1 |
Operation performance information system (OPIS) (n.d.), http://opis.kins.re.kr/opis?act=KEOBA3400R.
|
2 |
C. Griffith, S. Mahadevan, Sleep deprivation effect on human performance: a meta-analysis approach (PSAM-0010), Proc. Eighth Int. Conf. Probabilistic Saf. Assess. Manag. (2006) 1488-1496, https://doi.org/10.1115/1.802442.paper185.
|
3 |
J. Reason, A. Hobbs, Managing Maintenance Error: A Practical Guide, first ed., CRC Press, 2003.
|
4 |
J. Reason, Human Error, Cambridge University Press, Cambridge, 1990, https://doi.org/10.1017/CBO9781139062367.
|
5 |
J.S. Ha, P.H. Seong, M.S. Lee, J.H. Hong, Development of human performance measures for human factors validation in the advanced MCR of APR-1400, IEEE Trans. Nucl. Sci. 54 (2007) 2687-2700, https://doi.org/10.1109/TNS.2007.907549.
DOI
|
6 |
R.J. Mumaw, E.M. Roth, K.J. Vicente, C.M. Burns, There is more to monitoring a nuclear power plant than meets the eye, Hum. Factors J. Hum. Factors Ergon. Soc. 42 (2000) 36-55, https://doi.org/10.1518/001872000779656651.
|
7 |
M. Wang, Y. Maeda, Y. Takahashi, Human intention recognition via eye tracking based on fuzzy inference, in: 6th Int. Conf. Soft Comput. Intell. Syst. 13th Int. Symp. Adv. Intell. Syst. SCIS/ISIS 2012, 2012, pp. 846-851, https://doi.org/10.1109/SCIS-ISIS.2012.6505330.
|
8 |
K.B. Kristi Branch, Fitness for duty in the nuclear power Industry : an update of technical issues on drugs of abuse testing and fatigue management, Richland, WA, https://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr7156/, 2013.
|
9 |
L. Wang, Glissadic saccades: a possible measure of vigilance, Ergonomics 41 (1998) 721-732, https://doi.org/10.1080/001401398186874.
DOI
|
10 |
P.J. Rousseeuw, Silhouettes: a graphical aid to the interpretation and validation of cluster analysis, J. Comput. Appl. Math. 20 (1987) 53-65, https://doi.org/10.1016/0377-0427(87)90125-7.
DOI
|
11 |
L. Kaufman, P.J. Rousseeuw, Finding Groups in Data, first ed., John Wiley & Sons, Inc., Hoboken, NJ, USA, 1990 https://doi.org/10.1002/9780470316801.
|
12 |
Y. Morad, Y. Barkana, D. Zadok, M. Hartstein, E. Pras, Y. Bar-Dayan, Ocular parameters as an objective tool for the assessment of truck drivers fatigue, Accid. Anal. Prev. 41 (2009) 856-860, https://doi.org/10.1016/j.aap.2009.04.016.
DOI
|
13 |
US N.R.C 10 CFR Part 26: fitness for duty programs. https://www.nrc.gov/reading-rm/doc-collections/cfr/part026/, 2008.
|
14 |
L. De Gennaro, M. Ferrara, L. Urbani, M. Bertini, Oculomotor impairment after 1 night of total sleep deprivation: a dissociation between measures of speed and accuracy, Clin. Neurophysiol. 111 (2000) 1771-1778, https://doi.org/10.1016/S1388-2457(00)00393-X.
DOI
|
15 |
L.L. Di Stasi, A. Antolí, J.J. Canas, Main sequence: an index for detecting mental workload variation in complex tasks, Appl. Ergon. 42 (2011) 807-813, https://doi.org/10.1016/j.apergo.2011.01.003.
DOI
|
16 |
Y. Shinoda, Y. Sugiuchi, M. Takahashi, Y. Izawa, Neural substrate for suppression of omnipause neurons at the onset of saccades, Ann. N. Y. Acad. Sci. 1233 (2011) 100-106, https://doi.org/10.1111/j.1749-6632.2011.06171.x.
DOI
|
17 |
B.T. Jap, S. Lal, P. Fischer, E. Bekiaris, Using EEG spectral components to assess algorithms for detecting fatigue, Expert Syst. Appl. 36 (2009) 2352-2359, https://doi.org/10.1016/j.eswa.2007.12.043.
|
18 |
F. Gharagozlou, G.N. Saraji, A. Mazloumi, A. Nahvi, A.M. Nasrabadi, A.R. Foroushani, A.A. Kheradmand, M. Ashouri, M. Samavati, Detecting driver mental fatigue based on EEG alpha power changes during simulated driving, Iran, J. Public Health 44 (2015) 1693-1700.
|
19 |
Z. Mu, J. Hu, J. Yin, Driving fatigue detecting based on EEG signals of forehead Area, Int. J. Pattern Recognit. Artif. Intell. 31 (2017), https://doi.org/10.1142/S0218001417500112, 1750011.
|
20 |
C. Ahlstrom, M. Nystrom, K. Holmqvist, C. Fors, D. Sandberg, A. Anund, G. Kecklund, T. Åkerstedt, Fit-for-duty test for estimation of drivers' sleepiness level: eye movements improve the sleep/wake predictor, Transp. Res. C Emerg. Technol. 26 (2013) 20-32, https://doi.org/10.1016/j.trc.2012.07.008.
|
21 |
Y. Yamada, M. Kobayashi, Detecting mental fatigue from eye-tracking data gathered while watching video: evaluation in younger and older adults, Artif. Intell. Med. 91 (2018) 39-48, https://doi.org/10.1016/j.artmed.2018.06.005.
|
22 |
T.S. Madhulatha, An overview on clustering methods, IOSR J. Eng. 02 (2012) 719-725, https://doi.org/10.9790/3021-0204719725.
DOI
|
23 |
E. Zils, A. Sprenger, W. Heide, J. Born, S. Gais, Differential effects of sleep deprivation on saccadic eye movements, Sleep 28 (2005) 1109-1115, https://doi.org/10.1093/sleep/28.9.1109.
DOI
|
24 |
K. Holmqvist, N. Marcus, A. Richard, D. Richard, J. Halszka, W.J. van De, Eye Tracking: A Comprehensive Guide to Methods and Measures, first ed., Oxford University Press, New York, 2011.
|
25 |
M. Zhang, E.H. Sparer, L.A. Murphy, J.T. Dennerlein, D. Fang, J.N. Katz, A.J. Caban-Martinez, Development and validation of a fatigue assessment scale for U.S. construction workers, Am. J. Ind. Med. 58 (2015) 220-228, https://doi.org/10.1002/ajim.22411.
DOI
|
26 |
D. Ketchen, C. Shook, The application of cluster Analysis in strategic management Research : an analysis and critique, Strateg. Manag. J. 17 (1996) 441-458, author (s): David J. Ketchen , Jr. and christopher L. Shook Published by : Wiley stable URL, http://www.jstor.org/stable/2486927, 06-06-2016 06.
DOI
|
27 |
A. Heitmann, R. Guttkuhn, A. Aguirre, U. Trutschel, M. Moore-Ede, Technologies for the monitoring and prevention of driver fatigue, in: Proc. First Int. Driv. Symp. Hum. Factors Driv. Assessment, Train. Veh. Des. Driv. Assess. 2001, 2001, pp. 81-86, https://doi.org/10.17077/drivingassessment.1013.
|
28 |
J.S. Ha, Y.-J. Byon, C.-S. Cho, P.H. Seong, Eye-tracking studies based on attentional-resource effectiveness and insights into future research, Nucl. Technol. 202 (2018) 237-246, https://doi.org/10.1080/00295450.2018.1428003.
DOI
|