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The Outstanding Chapter Awards 2016-17

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The IEEE-Eta Kappa Nu (IEEE-HKN) Board of Governors has conferred on the following IEEE-HKN Chapters the 2016-2017 IEEE-HKN Outstanding Chapter Award:


Chapter Name University
Alpha Chapter University of Illinois at Urbana Champaign
Beta Alpha Chapter Drexel University
Beta Chapter Purdue University
Beta Epsilon Chapter University of Michigan
Beta Kappa Chapter Kansas State University
Beta Lambda Chapter Virginia Polytechnic Institute and State University
Beta Omega Chapter University of Connecticut
Beta Theta Chapter Massachusetts Institute of Technology
Delta Epsilon Chapter Ohio University
Delta Omega Chapter University of Hawaii at Manoa
Gamma Delta Chapter Worcester Polytechnic Institute
Gamma Tau Chapter North Dakota State University
Gamma Theta Chapter Missouri University of Science and Technology
Iota Chi Chapter Oakland University
Iota Gamma Chapter University of California, Los Angeles
Iota Zeta Chapter California State University, Chico
Kappa Psi Chapter University of California, San Diego
Lambda Sigma Chapter University of California, Riverside
Mu Alpha Chapter UCSI University
Mu Chapter University of California, Berkeley
Mu Iota Chapter Seattle University
Mu Nu Chapter Politecnico di Torino
Nu Chapter Iowa State University
Zeta Beta Chapter Texas A&M University – Kingsville

This award is presented to IEEE-HKN Chapters in recognition of excellence in their Chapter administration and programs. Service to the community and others is an expectation of IEEE-HKN Chapters.

Recipients are selected on the basis of their annual Chapter report. Winning Chapter reports showcase their Chapter’s activities in an individualized manner and provide multiple views and instances of their work, which really brings their Chapter’s activities to life. Of critical concern to the Outstanding Chapter Awards evaluation committee in judging a Chapter are activities to: improve professional development; raise instructional and institutional standards; encourage scholarship and creativity; provide a public service; and generally further the established goals of IEEE-HKN.

The awards will be presented at a special reception held on19 March 2018, in conjunction with the Annual Electrical and Computer Engineering Department Heads Association (ECEDHA) meeting; in Monterrey, California.  At the Awards Dinner immediately following the reception, the 2017 Alton B. Zerby and Carl T. Koerner Outstanding Student Award will be presented to Katelyn Brinker of the IEEE-HKN Gamma Theta Chapter at Missouri University of Science & Technology, and James Smith of the IEEE-HKN Xi Chapter at Auburn University.


 About IEEE-Eta Kappa Nu

Founded as Eta Kappa Nu in 1904 at the University of Illinois, Urbana-Champaign, then changed to IEEE-Eta Kappa Nu (IEEE-HKN) following a merger with IEEE in 2010, IEEE-HKN is the academic honor society for those studying the IEEE fields of interest, including electrical and computer engineering.

IEEE-HKN annually inducts over 3,000 students, faculty and professionals and has more than 200,000 alumni. The Society has chapters at more than 230 colleges and universities in the United States and around the world. Membership for students is by invitation only to those that possess outstanding academic achievement, character and attitude.

IEEE-HKN’s mission is to be the catalyst for the development of the “Complete Technical Professional.” Notable members include co-founder of Apple Inc. Steve Wozniak, “Father of the Internet” Vint Cerf, co-founder of Google Larry Page, and co-founder and Chairman Emeritus of Intel Corporation Gordon Moore.

For more information about IEEE-HKN, please visit www.hkn.org or call 732-465-6611.

About IEEE
IEEE is the world’s largest professional organization dedicated to advancing technology for the benefit of humanity. Through its highly cited publications, conferences, technology standards, and professional and educational activities, IEEE is the trusted voice on a wide variety of areas ranging from aerospace systems, computers and telecommunications to biomedical engineering, electric power and consumer electronics.

Learn more at http://www.ieee.org.

The Smart City Edge

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By Paula Reinman
Co-authored by Dr. Aakanksha Chowdhery


Smart cities are all the rage.  From Alphabet’s Sidewalk Labs turning Toronto’s eastern waterside into a smart neighborhood pilot to Barcelona’s superblock by superblock plan, cities around the world are integrating technology, data, analytics and citizen input to become cleaner, safer and easier places to live.

Safety and security is a critical concern for smart cities, requiring cameras deployed throughout the city for applications including surveillance, traffic statistics and post-event analysis for disasters like the Boston Marathon bombing.  Today, most of this collected video data is stored close to the camera.  The video is difficult to search, causing problems particularly when timely remote access would provide valuable real-time insights, because transferring camera video data to a cloud data center is particularly bandwidth intensive. While much of the attention in the networking space is on the cloud, it turns out that smart city security can only work at scale by innovating at the edge of the network.

Many of these important developments are happening in the labs at Princeton University led by 2012 Young Scholar, Dr. Aakanksha Chowdhery.


The Video Tsunami

“Cameras are ubiquitous,” Chowdhery says.  “We have surveillance cameras in buildings, traffic monitoring cameras on roads and at lights and drone cameras streaming live events, doing surveillance and helping with disaster response.”

There were over 62M building surveillance cameras in the US in 2016 and traffic surveillance cameras in over 400 metro areas, creating petabytes of content each year.

This tsunami of video and images contains information to help find perpetrators, to enforce traffic rules and to locate people who need help but finding exactly the right frames and shots to turn this huge collection of data into information is a technical challenge.  In one surveillance sample, only 20% of a 250-hour video feed had any faces at all.  Sending the full video to the cloud for analysis wastes bandwidth and power while compromising security of the video stream.

A better answer is to identify just the right information at the edge of the network and to send only those images over the cloud.  Fog computing, or edge computing, is an architecture proposed to solve this problem.  A fog node is part of a decentralized computing architecture that essentially extends cloud computing capabilities to the network’s edge by bringing analytics, computing, storage and applications to the most efficient place between the data and the cloud.

In this case, a fog node is comprised of something like a raspberry pi (a $25 computer with basic functionality) or Nvidia Jetson TK1 (a basic computer with a GPU) that serves a camera or a group of cameras in order to identify the right images for the problem and send them to the cloud.

Scaling Smart Cities in the Fog

Processing and analyzing video at the network edge, or in the fog, optimizes bandwidth and power usage, reduces latency and enhances privacy – all at the scale needed for smart cities.

Reducing Bandwidth

Suppose police are looking for a 6’1” tall blonde male suspect who is at large in the city or for a red BMW with license plate number “731RTZ.”  Police can put out a query, or classifier, for the description across the network and each node will do local analysis of video as it comes in, looking for images matching the description.  Fog nodes then filter for specific frames potentially including the suspect or vehicle.  This greatly reduces the bandwidth needed to transmit relevant video.












Reducing Bandwidth Consumption by Sending Only the Relevant Video Frames








Saving Power

Fog nodes enable smart city networks to send only filtered video frames (shown above), saving bandwidth.  However, moving the processing burden to the edge of the network uses power at the fog node.  By running the query, or activating the local classifier adaptively, the system itself can optimize between bandwidth savings and power consumption at the fog node.

Reducing Latency

Many applications, especially surveillance and disaster response, need real-time inputs from a human operator in situations where the latency on the video data link is critical to the mission’s success. Managing wireless link latency is challenging when the cameras collecting the video are mounted on a drone or a moving vehicle. In such scenarios, fog nodes at the drone adapt video bitrates or compresses video content based on the rapid wireless channel fluctuations as the drone moves by predicting future throughputs using spatial throughput maps and location information. This ensures that the relevant video frames are delivered within required latency budget.

Ensuring Privacy

When police collect video today from body cameras, they need to blur, or obfuscate, the faces of the people in the video before showing it to anyone.  Fog nodes allow law enforcement to obfuscate faces at the edge of the network.  This prevents potentially sensitive video from traveling over the cloud, where it is difficult to secure the video and images.  When specific faces are needed, they can be retrieved from the images at the fog node.

Safe and robust smart cities will rely on technology that moves computing closer to where the data connects to the cloud, removing many of the cloud security issues from the equation.  Securing at scale is a critical issue across the Internet of Things landscape.  The volume of video we are creating, combined with the bandwidth and network requirements needed to make that video useable, means the action will be at the edge for safety and security applications.


This post originally appeared in the blog for The Marconi Society, a foundation supporting scientific achievements in communications and the Internet that significantly benefit mankind.

Scholarship, Character, and Attitude

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“My name is Oliver Queen. For five years, I was stranded on an island with only one goal; survive.”

Just kidding, my name is Rafi Koutoby, the IEEE-Eta Kappa Nu resident blogger. I apologize for raising your hopes that I really was the [Green] Arrow, especially after the abomination that was Season 4. Anyway, I’m currently an electrical engineering grad student at California State University, Long Beach and I used to be the President of the chapter there, Epsilon Theta.

From time to time, there will be guest-star bloggers; namely, professional engineers who will provide some insight on their careers as well as some valuable advice on how to progress in yours. For my pilot blog, I’d like to talk about the significance of the IEEE-HKN ideals for success, which can be summarized in this motto; Scholarship, Character, and Attitude in Electrical and Computer Engineering.

First up of the three, scholarship. It’s no secret that honor societies (IEEE-HKN included) have a scholastic requirement for student candidates. Furthermore, companies interviewing internship/full-time position candidates place a lot of emphasis on technical knowledge and skills. However, grades are not the perfect test of a person, as grades may not accurately predict a person’s response to new, unfamiliar situations or their ideas and approaches to new problems. Nevertheless, with that being said, IEEE-HKN encourages you to improve your thinking methodologies and your resourcefulness, and by extension, your scholastic record. Electrical Engineer Michael McClay of Raytheon amplifies this by saying, “Do well in your engineering classes – get As and Bs.”

This brings me to the second ideal of the holy trinity, character. The Director of University Programs for IEEE, Burton Dicht, says, “Your technical skills get you your first job, but your communication skills get you your second job.” In other words, your skills in verbal and written communication play a huge factor in your role at the workplace. Without proper communication skills, projects may lag behind, misunderstandings can escalate into arguments, and the productivity of an organization falls. Therefore, it is up to you as an individual to cultivate your character, including honesty, sound judgment, capacity for hard work, and communication skills.

And last but not least, attitude. The first two qualities are meaningless without a positive attitude, as explained by Civil Engineering Associate at the Port of Los Angeles, Edwin Contreras, “Employers are more willing to take on a candidate who demonstrates humility and an optimistic attitude towards learning.” Whether as a contributor or leader, the people you interact with see the way you reflect on your education, your profession, and ultimately, your life. Your adaptability for working in harmony with others shows why a positive attitude is the third pillar for success in the eyes of IEEE-HKN. Well, that sums up #MyVeryFirstBlog. For the most part, I hope to have entertained you with the side effect of being quite informative. I can’t strengthen my work without your feedback, so critiquing me would go a long way.

Till next time!

Written by Rafi A. Koutoby

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