42 citations · 82 across the 7 of their papers we have counts for
7 papers
On the Practices of Autonomous Systems Development: Survey-based Empirical Findings
Katerina Goseva-Popstojanova, Denny Hood, Johann Schumann +1
Autonomous systems have gained an important role in many industry domains and are beginning to change everyday life. However, due to dynamically emerging applications and often pro…
The Untold Impact of Learning Approaches on Software Fault-Proneness Predictions
Mohammad Jamil Ahmad, Katerina Goseva-Popstojanova, Robyn R. Lutz
Software fault-proneness prediction is an active research area, with many factors affecting prediction performance extensively studied. However, the impact of the learning approach…
Scalable Solutions for Automated Single Pulse Identification and Classification in Radio Astronomy
Thomas Devine, Katerina Goseva-Popstojanova, Di Pang
Data collection for scientific applications is increasing exponentially and is forecasted to soon reach peta- and exabyte scales. Applications which process and analyze scientific…
A novel single-pulse search approach to detection of dispersed radio pulses using clustering and supervised machine learning
Di Pang, Katerina Goseva-Popstojanova, Thomas Devine +1
We present a novel two-stage approach which combines unsupervised and supervised machine learning to automatically identify and classify single pulses in radio pulsar search data.…
Towards Malware Detection via CPU Power Consumption: Data Collection Design and Analytics (Extended Version)
Robert Bridges, Jarilyn Hernandez Jimenez, Jeffrey Nichols +2
This paper presents an experimental design and data analytics approach aimed at power-based malware detection on general-purpose computers. Leveraging the fact that malware executi…
Malware Detection on General-Purpose Computers Using Power Consumption Monitoring: A Proof of Concept and Case Study
Jarilyn M. Hernández Jiménez, Jeffrey A. Nichols, Katerina Goseva-Popstojanova +2
Malware detection is challenging when faced with automatically generated and polymorphic malware, as well as with rootkits, which are exceptionally hard to detect. In an attempt to…
Detection of Dispersed Radio Pulses: A machine learning approach to candidate identification and classification
Thomas Devine, Katerina Goseva-Popstojanova, Maura McLaughlin
Searching for extraterrestrial, transient signals in astronomical data sets is an active area of current research. However, machine learning techniques are lacking in the literatur…