WorldWideScience

Sample records for knowledge discovery object

  1. A knowledge discovery object model API for Java

    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.

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

    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

  3. Knowledge discovery from data streams

    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,

  4. Discovery simulations and the assessment of intuitive knowledge

    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

  5. Knowledge Discovery from Vibration Measurements

    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.

  6. Object Knowledge Modulates Colour Appearance

    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.

  7. Object knowledge modulates colour appearance

    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

  8. Energy-Water Nexus Knowledge Discovery Framework

    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

  9. Knowledge discovery in the prediction of bankruptcy

    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,

  10. Rough – Granular Computing knowledge discovery models

    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.

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

    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.

  12. 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

    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.

  13. Knowledge management and Discovery for advanced Enterprise Knowledge Engineering

    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...

  14. Bioenergy Knowledge Discovery Framework Fact Sheet

    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.

  15. Knowledge Discovery in Data in Construction Projects

    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.

  16. Advances in knowledge discovery in databases

    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.  

  17. Asymmetric threat data mining and knowledge discovery

    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.

  18. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    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...

  19. Evaluating the inverse reasoning account of object discovery.

    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.

  20. Knowledge transfer objects and innovation performance

    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...

  1. Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

    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...

  2. 08471 Report -- Geographic Privacy-Aware Knowledge Discovery and Delivery

    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...

  3. Data mining and knowledge discovery technologies

    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...

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

    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

  5. Biomarker Gene Signature Discovery Integrating Network Knowledge

    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.

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

    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.

  7. Incremental Knowledge Discovery in Social Media

    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…

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

    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

  9. 4th International conference on Knowledge Discovery and Data Mining

    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.

  10. Learning object repositories as knowledge management systems

    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.

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

    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...

  12. Enhancing Big Data Value Using Knowledge Discovery Techniques

    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...

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

    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

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

    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.

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

    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.

  16. NEOview: Near Earth Object Data Discovery and Query

    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.

  17. Exploiting core knowledge for visual object recognition.

    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).

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

    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.

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

    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. Knowledge discovery in variant databases using inductive logic programming.

    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/.

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

    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.

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

    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...

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

    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.

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

    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

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

    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

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

    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.

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

    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. Network-based approaches to climate knowledge discovery

    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.

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

    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.

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

    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…

  11. Intelligent Discovery for Learning Objects Using Semantic Web Technologies

    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…

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

  17. The Role of Knowledge Objects in Participatory Ergonomics Simulation

    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...

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

    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.

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

    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. Knowledge discovery for pancreatic cancer using inductive logic programming.

    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.

  1. Context-aware pattern discovery for moving object trajectories

    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.

  2. 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.

    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)

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

    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

  4. The objectivity of local knowledge. Lessons from ethnobiology

    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

  5. The Objectivity of Local Knowledge: Lessons From Ethnobiology

    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

  6. OKBL: A language for representing object oriented knowledge

    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. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    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.

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

    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...

  9. Knowledge-based simulation using object-oriented programming

    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.

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

    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.

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

    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.

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

    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

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

    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.

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

    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.

  15. Automated cell type discovery and classification through knowledge transfer

    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. Knowledge discovery based on experiential learning corporate culture management

    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.

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

    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

  18. Knowledge driven discovery for opportunistic IoT networking.

    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...

  19. Formal concept analysis in knowledge discovery: A survey

    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. Knowledge Discovery and Pavement Performance : Intelligent Data Mining

    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

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

    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.

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

    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.

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

    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...

  4. Process Knowledge Discovery Using Sparse Principal Component Analysis

    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...

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

    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.

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

    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.

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

    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

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

    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.

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

    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.

  10. Knowledge Discovery in Spectral Data by Means of Complex Networks

    Stefano Boccaletti

    2013-03-01

    Full Text Available In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

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

    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.

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

    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.

  13. Knowledge discovery in cardiology: A systematic literature review.

    Kadi, I; Idri, A; Fernandez-Aleman, J L

    2017-01-01

    Data mining (DM) provides the methodology and technology needed to transform huge amounts of data into useful information for decision making. It is a powerful process employed to extract knowledge and discover new patterns embedded in large data sets. Data mining has been increasingly used in medicine, particularly in cardiology. In fact, DM applications can greatly benefit all those involved in cardiology, such as patients, cardiologists and nurses. The purpose of this paper is to review papers concerning the application of DM techniques in cardiology so as to summarize and analyze evidence regarding: (1) the DM techniques most frequently used in cardiology; (2) the performance of DM models in cardiology; (3) comparisons of the performance of different DM models in cardiology. We performed a systematic literature review of empirical studies on the application of DM techniques in cardiology published in the period between 1 January 2000 and 31 December 2015. A total of 149 articles published between 2000 and 2015 were selected, studied and analyzed according to the following criteria: DM techniques and performance of the approaches developed. The results obtained showed that a significant number of the studies selected used classification and prediction techniques when developing DM models. Neural networks, decision trees and support vector machines were identified as being the techniques most frequently employed when developing DM models in cardiology. Moreover, neural networks and support vector machines achieved the highest accuracy rates and were proved to be more efficient than other techniques. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

    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.

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

    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

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

    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.

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

    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.

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

    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

  19. Collaborative Cyberinfrastructure: Crowdsourcing of Knowledge and Discoveries (Invited)

    Gay, P.

    2013-12-01

    The design and implementation of programs to crowdsource science presents a unique set of challenges to system architects, programmers, and designers. In this presentation, one solution, CosmoQuest's Citizen Science Builder (CSB), will be discussed. CSB combines a clean user interface with a powerful back end to allow the quick design and deployment of citizen science sites that meet the needs of both the random Joe Public, and the detail driven Albert Professional. In this talk, the software will be overviewed, and the results of usability testing and accuracy testing with both citizen and professional scientists will be discussed. The software is designed to run on one or more LINUX systems running Apache webserver with MySQL and PHP. The interface is HTML5 and relies on javascript and AJAX to provide a dynamic interactive experience. CosmoQuest currently runs on Amazon Web Services and uses VBulletin for logins. The public-facing aspects of CSB provide a uniform experience that allows citizen scientists to use a simple set of tools to achieve a diversity of tasks. This interface presents users with a large view window for data, a toolbar reminiscent of MS Word or Adobe Photoshop with tools from drawing circles or segmented lines, flagging features from a dropdown menu, or marking specific objects with a set marker. The toolbar also allows users to select checkboxes describing the image as a whole. In addition to the viewer and toolbar, volunteers can also access tooltips, examples, and a video tutorial. The scientist interface for CSB gives the science team the ability to prioritize images, download results, create comparison data to validate volunteer data, and also provides access to downloadable tools for doing data analysis. Both these interfaces are controlled through a simple set of config files, although some tasks require customization of the controlling javascript. These are used to point the software at YouTube tutorials, graphics, and the correct

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

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

    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.

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

    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.

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

    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.

  11. Knowledge and Cognitive Process Dimensions of Technology Teachers' Lesson Objectives

    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…

  12. Development of Object and Grasping Knowledge by Robot Exploration

    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...

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

    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.

  14. Objective and Subjective Knowledge and HIV Testing among College Students

    Hou, Su-I

    2004-01-01

    Little research has been conducted on the knowledge domain specifically related to HIV testing among college students. Students (age 18-24) were recruited from a major university in the southeastern United States to participate in a Web-based survey during spring 2003 (N=440). About 21% of the students reported previous voluntary HIV tests.…

  15. Effect of Prior Knowledge of Instructional Objectives on Students ...

    Administrator

    instructional objectives on students' achievement in selected difficult concepts in senior ... nature of science learning in general, and physics learning in particular, as ..... curriculum as perceived by in-service mathematics teachers. Journal of ...

  16. Creating objectives-based knowledge to resolve organisational change dysfunctionality

    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 ...

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

    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

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

    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

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

    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.

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

    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.

  1. Knowledge Sharing in Construction Partnering - Redundancy, Boundary Objects and Brokers

    Koch, Christian; Thuesen, Christian Langhoff

    2013-01-01

    common assignment of meaning, brokers (e.g. design managers), boundary objects (e.g. drawings) and arenas (e.g. meetings). The paper presents an ethnographic case study of a project partnership between engineers, architects and contractors in construction using the partnering concept. The focus is on two...

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

    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

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

    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

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

    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.

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

    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

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

    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.

  7. Nuclear knowledge dissemination in Syria: An INIS objective

    Al-Hallack, R.

    2009-01-01

    International Nuclear Information System (INIS) is the world's leading information system on the peaceful uses of nuclear science and technology and it is operated by the International Atomic Energy Agency (IAEA) in Vienna, Austria. An overview of INIS products, services, philosophy and operation is given. INIS hold a database containing over 3 million references increasing at approximately 100,000 references per year and a collection of full text non-conventional, or grey literature that would be hard to obtain elsewhere. INIS national center in Syria is considered as a regional center for INIS inputs preparation. The center is responsible for selecting the relevant nuclear literature produced and published in Syria and preparing the national inputs and send them to INIS Secretariat to be included in the INIS database. The center also provides INIS services and products to users within Syria. Availability of INIS Database on CD-ROMs, which updated monthly, and the internet version, which updated weekly, and the NCL collections are also presented. Finally, translation activity of the center, such as INIS Booklet entitled Presenting INIS , INIS Database Interface, and the INIS Thesaurus into Arabic were mentioned. This was an in-kind contribution from the Atomic Energy Commission of Syria to support the valuable work of the INIS and Nuclear Knowledge Management (NKM) section and will contribute significantly the dissemination of information among the researchers and scientists in the Arab Countries. (author)

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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)

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

    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 in databases of biomechanical variables: application to the sit to stand motor task

    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.

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

    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.

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

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

    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.

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

    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...

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

    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.

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

    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.

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

    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.

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

    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

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

    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...

  9. Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

    Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

    2007-01-01

    With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

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

    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.

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

    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.

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

    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

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

    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.…

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

    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…

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

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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

  1. Discovery of M class objects among the near-earth asteroid population

    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.

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

    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.

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

    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.

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

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

    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

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

    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

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

    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.

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

    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...

  9. Aligning experimental design with bioinformatics analysis to meet discovery research objectives.

    Kane, Michael D

    2002-01-01

    The utility of genomic technology and bioinformatic analytical support to provide new and needed insight into the molecular basis of disease, development, and diversity continues to grow as more research model systems and populations are investigated. Yet deriving results that meet a specific set of research objectives requires aligning or coordinating the design of the experiment, the laboratory techniques, and the data analysis. The following paragraphs describe several important interdependent factors that need to be considered to generate high quality data from the microarray platform. These factors include aligning oligonucleotide probe design with the sample labeling strategy if oligonucleotide probes are employed, recognizing that compromises are inherent in different sample procurement methods, normalizing 2-color microarray raw data, and distinguishing the difference between gene clustering and sample clustering. These factors do not represent an exhaustive list of technical variables in microarray-based research, but this list highlights those variables that span both experimental execution and data analysis. Copyright 2001 Wiley-Liss, Inc.

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

    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.

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

    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...

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

    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

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

    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.

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

    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.

  15. 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

    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...

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

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

    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.

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

    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.

  19. 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.

    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

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

    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.

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

    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.

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

    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.

  3. Architectural Knowledge Discovery with Latent Semantic Analysis: Constructing a Reading Guide for Software Product Audits

    de Boer, R.C.; van Vliet, H.

    2008-01-01

    Architectural knowledge is reflected in various artifacts of a software product. In a software product audit this architectural knowledge needs to be uncovered and its effects assessed in order to evaluate the quality of the software product. A particular problem is to find and comprehend the

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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

  10. Acts of Discovery: Using Collaborative Research to Mobilize and Generate Knowledge about Visual Arts Teaching Practice

    Mitchell, Donna Mathewson

    2014-01-01

    Visual arts teachers engage in complex work on a daily basis. This work is informed by practical knowledge that is rarely examined or drawn on in research or in the development of policy. Focusing on the work of secondary visual arts teachers, this article reports on a research program conducted in a regional area of New South Wales, Australia.…

  11. Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

    Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen; Zhang, Jun Jason; Gao, Tianlu; Muljadi, Eduard

    2016-11-21

    In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.

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

    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.

  13. Text mining for literature review and knowledge discovery in cancer risk assessment and research.

    Anna Korhonen

    Full Text Available Research in biomedical text mining is starting to produce technology which can make information in biomedical literature more accessible for bio-scientists. One of the current challenges is to integrate and refine this technology to support real-life scientific tasks in biomedicine, and to evaluate its usefulness in the context of such tasks. We describe CRAB - a fully integrated text mining tool designed to support chemical health risk assessment. This task is complex and time-consuming, requiring a thorough review of existing scientific data on a particular chemical. Covering human, animal, cellular and other mechanistic data from various fields of biomedicine, this is highly varied and therefore difficult to harvest from literature databases via manual means. Our tool automates the process by extracting relevant scientific data in published literature and classifying it according to multiple qualitative dimensions. Developed in close collaboration with risk assessors, the tool allows navigating the classified dataset in various ways and sharing the data with other users. We present a direct and user-based evaluation which shows that the technology integrated in the tool is highly accurate, and report a number of case studies which demonstrate how the tool can be used to support scientific discovery in cancer risk assessment and research. Our work demonstrates the usefulness of a text mining pipeline in facilitating complex research tasks in biomedicine. We discuss further development and application of our technology to other types of chemical risk assessment in the future.

  14. In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids

    Birgit Viira

    2016-06-01

    Full Text Available Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

  15. In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids.

    Viira, Birgit; Gendron, Thibault; Lanfranchi, Don Antoine; Cojean, Sandrine; Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Maes, Louis; Maran, Uko; Loiseau, Philippe M; Davioud-Charvet, Elisabeth

    2016-06-29

    Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

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

    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

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

    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

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

    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

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

    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)

  20. Objectivity

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  1. The data bonanza improving knowledge discovery in science, engineering, and business

    Atkinson, Malcolm; Brezany, Peter; Corcho, Oscar; Galea, Michelle; Parsons, Mark; Snelling, David; van Hemert, Jano

    2013-01-01

    Complete guidance for mastering the tools and techniques of the digital revolution With the digital revolution opening up tremendous opportunities in many fields, there is a growing need for skilled professionals who can develop data-intensive systems and extract information and knowledge from them. This book frames for the first time a new systematic approach for tackling the challenges of data-intensive computing, providing decision makers and technical experts alike with practical tools for dealing with our exploding data collections. Emphasizing data-intensive thinking an

  2. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    Roco, Mihail C.; Bainbridge, William S.

    2013-09-01

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  3. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    Roco, Mihail C.; Bainbridge, William S.

    2013-01-01

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  4. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    Roco, Mihail C., E-mail: mroco@nsf.gov; Bainbridge, William S. [National Science Foundation (United States)

    2013-09-15

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  5. Selection of entropy-measure parameters for knowledge discovery in heart rate variability data.

    Mayer, Christopher C; Bachler, Martin; Hörtenhuber, Matthias; Stocker, Christof; Holzinger, Andreas; Wassertheurer, Siegfried

    2014-01-01

    Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical

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

    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

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

    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.

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

    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.

  9. The Adam and Eve Robot Scientists for the Automated Discovery of Scientific Knowledge

    King, Ross

    A Robot Scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scientific experimentation. A Robot Scientist can automatically execute cycles of hypothesis formation, selection of efficient experiments to discriminate between hypotheses, execution of experiments using laboratory automation equipment, and analysis of results. The motivation for developing Robot Scientists is to better understand science, and to make scientific research more efficient. The Robot Scientist `Adam' was the first machine to autonomously discover scientific knowledge: both form and experimentally confirm novel hypotheses. Adam worked in the domain of yeast functional genomics. The Robot Scientist `Eve' was originally developed to automate early-stage drug development, with specific application to neglected tropical disease such as malaria, African sleeping sickness, etc. We are now adapting Eve to work with on cancer. We are also teaching Eve to autonomously extract information from the scientific literature.

  10. Data mining and knowledge discovery for big data methodologies, challenge and opportunities

    2014-01-01

    The field of data mining has made significant and far-reaching advances over the past three decades.  Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease.  Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining da...

  11. Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

    O' Leary, Patrick [Kitware, Inc., Clifton Park, NY (United States)

    2017-09-13

    The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.

  12. Wi-Fi Hotspot Auto-Discovery: A Practical & Energy-Aware System for Smart Objects using Cellular Signals

    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%.

  13. Hackathons as a means of accelerating scientific discoveries and knowledge transfer.

    Ghouila, Amel; Siwo, Geoffrey Henry; Entfellner, Jean-Baka Domelevo; Panji, Sumir; Button-Simons, Katrina A; Davis, Sage Zenon; Fadlelmola, Faisal M; Ferdig, Michael T; Mulder, Nicola

    2018-05-01

    Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions. © 2018 Ghouila et al.; Published by Cold Spring Harbor Laboratory Press.

  14. BEST: Next-Generation Biomedical Entity Search Tool for Knowledge Discovery from Biomedical Literature.

    Sunwon Lee

    Full Text Available As the volume of publications rapidly increases, searching for relevant information from the literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced search tool that directly returns relevant biomedical entities such as targets, drugs, and mutations rather than a long list of articles. Some existing tools submit a query to PubMed and process retrieved abstracts to extract information at query time, resulting in a slow response time and limited coverage of only a fraction of the PubMed corpus. Other tools preprocess the PubMed corpus to speed up the response time; however, they are not constantly updated, and thus produce outdated results. Further, most existing tools cannot process sophisticated queries such as searches for mutations that co-occur with query terms in the literature. To address these problems, we introduce BEST, a biomedical entity search tool. BEST returns, as a result, a list of 10 different types of biomedical entities including genes, diseases, drugs, targets, transcription factors, miRNAs, and mutations that are relevant to a user's query. To the best of our knowledge, BEST is the only system that processes free text queries and returns up-to-date results in real time including mutation information in the results. BEST is freely accessible at http://best.korea.ac.kr.

  15. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

    Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

    2018-02-01

    A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

  16. Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

    Bethel, Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-07-24

    The primary challenge motivating this team’s work is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who are able to perform analysis only on a small fraction of the data they compute, resulting in the very real likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, an approach that is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by DOE science projects. In large, our objective was produce and enable use of production-quality in situ methods and infrastructure, at scale, on DOE HPC facilities, though we expected to have impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve that objective, we assembled a unique team of researchers consisting of representatives from DOE national laboratories, academia, and industry, and engaged in software technology R&D, as well as engaged in close partnerships with DOE science code teams, to produce software technologies that were shown to run effectively at scale on DOE HPC platforms.

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

    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.

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

    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...

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

    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

  20. Historical knowledge and the search for truth: a reading of subjectivity and objectivity in the duality between subject and object

    Fernando Tadeu Germinatti

    2018-04-01

    Full Text Available The present article presents the systematization of theoretical reflections about the debate of neutrality in the human sciences. From the presentation of the conception of scientific neutrality defended by the positivist perspective, a reflection is made on the relation between researcher and object of historical research and its imbrications to the present day. The focus is on the subjective factor and its decisive contribution to research in human science. Thus, the great epistemological richness contained in subjectivity is demonstrated. The methodology used was a bibliographical study, made from researches in classic works of historical science.

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

    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.

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

    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.

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

    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

  4. Objective Ventricle Segmentation in Brain CT with Ischemic Stroke Based on Anatomical Knowledge

    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.

  5. Architecture and Initial Development of a Digital Library Platform for Computable Knowledge Objects for Health.

    Flynn, Allen J; Bahulekar, Namita; Boisvert, Peter; Lagoze, Carl; Meng, George; Rampton, James; Friedman, Charles P

    2017-01-01

    Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this latency, what is actionable in scientific publications can be encoded to make it computable. We have created a purpose-built digital library platform to hold, manage, and share actionable, computable knowledge for health called the Knowledge Grid Library. Here we present it with its system architecture.

  6. An integrative approach to knowledge transfer and integration: Spanning boundaries through objects, people and processes

    Duijn, M.; Rijnveld, M.

    2008-01-01

    Knowledge transfer and integration is the main challenge in many knowledge management projects. This challenge follows from the observation that it is difficult to determine how and what knowledge may transfer from one person to another, from one team to another and from one network or organization

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

    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.

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

    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.

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

    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.

  10. Mathematical Basis of Knowledge Discovery and Autonomous Intelligent Architectures - Technology for the Creation of Virtual objects in the Real World

    Sokolov, B. V; Kulakov, F. M

    2005-01-01

    .... This project specifically aims at developing the mathematical basis architecture and software techniques implementing particular new technologies to support Global Awareness and comprises six main tasks. Task 6 was: 6...

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

    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.

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

    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.

  13. The Intermediate-mass Young Stellar Object 08576nr292: Discovery of A Disk-Jet System

    Ellerbroek, L.E.; Kaper, L.; Bik, A.; de Koter, A.; Horrobin, M.; Puga, E.; Sana, H.; Waters, L.B.F.M.

    2011-01-01

    We present observations of the embedded massive young stellar object (YSO) candidate 08576nr292, obtained with X-shooter and SINFONI on the ESO Very Large Telescope (VLT). The flux-calibrated, medium-resolution X-shooter spectrum (300–2500 nm) includes over 300 emission lines, but no (photospheric)

  14. Knowledges

    Berling, Trine Villumsen

    2012-01-01

    Scientific knowledge in international relations has generally focused on an epistemological distinction between rationalism and reflectivism over the last 25 years. This chapter argues that this distinction has created a double distinction between theory/reality and theory/practice, which works...... and reflectivism. Bourdieu, on the contrary, lets the challenge to the theory/reality distinction spill over into a challenge to the theory/practice distinction by thrusting the scientist in the foreground as not just a factor (discourse/genre) but as an actor. In this way, studies of IR need to include a focus...... as a ghost distinction structuring IR research. While reflectivist studies have emphasised the impossibility of detached, objective knowledge production through a dissolution of the theory/reality distinction, the theory/practice distinction has been left largely untouched by both rationalism...

  15. Engineering Objects for Collaboration: Strategies of Ambiguity and Clarity at Knowledge Boundaries

    Barley, William C.; Leonardi, Paul M.; Bailey, Diane E.

    2012-01-01

    Prior research suggests that boundary objects gain meaning through group interaction. Drawing from the literature on strategic ambiguity, we explore the possibility that individuals strategically create potential boundary objects in an attempt to shape the meanings that groups develop. From ethnographic observations of automotive engineers, we…

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

    Westerbeek, Hans; Koolen, Ruud; Maes, A.A.

    2015-01-01

    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

  17. Determining the object structure of ecological and economic research and knowledge base for decision support

    Kozulia, T.V.; Kozulia, M.M.

    2017-01-01

    The mathematical model of natural-technogenic objects is substantiated in the article. Natural-technogenic object of research is defined in form of a system model, which includes the economic, ecological and social components and processes system occurring in the selected systems and in their interaction. Basis for introduction systematic analysis methods for consistent problematic environmental safety tasks solution under conditions of uncertainty has been formed. The complex methods system includes entropy theory provisions on the objects state evaluation, the comparator identification method, substantively substantiated for solving complex environment quality assessment problems. An example of ecological state technogenically loaded landscape-geochemical complexes on the proposed methodological support studied in the work.

  18. Pre-Service Teachers' Knowledge and Teaching Comfort Levels for Agricultural Science and Technology Objectives

    Wingenbach, Gary J.; White, Judith McIntosh; Degenhart, Shannon; Pannkuk, Tim; Kujawski, Jenna

    2007-01-01

    Self-efficacy beliefs are defined as context-specific assessments of one's competence to perform specific tasks, influence one's efforts, persistence, and resilience to succeed in a given task. Such beliefs are important determinants when considering agricultural science teachers' subject matter knowledge, teaching comfort levels, and their…

  19. Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings

    Grand, Gabriel; Blank, Idan Asher; Pereira, Francisco; Fedorenko, Evelina

    2018-01-01

    The words of a language reflect the structure of the human mind, allowing us to transmit thoughts between individuals. However, language can represent only a subset of our rich and detailed cognitive architecture. Here, we ask what kinds of common knowledge (semantic memory) are captured by word meanings (lexical semantics). We examine a prominent computational model that represents words as vectors in a multidimensional space, such that proximity between word-vectors approximates semantic re...

  20. Non-invasive dendrochronology of late-medieval objects in Oslo: refinement of a technique and discoveries

    Daly, Aoife; Streeton, Noëlle L. W.

    2017-06-01

    A technique for non-invasive dendrochronological analysis of oak was developed for archaeological material, using an industrial CT scanner. Since 2013, this experience has been extended within the scope of the research project `After the Black Death: Painting and Polychrome Sculpture in Norway'. The source material for the project is a collection of late-medieval winged altarpieces, shrines, polychrome sculpture, and fragments from Norwegian churches, which are owned by the Museum of Cultural History, University of Oslo. The majority cannot be sampled, and many are too large to fit into the CT scanner. For these reasons, a combined approach was adopted, utilizing CT scanning where possible, but preceded by an `exposed-wood' imaging technique. Both non-invasive techniques have yielded reliable results, and CT scanning has confirmed the reliability of the imaging technique alone. This paper presents the analytical methods, along with results from two of the 13 objects under investigation. Results for reliable dates and provenances provide new foundations for historical interpretations.

  1. Usability of Discovery Portals

    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...

  2. Learning to Appraise the Quality of Qualitative Research Articles: A Contextualized Learning Object for Constructing Knowledge

    Chenail, Ronald J.

    2011-01-01

    Helping beginning qualitative researchers critically appraise qualitative research articles is a common learning objective for introductory methodology courses. To aid students in achieving competency in appraising the quality of qualitative research articles, a multi-part activity incorporating the Critical Appraisal Skills Programme's (CASP)…

  3. An integrated approach for visual analysis of a multisource moving objects knowledge base

    Willems, N.; van Hage, W.R.; de Vries, G.; Janssens, J.H.M.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  4. An Integrated Approach for Visual Analysis of a Multi-Source Moving Objects Knowledge Base

    Willems, C.M.E.; van Hage, W.R.; de Vries, G.K.D.; Janssens, J.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  5. An integrated approach for visual analysis of a multi-source moving objects knowledge base

    Willems, N.; Hage, van W.R.; Vries, de G.; Janssens, J.H.M.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  6. Designing Learning Object Repositories as Systems for Managing Educational Communities Knowledge

    Sampson, Demetrios G.; Zervas, Panagiotis

    2013-01-01

    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…

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

    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.

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

    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.

  9. The hollow-face illusion: object-specific knowledge, general assumptions or properties of the stimulus?

    Hill, Harold; Johnston, Alan

    2007-01-01

    The hollow-face illusion, in which a mask appears as a convex face, is a powerful example of binocular depth inversion occurring with a real object under a wide range of viewing conditions. Explanations of the illusion are reviewed and six experiments reported. In experiment 1 the detrimental effect of figural inversion, evidence for the importance of familiarity, was found for other oriented objects. The inversion effect held for masks lit from the side (experiment 2). The illusion was stronger for a mask rotated by 90 degrees lit from its forehead than from its chin, suggesting that familiar patterns of shading enhance the illusion (experiment 2). There were no effects of light source visibility or any left/right asymmetry (experiment 3). In experiments 4-6 we used a 'virtual' hollow face, with illusion strength quantified by the proportion of noise texture needed to eliminate the illusion. Adding characteristic surface colour enhanced the illusion, consistent with the familiar face pigmentation outweighing additional bottom-up cues (experiment 4). There was no difference between perspective and orthographic projection. Photographic negation reduced, but did not eliminate, the illusion, suggesting shading is important but not essential (experiment 5). Absolute depth was not critical, although a shallower mask was given less extreme convexity ratings (experiment 6). We argue that the illusion arises owing to a convexity preference when the raw data have ambiguous interpretations. However, using a familiar object with typical orientation, shading, and pigmentation greatly enhances the effect.

  10. The Emergence of New Successful Export Activities in Argentina: Self-Discovery, Knowledge Niches, or Barriers to Riches?

    Gabriel Sánchez; Ricardo Rozemberg; Inés Butler; Hernán Rufo

    2008-01-01

    This paper examines the emergence of three new successful export activities in Argentina: biotechnology applied to human health, blueberries and chocolate confections. The main interest lies in ascertaining why these sectors/products were targeted, on which previously accumulated capabilities they were built upon, and what type of hurdles they faced and how they were overcome. In the absence of government support for discovery, these new exports emerged because the pioneers could introduce pe...

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

    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...

  12. New knowledge in determining the astronomical orientation of Incas object in Ollantaytambo, Peru

    Hanzalová, K.; Klokočník, J.; Kostelecký, J.

    2014-06-01

    This paper deals about astronomical orientation of Incas objects in Ollantaytambo, which is located about 35 km southeast from Machu Picchu, about 40 km northwest from Cusco, and lies in the Urubamba valley. Everybody writing about Ollantaytambo, shoud read Protzen (1993). He devoted his monograph to description and interpretation of that locality. Book of Salazar and Salazar (2005) deals, among others, with the orientation of objects in Ollantaytambo with respect to the cardinal direction. Zawaski and Malville (2007) documented astronomical context of major monuments of nine sites in Peru, including Ollantaytambo. We tested astronomical orientation in these places and confirm or disprove hypothesis about purpose of Incas objects. For assessment orientation of objects we used our measurements and also satellite images on Google Earth and digital elevation model from ASTER. The satellite images used to approximate estimation of astronomical orientation. The digital elevation model is useful in the mountains, where we need the really horizon for a calculation of sunset and sunrise on specific days (solstices), which were for Incas people very important. By Incas is very famous that they worshiped the Sun. According to him they determined when to plant and when to harvest the crop. In this paper we focused on Temple of the Sun, also known the Wall of six monoliths. We tested which astronomical phenomenon is connected with this Temple. First, we tested winter solstice sunrise and the rides of the Pleiades for the epochs 2000, 1500 and 1000 A.D. According with our results the Temple isn't connected neither with winter solstice sunrise nor with the Pleiades. Then we tested also winter solstice sunset. We tried to use the line from an observation point near ruins of the Temple of Sun, to west-north, in direction to sunset. The astronomical azimuth from this point was about 5° less then we need. From this results we found, that is possible to find another observation

  13. New knowledge in determining the astronomical orientation of Incas object in Ollantaytambo, Peru

    K. Hanzalová

    2014-06-01

    Full Text Available This paper deals about astronomical orientation of Incas objects in Ollantaytambo, which is located about 35 km southeast from Machu Picchu, about 40 km northwest from Cusco, and lies in the Urubamba valley. Everybody writing about Ollantaytambo, shoud read Protzen (1993. He devoted his monograph to description and interpretation of that locality. Book of Salazar and Salazar (2005 deals, among others, with the orientation of objects in Ollantaytambo with respect to the cardinal direction. Zawaski and Malville (2007 documented astronomical context of major monuments of nine sites in Peru, including Ollantaytambo. We tested astronomical orientation in these places and confirm or disprove hypothesis about purpose of Incas objects. For assessment orientation of objects we used our measurements and also satellite images on Google Earth and digital elevation model from ASTER. The satellite images used to approximate estimation of astronomical orientation. The digital elevation model is useful in the mountains, where we need the really horizon for a calculation of sunset and sunrise on specific days (solstices, which were for Incas people very important. By Incas is very famous that they worshiped the Sun. According to him they determined when to plant and when to harvest the crop. In this paper we focused on Temple of the Sun, also known the Wall of six monoliths. We tested which astronomical phenomenon is connected with this Temple. First, we tested winter solstice sunrise and the rides of the Pleiades for the epochs 2000, 1500 and 1000 A.D. According with our results the Temple isn't connected neither with winter solstice sunrise nor with the Pleiades. Then we tested also winter solstice sunset. We tried to use the line from an observation point near ruins of the Temple of Sun, to west-north, in direction to sunset. The astronomical azimuth from this point was about 5° less then we need. From this results we found, that is possible to find another

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

    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.

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

    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.

  16. Knowledge-based object recognition for different morphological classes of plants

    Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.; Megnet, Roland

    1995-01-01

    Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic syshoot. In this paper we describe parts of the vision syshoot that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, shoot, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods. As a result of our work we present rules which help users to create specific algorithms for object recognition of plant species.

  17. Using P300 to Evaluate the Effect of Object Color Knowledge in Novelty Detection

    Mohammad Amin Khoshlessan1

    2010-05-01

    Full Text Available A B S T R A C T Introduction: In an oddball experiment, the context in which novel stimuli are presented affects characteristics of novelty P3, i.e. as long as there is a difficult task in which the difference between standard and target stimuli is small, recurrent presentation of a highly discrepant stimulus can lead to P300 highly similar to novelty P3. Effect of stimulus properties on P300 has also been previously examined and it has been shown that it plays a significant role in P300 topography, its amplitude and latency.Here we have examined the effect of surface color of objects of high color-diagnosticity in a visual oddball paradigm. Methods: In two separate conditions, we used pictures of fruits as target and novel stimuli. In condition one, novel stimuli were pictures of fruits in their canonical colors. In the second condition, novel stimuli were the same photo filtered to have a different non-canonical color. P300 was compared among these conditions. Results: Both target P3 and novelty P3 were detected in the two conditions but no significant difference was evident between conditions.Discussion: This result suggests that comparing to shape information; color cue does not play a significant role in detecting context novelty.

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

    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.

  19. Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

    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.

  20. A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

    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. Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

    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.

  2. A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

    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. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); Deacon, Niall R. [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany); Dupuy, Trent J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Redstone, Joshua [Facebook, 335 Madison Ave, New York, NY 10017-4677 (United States); Price, P. A., E-mail: wbest@ifa.hawaii.edu [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

    2013-11-10

    We present initial results from a wide-field (30,000 deg{sup 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)

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

    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

  4. A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric cancer agents.

    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.

  5. Discovery of a 105-ms X-ray Pulsar in Kesteven-79: On the Nature of Compact Central Objects in Supernova Remnants

    Gotthelf, E. V.; Halpern, J. P.; Seward, F. D.

    2005-01-01

    We report the discovery of 105-ms X-ray pulsations from the compact central object (CCO) in the supernova remnant \\snr\\ using data acquired with the {\\it Newton X-Ray Multi-Mirror Mission). Using two observations of the pulsar taken 6-days apart we derive an upper limit on its spin-down rate of $\\dot P 18.5$-kyr. The latter exceeds the remnant's estimated age, suggesting that the pulsar was born spinning near its current period. The X-ray spectrum of \\psr\\ is best characterized as a blackbody of temperature $kT {BB) =, 0.43\\pm0.02$ keV, radius $R-{BB) \\approx 1.3$-km, and $I{\\rm bol) = 5.2 \\times 10A{33)$ ergs-sSA{-1)$ at $d = 7.1$-kpc. The sinusoidal light curve is modulated with a pulsed fraction of $>45\\%$, suggestive of a small hot spot on the surface of the rotating neutron star. The lack of a discernible pulsar wind nebula is consistent with an interpretation of \\psr\\ as a rotation-powered pulsar whose spin-down luminosity falls below the empirical threshold for generating bright wind nebulae, $\\dot E-{\\rm c) = 4 \\times 10A{36)$-ergs-sSA{-I)$. The age discrepancy suggests that its $\\dot E$ has always been below $\\dot E c$, perhaps a distinguishing property of the CCOs. Alternatively, the X-ray spectrum of \\psr\\ suggests a low-luminosity AXP, but the weak inferred $B-{\\rm p)$ field is incompatible with a magnetar theory of its X-ray luminosity. The ordinary spin parameters discovered from \\psr\\ highlight the inability of existing theories to explain the high luminosities and temperatures of CCO thermal X-ray spectra.

  6. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  7. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  8. Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records [version 2; referees: 2 approved

    Richard Jackson

    2018-05-01

    Full Text Available Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing

  9. Improved Density Based Spatial Clustering of Applications of Noise Clustering Algorithm for Knowledge Discovery in Spatial Data

    Arvind Sharma

    2016-01-01

    Full Text Available There are many techniques available in the field of data mining and its subfield spatial data mining is to understand relationships between data objects. Data objects related with spatial features are called spatial databases. These relationships can be used for prediction and trend detection between spatial and nonspatial objects for social and scientific reasons. A huge data set may be collected from different sources as satellite images, X-rays, medical images, traffic cameras, and GIS system. To handle this large amount of data and set relationship between them in a certain manner with certain results is our primary purpose of this paper. This paper gives a complete process to understand how spatial data is different from other kinds of data sets and how it is refined to apply to get useful results and set trends to predict geographic information system and spatial data mining process. In this paper a new improved algorithm for clustering is designed because role of clustering is very indispensable in spatial data mining process. Clustering methods are useful in various fields of human life such as GIS (Geographic Information System, GPS (Global Positioning System, weather forecasting, air traffic controller, water treatment, area selection, cost estimation, planning of rural and urban areas, remote sensing, and VLSI designing. This paper presents study of various clustering methods and algorithms and an improved algorithm of DBSCAN as IDBSCAN (Improved Density Based Spatial Clustering of Application of Noise. The algorithm is designed by addition of some important attributes which are responsible for generation of better clusters from existing data sets in comparison of other methods.

  10. Objectives, priorities, reliable knowledge, and science-based management of Missouri River interior least terns and piping plovers

    Sherfy, Mark; Anteau, Michael J.; Shaffer, Terry; Sovada, Marsha; Stucker, Jennifer

    2011-01-01

    Supporting recovery of federally listed interior least tern (Sternula antillarum athalassos; tern) and piping plover (Charadrius melodus; plover) populations is a desirable goal in management of the Missouri River ecosystem. Many tools are implemented in support of this goal, including habitat management, annual monitoring, directed research, and threat mitigation. Similarly, many types of data can be used to make management decisions, evaluate system responses, and prioritize research and monitoring. The ecological importance of Missouri River recovery and the conservation status of terns and plovers place a premium on efficient and effective resource use. Efficiency is improved when a single data source informs multiple high-priority decisions, whereas effectiveness is improved when decisions are informed by reliable knowledge. Seldom will a single study design be optimal for addressing all data needs, making prioritization of needs essential. Data collection motivated by well-articulated objectives and priorities has many advantages over studies in which questions and priorities are determined retrospectively. Research and monitoring for terns and plovers have generated a wealth of data that can be interpreted in a variety of ways. The validity and strength of conclusions from analyses of these data is dependent on compatibility between the study design and the question being asked. We consider issues related to collection and interpretation of biological data, and discuss their utility for enhancing the role of science in management of Missouri River terns and plovers. A team of USGS scientists at Northern Prairie Wildlife Research Center has been conducting tern and plover research on the Missouri River since 2005. The team has had many discussions about the importance of setting objectives, identifying priorities, and obtaining reliable information to answer pertinent questions about tern and plover management on this river system. The objectives of this

  11. Discovery and characterization of the first low-peaked and intermediate-peaked BL Lacertae objects in the very high energy {gamma}-ray regime

    Berger, Karsten

    2009-12-19

    20 years after the discovery of the Crab Nebula as a source of very high energy {gamma}-rays, the number of sources newly discovered above 100 GeV using ground-based Cherenkov telescopes has considerably grown, at the time of writing of this thesis to a total of 81. The sources are of different types, including galactic sources such as supernova remnants, pulsars, binary systems, or so-far unidentified accelerators and extragalactic sources such as blazars and radio galaxies. The goal of this thesis work was to search for {gamma}-ray emission from a particular type of blazars previously undetected at very high {gamma}-ray energies, by using the MAGIC telescope. Those blazars previously detected were all of the same type, the so-called high-peaked BL Lacertae objects. The sources emit purely non-thermal emission, and exhibit a peak in their radio-to-X-ray spectral energy distribution at X-ray energies. The entire blazar population extends from these rare, low-luminosity BL Lacertae objects with peaks at X-ray energies to the much more numerous, high-luminosity infrared-peaked radio quasars. Indeed, the low-peaked sources dominate the source counts obtained from space-borne observations at {gamma}-ray energies up to 10 GeV. Their spectra observed at lower {gamma}-ray energies show power-law extensions to higher energies, although theoretical models suggest them to turn over at energies below 100 GeV. This opened the quest for MAGIC as the Cherenkov telescope with the currently lowest energy threshold. In the framework of this thesis, the search was focused on the prominent sources BL Lac, W Comae and S5 0716+714, respectively. Two of the sources were unambiguously discovered at very high energy {gamma}-rays with the MAGIC telescope, based on the analysis of a total of about 150 hours worth of data collected between 2005 and 2008. The analysis of this very large data set required novel techniques for treating the effects of twilight conditions on the data quality

  12. Discovery and characterization of the first low-peaked and intermediate-peaked BL Lacertae objects in the very high energy γ-ray regime

    Berger, Karsten

    2009-01-01

    20 years after the discovery of the Crab Nebula as a source of very high energy γ-rays, the number of sources newly discovered above 100 GeV using ground-based Cherenkov telescopes has considerably grown, at the time of writing of this thesis to a total of 81. The sources are of different types, including galactic sources such as supernova remnants, pulsars, binary systems, or so-far unidentified accelerators and extragalactic sources such as blazars and radio galaxies. The goal of this thesis work was to search for γ-ray emission from a particular type of blazars previously undetected at very high γ-ray energies, by using the MAGIC telescope. Those blazars previously detected were all of the same type, the so-called high-peaked BL Lacertae objects. The sources emit purely non-thermal emission, and exhibit a peak in their radio-to-X-ray spectral energy distribution at X-ray energies. The entire blazar population extends from these rare, low-luminosity BL Lacertae objects with peaks at X-ray energies to the much more numerous, high-luminosity infrared-peaked radio quasars. Indeed, the low-peaked sources dominate the source counts obtained from space-borne observations at γ-ray energies up to 10 GeV. Their spectra observed at lower γ-ray energies show power-law extensions to higher energies, although theoretical models suggest them to turn over at energies below 100 GeV. This opened the quest for MAGIC as the Cherenkov telescope with the currently lowest energy threshold. In the framework of this thesis, the search was focused on the prominent sources BL Lac, W Comae and S5 0716+714, respectively. Two of the sources were unambiguously discovered at very high energy γ-rays with the MAGIC telescope, based on the analysis of a total of about 150 hours worth of data collected between 2005 and 2008. The analysis of this very large data set required novel techniques for treating the effects of twilight conditions on the data quality. This was successfully achieved

  13. Response to traumatic brain injury neurorehabilitation through an artificial intelligence and statistics hybrid knowledge discovery from databases methodology.

    Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María

    2008-01-01

    Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.

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

    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:…

  15. [Rationalities of knowledge production: on transformations of objects, technologies and information in biomedicine and the life sciences].

    Paul, Norbert W

    2009-09-01

    primarily determined by the desire for knowledge but by the desire for relevance. This paper explores in which ways object-driven and hypotheses-driven experimental life-sciences transformed into domains of experimental research evolving in a technologically constructed, data-driven environment in which they are subjected to constant morphing due to the forces of different rationalities.

  16. Discovery Mondays

    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...

  17. Development of an objective mental workload assessment tool based on Rasmussen's skill–rule–knowledge framework

    Chuang Chunyu; Lin Chiuhsiang Joe; Shiang Weijung; Hsieh Tsungling; Lioud Jinliang

    2016-01-01

    It is important to monitor operators' mental workload during the operation phase. Physiological measurement approaches could record the operator's mental data continuously, and might be less interruptive on the work activities. However, these methods often require the attachment of physical sensors, which are not unobtrusive in the physical sense. Furthermore, the individual difference makes calibrating to each individual tedious and requires trained persons to use. Often high noise-to-signal ratio data are hard to analyze. Due to these factors, physiological workload measurements are hardly widely applied in practical fields. In this study, an objective, non-intrusive and performance-based mental workload predictive model was proposed with high validity (R 2 = 0.51), which can be applied during the operation phrase. This model, developed based on the Rasmussen's skill–rule–knowledge framework, is comprised of two novel cognitive indices, the attention required index and uncertainty index. It can be used as the basis for establishing an early online warning system automatically. Furthermore, this model also predicts the types of error-prone tasks. This kind of information is expected to provide managers and supervisors with opportunities to intervene and improve tasks before error occurred. Finally, the predictive model proposed in this paper requires more practical application in fields to be completed. (author)

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

    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.

  19. Rule knowledge aids performance on spatial and object alternation tasks by alcoholic patients with and without Korsakoff’s amnesia

    Fiona J Bardenhagen

    2007-01-01

    Full Text Available Fiona J Bardenhagen1,2, Marlene Oscar-Berman3, Stephen C Bowden2,41School of Psychology, Victoria University, Melbourne, Victoria, Australia; 2Clinical Neurosciences, St. Vincent’s Hospital, Melbourne, Australia; 3Division of Psychiatry and Departments of Neurology and Anatomy and Neurobiology, Boston University School of Medicine; and Psychology Research Service, US Department of Veterans Affairs (VA Healthcare System, Jamaica Plain Campus, MA, USA; 4School of Behavioural Science, University of Melbourne, Parkville, Victoria, AustraliaAbstract: Delayed alternation (DA and object alternation (OA tasks traditionally have been used to measure defective response inhibition associated with dysfunction of frontal brain systems. However, these tasks are also sensitive to nonfrontal lesions, and cognitive processes such as the induction of rule-learning strategies also are needed in order to perform well on these tasks. Performance on DA and OA tasks was explored in 10 patients with alcohol-induced persisting amnestic disorder (Korsakoff’s syndrome, 11 abstinent long-term alcoholics, and 13 healthy non-alcoholic controls under each of two rule provision conditions: Alternation Rule and Correction Rule. Results confirmed that rule knowledge is a crucial cognitive component for solving problems such as DA and OA, and therefore, that errors on these tasks are not due to defective response inhibition alone. Further, rule-induction strategies were helpful to Korsakoff patients, despite their poorer performance on the tasks. These results stress the role of multiple cognitive abilities in successful performance on rule induction tasks. Evidence that these cognitive abilities are served by diffusely distributed neural networks should be considered when interpreting behavioral impairments on these tasks.Keywords: alcoholism, Korsakoff’s syndrome, comparative neuropsychology, perseveration, rule induction, working memory

  20. Volatility Discovery

    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....

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

    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.

  2. Coming to See Objects of Knowledge: Guiding Student Conceptualization through Teacher Embodied Instruction in a Robotics Programming Class

    Kwah, Helen

    2013-01-01

    This thesis explores the questions of how a teacher guides students to see concepts, and the role of gesture and gesture viewpoints in mediating the process of guidance. To examine these questions, two sociocultural theoretical frameworks--Radford's cultural-semiotic theory of knowledge objectification (e.g., 2003), and Goldman's Points of Viewing…

  3. Knowledge transfer in the field of parental mental illness: objectives, effective strategies, indicators of success, and sustainability.

    Lauritzen, Camilla; Reedtz, Charlotte

    2015-01-01

    Mental health problems are often transmitted from one generation to the next. However, transferring knowledge about interventions that reduce intergenerational transmission of disease to the field of parental mental illness has been very difficult. One of the most critical issues in mental health services research is the gap between what is generally known about effective treatment and what is provided to consumers in routine care. In this article we discuss several aspects of knowledge transfer in the field of parental mental illness. Effective strategies and implementation prerequisites are explored, and we also discuss indicators of success and sustainability. Altogether, this article presents a rationale for the importance of preventive strategies for children of mentally ill parents. Furthermore, the discussion shows how complex it is to change clinical practice.

  4. 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-

    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...

  5. Beyond Discovery

    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...

  6. Chemical Discovery

    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)

  7. Pouw, Wassenburg, de Koning, Hostetter, & Paas (unpublished preprint; Version 2). Does Gesture Strengthen Sensorimotor Knowledge of Objects? The Case of the Size-Weight Illusion

    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...

  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

    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. ESTABLISHING THE COMMUNICATION MIX OF TOURISM ORGANIZATIONS BY THE OBJECTIVES COMMUNICATION, THROUGH GRADUALLY KNOWLEDGE OF THE CUSTOMER PROFILE

    Radu Blaga

    2013-12-01

    Full Text Available "Tourism is an industry of communication of the world and for that, it must help educate the world about the need to act consistently ..." (Magazine of the World Tourism Organization "World Tourism Day 2008 - Tourism Will Grow smartly" showed the experts meeting of the Reflections Forum on the occasion of Tourism Days in 2008 to Lima - Peru, with the theme "Short-term responses - Long Term Challenges". Multifunctional character of tourism, addressing it to the markets, namely the public sector, opening new perspectives for cross-disciplinary research focused on the individual and socio-cultural factors. Given the above, this paper aims to define a "pattern of communication" based on the knowledge of the characters of tourism consumer and buying decision process of this sector, developed from The Lavidge & Steiner-model hierarchy effects (model of communication.

  10. Higgs Discovery

    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...

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

    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.

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

    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.

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

    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.

  14. Coming to see objects of knowledge: Guiding student conceptualization through teacher embodied instruction in a robotics programming class

    Kwah, Helen

    This thesis explores the questions of how a teacher guides students to see concepts, and the role of gesture and gesture viewpoints in mediating the process of guidance. To examine these questions, two sociocultural theoretical frameworks--Radford's cultural-semiotic theory of knowledge objectification (e.g., 2003), and Goldman's Points of Viewing theory (e.g., 2007)--were applied to conduct a microanalytic, explanatory case study of the instructional activity of an exemplary teacher and his students in a middle school robotics programming class. According to Radford, students acquire concepts as they draw upon semiotic resources such as language and gesture to generalize and objectify initially concrete perceptions and actions. I applied Radford's framework to explain the mediations that a teacher might enact in guiding students to objectify and see concepts. Furthermore, I focused on gesture as semiotic means because of emergent research on gesture's role in communicating the visuospatial imagery that underlies math/ scientific concepts. I extended the view of gestures to the viewpoints constructed in gesture, and applied Goldman's theory to explain how perspectives might be actively constructed and shared in the process of guiding student conceptualization. Data was collected over a semester through participant observation, field notes, teacher and student interviews, and reviews of artifacts. Multimodal microanalyses were conducted on video data from eight class sessions. The findings provide confirmations and some disconfirmations about the applicability of Radford's and Goldman's theories for explaining a teacher's process of guiding student conceptualization. Notably, some of Radford's notions about de-contextualization and symbolic generalizations were not confirmed. Overall, the findings are summarized through three themes including, grounding, and perceptual organizers as two ways that gesture and other means served to both index and identify action

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

    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.

  16. Necessidade, objetividade e o paradoxo metafísico do conhecimento científico Necessity, objectivity, and the metaphysical paradox of scientific knowledge

    José Ricardo de C. M. Ayres

    1995-06-01

    Full Text Available A racionalidade científica moderna, buscando superar a fundamentação metafísica do conhecimento objetivo, toma a experiência do fato particular como a atualização de leis dadas a priori na mente humana ou na natureza, constituindo, paradoxalmente, uma nova e 'intransparente' metafísica. Entre as críticas contemporâneas a esta forma de pensar e fazer ciência, delineia-se uma compreensão construtivista, segundo a qual o fato particular e seu conhecimento objetivo resultam de relações circunstanciais entre o homem e seu mundo. Revisitando alguns dos principais fundadores da ciência ocidental, como Aristóteles, Bacon, Descartes, Leibniz, Kant, Newton e Stuart Mill, este ensaio hermenêutico procura explorar a participação do metaconceito de 'necessidade' nessa dialética do conhecimento, interpretando, em termos epistemológicos, seu papel na construção e hipóstase da racionalidade científica moderna.Modern scientific rationality, seeking to move beyond the metaphysical foundations of objective knowledge, takes the experience of a particular fact to be the actual expression of prior laws of the human mind or of nature, thereby paradoxically constituting a new, 'invisible' metaphysics. Among contemporary critiques of this way of 'thinking and doing science', a constructivist understanding is gaining outline; according to this conception, a particular fact and objective knowledge thereof derive from circumstantial relations between human beings and their world. Revisiting some of the main founders of Western science, such as Aristotle, Bacon, Descartes, Leibniz, Kant, Newton, and Stuart Mill, this hermeneutic essay explores the participation of the meta-concept of 'necessity' within this dialectic of knowledge and, in epistemological terms, interprets its role in the construction and hypostatization of modern scientific rationality.

  17. 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

    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

  18. 10 CFR 205.198 - Discovery.

    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...

  19. Knowledge Discovery and Intensive Management of Manufacturing enterprise Based on Data Mining Technology%基于数据挖掘技术的制造企业工艺知识发现和集约化管理

    王茨; 彭静; 刘雁; 杨素明

    2016-01-01

    A great deal of useful knowledge and law were hidden in lots of experience,case data in the process of design and production everyday. These knowledge would be wasted if these data were just stored in computers or work packages. In this paper,one knowledge discovery based rough set theory on was proposed. Combined with a case,three pieces of knowledge were dug from 25 production data. the result showed that the way was valid. The data digging technology could help enterprises to realize the knowledge fully dug up and intensive management to avoid that the enterprise had a great volume of data but no useful knowledge,and improved the core competitiveness of the company.%制造型企业在日常设计、生产过程中,积累了大量的经验、案例和设计生产数据。为挖掘这些数据中的有用知识和规律,实现知识的充分挖掘和集约化管理,提升企业的核心竞争力,提出一种基于粗糙集的工艺知识发现技术,并通过具体算例从25条生产数据中挖掘出3条知识,结果显示:该方法是有效的。

  20. Radioactivity. Centenary of radioactivity discovery

    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.)

  1. Designing the Object Game

    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...

  2. Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

    Repperger, D. W; Phillips, C. A; Schrider, C. D; Smith, E. A

    2004-01-01

    In an effort to improve decision-making on the identity of unknown objects appearing in visual images when the surrounding environment may be noisy and cluttered, a highly sensitive target detection...

  3. The discovery of radioactivity: the centenary

    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

  4. Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

    Taveira-Gomes, Tiago; Prado-Costa, Rui; Severo, Milton; Ferreira, Maria Amélia

    2015-01-24

    Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further

  5. Swift: 10 Years of Discovery

    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

  6. Knowledge discovery from patients' behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services.

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers.

  7. Knowledge discovery from patients’ behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers. PMID:27610177

  8. Knowledge-based identification of the ERK2/STAT3 signal pathway as a therapeutic target for type 2 diabetes and drug discovery.

    Kinoshita, Takayoshi; Doi, Kentaro; Sugiyama, Hajime; Kinoshita, Shuhei; Wada, Mutsuyo; Naruto, Shuji; Tomonaga, Atsushi

    2011-09-01

    Many existing agents for diabetes therapy are unable to restore or maintain normal glucose homeostasis or prevent the eventual emergence of hyperglycemia-related complication. Therefore, agents based on novel mechanisms are sought to complement and extend the current therapeutic approaches. Based on the initial paper research, we focused on active STAT3 as an attractive pharmacological target for type 2 diabetes. The subsequent text mining with a unique query to identify suppressors but not activators of STAT3 revealed the ERK2/STAT3 pathway as a novel diabetes target. The description of ERK2 inhibitors as diabetes target had not been found in our text mining research at present. The mechanism-based peptide inhibitor for ERK2 was identified using the knowledge of the KIM sequence, which has an important role in the recognition of cognate kinases, phosphatases, scaffold proteins, and substrates. The peptide inhibitor was confirmed to exert effects in vitro and in vivo. The peptide inhibitor conferred a significant decrease in HOMA-IR levels on Day 28 compared with that in the vehicle group. Besides lowering the fasting blood glucose level, the peptide inhibitor also attenuated the blood glucose increment in the fed state, as compared with the vehicle group. © 2011 John Wiley & Sons A/S.

  9. Exhibiting Epistemic Objects

    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...

  10. Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

    Strong, Laurence L.

    2012-01-01

    A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

  11. Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

    Strong, Laurence L.

    2012-01-01

    A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

  12. Computational methods in drug discovery

    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.

  13. Pinocchio: Geppetto's transitional object

    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.

  14. Resurrecting Legacy Code Using Ontosoft Knowledge-Sharing and Digital Object Management to Revitalize and Reproduce Software for Groundwater Management Research

    Kwon, N.; Gentle, J.; Pierce, S. A.

    2015-12-01

    Software code developed for research is often used for a relatively short period of time before it is abandoned, lost, or becomes outdated. This unintentional abandonment of code is a valid problem in the 21st century scientific process, hindering widespread reusability and increasing the effort needed to develop research software. Potentially important assets, these legacy codes may be resurrected and documented digitally for long-term reuse, often with modest effort. Furthermore, the revived code may be openly accessible in a public repository for researchers to reuse or improve. For this study, the research team has begun to revive the codebase for Groundwater Decision Support System (GWDSS), originally developed for participatory decision making to aid urban planning and groundwater management, though it may serve multiple use cases beyond those originally envisioned. GWDSS was designed as a java-based wrapper with loosely federated commercial and open source components. If successfully revitalized, GWDSS will be useful for both practical applications as a teaching tool and case study for groundwater management, as well as informing theoretical research. Using the knowledge-sharing approaches documented by the NSF-funded Ontosoft project, digital documentation of GWDSS is underway, from conception to development, deployment, characterization, integration, composition, and dissemination through open source communities and geosciences modeling frameworks. Information assets, documentation, and examples are shared using open platforms for data sharing and assigned digital object identifiers. Two instances of GWDSS version 3.0 are being created: 1) a virtual machine instance for the original case study to serve as a live demonstration of the decision support tool, assuring the original version is usable, and 2) an open version of the codebase, executable installation files, and developer guide available via an open repository, assuring the source for the

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

    Køster, Brian; Søndergaard, Jens; Nielsen, Jesper Bo

    2017-01-01

    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...

  16. Interactive data exploration and knowledge discovery

    Zudilova-Seinstra, E.; Martens, J.B.O.S.; Adriaansen, T.

    2010-01-01

    People have always relied on visual tools such as maps, charts and diagrams to better understand problems and solve them in less time. Continuous improvements in computer processing power and graphics capabilities have made it possible to incorporate a wide range of advanced visualization techniques

  17. Process mining: making knowledge discovery process centric

    Aalst, van der W.M.P.

    2011-01-01

    Recently, the Task Force on Process Mining released the Process Mining Manifesto. The manifesto is supported by 53 organizations and 77 process mining experts contributed to it. The active contributions from end-users, tool vendors, consultants, analysts, and researchers illustrate the growing

  18. Knowledge Discovery from Growing Social Networks

    2009-12-24

    a trackback. We exploited the blog “Theme salon of blogs” in the site “goo” 2, where a blogger can recruit trackbacks of other bloggers by registering...using trackbacks. Thus, a piece of information can propagate from one blogger to another blogger through a trackback. We exploited the blog “Theme salon ...interesting propagation properties. The circle is a URL that corresponds to the musical baton which is a kind of telephone game on the Internet. It has the

  19. Accounting for discovery bias in genomic prediction

    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...

  20. Socratic Questioning-Guided Discovery

    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

  1. Causality discovery technology

    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.

  2. Stabilizing a crisis as an object of knowledge: How the NATO Defense College made sense of the emerging crises in Libya and Ukraine

    Berling, Trine Villumsen

    2017-01-01

    draws on insights from science and technology studies and its insistence that the production of expert knowledge consists of social and practical processes endowed with power. By stabilizing the knowledge of a messy situation as a certain type of situation with specific features, different types...... of expertise both define and are constitutively brought in as the right, authoritative type of expertise to inform decisions and evaluations about a crisis. Some types of expertise are ignored, others seem to be somehow privileged. By telling two stories of the types of expertise that went into ‘knowing......’ the Libya and the Ukraine ‘situations’, the chapter highlights how the NDC operates with two conceptual pairs which define security expertise: academic knowledge/practical experience and civilian/military perspectives. With regards to Libya, the types of expertise mobilised were both practical expertise...

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

    Køster, Brian; Søndergaard, Jens; Nielsen, Jesper Bo

    2017-01-01

    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...

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

    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…

  5. 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

    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

  6. A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

    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.

  7. View discovery in OLAP databases through statistical combinatorial optimization

    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.

  8. Object and Objective Lost?

    Lopdrup-Hjorth, Thomas

    2015-01-01

    This paper explores the erosion and problematization of ‘the organization’ as a demarcated entity. Utilizing Foucault's reflections on ‘state-phobia’ as a source of inspiration, I show how an organization-phobia has gained a hold within Organization Theory (OT). By attending to the history...... of this organization-phobia, the paper argues that OT has become increasingly incapable of speaking about its core object. I show how organizations went from being conceptualized as entities of major importance to becoming theoretically deconstructed and associated with all kinds of ills. Through this history......, organizations as distinct entities have been rendered so problematic that they have gradually come to be removed from the center of OT. The costs of this have been rather significant. Besides undermining the grounds that gave OT intellectual credibility and legitimacy to begin with, the organization-phobia...

  9. Usability of Discovery Portals

    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

  10. Discovery and the atom

    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)

  11. On the threshold of discovery

    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.)

  12. Illustrating phallic worship: uses of material objects and the production of sexual knowledge in eighteenth-century antiquarianism and early twentieth-century sexual science.

    Funke, Jana; Fisher, Kate; Grove, Jen; Langlands, Rebecca

    2017-07-03

    This article reveals previously overlooked connections between eighteenth-century antiquarianism and early twentieth-century sexual science by presenting a comparative reading of two illustrated books: An Account of the Remains of the Worship of Priapus , by British antiquarian scholar Richard Payne Knight (1750-1824), and Die Weltreise eines Sexualforschers (The World Journey of a Sexologist), by German sexual scientist Magnus Hirschfeld (1868-1935). A close analysis of these publications demonstrates the special status of material artefacts and the strategic engagement with visual evidence in antiquarian and scientific writings about sex. Through its exploration of the similarities between antiquarian and sexual scientific thought, the article demonstrates the centrality of material culture to the production of sexual knowledge in the Western world. It also opens up new perspectives on Western intellectual history and on the intellectual origins of sexual science. While previous scholarship has traced the beginnings of sexual science back to nineteenth-century medical disciplines, this article shows that sexual scientists drew upon different forms of evidence and varied methodologies to produce sexual knowledge and secure scientific authority. As such, sexual science needs to be understood as a field with diverse intellectual roots that can be traced back (at least) to the eighteenth century.

  13. Identificación de los requisitos del usuario en el sector de la construcción bajo mecanismos de descubrimiento del conocimiento A knowledge discovery mechanism to user requirement identification in building design

    Fernanda Flach

    2012-08-01

    project well adjusted to the user requirements increase value and causes minors changes during its life cycle. As a consequence, renewal, refurbishments, and demolition are less present, reducing waste generation, reworking and material consumption. It is especially important in housing customization markets. However, one of the challenges faced by designers is frequently concerned about how properly to identify user requirements, wishes and needs, which are on the essence of the briefing phase. In this context, real estate data can be useful to designers, since it reflects the users' evaluation of the building attributes. The research strategy uses a knowledge discovery mechanism, composed by five steps: (1 formulation of a general database; (2 specific data selection using Case-Based Reasoning; (3 enrichment of data-sample; (4 development of hedonic price models using regression analysis; and (5 simulation of the value of design alternatives. Based on an application of an hedonic price model, using data from the medium-class housing market of Porto Alegre, Brazil, the main results indicate that adjusted price models have sufficient detailing and statistical precision to support decisions in the initial stage of design.

  14. Topology Discovery Using Cisco Discovery Protocol

    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 ...

  15. Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

    Fredouille, Corinne; Pouchoulin, Gilles; Ghio, Alain; Revis, Joana; Bonastre, Jean-François; Giovanni, Antoine

    2009-12-01

    This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0-3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

  16. Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

    Corinne Fredouille

    2009-01-01

    Full Text Available This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists. The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices, rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0–3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

  17. Reorienting Esthetic Knowing as an Appropriate "Object" of Scientific Inquiry to Advance Understanding of a Critical Pattern of Nursing Knowledge in Practice.

    Bender, Miriam; Elias, Dina

    The esthetic pattern of knowing is critical for nursing practice, yet remains weakly defined and understood. This gap has arguably relegated esthetic knowing to an "ineffable" creativity that resists transparency and understanding, which is a barrier to articulating its value for nursing and its importance in producing beneficial health outcomes. Current philosophy of science developments are synthesized to argue that esthetic knowing is an appropriate "object" of scientific inquiry. Examples of empirical scholarship that can be conceived as scientific inquiry into manifestations of esthetic knowing are highlighted. A program of research is outlined to advance a science of esthetic knowing.

  18. The special status of verbal knowledge in semantic memory: evidence from performance of semantically impaired subjects on verbalizable and non-verbalizable versions of the object decision task.

    Zannino, Gian Daniele; Perri, Roberta; Monaco, Marco; Caltagirone, Carlo; Luzzi, Simona; Carlesimo, Giovanni A

    2014-01-01

    According to the semantic hub hypothesis, a supramodal semantic hub is equally needed to deal with verbal and extraverbal "surface" representations. Damage to the supramodal hub is thought to underlie the crossmodal impairment observed in selective semantic deficits. In the present paper, we provide evidence supporting an alternative view: we hold that semantic impairment is not equal across domains but affects verbal behavior disproportionately. We investigated our hypothesis by manipulating the verbal load in an object decision task. Two pathological groups showing different levels of semantic impairment were enrolled together with their normal controls. The severe group included 10 subjects with semantic dementia and the mild group 10 subjects with Alzheimer's disease. In keeping with our hypothesis, when shifting from the low verbal load to the high verbal load condition, brain-damaged individuals, as compared to controls, showed a disproportionate impairment as a function of the severity of their semantic deficit. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Compte rendu de : Charles T. Wolfe and Ofer Gal (eds., The body as object and instrument of knowledge. Embodied empiricism in early modern science

    Bernard Joly

    2011-03-01

    Full Text Available Cet ouvrage collectif, qui résulte en partie des travaux d’un atelier sur l’empirisme incarné dans la science moderne qui s’est tenu à l’université de Sydney en février 2009, rassemble quinze communications regroupées en trois parties : « The Body as Object », « The Body as Instrument », « Embodies Minds ». L’objectif des auteurs est de corriger la conception dominante que se font les historiens des sciences et de la philosophie de l’émergence de la philosophie expérimentale, et de l’empirism...

  20. Effective Online Group Discovery in Trajectory Databases

    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...

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

    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....

  2. Automated discovery systems and the inductivist controversy

    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

  3. Guided Discovery with Socratic Questioning

    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. Students Excited by Stellar Discovery

    2011-02-01

    In the constellation of Ophiuchus, above the disk of our Milky Way Galaxy, there lurks a stellar corpse spinning 30 times per second -- an exotic star known as a radio pulsar. This object was unknown until it was discovered last week by three high school students. These students are part of the Pulsar Search Collaboratory (PSC) project, run by the National Radio Astronomy Observatory (NRAO) in Green Bank, WV, and West Virginia University (WVU). The pulsar, which may be a rare kind of neutron star called a recycled pulsar, was discovered independently by Virginia students Alexander Snider and Casey Thompson, on January 20, and a day later by Kentucky student Hannah Mabry. "Every day, I told myself, 'I have to find a pulsar. I better find a pulsar before this class ends,'" said Mabry. When she actually made the discovery, she could barely contain her excitement. "I started screaming and jumping up and down." Thompson was similarly expressive. "After three years of searching, I hadn't found a single thing," he said, "but when I did, I threw my hands up in the air and said, 'Yes!'." Snider said, "It actually feels really neat to be the first person to ever see something like that. It's an uplifting feeling." As part of the PSC, the students analyze real data from NRAO's Robert C. Byrd Green Bank Telescope (GBT) to find pulsars. The students' teachers -- Debra Edwards of Sherando High School, Leah Lorton of James River High School, and Jennifer Carter of Rowan County Senior High School -- all introduced the PSC in their classes, and interested students formed teams to continue the work. Even before the discovery, Mabry simply enjoyed the search. "It just feels like you're actually doing something," she said. "It's a good feeling." Once the pulsar candidate was reported to NRAO, Project Director Rachel Rosen took a look and agreed with the young scientists. A followup observing session was scheduled on the GBT. Snider and Mabry traveled to West Virginia to assist in the

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

    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

  6. A New Universe of Discoveries

    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.

  7. Service Discovery At Home

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    Service discovery is a fady new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between deviies. This paper provides an ovewiew and comparison of several prominent

  8. Academic Drug Discovery Centres

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...

  9. Decades of Discovery

    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.

  10. Service discovery at home

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    2003-01-01

    Service discovery is a fairly new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between devices. This paper provides an overview and comparison of several

  11. Knowledge Exchange and Discovery in the Age of Social Media: The Journey From Inception to Establishment of a Parent-Led Web-Based Research Advisory Community for Childhood Disability.

    Russell, Dianne J; Sprung, Jennifer; McCauley, Dayle; Kraus de Camargo, Olaf; Buchanan, Francine; Gulko, Roman; Martens, Rachel; Gorter, Jan Willem

    2016-11-11

    Efforts to involve parents and families in all aspects of research, from initiating the question through to dissemination and knowledge exchange, are increasing. While social media as a method for health communication has shown numerous benefits, including increasing accessibility, interactions with others, and access to health care information, little work has been published on the use of social media to enhance research partnerships. Our objective was to describe the development and evaluation of a Web-based research advisory community, hosted on Facebook and connecting a diverse group of parents of special needs children with researchers at CanChild Centre for Childhood Disability Research. The goal of this community is to work together and exchange knowledge in order to improve research and the lives of children and their families. The Web-based Parents Participating in Research (PPR) advisory community was a secret Facebook group launched in June 2014 and run by 2 parent moderators who worked in consultation with CanChild. We evaluated its success using Facebook statistics of engagement and activity (eg, number of posts, number of comments) between June 2014 and April 2015, and a Web-based survey of members. The PPR community had 96 participants (2 parent moderators, 13 researchers, and 81 family members) as of April 1, 2015. Over 9 months, 432 original posts were made: 155 (35.9%) by moderators, 197 (45.6%) by parents, and 80 (18.5%) by researchers. Posts had a median of 3 likes (range 0-24) and 4 comments (range 0-113). Members, rather than moderators, generated 64% (277/432) of posts. The survey had a 51% response rate (49/96 members), with 40 (82%) being parent members and 9 (18%) being researchers. The initial purpose of the group was to be an advisory to CanChild, and 76% (28/37) of parents and all the researchers (9/9) identified having an impact on childhood disability research as their reason for participating. A total of 58% (23/40) of parents and 56

  12. GrandBase: generating actionable knowledge from Big Data

    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.

  13. Supernovae Discovery Efficiency

    John, Colin

    2018-01-01

    Abstract:We present supernovae (SN) search efficiency measurements for recent Hubble Space Telescope (HST) surveys. Efficiency is a key component to any search, and is important parameter as a correction factor for SN rates. To achieve an accurate value for efficiency, many supernovae need to be discoverable in surveys. This cannot be achieved from real SN only, due to their scarcity, so fake SN are planted. These fake supernovae—with a goal of realism in mind—yield an understanding of efficiency based on position related to other celestial objects, and brightness. To improve realism, we built a more accurate model of supernovae using a point-spread function. The next improvement to realism is planting these objects close to galaxies and of various parameters of brightness, magnitude, local galactic brightness and redshift. Once these are planted, a very accurate SN is visible and discoverable by the searcher. It is very important to find factors that affect this discovery efficiency. Exploring the factors that effect detection yields a more accurate correction factor. Further inquires into efficiency give us a better understanding of image processing, searching techniques and survey strategies, and result in an overall higher likelihood to find these events in future surveys with Hubble, James Webb, and WFIRST telescopes. After efficiency is discovered and refined with many unique surveys, it factors into measurements of SN rates versus redshift. By comparing SN rates vs redshift against the star formation rate we can test models to determine how long star systems take from the point of inception to explosion (delay time distribution). This delay time distribution is compared to SN progenitors models to get an accurate idea of what these stars were like before their deaths.

  14. Building Scalable Knowledge Graphs for Earth Science

    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.

  15. "Eureka, Eureka!" Discoveries in Science

    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…

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

    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

  17. An interactive visualization tool for mobile objects

    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

  18. Predicting future discoveries from current scientific literature.

    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.

  19. The Greatest Mathematical Discovery?

    Bailey, David H.; Borwein, Jonathan M.

    2010-05-12

    What mathematical discovery more than 1500 years ago: (1) Is one of the greatest, if not the greatest, single discovery in the field of mathematics? (2) Involved three subtle ideas that eluded the greatest minds of antiquity, even geniuses such as Archimedes? (3) Was fiercely resisted in Europe for hundreds of years after its discovery? (4) Even today, in historical treatments of mathematics, is often dismissed with scant mention, or else is ascribed to the wrong source? Answer: Our modern system of positional decimal notation with zero, together with the basic arithmetic computational schemes, which were discovered in India about 500 CE.

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

    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.

  1. Multidimensional process discovery

    Ribeiro, J.T.S.

    2013-01-01

    Typically represented in event logs, business process data describe the execution of process events over time. Business process intelligence (BPI) techniques such as process mining can be applied to get strategic insight into business processes. Process discovery, conformance checking and

  2. Fateful discovery almost forgotten

    1989-01-01

    "The discovery of the fission of uranium exactly half a century ago is at risk of passing unremarked because of the general ambivalence towards the consequences of this development. Can that be wise?" (4 pages)

  3. Toxins and drug discovery.

    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.

  4. Defining Creativity with Discovery

    Wilson, Nicholas Charles; Martin, Lee

    2017-01-01

    The standard definition of creativity has enabled significant empirical and theoretical advances, yet contains philosophical conundrums concerning the nature of novelty and the role of recognition and values. In this work we offer an act of conceptual valeting that addresses these issues and in doing so, argue that creativity definitions can be extended through the use of discovery. Drawing on dispositional realist philosophy we outline why adding the discovery and bringing into being of new ...

  5. On the antiproton discovery

    Piccioni, O.

    1989-01-01

    The author of this article describes his own role in the discovery of the antiproton. Although Segre and Chamberlain received the Nobel Prize in 1959 for its discovery, the author claims that their experimental method was his idea which he communicated to them informally in December 1954. He describes how his application for citizenship (he was Italian), and other scientists' manipulation, prevented him from being at Berkeley to work on the experiment himself. (UK)

  6. Discovery Driven Growth

    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...

  7. The π discovery

    Fowler, P.H.

    1988-01-01

    The paper traces the discovery of the Π meson. The discovery was made by exposure of nuclear emulsions to cosmic radiation at high altitudes, with subsequent scanning of the emulsions for meson tracks. Disintegration of nuclei by a negative meson, and the decay of a Π meson were both observed. Further measurements revealed the mass of the meson. The studies carried out on the origin of the Π-mesons, and their mode of decay, are both described. (U.K.)

  8. CBT Data /Knowledge Acquisition: Using Knowledge Objects to Prototype Courseware

    Muraida, Daniel

    1998-01-01

    .... Ideally the SME can save the developers vital production time when he or she provides them annotated or structured documentation that shows how concepts and skills fit together in a given piece of curriculum...

  9. Knowledge about knowledge

    Ramm, Hans Henrik

    2006-01-01

    Technology and knowledge make up the knowledge capital that has been so essential to the oil and gas industry's value creation, competitiveness and internationalization. Report prepared for the Norwegian Oil Industry Association (OLF) and The Norwegian Society of Chartered Technical and Scientific Professionals (Tekna), on the Norwegian petroleum cluster as an environment for creating knowledge capital from human capital, how fiscal and other framework conditions may influence the building of knowledge capital, the long-term perspectives for the petroleum cluster, what Norwegian society can learn from the experiences in the petroleum cluster, and the importance of gaining more knowledge about the functionality of knowledge for increased value creation (author) (ml)

  10. MULTIPLE OBJECTS

    A. A. Bosov

    2015-04-01

    Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

  11. Polar Domain Discovery with Sparkler

    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.

  12. A Technique Socratic Questioning-Guided Discovery

    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

  13. Elegant objects

    Bugayenko, Yegor

    2017-01-01

    There are 23 practical recommendations for object-oriented programmers. Most of them are completely against everything you've read in other books. For example, static methods, NULL references, getters, setters, and mutable classes are called evil. Compound variable names, validators, private static literals, configurable objects, inheritance, annotations, MVC, dependency injection containers, reflection, ORM and even algorithms are our enemies.

  14. Objective lens

    Olczak, Eugene G. (Inventor)

    2011-01-01

    An objective lens and a method for using same. The objective lens has a first end, a second end, and a plurality of optical elements. The optical elements are positioned between the first end and the second end and are at least substantially symmetric about a plane centered between the first end and the second end.

  15. Microcosm 2015: showcasing real objects, real people and real discoveries

    CERN Bulletin

    2014-01-01

    Every year since its inauguration in 1994, the well-loved Microcosm exhibition has played host to tens of thousands of students, tourists and VIPs alike. But the ever-changing CERN landscape warranted a new look for the exhibition, which was last updated in 2003. On 8 December, Microcosm will close for refurbishment, making way for a new, interactive exhibition space to be opened summer 2015.   In the Accelerator zone, Microcosm visitors will don the helmet of an LHC operator. Social media tools will be integrated into the exhibit, allowing visitors to share their "beam" with friends at home. (Conceptual art for the new Microcosm exhibition.) While the Globe of Science and Innovation provides a spectacular introduction to CERN's key messages, Microcosm has always employed a more didactic approach. The new Microcosm will continue this complementary approach, whilst also immersing visitors into the day-to-day life of CERN people. "We want to highlight the ama...

  16. Discovery of charm

    Goldhaber, G.

    1984-11-01

    In my talk I will cover the period 1973 to 1976 which saw the discoveries of the J/psi and psi' resonances and most of the Psion spectroscopy, the tau lepton and the D 0 ,D + charmed meson doublet. Occasionally I will refer briefly to more recent results. Since this conference is on the history of the weak-interactions I will deal primarily with the properties of naked charm and in particular the weakly decaying doublet of charmed mesons. Most of the discoveries I will mention were made with the SLAC-LBL Magnetic Detector or MARK I which we operated at SPEAR from 1973 to 1976. 27 references

  17. Extended objects

    Creutz, M.

    1976-01-01

    After some disconnected comments on the MIT bag and string models for extended hadrons, I review current understanding of extended objects in classical conventional relativistic field theories and their quantum mechanical interpretation

  18. Trusted Objects

    CAMPBELL, PHILIP L.; PIERSON, LYNDON G.; WITZKE, EDWARD L.

    1999-01-01

    In the world of computers a trusted object is a collection of possibly-sensitive data and programs that can be allowed to reside and execute on a computer, even on an adversary's machine. Beyond the scope of one computer we believe that network-based agents in high-consequence and highly reliable applications will depend on this approach, and that the basis for such objects is what we call ''faithful execution.''

  19. Discovery: Pile Patterns

    de Mestre, Neville

    2017-01-01

    Earlier "Discovery" articles (de Mestre, 1999, 2003, 2006, 2010, 2011) considered patterns from many mathematical situations. This article presents a group of patterns used in 19th century mathematical textbooks. In the days of earlier warfare, cannon balls were stacked in various arrangements depending on the shape of the pile base…

  20. Discovery and Innovation

    Discovery and Innovation is a journal of the African Academy of Sciences (AAS) ... World (TWAS) meant to focus attention on science and technology in Africa and the ... of Non-wood Forest Products: Potential Impacts and Challenges in Africa ...

  1. Discovery of TUG-770

    Christiansen, Elisabeth; Hansen, Steffen V F; Urban, Christian

    2013-01-01

    Free fatty acid receptor 1 (FFA1 or GPR40) enhances glucose-stimulated insulin secretion from pancreatic β-cells and currently attracts high interest as a new target for the treatment of type 2 diabetes. We here report the discovery of a highly potent FFA1 agonist with favorable physicochemical...

  2. The discovery of fission

    McKay, H.A.C.

    1978-01-01

    In this article by the retired head of the Separation Processes Group of the Chemistry Division, Atomic Energy Research Establishment, Harwell, U.K., the author recalls what he terms 'an exciting drama, the unravelling of the nature of the atomic nucleus' in the years before the Second World War, including the discovery of fission. 12 references. (author)

  3. The Discovery of America

    Martin, Paul S.

    1973-01-01

    Discusses a model for explaining the spread of human population explosion on North American continent since its discovery 12,000 years ago. The model may help to map the spread of Homo sapiens throughout the New World by using the extinction chronology of the Pleistocene megafauna. (Author/PS)

  4. Resource-estimation models and predicted discovery

    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)

  5. Does scientism undermine other forms of knowledge?

    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.

  6. Managing knowledge management

    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...

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

    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...

  8. Fashion Objects

    Andersen, Bjørn Schiermer

    2009-01-01

    -- an outline which at the same time indicates the need for transformations of the Durkheimian model on decisive points. Thus, thirdly, it returns to Durkheim and undertakes to develop his concepts in a direction suitable for a sociological theory of fashion. Finally, it discusses the theoretical implications......This article attempts to create a framework for understanding modern fashion phenomena on the basis of Durkheim's sociology of religion. It focuses on Durkheim's conception of the relation between the cult and the sacred object, on his notion of 'exteriorisation', and on his theory of the social...... symbol in an attempt to describe the peculiar attraction of the fashion object and its social constitution. However, Durkheim's notions of cult and ritual must undergo profound changes if they are to be used in an analysis of fashion. The article tries to expand the Durkheimian cult, radically enlarging...

  9. Utilities objectives

    Cousin, Y.; Fabian, H.U.

    1996-01-01

    The policy of French and german utilities is to make use of nuclear energy as a long term, competitive and environmentally friendly power supply. The world electricity generation is due to double within the next 30 years. In the next 20 to 30 years the necessity of nuclear energy will be broadly recognized. More than for most industries, to deal properly with nuclear energy requires the combination of a consistent political will, of a proper institutional framework, of strong and legitimate control authorities, of a sophisticated industry and of operators with skilled management and human resources. One of the major risk facing nuclear energy is the loss of competitiveness. This can be achieved only through the combination of an optimized design, a consistent standardization, a proper industrial partnership and a stable long term strategy. Although the existing plants in Western Europe are already very safe, the policy is clearly to enhance the safety of the next generation of nuclear plants which are designing today. The French and German utilities have chosen an evolutionary approach based on experience and proven technologies, with an enhanced defense in depth and an objective of easier operation and maintenance. The cost objective is to maintain and improve what has been achieved in the best existing power plants in both countries. This calls for rational choices and optimized design to meet the safety objectives, a strong standardization policy, short construction times, high availability and enough flexibility to enable optimization of the fuel cycle throughout the lifetime of the plants. The conceptual design phase has proven that the French and German teams from industry and from the utilities are able to pursue both the safety and the cost objectives, basing their decision on a rational approach which could be accepted by the safety authorities. (J.S.)

  10. The neutron discovery

    Six, J.

    1987-01-01

    The neutron: who had first the idea, who discovered it, who established its main properties. To these apparently simple questions, multiple answers exist. The progressive discovery of the neutron is a marvellous illustration of some characteristics of the scientific research, where the unforeseen may be combined with the expected. This discovery is replaced in the context of the 1930's scientific effervescence that succeeded the revolutionary introduction of quantum mechanics. This book describes the works of Bothe, the Joliot-Curie and Chadwick which led to the neutron in an unexpected way. A historical analysis allows to give a new interpretation on the hypothesis suggested by the Joliot-Curie. Some texts of these days will help the reader to revive this fascinating story [fr

  11. Atlas of Astronomical Discoveries

    Schilling, Govert

    2011-01-01

    Four hundred years ago in Middelburg, in the Netherlands, the telescope was invented. The invention unleashed a revolution in the exploration of the universe. Galileo Galilei discovered mountains on the Moon, spots on the Sun, and moons around Jupiter. Christiaan Huygens saw details on Mars and rings around Saturn. William Herschel discovered a new planet and mapped binary stars and nebulae. Other astronomers determined the distances to stars, unraveled the structure of the Milky Way, and discovered the expansion of the universe. And, as telescopes became bigger and more powerful, astronomers delved deeper into the mysteries of the cosmos. In his Atlas of Astronomical Discoveries, astronomy journalist Govert Schilling tells the story of 400 years of telescopic astronomy. He looks at the 100 most important discoveries since the invention of the telescope. In his direct and accessible style, the author takes his readers on an exciting journey encompassing the highlights of four centuries of astronomy. Spectacul...

  12. Viral pathogen discovery

    Chiu, Charles Y

    2015-01-01

    Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

  13. Resource Discovery in Activity-Based Sensor Networks

    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...

  14. Fateful discovery almost forgotten

    Anon.

    1989-01-01

    The paper reviews the discovery of the fission of uranium, which took place fifty years ago. A description is given of the work of Meitner and Frisch in interpreting the Fermi data on the bombardment of uranium nuclei with neutrons, i.e. proposing fission. The historical events associated with the development and exploitation of uranium fission are described, including the Manhattan Project, Hiroshima and Nagasaki, Shippingport, and Chernobyl. (U.K.)

  15. Discovery as a process

    Loehle, C.

    1994-05-01

    The three great myths, which form a sort of triumvirate of misunderstanding, are the Eureka! myth, the hypothesis myth, and the measurement myth. These myths are prevalent among scientists as well as among observers of science. The Eureka! myth asserts that discovery occurs as a flash of insight, and as such is not subject to investigation. This leads to the perception that discovery or deriving a hypothesis is a moment or event rather than a process. Events are singular and not subject to description. The hypothesis myth asserts that proper science is motivated by testing hypotheses, and that if something is not experimentally testable then it is not scientific. This myth leads to absurd posturing by some workers conducting empirical descriptive studies, who dress up their study with a ``hypothesis`` to obtain funding or get it published. Methods papers are often rejected because they do not address a specific scientific problem. The fact is that many of the great breakthroughs in silence involve methods and not hypotheses or arise from largely descriptive studies. Those captured by this myth also try to block funding for those developing methods. The third myth is the measurement myth, which holds that determining what to measure is straightforward, so one doesn`t need a lot of introspection to do science. As one ecologist put it to me ``Don`t give me any of that philosophy junk, just let me out in the field. I know what to measure.`` These myths lead to difficulties for scientists who must face peer review to obtain funding and to get published. These myths also inhibit the study of science as a process. Finally, these myths inhibit creativity and suppress innovation. In this paper I first explore these myths in more detail and then propose a new model of discovery that opens the supposedly miraculous process of discovery to doser scrutiny.

  16. Introduction to fragment-based drug discovery.

    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.

  17. Discovery stories in the science classroom

    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.

  18. Nesnel ve Öznel Bilginin Tüketicilerin Satın Alma Davranışlarına Etkisine Yönelik Bir Araştırma(An Investigation of The Effect of Objective and Subjective Knowledge on Consumers’ Buying Behaviour

    Kalender Özcan ATILGAN

    2014-12-01

    Full Text Available In the growing body of marketing literature on the impact of consumer knowledge on intention to buy, distinction between subjective and objective knowledge has clearly been made. The difference between subjective and objective knowledge may be due to both the definition and measurement process. The goal of this research is to examine the impact of both subjective and objective knowledge related to attitude to and intention to buy light milk and dairy products. Data were gathered via face-to-face survey from 330 consumers living in Erdemli district of Mersin, Turkey. A Hybrid Path Analysis was performed to test the hypothesis. The results of Structural Equations Modelling clearly indicate that subjective knowledge and health consciousness are positively associated with attitude towards light milk and dairy products and objective knowledge is negatively associated with attitude towards light milk and dairy products. Also, attitude towards light milk and dairy products is positively associated with intention to buy these products. Implications and suggestions are developed based on the structural model for future researches.

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

    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.

  20. Unifying Learning Object Repositories in MACE

    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,

  1. Panorama 2014 - New oil and gas discoveries

    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)

  2. 14 CFR 406.143 - Discovery.

    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...

  3. BayesMD: flexible biological modeling for motif discovery

    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...

  4. "Tacit Knowledge" versus "Explicit Knowledge"

    Sanchez, Ron

    creators and carriers. By contrast, the explicit knowledge approach emphasizes processes for articulating knowledge held by individuals, the design of organizational approaches for creating new knowledge, and the development of systems (including information systems) to disseminate articulated knowledge...

  5. Automated Supernova Discovery (Abstract)

    Post, R. S.

    2015-12-01

    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  6. West Nile Virus Drug Discovery

    Siew Pheng Lim

    2013-12-01

    Full Text Available The outbreak of West Nile virus (WNV in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development.

  7. Computational methods in drug discovery

    Sumudu P. Leelananda; Steffen Lindert

    2016-01-01

    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 project...

  8. Representation Discovery using Harmonic Analysis

    Mahadevan, Sridhar

    2008-01-01

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

  9. Semantic memory in object use.

    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.

  10. Managing knowledge management

    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...

  11. Hippocampus discovery First steps

    Eliasz Engelhardt

    Full Text Available The first steps of the discovery, and the main discoverers, of the hippocampus are outlined. Arantius was the first to describe a structure he named "hippocampus" or "white silkworm". Despite numerous controversies and alternate designations, the term hippocampus has prevailed until this day as the most widely used term. Duvernoy provided an illustration of the hippocampus and surrounding structures, considered the first by most authors, which appeared more than one and a half century after Arantius' description. Some authors have identified other drawings and texts which they claim predate Duvernoy's depiction, in studies by Vesalius, Varolio, Willis, and Eustachio, albeit unconvincingly. Considering the definition of the hippocampal formation as comprising the hippocampus proper, dentate gyrus and subiculum, Arantius and Duvernoy apparently described the gross anatomy of this complex. The pioneering studies of Arantius and Duvernoy revealed a relatively small hidden formation that would become one of the most valued brain structures.

  12. Nuclear Energy General Objectives

    2011-01-01

    considered and the specific goals to be achieved at different stages of implementation, all of which are consistent with the Basic Principles. The four Objectives publications include Nuclear General Objectives, Nuclear Power Objectives, Nuclear Fuel Cycle Objectives, and Radioactive Waste Management and Decommissioning Objectives. All four Objectives publications follow the same structure. For each topic in the area, the objectives are described in accordance with the sequence in the Basic Principles publication. Within each of these four Objectives publications, the individual topics that make up each area are addressed. The topics included in Nuclear General Objectives are Energy Systems Analysis and Development of Strategies for Nuclear Energy, Economics, Infrastructure, Management Systems, Human Resources and Knowledge Management. The diversity of the topics contained in Nuclear General Objectives necessitated incorporating some repetition in order to simplify access to the relevant information for the various interested audiences.

  13. Participative knowledge management to empower manufacturing workers

    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...

  14. Biomimicry as a basis for drug discovery.

    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.

  15. Discovery Mondays: Zoom on materials

    2003-01-01

    Following the success of the first Discovery Monday, which had over 100 visitors, the series of evening events in Microcosm continues. On Monday 2nd June, discover the world of materials. Find out how CERN scientists examine, manufacture and study different materials, at different scales. Did you know for example that using electrons you can observe a hair at a scale equivalent to looking at a boat with the naked eye? Also, that using ultrasound, you can measure the thickness of an object that is completely inaccessible? Find out more about these techniques, and also the high-tech machining and soldering that is carried out in CERN's central workshop. Plus, see how engineers can detect tiny leaks through solder points - essential for maintaining the vacuum in the LHC. The evening is open to all, without reservation, suggested age 12 and above. Rendez-vous in Microcosm on Monday 2nd June From 19.30 - 21.00 Free entry For more information : http://www.cern.ch/microcosm Using a scanning microscope, the head o...

  16. Early object relations into new objects.

    Downey, T W

    2001-01-01

    . Pain deprived of meaning is buried as neurosis. As we see in John's story, experience that cannot be integrated at the time is locked away from whatever developmental progression has occurred. Intolerable affects and ideas require particular circumstances of object relation and verbalization such as are found in the context of psychoanalysis and arrived at through psychoanalytic interpretation. Or, as in John's case, they may give way only slowly and irregularly over long stretches of time, when subjected to life experiences in the company of new object relations. Broadly stated, the Freud-Dann paper helps us to appreciate that there are several pathways of protection and growth in the ego that involve the discovery or construction of new objects. Family-romance fantasies are a common manifestation of new-object phenomena. Transitional object phenomena are also related. For some individuals at a particular time or over a span of time, providing the right circumstances for the resumption of maturational and developmental growth is all it takes to make them whole. Changes in the adaptive ego are sufficient to alleviate the conflicts stemming from the neurotic ego. For others, depending upon the degree of their neurotic impairment, or for the same individual under other circumstances, therapeutic change in the deepest sense demands the relatively unconditional presence of the interactive and interpreting other. Children of the storm who come in for shelter and warmth may thrive, but they also require a means of getting at the storm in their core that has been internalized as part of the ego's survival mechanism. What can be extracted from the poignant story of the Bulldogs Bank children about current child-analytic technique? The psychoanalytic piano now may be more formally conceptualized as having white as well as black keys. Most analyses, adult and child, have been conducted as though the "black keys"--pressure to mastery through repetition and its subsequent

  17. Materials Discovery | Materials Science | NREL

    Discovery Materials Discovery Images of red and yellow particles NREL's research in materials characterization of sample by incoming beam and measuring outgoing particles, with data being stored and analyzed Staff Scientist Dr. Zakutayev specializes in design of novel semiconductor materials for energy

  18. Service discovery using Bloom filters

    Goering, P.T.H.; Heijenk, Geert; Lelieveldt, B.P.F.; Haverkort, Boudewijn R.H.M.; de Laat, C.T.A.M.; Heijnsdijk, J.W.J.

    A protocol to perform service discovery in adhoc networks is introduced in this paper. Attenuated Bloom filters are used to distribute services to nodes in the neighborhood and thus enable local service discovery. The protocol has been implemented in a discrete event simulator to investigate the

  19. On the pulse of discovery

    2017-12-01

    What started 50 years ago as a `smudge' on paper has flourished into a fundamental field of astrophysics replete with unexpected applications and exciting discoveries. To celebrate the discovery of pulsars, we look at the past, present and future of pulsar astrophysics.

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

    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

  1. A Knowledge Discovery from POS Data using State Space Models

    Sato, Tadahiko; Higuchi, Tomoyuki

    The number of competing-brands changes by new product's entry. The new product introduction is endemic among consumer packaged goods firm and is an integral component of their marketing strategy. As a new product's entry affects markets, there is a pressing need to develop market response model that can adapt to such changes. In this paper, we develop a dynamic model that capture the underlying evolution of the buying behavior associated with the new product. This extends an application of a dynamic linear model, which is used by a number of time series analyses, by allowing the observed dimension to change at some point in time. Our model copes with a problem that dynamic environments entail: changes in parameter over time and changes in the observed dimension. We formulate the model with framework of a state space model. We realize an estimation of the model using modified Kalman filter/fixed interval smoother. We find that new product's entry (1) decreases brand differentiation for existing brands, as indicated by decreasing difference between cross-price elasticities; (2) decreases commodity power for existing brands, as indicated by decreasing trend; and (3) decreases the effect of discount for existing brands, as indicated by a decrease in the magnitude of own-brand price elasticities. The proposed framework is directly applicable to other fields in which the observed dimension might be change, such as economic, bioinformatics, and so forth.

  2. Knowledge Discovery in Chess Using an Aesthetics Approach

    Iqbal, Azlan

    2012-01-01

    Computational aesthetics is a relatively new subfield of artificial intelligence (AI). It includes research that enables computers to "recognize" (and evaluate) beauty in various domains such as visual art, music, and games. Aside from the benefit this gives to humans in terms of creating and appreciating art in these domains, there are perhaps…

  3. The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

    Stone, George F. III; Greenberg, Brandi; Daehler-Wilking, Richard; Hunt, Steven

    2011-01-01

    The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

  4. Data mining, knowledge discovery and data-driven modelling

    Solomatine, D.P.; Velickov, S.; Bhattacharya, B.; Van der Wal, B.

    2003-01-01

    The project was aimed at exploring the possibilities of a new paradigm in modelling - data-driven modelling, often referred as "data mining". Several application areas were considered: sedimentation problems in the Port of Rotterdam, automatic soil classification on the basis of cone penetration

  5. Visual Climate Knowledge Discovery within a Grid Environment

    Heitzler, Magnus; Kiertscher, Simon; Lang, Ulrich; Nocke, Thomas; Wahnes, Jens; Winkelmann, Volker

    2013-04-01

    The C3Grid-INAD project aims to provide a common grid infrastructure for the climate science community to improve access to climate related data and domain workflows via the Internet. To make sense of the heterogeneous, often large-sized or even dynamically generated and modified files originating from C3Grid, a highly flexible and user-friendly analysis software is needed to run on different high-performance computing nodes within the grid environment, when requested by a user. Because visual analysis tools directly address human visual perception and therefore are being considered to be highly intuitive, two distinct visualization workflows have been integrated in C3Grid-INAD, targeting different application backgrounds. First, a GrADS-based workflow enables the ad-hoc visualization of selected datasets in respect to data source, temporal and spatial extent, as well as variables of interest. Being low in resource demands, this workflow allows for users to gain fast insights through basic spatial visualization. For more advanced visual analysis purposes, a second workflow enables the user to start a visualization session via Virtual Network Computing (VNC) and VirtualGL to access high-performance computing nodes on which a wide variety of different visual analysis tools are provided. These are made available using the easy-to-use software system SimEnvVis. Considering metadata as well as user preferences and analysis goals, SimEnvVis evaluates the attached tools and launches the selected visual analysis tool by providing a dynamically parameterized template. This approach facilitates the selection of the most suitable tools, and at the same time eases the process of familiarization with them. Because of a higher demand for computational resources, SimEnvVis-sessions are restricted to a smaller set of users at a time. This architecture enables climate scientists not only to remotely access, but also to visually analyze highly heterogeneous data originating from C3Grid for different purposes. The analysis products, such as images and videos, can then be exported and shared with the community, enhancing scientific communication and therefore accelerating scientific research.

  6. Teaching APA Style Documentation: Discovery Learning, Scaffolding and Procedural Knowledge

    Skeen, Thomas; Zafonte, Maria

    2015-01-01

    Students struggle with learning correct documentation style as found in the Publication Manual of the American Psychological Association and teachers are often at a loss for how to best instruct students in correct usage of APA style. As such, the first part of this paper discusses the current research on teaching documentation styles as well as…

  7. Energy-Water Nexus Knowledge Discovery Framework, Experts’ Meeting Report

    Bhaduri, Budhendra L. [ORNL; Simon, AJ [Lawrence Livermore National Laboratory (LLNL); Allen, Melissa R. [ORNL; Sanyal, Jibonananda [ORNL; Stewart, Robert N. [ORNL; McManamay, Ryan A. [ORNL

    2018-01-01

    Energy and water generation and delivery systems are inherently interconnected. With worldwide demandfor energy growing, the energy sector is experiencing increasing competition for water. With increasingpopulation and changing environmental, socioeconomic, and demographic scenarios, new technology andinvestment decisions must be made for optimized and sustainable energy-water resource management. These decisions require novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales.

  8. 29 CFR 2700.56 - Discovery; general.

    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...

  9. 19 CFR 207.109 - Discovery.

    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...

  10. 30 CFR 44.24 - Discovery.

    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...

  11. 19 CFR 356.20 - Discovery.

    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...

  12. 24 CFR 180.500 - Discovery.

    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...

  13. 15 CFR 25.21 - Discovery.

    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...

  14. 39 CFR 963.14 - Discovery.

    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...

  15. 22 CFR 224.21 - Discovery.

    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...

  16. 75 FR 66766 - NIAID Blue Ribbon Panel Meeting on Adjuvant Discovery and Development

    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...

  17. Discovery of the monopole

    Galitskii, V [Gosudarstvennyj Komitet po Ispol' zovaniyu Atomnoj Ehnergii SSSR, Moscow. Inst. Atomnoj Ehnergii

    1978-04-01

    An experiment is described conducted in Berkeley in which the magnetic monopole was first detected. The objections are reported of prof. Fowler (U.K.) and prof. Alvarez (U.S.A.) permitting a different interpretation of experimental data.

  18. Knowledge Sharing is Knowledge Creation

    Greve, Linda

    2015-01-01

    Knowledge sharing and knowledge transfer are important to knowledge communication. However when groups of knowledge workers engage in knowledge communication activities, it easily turns into mere mechanical information processing despite other ambitions. This article relates literature of knowledge...... communication and knowledge creation to an intervention study in a large Danish food production company. For some time a specific group of employees uttered a wish for knowledge sharing, but it never really happened. The group was observed and submitted to metaphor analysis as well as analysis of co...

  19. Discovery Mondays: Surveyors' Tools

    2003-01-01

    Surveyors of all ages, have your rulers and compasses at the ready! This sixth edition of Discovery Monday is your chance to learn about the surveyor's tools - the state of the art in measuring instruments - and see for yourself how they work. With their usual daunting precision, the members of CERN's Surveying Group have prepared some demonstrations and exercises for you to try. Find out the techniques for ensuring accelerator alignment and learn about high-tech metrology systems such as deviation indicators, tracking lasers and total stations. The surveyors will show you how they precisely measure magnet positioning, with accuracy of a few thousandths of a millimetre. You can try your hand at precision measurement using different types of sensor and a modern-day version of the Romans' bubble level, accurate to within a thousandth of a millimetre. You will learn that photogrammetry techniques can transform even a simple digital camera into a remarkable measuring instrument. Finally, you will have a chance t...

  20. Knowledge Management.

    1999

    The first of the four papers in this symposium, "Knowledge Management and Knowledge Dissemination" (Wim J. Nijhof), presents two case studies exploring the strategies companies use in sharing and disseminating knowledge and expertise among employees. "A Theory of Knowledge Management" (Richard J. Torraco), develops a conceptual…

  1. Discovery of Paradigm Dependencies

    Sun, Jizhou; Li, Jianzhong; Gao, Hong

    2017-01-01

    Missing and incorrect values often cause serious consequences. To deal with these data quality problems, a class of common employed tools are dependency rules, such as Functional Dependencies (FDs), Conditional Functional Dependencies (CFDs) and Edition Rules (ERs), etc. The stronger expressing ability a dependency has, data with the better quality can be obtained. To the best of our knowledge, all previous dependencies treat each attribute value as a non-splittable whole. Actually however, i...

  2. Managing Knowledge

    Connolly, Niall

    2013-01-01

    This paper provides a perspective on what knowledge is, why knowledge is important, and how we might encourage good knowledge behaviours. A knowledge management framework is described, and although the framework is project management-centric the basic principles are transferrable to other contexts. From a strategic perspective, knowledge can be considered an asset that has the potential to provide a competitive advantage provided that it has intrinsic value, it is not easily accessible by ...

  3. Performance Evaluation of Frequent Subgraph Discovery Techniques

    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.

  4. Resource Discovery in Activity-Based Sensor Networks

    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...

  5. 'The Lusiads', poem of discovery

    Natasha Furlan Felizi

    2016-07-01

    Full Text Available The article proposes reading Os Lusíadas as a discovery journey. Discovery here read as aletheia or “revelation”, as proposed by Sophia de Mello Brey­ner Andresen in 1980. Using Martin Heidegger’s notion of aletheia in the book Parmenides along with Jorge de Sena and Sophia de Mello Breyner Andresen reflections on Camões, I’ll seek to point out alternative readings for Os Lusíadas as a “discovery journey”.

  6. Discovery of convoys in trajectory databases

    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....

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

    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

  8. Discovery of natural resources

    Guild, P.W.

    1976-01-01

    Mankind will continue to need ores of more or less the types and grades used today to supply its needs for new mineral raw materials, at least until fusion or some other relatively cheap, inexhaustible energy source is developed. Most deposits being mined today were exposed at the surface or found by relatively simple geophysical or other prospecting techniques, but many of these will be depleted in the foreseeable future. The discovery of deeper or less obvious deposits to replace them will require the conjunction of science and technology to deduce the laws that governed the concentration of elements into ores and to detect and evaluate the evidence of their whereabouts. Great theoretical advances are being made to explain the origins of ore deposits and understand the general reasons for their localization. These advances have unquestionable value for exploration. Even a large deposit is, however, very small, and, with few exceptions, it was formed under conditions that have long since ceased to exist. The explorationist must suppress a great deal of "noise" to read and interpret correctly the "signals" that can define targets and guide the drilling required to find it. Is enough being done to ensure the long-term availability of mineral raw materials? The answer is probably no, in view of the expanding consumption and the difficulty of finding new deposits, but ingenuity, persistence, and continued development of new methods and tools to add to those already at hand should put off the day of "doing without" for many years. The possibility of resource exhaustion, especially in view of the long and increasing lead time needed to carry out basic field and laboratory studies in geology, geophysics, and geochemistry and to synthesize and analyze the information gained from them counsels against any letting down of our guard, however (17). Research and exploration by government, academia, and industry must be supported and encouraged; we cannot wait until an eleventh

  9. Knowledge Sharing

    Holdt Christensen, Peter

    The concept of knowledge management has, indeed, become a buzzword that every single organization is expected to practice and live by. Knowledge management is about managing the organization's knowledge for the common good of the organization -but practicing knowledge management is not as simple...... as that. This article focuses on knowledge sharing as the process seeking to reduce the resources spent on reinventing the wheel.The article introduces the concept of time sensitiveness; i.e. that knowledge is either urgently needed, or not that urgently needed. Furthermore, knowledge sharing...... is considered as either a push or pull system. Four strategies for sharing knowledge - help, post-it, manuals and meeting, and advice are introduced. Each strategy requires different channels for sharing knowledge. An empirical analysis in a production facility highlights how the strategies can be practiced....

  10. Discovery of the monopole

    Galitskij, V.

    1978-01-01

    An experiment is described conducted in Berkeley in which the magnetic monopole was first detected. The objections are reported of prof. Fowler (U.K.) and prof. Alvarez (U.S.A.) permitting a different interpretation of experimental data. (Z.J.)

  11. Discovery of hydrodynamic behavior in high energy heavy ion collisions

    Hamagaki, Hideki

    2010-01-01

    The objective of high energy heavy ion collision experiments is creating high temperature and high density states to investigate hadron matter properties in such extreme conditions. Since the start of heavy ion collision experiments with BEVALAC, knowledge of the space-time evolution of collision has become indispensable for understanding the hadronic matter properties. This problem is reviewed here from the hydrodynamics view point. Although its importance has been generally recognized since the time of BEVALAC, the hydrodynamic description has not been successful because the hydrodynamic model assuming non-viscous or small fluid had not been considered to be enough to properly describe the space-time evolution of hadron-hadron collisions until the RHIC experiments. Items of the following titles are picked up and reviewed here: Development of heavy ion accelerations; Space-time evolution of hadron collision process and hydrodynamic model; Chemical freezing and kinematical freezing, including transverse momentum spectra at proton-proton collisions and particle spectra in heavy ion collisions; Elliptical azimuthal angle anisotropy; Discovery of hydrodynamic flow at BEVALAC; Problems of incident beam dependence of v2; Elliptic azimuthal angle anisotropy at RHIC; What is it that carries the elliptic anisotropy? Discussion of attainment of thermodynamical equilibrium state at RHIC; and finally investigations of fluid properties other than azimuthal anisotropy, such as, Fluid properties probed by heavy quarks and Observing QCD fluid responses. (S. Funahashi)

  12. Knowledge management

    Foss, Nicolai Juul; Mahnke, Volker

    2003-01-01

    Knowledge management has emerged as a very successful organization practice and has beenextensively treated in a large body of academic work. Surprisingly, however, organizationaleconomics (i.e., transaction cost economics, agency theory, team theory and property rightstheory) has played no role...... in the development of knowledge management. We argue thatorganizational economics insights can further the theory and practice of knowledge managementin several ways. Specifically, we apply notions of contracting, team production,complementaries, hold-up, etc. to knowledge management issues (i.e., creating...... and integrationknowledge, rewarding knowledge workers, etc.) , and derive refutable implications that are novelto the knowledge management field from our discussion....

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

    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.

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

    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

  15. RAS - Screens & Assays - Drug Discovery

    The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.

  16. Antibody informatics for drug discovery

    Shirai, Hiroki; Prades, Catherine; Vita, Randi

    2014-01-01

    to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic...... infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies...... for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii...

  17. Discovery of the iron isotopes

    Schuh, A.; Fritsch, A.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Twenty-eight iron isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  18. Discovery of the silver isotopes

    Schuh, A.; Fritsch, A.; Ginepro, J.Q.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Thirty-eight silver isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  19. Synthetic biology of antimicrobial discovery

    Zakeri, Bijan; Lu, Timothy K.

    2012-01-01

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore, used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery. PMID:23654251

  20. Discovery of the cadmium isotopes

    Amos, S.; Thoennessen, M.

    2010-01-01

    Thirty-seven cadmium isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  1. Discoveries of isotopes by fission

    country of discovery as well as the production mechanism used to produce the isotopes. ... the disintegration products of bombarded uranium, as a consequence of a ..... advanced accelerator and newly developed separation and detection ...

  2. Synthetic biology of antimicrobial discovery.

    Zakeri, Bijan; Lu, Timothy K

    2013-07-19

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug-resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery.

  3. The discovery of 'heavy light'

    Anon.

    1983-01-01

    The history of the discoveries of fundamental quanta is described starting from Maxwell's theory of electromagnetism up to the development of a theory of weak interaction and the detection of the W and Z bosons. (HSI).

  4. Discovery – Development of Rituximab

    NCI funded the development of rituximab, one of the first monoclonal antibody cancer treatments. With the discovery of rituximab, more than 70 percent of patients diagnosed with non-hodgkin lymphoma now live five years past their initial diagnosis.

  5. Knowledge Representation and Ontologies

    Grimm, Stephan

    Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

  6. On Discovery of Gathering Patterns from Trajectories

    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...

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

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

    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

  9. Accessible Knowledge - Knowledge on Accessibility

    Kirkeby, Inge Mette

    2015-01-01

    Although serious efforts are made internationally and nationally, it is a slow process to make our physical environment accessible. In the actual design process, architects play a major role. But what kinds of knowledge, including research-based knowledge, do practicing architects make use of when...... designing accessible environments? The answer to the question is crucially important since it affects how knowledge is distributed and how accessibility can be ensured. In order to get first-hand knowledge about the design process and the sources from which they gain knowledge, 11 qualitative interviews...... were conducted with architects with experience of designing for accessibility. The analysis draws on two theoretical distinctions. The first is research-based knowledge versus knowledge used by architects. The second is context-independent knowledge versus context-dependent knowledge. The practitioners...

  10. Standard model of knowledge representation

    Yin, Wensheng

    2016-09-01

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

  11. Integrating knowledge seeking into knowledge management models and frameworks

    Francois Lottering

    2012-09-01

    Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking. Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies. Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing. Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies.

  12. Software patterns, knowledge maps, and domain analysis

    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

  13. Knowledge spaces

    Doignon, Jean-Paul

    1999-01-01

    Knowledge spaces offer a rigorous mathematical foundation for various practical systems of knowledge assessment. An example is offered by the ALEKS system (Assessment and LEarning in Knowledge Spaces), a software for the assessment of mathematical knowledge. From a mathematical standpoint, knowledge spaces generalize partially ordered sets. They are investigated both from a combinatorial and a stochastic viewpoint. The results are applied to real and simulated data. The book gives a systematic presentation of research and extends the results to new situations. It is of interest to mathematically oriented readers in education, computer science and combinatorics at research and graduate levels. The text contains numerous examples and exercises and an extensive bibliography.

  14. Protecting knowledge

    Sofka, Wolfgang; de Faria, Pedro; Shehu, Edlira

    2018-01-01

    Most firms use secrecy to protect their knowledge from potential imitators. However, the theoretical foundations for secrecy have not been well explored. We extend knowledge protection literature and propose theoretical mechanisms explaining how information visibility influences the importance...... of secrecy as a knowledge protection instrument. Building on mechanisms from information economics and signaling theory, we postulate that secrecy is more important for protecting knowledge for firms that have legal requirements to reveal information to shareholders. Furthermore, we argue that this effect...... and a firm's investment in fixed assets. Our findings inform both academics and managers on how firms balance information disclosure requirements with the use of secrecy as a knowledge protection instrument....

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

    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…

  16. Distributed Service Discovery for Heterogeneous Wireless Sensor Networks

    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

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

    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)

  18. 巴赫型音乐对波普尔“客观知识”学说的影响%The Influence of Bach-Type Music on Popper's Thought of Objective Knowledge

    何超

    2012-01-01

    摘耍:波普尔的“客客观知识”在其客观性属性上,类似于超脱贝多芬的自我性、体现客观美感的巴赫型音乐。巴赫音乐音符与音符之间具有严谨又不失美感的客观秩序、不能被理性所摒弃的严密的数的逻辑构架,其客观性诉求与波普尔寻求超脱于主观、从而能够在客观形式中达到统一的知识类型——“客观知识”学说建构之间,存在发生学关联,直接导致波普尔对世界2与世界3的医分。巴赫型音乐对于波普尔科学哲学的深刻影响,为音乐与科学、哲学之间的彼此通约,提供了典型的个案。关键词:波普尔;巴赫型音乐;贝多芬;客观知识;世界3%The objective style of Bach type music enlightens in depth the thought of "objective knowledge" proposed by Karl Popper. Beethoven's music gives expression to "subjective" appeal, while Bach-type music, "subjective" soberness and reason in style. Karl Popper's "objective knowledge" is based on the partition of three worlds. As "world 3", it is characterized by objectivity, autonomy, shareability, etc. The isostructuralism and coherence in style between "objective knowledge" and Bach- type music provide an illustrative case for the commensuration of art and philosophy in certain sense through the reflective han- dling by Karl Popper.

  19. 42 CFR 426.432 - Discovery.

    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...

  20. 40 CFR 27.21 - Discovery.

    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...

  1. 13 CFR 134.213 - Discovery.

    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...

  2. 37 CFR 41.150 - Discovery.

    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...

  3. 19 CFR 354.10 - Discovery.

    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...

  4. 14 CFR 13.220 - Discovery.

    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...

  5. 49 CFR 604.38 - Discovery.

    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...

  6. 15 CFR 719.10 - Discovery.

    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...

  7. 14 CFR 16.213 - Discovery.

    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...

  8. 28 CFR 76.21 - Discovery.

    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...

  9. 36 CFR 1150.63 - Discovery.

    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...

  10. 10 CFR 13.21 - Discovery.

    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...

  11. 49 CFR 1121.2 - Discovery.

    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...

  12. 24 CFR 26.18 - Discovery.

    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...

  13. 38 CFR 42.21 - Discovery.

    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...

  14. 22 CFR 521.21 - Discovery.

    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...

  15. 31 CFR 10.71 - Discovery.

    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...

  16. 42 CFR 426.532 - Discovery.

    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...

  17. 39 CFR 955.15 - Discovery.

    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...

  18. 49 CFR 1503.633 - Discovery.

    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...

  19. 43 CFR 35.21 - Discovery.

    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...

  20. 14 CFR 1264.120 - Discovery.

    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...