This webinar will discuss how people facing intermittent and unreliable grid conditions in tough environments can use solar generators to power critical infrastructure. Speaker: Paul Shmotolokha is an IEEE member in Seattle. He presented and exhibited at GHTC 2022. Paul is the CEO of (https://www.newuseenergy.com/) (NUE). NUE's solar power systems are being deployed in (https://www.uschamber.com/small-business/how-one-small-business-helped-ukraine-power-up-in-a-time-of-need). REGISTER NOW @ https://www.newuseenergy.com/webinar-solar-generators-in-ukraine-a-case-study-on-resilience/ Co-sponsored by: Paul Shmotolokha, CEO of New Use Energy (NUE) Virtual: https://events.vtools.ieee.org/m/334285

Abstract: First published in 1998, Roger Grace Associates has created and conducted the MEMS Industry Commercialization Report Card (Report Card) Study which has annually monitored the “health” of the worldwide MEMS industry vis-à-vis 14 subjects (a.k.a. critical success factors) and supplemented by verbatims from the respondents. The Report Card market study uses the “Delphi Method” which is based on the inputs of a limited number of highly experienced and acknowledged worldwide MEMS industry experts. The 2021 Report Card overall grade was a C+ which declined from the previous five years grade of B- and with virtually all of the 14 subjects receiving decreasing grades. The hundreds of verbatim responses received along with the letter grades emphatically showed the culprit of the grade decreases to be inextricably linked to the results of the effects of Covid. This was especially true in the subject of “Established Infrastructure” where the grade decreased from B+ to B- and was primarily due to supply chain disruptions. Recommendations of the study include actionable strategies to mitigate and overcome the highly expected resulting negative effects to the MEMS commercialization process due to expected continuance of Covid into 2022. Speaker(s): Mr. Roger H. Grace, Agenda: 6:30 – 6:45 PM Zoom Registration & Networking 6:50 – 7:00 PM Announcements & Polling 7:00 – 7:45 PM Invited Talk 7:45 – 8:00 PM Questions & Answers Virtual: https://events.vtools.ieee.org/m/332120

Industry 5.0 promises to have robots and people working side-by-side, accomplishing things that neither one would be able to do as well alone. But what will it take to make this happen? How can one ensure, and more importantly measure, the safety, efficiency, and effectiveness of a human-robot collaborative systems. What might the future of the manufacturing world look like? In this talk a vision of this future will be presented, highlighting work being performed at the National Institute of Standards and Technology as well as other efforts around the world. Speaker(s): Dr.Craig Schlenoff, Virtual: https://events.vtools.ieee.org/m/326200

Autonomous robots depend on their perception systems to understand the world around them. These machines often leverage a host of sensors including cameras, lidars, radars, and ultrasonic sensors to create this environmental understanding. Stereo cameras play a big role in providing depth perception to robotic systems. This depth information can be estimated using classical computer vision techniques, like semi-global matching (SGM) or leverage deep neural networks (DNNs). Each individual algorithm may struggle in a particular set of operating conditions. But when multiple depth estimation algorithms are leveraged simultaneously, It is possible that more robust depth information can be calculated. In this talk, we'll cover work at NVIDIA to train the ESS DNN model for determining stereo disparity using both synthetic and real-world data to perform well where SGM may not. We'll also introduce the Bi3D model which is trained on the simplified question of "is X closer than M meters?" rather than "how far away is X?", yielding improvements in both accuracy and speed. As every approach has deficiencies on its own, we'll touch upon how ensembling the responses of ESS and Bi3D, DNNs developed specifically for robotic perception with SGM could lead to robust obstacle detection. Finally, we'll discuss how we've tuned the performance of these models to run on embedded compute for the responsive stopping behavior required in autonomous mobile robots (AMRs). Speaker(s): Hemal Shah, Gerard Andrews Agenda: 6:30 PM Introduction (Tom Coughlin) 6:45 PM Talk 7:30 PM Q&A 8:00 PM End Virtual: https://events.vtools.ieee.org/m/332953

The common mode (CM) voltage generated by a switching power converter yields unwanted currents to circulate in the ground paths, tripping ground faults relays, accelerating motor bearing aging, and producing electromagnetic interference (EMI). Typical differential mode (DM) models of power converters do not account for CM paths and currents, so models including parasitic components and CM voltages must be used to predict CM EMI. In this presentation CM modeling and analysis will be highlighted and popular CM EMI mitigation methods, including passive filters, active filters, and novel power converter topologies will be briefly summarized. The second part of the presentation will focus on novel CM voltage elimination methods based on a game-changing shift from pulse width modulation (PWM) to pulse density modulation (PDM) for grid-forming and grid-following inverters. Rapid prototyping of three-phase four-leg inverters, built with wide bandgap devices (WBG), will also be presented to demonstrate the elimination of the CM voltage at the switching frequency and significantly reducing the size of the CM passive filters required to meet the conducted emission limits in MIL-STD-461G. Speaker(s): Dr. Giovanna Oriti, Virtual: https://events.vtools.ieee.org/m/329518

Sponsored by the (https://vtsociety.org/chapter/santa-clara-valley-joint-section-chapter) (https://us02web.zoom.us/webinar/register/WN_D7J6sY6pRzusWcCWp7EbyA) When: Dec 8, 2022 06:00 -7.00 PM Pacific Time (US and Canada) The IEEE P2851 standardization initiative was started to define a dependability lifecycle as well as methods and formats for exchange/interoperability of data across all steps of the lifecycle in a consistent way. Additionally, the work products of this standardization initiative will help enable interoperability between tools. The goal of this work is to provide structures and directions to allow a seamless exchange of information and interoperability between activities at the same or different level of abstraction, as well as activities across lifecycles related to different dependability attributes across application domains such as automotive, industrial, medical and avionics safety critical systems. Co-sponsored by: Buenaventura Section Chapter Speaker(s): Jyotika Athavale, Virtual: https://events.vtools.ieee.org/m/335845

Sponsored by the (https://vtsociety.org/chapter/santa-clara-valley-joint-section-chapter) (https://us02web.zoom.us/webinar/register/WN_D7J6sY6pRzusWcCWp7EbyA) When: Dec 8, 2022 06:00 -7.00 PM Pacific Time (US and Canada) The IEEE P2851 standardization initiative was started to define a dependability lifecycle as well as methods and formats for exchange/interoperability of data across all steps of the lifecycle in a consistent way. Additionally, the work products of this standardization initiative will help enable interoperability between tools. The goal of this work is to provide structures and directions to allow a seamless exchange of information and interoperability between activities at the same or different level of abstraction, as well as activities across lifecycles related to different dependability attributes across application domains such as automotive, industrial, medical and avionics safety critical systems. Co-sponsored by: Buenaventura Section Chapter Speaker(s): Jyotika Athavale, Virtual: https://events.vtools.ieee.org/m/335845

Free Registration: https://www.eventbrite.com/e/democratizing-nlp-considerations-from-resources-to-algorithms-tickets-450900324007 Synopsis: n recent times, there is an enormous increase in the use of digital media as a channel for communication. This, combined with the fact that natural language is a ubiquitous mode of communication, has increased the volume of natural language data available for processing. Also, this has resulted in opportunities for extending NLP based services/solutions in multiple languages. Although existing algorithms for NLP tasks have been shown to achieve reasonable performances for the high-resource languages such as English, French etc. across tasks, the same is not true for many other languages widely spoken in the world. To ensure that the benefit of NLP research reaches a wider audience across different regions, it is important to pay special focus to the low-resource languages, or consider support for low-resource languages in an intelligent manner in the algorithm design phase. The talk will touch upon a few such considerations in this talk. Speaker(s): Dr Desarkar, Vishnu S. Pendyala Virtual: https://events.vtools.ieee.org/m/329813