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UNIVERSITY of CALGARY Concept-Learning Supported
UNIVERSITY OF CALGARY Concept-Learning Supported Semantic Search using Multi-Agent System by Cheng Zhong A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING CALGARY, ALBERTA April, 2009 © Cheng Zhong 2009 ISBN: 978-0-494-51171-8 UNIVERSITY OF CALGARY FACULTY OF GRADUATE STUDIES The undersigned certify that they have read, and recommend to the Faculty of Graduate Studies for acceptance, a thesis entitled "Concept-Learning Supported Semantic Search using Multi-Agent System" submitted by Cheng Zhong in partial fulfilment of the requirements of the degree of Master of Science. Supervisor, Dr. B. H. Far Department of Electrical and Computer Engineering Dr. M. Moussavi Department of Electrical and Computer Engineering Dr. D. Krishnamurthy Department of Electrical and Computer Engineering Dr. Y. Hu Department of Electrical and Computer Engineering Dr. M. Ghaderi Department of Computer Science Date ii Abstract Currently, the mainstream of semantic search is based on both centralized networking that could be barrier to access trillions of dynamically generated bytes on individual websites, and group commitment to a common ontology that is often too strong or unrealistic. In real world, it is preferred to enable stakeholders of knowledge to exchange information freely while they keep their own individual ontology. While this assumption makes stakeholders represent their knowledge more independently and gives them more flexibility, it brings complexity to the communication among them. To solve this communication complexity, in this thesis, we present (1) a method for semantic search supported by ontological concept learning, and (2) a prototype multi-agent system that can handle semantic search and encapsulate the complexity of such process from the users. -
Artificial Intelligence in Health Care: the Hope, the Hype, the Promise, the Peril
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril Michael Matheny, Sonoo Thadaney Israni, Mahnoor Ahmed, and Danielle Whicher, Editors WASHINGTON, DC NAM.EDU PREPUBLICATION COPY - Uncorrected Proofs NATIONAL ACADEMY OF MEDICINE • 500 Fifth Street, NW • WASHINGTON, DC 20001 NOTICE: This publication has undergone peer review according to procedures established by the National Academy of Medicine (NAM). Publication by the NAM worthy of public attention, but does not constitute endorsement of conclusions and recommendationssignifies that it is the by productthe NAM. of The a carefully views presented considered in processthis publication and is a contributionare those of individual contributors and do not represent formal consensus positions of the authors’ organizations; the NAM; or the National Academies of Sciences, Engineering, and Medicine. Library of Congress Cataloging-in-Publication Data to Come Copyright 2019 by the National Academy of Sciences. All rights reserved. Printed in the United States of America. Suggested citation: Matheny, M., S. Thadaney Israni, M. Ahmed, and D. Whicher, Editors. 2019. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. NAM Special Publication. Washington, DC: National Academy of Medicine. PREPUBLICATION COPY - Uncorrected Proofs “Knowing is not enough; we must apply. Willing is not enough; we must do.” --GOETHE PREPUBLICATION COPY - Uncorrected Proofs ABOUT THE NATIONAL ACADEMY OF MEDICINE The National Academy of Medicine is one of three Academies constituting the Nation- al Academies of Sciences, Engineering, and Medicine (the National Academies). The Na- tional Academies provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. -
Deep Semantics in the Geosciences: Semantic Building Blocks for a Complete Geoscience Infrastructure
Deep Semantics in the Geosciences: semantic building blocks for a complete geoscience infrastructure Brandon Whitehead,1,2 Mark Gahegan1 1Centre for eResearch 2 Institute of Earth Science and Engineering The University of Auckland, Private Bag 92019, Auckland, New Zealand {b.whitehead, m.gahegan}@auckland.ac.nz Abstract. In the geosciences, the semantic models, or ontologies, available are typically narrowly focused structures fit for single purpose use. In this paper we discuss why this might be, with the conclusion that it is not sufficient to use semantics simply to provide categorical labels for instances—because of the interpretive and uncertain nature of geoscience, researchers need to understand how a conclusion has been reached in order to have any confidence in adopting it. Thus ontologies must address the epistemological questions of how (and possibly why) something is ‘known’. We provide a longer justification for this argument, make a case for capturing and representing these deep semantics, provide examples in specific geoscience domains and briefly touch on a visualisation program called Alfred that we have developed to allow researchers to explore the different facets of ontology that can support them applying value judgements to the interpretation of geological entities. Keywords: geoscience, deep semantics, ontology-based information retrieval 1 Introduction From deep drilling programs and large-scale seismic surveys to satellite imagery and field excursions, geoscience observations have traditionally been expensive to capture. As such, many disciplines related to the geosciences have relied heavily on inferential methods, probability, and—most importantly—individual experience to help construct a continuous (or, more complete) description of what lies between two data values [1]. -
The Ingham County News Oh! ~.No ••••• Published THURSDAY AFTERNOONS Rev
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R Markdown Cheat Sheet I
1. Workflow R Markdown is a format for writing reproducible, dynamic reports with R. Use it to embed R code and results into slideshows, pdfs, html documents, Word files and more. To make a report: R Markdown Cheat Sheet i. Open - Open a file that ii. Write - Write content with the iii. Embed - Embed R code that iv. Render - Replace R code with its output and transform learn more at rmarkdown.rstudio.com uses the .Rmd extension. easy to use R Markdown syntax creates output to include in the report the report into a slideshow, pdf, html or ms Word file. rmarkdown 0.2.50 Updated: 8/14 A report. A report. A report. A report. A plot: A plot: A plot: A plot: Microsoft .Rmd Word ```{r} ```{r} ```{r} = = hist(co2) hist(co2) hist(co2) ``` ``` Reveal.js ``` ioslides, Beamer 2. Open File Start by saving a text file with the extension .Rmd, or open 3. Markdown Next, write your report in plain text. Use markdown syntax to an RStudio Rmd template describe how to format text in the final report. syntax becomes • In the menu bar, click Plain text File ▶ New File ▶ R Markdown… End a line with two spaces to start a new paragraph. *italics* and _italics_ • A window will open. Select the class of output **bold** and __bold__ you would like to make with your .Rmd file superscript^2^ ~~strikethrough~~ • Select the specific type of output to make [link](www.rstudio.com) with the radio buttons (you can change this later) # Header 1 • Click OK ## Header 2 ### Header 3 #### Header 4 ##### Header 5 ###### Header 6 4. -
Japanese Bibliographic Records and CJK Cataloging in U.S
San Jose State University SJSU ScholarWorks Master's Theses Master's Theses and Graduate Research Fall 2009 Japanese bibliographic records and CJK cataloging in U.S. university libraries. Mie Onnagawa San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_theses Recommended Citation Onnagawa, Mie, "Japanese bibliographic records and CJK cataloging in U.S. university libraries." (2009). Master's Theses. 4010. DOI: https://doi.org/10.31979/etd.pcb8-mryq https://scholarworks.sjsu.edu/etd_theses/4010 This Thesis is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Theses by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. JAPANESE BIBLIOGRAPHIC RECORDS AND CJK CATALOGING IN U.S. UNIVERSITY LIBRARIES A Thesis Presented to The Faculty of the School of Library and Information Science San Jose State University In Partial Fulfillment of the Requirements for the Degree Master of Library and Information Science by Mie Onnagawa December 2009 UMI Number: 1484368 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMT Dissertation Publishing UM! 1484368 Copyright 2010 by ProQuest LLC. All rights reserved. This edition of the work is protected against unauthorized copying under Title 17, United States Code. -
Introduction to Ontologies Part I
EMMC The European Materials Modelling Council Introduction to Ontologies Part I Alexandra Simperler On-line 29.4.2019 https://emmc.info/ EMMC The EMMO round table Emanuele Ghedini (University of Bologna) Gerhard Goldbeck Adham Hashibon (Goldbeck Consulting) (Fraunhofer Institut) Georg J. Schmitz Jesper Friis (Access) (SINTEF) EMMC Outline • Taxonomy vs Ontology • The value of ontologies • Semantic Technologies • Representation of Ontologies What’s the difference between an EMMC ontology and a taxonomy? TAXONOMY ONTOLOGY • Like a tree with branches • Like a spiderweb • Parent – Child relation, • Manifold of relations, is_a adds non is_a relations • Generally limited to a • Not limited to a specific specific subject area subject area • Hierarchy of (simple) • Complex relations with concepts complex concepts EMMC The Value of Semantic Technologies • Natural perspective of human communication • Greater expressivity than a database • Improved logical structure • Knowledge layer is separated from data layer • Flexibility, reusability, interoperability • Hierarchies, relationships and annotation • Search patterns can be stored, share, reused • Reasoning – answers to what-if, if-then questions • Accessible to Artificial Intelligence EMMC The Value of Ontology in the Materials Field Artificial Intelligence Materials Ontology will contribute to: Semantic Web Systems Engineering • High throughput experiments Biomedical Informatics • High throughput characterization Library Science • Cost reduction Enterprise Bookmarking Information Architecture • Reliable results • Standard operation procedures (SOPs) • Design of materials with improved characteristics All these fields create Ontologies to limit • Classification of techniques and complexity and acceleration of results organize information. The Ontology can then • Uniform query interface be applied to problem solving. EMMC Examples/Use of Ontologies • Database integration – Connected data! Discover new trends – Takahashi, et al (2018). -
Course Structure & Syllabus of B.Tech Programme In
Course Structure & Syllabus of B.Tech Programme in Information Technology (From the Session 2015-16) VSSUT, BURLA COURSE STRUCTURE FIRST YEAR (COMMON TO ALL BRANCHES) FIRST SEMESTER SECOND SEMESTER Contact Contact Theory Hrs. Theory Hrs. CR CR Course Course Subject L .T .P Subject L. T. P Code Code Mathematics-I 3 - 1 - 0 4 Mathematics-II 3 - 1 - 0 4 Physics/Chemistry 3 - 1 - 0 4 Chemistry/ Physics 3 - 1 - 0 4 Engineering Computer /CS15- CS15- Mechanics/Computer 3 - 1 - 0 4 Programming/Engineering 3 - 1 - 0 4 008 008/ Programming Mechanics Basic Electrical Engineering/ Basic Electronics/Basic 3 - 1 - 0 4 3 - 1 - 0 4 Basic Electronics Electrical Engineering English/Environmental Environmental 3 - 1 - 0 4 3 - 1 - 0 4 Studies Studies/English Sessionals Sessionals Physics Laboratory/ Chemistry Lab/ Physics 0 - 0 - 3 2 0 - 0 - 3 2 Chemistry Lab Laboratory Workshop-I/Engineering Engineering Drawing/ 0 - 0 - 3 2 0 - 0 - 3 2 Drawing Workshop-I Basic Electrical Engineering Basic Electronics Lab/Basic 0 - 0 - 3 2 0 - 0 - 3 2 Lab/Basic Electronics Lab Electrical Engineering Lab Business Communication Programming Lab/ /CS15- CS15- and Presentation Skill/ 0 - 0 - 3 2 Business Communication 0 - 0 - 3 2 984 984/ Programming Lab and Presentation Skill Total 15-5-15 28 Total 15-5-15 28 SECOND YEAR THIRD SEMESTER FOURTH SEMESTER Contact Contact Theory Hrs. Theory Hrs. CR CR Course Subject L .T .P Course Code Subject L. T. P Code Mathematics-III Computer Organization 3 - 1 - 0 4 CS15-007 and Architecture 3 - 1 - 0 4 Digital Systems 3 - 1 - 0 4 CS15-032 Theory -
Ech-0205 V1.0 Linked Open Data
E-Government Standards Page 1 of 49 eCH-0205 Linked Open Data Name Linked Open Data eCH-number eCH-0205 Category Accessory Document Quality stage Defined Version 1.0 Status Approved Decision on 2018-03-06 Date of issue 2018-03-13 Replaces version - Requirements - Annexes - Languages English (original) Authors Members of the eCH Specialized Group “Open Government Data” Main Author: Beat Estermann, Berner Fachhochschule [email protected] For a list of further contributors, see Annex B. Editor / Distribution eCH registered association, Mainaustrasse 30, Postfach [P.O. Box], 8034 Zürich T 044 388 74 64, F 044 388 71 80 www.ech.ch / [email protected] eCH registered association www.ech.ch / [email protected] eCH-0205 Linked Open Data / 1.0 / Approved / 2018-03-13 E-Government Standards Page 2 of 49 Summary This document provides the Swiss Linked Data community with a shared vision of the state of linked open data publication in the public and heritage sectors in Switzerland and gives people who are new to the community a first overview of previous and ongoing activities in the area of data publication, data use, and know-how exchange. The document contains a short introduction to linked (open) data, gives a detailed account of what linked data publica- tion is about, provides an overview of the present state of linked data publication by Swiss public and heritage sector organizations, and presents a series of exemplary use cases that serve as test and study cases to tackle current challenges and demonstrate the usefulness of linked (open) data in practice. -
Rmarkdown : : CHEAT SHEET RENDERED OUTPUT File Path to Output Document SOURCE EDITOR What Is Rmarkdown? 1
rmarkdown : : CHEAT SHEET RENDERED OUTPUT file path to output document SOURCE EDITOR What is rmarkdown? 1. New File Write with 5. Save and Render 6. Share find in document .Rmd files · Develop your code and publish to Markdown ideas side-by-side in a single rpubs.com, document. Run code as individual shinyapps.io, The syntax on the lef renders as the output on the right. chunks or as an entire document. set insert go to run code RStudio Connect Rmd preview code code chunk(s) Plain text. Plain text. Dynamic Documents · Knit together location chunk chunk show End a line with two spaces to End a line with two spaces to plots, tables, and results with outline start a new paragraph. start a new paragraph. narrative text. Render to a variety of 4. Set Output Format(s) Also end with a backslash\ Also end with a backslash formats like HTML, PDF, MS Word, or and Options reload document to make a new line. to make a new line. MS Powerpoint. *italics* and **bold** italics and bold Reproducible Research · Upload, link superscript^2^/subscript~2~ superscript2/subscript2 to, or attach your report to share. ~~strikethrough~~ strikethrough Anyone can read or run your code to 3. Write Text run all escaped: \* \_ \\ escaped: * _ \ reproduce your work. previous modify chunks endash: --, emdash: --- endash: –, emdash: — chunk run options current # Header 1 Header 1 chunk ## Header 2 Workflow ... Header 2 2. Embed Code ... 11. Open a new .Rmd file in the RStudio IDE by ###### Header 6 Header 6 going to File > New File > R Markdown. -
Conda-Build Documentation Release 3.21.5+15.G174ed200.Dirty
conda-build Documentation Release 3.21.5+15.g174ed200.dirty Anaconda, Inc. Sep 27, 2021 CONTENTS 1 Installing and updating conda-build3 2 Concepts 5 3 User guide 17 4 Resources 49 5 Release notes 115 Index 127 i ii conda-build Documentation, Release 3.21.5+15.g174ed200.dirty Conda-build contains commands and tools to use conda to build your own packages. It also provides helpful tools to constrain or pin versions in recipes. Building a conda package requires installing conda-build and creating a conda recipe. You then use the conda build command to build the conda package from the conda recipe. You can build conda packages from a variety of source code projects, most notably Python. For help packing a Python project, see the Setuptools documentation. OPTIONAL: If you are planning to upload your packages to Anaconda Cloud, you will need an Anaconda Cloud account and client. CONTENTS 1 conda-build Documentation, Release 3.21.5+15.g174ed200.dirty 2 CONTENTS CHAPTER ONE INSTALLING AND UPDATING CONDA-BUILD To enable building conda packages: • install conda • install conda-build • update conda and conda-build 1.1 Installing conda-build To install conda-build, in your terminal window or an Anaconda Prompt, run: conda install conda-build 1.2 Updating conda and conda-build Keep your versions of conda and conda-build up to date to take advantage of bug fixes and new features. To update conda and conda-build, in your terminal window or an Anaconda Prompt, run: conda update conda conda update conda-build For release notes, see the conda-build GitHub page. -
A Comparison of Flexible BPMN and CMMN in Practice: a Case Study on Component Release Processes
2018 IEEE 22nd International Enterprise Distributed Object Computing Conference A Comparison of Flexible BPMN and CMMN in Practice: A Case Study on Component Release Processes Andre´ Zensen Jochen M. Kuster¨ Bielefeld University of Applied Sciences Bielefeld University of Applied Sciences Bielefeld, Germany Bielefeld, Germany Email: [email protected] Email: [email protected] Abstract—The Object Management Group maintains two no- derive simple guidelines. While the findings can not be used tations to model business processes, BPMN and CMMN. While to make generalized statements, they can aid in choosing ff ff the two follow di erent approaches, both o er structures to which standard to use to model processes or parts of processes model flexible processes or parts thereof. This gives rise to the question which standard should be chosen to adequately model requiring flexible parts. such processes. We compare BPMN with a focus on its ad-hoc sub- The work is structured as follows: Section II introduces the process with elements of CMMN case models along a practical approaches and modeling standards. Section III describes the case study. While BPMN offers a certain degree of flexibility, case study and process. Section IV describes the models created CMMN has several benefits but also drawbacks. We discuss to capture the work on tasks needed to release a component advantages and disadvantages of both notations. To answer the question of which notation to use for modeling flexible processes, for production. A comparison is made in section V to highlight we derive simple guidelines to help in making an informed choice.