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This book provides glimpses into contemporary research in
information systems & technology, learning, artificial
intelligence (AI), machine learning, and security and how it
applies to the real world, but the ideas presented also span the
domains of telehealth, computer vision, the role and use of mobile
devices, brain-computer interfaces, virtual reality, language and
image processing and big data analytics and applications. Great
research arises from asking pertinent research questions. This book
reveals some of the authors' "beautiful questions" and how they
develop the subsequent "what if" and "how" questions, offering
readers food for thought and whetting their appetite for further
research by the same authors.
This book provides glimpses into contemporary research in
information systems & technology, learning, artificial
intelligence (AI), machine learning, and security and how it
applies to the real world, but the ideas presented also span the
domains of telehealth, computer vision, the role and use of mobile
devices, brain-computer interfaces, virtual reality, language and
image processing and big data analytics and applications. Great
research arises from asking pertinent research questions. This book
reveals some of the authors' "beautiful questions" and how they
develop the subsequent "what if" and "how" questions, offering
readers food for thought and whetting their appetite for further
research by the same authors.
Developing a reliable software system, several issues need to be
addressed. These issues include the definition of reliable
software, reliable development methodologies, testing methods for
reliability, and reliability growth prediction modeling. Many
software reliability growth models were proposed with the goal to
estimate the number of residual software faults, which occur in the
software testing process. In this thesis, we explore an alternative
approach using two types of neural networks (NN) models, the
feedforward and the Radial basis function. We also use of fuzzy
rules. NNs have been used both to estimate parameters of a formal
model and to learn to emulate the process model itself to predict
future faults. Feedforward and Radial basis function have been
successfully used to solve a variety of prediction problems, which
include real-time control, military, and operating system
applications. A set of fuzzy rules were also developed to model the
dynamics of the software reliability growth models in various
applications. The reported results using neural networks and fuzzy
logic can improve the software reliability growth modeling
solution.
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