Her primary scientific interests are in Fault tree analysis, Reliability engineering, Algorithm, Fault tolerance and Data structure. Her Fault tree analysis study combines topics in areas such as Reliability theory, Set, Binary decision diagram and Markov chain. Her work carried out in the field of Markov chain brings together such families of science as Fault model, Logic gate and Parallel computing, Parallel processing.
Her Reliability engineering research focuses on subjects like Markov model, which are linked to Hazard and Fault coverage. She works mostly in the field of Fault tolerance, limiting it down to topics relating to Redundancy and, in certain cases, Hypercube, as a part of the same area of interest. Her work is dedicated to discovering how Data structure, Boolean function are connected with Computational complexity theory and Maintenance engineering and other disciplines.
The scientist’s investigation covers issues in Fault tree analysis, Reliability engineering, Fault tolerance, Algorithm and Software. Joanne Bechta Dugan has researched Fault tree analysis in several fields, including Data mining, Binary decision diagram, Markov chain, Markov model and Data structure. Her studies deal with areas such as Bayesian network, Expert system, Artificial intelligence, Event tree and Probabilistic risk assessment as well as Data mining.
Her study in the field of Dependability is also linked to topics like Reliability and Imperfect. Her Fault tolerance research is multidisciplinary, incorporating perspectives in Redundancy, Fault model and Fault detection and isolation. Joanne Bechta Dugan combines subjects such as Reliability theory and Fault coverage with her study of Algorithm.
Her scientific interests lie mostly in Artificial intelligence, Fault tree analysis, Binary decision diagram, Human–computer interaction and Reliability engineering. Her study on Robot learning, Stochastic gradient descent, Convolutional neural network and Deep learning is often connected to Experiential learning as part of broader study in Artificial intelligence. In her study, which falls under the umbrella issue of Fault tree analysis, Fault tolerance is strongly linked to Algorithm.
Her Fault tolerance research incorporates themes from Mathematical optimization and Markov chain, Markov model. Joanne Bechta Dugan has included themes like Boolean function and Data structure in her Binary decision diagram study. Her Reliability engineering study incorporates themes from Computation and Component.
Her primary areas of investigation include Fault tree analysis, Binary decision diagram, Reliability engineering, Algorithm and Component. The study incorporates disciplines such as Computation, Boolean function and Data structure in addition to Binary decision diagram. Her Data structure research integrates issues from Redundancy and Maintenance engineering.
Her study brings together the fields of Fault tolerance and Algorithm. Her biological study spans a wide range of topics, including Mathematical optimization and Markov chain, Markov model. Joanne Bechta Dugan works mostly in the field of Component, limiting it down to topics relating to Failure mode and effects analysis and, in certain cases, Computational complexity theory and Benchmark.
J.B. Dugan;S.J. Bavuso;M.A. Boyd
Hichem Boudali;Joanne Bechta Dugan
J.B. Dugan;K.S. Trivedi
J.B. Dugan;K.J. Sullivan;D. Coppit
R. Gulati;J.B. Dugan
G.J. Pai;J.B. Dugan
H. Boudali;J.B. Dugan
Liudong Xing;J.B. Dugan
K.J. Sullivan;J.B. Dugan;D. Coppit
Joanne Bechta Dugan;Kishor S. Trivedi;Mark K. Smotherman;Robert M. Geist
G.J. Pai;J.B. Dugan
J.B. Dugan
J.B. Dugan;S.J. Bavuso;M.A. Boyd
Zhihua Tang;J.B. Dugan
S.V. Amari;J.B. Dugan;R.B. Misra
Joanne Bechta Dugan;Salvatore J. Bavuso;Mark A. Boyd
R. Manian;J. Bechta Dugan;D. Coppit;K.J. Sullivan
Liudong Xing;O. Tannous;J. B. Dugan
J.B. Dugan;B. Venkataraman;R. Gulati
Salvatore J. Bavuso;Joanne Bechta Dugan;Kishor S. Trivedi;Elizabeth M. Rothmann
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