Region 1

September 21 through November 2, 2024. Six Saturdays 1:30-4:30pm (9/21, 9/28, 10/5, 10/19, 10/26, 11/2). The IEEE North Jersey Section Communications Society Chapter is offering a course entitled "DEEP LEARNING WITH APPLICATIONS". Deep learning is a transformative field within artificial intelligence and machine learning that has revolutionized our ability to solve complex problems in various domains, including computer vision, natural language processing, and reinforcement learning. This hands-on course on deep learning is designed to provide students with an understanding how these amazing successes are made possible by drawing inspiration from the way that brains, both human and otherwise, operate. Students will gain a comprehensive foundation in the principles, techniques, and applications of deep neural networks. Learning how to solve real data-set based applications will teach students how to really apply deep learning with Python programming software. Participants will be asked to design and train deep neural networks to perform tasks such as image classification using commonly available data sets. However, participants are encouraged to apply the techniques from this course to other data sets according to their interests. Discuss with the instructor in order to propose your own project. More importantly, this will set the foundations for understanding and developing Generative AI applications. The IEEE North Jersey Section's Communications Society Chapter can arrange for providing IEEE CEUs - Continuing Education Units (for a $5 charge) upon completion of the course. Course prices: $75 for Undergrad/Grad/Life/ComSoc members, $100 for IEEE members, $150 for non-IEEE members Co-sponsored by: Education Committee Speaker(s): Thomas Long, Agenda: 1. Introduction to Neural Networks: Explore the fundamental concepts of artificial neural networks, backpropagation, activation functions, and gradient descent, laying the groundwork for deep learning understanding. 2. Introduction to PyTorch: Learn how to implement and train neural networks using PyTorch one of the most popular deep learning frameworks. Understand tensors. 3. Computer Vision Applications: Apply deep learning to computer vision problems, including image classification and object detection using Convolutional Neural Networks (CNNs) 4. Training and Optimizing Deep Neural Networks: Study techniques for training deep neural networks effectively, including optimization algorithms, weight initialization, regularization, and dropout. 5. Sequential Data Analysis: Explore how deep learning is used to analyze sequential data using Recurrent Neural Networks (RNNs). In particular, explore how neural networks are used in Natural Language Processing (NLP) tasks such as sentiment analysis and machine translation. 6. Generative AI: Overview of generative ai techniques that leverage the patterns present in a dataset to generate new content. Applications of generative ai include large language models such as ChatGPT and image generation models such as Midjourney and Stable Diffusion. This course assumes a basic understanding of machine learning concepts and programming skills in Python. Familiarity with linear algebra and calculus will be beneficial, but not mandatory. Statistical software (Python, Scikit-learn) and Deep Learning Frameworks (Pytorch, TensorFlow) will be used throughout the course for the exploration of different learning algorithms and for the creation of appropriate graphics for analysis. Learning objectives: Subjects covered include these and other deep learning related materials: artificial neural networks, training deep neural networks, RNN, CNN, image recognition, natural language processing, GANs, data processing techniques, and NN architectures. The course is intended to be subdivided into 3-hour sessions. Each lecture is further subdivided into lecture, guided and independent project based exercises to build experience with hands-on techniques. This course will be held at FDU - Teaneck, NJ campus. Checks should NOT be mailed to this address. Can bring checks in person or use online payments at registration. Email the organizer for any questions about course, registration, or other issues. Technical Requirements: Students will need access to the Python programming language. In addition to a standard Python installation, most programming exercises will use the package Scikit-learn. Basic programming skills and some familiarity with the Python language are assummed. Students are expected to be able to bring a laptop onto which most of these libraries can be pre-installed using python's pip install. Most of the coding in this course will use the Python programming language. Coding examples and labs will be distributed in the form of Juypter notebooks. In addition to standard Python, most programming exercises will use either the PyTorch or TensorFlow libraries. Books and other resources will be referenced. Room: Room 306, Bldg: Becton Building , FDU Metropolitan Campus, 960 River Road, Teaneck, New Jersey, United States, 07666

Key areas of discussion: • Current changes to SF6 legislation and practices o NY SF6 phase out: dates and voltage classes o MA SF6 phase out: dates and voltage classes o EPA changes to reporting o Is SF6 Dead? • SF6 Alternatives and changing infrastructure demands on utilities o C4-FN  Pros and Cons of the gases  Mixing, handling & recovery  Gas analysis  Leakage and Safety o Natural Origin Gases  Pros and Cons of the gases  handling & recovery  Gas analysis  Leakage & Safety o Logistics and Infrastructure  Challenges with cylinder handling & management  Fittings [] Speaker(s): Devin 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: Auditorium, Bldg: PSE&G - Hadley Road Facility, 4000 Hadley Road, South Plainfield, New Jersey, United States, 07080

(https://ieeeboston.org/event/pythonapplications/?instance_id=3232) Course Kick-off / Orientation 6:00PM - 6:30PM EDT; Thursday, August 29, 2024 Live Workshops: 6:00PM – 7:30PM EDT; Thursdays, September 5, 12, 19, 26 Registration is open through the last live workshop date. Live workshops are recorded for later use. Registration Fees: IEEE Member Early Rate (August 28): $190.00 IEEE Member Rate (after August 28): $285.00 IEEE Non-Member Early Rate (by August 28): $210.00 IEEE Non-Member Rate (after August 28): $315.00 Decision to run/cancel course: Thursday, August 22, 2024 Course information will be distributed by Wednesday August 28, and then a brief live Orientation meeting will be held on Thursday August 29 ahead of the weekly live workshops that follow. Attendees will have access to the recorded session and exercises for two months (until November 26, 2024) after the last live session ends! This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language. Pre-Recorded Videos: The course format has been updated to release pre-recorded video lectures that students can watch on their own schedule, and an unlimited number of times, prior to live Q&A workshop sessions on Zoom with the instructor. The videos will also be available to the students for viewing for up to two months after the conclusion of the course. Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, providing a best-practices approach for quickly getting up to speed using Python for modelling and analysis for applications in signal processing and digital design verification. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and Jupyter Notebooks for a rich, interactive experience. The course begins with basic Python data structures and constructs, including key “Pythonic” concepts, followed by an overview and use of popular packages for scientific computing enabling rapid prototyping for system design. During the course students will create example designs including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will include considerations for cycle and bit accurate models useful for digital design verification (FPGA/ASIC), while bringing forward the signal processing tools for frequency and time domain analysis. Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python code with interactive plots and graphics for a rich user experience. Jupyter Notebooks is an open-source web-based application (that can be run locally) that allows users to create and share visually appealing documents containing code, graphics, visualizations and interactive plots. Students will be able to interact with the notebook contents and use “take-it-with-you” results for future applications in signal processing. Target Audience: This course is targeted toward users with little to no prior experience in Python, however familiarity with other modern programming languages and an exposure to object-oriented constructs is very helpful. Students should be comfortable with basic signal processing concepts in the frequency and time domain. Familiarity with Matlab or Octave is not required, but the equivalent operations in Python using the NumPy package will be provided for those students that do currently use Matlab and/or Octave for signal processing applications. Benefits of Attending / Goals of Course: Attendees will gain an overall appreciation of using Python and quickly get up to speed in best practice use of Python. All set-up information for the installation of all tools will be provided before the start of class. Speaker(s): Dan Boschen , Agenda: Topics / Schedule: Pre-recorded lectures (3 hours each) will be distributed Friday prior to all Workshop dates. Workshop/ Q&A Sessions are 6pm-7:30pm on the dates listed below: Kick-off / Orientation: Thursday, August 29, 2024 Thursday, September 5, 2024 Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples. Core Python constructs. Thursday, September 12, 2024 Topic 2: Core Python constructs; iterators, functions, reading writing data files. Thursday, September 19, 2024 Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib. Thursday, September 26, 2024 Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages Virtual: https://events.vtools.ieee.org/m/422879

Photonic integration has been at the center of photonic activity for several years. Over this period, great strides have been made to increase the integration density and integrated chip functionality. This talk will work its way up from the drivers for photonic integration – why do we need Photonic Integrated Circuits (PICs)? What are their similarities and differences with Electronic Integrated Circuits (EICs)? This analysis of integration drivers will lead to a discussion of recent progress on the main paths: monolithic, heterogeneous and hybrid. The talk will conclude with possible approaches to meet the additional demanding considerations for future Quantum PICs. Speaker(s): Daniel Agenda: This will be a hybrid talk held at Holmdel Community Center, 6 Crawfords Corner Road, Holmdel, NJ. Ample parking is available in the back of the building too. For online attendance Webex link is provided. Please register for the talk. There is no fee for this talk. Please indicate if you are able to attend in person. This will help with reserving space for dinner at the restaurant. 6:30 PM: Speaker Introduction 6:45 - 7:45 PM: Distinguished lecture 7:45 - 8 PM: Discussion 8:15 PM: Dinner with speaker Bldg: Holmdel Community Center (townhall), 6 Crawfords Corner Road, Holmdel, New Jersey, United States, 07733, Virtual: https://events.vtools.ieee.org/m/433216

R1/R2 Excom members to complete awareness/assessment/and get a commitment from area chairs to do likewise with section chairs. From Bala's email on September 3, 2024 Good Morning R1 ExCom, Section Chairs & Members of BOG. Hope you all had a great summer! IEEE places great emphasis on the Code of Ethics and Code of Conduct of its volunteers and staff. Awareness, adherence and compliance to this is extremely important . The Code of Ethics & Code of Conduct were updated in 2020 and they are available at: (These are short, no more than one page documents. (3 documents that are repetitive in substance)) https://www.ieee.org/about/corporate/governance/p7-8.html https://www.ieee.org/content/dam/ieee-org/ieee/web/org/about/ieee_code_of_conduct.pdf https://www.ieee.org/content/dam/ieee-org/ieee/web/org/about/corporate/ieee-code-of-ethics.pdf Our Region 1 Membership Development Chair Oscar Tonello is leading an effort to get Region 1 leaders, officers and volunteers become aware of IEEE Code of Ethics through a study and assessment program. https://ieee.surveysparrow.com/s/Ethics-Super-Power-Challenge-Region-1--2/tt-uq7ASzQyqLxsk5ckbAftS6 Here is the ask from Oscar: R1 ExCom, Section Chairs & BoG will review of Code of Ethics/Code of Conduct and complete the assessment. (The assessment involves 10 questions you need to answer and should get at least 70% right.) Section Chairs are asked to have their section officers and chapter officers complete the review and assessment in the second round. Oscar will work with you to reach non-volunteer IEEE members in the third round. There will be recognition of those who complete the assessment by Sept 28, 2024 with a beautiful, collector grade R1/R2 Ethics pin. Other recognitions will be shared by Oscar in his communications with you. The Code of Ethics and Code of Conduct Awareness & Assessment was initially started by R10 and we are taking their generous help to get R1 members complete their review and assessment. Virtual: https://events.vtools.ieee.org/m/435508