security constraints are fully respected. GENESI-DR also gives access to Grid and Cloud computing resources allowing authorized users to run a number of different processing services on the available data. The GENESI

  11. Knowledge is power: how conceptual knowledge transforms visual cognition.

    Science.gov (United States)

    Collins, Jessica A; Olson, Ingrid R

    2014-08-01

    In this review, we synthesize the existing literature demonstrating the dynamic interplay between conceptual knowledge and visual perceptual processing. We consider two theoretical frameworks that demonstrate interactions between processes and brain areas traditionally considered perceptual or conceptual. Specifically, we discuss categorical perception, in which visual objects are represented according to category membership, and highlight studies showing that category knowledge can penetrate early stages of visual analysis. We next discuss the embodied account of conceptual knowledge, which holds that concepts are instantiated in the same neural regions required for specific types of perception and action, and discuss the limitations of this framework. We additionally consider studies showing that gaining abstract semantic knowledge about objects and faces leads to behavioral and electrophysiological changes that are indicative of more efficient stimulus processing. Finally, we consider the role that perceiver goals and motivation may play in shaping the interaction between conceptual and perceptual processing. We hope to demonstrate how pervasive such interactions between motivation, conceptual knowledge, and perceptual processing are in our understanding of the visual environment, and to demonstrate the need for future research aimed at understanding how such interactions arise in the brain.

  12. Revealing Significant Relations between Chemical/Biological Features and Activity: Associative Classification Mining for Drug Discovery

    Science.gov (United States)

    Yu, Pulan

    2012-01-01

    Classification, clustering and association mining are major tasks of data mining and have been widely used for knowledge discovery. Associative classification mining, the combination of both association rule mining and classification, has emerged as an indispensable way to support decision making and scientific research. In particular, it offers a…

  13. Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA. Part 2: Novel system Architecture, Information/Knowledge Representation, Algorithm Design and Implementation

    Directory of Open Access Journals (Sweden)

    Luigi Boschetti

    2012-09-01

    Full Text Available According to literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA systems and three-stage iterative geographic object-oriented image analysis (GEOOIA systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the Quality Indexes of Operativeness (OQIs of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO guidelines, this methodological work is split into two parts. Based on an original multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT analysis of the GEOBIA/GEOOIA approaches, the first part of this work promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS image understanding system (RS-IUS, from sub-symbolic statistical model-based (inductive image segmentation to symbolic physical model-based (deductive image preliminary classification capable of accomplishing image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the present second part of this work, a novel hybrid (combined deductive and inductive RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a computational theory (system design, (b information/knowledge representation, (c algorithm design and (d implementation. As proof-of-concept of symbolic physical model-based pre-attentive vision first stage, the spectral knowledge-based, operational, near real-time, multi-sensor, multi-resolution, application-independent Satellite Image Automatic Mapper™ (SIAM™ is selected from existing literature. To the best of these authors’ knowledge, this is the first time a symbolic syntactic inference system, like SIAM™, is made available to the RS community for operational use in a RS-IUS pre-attentive vision first stage

  14. Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research.

    Science.gov (United States)

    Vos, Rein; Aarts, Sil; van Mulligen, Erik; Metsemakers, Job; van Boxtel, Martin P; Verhey, Frans; van den Akker, Marjan

    2014-01-01

    Multimorbidity, the co-occurrence of two or more chronic medical conditions within a single individual, is increasingly becoming part of daily care of general medical practice. Literature-based discovery may help to investigate the patterns of multimorbidity and to integrate medical knowledge for improving healthcare delivery for individuals with co-occurring chronic conditions. To explore the usefulness of literature-based discovery in primary care research through the key-case of finding associations between psychiatric and somatic diseases relevant to general practice in a large biomedical literature database (Medline). By using literature based discovery for matching disease profiles as vectors in a high-dimensional associative concept space, co-occurrences of a broad spectrum of chronic medical conditions were matched for their potential in biomedicine. An experimental setting was chosen in parallel with expert evaluations and expert meetings to assess performance and to generate targets for integrating literature-based discovery in multidisciplinary medical research of psychiatric and somatic disease associations. Through stepwise reductions a reference set of 21,945 disease combinations was generated, from which a set of 166 combinations between psychiatric and somatic diseases was selected and assessed by text mining and expert evaluation. Literature-based discovery tools generate specific patterns of associations between psychiatric and somatic diseases: one subset was appraised as promising for further research; the other subset surprised the experts, leading to intricate discussions and further eliciting of frameworks of biomedical knowledge. These frameworks enable us to specify targets for further developing and integrating literature-based discovery in multidisciplinary research of general practice, psychology and psychiatry, and epidemiology.

  15. Wi-Fi Hotspot Auto-Discovery: A Practical & Energy-Aware System for Smart Objects using Cellular Signals

    Directory of Open Access Journals (Sweden)

    Nithyananthan Poosamani

    2015-08-01

    Full Text Available The Internet of Things (IoT paradigm aims to interconnect a variety of heterogeneous Smart Objects (SO using energy-efficient methodologies and standard communication protocols. A majority of consumer devices sold today come equipped with wireless LAN and cellular technology to connect with the world-wide network. To discover Wi-Fi hot spots, there is a need for constant scanning of Wi-Fi radio in these devices and results in significant battery drain. We present PRiSM, a practical system to automatically locate Wi-Fi hotspots while Wi-Fi radio is turned off, by using the statistical characteristics of cellular signals. Cellular signals are received at zero extra cost in mobile devices and hence PRiSM is highly energy-efficient. It is a lightweight client-side only implementation and needs no prior knowledge on floor plans or wireless infrastructure. We implement PRiSM on Android-based devices and show up to 96% of energy savings in Wi-Fi sensing operations which is equivalent to saving up to 16% of total battery capacity, together with an average prediction accuracy of up to 98%.

  16. A Tale of Two Discoveries: Comparing the Usability of Summon and EBSCO Discovery Service

    Science.gov (United States)

    Foster, Anita K.; MacDonald, Jean B.

    2013-01-01

    Web-scale discovery systems are gaining momentum among academic libraries as libraries seek a means to provide their users with a one-stop searching experience. Illinois State University's Milner Library found itself in the unique position of having access to two distinct discovery products, EBSCO Discovery Service and Serials Solutions' Summon.…

  17. PENGUATAN KARAKTER RASA INGIN TAHU DAN PEDULI SOSIAL MELALUI DISCOVERY LEARNING

    Directory of Open Access Journals (Sweden)

    Achmad Fauzi

    2018-01-01

    Full Text Available Efforts to strengthen the character become the basis in the implementation of the curriculum 2013. Application of the 2013 curriculum provides a paradigm shift, which in the end result of learning students not only master the knowledge but also master the attitude and skills. One of the two characters developed is curiosity and social care. To form the character, it needs an educational instrument such as a competent teacher, adequate learning resources, and the most important is the action of learning in the form of approach, model, method, or appropriate learning strategy. So the application of discovery learning model with scientific approach. Which model is effective and efficient in bring up the character of curiosity and social care.   Keywords Curiosity, Social Care, Discovery Learning   http://dx.doi.org/10.17977/um022v2i22017p079

  18. 29 CFR 2200.208 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 9 2010-07-01 2010-07-01 false Discovery. 2200.208 Section 2200.208 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH REVIEW COMMISSION RULES OF PROCEDURE Simplified Proceedings § 2200.208 Discovery. Discovery, including requests for admissions, will only be...

  19. 47 CFR 65.105 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Discovery. 65.105 Section 65.105... OF RETURN PRESCRIPTION PROCEDURES AND METHODOLOGIES Procedures § 65.105 Discovery. (a) Participants... evidence. (c) Discovery requests pursuant to § 65.105(b), including written interrogatories, shall be filed...

  20. 49 CFR 209.313 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Discovery. 209.313 Section 209.313 Transportation... TRANSPORTATION RAILROAD SAFETY ENFORCEMENT PROCEDURES Disqualification Procedures § 209.313 Discovery. (a... parties. Discovery is designed to enable a party to obtain relevant information needed for preparation of...

  1. Quantifying the Ease of Scientific Discovery.

    Science.gov (United States)

    Arbesman, Samuel

    2011-02-01

    It has long been known that scientific output proceeds on an exponential increase, or more properly, a logistic growth curve. The interplay between effort and discovery is clear, and the nature of the functional form has been thought to be due to many changes in the scientific process over time. Here I show a quantitative method for examining the ease of scientific progress, another necessary component in understanding scientific discovery. Using examples from three different scientific disciplines - mammalian species, chemical elements, and minor planets - I find the ease of discovery to conform to an exponential decay. In addition, I show how the pace of scientific discovery can be best understood as the outcome of both scientific output and ease of discovery. A quantitative study of the ease of scientific discovery in the aggregate, such as done here, has the potential to provide a great deal of insight into both the nature of future discoveries and the technical processes behind discoveries in science.

  2. WISE Observations of Comets, Centaurs, & Scattered Disk Objects

    Science.gov (United States)

    Bauer, J.; Walker, R.; Mainzer, A.; Masiero, J.; Grav, T.; Cutri, R.; Dailey, J.; McMillan, R.; Lisse, C. M.; Fernandez, Y. R.; hide

    2011-01-01

    The Wide-Field Infrared Survey Explorer (WISE) was luanched on December 14, 2009. WISE imaged more than 99% of the sky in the mid-infrared for a 9-month mission lifetome. In addition to its primary goals of detecting the most luminous infrared galaxies and the nearest brown dwarfs, WISE, detected over 155500 of solar system bodies, 33700 of which were previously unknown. Most of the new objects were main Belt asteriods, and particular emphasis was on the discovery of Near Earth Asteoids. Hundreds of Jupiter Trojans have been imaged by WISE as well. However a substantial number of Centaurs, Scattered Disc Objects (SDOs), & cometary objects, were observed and discovered.

  3. Creating objectives-based knowledge to resolve organisational change dysfunctionality

    OpenAIRE

    Mendy, John

    2017-01-01

    Lewin’s (1947) tripartite approach seems forgotten and hence to be considered of no value when organisational structures are initiated. Proposals for organisational structures, architectures and staff interactions as the panacea to organisational problems appear to have had limited success (Zack, 2000; Massini, Lewin and Pettigrew, 2001; Feher, 2004 and Garezzi and Terzi, 2005). This raises the question what types of organisational knowledge are wealth-producing. It seems advisable to search ...

  4. Discovery of M class objects among the near-earth asteroid population

    Science.gov (United States)

    Tedesco, Edward F.; Gradie, Jonathan

    1987-01-01

    Broadband colorimetry, visual photometry, near-infrared photometry, and 10 and 20 micron radiometry of the near-earth asteroids (NEAs) 1986 DA and 1986 EB are used to show that these objects belong to the M class of asteroids. The similarity among the distributions of taxonomic classes among the 38 NEAs to the abundances found in the inner astoroid belt between the 3:1 and 5:2 resonances suggests that NEAs have their origins among asteroids in the vicinity of these resonances. The implied mineralogy of 1986 DA and 1986 EB is mostly nickel-iron metal; if this is indeed the case, then current models for meteorite production based on strength-related collisional processes on asteroidal surfaces predict that these two objects alone should produce about one percent of all meteorite falls. Iron meteorites derived from these near-earth asteroids should have low cosmic-ray exposure ages.

  5. Label-assisted mass spectrometry for the acceleration of reaction discovery and optimization

    Science.gov (United States)

    Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.

    2013-05-01

    The identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations, thereby revealing new chemical reactivity. Our strategy is based on labelling one of the reactants with a polyaromatic chemical tag, which selectively undergoes a photoionization/desorption process upon laser irradiation, without the assistance of an external matrix, and enables rapid mass spectrometric detection of any products originating from such labelled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully used for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions.

  6. 15 CFR 280.210 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 280.210 Section 280.210... STANDARDS AND TECHNOLOGY, DEPARTMENT OF COMMERCE ACCREDITATION AND ASSESSMENT PROGRAMS FASTENER QUALITY Enforcement § 280.210 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery...

  7. Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison.

    Science.gov (United States)

    Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S; Sinha, Saurabh

    2011-12-01

    Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, 'enhancers'), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for 'motif-blind' CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to 'supervise' the search. We propose a new statistical method, based on 'Interpolated Markov Models', for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. © The Author(s) 2011. Published by Oxford University Press.

  8. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

  9. Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

    Science.gov (United States)

    Manoharan, Prabu; Vijayan, R S K; Ghoshal, Nanda

    2010-10-01

    The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables (X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

  10. Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

    Science.gov (United States)

    Manoharan, Prabu; Vijayan, R. S. K.; Ghoshal, Nanda

    2010-10-01

    The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables ( X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

  11. Computational discovery of picomolar Q(o) site inhibitors of cytochrome bc1 complex.

    Science.gov (United States)

    Hao, Ge-Fei; Wang, Fu; Li, Hui; Zhu, Xiao-Lei; Yang, Wen-Chao; Huang, Li-Shar; Wu, Jia-Wei; Berry, Edward A; Yang, Guang-Fu

    2012-07-11

    A critical challenge to the fragment-based drug discovery (FBDD) is its low-throughput nature due to the necessity of biophysical method-based fragment screening. Herein, a method of pharmacophore-linked fragment virtual screening (PFVS) was successfully developed. Its application yielded the first picomolar-range Q(o) site inhibitors of the cytochrome bc(1) complex, an important membrane protein for drug and fungicide discovery. Compared with the original hit compound 4 (K(i) = 881.80 nM, porcine bc(1)), the most potent compound 4f displayed 20 507-fold improved binding affinity (K(i) = 43.00 pM). Compound 4f was proved to be a noncompetitive inhibitor with respect to the substrate cytochrome c, but a competitive inhibitor with respect to the substrate ubiquinol. Additionally, we determined the crystal structure of compound 4e (K(i) = 83.00 pM) bound to the chicken bc(1) at 2.70 Å resolution, providing a molecular basis for understanding its ultrapotency. To our knowledge, this study is the first application of the FBDD method in the discovery of picomolar inhibitors of a membrane protein. This work demonstrates that the novel PFVS approach is a high-throughput drug discovery method, independent of biophysical screening techniques.

  12. Peningkatan Hasil Belajar Kompetensi Dasar Mengklasifikasikan Jenis Bisnis Ritel melalui Model Discovery Learning dengan Media Mind Mapping

    Directory of Open Access Journals (Sweden)

    Sri Lestari

    2016-11-01

    Full Text Available This research aimed to determine how is the implementation of discovery learning model with mind mapping media on the basic comptences of clasify kinds of retail business and whether the implementation of the discovery learning model with mind mapping media can increase learning outcomes of student. This research conducted using qualitative approach and quantitative in the planning of class action research by two cycles with research time for every cycle 2 meeting @ 3x45 minute. The result showed that by using discovery learning model with mind mapping media learning outcomes of student was good in the aspect of knowledge, skill, and the attitude have increased. Abstrak : Penelitian ini bertujuan untuk mengetahui bagaimana penerapan model discovery learning dengan menggunakan media mind mapping pada kompetensi dasar mengklasifikasikan jenis bisnis ritel dan apakah penerapan model discovery learning dengan menggunakan media mind mapping dapat meningkatkan hasil belajar siswa. Penelitian dilakukan dengan pendekatan kualitatif dan kuantitatif dalam rancangan penelitian tindakan kelas dengan dua siklus dengan waktu penelitian untuk masing-masing siklus 2 pertemuan @ 3 x 45 menit.  yang hasilnya menunjukkan bahwa melalui penggunaan model discovery learning dengan media mind mapping hasil belajar siswa baik dalam ranah pengetahuan, ketrampilan, maupun sikap mengalami peningkatan.

  13. 10 CFR 1013.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Discovery. 1013.21 Section 1013.21 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) PROGRAM FRAUD CIVIL REMEDIES AND PROCEDURES § 1013.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and...

  14. 37 CFR 2.120 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Discovery. 2.120 Section 2... COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Procedure in Inter Partes Proceedings § 2.120 Discovery. (a... to disclosure and discovery shall apply in opposition, cancellation, interference and concurrent use...

  15. 46 CFR 550.502 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 9 2010-10-01 2010-10-01 false Discovery. 550.502 Section 550.502 Shipping FEDERAL... Proceedings § 550.502 Discovery. The Commission may authorize a party to a proceeding to use depositions, written interrogatories, and discovery procedures that, to the extent practicable, are in conformity with...

  16. 15 CFR 785.8 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Discovery. 785.8 Section 785.8... INDUSTRY AND SECURITY, DEPARTMENT OF COMMERCE ADDITIONAL PROTOCOL REGULATIONS ENFORCEMENT § 785.8 Discovery. (a) General. The parties are encouraged to engage in voluntary discovery regarding any matter, not...

  17. 22 CFR 35.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 35.21 Section 35.21 Foreign Relations DEPARTMENT OF STATE CLAIMS AND STOLEN PROPERTY PROGRAM FRAUD CIVIL REMEDIES § 35.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for...

  18. 45 CFR 96.65 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 1 2010-10-01 2010-10-01 false Discovery. 96.65 Section 96.65 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION BLOCK GRANTS Hearing Procedure § 96.65 Discovery. The use of interrogatories, depositions, and other forms of discovery shall not be allowed. ...

  19. 49 CFR 31.21 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 1 2010-10-01 2010-10-01 false Discovery. 31.21 Section 31.21 Transportation Office of the Secretary of Transportation PROGRAM FRAUD CIVIL REMEDIES § 31.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and...

  20. 43 CFR 4.1130 - Discovery methods.

    Science.gov (United States)

    2010-10-01

    ... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Discovery methods. 4.1130 Section 4.1130... Special Rules Applicable to Surface Coal Mining Hearings and Appeals Discovery § 4.1130 Discovery methods. Parties may obtain discovery by one or more of the following methods— (a) Depositions upon oral...

  1. Discovery machines accelerators for science, technology, health and innovation

    CERN Document Server

    Australian Academy of Sciences

    2016-01-01

    Discovery machines: Accelerators for science, technology, health and innovation explores the science of particle accelerators, the machines that supercharge our ability to discover the secrets of nature and have opened up new tools in medicine, energy, manufacturing, and the environment as well as in pure research. Particle accelerators are now an essential ingredient in discovery science because they offer new ways to analyse the world, such as by probing objects with high energy x-rays or colliding them beams of electrons. They also have a huge—but often unnoticed—impact on all our lives; medical imaging, cancer treatment, new materials and even the chips that power our phones and computers have all been transformed by accelerators of various types. Research accelerators also provide fundamental infrastructure that encourages better collaboration between international and domestic scientists, organisations and governments.

  2. A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.

    Directory of Open Access Journals (Sweden)

    Yunierkis Perez-Castillo

    Full Text Available Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents.

  3. Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

    Science.gov (United States)

    Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

    2016-09-01

    In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

  4. 6 CFR 13.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Discovery. 13.21 Section 13.21 Domestic Security DEPARTMENT OF HOMELAND SECURITY, OFFICE OF THE SECRETARY PROGRAM FRAUD CIVIL REMEDIES § 13.21 Discovery. (a) In general. (1) The following types of discovery are authorized: (i) Requests for production of...

  5. 45 CFR 99.23 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 1 2010-10-01 2010-10-01 false Discovery. 99.23 Section 99.23 Public Welfare... DEVELOPMENT FUND Hearing Procedures § 99.23 Discovery. The Department, the Lead Agency, and any individuals or groups recognized as parties shall have the right to conduct discovery (including depositions) against...

  6. 20 CFR 355.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Discovery. 355.21 Section 355.21 Employees... UNDER THE PROGRAM FRAUD CIVIL REMEDIES ACT OF 1986 § 355.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and copying; (2) Requests...

  7. 10 CFR 2.1018 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 1 2010-01-01 2010-01-01 false Discovery. 2.1018 Section 2.1018 Energy NUCLEAR REGULATORY... Geologic Repository § 2.1018 Discovery. (a)(1) Parties, potential parties, and interested governmental participants in the high-level waste licensing proceeding may obtain discovery by one or more of the following...

  8. 28 CFR 71.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Discovery. 71.21 Section 71.21 Judicial... REMEDIES ACT OF 1986 Implementation for Actions Initiated by the Department of Justice § 71.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for...

  9. 13 CFR 134.310 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Discovery. 134.310 Section 134.310 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION RULES OF PROCEDURE GOVERNING CASES BEFORE THE... Designations § 134.310 Discovery. Discovery will not be permitted in appeals from size determinations or NAICS...

  10. 34 CFR 33.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 34 Education 1 2010-07-01 2010-07-01 false Discovery. 33.21 Section 33.21 Education Office of the Secretary, Department of Education PROGRAM FRAUD CIVIL REMEDIES ACT § 33.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and copying...

  11. 28 CFR 18.7 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Discovery. 18.7 Section 18.7 Judicial Administration DEPARTMENT OF JUSTICE OFFICE OF JUSTICE PROGRAMS HEARING AND APPEAL PROCEDURES § 18.7 Discovery.... Such order may be entered upon a showing that the deposition is necessary for discovery purposes, and...

  12. 7 CFR 1.322 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 1 2010-01-01 2010-01-01 false Discovery. 1.322 Section 1.322 Agriculture Office of... Under the Program Fraud Civil Remedies Act of 1986 § 1.322 Discovery. (a) The following types of discovery are authorized: (1) Requests for production, inspection and photocopying of documents; (2...

  13. 45 CFR 1386.103 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Discovery. 1386.103 Section 1386.103 Public... Hearing Procedures § 1386.103 Discovery. The Department and any party named in the Notice issued pursuant to § 1386.90 has the right to conduct discovery (including depositions) against opposing parties as...

  14. 45 CFR 79.21 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 1 2010-10-01 2010-10-01 false Discovery. 79.21 Section 79.21 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION PROGRAM FRAUD CIVIL REMEDIES § 79.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for...

  15. 12 CFR 308.520 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Discovery. 308.520 Section 308.520 Banks and... PROCEDURE Program Fraud Civil Remedies and Procedures § 308.520 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and copying; (2) Requests...

  16. 47 CFR 1.729 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Discovery. 1.729 Section 1.729..., and Reports Involving Common Carriers Formal Complaints § 1.729 Discovery. (a) Subject to paragraph (i... seek discovery of any non-privileged matter that is relevant to the material facts in dispute in the...

  17. 7 CFR 283.12 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 4 2010-01-01 2010-01-01 false Discovery. 283.12 Section 283.12 Agriculture... of $50,000 or More § 283.12 Discovery. (a) Dispositions—(1) Motion for taking deposition. Only upon a... exist if the information sought appears reasonably calculated to lead to the discovery of admissible...

  18. Knowledge and Cognitive Process Dimensions of Technology Teachers' Lesson Objectives

    Science.gov (United States)

    Mathumbu, David; Rauscher, Willem; Braun, Max

    2014-01-01

    A clearly stated lesson objective is considered an essential component of a well-planned lesson. Many teachers of Technology, a relatively new subject in South African schools, teach Technology with rather limited training both in content and methodological approaches. This study sought to investigate and classify lesson objectives framed or…

  19. A New Perspective on Knowledge Metaphorical Analysis: Knowledge as a Field

    Directory of Open Access Journals (Sweden)

    Constantin BRATIANU

    2010-01-01

    Full Text Available The purpose of this paper is to present a new perspective on knowledge metaphorical analysis: knowledge as a field. The concept of field is taken from physics, where it is defined as an intangible continuum of forces generated by a specific tangible object. This perspective overcomes the limits of the previous interpretations of knowledge as stuff or flow, especially the limits of substantiality and linearity. In the new perspective knowledge is conceived as a nonsubstantial entity, nonuniform, nonhomogeneous and nonlinear. Thus, we open new opportunities for understanding knowledge and its organizational dynamics.

  20. A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

    International Nuclear Information System (INIS)

    Best, William M. J.; Liu, Michael C.; Magnier, Eugene A.; Aller, Kimberly M.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Morgan, J. S.; Tonry, J. L.; Wainscoat, R. J.; Deacon, Niall R.; Dupuy, Trent J.; Redstone, Joshua; Price, P. A.

    2013-01-01

    We present initial results from a wide-field (30,000 deg 2 ) search for L/T transition brown dwarfs within 25 pc using the Pan-STARRS1 and Wide-field Infrared Survey Explorer (WISE) surveys. Previous large-area searches have been incomplete for L/T transition dwarfs, because these objects are faint in optical bands and have near-infrared (near-IR) colors that are difficult to distinguish from background stars. To overcome these obstacles, we have cross-matched the Pan-STARRS1 (optical) and WISE (mid-IR) catalogs to produce a unique multi-wavelength database for finding ultracool dwarfs. As part of our initial discoveries, we have identified seven brown dwarfs in the L/T transition within 9-15 pc of the Sun. The L9.5 dwarf PSO J140.2308+45.6487 and the T1.5 dwarf PSO J307.6784+07.8263 (both independently discovered by Mace et al.) show possible spectroscopic variability at the Y and J bands. Two more objects in our sample show evidence of photometric J-band variability, and two others are candidate unresolved binaries based on their spectra. We expect our full search to yield a well-defined, volume-limited sample of L/T transition dwarfs that will include many new targets for study of this complex regime. PSO J307.6784+07.8263 in particular may be an excellent candidate for in-depth study of variability, given its brightness (J = 14.2 mag) and proximity (11 pc)

  1. 42 CFR 1005.7 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 5 2010-10-01 2010-10-01 false Discovery. 1005.7 Section 1005.7 Public Health... OF EXCLUSIONS, CIVIL MONEY PENALTIES AND ASSESSMENTS § 1005.7 Discovery. (a) A party may make a... and any forms of discovery, other than those permitted under paragraph (a) of this section, are not...

  2. 29 CFR 1603.210 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 4 2010-07-01 2010-07-01 false Discovery. 1603.210 Section 1603.210 Labor Regulations... GOVERNMENT EMPLOYEE RIGHTS ACT OF 1991 Hearings § 1603.210 Discovery. (a) Unless otherwise ordered by the administrative law judge, discovery may begin as soon as the complaint has been transmitted to the administrative...

  3. 45 CFR 150.435 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 1 2010-10-01 2010-10-01 false Discovery. 150.435 Section 150.435 Public Welfare... AND INDIVIDUAL INSURANCE MARKETS Administrative Hearings § 150.435 Discovery. (a) The parties must identify any need for discovery from the opposing party as soon as possible, but no later than the time for...

  4. 34 CFR 81.16 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 34 Education 1 2010-07-01 2010-07-01 false Discovery. 81.16 Section 81.16 Education Office of the... Discovery. (a) The parties to a case are encouraged to exchange relevant documents and information voluntarily. (b) The ALJ, at a party's request, may order compulsory discovery described in paragraph (c) of...

  5. 29 CFR 1905.25 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 5 2010-07-01 2010-07-01 false Discovery. 1905.25 Section 1905.25 Labor Regulations... OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 Hearings § 1905.25 Discovery. (a) Depositions. (1) For reasons of... discovery. Whenever appropriate to a just disposition of any issue in a hearing, the presiding hearing...

  6. 12 CFR 1780.26 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Discovery. 1780.26 Section 1780.26 Banks and... OF PRACTICE AND PROCEDURE RULES OF PRACTICE AND PROCEDURE Prehearing Proceedings § 1780.26 Discovery. (a) Limits on discovery. Subject to the limitations set out in paragraphs (b), (d), and (e) of this...

  7. 45 CFR 160.516 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 1 2010-10-01 2010-10-01 false Discovery. 160.516 Section 160.516 Public Welfare... ADMINISTRATIVE REQUIREMENTS Procedures for Hearings § 160.516 Discovery. (a) A party may make a request to... forms of discovery, other than those permitted under paragraph (a) of this section, are not authorized...

  8. 42 CFR 430.86 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 4 2010-10-01 2010-10-01 false Discovery. 430.86 Section 430.86 Public Health... Plans and Practice to Federal Requirements § 430.86 Discovery. CMS and any party named in the notice issued under § 430.70 has the right to conduct discovery (including depositions) against opposing parties...

  9. Pouw, Wassenburg, de Koning, Hostetter, & Paas (unpublished preprint; Version 2). Does Gesture Strengthen Sensorimotor Knowledge of Objects? The Case of the Size-Weight Illusion

    OpenAIRE

    Paas, Fred; De Koning, Bjorn; Pouw, Wim; Hostetter, Autumn; Wassenburg, Stephanie

    2018-01-01

    Co-speech gestures have been proposed to strengthen sensorimotor knowledge related to objects’ weight and manipulability. In this pre-registered study (N =159) designed to provide a robust, direct, and detailed test of this proposal, participants practiced a problem-solving task with small and large objects that were designed to induce a size-weight illusion (i.e., objects weigh the same but are experienced as different in weight). Participants then explained the task with or without co-speec...

  10. Data mining workflow templates for intelligent discovery assistance in RapidMiner

    OpenAIRE

    Kietz, J U; Serban, F; Bernstein, A; Fischer, S

    2010-01-01

    Knowledge Discovery in Databases (KDD) has evolved during the last years and reached a mature stage offering plenty of operators to solve complex tasks. User support for building workflows, in contrast, has not increased proportionally. The large number of operators available in current KDD systems make it difficult for users to successfully analyze data. Moreover, workflows easily contain a large number of operators and parts of the workflows are applied several times, thus it is hard for us...

  11. Discovery Driven Growth

    DEFF Research Database (Denmark)

    Bukh, Per Nikolaj

    2009-01-01

    Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august......Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august...

  12. 42 CFR 405.1037 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Discovery. 405.1037 Section 405.1037 Public Health... Appeals Under Original Medicare (Part A and Part B) Alj Hearings § 405.1037 Discovery. (a) General rules. (1) Discovery is permissible only when CMS or its contractor elects to participate in an ALJ hearing...

  13. 20 CFR 498.207 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Discovery. 498.207 Section 498.207 Employees... § 498.207 Discovery. (a) For the purpose of inspection and copying, a party may make a request to...) Any form of discovery other than that permitted under paragraph (a) of this section, such as requests...

  14. 42 CFR 93.512 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Discovery. 93.512 Section 93.512 Public Health... Process § 93.512 Discovery. (a) Request to provide documents. A party may only request another party to...) Responses to a discovery request. Within 30 days of receiving a request for the production of documents, a...

  15. 42 CFR 3.516 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Discovery. 3.516 Section 3.516 Public Health PUBLIC... AND PATIENT SAFETY WORK PRODUCT Enforcement Program § 3.516 Discovery. (a) A party may make a request... and any forms of discovery, other than those permitted under paragraph (a) of this section, are not...

  16. 29 CFR 22.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 1 2010-07-01 2010-07-01 true Discovery. 22.21 Section 22.21 Labor Office of the Secretary of Labor PROGRAM FRAUD CIVIL REMEDIES ACT OF 1986 § 22.21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for inspection and copying; (2) Requests...

  17. Featured Image: Revealing Hidden Objects with Color

    Science.gov (United States)

    Kohler, Susanna

    2018-02-01

    Stunning color astronomical images can often be the motivation for astronomers to continue slogging through countless data files, calculations, and simulations as we seek to understand the mysteries of the universe. But sometimes the stunning images can, themselves, be the source of scientific discovery. This is the case with the below image of Lynds Dark Nebula 673, located in the Aquila constellation, that was captured with the Mayall 4-meter telescope at Kitt Peak National Observatory by a team of scientists led by Travis Rector (University of Alaska Anchorage). After creating the image with a novel color-composite imaging method that reveals faint H emission (visible in red in both images here), Rector and collaborators identified the presence of a dozen new Herbig-Haro objects small cloud patches that are caused when material is energetically flung out from newly born stars. The image adapted above shows three of the new objects, HH 118789, aligned with two previously known objects, HH 32 and 332 suggesting they are driven by the same source. For more beautiful images and insight into the authors discoveries, check out the article linked below!Full view of Lynds Dark Nebula 673. Click for the larger view this beautiful composite image deserves! [T.A. Rector (University of Alaska Anchorage) and H. Schweiker (WIYN and NOAO/AURA/NSF)]CitationT. A. Rector et al 2018 ApJ 852 13. doi:10.3847/1538-4357/aa9ce1

  18. Quantity and structure of word knowledge across adulthood.

    Science.gov (United States)

    Salthouse, Timothy A

    2014-09-01

    Cross-sectional and longitudinal data from moderately large samples of healthy adults confirmed prior findings of age-related declines in measures of the quantity of word knowledge beginning around age 65. Additional analyses were carried out to investigate the interrelations of different types of vocabulary knowledge at various periods in adulthood. Although the organizational structures were similar in adults of different ages, scores on tests with different formats had weaker relations to a higher-order vocabulary construct beginning when adults were in their 60's. The within-person dispersion among different vocabulary test scores was also greater after about 65 years of age. The discovery of quantitative decreases in amount of knowledge occurring at about the same age as qualitative shifts in the structure of knowledge raises the possibility that the two types of changes may be causally linked.

  19. 12 CFR 908.46 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Discovery. 908.46 Section 908.46 Banks and... PRACTICE AND PROCEDURE IN HEARINGS ON THE RECORD Pre-Hearing Proceedings § 908.46 Discovery. (a) Limits on discovery. Subject to the limitations set out in paragraphs (b), (d), and (e) of this section, any party to...

  20. 21 CFR 17.23 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Discovery. 17.23 Section 17.23 Food and Drugs FOOD... HEARINGS § 17.23 Discovery. (a) No later than 60 days prior to the hearing, unless otherwise ordered by the..., depositions, and any forms of discovery, other than those permitted under paragraphs (a) and (e) of this...

  1. Knowledge for Healthcare: the future of health librarianship.

    Science.gov (United States)

    Bryant, Sue Lacey; Stewart, David; Goswami, Louise

    2015-09-01

    Many people are still not receiving the right care. It is imperative for health care librarians to come together around a common vision to achieve Knowledge for Healthcare so that the right knowledge and evidence is used at the right time in the right place. The authors describe five workstreams within a modernisation programme: Service Transformation, Workforce Planning and Development, Quality and Impact, Resource Discovery and Optimising Investment. Communications, engagement and partnership working are central to success. The development framework sets out principles on which to base decisions, and design criteria for transforming services. © 2015 Health Libraries Group.

  2. Consumer knowledge and interest in information about fish

    DEFF Research Database (Denmark)

    Pieniak, Zuzanna; Verbeke, Wim; Brunsø, Karen

    2006-01-01

    . Objective and subjective knowledge, as measured using multi-item constructs, are poorly correlated and actual levels differ strongly between countries. Subjective knowledge is found to be a better predictor of fish consumption frequency than objective knowledge, particularly so among the populations...

  3. Consumer knowledge and interest in information about fish

    DEFF Research Database (Denmark)

    Pieniak, Zuzanna; Verbeke, Wim; Brunsø, Karen

    . Objective and subjective knowledge, as measured using multi-item constructs, are only moderately correlated and actual levels differ strongly between countries. Subjective knowledge is found to be a better predictor of fish consumption frequency than objective knowledge, particularly so among...

  4. Freely Accessible Chemical Database Resources of Compounds for in Silico Drug Discovery.

    Science.gov (United States)

    Yang, JingFang; Wang, Di; Jia, Chenyang; Wang, Mengyao; Hao, GeFei; Yang, GuangFu

    2018-05-07

    In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases are crucial. To the best of our knowledge, this is the first systematic review on this issue. The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review. Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced. In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. The circumstances of minor planet discovery

    International Nuclear Information System (INIS)

    Pilcher, F.

    1989-01-01

    The circumstances of discoveries of minor planets are presented in tabular form. Complete data are given for planets 2125-4044, together with notes pertaining to these planets. Information in the table includes the permanent number; the official name; for planets 330 and forward, the table includes the provisional designation attached to the discovery apparition and the year, month, the day of discovery, and the discovery place

  6. Discovery of a blue whale feeding and nursing ground in southern Chile.

    Science.gov (United States)

    Hucke-Gaete, Rodrigo; Osman, Layla P; Moreno, Carlos A; Findlay, Ken P; Ljungblad, Don K

    2004-05-07

    After the extensive exploitation that reduced the Southern Hemisphere blue whale (Balaenoptera musculus) populations to less than 3% of its original numbers, studies on its recovery have been compounded by the inaccessibility of most populations and the extensive migrations between low and high latitudes, thus ensuring that knowledge about blue whale ecology and status remains limited. We report the recent discovery of, arguably, the most important blue whale feeding and nursing ground known to date in the Southern Hemisphere, which is located near the fjords off southern Chile. Through aerial and marine surveys (n = 7) 47 groups, comprising 153 blue whales including at least 11 mother-calf pairs, were sighted during the austral summer and early autumn of 2003. The implications of this discovery on the biological understanding and conservation of this endangered species are discussed.

  7. On the Detectability of Interstellar Objects Like 1I/'Oumuamua

    Science.gov (United States)

    Ragozzine, Darin

    2018-04-01

    Almost since Oort's 1950 hypothesis of a tenuously bound cloud of comets, planetary formation theorists have realized that the process of planet formation must have ejected very large numbers of planetesimals into interstellar space. Unforunately, these objects are distributed over galactic volumes, while they are only likely to be detectable if they pass within a few AU of Earth, resulting in an incredibly sparse detectable population. Furthermore, hypotheses for the formation and distribution of these bodies allows for uncertainties of orders of magnitude in the expected detection rate: our analysis suggested LSST would discover 0.01-100 objects during its lifetime (Cook et al. 2016). The discovery of 1I/'Oumuamua by a survey less powerful that LSST indicates either a low probability event and/or that properties of this population are on the more favorable end of the spectrum. We revisit the detailed detection analysis of Cook et al. 2016 in light of the detection of 1I/'Oumuamua. We use these results to better understand 1I/'Oumuamua and to update our assessment of future detections of interstellar objects. We highlight some key questions that can be answered only by additional discoveries.

  8. Conocimiento objetivo y subjetivo sobre el VIH/SIDA como predictor del uso de condón en adolescentes Objective and subjective knowledge on HIV/AIDS as predictors of condom use in adolescents

    Directory of Open Access Journals (Sweden)

    Alberto Villaseñor-Sierra

    2003-01-01

    Full Text Available OBJETIVO: Evaluar la asociación de conocimientos objetivo y subjetivo sobre VIH/SIDA con el uso del condón. MATERIAL Y MÉTODOS: Se analizó la base de datos de una encuesta aleatoria, anónima y autoaplicada en 1 410 adolescentes de cuatro estratos socioeconómicos de Guadalajara, Jalisco, México, entre 1995 y 1996. El conocimiento objetivo se evaluó mediante 24 preguntas sobre VIH/SIDA y el "subjetivo" con la pregunta: "¿qué tanto crees conocer sobre el SIDA?" Las variables predictoras del uso del condón se identificaron mediante regresión logística y cálculo de la razón de momios con IC 95%. RESULTADOS: El nivel de conocimiento objetivo fue regular y tuvo diferencias por estratos (pOBJECTIVE: To evaluate the association between objective and subjective knowledge on HIV/AIDS and condom use. MATERIAL AND METHODS: Analysis of a database from an anonymous, self-applied, randomized survey conducted between 1995 and 1996. Study subjects were 1 410 adolescents of four socioeconomic strata from Guadalajara, Mexico. Objective knowledge was assessed with 24 questions regarding HIV/AIDS, and subjective knowledge with the question "how much do you think you know about HIV/AIDS?" The variables associated with condom use were identified using logistic regression analysis and by calculating odds ratios with a 95% confidence interval. RESULTS: The degree of objective knowledge was "average", differentiated by socioeconomic strata (p< 0.001, and was higher in adolescents from medium and high socioeconomic strata (p< 0.008. Regarding subjective knowledge, adolescents from the low, medium, and high socioeconomic strata claimed to know "a little", and the ones from the lowest stratum claimed to know "very little". Condom use was higher in males (35.4%, and in adolescents from high socioeconomic strata (p< 0.005, than in females (15.3% (p< 0.001. Although there was a correlation between objective and subjective knowledge (r = 0.37, p< 0.001, a higher

  9. The search for knowledge and the avoidance of knowledge.

    Science.gov (United States)

    Waska, Robert

    2007-01-01

    In the psychoanalytic setting, patients can develop a strong reaction to the therapeutic opportunity to gain new knowledge about themselves. This reaction to knowledge is manifested in the patient by walling it off, splitting it off, or attacking it and erasing it from one's internal experience. The avoidance of knowledge can be the result of various phantasy states that bring on defensive postures. Knowledge can be experienced as a persecutory threat to be avoided and defended against. Knowledge can also elicit depressive concerns of loss and separation. Issues of dependence and autonomy can be equated with knowledge and therefore learning must be warded off. As a result of any or all of these internal threats, the ego can instigate a moratorium on thinking and creativity, a shutdown on feeling, thinking, and learning. As will be shown in the case material, wanting to know can be offset by a greater defensive need to not know. Through projective identification cycles, knowledge is placed into the analyst and experienced as dangerous, unobtainable, or a gift one deserves to be given rather than earned. The patient in the case example demonstrates a more paranoid experience of knowledge and a more paranoid avoidance of learning and change. When paranoid phantasies drive the patient to destroy object-relational links between self and analyst, the transference becomes colored with the phantasy of knowledge being equal to dangerous dependence that leads to destruction of either self or object. Therefore, curiosity and learning are to be avoided. Change is no longer a safe option. Psychic change can only occur when past and current knowledge are allowed to be part of the ego's selfobject world. In other words, Psychic change is possible when the ego is less restrictive and open to new selfobject experience. Therefore, the ego must tolerate conflicted feelings and thoughts about the self and others for knowledge to be allowable and accessible. This is the core struggle

  10. A MODERN SEARCH FOR WOLF–RAYET STARS IN THE MAGELLANIC CLOUDS. II. A SECOND YEAR OF DISCOVERIES

    Energy Technology Data Exchange (ETDEWEB)

    Massey, Philip; Neugent, Kathryn F. [Lowell Observatory, 1400 W Mars Hill Road, Flagstaff, AZ 86001 (United States); Morrell, Nidia, E-mail: phil.massey@lowell.edu, E-mail: kneugent@lowell.edu, E-mail: nmorrell@lco.cl [Las Campanas Observatory, Carnegie Observatories, Casilla 601, La Serena (Chile)

    2015-07-01

    The numbers and types of evolved massive stars found in nearby galaxies provide an exacting test of stellar evolution models. Because of their proximity and rich massive star populations, the Magellanic Clouds have long served as the linchpins for such studies. Yet the continued accidental discoveries of Wolf–Rayet (WR) stars in these systems demonstrate that our knowledge is not as complete as usually assumed. Therefore, we undertook a multi-year survey for WRs in the Magellanic Clouds. Our results from our first year (reported previously) confirmed nine new LMC WRs. Of these, six were of a type never before recognized, with WN3-type emission combined with O3-type absorption features. Yet these stars are 2–3 mag too faint to be WN3+O3 V binaries. Here we report on the second year of our survey, including the discovery of four more WRs, two of which are also WN3/O3s, plus two “slash” WRs. This brings the total of known LMC WRs to 152, 13 (8.2%) of which were found by our survey, which is now ∼60% complete. We find that the spatial distribution of the WN3/O3s is similar to that of other WRs in the LMC, suggesting that they are descended from the same progenitors. We call attention to the fact that 5 of the 12 known SMC WRs may in fact be similar WN3/O3s rather than the binaries they have often assumed to be. We also discuss our other discoveries: a newly discovered Onfp-type star, and a peculiar emission-line object. Finally, we consider the completeness limits of our survey.

  11. Investigation of the effect of specific knowledge in functional areas of business on information systems analysis and design

    Energy Technology Data Exchange (ETDEWEB)

    Laengle, G.B.

    1988-01-01

    Recent studies on the design of computer-based information systems have indicated that the content of the knowledge base and the reasoning behavior of systems analysts are two important factors in the development of computer-based, information systems. This study focuses on knowledge that relates to a specific functional area of business (such as accounting, manufacturing, or marketing) and the effect of the presence or absence of such function-specific domain knowledge on how systems analysts determine information requirements. Determining information requirements is postulated to involve the construction of representations utilizing modeling, discovery, and validation processes. Results indicate that presence of function-specific domain knowledge affected construction of representations as well as modeling, discovery, and validation processes. Subjects with function-specific domain knowledge were found to (1) build representations considering a larger number of facts and concepts relating to the information system's application domain; (2) discover and validate the representations requesting additional domain-specific information more frequently; and (3) model the information system utilizing analogical reasoning more often than subjects without function-specific domain knowledge.

  12. Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs.

    Science.gov (United States)

    Payne, Philip R O; Kwok, Alan; Dhaval, Rakesh; Borlawsky, Tara B

    2009-03-01

    The conduct of large-scale translational studies presents significant challenges related to the storage, management and analysis of integrative data sets. Ideally, the application of methodologies such as conceptual knowledge discovery in databases (CKDD) provides a means for moving beyond intuitive hypothesis discovery and testing in such data sets, and towards the high-throughput generation and evaluation of knowledge-anchored relationships between complex bio-molecular and phenotypic variables. However, the induction of such high-throughput hypotheses is non-trivial, and requires correspondingly high-throughput validation methodologies. In this manuscript, we describe an evaluation of the efficacy of a natural language processing-based approach to validating such hypotheses. As part of this evaluation, we will examine a phenomenon that we have labeled as "Conceptual Dissonance" in which conceptual knowledge derived from two or more sources of comparable scope and granularity cannot be readily integrated or compared using conventional methods and automated tools.

  13. Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

    Science.gov (United States)

    Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

    2014-01-01

    Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  14. Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Marjan Radi

    2014-01-01

    Full Text Available Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  15. Toxins and drug discovery.

    Science.gov (United States)

    Harvey, Alan L

    2014-12-15

    Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

  16. Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

    Energy Technology Data Exchange (ETDEWEB)

    Gebhardt, Thomas, E-mail: gebhardt@mch.rwth-aachen.de; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

    2012-06-30

    This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition-structure-property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

  17. Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

    International Nuclear Information System (INIS)

    Gebhardt, Thomas; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

    2012-01-01

    This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition–structure–property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

  18. mHealth Visual Discovery Dashboard.

    Science.gov (United States)

    Fang, Dezhi; Hohman, Fred; Polack, Peter; Sarker, Hillol; Kahng, Minsuk; Sharmin, Moushumi; al'Absi, Mustafa; Chau, Duen Horng

    2017-09-01

    We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do - in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking.

  19. Scout: orbit analysis and hazard assessment for NEOCP objects

    Science.gov (United States)

    Farnocchia, Davide; Chesley, Steven R.; Chamberlin, Alan B.

    2016-10-01

    It typically takes a few days for a newly discovered asteroid to be officially recognized as a real object. During this time, the tentative discovery is published on the Minor Planet Center's Near-Earth Object Confirmation Page (NEOCP) until additional observations confirm that the object is a real asteroid rather than an observational artifact or an artificial object. Also, NEOCP objects could have a limited observability window and yet be scientifically interesting, e.g., radar and lightcurve targets, mini-moons (temporary Earth captures), mission accessible targets, close approachers or even impactors. For instance, the only two asteroids discovered before an impact, 2008 TC3 and 2014 AA, both reached the Earth less than a day after discovery. For these reasons we developed Scout, an automated system that provides an orbital and hazard assessment for NEOCP objects within minutes after the observations are available. Scout's rapid analysis increases the chances of securing the trajectory of interesting NEOCP objects before the ephemeris uncertainty grows too large or the observing geometry becomes unfavorable. The generally short observation arcs, perhaps only a few hours or even less, lead severe degeneracies in the orbit estimation process. To overcome these degeneracies Scout relies on systematic ranging, a technique that derives possible orbits by scanning a grid in the poorly constrained space of topocentric range and range rate, while the plane-of-sky position and motion are directly tied to the recorded observations. This scan allows us to derive a distribution of the possible orbits and in turn identify the NEOCP objects of most interest to prioritize followup efforts. In particular, Scout ranks objects according to the likelihood of an impact, estimates the close approach distance, the Earth-relative minimum orbit intersection distance and v-infinity, and computes scores to identify objects more likely to be an NEO, a km-sized NEO, a Potentially

  20. Objective Ventricle Segmentation in Brain CT with Ischemic Stroke Based on Anatomical Knowledge

    Directory of Open Access Journals (Sweden)

    Xiaohua Qian

    2017-01-01

    Full Text Available Ventricle segmentation is a challenging technique for the development of detection system of ischemic stroke in computed tomography (CT, as ischemic stroke regions are adjacent to the brain ventricle with similar intensity. To address this problem, we developed an objective segmentation system of brain ventricle in CT. The intensity distribution of the ventricle was estimated based on clustering technique, connectivity, and domain knowledge, and the initial ventricle segmentation results were then obtained. To exclude the stroke regions from initial segmentation, a combined segmentation strategy was proposed, which is composed of three different schemes: (1 the largest three-dimensional (3D connected component was considered as the ventricular region; (2 the big stroke areas were removed by the image difference methods based on searching optimal threshold values; (3 the small stroke regions were excluded by the adaptive template algorithm. The proposed method was evaluated on 50 cases of patients with ischemic stroke. The mean Dice, sensitivity, specificity, and root mean squared error were 0.9447, 0.969, 0.998, and 0.219 mm, respectively. This system can offer a desirable performance. Therefore, the proposed system is expected to bring insights into clinic research and the development of detection system of ischemic stroke in CT.