Member in the spotlight: Jorge Arroyo Palacios
1 March 2015
In this series, we introduce a scientist, who uses signal processing techniques for his research findings, by means of an interview. This month, we…
Read moreGopalan, Prem K (Princeton University) “Scalable inference of discrete data: User behavior, networks and genetic variation” (2015)
1 March 2015
Gopalan, Prem K (Princeton University) “Scalable inference of discrete data: User behavior, networks and genetic variation” (2015) Advisor: Blei,…
Read morevTools Release Announcement; WebEx Updates
1 March 2015
The IEEE MGA vTools team is happy to announce successful new releases for the following vTools applications: Meetings 5.0 WebInABox 3.0…
Read moreNew Standards-Related Patent Policy by IEEE
1 March 2015
On February 8, the Board of Directors of the IEEE voted to approve a set of amendments to the organization’s patent policy. Previously, the IEEE…
Read morevTools Release Announcement; WebEx Updates
1 March 2015
The IEEE MGA vTools team is happy to announce successful new releases for the following vTools applications:
Read moreRecent Patents in Signal Processing (March 2015) – Deep Learning Techniques
1 March 2015
For our March 2015 issue, we cover recent patents granted in the area of Deep Lerning techniques. The section below covers patents granted recently…
Read moreSignal Processing Conferences
1 March 2015
Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing. http://www.signalprocessingsociety.org…
Read moreFree Student and Graduate Student Membership for 2015
1 March 2015
Know a classmate or student who may benefit from a Student membership to the IEEE Signal Processing Society (SPS)? We are pleased to announce that…
Read moreThe PhysioNet/Computing in Cardiology Challenge 2015 Announcement
1 March 2015
The PhysioNet/Computing in Cardiology Challenge 2015 is now open! This year's challenge is 'Reducing False Arrhythmia Alarms in the ICU'. False alarms in the ICU can lead to a disruption of care, impacting both the patient and the clinical staff through noise disturbances, desensitization to warnings and slowing of response times, leading to decreased quality of care. False alarm rates can be as high as 90% or more. To address this issue we have developed an expert-labelled data set of 1250 life-threatening arrhythmia alarms with five minutes of electrophysiological and pulsatile waveform data leading up to each alarm event. Competitors are challenged to devise a method of processing all the available data to reduce false alarms with minimal or no effect on true (vital) alarms.
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