ACM Transactions on Computational Logic, ‎1529-3785

Fachzeitschrift: Zeitschrift

Zuletzt angesehen

Publikationen

  1. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations
  2. Supporting discourse in a synchronous learning environment
  3. How Much Tracking Is Necessary? - The Learning Curve in Bayesian User Journey Analysis
  4. Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach
  5. Expertise in research integration and implementation for tackling complex problems
  6. Using augmented video to test in-car user experiences of context analog HUDs
  7. Microstructural development of as-cast AM50 during Constrained Friction Processing: grain refinement and influence of process parameters
  8. Special Issue The Discourse of Redundancy Introduction
  9. Multiphase-field modeling of temperature-driven intermetallic compound evolution in an Al-Mg system for application to solid-state joining processes
  10. Failure to Learn From Failure Is Mitigated by Loss-Framing and Corrective Feedback
  11. Towards an open question answering architecture
  12. Systematic feature evaluation for gene name recognition
  13. Guest Editorial - ''Econometrics of Anonymized Micro Data''
  14. Embarrassment as a public vs. private emotion and symbolic coping behaviour
  15. »HOW TO MAKE YOUR OWN SAMPLES«
  16. Meta-Image – a collaborative environment for the image discourse
  17. Development of high performance single-phase solid solution magnesium alloy at low temperature
  18. HAWK - hybrid question answering using linked data
  19. Binary Random Nets II
  20. Is the market classification of risk always efficient?
  21. Reporting and Analysing the Environmental Impact of Language Models on the Example of Commonsense Question Answering with External Knowledge
  22. Does cognitive load moderate the seductive details effect? A multimedia study
  23. Current issues in competence modeling and assessment
  24. Estimation of minimal data sets sizes for machine learning predictions in digital mental health interventions