Semiconductor Research Corporation’s TECHCON 2016 is scheduled for September 12 – 13, 2016 at the Renaissance Austin Hotel in Austin Texas.
According to the email announcement, the general call for abstracts will open on Monday March 14, 2016.
TECHCON is largely student-presented and is an outstanding opportunity for networking with the world’s leading semiconductor industry companies and with researchers from other universities. Students will be invited to submit an abstract for consideration based on their association with SRC sponsored research. Abstracts are reviewed by technical committees that include member company representatives. Students with accepted abstracts are invited to present at TECHCON and have a unique opportunity to network with other researchers, students, and industry representatives. Because TECHCON 2016 is open only to the SRC community, authors are not precluded from publishing/presenting in open literature at a later date.
A separate call for students participating in Undergraduate programs will be made, opening on Monday April 18, 2016.
Please watch your email and the SRC website for more details for information about TECHCON 2016.
The TerraSwarm Research Center Blog covers news items about the TerraSwarm Research Center at http://www.terraswarm.org. The TerraSwarm Research Center, launched on January 15, 2013, is addressing the huge potential (and associated risks) of pervasive integration of smart, networked sensors and actuators into our connected world. The center is funded by the STARnet phase of the Focus Center Research Program (FCRP) administered by the Semiconductor Research Corporation (SRC).
Tuesday, January 19, 2016
Monday, November 30, 2015
TerraSwarm Funded Researcher Roozbeh Jafari's Group Developing Wearable Technology to Translate Sign Language into Text
Using a system of sensors to record and decode the muscle
activity associated with each sign, TerraSwarm funded researcher Roozbeh Jafari's group at Texas A&M
University is developing a wearable technology to translate sign language into
text. Possible applications include decreased communication barriers for those who use
sign language.
The current proof of concept device is able to send the resulting
translation from the device to a computer or smartphone using Bluetooth. The system is designed to learn from its user
to accommodate the individual movement of each person. Sophisticated algorithms
allow this process of adjustment and are also used to enable real time
translation. Going forward the team hopes to develop a smaller device that can
be worn as a watch, add a synthetic voice, and translate full sentences
rather then individual signs.
Tuesday, November 17, 2015
TerraSwarm funded
paper “Fast Redistribution of a Swarm of Heterogeneous Robots” Receives Best
Paper Award at the 9th EAI International Conference on Bio-inspired Information
and Communications Technologies
The paper, "Fast Redistribution of a Swarm of Heterogeneous Robots," received best paper award at the 9th EAI International Conference on Bio-inspired Information and Communications Technologies in New York.
The paper states: "The authors gratefully acknowledge the support of ONR grants N00014-15-1-2115 and N00014-14-1-05-10, ARL grand W911NF-08-2-0004, NSF grant IIS-1426840, and TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA."
Amanda Prorok, M. Ani Hsieh, Vijay Kumar. Fast Redistribution of a Swarm of Heterogeneous Robots. Proceedings of 9th EAI International Conference on Bio-inspired Information and Communications Technologies, December, 3- 5, 2015, New York.
Abstract:
We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level, as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution among the tasks is reached as quickly as possible. Our solution is based on an analytical gradient, and is computationally efficient, even for large choices of traits and species. Finally, we show that our method is capable of producing fast convergence times when compared to state-of-the-art methods.
The paper, "Fast Redistribution of a Swarm of Heterogeneous Robots," received best paper award at the 9th EAI International Conference on Bio-inspired Information and Communications Technologies in New York.
The paper states: "The authors gratefully acknowledge the support of ONR grants N00014-15-1-2115 and N00014-14-1-05-10, ARL grand W911NF-08-2-0004, NSF grant IIS-1426840, and TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA."
Amanda Prorok, M. Ani Hsieh, Vijay Kumar. Fast Redistribution of a Swarm of Heterogeneous Robots. Proceedings of 9th EAI International Conference on Bio-inspired Information and Communications Technologies, December, 3- 5, 2015, New York.
Abstract:
We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level, as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution among the tasks is reached as quickly as possible. Our solution is based on an analytical gradient, and is computationally efficient, even for large choices of traits and species. Finally, we show that our method is capable of producing fast convergence times when compared to state-of-the-art methods.
Wednesday, November 4, 2015
TerraSwarm Funded PI Vijay Kumar Receives $5.5 Million DARPA Grant
A three year, $5.5 Million dollar grant has been awarded to GRASP Laboratory at The University of Pennsylvania from the Defense Advanced Research Project Agency for the purpose of creating new robots that are capable of navigating unfamiliar environments independently and swiftly.
TerraSwarm funded PI Vijay Kumar and fellow researchers Daniel Lee, Camillo J. Taylor, Kostas Daniilidis and Jianbo Shi will use their various expertise to develop autonomous robots, capable of flying 20 meters per second, and weighing less than three kilograms. Possible applications include search and rescue and disaster response, particularly in situations that are hazardous for humans.
A three year, $5.5 Million dollar grant has been awarded to GRASP Laboratory at The University of Pennsylvania from the Defense Advanced Research Project Agency for the purpose of creating new robots that are capable of navigating unfamiliar environments independently and swiftly.
TerraSwarm funded PI Vijay Kumar and fellow researchers Daniel Lee, Camillo J. Taylor, Kostas Daniilidis and Jianbo Shi will use their various expertise to develop autonomous robots, capable of flying 20 meters per second, and weighing less than three kilograms. Possible applications include search and rescue and disaster response, particularly in situations that are hazardous for humans.
Friday, September 25, 2015
TerraSwarm funded paper "Robust Online Monitoring of Signal Temporal Logic" Receives Best Paper Award at Runtime Verification '15, Vienna
The paper, "Robust online Monitoring of Signal Temporal Logic," received best paper award at Runtime Verification '15 in Vienna.
The paper states: "This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA, by NSF Expeditions grant CCF-1139138, and by Toyota under the CHESS center at UC Berkeley."
Jyotirmoy V. Deshmukhh, Alexandre Donze, Shromona Ghosh, Xiaoqing Jin, Garvit Juniwal, Sanjit A. Seshia. Robust Online Monitoring of Signal TemporalLogic, Runtime Verification '15, Vienna, September 22, 2015.
Abstract:
Signal Temporal Logic(STL) is a formalism used to rigorously specify requirements of cyberphysical systems (CPS), i.e., systems mixing digital or discrete components in interaction with a continuous environment or analog components. STL is naturally equipped with a quantitative semantics which can be used for various purposes: from assessing the robustness of a specification to guiding searches over the input and parameter space with the goal of falsifying the given property over system behaviors. Algorithms have been proposed and implemented for offline computation of such quantitative semantics, but only few methods exist for an online setting, where one would want to monitor the satisfaction of a formula during simulation. In this paper, we formalize a semantics for robust online monitoring of partial traces, i.e., traces for which there might not be enough data to decide the Boolean satisfaction (and to compute its quantitative counterpart). We propose an efficient algorithm to compute it and demonstrate its usage on two large scale real-world case studies coming from the automotive domain and from CPS education in a Massively Open Online Course (MOOC) setting. We show that savings in computationally expensive simulations far out- weigh any overheads incurred by an online approach.
Thursday, September 24, 2015
TerraSwarm researcher Alex Halderman is one of PopSci's Brilliant 10
University of Michigan Professor and TerraSwarm-funded researcher J. Alex Halderman has been named one of PopSci's Brilliant 10. The article "Brilliant 10: Alex Halderman Strengthens Democracy Using Software," discusses Halderman's 2010 efforts surrounding a mock Washington D.C. election where researchers were invited to break into the electronic voting system. Halderman and his group were able to take complete control of the system, which they directed to play the Michigan fight song each time a vote was cast.
The article also covers TapDance, software that allows citizens of countries with restricted firewalls to bypass government censors. TapDance is described in the following paper
* Eric Wustrow, Colleen Swanson, Alex Halderman. TapDance: End-to-Middle Anticensorship without Flow Blocking, Usenix Security 2014, 20, August, 2014.
Abstract: In response to increasingly sophisticated state-sponsored Internet censorship, recent research has proposed a new approach to censorship resistance: end-to-middle proxying. This concept, developed in systems such as Telex, Decoy Routing, and Cirripede, moves anticensorship technology into the core of the network, at large ISPs outside the censoring country. In this paper, we focus on two technical barriers to the deployment of end-to-middle proxy designs-- the need to selectively block flows, and the need to observe both directions of a connection-- and we propose a new construction, TapDance, that avoids these shortcomings. To accomplish this, we employ a novel TCP-level technique that allows the anticensorship station at an ISP to function as a passive network tap, without an inline blocking component. We also apply a novel steganographic encoding to embed control messages in TLS ciphertext, allowing us to operate on HTTPS connections even with asymmetric flows. We implement and evaluate a proof-of-concept prototype of TapDance with the goal of functioning with minimal impact on normal ISP operations.
This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation pro- gram sponsored by MARCO and DARPA.
Note that in 2014, University of Michigan Professor and TerraSwarm-funded research Prabal Dutta was named one of the Brilliant 10. See "The Brilliant Ten: Prabal Dutta Powers The Internet of Things."
The article also covers TapDance, software that allows citizens of countries with restricted firewalls to bypass government censors. TapDance is described in the following paper
* Eric Wustrow, Colleen Swanson, Alex Halderman. TapDance: End-to-Middle Anticensorship without Flow Blocking, Usenix Security 2014, 20, August, 2014.
Abstract: In response to increasingly sophisticated state-sponsored Internet censorship, recent research has proposed a new approach to censorship resistance: end-to-middle proxying. This concept, developed in systems such as Telex, Decoy Routing, and Cirripede, moves anticensorship technology into the core of the network, at large ISPs outside the censoring country. In this paper, we focus on two technical barriers to the deployment of end-to-middle proxy designs-- the need to selectively block flows, and the need to observe both directions of a connection-- and we propose a new construction, TapDance, that avoids these shortcomings. To accomplish this, we employ a novel TCP-level technique that allows the anticensorship station at an ISP to function as a passive network tap, without an inline blocking component. We also apply a novel steganographic encoding to embed control messages in TLS ciphertext, allowing us to operate on HTTPS connections even with asymmetric flows. We implement and evaluate a proof-of-concept prototype of TapDance with the goal of functioning with minimal impact on normal ISP operations.
This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation pro- gram sponsored by MARCO and DARPA.
Note that in 2014, University of Michigan Professor and TerraSwarm-funded research Prabal Dutta was named one of the Brilliant 10. See "The Brilliant Ten: Prabal Dutta Powers The Internet of Things."
Madhur Behl wins the Best-in-Session award (IoT Systems session) at the 2015 SRC TECHCON
Madhur Behl (final year PhD at UPenn) won the Best-in-Session award for the IoT Systems session at the 2015 SRC TECHCON on September 22, 2015. This is for his TerraSwarm work on Data-driven Demand Response Recommender System (DR-Advisor), titled "Sometimes, Money Does Grow on Trees".
Last year, Zhihao Jiang (also final year PhD at UPenn) won the Best-in-Session award for his TerraSwarm work on Formal Verification of Closed-loop Medical Devices.
Subscribe to:
Posts (Atom)