Abstraction, Reformulation, and Approximation
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Conserving Common Ground: Exploring the Place of Cultural Heritage in Protected Area Management
University of Calgary PRISM: University of Calgary's Digital Repository Graduate Studies The Vault: Electronic Theses and Dissertations 2020-12-08 Conserving Common Ground: Exploring the Place of Cultural Heritage in Protected Area Management Weller, Jonathan Weller, J. (2020). Conserving Common Ground: Exploring the Place of Cultural Heritage in Protected Area Management (Unpublished doctoral thesis). University of Calgary, Calgary, AB. http://hdl.handle.net/1880/112818 doctoral thesis University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. Downloaded from PRISM: https://prism.ucalgary.ca UNIVERSITY OF CALGARY Conserving Common Ground: Exploring the Place of Cultural Heritage in Protected Area Management by Jonathan Weller A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN ENVIRONMENTAL DESIGN CALGARY, ALBERTA DECEMBER, 2020 © Jonathan Weller 2020 ii Abstract That parks and protected areas are places where the conservation of cultural heritage can and should take place has not always been immediately apparent. However, today there is widespread acknowledgement that the management of cultural heritage resources needs to be brought into large-scale planning and management processes in an integrated and holistic manner. This is particularly true in protected areas, which not only contain significant cultural heritage resources, but are also often mandated to conserve these resources and can benefit significantly from the effort. -
The 10Th Annual CON-RCO Obesity Summer Boot Camp Delegates Will Receive a Certificate of Attendance
th the 10 Annual SUMMER BOOT CAMP JULY 18–26, 2015 Delta Lodge at Kananaskis, Kananaskis Village, Alberta, Canada TABLE OF coNTENTS Learning Objectives 3 Message from the Host 4 General Information 5 Daily Schedule 6 Speakers 12 Floor plan 21 Faculty Contact List 22 Trainee Contact List 23 THE OBESITY Boot CAMP HAS BEEN MADE POSSIBLE THE CANADIAN OBESITY NETWORK’S SUPPORTERS. We are extremely grateful for their help in making the boot camp possible! Alberta-Saxony Obesity Research & Training Alliance Canadian Beverage Association Canadian Institutes of Health Research Coca Cola Craving Change Dairy Farmers of Canada Ethicon Integrated Research and Treatment Center (IFB) Adiposity Diseases Natural Factors Nestle Health Science Novo Nordisk TOPS Club Inc. (Take Pounds Off Sensibly) LEARNING OBJEctIVES The overall objective of the Boot Camp is to provide participants with a sound outline of the scientific and method- ological issues around obesity research. The camp aims to cover all aspects of obesity ranging from epidemiology and public health to cell biology, energy regulation, clinical management and health policy. The Canadian Obesity Network – Réseau canadien en obésité (CON-RCO) is a broad network of over 10,000 organizations and individuals from many sectors and disciplines who are committed to stemming the tide of obesity in Canada and to reducing the mental, physical and economic burden of obesity on Canadians. The mission of CON-RCO is to act as a catalyst for addressing obesity in Canada and to foster knowledge translation, capacity building, and partnerships among stakeholders so that researchers, health professionals, policy makers and other stakeholders may develop effective solutions to treat, and to prevent obesity. -
Appendix A—Digest of Other White House Announcements
Appendix A—Digest of Other White House Announcements The following list includes the President’s public President Vicente Fox of Mexico to discuss the schedule and other items of general interest an- situation in Argentina. nounced by the Office of the Press Secretary In the afternoon, the President traveled to and not included elsewhere in this book. Portland, OR, and later returned to the Bush Ranch in Crawford, TX. January 1 In the morning, at the Bush Ranch in January 7 Crawford, TX, the President had an intelligence In the morning, the President had an intel- briefing. ligence briefing. Later, he returned to Wash- The President issued an emergency declara- ington, DC. tion for areas struck by record and near-record The President announced the recess appoint- snowfall in New York. ment of John Magaw to be Under Secretary January 2 of Transportation for Security. In the morning, the President had an intel- The President announced his intention to ligence briefing. nominate Anthony Lowe to be Administrator of the Federal Insurance Administration at the January 3 Federal Emergency Management Agency. In the morning, the President had an intel- The President announced his intention to des- ligence briefing. ignate Under Secretary of Commerce for Inter- national Trade Grant D. Aldonas, Deputy Sec- January 4 retary of Labor Donald C. Findlay, and Under In the morning, the President had an intel- Secretary of the Treasury for International Af- ligence briefing. He then traveled to Austin, TX, and later returned to Crawford, TX. fairs John B. Taylor as members of the Board The President announced his intention to of the Overseas Private Investment Corporation. -
Dear Colleague Letter: OFR-NSF Partnership in Support of Research Collaborations in Finance Informatics
National Science Foundation 4201 Wilson Boulevard Arlington, Virginia 22230 NSF 13-093 Dear Colleague Letter: Date: May 14, 2013 The Directorate for Computer and Information Science and Engineering (CISE) of the National Science Foundation (NSF) and the Office of Financial Research (OFR) of the Department of Treasury share an interest in advancing basic and applied research centered on Computational and Information Processing Approaches to and Infrastructure in support of, Financial Research and Analysis and Management (CIFRAM). The complexity of modern financial instruments presents many challenges in recognizing and regulating Systemic Risk. The topic has been the subject of a recent National Academy of Science Report titled "Technical Capabilities Necessary for Systemic Risk Regulation: Summary of a Workshop." The CISE directorate and the Computing Community Consortium have sponsored workshops on Knowledge Representation and Information Management for Financial Risk Management and on Next-Generation Financial Cyberinfrastructure aimed at identifying research opportunities and challenges in CIFRAM. NSF and OFR have established a collaboration (hereafter referred to as CIFRAM) to identify and fund a small number of exploratory but potentially transformative CIFRAM research proposals. The collaboration enables OFR to support a broad range of financial research related to OFR’s mission, including research on potential threats to financial stability. It also assists OFR with the goal of promoting and encouraging collaboration between the government, the private sector, and academic institutions interested in furthering financial research and analysis. The collaboration enables the NSF to nurture fundamental CISE research on a variety of topics including algorithms, informatics, knowledge representation, and data analytics needed to advance the current state of the art in financial research and analysis. -
Calendar of Events APRIL 6–7 Workshop on Lexical Semantics Systems (WLSS–98)
AI Magazine Volume 19 Number 1 (1998) (© AAAI) E-mail: [email protected] Calendar of Events APRIL 6–7 Workshop on Lexical Semantics Systems (WLSS–98). Pisa, Italy ■ Contact: Alessandro Lenci Scuola Normale Superiore College Park, MD 20742 Laboratorio di linguistica March 1998 Piazza dei Cavalieri 7 MARCH 23–27 56126 Pisa, Italy MARCH 16–20 Practical Application Expo-98. Voice: +39 50 509219 Fourth World Congress on Expert London. Fax: +39 50 563513 Systems. Mexico City, Mexico celi.sns.it/~wlss98 ■ Contact: Tenth International Symposium on Steve Cartmell Artificial Intelligence. Mexico City, Practical Application Company APRIL 6–8 Mexico PO Box 173, Blackpool 1998 International Symposium on ■ Sponsor: Lancs. FY2 9UN Physical Design (ISPD–98). Mon- ITESM Center for Artificial United Kingdom terey, CA Intelligence Voice: +44 (0)1253 358081 ■ Sponsors: ■ Contact: Fax: +44 (0)1253 353811 ACM SIGDA, in cooperation with Rogelio Soto E-mail: [email protected] IEEE Circuits and Systems Society Program Chair, ITESM www.demon.co.uk/ar/Expo98/ and IEEE Computer Society Centro de Inteligencia Artificial ■ Contact: Av. Eugenio Garza Sada #2501 Sur D. F. Wong Monterrey, N. L. 64849, Mexico Technical Program Chair, ISPD–98 Voice: (52–8) 328-4197 University of Texas at Austin Fax: (52-8) 328-4189 April 1998 Department of Computer Sciences E-mail: [email protected]. Austin, TX 78712 APRIL 1–4 itesm.mx E-mail: [email protected] Second European Conference on www.ee.iastate.edu/~ispd98 Cognitive Modeling (ECCM–98). MARCH 16–20 Nottingham, UK International Workshop on APRIL 14–17 ■ Intelligent Agents on the Internet Contact: Fourteenth European Meeting on and Web. -
Technology and Engineering International Journal of Recent
International Journal of Recent Technology and Engineering ISSN : 2277 - 3878 Website: www.ijrte.org Volume-7 Issue-5S2, JANUARY 2019 Published by: Blue Eyes Intelligence Engineering and Sciences Publication d E a n n g y i n g o e l e o r i n n h g c e T t n e c Ijrt e e E R X I N P n f L O I O t T R A o e I V N O l G N r IN n a a n r t i u o o n J a l www.ijrte.org Exploring Innovation Editor-In-Chief Chair Dr. Shiv Kumar Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT), Senior Member of IEEE Professor, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence (LNCTE), Bhopal (M.P.), India Associated Editor-In-Chief Chair Dr. Dinesh Varshney Professor, School of Physics, Devi Ahilya University, Indore (M.P.), India Associated Editor-In-Chief Members Dr. Hai Shanker Hota Ph.D. (CSE), MCA, MSc (Mathematics) Professor & Head, Department of CS, Bilaspur University, Bilaspur (C.G.), India Dr. Gamal Abd El-Nasser Ahmed Mohamed Said Ph.D(CSE), MS(CSE), BSc(EE) Department of Computer and Information Technology, Port Training Institute, Arab Academy for Science, Technology and Maritime Transport, Egypt Dr. Mayank Singh PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu- Natal, Durban, South Africa. Scientific Editors Prof. -
Node Injection a Acks on Graphs Via Reinforcement Learning
Node Injection Aacks on Graphs via Reinforcement Learning Yiwei Sun, , Suhang Wangx , Xianfeng Tang, Tsung-Yu Hsieh, Vasant Honavar Pennsylvania State University fyus162, szw494, xut10 ,tuh45 ,[email protected] ABSTRACT (a) (b) (c) Real-world graph applications, such as advertisements and prod- uct recommendations make prots based on accurately classify the label of the nodes. However, in such scenarios, there are high incentives for the adversaries to aack such graph to reduce the node classication performance. Previous work on graph adversar- ial aacks focus on modifying existing graph structures, which is clean graph dummy attacker smart attacker infeasible in most real-world applications. In contrast, it is more practical to inject adversarial nodes into existing graphs, which can Figure 1: (a) is the toy graph where the color of a node repre- also potentially reduce the performance of the classier. sents its label; (b) shows the poisoning injection attack per- In this paper, we study the novel node injection poisoning aacks formed by a dummy attacker; (c) shows the poisoning in- problem which aims to poison the graph. We describe a reinforce- jection attack performed by a smart attacker. e injected ment learning based method, namely NIPA, to sequentially modify nodes are circled with dashed line. the adversarial information of the injected nodes. We report the results of experiments using several benchmark data sets that show the superior performance of the proposed method NIPA, relative to Recent works [12, 32, 35] have shown that even the state-of-the- the existing state-of-the-art methods. art graph classiers are susceptible to aacks which aim at adversely impacting the node classication accuracy. -
Bow & Kananaskis Valleys Trail
Old Fort Creek 1300 Stone Creek To Cochrane 1650 To Calgary BOW CORRIDOR & To Banff Bow Valley 0 40 20 3 Yamnuska 0 4 2 0 Tibits 3 N Ridge 6 Quarry 0 KANANASKIS VALLEY 0 0 3 NW NE Montane 1 Wildland 8 0 0 8 1A 2 Traverse 2000 W E Bow 1 0 Ridge 0 6 0 2 Yamnuska River Mount Traverse SW SE Harvie 1 Mount John Laurie 2 0 0 4 Stoneworks 2 Lady MacDonald Provincial 1 (aka Yamnuska) 4 Mount Heights Creek 0 2 0 2 S 1 6 0 0 2,606 m 0 2 1 8 0 Rundle 1 2,240 m Meander ROAD CLOSURES: 2,949 m ParkEExxplpl rree Montane HIGHWAY #40: Traverse Mount Lady Cougar Bow Valley st Bow Valley 1 MacDonald Creek Closed December 1 to Wildland th Wildlife Corridor Wildland June 14 inclusive from Johnny’s Management Area Stoney Provincial 1500 Nakoda Kananaskis Lakes Trail to 1X Resort & Chiniki Canmore Lake Park Cougar Provincial Brewster’s Casino the Highwood House Junction. Goat Kananaskis Nordic Creek Jura Slabs Guest Douglas Montane Creek Ranch 40 Centre Policeman’s Fir Traverse Loder Park 1A 1 Creek Bench Door Jamb Peak P POWDERFACE TRAIL/ROAD: Banff Provincial Mountain 2,088 m Flowing 1,996m Open May 1- Water Closed December 1st to May 14th, P Bow October Long Park Nanny Goat Weekend National Butress Valley Canmore Bow River Montane inclusive south of Dawson. Kananaskis Nordic Centre Grotto Exshaw Mountain Grotto Creek Park Day Lodge Horseshoe 2500 Mountain Willow Stoney Nation Canmore Loop 2,706 m Kid Goat Bow Rock No 142, 143, 144 Butress WhiteshMoraine Valley Reclaimer 1500 Bike ALBERTA East End Grassi Middle Path 2000 Lake Grassi Lakes 2200 Middle (Paved) -
AAAI-12 Conference Committees
AAAI 2012 Conference Committees Chairs and Cochairs AAAI Conference Committee Chair Dieter Fox (University of Washington, USA) AAAI12 Program Cochairs Jörg Hoffmann (Saarland University, Germany) Bart Selman (Cornell University, USA) IAAI12 Conference Chair and Cochair Markus Fromherz (ACS, a Xerox Company, USA) Hector Munoz‐Avila (Lehigh University, USA) EAAI12 Symposium Chair David Kauchak (Middlebury College, USA) Special Track on Artificial Intelligence and the Web Cochairs Denny Vrandecic (Institute of Applied Informatics and Formal Description Methods, Germany) Chris Welty (IBM Research, USA) Special Track on Cognitive Systems Cochairs Matthias Scheutz (Tufts University, USA) James Allen (University of Rochester, USA) Special Track on Computational Sustainability and Artificial Intelligence Cochairs Carla P. Gomes (Cornell University, USA) Brian C. Williams (Massachusetts Institute of Technology, USA) Special Track on Robotics Cochairs Kurt Konolige (Industrial Perception, Inc., USA) Siddhartha Srinivasa (Carnegie Mellon University, USA) Turing Centenary Events Chair Toby Walsh (NICTA and University of New South Wales, Australia) Tutorial Program Cochairs Carmel Domshlak (Technion Israel Institute of Technology, Israel) Patrick Pantel (Microsoft Research, USA) Workshop Program Cochairs Michael Beetz (University of Munich, Germany) Holger Hoos (University of British Columbia, Canada) Doctoral Consortium Cochairs Elizabeth Sklar (Brooklyn College, City University of New York, USA) Peter McBurney (King’s College London, United Kingdom) -
An Incremental Learning Algorithm with Confidence Estimation For
990 ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 8, august 2004 An Incremental Learning Algorithm with Confidence Estimation for Automated Identification of NDE Signals Robi Polikar, Member, IEEE, Lalita Udpa, Senior Member, IEEE, Satish Udpa, Fellow, IEEE, and Vasant Honavar, Member, IEEE Abstract—An incremental learning algorithm is intro- • applications calling for analysis of large volumes of duced for learning new information from additional data data; and/or that may later become available, after a classifier has al- • applications in which human factors may introduce ready been trained using a previously available database. The proposed algorithm is capable of incrementally learn- significant errors. ing new information without forgetting previously acquired knowledge and without requiring access to the original Such NDE applications are numerous, including but are database, even when new data include examples of previ- not limited to, defect identification in natural gas trans- ously unseen classes. Scenarios requiring such a learning mission pipelines [1], [2], aircraft engine and wheel compo- algorithm are encountered often in nondestructive evalua- nents [3]–[5], nuclear power plant pipings and tubings [6], tion (NDE) in which large volumes of data are collected in batches over a period of time, and new defect types may [7], artificial heart valves, highway bridge decks [8], optical become available in subsequent databases. The algorithm, components such as lenses of high-energy laser generators named Learn++, takes advantage of synergistic general- [9], or concrete sewer pipelines [10] just to name a few. ization performance of an ensemble of classifiers in which A rich collection of classification algorithms has been each classifier is trained with a strategically chosen subset of the training databases that subsequently become avail- developed for a broad range of NDE applications. -
Conference Program Contents AAAI-14 Conference Committee
Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14) Twenty-Sixth Conference on Innovative Applications of Artificial Intelligence (IAAI-14) Fih Symposium on Educational Advances in Artificial Intelligence (EAAI-14) July 27 – 31, 2014 Québec Convention Centre Québec City, Québec, Canada Sponsored by the Association for the Advancement of Artificial Intelligence Cosponsored by the AI Journal, National Science Foundation, Microso Research, Google, Amazon, Disney Research, IBM Research, Nuance Communications, Inc., USC/Information Sciences Institute, Yahoo Labs!, and David E. Smith In cooperation with the Cognitive Science Society and ACM/SIGAI Conference Program Contents AAAI-14 Conference Committee AI Video Competition / 7 AAAI acknowledges and thanks the following individuals for their generous contributions of time and Awards / 3–4 energy to the successful creation and planning of the AAAI-14, IAAI-14, and EAAI-14 Conferences. Computer Poker Competition / 7 Committee Chair Conference at a Glance / 5 CRA-W / CDC Events / 4 Subbarao Kambhampati (Arizona State University, USA) Doctoral Consortium / 6 AAAI-14 Program Cochairs EAAI-14 Program / 6 Carla E. Brodley (Northeastern University, USA) Exhibition /24 Peter Stone (University of Texas at Austin, USA) Fun & Games Night / 4 IAAI Chair and Cochair General Information / 25 David Stracuzzi (Sandia National Laboratories, USA) IAAI-14 Program / 11–19 David Gunning (PARC, USA) Invited Presentations / 3, 8–9 EAAI-14 Symposium Chair and Cochair Posters / 4, 23 Registration / 9 Laura -
World Climate Research Programme__WCRP LAND
Global Energy and Water Cycle Experiment NEWS Vol. 12, No. 2 NEWS May 2002 World Climate Research Programme__WCRP LAND-SURFACE DATA ASSIMILATION SYSTEM CONCEPTS ARE EXPANDING (See Articles on Pages 2 and 9) SUPER-PARAMETERIZATIONS: FAST FORWARD TO THE FUTURE David Randall and Marat Khairoutdinov Colorado State University Editor's Note: This is a summary of a talk given at the GCSS-ARM workshop in Kananaskis, Canada. Deficiencies in the representation of cloud- What's New dynamical processes in climate models drive much of the uncertainty surrounding predictions of cli- mate change. This was true 30 years ago and it is • SSG Members and Panel Chairs Highlighted still true now. To take conventional parameterizations • CEOP to benefit from GLDAS much beyond where we are now, it seems likely that we will have to make them very complicated—in • GSWP-2 to Begin this Year some ways much more complicated than Cloud-Sys- • GCSS and GLASS Set Strategies for the Future (Continued on Page 5) COMMENTARY GLDAS: AN IMPORTANT CONTRIBUTION TO CEOP NEW GEWEX SSG MEMBERS ENHANCE INTERDISCIPLINARY AND Paul R. Houser and Matthew Rodell INTERNATIONAL GUIDANCE Soroosh Sorooshian, Chair Hydrological Sciences Branch GEWEX Scientific Steering Group NASA Goddard Space Flight Center The GEWEX Scientific Steering Group (SSG) has Scientists at NASA's Goddard Space Flight Center added more new members than usual this cycle after (GSFC) have developed a high-resolution Global Land many years of excellent service from our previous mem- Data Assimilation System (GLDAS) in cooperation with bers. The diversity of this SSG provides an opportunity to researchers at NOAA's National Centers for Environ- enhance our interdisciplinary and international participa- mental Prediction (NCEP).