BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Office of Advanced Research Computing - ECPv6.0.10//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Office of Advanced Research Computing X-ORIGINAL-URL:https://oarc.rutgers.edu X-WR-CALDESC:Events for Office of Advanced Research Computing REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20230312T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20231105T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20231102T133000 DTEND;TZID=America/New_York:20231102T150000 DTSTAMP:20260404T170332 CREATED:20221007T190909Z LAST-MODIFIED:20231013T174619Z UID:7850-1698931800-1698937200@oarc.rutgers.edu SUMMARY:Machine Learning: Decision Trees and Random Forests DESCRIPTION:This workshop will give an introduction to machine learning methods with decision trees and random forests. \nSupplemental materials are available at https://libguides.rutgers.edu/datascience/python \n​ \n \n Learn more and register URL:https://oarc.rutgers.edu/event/11-2-23/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231102T153000 DTEND;TZID=America/New_York:20231102T163000 DTSTAMP:20260404T170332 CREATED:20221007T191124Z LAST-MODIFIED:20231013T205812Z UID:7854-1698939000-1698942600@oarc.rutgers.edu SUMMARY:Evidence Synthesis in the Social Sciences DESCRIPTION:Systematic\, Scoping\, and Literature Reviews\, Oh My! An Introduction to Evidence Synthesis in the Social Sciences \nAre you a social science faculty member or graduate student interested in learning about systematic or scoping reviews? Are you curious about what these methods entail? This workshop is for you! \nEvidence synthesis methods are growing in popularity among social science disciplines\, but many faculty and students aren’t sure of the steps\, tools\, resources\, or types of methods used in an evidence synthesis project. This workshop will provide a broad overview of the concepts behind evidence synthesis\, so that you can approach future projects with confidence. \nYou will also have the opportunity to provide valuable feedback on this workshop\, which will inform future evidence synthesis library workshops and support. \nThis workshop is part of a series on Evidence Synthesis in the Social Sciences. \n \n Learn more and register URL:https://oarc.rutgers.edu/event/11-2-23-systematic-scoping-literature-reviews/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231103T130000 DTEND;TZID=America/New_York:20231103T160000 DTSTAMP:20260404T170332 CREATED:20230126T220043Z LAST-MODIFIED:20230126T221038Z UID:8275-1699016400-1699027200@oarc.rutgers.edu SUMMARY:Deep Learning with Python and Keras DESCRIPTION:Register to attend this workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. \nDeep learning (DL) outperforms Machine Learning (ML) in many applications such as Computer Vision (CV) and Natural Language Processing (NLP). In this workshop\, we will go through the basics of artificial neural networks (ANN)\, Convolutional Neural Networks (CNN)\, Recurrent Neural Networks (RNN)\, and Transformers\, and focus on doing hands-on training to apply these DL models on image and text data for building predictive analytics. \n\nObjective of the workshop\nUnderstand the basics of Artificial Neural Networks (ANN)\nPrepare image and text data suitable for the neural networks\nLearn how to apply various DL models such as ANN\, CNN\, RNN\, and Transformers\nImprove the accuracy of the model with hyperparameter optimization\n\nIf you have questions or need help\, please email Bala Desinghu. \nAmarel account: Apply here as soon as possible. You must have an Amarel account set up before the workshop. \nVPN setup: You have to be connected on Rutgers’ network or be on VPN to access Amarel resources. \nSSH setup: Windows users must install an SSH client like PuTTY or MobaXterm. Alternatively\, Windows 10 users can install the complete Windows Subsystem for Linux. \nRegister to attend the workshop:\n Notice: JavaScript is required for this content. URL:https://oarc.rutgers.edu/event/deep-learning-with-python-and-keras-11-3-23/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231108T100000 DTEND;TZID=America/New_York:20231108T180000 DTSTAMP:20260404T170332 CREATED:20231017T182853Z LAST-MODIFIED:20231017T192710Z UID:9218-1699437600-1699466400@oarc.rutgers.edu SUMMARY:Big Ten Academic Alliance GIS Conference 2023 DESCRIPTION:Registration for the 2023 conference is now open! \nKeynote Speaker: Katie McDonough\, Alan Turing InstituteThe Conference Planning Committee is pleased to announce Katie McDonough as the 2023 BTAA GIS Conference Keynote Speaker\, presenting “Reading Maps: Making\, Searching\, and Interpreting Text on Maps”. \nMachine learning methods are transforming the ways that anyone can interact with map collections. Using the results of a computer vision pipeline to understand past places at scale comes with new challenges and opportunities. The Machines Reading Maps project has worked with partners at the Library of Congress\, the National Library of Scotland\, the British Library\, and also the David Rumsey Map Collection to create datasets of the text on large collections of digitized maps. This talk explores the results of the Machines Reading Maps project to date including our work in progress to\, on the one hand\, visualize and analyze the results for historical research\, and\, on the other\, use text on maps data to improve map collection discovery. \nPlease register to ensure that you receive the Zoom links and invitation \nRelated links:BTAA Geoportal \nBig Ten Academic Alliance Geospatial Information Network \n \n Register URL:https://oarc.rutgers.edu/event/btaa-gis-conference-2023/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231109T133000 DTEND;TZID=America/New_York:20231109T150000 DTSTAMP:20260404T170332 CREATED:20221007T191440Z LAST-MODIFIED:20231013T185512Z UID:7858-1699536600-1699542000@oarc.rutgers.edu SUMMARY:Machine Learning: Deep Learning and Convolutional Neural Networks DESCRIPTION:This workshop will discuss Deep Learning and Convolutional Neural Networks as used in Machine Learning. \nSupplemental materials are available at https://libguides.rutgers.edu/datascience/python \n \n Register and learn more URL:https://oarc.rutgers.edu/event/11-9-23/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231114T130000 DTEND;TZID=America/New_York:20231114T143000 DTSTAMP:20260404T170332 CREATED:20230201T201247Z LAST-MODIFIED:20231013T212030Z UID:8336-1699966800-1699972200@oarc.rutgers.edu SUMMARY:Collecting Newspaper Data Programmatically Using R DESCRIPTION:In this introductory workshop\, we will access historical and current newspaper data via web APIs using the programming language R. We will use freely available newspaper data from the Library of Congress’s Chronicling America website and the New York Times Developer Portal. We will generate dataframes and create some simple data visualizations from downloaded data. \n \n Learn more and register URL:https://oarc.rutgers.edu/event/11-14-23/ CATEGORIES:Research END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231115T163000 DTEND;TZID=America/New_York:20231115T183000 DTSTAMP:20260404T170332 CREATED:20221007T192118Z LAST-MODIFIED:20231013T212133Z UID:7867-1700065800-1700073000@oarc.rutgers.edu SUMMARY:Mapathon for Humanitarian Relief DESCRIPTION:Location: Hatchery Innovation Studio in Alexander LibraryCelebrate GIS Day and Geography Awareness week! Together with fellow Rutgers students\, staff and faculty\, you will contribute geospatial data to OpenStreetMap\, a free and editable map of the world that is used by communities\, organizations and governments worldwide to address local development challenges and aid disaster response. Our project will be decided closer to the date. In past years\, Rutgers students\, staff\, and faculty worked together on a mapping project to help NGO efforts with relief operations in Puerto Rico\, the Democratic Republic of the Congo and Tanzania. No mapping experience or knowledge is necessary. Training will be provided. Join at any time during the scheduled event!We will use the Humanitarian OpenStreetMap platform to contribute data. The selected project will be appropriate for beginners. If you’re looking for a head start\, sign up for a HOTOSM account and check out these online tutorials about HOTOSM and their iD editor: \n\nHOTOSM account and click ‘Sign Up’\n“The iD Editor”\nHumanitarian OpenStreetMap Two Minute Tutorials\n\n \n Learn more and register URL:https://oarc.rutgers.edu/event/11-15-23/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231116T100000 DTEND;TZID=America/New_York:20231116T113000 DTSTAMP:20260404T170332 CREATED:20231016T140736Z LAST-MODIFIED:20231016T142023Z UID:9342-1700128800-1700134200@oarc.rutgers.edu SUMMARY:Collecting Newspaper Data Programmatically Using R DESCRIPTION:In this introductory workshop\, we will access historical and current newspaper data via web APIs using the programming language R. We will use freely available newspaper data from the Library of Congress’s Chronicling America website and the New York Times Developer Portal. We will generate dataframes and create some simple data visualizations from downloaded data. \n \n Learn more and register URL:https://oarc.rutgers.edu/event/collecting-newspaper-data-programmatically-using-r/ CATEGORIES:Research END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/New_York:20231121T080000 DTEND;TZID=America/New_York:20231122T190000 DTSTAMP:20260404T170332 CREATED:20230217T194152Z LAST-MODIFIED:20230217T200246Z UID:8451-1700553600-1700679600@oarc.rutgers.edu SUMMARY:Amarel monthly maintenance DESCRIPTION:Usually scheduled for every 3rd Tuesday and Wednesday of the month from 08:00 ET on the first day till 19:00 ET on the second day. \n2023 anticipated maintenance schedule (all dates subject to change):\nJAN 24-25 (1 week late)\nFEB 21-22\nMAR 14 -15 (1 week earlier\, spring break)\nAPR 18-19\nMAY 16-17\nJUN 20-21\nJUL 18-19\nAUG 15-16\nSEP 19-20\nOCT 17-18\nNOV 21-22\nDEC 19-20 \nMaintenance is usually scheduled for weekdays because it often involves coordination with University facilities teams or external vendors. There may also be times when Amarel must be unavailable due to externally-scheduled data center facilities\, power\, or telecommunications maintenance. When this happens\, we will do our best to avoid adding to a month’s downtime with our own maintenance work (e.g.\, by working in parallel or postponing some tasks). \n \n Visit Amarel system status for more information URL:https://oarc.rutgers.edu/event/amarel-monthly-maintenance-11-21-23/ END:VEVENT END:VCALENDAR