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10 years of news and resources for members of the IEEE Signal Processing Society

Initiatives & Trends

In our “What should we learn from… ” series we report a special issue of the Proceedings of the IEEE in August, Memories in the Future of Information Processing aiming to explore memories and information processing multidimensionally. It covers the subject of memory in its multitudinous forms in circuits and systems.

John Leonard’s group in the MIT Department of Mechanical Engineering specializes in SLAM, or simultaneous localization and mapping, the technique whereby mobile autonomous robots map their environments and determine their locations.

For our August 2015 issue, we cover recent patents dealing with various applications of fingerprint analysis and recognition. The section below covers patents granted recently for server and client side performance enhancement in fingerprint ACR systems, fingerprint matching methods, high speed fingerprint recognition systems, fingerprint preview quality enhancement, and finger print based authentication issues.

On July 6 a technical study titled: Keys Under Doormats: Mandating Insecurity by Requiring Government Access to All Data and Communications has been published. The scientists behind this work are more than domain experts. Among the others: Steven M. Bellovin known for his work in the encrypted keys exchange; Josh Benaloh who invented the Benaloh cryptosystem; Matt Blaze who worked on cryptographic files systems; Whitfield Diffie universally known as one the pioneers of public key cryptography; Peter G. Neumann who worked on Provably Secure Operative Systems; Ronald L. Rivest who is “R” in RSA; Jeffrey I. Schiller known for being one of the creator of Kerberos and Bruce Schneier one the biggest expert in security and cryptography.

In order to protect endangered rhinos, the Kenya Wildlife Service has recently teamed up with the US-based Stimson Center and Linköping University in Sweden in a project called Ngulia, named after the Kenyan rhino sanctuary where the technology is to be implemented. The aim is to investigate how new technology and signal processing algorithms can be combined to create a smart savannah and to help stamp out poaching.

For our July 2015 issue, we cover recent patents dealing with various applications of adaptive filtering. The section below covers patents granted recently for reducing blocking effect and ringing noise, radio frequency spektrum analysis, filter bank implementation, signal amplifying, low complexity filtering, magnetic fluid analysis, signal canceling and filter representation.

This Funding Opportunity Announcement (FOA) seeks applications that propose research studies that extend experimental protocols beyond the range of acoustic psychophysical research studies widely performed today. This will require design of algorithms and research studies that validate the potential benefits from these novel approaches to acoustic signal processing.

The special issue of the Proceedings of the IEEE in July is the second issue focusing on reconfigurable systems. In the first special issue (vol. 103, no. 3, 2015) introduced by eNewsletter in June, the foundational concepts are addressed. In this special issue, the editors focus on the basic concepts discussed in the first issue by considering more advanced applications, the extension of reconfigurability to other phenomenologies/domains, and the impacts of selected emerging technologies.

For our June 2015 issue, we cover recent patents dealing with various applications of image inpainting. The section below covers patents granted recently for image segmentation, image enhancement, mobile authentication, texture analysis and image compression.

Machine learning, a subfield of computer science, has been widely applied in many areas from science to engineering to many interdisciplinary fields. Nature Reviews Genetics recently published an article that summarized machine learning applications in genetics and genomics, authored by University of Washington researchers Maxwell W. Libbrecht and William Stafford Noble. The topics of interest included supervised versus unsupervised learning, generative versus discriminative modeling, incorporating prior knowledge, handling heterogeneous data, feature selection, imbalanced class sizes, handling missing data, and modelling dependence among examples.

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