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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
UMich introductory engineering course aims to revolutionize nuclear energy through community engagement
A new course at the University of Michigan offered by the Nuclear Engineering and Radiological Sciences (NERS) Department seeks to address the lack of community engagement in the design of energy technologies by pioneering a socially engaged approach.
S. Chatzidakis, P. T. Forsberg, L. H. Tsoukalas
Nuclear Technology | Volume 192 | Number 1 | October 2015 | Pages 61-73
Technical Paper | Radiation Transport and Protection | doi.org/10.13182/NT14-112
Articles are hosted by Taylor and Francis Online.
Governments are interested in radiation signal encryption in projects relating to international safeguards; however, the available algorithms do not suitably address the challenges presented by the increasing computational capability of various actors, which require recent encryption algorithms to be more robust against attack algorithms. Therefore, an algorithmic approach for performing radiation signal encryption employing the nonlinear capabilities of artificial neural networks with the noise-like properties of chaotic systems is proposed herein. The radiation signal digital envelope consists of the encrypted signal such as may be found through gamma spectroscopy, the secret key for the encryption, and the associated hash value. The presented algorithmic approach demonstrates, in an orderly manner, an integrated method for computing this radiation signal digital envelope. Indispensable constituents of encryption include both the construction of a time series with chaotic characteristics and the incorporation of a hash function generator to satisfy the security requirements of confidentiality, authentication, and nonrepudiation. The methodology is demonstrated via the encryption and subsequent decryption of two frequently occurring radiation signals, namely, gamma spectroscopy signals from 60Co and 137Cs. The results obtained demonstrate the capability of the algorithmic approach to integrate artificial neural networks and chaos dynamics to produce the radiation signal digital envelope (for given security requirements).