  Emerging technologies can have major economic impacts and affect strategic
stability. Yet, early identification of emerging technologies remains
challenging. In order to identify emerging technologies in a timely and
reliable manner, a comprehensive examination of relevant scientific and
technological (S&T) trends and their related references is required. This
examination is generally done by domain experts and requires significant
amounts of time and effort to gain insights. The use of domain experts to
identify emerging technologies from S&T trends may limit the capacity to
analyse large volumes of information and introduce subjectivity in the
assessments. Decision support systems are required to provide accurate and
reliable evidence-based indicators through constant and continuous monitoring
of the environment and help identify signals of emerging technologies that
could alter security and economic prosperity. For example, the research field
of hypersonics has recently witnessed several advancements having profound
technological, commercial, and national security implications. In this work, we
present a multi-layer quantitative approach able to identify future signs from
scientific publications on hypersonics by leveraging deep learning and weak
signal analysis. The proposed framework can help strategic planners and domain
experts better identify and monitor emerging technology trends.
