Information Technology Reference
In-Depth Information
16. Lazarus, R.S.: Psychological stress and the coping process. McGraw-Hill, New York
(1966)
17. http://www.drlwilson.com/Articles/NERVOUS%20SYSTEM. htm (last re-
ferred March 2010)
18. http://www.s-cool.co.uk/alevel/psychology/stress/
what-is-stress. html (last referred March 2010)
19. Andreassi, J.L.: Psychophysiology: Human Behavior and Physiological Response, 3rd edn.
Erlbaum, Hillsdale (1995)
20. John, T.C., Louis, G.T., Gary, G.B.: Handbook of Psychophysiology. Cambridge Univer-
sity Press, Cambridge (2000)
21. AAPB.: The Association for Applied Psychophysiology and Biofeedback,
http://www.aapb.org/i4a/pages/index.cfm?pageid= 336
(last referred March 2010)
22. Lehrer, M.P., Smetankin, A., Potapova, T.: Respiratory Sinus Arrytmia Biofeedback Ther-
apy for Asthma: A report of 20 Unmediated Pediatric Cases Using the Smetaniknnnn
Method. Applied Psychophysiology and Biofeedback 25(3), 193-200 (2000)
23. https://www.cs.tcd.ie/medilink/index.htm?href=components/
CBR. htm (last referred March 2010)
24. Kang, S.H., Lau, S.K.: Intelligent Knowledge Acquisition with Case-Based Reasoning
Techniques. Technical report, University of Wollongong, NSW, Australia, pp. 1-8 (2002)
25. Schank, R.C., Abelson, R.P.: Scripts, Plans, Goals and Understanding. Erlbaum, Hillsdale
(1977)
26. Schank, R.: Dynamic memory: a theory of reminding and learning in computers and peo-
ple. Cambridge University Press, Cambridge (1982)
27. Kolodner, J.L.: Maintaining Organization in a Dynamic Long-Term Memory. Cognitive
Science 7(4), 243-280 (1983)
28. Kolodner, J.L.: Reconstructive Memory: A Computer Model. Cognitive Science 7(4),
281-285 (1983)
29. Koton, P.: Using experience in learning and problem solving. Massachusetts Institute of
Technology, Laboratory of Computer Science, Ph.D. Thesis MIT/LCS/TR-441 (1989)
30. Simpson, R.L.: A Computer Model of Case-Based Reasoning in Problem Solving: An Inves-
tigation in the Domain of Dispute Mediation. Technical Report GIT-ICS-85/18, Georgia In-
stitute of Technology, School of Information and Computer Science, Atlanta USA (1985)
31. Bareiss, E.: RPROTOS: A Unified Approach to Concept Representation, Classification,
and learning. Ph.D. thesis, Department of Computer Science, University of Texas (1988)
32. Bareiss, E.: Examplar-based Knowledge Acquisition: A unified Approach to Concept,
Classification and learning. PHD thesis, 300 North Zeeb Road, Ann Arbor, AI 48106-
1346 (1989)
33. Gierl, L., Schmidt, R.: CBR in Medicine. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D.,
Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 273-
298. Springer, Heidelberg (1998)
34. Ahmed, M.U., Begum, S., Funk, P., Xiong, N.: Fuzzy Rule-Based Classification to Build
Initial Case Library for Case-Based Stress Diagnosis. In: 9th International conference on
Artificial Intelligence and Applications, Austria, pp. 225-230 (2009)
35. Ahmed, M.U., Begum, S., Funk, P., Xiong, N., von Schéele, B.: A Multi-Module Case
Based Biofeedback System for Stress Treatment. Artificial Intelligence in Medicine (in
press, 2010)
36. Bichindaritz, I., Marling, C.: Case-based reasoning in the health sciences: What's next?
Artificial Intelligence in Medicine 36(2), 127-135 (2006)
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