Martin, Fred: September 2011 Archives

Profs. Fred Martin (Computer Science) and Michelle Scribner-MacLean (Graduate School of Education) were guests at the Fifth Annual River Day, hosted by Congresswomen Niki Tsongas on September 15, 2011.

Martin and Scribner-MacLean joined Rep. Tsongas on the banks of the Concord River to describe their new four-year, $1.3M NSF award to create an internet-based platform, dubbed iSENSE, which will engage students in data-intensive science inquiry. Working with a number of school systems in the Merrimack Valley, Martin and Scribner-MacLean will support teachers in integrating the internet-based technology into their science instruction. Machine Science Inc., of Cambridge, MA, is a grant partner, and will involve schools in the Boston area in project work.

The grant also includes a partnership with the Tsongas Industrial History Center and the National Park Service. Martin and Scribner-MacLean will work with staff at these two institutions to develop a new version of their River As A Classroom field trip, which brings middle- and high-school students onto the Merrimack River to study water quality. Students and teachers who participate in the new river-based field trip will use the project’s “iSENSE” technology to record, visualize, and discuss river water quality measurements.

At the River Day event, Martin and Scribner-MacLean had the opportunity to present their work to the Lock Masters, a Lowell-based volunteer group who operates the centuries-old canal locks system in the city, and high school students from the Spindle City Corp, who volunteer their service for beautification projects in the city.

martin-tsongas-scribner-maclean.jpg
(L-R) Prof. Fred Martin, U.S. Congresswoman Niki Tsongas, and Prof. Michelle Scribner-MacLean on the banks of the Concord River behind the UMass Lowell Inn and Conference Center. For more information about Martin and Scribner-MacLean’s new science education award, see this story.

Computer Science Ph.D. students Zhongli Liu and Yinjie Chen won the silver medal at the ACM Student Research Competition (SRC) at ACM MobiCom 2011 with their work titled HAWK: An Unmanned Mini Helicopter-based Aerial Wireless Kit for Search, Rescue and Surveillance. Zhongli also won the ACM’s SRC Travel Award of $500. MobiCom is a top academic conference on wireless networks.

HAWK is a small programmable unmanned helicopter (Draganflyer X6) equipped with a wireless sniffer (a Nokia n900 smartphone). It is the first mini autonomous Unmanned Aerial Vehicle (UAV) as an aerial wireless kit for search, rescue and surveillance, based on a mini helicopter, instead of a mini airplane. As a “warflying” tool, HAWK is more flexible than warwalking and wardriving tools in many situations.

HAWK was developed as a generic aerial surveillance tool. The project’s central contributions can be summarized as follows:

  1. The fully-functional HAWK helicopter flies using a simple mechanical dynamics model for Draganflyer X6, with customized PI-Control laws for pitch, roll and yaw maneuvers to control its movement. Waypoint functionality allows the X6 to take a planned route.
  2. A space-filling curve based flight route is used to survey a specific area without the help of any positioning infrastructure. To ensure that all target mobile devices are detected during flight, the minimum Moore curve level that is constrained by flight velocity and target packet transmission interval is derived and used.
  3. Real-world experiments to validate the feasibility of HAWK for localization were conducted. The experimental results match the theoretical analysis very well, and the team was able to achieve a localization accuracy of 5 meters on average.
At the conference, Zhongli Liu and Yinjie Chen first competed in a poster session, which is open to more than 300 conference participants on September 20, 2011 in Las Vegas. Then the ACM SRC committee selected three finalists to compete in a presentation session, in which Zhongli presented HAWK on the same day. At the MobiCom 2011 banquet on September 21, 2011, the winners were then announced.

UMassLowellTeamACMStudentResearchAward_092111.jpg
(L-R) Prof. Benyuan Liu, CS Ph.D. students Xian Pan, Zhongli Liu, Yinjie Chen and Junwei Huang, and Prof. Xinwen Fu. Zhongli and Yinjie are holding their silver medal. Xian and Junwei helped them prepare the talk at the conference and manage the equipment shipped for demo. The adviser of these four students is Dr. Xinwen Fu. On far left: Prof. Benyuan Liu, a collaborator on the the project.

Prof. Jesse Heines is the leader of a multi-departmental UMass Lowell team that has been awarded $450K from the National Science Foundation for their project, Computational Thinking through Computing and Music. Profs. Gena Greher and Alex Ruthmann (both of UMass Lowell’s Music Department) are co-PIs on the award.

In “Performamatics,” an earlier NSF project led by Heines, a number of partnerships between computing and the arts were created.  As part of this work, Heines, Greher, and Ruthmann developed an interdisciplinary undergraduate course, Sound Thinking, which has been offered at UMass Lowell for each of the last three years.

Building on this work, the new award focuses on ways to engage both computing, music, and students of other disciplines in “computational thinking,” an emerging idea in computer science education.

In the new project, the faculty team will leverage the natural relationship between music and computing to teach computational thinking concepts across the undergraduate curriculum, including both introductory general education courses, and discipline-specific music and computing courses at more advanced levels.

The team will also lead workshops to share their approaches with undergraduate faculty across the United States.

For more, please see UMass Lowell's eNews article, New Curriculum Combines Computing and Music, and the project web site, performamatics.org.

Heines_160x200.jpg Gena_Greher_opt_200.jpg Ruthmann-opt200.jpg
(L-R) Profs. Jesse Heines (Computer Science), Gena Greher (Music), and Alex Ruthmann (Music).
Prof. Xinwen Fu was awarded a grant entitled “Membership Inference in a Differentially Private World and Beyond” from NSF’s Trustworthy Computing program. The award is a great boost to the Department's security program, and will strengthen its national status in related fields.

The award funds a three-year research agenda among three universities—George Washington University, Towson University, and the University of Massachusetts Lowell. The overall award totals $495K and UMass Lowell’s share is $166K.

The objective of the research project is to systematically understand, evaluate and contribute to the problem of membership inference in aggregate data publishing, which is a generic, novel, and dangerous privacy threat in a wide variety of real-world applications.

The central idea to be developed for addressing the problem of membership inference is an information-theoretic model of privacy disclosure as a noisy communication channel. Based on the channel coding theory and the recent advance in multi-input multi-output (MIMO) communication channels, the research will study novel techniques for membership inference and explores the corresponding privacy-preserving mechanisms.

The outcome of this research has broader impacts on the nation’s higher education system and high-tech industries. The prospect of sensitive membership information disclosure techniques and privacy-preserving techniques can help the providers of aggregated data publishing, including national health organizations, Internet security service providers, and others to secure their published data.

Prof. Fu is a member of the Computer Science department’s Center for Network and Information Security (CNIS). His research focuses on network security and privacy, network and computer forensics, and distributed systems.

XinwenFu.jpg
Prof. Xinwen Fu

About this Archive

This page is a archive of recent entries written by Martin, Fred in September 2011.

Martin, Fred: August 2011 is the previous archive.

Martin, Fred: October 2011 is the next archive.

Find recent content on the main index or look in the archives to find all content.

Subscribe to feed Subscribe to this blog's feed