IEEE North Jersey Section

The IEEE North Jersey Section's Executive Committee (EXCOM) monthly meeting will be held hybridly. The EXCOM meeting starts at 6:30 pm EST and typically ends at 8:30 pm. The meeting is meant to discuss and coordinate the activities of the Section and its Chapters and Groups, as well as new initiatives. Everyone is welcome to attend this meeting. Please register in advance for this meeting using vTools (Please make a note if you join the meeting remotely) You can change/cancel the registration if your plans change. For more information, please contact our IEEE North Jersey Section Chair Hong Zhao ([email protected]) , or Secretary, Adriaan van Wijngaarden, ([email protected]). Location: FDU Metropolitan Campus, 1000 River Rd. Muscarelle Center 105, Teaneck, NJ 07666 To join remotely by the following Zoom link: https://fdu.zoom.us/j/94986383393 Meeting ID: 949 8638 3393 Note: If you are unable to join the meeting, please send your chapter activity report to the section chair at [email protected] Agenda: 06:30 pm - 06:45 pm Networking 06:45 pm - 08:30 pm IEEE North Jersey Section Executive Committee Meeting The meeting agenda typically includes news related to the IEEE and the IEEE North Jersey Section, Secretary and Treasurer reports, Chapter and Affinity Group reports, Committee reports, and reports by various Chairs and Representatives, Committee Chairs, and planning, and new initiatives. Bldg: Center for Environmental and Life Sciences, Room 120, Red Hawk Deck, 1 Normal Ave, Montclair, New Jersey, United States, 07043, Virtual: https://events.vtools.ieee.org/m/401019

The IEEE North Jersey Section's Executive Committee (EXCOM) monthly meeting will be held hybridly. The EXCOM meeting starts at 6:30 pm EST and typically ends at 8:30 pm. The meeting is meant to discuss and coordinate the activities of the Section and its Chapters and Groups, as well as new initiatives. Everyone is welcome to attend this meeting. Please register in advance for this meeting using vTools (Please make a note if you join the meeting remotely) You can change/cancel the registration if your plans change. For more information, please contact our IEEE North Jersey Section Chair Hong Zhao ([email protected]) , or Secretary, Adriaan van Wijngaarden, ([email protected]). Location: FDU Metropolitan Campus, 1000 River Rd. Muscarelle Center 105, Teaneck, NJ 07666 To join remotely by the following Zoom link: https://fdu.zoom.us/j/94986383393 Meeting ID: 949 8638 3393 Note: If you are unable to join the meeting, please send your chapter activity report to the section chair at [email protected] Agenda: 06:30 pm - 06:45 pm Networking 06:45 pm - 08:30 pm IEEE North Jersey Section Executive Committee Meeting The meeting agenda typically includes news related to the IEEE and the IEEE North Jersey Section, Secretary and Treasurer reports, Chapter and Affinity Group reports, Committee reports, and reports by various Chairs and Representatives, Committee Chairs, and planning, and new initiatives. Bldg: Center for Environmental and Life Sciences, Room 120, Red Hawk Deck, 1 Normal Ave, Montclair, New Jersey, United States, 07043, Virtual: https://events.vtools.ieee.org/m/401019

In this webinar, the speaker will discuss the following topics:- Why is HF radar enjoying renewed interest?- Principles of operating in the HF band- Examples of operation OTH radars- Challenges of operating OTH radarsCo-sponsored by: IEEE North Jersey SectionSpeaker(s): Tim Fountain Virtual: https://events.vtools.ieee.org/m/404077

In this webinar, the speaker will discuss the following topics: - Why is HF radar enjoying renewed interest? - Principles of operating in the HF band - Examples of operation OTH radars - Challenges of operating OTH radars Co-sponsored by: IEEE North Jersey Section Speaker(s): Tim Fountain Virtual: https://events.vtools.ieee.org/m/404077

- (https://r20.rs6.net/tn.jsp?f=001FPVMiMQRxnW9xFiYXAhx4oOw2TiagRolO-PCGRCyqJMYqb2FQn3H_pK0Ce-jiZ7AXlHtl_r--DuufoFv2d9wVAFdiZpUrK56WZ60Df96FYl6b9Uq9laeGBWwhsRO2N69W_DgerAH-irXn7GNSVsd3NfMPZ97ZcihHr76fp5g1-jbaAotyyV9RSYpOOW_TWLublkWbjuU006vF0qA73Kdgg==&c=L_63GiPXRSnQGiX9ujGPggJlcXUjkCoCWHGlck_OTs5RqF4eGPpGkg==&ch=YdNsxMiYze4EidBWNVzQxa6Wdu1nkD6-s8YfxwRqygI8XsPn3NAltA==) Co-sponsored by: IEEE North Jersey Section Speaker(s): Dr. Abbas Omar, Virtual: https://events.vtools.ieee.org/m/399904

- (https://r20.rs6.net/tn.jsp?f=001FPVMiMQRxnW9xFiYXAhx4oOw2TiagRolO-PCGRCyqJMYqb2FQn3H_pK0Ce-jiZ7AXlHtl_r--DuufoFv2d9wVAFdiZpUrK56WZ60Df96FYl6b9Uq9laeGBWwhsRO2N69W_DgerAH-irXn7GNSVsd3NfMPZ97ZcihHr76fp5g1-jbaAotyyV9RSYpOOW_TWLublkWbjuU006vF0qA73Kdgg==&c=L_63GiPXRSnQGiX9ujGPggJlcXUjkCoCWHGlck_OTs5RqF4eGPpGkg==&ch=YdNsxMiYze4EidBWNVzQxa6Wdu1nkD6-s8YfxwRqygI8XsPn3NAltA==)Co-sponsored by: IEEE North Jersey SectionSpeaker(s): Dr. Abbas Omar, Virtual: https://events.vtools.ieee.org/m/399904

As the industry moves towards the official release of 5G NR Advanced and eventually 6G, the prospect of measuring the phase noise of synthesizers, oscillators, and residual noise of amplifiers is becoming more challenging than ever. The spatial resolution required for devices operating above 50 GHz and into 100 GHz means that every degree matters more than ever. This webinar discusses these challenges in detail with a deep dive into phase noise and its advanced measurement techniques at high frequency. A solution will be presented to enable the testing for high GHz and sub-THz and beyond with only a few simple additions to most current phase noise setups. Co-sponsored by: IEEE North Jersey Section Speaker(s): Paul Peterson Virtual: https://events.vtools.ieee.org/m/404485

As the industry moves towards the official release of 5G NR Advanced and eventually 6G, the prospect of measuring the phase noise of synthesizers, oscillators, and residual noise of amplifiers is becoming more challenging than ever. The spatial resolution required for devices operating above 50 GHz and into 100 GHz means that every degree matters more than ever. This webinar discusses these challenges in detail with a deep dive into phase noise and its advanced measurement techniques at high frequency. A solution will be presented to enable the testing for high GHz and sub-THz and beyond with only a few simple additions to most current phase noise setups. Co-sponsored by: IEEE North Jersey Section Speaker(s): Paul Peterson Virtual: https://events.vtools.ieee.org/m/404485

Special Presentation on “A Comprehensive Overview of Optimization Techniques for RISs”by Dr. Hao Zhou (MgGill University, Canada)Hosted by Future Networks Artificial Intelligence & Machine Learning (AIML) Working GroupDate/Time: Thursday, February 15th, 2024 @ 12:00 UTCRegistration Link: https://bit.ly/FN-AIML-15Feb2024Topic:Optimization Techniques for RISsAbstract:Reconfigurable intelligent surfaces (RISs) have received considerable attention as a key enabler for envisioned 6G networks, for the purpose of improving the network capacity, coverage, efficiency, and security with low energy consumption and low hardware cost. However, integrating RISs into the existing infrastructure greatly increases the network management complexity, especially for controlling a significant number of RIS elements. To unleash the full potential of RISs, efficient optimization approaches are of great importance. This talk will provide a comprehensive overview of state-of-the-art optimization techniques for RIS-aided 6G, e.g., model-based, heuristic, and especially machine learning (ML) algorithms. It will present in-depth analyses of the features, advantages, and difficulties of using various optimization techniques. In addition, it will also present some novel techniques for RIS-optimization, e.g., combining heuristic algorithms with machine learning techniques to enable higher flexibility.Co-sponsored by: IEEE Future NetworksSpeaker(s): , Dr. Hao ZhouVirtual: https://events.vtools.ieee.org/m/403450

Special Presentation on “A Comprehensive Overview of Optimization Techniques for RISs” by Dr. Hao Zhou (MgGill University, Canada) Hosted by Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, February 15th, 2024 @ 12:00 UTC Registration Link: https://bit.ly/FN-AIML-15Feb2024 Topic: Optimization Techniques for RISs Abstract: Reconfigurable intelligent surfaces (RISs) have received considerable attention as a key enabler for envisioned 6G networks, for the purpose of improving the network capacity, coverage, efficiency, and security with low energy consumption and low hardware cost. However, integrating RISs into the existing infrastructure greatly increases the network management complexity, especially for controlling a significant number of RIS elements. To unleash the full potential of RISs, efficient optimization approaches are of great importance. This talk will provide a comprehensive overview of state-of-the-art optimization techniques for RIS-aided 6G, e.g., model-based, heuristic, and especially machine learning (ML) algorithms. It will present in-depth analyses of the features, advantages, and difficulties of using various optimization techniques. In addition, it will also present some novel techniques for RIS-optimization, e.g., combining heuristic algorithms with machine learning techniques to enable higher flexibility. Co-sponsored by: IEEE Future Networks Speaker(s): , Dr. Hao Zhou Virtual: https://events.vtools.ieee.org/m/403450

ACTIVATE THE PEACE WITHIN WITH GUIDED MEDITATIONLearn to meditate with Jo BojescuSpeaker(s): Jo, Agenda: 11:30- Meet and greet11:40- 12:30 meditation12:30-1:30 lunch and networkingNewark, New Jersey, United States

ACTIVATE THE PEACE WITHIN WITH GUIDED MEDITATION Learn to meditate with Jo Bojescu Speaker(s): Jo , Agenda: 11:30- Meet and greet 11:40- 12:30 meditation 12:30-1:00 lunch and networking Room: 202, Bldg: ECEC, Newark, New Jersey, United States

Mobile Edge Computing (MEC) is a technology framework that brings computational resources, including processing power, storage, and network connectivity, closer to mobile devices and users. In MEC, these resources are deployed at the edge of the cellular network, typically in close proximity to cell towers and base stations. This contrasts with traditional cloud computing, where data processing and storage occur in centralized data centers that can be distant from the end-user. Key aspects and features of MEC include Low Latency, Proximity, Resource Optimization, Scalability, Context Awareness and Security. Security measures are implemented at the edge to protect sensitive data and ensure the integrity of the network. This can include encryption, access control, and authentication mechanisms. Applications and use cases of MEC are diverse and include AR/VR, IoT, Content Delivery, Connected Vehicles, Smart Grids. MEC is also a critical component in the evolution of 5G networks. The webinar will provide a forum for researchers and engineers from academia and industry to develop a deep understanding of MEC Security. The participants would be exposed to wide and diverse topics in MEC Security, *This event is being recorded Co-sponsored by: IEEE Future Networks Speaker(s): Rajeev Shorey, Giridhar (Giri) D. Mandyam Virtual: https://events.vtools.ieee.org/m/403457

The following will be discussed in this lecture: - Spectrum utilization for XR: Understand the significance of the FR3 spectrum and THz frequencies in 5G-Advanced and 6G networks for XR applications - 3GPP standards and XR enhancements: Gain insights into how 3GPP Release 18 addresses XR requirements - Challenges in XR traffic management: Learn about the complexities of managing XR traffic and how various factors influence the design and functionality of XR services Co-sponsored by: IEEE North Jersey Section Speaker(s): Andreas Roessler Virtual: https://events.vtools.ieee.org/m/405367

AbstractNERC PRC-005-2 compliance drives utility operators to seek a reliable, validated, and advanced Battery Monitoring System (BMS) for their power plants and substations. This seminar is intended to present and discuss the available technologies and implementation challenges. Experiences with field installations and real-time data/charts will be shared in the meeting.Contents- Battery condition and maintenance basics- Battery monitoring technologies- IEEE standards for battery maintenance and monitoring- NERC PRC-005-2 standard- Communication and IT security- Data driven battery maintenance- Planning for implementation- Product and software demoSpeaker(s): Alan LongAgenda: The seminar fee includes lunch, refreshments and handouts. Non-members joining IEEE within 30 days of the seminar will be rebated 50% of the IEEE registration charge.Four hours of instruction will be provided. If desired, IEEE Continuing Education Units (0.4 CEUs) will be offered for this course - a small fee of $55 will be required for processing.Please pay attention to the “Registration Fee” and choose the appropriate choice either with or without CEUs.CEU Evaluation Form can be found at: (https://innovationatwork.ieee.org/ieee-pes-northjersey-certificates/)At this time, our attendance is being limited to fifty (50). Please only register if you know you are going to attend, and you must be registered to participate.Room: Aruba Room, Bldg: PSE&G - Hadley Road Facility, 4000 Hadley Road, South Plainfield, New Jersey, United States, 07080

Abstract NERC PRC-005-2 compliance drives utility operators to seek a reliable, validated, and advanced Battery Monitoring System (BMS) for their power plants and substations. This seminar is intended to present and discuss the available technologies and implementation challenges. Experiences with field installations and real-time data/charts will be shared in the meeting. Contents - Battery condition and maintenance basics - Battery monitoring technologies - IEEE standards for battery maintenance and monitoring - NERC PRC-005-2 standard - Communication and IT security - Data driven battery maintenance - Planning for implementation - Product and software demo Speaker(s): Alan Long Agenda: The seminar fee includes lunch, refreshments and handouts. Non-members joining IEEE within 30 days of the seminar will be rebated 50% of the IEEE registration charge. Four hours of instruction will be provided. If desired, IEEE Continuing Education Units (0.4 CEUs) will be offered for this course - a small fee of $55 will be required for processing. Please pay attention to the “Registration Fee” and choose the appropriate choice either with or without CEUs. CEU Evaluation Form can be found at: (https://innovationatwork.ieee.org/ieee-pes-northjersey-certificates/) At this time, our attendance is being limited to fifty (50). Please only register if you know you are going to attend, and you must be registered to participate. Room: Aruba Room, Bldg: PSE&G - Hadley Road Facility, 4000 Hadley Road, South Plainfield, New Jersey, United States, 07080

IEEE Communications Society Distinguished Lecture, sponsored by IEEE North Jersey ComSoc Chapter, Systems Council and NJIT (host). Smart assistive environments adapt to the needs and preferences of disabled or elderly users who need help with the activities of daily living. However, the needs and requests of users vary greatly, both due to personal preferences and type of disability. As handcrafting an environment is prohibitively expensive, in recent years significant research was done in systems that use machine learning to create a predictive model of the user. Machine learning, however, typically requires large amounts of data. A stand-alone smart environment, however, only has access to the data collected from its user since it was deployed. A possible solution is to perform centralized, cloud-based learning by pooling the training data collected from multiple users. However, uploading data collected from the personal habits of elderly and disabled users create significant security and privacy concerns. In this talk, we investigate the type of data sharing necessary for learning user models in smart environments and propose several novel considerations. We point out that data sharing is only ethical if the user derives a benefit from it. This implies that the decision to share data must be periodically revisited, it is not a commitment extending indefinitely in the future. We study the data sharing decisions made by users under several machine learning frameworks: local, cloud, and federated learning. We show that most users only benefit from data sharing for a limited interval after the deployment of the system. We also investigate machine learning techniques that predict whether the user will benefit from sharing the data before the data is shared. Co-sponsored by: Systems Counil North Jersey Speaker(s): , Damla Turgut Agenda: Seminar from 11 am to noon. On-campus ECE 202 and zoom. Room: 202, Bldg: ECEC, New Jersey Institute of Technology, Newark, New Jersey, United States, Virtual: https://events.vtools.ieee.org/m/405574

IEEE Communications Society Distinguished Lecture, sponsored by IEEE North Jersey ComSoc Chapter, Systems Council and NJIT (host).Smart assistive environments adapt to the needs and preferences of disabled or elderly users who need help with the activities of daily living. However, the needs and requests of users vary greatly, both due to personal preferences and type of disability. As handcrafting an environment is prohibitively expensive, in recent years significant research was done in systems that use machine learning to create a predictive model of the user. Machine learning, however, typically requires large amounts of data. A stand-alone smart environment, however, only has access to the data collected from its user since it was deployed. A possible solution is to perform centralized, cloud-based learning by pooling the training data collected from multiple users. However, uploading data collected from the personal habits of elderly and disabled users create significant security and privacy concerns.In this talk, we investigate the type of data sharing necessary for learning user models in smart environments and propose several novel considerations. We point out that data sharing is only ethical if the user derives a benefit from it. This implies that the decision to share data must be periodically revisited, it is not a commitment extending indefinitely in the future. We study the data sharing decisions made by users under several machine learning frameworks: local, cloud, and federated learning. We show that most users only benefit from data sharing for a limited interval after the deployment of the system. We also investigate machine learning techniques that predict whether the user will benefit from sharing the data before the data is shared.Co-sponsored by: Systems Counil North JerseySpeaker(s): , Damla TurgutAgenda: Seminar from 11 am to noon. On-campus ECE 202 and zoom.Room: 202, Bldg: ECEC, New Jersey Institute of Technology, Newark, New Jersey, United States, Virtual: https://events.vtools.ieee.org/m/405574

For nearly 50 years, chemical engineer and inventor Mária Telkes applied her prodigious intellect to harnessing the power of the sun. She designed and built the world’s first successfully solar-heated modern residence and identified a promising new chemical that, for the first time, could store solar heat like a battery. And yet, along the way, she was undercut and thwarted by her boss and colleagues — all men — at MIT. Despite these obstacles, Telkes persevered and, upon her death in 1995, held more than 20 patents. She is now recognized as a visionary pioneer in the field of sustainable energy. An unexpected and largely forgotten heroine, Telkes was remarkable in her vision and tenacity — a scientist and a woman in every way ahead of her time. Her research and innovations from the 1930s through the ‘70s continue to shape how we power our lives today AFTER the documentary - we can have a brief discussion session. NOTE: You must supply your own soda pop and popcorn! :-) Trivia may also follow, so bring your Jeopardy hats too! Agenda: 6:00 PM - Welcome and Introductions, Chapter business update; (on your own) Pizza, Popcorn and Soda Pop6:05 PM - Documentary7:05 PM - End of Documentary; Start of Q & A; Group Discussion7:15 PM - Wrap Up ALL times are in EST/EDT (UTC-4 or UTC-5) depending upon local day light savings times in when effect Virtual: https://events.vtools.ieee.org/m/401391