Search alternatives:
based mutation » based nutrition (Expand Search), based population (Expand Search)
models » model (Expand Search)
based mutation » based nutrition (Expand Search), based population (Expand Search)
models » model (Expand Search)
-
1
Testing and Assessment of Protocols and Systems Modeled as Extended Finite State Machines
Published 2013Get full text
doctoralThesis -
2
Assessing test suites of extended finite state machines against model and code based faults
Published 2021Subjects: “…Model-based testing…”
Get full text
article -
3
On Studying the Effectiveness of Extended Finite State Machine Based Test Selection Criteria
Published 2015Subjects: Get full text
doctoralThesis -
4
Parallel Implementations for Eliminating Finite State Machine Mutants
Published 2017Subjects: “…Model Based Testing…”
Get full text
doctoralThesis -
5
A Formal Assisted Approach for Modeling and Testing Security Attacks in IoT Edge Devices
Published 2023Get full text
doctoralThesis -
6
Fault Coverage and Diagnosis of Protocols and Systems Modeled As Extended Finite State Machines
Published 2015Get full text
doctoralThesis -
7
Machine learning based personalized drug response prediction for lung cancer patients
Published 2022“…Each patient’s unique mutation status was modeled considering MD simulation to extract molecular-level geometric features. …”
-
8
Testing web applications
Published 2006“…Traditional testing techniques are not adequate for web-based applications, since they miss their additional features such as their multi-tier nature, hyperlink-based structure, and event-driven feature. …”
Get full text
Get full text
Get full text
article -
9
-
10
MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction
Published 2023“…In this study, we propose a novel computational approach, called MMPatho, for enhancing missense mutation pathogenic prediction. First, we established a large-scale nonredundant MM benchmark data set based on the entire Ensembl database, complemented by a focused blind test set specifically for pathogenic GOF/LOF MM. …”
-
11
Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition
Published 2019“…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …”
Get full text
Get full text
Get full text
Get full text
article