References
- J.V. Hugo, D.I. Gertman, A method to select human-system interfaces for nuclear power plants, Nucl. Eng. Technol. 48 (2016) 87-97. https://doi.org/10.1016/j.net.2015.10.004
- J. O'hara, J. Higgins, J. Persensky, P. Lewis, J. Bongarra, Human factors engineering program review model, in: Report no.ADA488603, Brookhaven National Lab Upton, NY, 2004.
- M. Hatch, E. Ron, A. Bouville, L. Zablotska, G. Howe, The Chernobyl disaster: cancer following the accident at the Chernobyl nuclear power plant, Epidemiol. Rev. 27 (2005) 56-66. https://doi.org/10.1093/epirev/mxi012
- L.H. Ikuma, C. Harvey, C.F. Taylor, C. Handal, A guide for assessing control room operator performance using speed and accuracy, perceived workload, situation awareness, and eye tracking, J. Loss Prev. Process. Ind. 32 (2014) 454-465. https://doi.org/10.1016/j.jlp.2014.11.001
- A. Anokhin, A. Ivkin, S. Dorokhovich, Application of ecological interface design in nuclear power plant (NPP) operator support system, Nucl. Eng. Technol. 50 (2018) 619-626. https://doi.org/10.1016/j.net.2018.03.005
- F. Nachreiner, Standards for ergonomics principles relating to the design of work systems and to mental workload, Appl. Ergon. 26 (1995) 259-263. https://doi.org/10.1016/0003-6870(95)00029-C
- N. Moray, Mental workload since 1979, Int. Rev. Ergon 2 (1988) 123-150.
- Q. Gao, Y. Wang, F. Song, Z. Li, X. Dong, Mental workload measurement for emergency operating procedures in digital nuclear power plants, Ergonomics 56 (2013) 1070-1085. https://doi.org/10.1080/00140139.2013.790483
- Y.-T. Jou, T.-C. Yenn, C.J. Lin, C.-W. Yang, C.-C. Chiang, Evaluation of operators' mental workload of human-system interface automation in the advanced nuclear power plants, Nucl. Eng. Des. 239 (2009) 2537-2542. https://doi.org/10.1016/j.nucengdes.2009.06.023
- P.S. Tsang, M.A. Vidulich, Mental Workload and Situation Awareness, Wiley, New York, NY, 2006.
- M. Kankal, O. Yuksek, Artificial neural network approach for assessing harbor tranquility: the case of Trabzon Yacht Harbor, Turkey, Appl. Ocean Res. 38 (2012) 23-31. https://doi.org/10.1016/j.apor.2012.05.009
- X. Dou, Y. Yang, Comprehensive evaluation of machine learning techniques for estimating the responses of carbon fluxes to climatic forces in different terrestrial ecosystems, Atmosphere 9 (2018) 83. https://doi.org/10.3390/atmos9030083
- L. Yingying, L. Guodong, G. Qiang, X. Yonghai, Radial basis function neural network based comprehensive evaluation for power quality, in: Power System Technology, 2006. PowerCon 2006. International Conference on, IEEE, 2006, pp. 1-5.
- C.E. Balas, M.L. Koc, R. Tur, Artificial neural networks based on principal component analysis, fuzzy systems and fuzzy neural networks for preliminary design of rubble mound breakwaters, Appl. Ocean Res. 32 (2010) 425-433. https://doi.org/10.1016/j.apor.2010.09.005
- A. Ergin, I.H. Ozolcer, F. Sahin, Evaluating coastal scenery using fuzzy logic: application at selected sites in Western Black Sea coastal region of Turkey, Ocean Eng. 37 (2010) 583-591. https://doi.org/10.1016/j.oceaneng.2010.02.003
- H.Y. Wu, K.L. Chen, Z.H. Chen, Q.H. Chen, Y.P. Qiu, J.C. Wu, J.F. Zhang, Evaluation for the ecological quality status of coastal waters in East China Sea using fuzzy integrated assessment method, Mar. Pollut. Bull. 64 (2012) 546-555. https://doi.org/10.1016/j.marpolbul.2011.12.022
- L.A. Zadeh, Information and control, Fuzzy sets 8 (1965) 338-353.
- Q. Xie, J.-Q. Ni, Z. Su, Fuzzy comprehensive evaluation of multiple environmental factors for swine building assessment and control, J. Hazard Mater. 340 (2017) 463-471. https://doi.org/10.1016/j.jhazmat.2017.07.024
- C.J. Gao, D.P. Li, Fuzzy comprehensive assessment on environmental impact of petroleum project, in: Applied Mechanics and Materials, Trans Tech Publ, 2013, pp. 734-737.
- L. Liu, J. Zhou, X. An, Y. Zhang, L. Yang, Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China, Expert Syst. Appl. 37 (2010) 2517-2521. https://doi.org/10.1016/j.eswa.2009.08.004
- W. Chu, Y. Li, C. Liu, W. Mou, L. Tang, A manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation for aircraft structural parts, Int. J. Prod. Res. 52 (2014) 3239-3258. https://doi.org/10.1080/00207543.2013.869369
- J. Jiao, H. Ren, S. Sun, Assessment of surface ship environment adaptability in seaways: a fuzzy comprehensive evaluation method, Int. J. Nav. Arch. Ocean 8 (2016) 344-359. https://doi.org/10.1016/j.ijnaoe.2016.05.002
- F. Jiang, Q. Zheng, W. Shi, The applied research of fuzzy comprehensive evaluation on talent training mode of safety engineering, Procedia Engineering 43 (2012) 425-430. https://doi.org/10.1016/j.proeng.2012.08.073
- J. Kang, J. Zhang, J. Gao, Improving performance evaluation of health, safety and environment management system by combining fuzzy cognitive maps and relative degree analysis, Saf. Sci. 87 (2016) 92-100. https://doi.org/10.1016/j.ssci.2016.03.023
- D. Li, Y. Sui-huai, W. Wen-jun, Research on fuzzy comprehensive evaluation of human-machine interface layout of driller control room, in: Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on, IEEE, 2013, pp. 1114-1117.
- F.G. Paas, J.J. Van Merrienboer, The efficiency of instructional conditions: an approach to combine mental effort and performance measures, Hum. Factors 35 (1993) 737-743. https://doi.org/10.1177/001872089303500412
- Y.-Y. Yeh, C.D. Wickens, Dissociation of performance and subjective measures of workload, Hum. Factors 30 (1988) 111-120. https://doi.org/10.1177/001872088803000110
- V.J. Gawron, Human Performance, Workload, and Situational Awareness Measures Handbook, CRC Press, 2008.
- S. Yan, C.C. Tran, Y. Wei, J.L. Habiyaremye, Driver's mental workload prediction model based on physiological indices, Int. J. Occup. Saf. Ergon. (2017) 1-9.
- S.-L. Hwang, Y.-J. Yau, Y.-T. Lin, J.-H. Chen, T.-H. Huang, T.-C. Yenn, C.-C. Hsu, Predicting work performance in nuclear power plants, Saf. Sci. 46 (2008) 1115-1124. https://doi.org/10.1016/j.ssci.2007.06.005
- R.F. Dyer, J.J. Matthews, C.E. Wright, K.L. Yudowitch, Questionnaire construction manual, in: DTIC Document, 1976.
- D. de Waard, B. Lewis-Evans, Self-report scales alone cannot capture mental workload, Cogn. Technol. Work 16 (2014) 303-305. https://doi.org/10.1007/s10111-014-0277-z
- S. Hart, L. Staveland, Development of NASA-TLX (task load index): results of empirical and theoretical research, Hum. Mental Workload (1988) 139-183.
- S. Rubio, E. Diaz, J. Martin, J.M. Puente, Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods, Appl. Psychol. 53 (2004) 61-86. https://doi.org/10.1111/j.1464-0597.2004.00161.x
- Y. Lean, F. Shan, Brief review on physiological and biochemical evaluations of human mental workload, Hum. Factors Ergon. Manuf. 22 (2012) 177-187. https://doi.org/10.1002/hfm.20269
- T.Q. Tran, R.L. Boring, D.D. Dudenhoeffer, B.P. Hallbert, M.D. Keller, T.M. Anderson, Advantages and disadvantages of physiological assessment for next generation control room design, in: Human Factors and Power Plants and HPRCT 13th Annual Meeting, 2007 IEEE 8th, IEEE, 2007, pp. 259-263.
- T. Heine, G. Lenis, P. Reichensperger, T. Beran, O. Doessel, B. Deml, Electrocardiographic features for the measurement of drivers' mental workload, Appl. Ergon. 61 (2017) 31-43. https://doi.org/10.1016/j.apergo.2016.12.015
- G.F. Wilson, An analysis of mental workload in pilots during flight using multiple psychophysiological measures, Int. J. Aviat. Psychol. 12 (2002) 3-18. https://doi.org/10.1207/S15327108IJAP1201_2
- J.L. Rosch, J.J. Vogel-Walcutt, A review of eye-tracking applications as tools for training, Cognit. Technol. Work 15 (2013) 313-327. https://doi.org/10.1007/s10111-012-0234-7
- D. Toker, C. Conati, B. Steichen, G. Carenini, Individual user characteristics and information visualization: connecting the dots through eye tracking, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, 2013, pp. 295-304.
- J.S. Ha, Y.-J. Byon, J. Baek, P.H. Seong, Method for inference of operators' thoughts from eye movement data in nuclear power plants, Nucl. Eng. Technol. 48 (2016) 129-143. https://doi.org/10.1016/j.net.2015.09.004
- Z.-H. Zou, Y. Yun, J.-N. Sun, Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment, J. Environ. Sci-china 18 (2006) 1020-1023. https://doi.org/10.1016/S1001-0742(06)60032-6
- X. Gai, The design and evaluation of ship navigation display and control system based on cognitive load, in: Harbin Engineering University Thesis, China, 2015.
- D. Liu, Z. Zou, Water quality evaluation based on improved fuzzy matterelement method, J. Environ. Sci. (China) 24 (2012) 1210-1216. https://doi.org/10.1016/S1001-0742(11)60938-8
- L.I. Xiao-Xing, D.U. Jun-Kai, F.U. Yao, Water quality evaluation model of normal cloud based on coefficient variation and entropy weight, Water Resour. Power 10 (2017) 55-58. China.
- P.V. Carvalho, J.O. Gomes, M.R. Borges, Human centered design for nuclear power plant control room modernization, in: 4th Workshop HCP Human Centered Processes, Citeseer, 2011.
- F. Nachreiner, P. Nickel, I. Meyer, Human factors in process control systems: the design of humanemachine interfaces, Saf. Sci. 44 (2006) 5-26. https://doi.org/10.1016/j.ssci.2005.09.003
- S. Yan, C.C. Tran, Y. Chen, K. Tan, J.L. Habiyaremye, Effect of user interface layout on the operators' mental workload in emergency operating procedures in nuclear power plants, Nucl. Eng. Des. 322 (2017) 266-276. https://doi.org/10.1016/j.nucengdes.2017.07.012
- T.M. Lanzetta, W.N. Dember, J.S. Warm, D.B. Berch, Effects of task type and stimulus heterogeneity on the event rate function in sustained attention, Hum. Factors: J. Hum. Fact. Ergon. Soc. 29 (1987) 625-633. https://doi.org/10.1177/001872088702900602
- M. Castor, E. Hanson, E. Svensson, S. Nahlinder, P. LeBlaye, I. MacLeod, N. Wright, J. Alfredson, L. Agren, P. Berggren, GARTEUR Handbook of Mental Workload Measurement, GARTEUR, Group for Aeronautical Research and Technology in Europe, Flight Mechanics Action Group FM, 2003, p. 164. AG13.
- S. Moresi, J.J. Adam, J. Rijcken, P.W. Van Gerven, H. Kuipers, J. Jolles, Pupil dilation in response preparation, Int. J. Psychophysiol. 67 (2008) 124-130. https://doi.org/10.1016/j.ijpsycho.2007.10.011
- S.M. Wierda, H. van Rijn, N.A. Taatgen, S. Martens, Pupil dilation deconvolution reveals the dynamics of attention at high temporal resolution, Proc. Natl. Acad. Sci. Unit. States Am. 109 (2012) 8456-8460. https://doi.org/10.1073/pnas.1201858109
- K.F. Van Orden, T.-P. Jung, S. Makeig, Combined eye activity measures accurately estimate changes in sustained visual task performance, Biol. Psychol. 52 (2000) 221-240. https://doi.org/10.1016/S0301-0511(99)00043-5
- M. Nakayama, K. Takahashi, Y. Shimizu, The act of task difficulty and eye-movement frequency for the'Oculo-motor indices, in: Proceedings of the 2002 Symposium on Eye Tracking Research & Applications, New Orleans, Louisiana, 2002, pp. 37-42.
- U. Ahlstrom, F.J. Friedman-Berg, Using eye movement activity as a correlate of cognitive workload, Int. J. Ind. Ergon. 36 (2006) 623-636. https://doi.org/10.1016/j.ergon.2006.04.002
- L.L. Di Stasi, A. Antoli, J.J. Canas, Evaluating mental workload while interacting with computer-generated artificial environments, Entertain. Comput. 4 (2013) 63-69. https://doi.org/10.1016/j.entcom.2011.03.005
- P. Lehrer, M. Karavidas, S.E. Lu, E. Vaschillo, B. Vaschillo, A. Cheng, Cardiac data increase association between self-report and both expert ratings of task load and task performance in flight simulator tasks: an exploratory study, Int. J. Psychophysiol. 76 (2010) 80-87. https://doi.org/10.1016/j.ijpsycho.2010.02.006
- A. Pauzie, Evaluation of the driver's mental workload: a necessity in a perspective of in-vehicle system design for road safety improvement, Cognit. Technol. Work 16 (2014) 299-302. https://doi.org/10.1007/s10111-014-0276-0
- M. Naderpour, J. Lu, G. Zhang, A safety-critical decision support system evaluation using situation awareness and workload measures, Reliab. Eng. Syst. Saf. 150 (2016) 147-159. https://doi.org/10.1016/j.ress.2016.01.024
Cited by
- A Systematic Review of Physiological Measures of Mental Workload vol.16, pp.15, 2019, https://doi.org/10.3390/ijerph16152716
- Using Artificial Neural Networks for Predicting Mental Workload in Nuclear Power Plants Based on Eye Tracking vol.206, pp.1, 2019, https://doi.org/10.1080/00295450.2019.1620055
- Enhanced Accuracy for Multiclass Mental Workload Detection Using Long Short-Term Memory for Brain–Computer Interface vol.14, 2019, https://doi.org/10.3389/fnins.2020.00584
- Measuring and multilevel fuzzy comprehensive predicting comfort parameters of soft materials by a new handle evaluation system vol.90, pp.23, 2020, https://doi.org/10.1177/0040517520928792
- Evaluating aircraft cockpit emotion through a neural network approach vol.35, pp.1, 2019, https://doi.org/10.1017/s0890060420000475
- Fuzzy clustering analysis of comprehensive hand of polyester fabric based on the CHES-FY system vol.91, pp.7, 2021, https://doi.org/10.1177/0040517520957409
- Fuzzy FMECA analysis of radioactive gas recovery system in the SPES experimental facility vol.53, pp.5, 2019, https://doi.org/10.1016/j.net.2020.11.011
- Development of an Ergonomic User Interface Design of Calcium Imaging Processing System vol.12, pp.4, 2019, https://doi.org/10.3390/app12041877