Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 16 Similar Profiles
Hardware Engineering & Materials Science
Embedded systems Engineering & Materials Science
Field programmable gate arrays (FPGA) Engineering & Materials Science
Monitoring Engineering & Materials Science
Computer hardware Engineering & Materials Science
Networks (circuits) Engineering & Materials Science
Data storage equipment Engineering & Materials Science
Electric power utilization Engineering & Materials Science

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Research Output 1999 2017

  • 781 Citations
  • 13 h-Index
  • 53 Conference contribution
  • 30 Article
  • 1 Chapter

An analysis of incorporating small coding exercises as homework in introductory programming courses

Edgcomb, A. D., Vahid, F., Lysecky, R. & Lysecky, S. Jun 24 2017 In : ASEE Annual Conference and Exposition, Conference Proceedings. 2017-June

Research output: Research - peer-reviewArticle

Students
Feedback

Composite risk modeling for automated threat mitigation in medical devices

Rao, A., Rozenblit, J., Lysecky, R. & Sametinger, J. 2017 In : Simulation Series. 49, 6, p. 90-99 10 p.

Research output: Research - peer-reviewArticle

Composite materials
Remediation
Pacemakers
Risk management
Middleware
Problem-Based Learning
Students
Computer programming

Getting students to earnestly do reading, studying, and homework in an introductory programming class

Edgcomb, A., Vahid, F., Lysecky, R. & Lysecky, S. Mar 8 2017 SIGCSE 2017 - Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. Association for Computing Machinery, p. 171-176 6 p.

Research output: ResearchConference contribution

homework
programming
student
Students
learning

Hierarchical non-intrusive in-situ requirements monitoring for embedded systems

Seo, M. & Lysecky, R. 2017 Runtime Verification - 17th International Conference, RV 2017, Proceedings. Springer Verlag, Vol. 10548 LNCS, p. 259-276 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10548 LNCS)

Research output: ResearchConference contribution

Embedded Systems
Monitoring
Requirements
Embedded systems
Hardware