Cognition and Cognitive Dynamic Systems Concepts and Applications in Project Risk Management

Authors

  • Hanieh Pakroogolafshani School of Engineering Practice and Technology, McMaster University, Hamilton, Canada

Keywords:

Project Management, Risk Management, Cognitive Dynamic Systems, Cognition.

Abstract

Cognition is the brain’s ability to perform high-level functions including understanding and information processing. In general, cognition is considered analytical rather than emotional. Cognitive models are mathematical representations of issues that are not necessarily mathematical. On the other hand, risk analysis and management is a process of defining factors or parameters that are mildly to severely dangerous for a given system involving businesses or individuals. Recently, research and investigations have explored the potential of utilizing cognitive models in risk management and analysis in order to better clarify risk factors in a system and control risk resources. In this paper, fundamentals of risk management and cognitive dynamic systems are discussed, and applications and various implementations of cognitive systems based on real-life examples are introduced.

References

[1] David Louis Olson, Desheng Dash Wu, Enterprise risk management. Vol. 1., World Scientific, 2008.
[2] Jie Lu, Lakhmi C. Jain, Guangquan Zhang, Handbook on decision making: Vol 2: Risk management in decision making. Vol. 33., 2012: Springer Science & Business Media.
[3] Lionel Galway , "Quantitative Risk Analysis for Project Management," A Critical Review, WR-112-RC, http://www. rand. org/pubs/working_papers/2004/RAND_WR112. pdf , 2004.
[4] Jan Emblemsvåg, Augmenting the risk management process, INTECH Open Access Publisher, 2011.
[5] H.-P. Berg, "Risk management: procedures, methods and experiences," Risk Management , vol. 1, no. 17, pp. 79-95, 2010.
[6] P. K. Dey, "Project risk management: a combined analytic hierarchy process and decision tree approach," Cost Engineering , Vols. 44, no. 3 (2002): , no. 3, pp. 13-27, 2002.
[7] M. T. Taghavifard, K. Khalili Damghani, R. Tavakkoli Moghaddam, "Decision Making Under Uncertain and Risky Situations," In Enterprise Risk Management Symposium Monograph Society of Actuaries. , 2009.
[8] P. M. Institute, Practice Standard for Project Risk Management, Project Management Institute, 2009.
[9] W. D. J. Price, "Methods of risk identification," Fire safety journal , vol. 2, no. 2, pp. 105-110, 1980.
[10] Robin K. McGuire, "Deterministic vs. probabilistic earthquake hazards and risks," Soil Dynamics and Earthquake Engineering, vol. 21, no. 5, pp. 377-384, 2001.
[11] B. Fremouw, PMP Pocket Guide: The Ultimate PMP Exam Cheat Sheets, : Goodrich Fremaux Publishing, 2016.
[12] N. R. Council, The Owner's Role in Project Risk Management, National Academies Press, 2005.
[13] Kai Meng Tay, Chee Peng Lim, "On the use of fuzzy inference techniques in assessment models: part II: industrial applications," Fuzzy Optimization and Decision Making, vol. 7, no. 3, pp. 283-302, 2008.
[14] I. Stockwell, "Introduction to Correlation and Regression analysis," In Statistics and Data Analysis. SAS Global Forum, 2008.
[15] J. M. Fuster, Cortex and Mind: Unifying Cognition, New York: Oxforf, 2005.
[16] S. HAYKIN, "Cognitive Dynamic Systems: Radar, Control and Radio," Proceedings of the IEEE, Vols. Vol. 100, No. 7, no. July 2012, pp. 2095-2103, 2012.
[17] S. Haykin, Coginitive Dynamic Systems, New York: Cambridge University Press, 2012.
[18] Saman Sarraf , Cristina Saverino, Ali Mohammad Golestani, "A Robust and Adaptive Decision-Making Algorithm for Detecting Brain Networks Using Functional MRI within the Spatial and Frequency Domain," in The IEEE International Conference on Biomedical and Health Informatics (BHI) , Las Vegas, 2016.
[19] Saman Sarraf, Cristina Saverino, Halleh Ghaderi, John Anderson, "Brain network extraction from probabilistic ICA using functional Magnetic Resonance Images and advanced template matching techniques," in Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference, Toronto, 2014.
[20] Joaquin M. Fuster, Steven L. Bressler, "Cognit activation: a mechanism enabling temporal integration in working memory," Trends in Cognitive Sciences, Vols. Vol. 16, No. 4, no. 2012, pp. 207-218, April 2012.
[21] Saman Sarraf, Danielle D. DeSouza, John Anderson, and Ghassem Tofighi, "DeepAD: Alzheimer? s Disease Classification via Deep Convolutional Neural Networks using MRI and fMRI," bioRxiv, vol. 070441, 2017.
[22] John AE Anderson, Saman Sarraf, Tarek Amer, Buddhika Bellana, Vincent Man, Karen L. Campbell, Lynn Hasher, and Cheryl L. Grady, "Task-linked Diurnal Brain Network Reorganization in Older Adults: A Graph Theoretical Approach," Journal of Cognitive Neuroscience, 2016.
[23] Abadi, Mart?n, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado et al. , ""TensorFlow: Large-scale machine learning on heterogeneous systems, 2015."," Software available from tensorflow.org, vol. 1, 2015.
[24] Simon Haykin, Yanbo Xue, Peyman Setoodeh, "Cognitive Radar: Step Toward Bridging thr Gap Between Neuroscience and Engineering," Proceedings of the IEEE, Vols. Vol. 100, No. 11, no. November 2012, pp. 3012-3030, 2012.
[25] Krishnan, Krishanth, Taralyn Schwering, Saman Sarraf, "Cognitive Dynamic Systems: A Technical Review of Cognitive Radar.," arXiv preprint arXiv:1605.08150, 2016.
[26] Rob Ranyard, W. Ray Crozier, Ola Svenson, Decision making: Cognitive models and explanations, Psychology Press, 1997.
[27] Robert Karayev, Miragha Naghiyev, "Cognitive approach in development of innovation management models for company," Procedia-Social and Behavioral Sciences, vol. 58 , pp. 812-819, 2012.
[28] Cristina Saverino, Zainab Fatima, Saman Sarraf, Anita Oder, Stephen C. Strother, and Cheryl L. Grady, "The Associative Memory Deficit in Aging Is Related to Reduced Selectivity of Brain Activity during Encoding.," Journal of cognitive neuroscience, 2016.
[29] Saman Sarraf, Jian Sun, "ADVANCES IN FUNCTIONAL BRAIN IMAGING: A COMPREHENSIVE SURVEY FOR ENGINEERS AND PHYSICAL SCIENTISTS.," International Journal of Advanced Research, vol. 4, no. 8, pp. 640-660, 2016.
[30] Saman Sarraf, Ghassem Tofighi, "Deep Learning-based Pipeline to Recognize Alzheimer's Disease using fMRI Data," in Future Technologies Conference (FTC), 2016.
[31] Nazanin Sadat Hashemi, Roya Babaei Aghdam, Atieh Sadat Bayat Ghiasi, and Parastoo Fatemi, "Template Matching Advances and Applications in Image Analysis," American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), vol. 26, no. 3, pp. 91-108, 2016.

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Published

2017-02-03

How to Cite

Pakroogolafshani, H. (2017). Cognition and Cognitive Dynamic Systems Concepts and Applications in Project Risk Management. American Scientific Research Journal for Engineering, Technology, and Sciences, 28(1), 75–87. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/2640

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