Analysis of Cognitive Technology Components in Uncertainty Environment Using Bipolar Fuzzy Set
Subject Areas : Technology Management
Mohammad Hosein Asgharpour Sareshkeh
1
,
S. Sina Masoumi
2
,
Mehrzad Jamshidi Guilani
3
1 - Masters student
2 -
3 - independent researcher
Keywords: Cognitive Technology, Fuzzy Bipolar, Industry 4.0, Cognitive Management.,
Abstract :
Cognitive science along with nanotechnology, biotechnology, and communication technology as emerging sciences and technologies, by promoting human mental and physical functions can be a launching point for industries in industry 4.0. Therefore, the present study aims to analyze cognitive technology criteria to find examples to communicate with management concepts. Based on this, initially, using the opinions of experts, the weight related to cognitive technology criteria was obtained through Shannon entropy; then the components of cognitive technology were studied and analyzed using bipolar fuzzy electrode method. The results show that the components of "skills and abilities", "storage, retrieval and use" and "encouragement" are superior to other components, which shows the importance of neuroscience and cognitive defense approaches. Considering that perceptual and behavioral metrics can be used in a business-oriented perspective, cognitive science and technology can enhance performance by influencing concepts related to the soft aspects of management. Cognitive management seeks to explain how to achieve the ultimate goals of each of the additional management based on science, principles and cognitive approaches based on leadership and strategic management with cognitive approach, management of organizational behavior and human characteristics with cognitive approach, marketing management and Branding is focused with a cognitive approach.
1- B. Salgues. Society 5.0: Industry of the Future, Technologies, Methods and tools. 2018.
2- M. Brettel., N. Friederichsen., M. Keller., M. Rosenberg. “How virtualization, decentralization and network building change the manufacturing landscape: an Industry 4.0 perspective,” World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, vol. 8, no. 1, pp. 37–44, Nov. 2014, doi: 10.5281/zenodo.1336426.
3- M. A. M. S. Lemstra and M. A. De Mesquita, “Industry 4.0: a tertiary literature review,” Technological Forecasting and Social Change, vol. 186, p. 122204, Jan. 2023, doi: 10.1016/j.techfore.2022.122204.
4- T. Durand., M. Dubreuil. “Humanizing the future: managing change with soft technology,” Foresight, vol. 3, no. 4, pp. 285–295, Aug. 2001, doi: 10.1108/14636680110803283.
5- Z. Jin. Soft technology: the essential of innovation. Futures Research Quarterly, 18(2), 1-24. 2002.
6- Z. Jin. The fourth generation of technology foresight and soft technology. Futures Research Quarterly, 19(2), 23-38. 2003.
7- Z. Jin. Global technological change: From hard technology to soft technology. Intellect Books. 2011.
8- M.I. Madahi., M. Samadzadeh., A. Karavand. Cognition in complex organizations, Management Accounting, 3(7), 19-28. 2008. (In Persian)
9- J.C. Smith. Historical foundations of cognitive science (Vol. 46). Springer Science & Business Media. 2012.
10- A. R. Hemmati Moghadam. The history of the formation of cognitive sciences, an introduction to cognitive sciences and technologies and their applications, the Organization for the Study and Compilation of Humanities Books of Universities (Samet), Research Institute for Research and Development of Humanities. 2017.
11- K. Frankish., W. Ramsey. The Cambridge handbook of cognitive science. Cambridge University Press. 2012.
12- Z. A. Caddick, S. H. Fraundorf, B. M. Rottman, and T. J. Nokes-Malach, “Cognitive perspectives on maintaining physicians’ medical expertise: II. Acquiring, maintaining, and updating cognitive skills,” Cognitive Research: Principles and Implications, vol. 8, no. 1, Jul. 2023, doi: 10.1186/s41235-023-00497-8.
13- Supreme Council of Cultural Revolution. Strategic document of cognitive sciences and technologies. 1390. (In Persian)
14- Parliament Research Office. Familiarity with knowledge and cognitive technology and its status in Iran, serial number: 13750. 2014. (In Persian)
15- H. Moradi. Cognitive enhancement games and software, an introduction to cognitive sciences and technologies and their applications, Tehran: Organization for the study and editing of university humanities books (Samt), Humanities Research and Development Institute. 2017. (In Persian)
16- M. Shahba. Art, creativity, media and cognitive sciences, an introduction to cognitive sciences and technologies and their applications, Tehran: Organization for the Study and Compilation of University Humanities Books (Samt), Humanities Research and Development Institute. 2017. (In Persian)
17- S, Semnanian., A. Asadollahi. Cognitive neurosciences, an introduction to cognitive sciences and technologies and their applications, Tehran: Organization for Studying and Compiling Humanities Books of Universities (Samt), Humanities Research and Development Institute. 2017. (In Persian)
18- S. Ghorbani., M. Zahedi., R. Hosnawi. Moving towards soft technologies in the field of soft war, Soft Power Studies, (6), 149-182. 2011. (In Persian)
19- H. Poladi. Explaining the concept of soft technology and its transfer; Case Study of SPR Project, Campus Technology Park, (14), 22-25. 2016. (In Persian)
20- G. Lakkof. The Invariance Hypothesis: is abstract reason based on image-schemas? Cognitive Linguistics (includes Cognitive Linguistic Bibliography), 1(1), 39-74. 1990.
21- S. K. Kharazi. Cognitive management. An introduction to cognitive science and technology and its applications, Tehran (Samt): Human Sciences Research and Development Institute. 2017. (In Persian)
22- H. Abedi Jafari., M.S. Taslimi., A. Faqihi., M. Sheikh Zadeh. Theme analysis and theme network: a simple and efficient way to explain patterns in qualitative data. Strategic Management Thought (Management Thought), Vol. 5, no. 2 (Sequential 10), pp. 151-198. 2010. (In Persian)
23- H. Khanifar., N. Muslimi. Basics and principles of qualitative research methods (new and applied approach). Tehran: Negha Danesh, 2016. (In Persian)
24- E. Fontela., A. Gabus. The DEMATEL observer. 1976.
25- B. Srđević., Y. Medeiros., A. Faria., M. Schaer. Objective Evaluation of Performance Criteria for a Reservoir System, Vodoprivreda, 35 (3-4), 163-176. 2003.
26- R. Benayoun., B. Roy., N. Sussman. Manual de reference du programme electre. Note de synthese et Formation, 25, 79. 1996.
27- M.A. Alghamdi., N.O. Alshehri, M. Akram. Multi-criteria decision-making methods in bipolar fuzzy environment. International Journal of Fuzzy Systems, 20(6), 2057-2064. 2018.
28- W. R. Zhang. Bipolar fuzzy sets and relations: a computational framework for cognitive modeling and multiagent decision analysis. In NAFIPS/IFIS/NASA'94. Proceedings of the First International Joint Conference of The North American Fuzzy Information Processing Society Biannual Conference. The Industrial Fuzzy Control and Intellige (pp. 305-309). IEEE. 1994.
29- A. M. Birang. The future scenario of cognitive sciences and technologies in Iran, Ph.D. thesis, Scientific Political Research Center of Iran, Future Thinking Department. 2017. (In Persian)
