Paper to Appear in IEEE Trans. Information Security
April 24, 2016
associated with RF Fingerprinting, classifier
improvements and feature selection methods will
appear in a summer 2016 issues of the IEEE
Transactions on Information Forensics and Security
(TIFS), a top tier journal for cyber security.
The paper, "Feature Selection for RF Fingerprinting
with Multiple Discriminant Analysis and Using ZigBee
Device Emissions," discusses research on developing
improved feature selection methods for multiple
discriminant analysis. Robust device identification
was presented, which beat competing methods.
RF emissions from ZigBee devices were
considered. In addition to print, this paper
can be found on ResearchGate.
Book Deal Signed
With SAS Press
April 23, 2016
Trevor Bihl, President and CEO of Bihl Engineering,
signed a contract with SAS Press on April 23, 2016
to write Biostatistics Using JMP, A Practical
Guide. This book will leverage his familiarity
with JMP software and his biostatistics teaching
experience at Wright State. The estimated publication date is
Nodal Metasis in Endometrial Cancer
Andressa Teixeira (visiting scholar at Wright State
University) presented the poster "A Pre and
Intraoperative Scoring System to Predict Nodal
Metasis in Endometrial Cancer" at the 2016 Society
of Surgical Oncology – Annual Cancer Symposium in
Boston. Dr. Trevor Bihl provided statistical
data analysis and methodological support in this
research to develop a scoring mechanism for
endometrial cancer. A journal paper is in the works
and a copy of the poster can be found on ResearchGate.
Understanding, and Addressing Big Data
Global will publish the comprehensive big data
survey paper written by Dr. Trevor Bihl (President
and CEO of Bihl Engineering), Dr. Bill Young
(Assistant Professor of Business at OU), and Dr.
Gary Weckman (Associate Professor of Engineering at
OU) in their April-June 2016 issue. This paper
reviewed all aspects of big data from analytics,
linguistics, history, and social issues. An
advance copy can be found on ResearchGate.
Networks for SAR Combat Identification
Military Operations Research Society (MORS) Journal
published "Contextual Features and Bayesian Belief
Networks for Improved Synthetic Aperture Radar
Combat Identification" in January. This paper
was written by John Situ (George Mason University),
Dr. Mark Friend (Northern Arizona University), Dr.
Kenneth Bauer (Air Force Institute of Technology)
and Dr. Trevor Bihl (President and CEO of Bihl
Engineering). This paper created an innovative
approach to Synthetic Aperture Radar (SAR) combat
identification which used contextual information,
Bayesian Belief Networks, Probabilistic Neural
Networks, and Extended Confusion Matrices.
Performance statistically outperformed the best
currently in literature. An advance copy can
be found on ResearchGate.