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Cyber Security Paper to Appear in IEEE Trans. Information Security and Forensics

April 24, 2016

Research 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

Dr. 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 Spring/Summer 2017.


Scoring for Nodal Metasis in Endometrial Cancer

March, 2016

Dr. 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.


Defining, Understanding, and Addressing Big Data

February, 2016

IGI 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.


Bayesian Belief Networks for SAR Combat Identification

January, 2016

The 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.


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