BEGIN:VCALENDAR VERSION:2.0 PRODID:-//IEEE Toronto Section - ECPv6.15.17//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-ORIGINAL-URL:https://www.ieeetoronto.ca X-WR-CALDESC:Events for IEEE Toronto Section 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:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20221106T060000 END:STANDARD 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:VTIMEZONE TZID:UTC BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:+0000 TZNAME:UTC DTSTART:20200101T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20220123T110000 DTEND;TZID=America/New_York:20220123T120000 DTSTAMP:20260417T222707 CREATED:20220119T022107Z LAST-MODIFIED:20220123T120320Z UID:10000497-1642935600-1642939200@www.ieeetoronto.ca SUMMARY:The Bitcoin Blockchain DESCRIPTION:Join us to learn about the basics of the Bitcoin blockchain\, how mining works\, and what hashes are. The Bitcoin blockchain was the first cryptocurrency\, but not the first use of blockchain; blockchain was invented much earlier than the Bitcoin creation. Both Bitcoin and blockchain topics will be covered over the course of this session. At the end of the workshop we will have a Q&A section to answer any questions. \nSpeaker(s): Adi Malihi \nClick here to register. URL:https://www.ieeetoronto.ca/event/the-bitcoin-blockchain/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/299554 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211216T120000 DTEND;TZID=UTC:20211216T130000 DTSTAMP:20260417T222707 CREATED:20211125T133529Z LAST-MODIFIED:20220105T232652Z UID:10000493-1639656000-1639659600@www.ieeetoronto.ca SUMMARY:Introduction to CPI’s Satcom & Medical Products DESCRIPTION:Founded in 1948\, CPI is a global manufacturer of electronic components and subsystems focused primarily on communications and defense markets. The company develops\, manufactures\, and globally distributes innovative and reliable technology solutions used in the generation\, amplification\, transmission\, and reception of microwave signals for commercial and military applications. CPI serves customers in the communications\, defense\, medical\, industrial\, and scientific markets. \nThe Satcom & Medical Products Division of CPI is located in Georgetown\, Ontario. This presentation introduces some of the CPI products\, basic technical background\, and the application of High Voltage for such medical and Satcom products. \nSpeaker(s): Mahdi Khanali \nAgenda: Registration is mandatory. \nRegister: https://events.vtools.ieee.org/m/291432 URL:https://www.ieeetoronto.ca/event/introduction-to-cpis-satcom-medical-products/ LOCATION:Toronto\, Ontario\, Canada END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211214T170000 DTEND;TZID=UTC:20211214T183000 DTSTAMP:20260417T222707 CREATED:20211109T123536Z LAST-MODIFIED:20220105T094814Z UID:10000489-1639501200-1639506600@www.ieeetoronto.ca SUMMARY:Ethics: How might the machine learning make the world a better place? How might it make the world worse? DESCRIPTION:How might the machine learning make the world a better place?\nHow might it make the world worse?\nI have some thoughts. Likely you do too.\nVirtual: https://events.vtools.ieee.org/m/289243 URL:https://www.ieeetoronto.ca/event/ethics-how-might-the-machine-learning-make-the-world-a-better-place-how-might-it-make-the-world-worse/ LOCATION:Virtual: https://events.vtools.ieee.org/m/289243 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211212T093000 DTEND;TZID=UTC:20211212T160000 DTSTAMP:20260417T222707 CREATED:20211022T100329Z LAST-MODIFIED:20220105T232818Z UID:10000316-1639301400-1639324800@www.ieeetoronto.ca SUMMARY:IEEE Toronto Member Appreciation at The Toronto Zoo DESCRIPTION:The IEEE Toronto would like to thank all of our members for sticking with us through the pandemic. As our way of saying thank you\, we would like to invite you and your family (or friends) to join us for lunch and wild times at the Toronto Zoo! \nIncluded in the $10 per person registration fee: \n\nOne general admission ticket to the Toronto Zoo\nIEEE-Toronto branded swag\nLunch at the Special Events Centre (inside the Zoo)\n\nAt least one IEEE member number must be provided for each registration. Each IEEE member may bring up to 3 additional friend or family members. \nPlease note that all participants in the event must adhere to the Toronto Zoo mask and vaccination policies. URL:https://www.ieeetoronto.ca/event/ieee-toronto-member-appreciation-at-the-toronto-zoo/ LOCATION:The Toronto Zoo\, 2000 Meadowvale Rd\, Toronto\, Ontario\, Canada\, M1B 5K7\, Virtual: https://events.vtools.ieee.org/m/286646 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211211T170000 DTEND;TZID=UTC:20211211T190000 DTSTAMP:20260417T222707 CREATED:20211205T071803Z LAST-MODIFIED:20220105T232859Z UID:10000495-1639242000-1639249200@www.ieeetoronto.ca SUMMARY:Introduction to Web Development with HTML and CSS Part 3 DESCRIPTION:Ieee Programming HTML and CSS workshops from Saturday 27 November to 18 December \nCo-sponsored by: Professor Arman Hamzehlou Kahrizi \nAgenda: It is a hands-on workshop aiming to introduce the basics of web design using HTML5 and CSS. In this series of workshops\, we will step-by-step\, create and publish a simple and responsive website to a web-hosting service and finally optimize our website for search engines (SEO) so the website is better picked up by the search engine during a search query. \nVirtual: https://events.vtools.ieee.org/m/293260 URL:https://www.ieeetoronto.ca/event/introduction-to-web-development-with-html-and-css-part-3/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/293260 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211211T100000 DTEND;TZID=UTC:20211211T110000 DTSTAMP:20260417T222707 CREATED:20211211T074913Z LAST-MODIFIED:20220105T232933Z UID:10000496-1639216800-1639220400@www.ieeetoronto.ca SUMMARY:Machine Learning Applications in Cybersecurity Domain. DESCRIPTION:Internet is the baseline for cyberspace\, where technology infrastructure can be autonomous. It is a virtual space that can be accessed via different interconnected network devices. Cyber-security can be described as a set of measures that makes cyberspace safe. Identifying threats and predicting vulnerabilities in this environment are the key components of the security mechanism. The main cause of security violations is the intrusion of an attacker into the network or electronic devices. Machine learning can be used to increase the accuracy level of detection of threats to improve system efficiency and performance. In this talk\, we present how machine learning can help detect and mitigate cyber threats in the systems. \nSpeaker(s): Dr. Mizanur Rahman \nVirtual: https://events.vtools.ieee.org/m/294505 URL:https://www.ieeetoronto.ca/event/machine-learning-applications-in-cybersecurity-domain/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/294505 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211207T170000 DTEND;TZID=UTC:20211207T183000 DTSTAMP:20260417T222707 CREATED:20211109T123536Z LAST-MODIFIED:20220105T233027Z UID:10000488-1638896400-1638901800@www.ieeetoronto.ca SUMMARY:Generative Adversarial Networks: Used for understanding and producing a random data item DESCRIPTION:Prerequisites: You do not need to have attended the earlier talks. If you know zero math and zero machine learning\, then this talk is for you. Jeff will do his best to explain fairly hard mathematics to you. If you know a bunch of math and/or a bunch machine learning\, then these talks are for you. Jeff tries to spin the ideas in new ways. \nLonger Abstract: Suppose you have a distributions of random images of cats. Suppose you want to learn a neural network that takes uniformly random bits as input and outputs an image of a cat according to this same distribution. One fun thing is that this neural network won’t be perfect and hence it will output images of “cats” that it has never seen before. Also you can make small changes in the network input bits and see how it changes the resulting image of a cat. The way we do this is with Generative Adversarial Networks. This is formed by having two competing agents. The task of the first agent\, as described above\, is to output random images of cats. The task of the second is to discern whether a given image was produced by the true random distribution or by the first agent. By competing\, they learn. If we have more time in the talk then we will talk about Convolutional & Recurrent Networks which are used for learning images and sound that are invariant over location and time. \nVirtual: https://events.vtools.ieee.org/m/289241 URL:https://www.ieeetoronto.ca/event/generative-adversarial-networks-used-for-understanding-and-producing-a-random-data-item/ LOCATION:Virtual: https://events.vtools.ieee.org/m/289241 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211204T180000 DTEND;TZID=UTC:20211204T200000 DTSTAMP:20260417T222707 CREATED:20211030T112020Z LAST-MODIFIED:20220105T233546Z UID:10000482-1638640800-1638648000@www.ieeetoronto.ca SUMMARY:IEEE CIC x GMU Indie Game Jam: Finishing up & QnA DESCRIPTION:This series of 5 beginner friendly workshops will teach students how to create their own indie game in Unity. \nWe will teach the building blocks and best practices to create a shooter including creating the player\, creating enemies\, collectibles\, effects\, and more! \nAll who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a showcase with small prizes at the end of the workshop series. \n\nQuick review of last week’s progress (10 minutes)\nIntroduction to the Package Manager & Post Processing package (10 minutes) ● Apply post processing effects to camera (20 minutes)\nImplement camera shaking (20 minutes)\nBreak (10 minutes)\nBuilding our project (10 minutes)\nQnA (40 minutes)\n\nVirtual: https://events.vtools.ieee.org/m/287758 URL:https://www.ieeetoronto.ca/event/ieee-cic-x-gmu-indie-game-jam-finishing-up-qna/ LOCATION:Virtual: https://events.vtools.ieee.org/m/287758 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211204T170000 DTEND;TZID=UTC:20211204T190000 DTSTAMP:20260417T222707 CREATED:20211130T140258Z LAST-MODIFIED:20220105T233218Z UID:10000494-1638637200-1638644400@www.ieeetoronto.ca SUMMARY:Introduction to Web Development with HTML and CSS DESCRIPTION:Ieee Programming HTML and CSS workshops from Saturday 27 November to 18 December \nCo-sponsored by: Professor Arman Hamzehlou Kahrizi \nAgenda: It is a hands-on workshop aiming to introduce the basics of web design using HTML5 and CSS. In this series of workshops\, we will step-by-step\, create and publish a simple and responsive website to a web-hosting service and finally optimize our website for search engines (SEO) so the website is better picked up by the search engine during a search query. \nVirtual: https://events.vtools.ieee.org/m/292234 URL:https://www.ieeetoronto.ca/event/introduction-to-web-development-with-html-and-css-2/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/292234 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211203T160000 DTEND;TZID=UTC:20211203T170000 DTSTAMP:20260417T222707 CREATED:20211125T133527Z LAST-MODIFIED:20220105T233709Z UID:10000492-1638547200-1638550800@www.ieeetoronto.ca SUMMARY:"Advances in Microwave Planar Sensors Using Active Circuitry" by Mohammad Abdolrazzaghi DESCRIPTION:Please join us for an upcoming talk on Dec 03\, 4-5 pm (Eastern Time) by Mohammad Abdolrazzaghi titled “Advances in Microwave Planar Sensors Using Active Circuitry”\, as part of the 2020-2021 IEEE AP-S seminar series. \nAbstract: Nowadays\, electromagnetism (EM) is being extensively investigated as a leading technology on noninvasive sensing. EM sensors make use of metallic elements\, including split-ring resonators (SRRs) and complementary SRRs\, to both radiate or receive EM waves. Using EM sensors to monitor changes in a medium\, e.g. human body\, is based on interrogation of a medium with EM waves that reveals valuable information about its properties. EM-based technologies enable compact\, low-profile\, yet highly sensitive sensors for cutting-edge sensors. In this talk\, a variety of microwave planar sensors will be presented that exhibit high sensitivity for material characterization\, focusing on high-performance sensors aided with active circuitry. Emerging technologies such as machine learning will be introduced that enhances the sensor robustness. Last\, the potential capabilities of the microwave sensors in microwave and mm-wave frequencies will be discussed to conclude the talk. \nSpeaker: Mohammad Abdolrazzaghi received the B.Sc. degree from the Iran University of Science and Technology\, Tehran\, Iran\, in 2009\, and M.Sc. degree from the University of Alberta\, Edmonton\, AB\, Canada\, in 2017\, all in electrical and computer engineering. He then became involved as a research assistant of Microwave and Millimeter Wave Lab (M2M) at the University of Alberta and Electromagnetics Lead at the Phase Advanced Sensors Corp. in Edmonton\, AB. He joined University of Toronto community in 2020 as a PhD student in Electrical and Computer Engineering Department. His research interest includes: Analog Circuit Design\, RF Circuits and Microwave Active Sensors\, Machine learning\, Wireless Power Transfer\, and Phased Arrays. He was awarded Alberta Innovates Technology Futures (AITF) Scholarship from University of Alberta (2015)\, got the first place in for CMC Microsystems’s National Research Council Industrial Collaboration Award in 2015\, and Ontario Graduate Scholarship (2021). \nVirtual: https://events.vtools.ieee.org/m/291426 URL:https://www.ieeetoronto.ca/event/advances-in-microwave-planar-sensors-using-active-circuitry-by-mohammad-abdolrazzaghi/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/291426 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211202T180000 DTEND;TZID=UTC:20211202T200000 DTSTAMP:20260417T222707 CREATED:20211107T122059Z LAST-MODIFIED:20220101T093308Z UID:10000484-1638468000-1638475200@www.ieeetoronto.ca SUMMARY:Six Sigma Quality DESCRIPTION:Six Sigma is a management philosophy and set of methods introduced by Motorola and General Electric to eliminate defects in their products and processes. Six Sigma views variation as the enemy and provides with a goal of having less than 3.4 defects per million opportunities. This methodology prescribes project-oriented improvement phases known as Define\, Measure\, Analyze\, Improve and Control (DMAIC). The most important focus of the Six Sigma methodology is that it propagates companies to become customer centric and deliver customers the products and services in the exact specification\, highest quality\, exact delivery time and quantity Speaker(s): Omar Malik \, Agenda: – Introduction – Bio of the presenter – Presentation of the Webinar – Q & A Virtual: https://events.vtools.ieee.org/m/288981 URL:https://www.ieeetoronto.ca/event/six-sigma-quality/ LOCATION:Virtual: https://events.vtools.ieee.org/m/288981 CATEGORIES:Industrial Electronics END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211130T170000 DTEND;TZID=UTC:20211130T183000 DTSTAMP:20260417T222707 CREATED:20211109T123535Z LAST-MODIFIED:20211230T092235Z UID:10000487-1638291600-1638297000@www.ieeetoronto.ca SUMMARY:Dimension Reduction & Maximum Likelihood: How to compress your data while retaining the key features DESCRIPTION:Prerequisites: You do not need to have attended the earlier talks. If you know zero math and zero machine learning\, then this talk is for you. Jeff will do his best to explain fairly hard mathematics to you. If you know a bunch of math and/or a bunch machine learning\, then these talks are for you. Jeff tries to spin the ideas in new ways. Longer Abstract: A randomly chosen bit string cannot be compressed at all. But if there is a pattern to it\, eg it represents an image\, then maybe it can be compressed. Each pixel of an image is specified by one (or three) real numbers. If an image has thousands/millions of pixels\, then each of these acts as a coordinate of the point where the image sits in a very high dimensional space. A set of such images then corresponds to a set of these points. We can understand the pattern of points/images as follows. Maximum Likelihood assumes that the given set of points/images were randomly chosen according a multi-dimensional normal distribution and then adjusts the parameters of this normal distribution in the way that maximizes the probability of getting the images that we have. The obtained parameters effectively fits an ellipse around the points/images in this high dimensional space. We then reduce the number of dimensions in our space by collapsing this ellipse along its least significant axises. Projecting each point/image to this lower dimensional space compresses the amount of information needed to represent each image. Virtual: https://events.vtools.ieee.org/m/289240 URL:https://www.ieeetoronto.ca/event/dimension-reduction-maximum-likelihood-how-to-compress-your-data-while-retaining-the-key-features/ LOCATION:Virtual: https://events.vtools.ieee.org/m/289240 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211129T120000 DTEND;TZID=UTC:20211129T130000 DTSTAMP:20260417T222707 CREATED:20211121T133554Z LAST-MODIFIED:20211229T092505Z UID:10000490-1638187200-1638190800@www.ieeetoronto.ca SUMMARY:BorealisAI presents: Machine Learning Product Development & Business Value DESCRIPTION:IEEE Canada Region and IEEE Toronto Section Industry Engagement Committees are pleased to announce an exceptional talk by Calvin Gerus\, Director of Product at BorealisAI. The talk is titled “Machine Learning Product Development & Business Value”. Co-sponsored by: BorealisAI Speaker(s): Calvin Gerus\, Virtual: https://events.vtools.ieee.org/m/290691 URL:https://www.ieeetoronto.ca/event/borealisai-presents-machine-learning-product-development-business-value/ LOCATION:Virtual: https://events.vtools.ieee.org/m/290691 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211127T170000 DTEND;TZID=UTC:20211127T180000 DTSTAMP:20260417T222707 CREATED:20211124T133623Z LAST-MODIFIED:20211227T091802Z UID:10000491-1638032400-1638036000@www.ieeetoronto.ca SUMMARY:Introduction to Web Development with HTML and CSS DESCRIPTION:Ieee Programming HTML and CSS workshops from Saturday 27 November to 18 December Co-sponsored by: Professor Arman Hamzehlou Kahrizi Agenda: It is a hands-on workshop aiming to introduce the basics of web design using HTML5 and CSS. In this series of workshops\, we will step-by-step\, create and publish a simple and responsive website to a web-hosting service and finally optimize our website for search engines (SEO) so the website is better picked up by the search engine during a search query. Virtual: https://events.vtools.ieee.org/m/291174 URL:https://www.ieeetoronto.ca/event/introduction-to-web-development-with-html-and-css/ LOCATION:Virtual: https://events.vtools.ieee.org/m/291174 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211125T180000 DTEND;TZID=UTC:20211125T200000 DTSTAMP:20260417T222707 CREATED:20211030T112020Z LAST-MODIFIED:20211225T090309Z UID:10000481-1637863200-1637870400@www.ieeetoronto.ca SUMMARY:IEEE CIC x GMU Indie Game Jam: UI & Game Controller DESCRIPTION:This series of 5 beginner friendly workshops will teach students how to create their own indie game in Unity. We will teach the building blocks and best practices to create a shooter including creating the player\, creating enemies\, collectibles\, effects\, and more! All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a showcase with small prizes at the end of the workshop series. – Quick review of last week’s progress (10 minutes) – Introduction to the Package Manager & Post Processing package (10 minutes) ● Apply post processing effects to camera (20 minutes) – Implement camera shaking (20 minutes) – Break (10 minutes) – Building our project (10 minutes) ● QnA (40 minutes) Virtual: https://events.vtools.ieee.org/m/287756 URL:https://www.ieeetoronto.ca/event/ieee-cic-x-gmu-indie-game-jam-ui-game-controller/ LOCATION:Virtual: https://events.vtools.ieee.org/m/287756 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211123T170000 DTEND;TZID=UTC:20211123T183000 DTSTAMP:20260417T222707 CREATED:20211030T112020Z LAST-MODIFIED:20211223T084823Z UID:10000480-1637686800-1637692200@www.ieeetoronto.ca SUMMARY:Reinforcement Learning Game Tree / Markoff Chains DESCRIPTION:Prerequisites: You do not need to have attended the earlier talks. If you know zero math and zero machine learning\, then this talk is for you. Jeff will do his best to explain fairly hard mathematics to you. If you know a bunch of math and/or a bunch machine learning\, then these talks are for you. Jeff tries to spin the ideas in new ways. Longer Abstract: At the risk of being non-standard\, Jeff will tell you the way he thinks about this topic. Both “Game Trees” and “Markoff Chains” represent the graph of states through which your agent will traverse a path while completing the task. Suppose we could learn for each such state a value measuring “how good” this state is for the agent. Then competing the task in an optimal way would be easy. If our current state is one within which our agent gets to choose the next action\, then she will choose the action that maximizes the value of our next state. On the other hand\, if our adversary gets to choose\, he will choose the action that minimizes this value. Finally\, if our current state is one within which the universe flips a coin\, then each edge leaving this state will be labeled with the probability of taking it. Knowing that that is how the game is played\, we can compute how good each state is. The states in which the task is complete is worth whatever reward the agent receives in the said state. These values somehow trickle backwards until we learn the value of the start state. The computational challenge is that there are way more states then we can ever look at. Speaker(s): Prof. Jeff Edmonds\, Virtual: https://events.vtools.ieee.org/m/287737 URL:https://www.ieeetoronto.ca/event/reinforcement-learning-game-tree-markoff-chains/ LOCATION:Virtual: https://events.vtools.ieee.org/m/287737 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211123T160000 DTEND;TZID=UTC:20211123T173000 DTSTAMP:20260417T222707 CREATED:20211109T123535Z LAST-MODIFIED:20211223T084823Z UID:10000485-1637683200-1637688600@www.ieeetoronto.ca SUMMARY:Third Richard Marceau Energy Symposium DESCRIPTION:IEEE Toronto Section will be the host for the Third Richard Marceau Energy Symposium. Extending the success of prior events\, the Third Richard Marceau Energy Symposium is a collaboration by the Bowman Centre for Sustainable Energy\, the Canadian Academy of Engineering\, and the Canadian Society of Senior Engineers. Agenda: – Welcome by IEEE Toronto Section Chair– Dr. Ali Nabavi – The Continuing Legacy of Dr. Richard Marceau – Canadian Academy of Engineering: Dr. Oskar Sigvaldason – Sigvaldason is the Project Manager for Trottier Energy Futures Project – – CANADA: Evaluation of Three Energy System Chains – Bowman Centre for Sustainable Energy: Marshall Kern – Marshall Kern is the President of the Bowman Centre for Sustainable Energy – – Super-Grid to Strengthen North American Electrical Energy Security – Canadian Society of Senior Engineers: Guy Van Uytven – Guy Van Uytven is the President of the CSSE Please register using the link provided below. Co-sponsored by: Ali Nabavi Speaker(s): .\, Agenda: Agenda: – Welcome by IEEE Toronto Section Chair– Dr. Ali Nabavi – The Continuing Legacy of Dr. Richard Marceau – Canadian Academy of Engineering: Dr. Oskar Sigvaldason – Sigvaldason is the Project Manager for Trottier Energy Futures Project – – CANADA: Evaluation of Three Energy System Chains – Bowman Centre for Sustainable Energy: Marshall Kern – Marshall Kern is the President of the Bowman Centre for Sustainable Energy – – Super-Grid to Strengthen North American Electrical Energy Security – Canadian Society of Senior Engineers: Guy Van Uytven – Guy Van Uytven is the President of the CSSE Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/289246 URL:https://www.ieeetoronto.ca/event/third-richard-marceau-energy-symposium/ LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/289246 END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211123T120000 DTEND;TZID=UTC:20211123T130000 DTSTAMP:20260417T222707 CREATED:20211019T092612Z LAST-MODIFIED:20211223T084823Z UID:10000315-1637668800-1637672400@www.ieeetoronto.ca SUMMARY:3GPP Standards for 5G New Radio: from Release 15 and beyond DESCRIPTION:Event to introduce the 3GPP standardization process and discuss the existing and future specifications for 5G New Radio. The fifth and latest generation of cellular mobile communication protocols (5G) is meant to address use cases well beyond the next decade. The first set of technical specifications for 5G\, also referred to as “New Radio” or NR in 3GPP\, were completed as part of 3GPP Release 15. The standardization work for 5G NR continues and new features are continuously added to address more advanced use cases and verticals. This presentation will provide an overview of the standardization process in 3GPP and an overview of the technical features for Release 16 and Release 17 of the specifications. The presentation will conclude with an outlook of future wireless evolution. Speaker(s): Benoît Pelletier\, Montreal\, Quebec\, Canada URL:https://www.ieeetoronto.ca/event/3gpp-standards-for-5g-new-radio-from-release-15-and-beyond/ LOCATION:Montreal\, Quebec\, Canada CATEGORIES:Young Professionals END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211118T180000 DTEND;TZID=UTC:20211118T200000 DTSTAMP:20260417T222707 CREATED:20211030T112020Z LAST-MODIFIED:20211218T081851Z UID:10000479-1637258400-1637265600@www.ieeetoronto.ca SUMMARY:IEEE CIC x GMU Indie Game Jam: Enemy & Enemy AI DESCRIPTION:This series of 5 beginner friendly workshops will teach students how to create their own indie game in Unity. We will teach the building blocks and best practices to create a shooter including creating the player\, creating enemies\, collectibles\, effects\, and more! All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a showcase with small prizes at the end of the workshop series. – Quick review of last week’s progress (10 minutes) – Add enemy object & its components (10 minutes): ○ Rigidbody 2D (kinematic) ○ Box Collider 2D ○ Sprite Renderer – Add enemy script & implement enemy random generation (20 minutes) ● Implement enemy movement & shooting behaviour (20 minutes) – Break (10 minutes) – Implement bullet damaging player & enemy (20 minutes) – Add game controller script & implement enemy spawning (20 minutes) ● Add basic player resources (health\, ammo) & player score (10 minutes) Virtual: https://events.vtools.ieee.org/m/287749 URL:https://www.ieeetoronto.ca/event/ieee-cic-x-gmu-indie-game-jam-enemy-enemy-ai/ LOCATION:Virtual: https://events.vtools.ieee.org/m/287749 CATEGORIES:Instrumentation & Measurement,Women in Engineering END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20211116T170000 DTEND;TZID=UTC:20211116T183000 DTSTAMP:20260417T222707 CREATED:20211030T112019Z LAST-MODIFIED:20211216T081306Z UID:10000478-1637082000-1637087400@www.ieeetoronto.ca SUMMARY:Generalizing from Training Data DESCRIPTION:Prerequisites: You do not need to have attended the earlier talks. If you know zero math and zero machine learning\, then this talk is for you. Jeff will do his best to explain fairly hard mathematics to you. If you know a bunch of math and/or a bunch machine learning\, then these talks are for you. Jeff tries to spin the ideas in new ways. Longer Abstract: There is some theory. If a machine is found that gives the correct answers on the randomly chosen training data without simply memorizing\, then we can prove that with high probability this same machine will also work well on never seen before instances drawn from the same distribution. The easy proof requires D>m\, where m is the number of bits needed to describe your learned machine and D is the number of train data items. A much harder proof (which we likely won’t cover) requires only D>VC\, where VC is VC-dimension (Vapnik–Chervonenkis) of your machine. The second requirement is easier to meet because VC