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Aggarwal, A., Chauhan, A., Kumar, D., Mittal, M., & Verma, S. (2020). Classification of fake news by fine-tuning deep bidirectional transformers based language model. EAI Endorsed Transactions on Scalable Information Systems Online First; EAI: Ghent, Belgium.  
10/28/20, 1:54 PM
Baonan, W., Feng, H., Huanguo, Z., & Chao, W. (2019). From evolutionary cryptography to quantum artificial intelligent cryptography. Journal of Computer Research and Development, 56(10), 2112.  
7/12/21, 9:45 AM
Bertino, E., Calo, S., Toma, M., Verma, D., Williams, C., & Rivera, B. 2017, A cognitive policy framework for next-generation distributed federated systems: Concepts and research directions. Paper presented at 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).  
6/12/23, 6:16 PM
Blasch, E., Schuck, T., & Gagne, O. B. (2021). Trusted entropy-based information maneuverability for ai information systems engineering. In Engineering Artificially Intelligent Systems (pp. 34–52). Springer.  
7/21/22, 10:16 AM
Booker, C. M. (2013). First-strike advantage: The united states' counter to china's preemptive integrated network electronic warfare strategy AIR UNIV MAXWELL AFB AL SCHOOL OF ADVANCED AIR AND SPACE STUDIES.  
8/17/21, 10:12 AM
Carlin, J. P., & Graff, G. M. (2019). Dawn of the code war: America's battle against russia, china, and the rising global cyber threat. PublicAffairs.  
6/25/20, 10:16 AM
DC, J. C. O. S. W. (2012). Joint electromagnetic spectrum management operations. Joint Publication.  
10/20/23, 8:27 PM
Deng, S., Zhao, H., Fang, W., Yin, J., Dustdar, S., & Zomaya, A. Y. (2020). Edge intelligence: The confluence of edge computing and artificial intelligence. IEEE Internet of Things Journal.  
8/12/20, 9:34 AM
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.  
10/28/20, 4:47 PM
Dulhanty, C., Deglint, J. L., Daya, I. B., & Wong, A. (2019). Taking a stance on fake news: Towards automatic disinformation assessment via deep bidirectional transformer language models for stance detection. arXiv preprint arXiv:1911.11951.  
10/28/20, 4:50 PM
Elhefnawy, N. (2021). 'a sixth generation fighter?' an update. An Update (May 4, 2021).  
5/18/21, 3:31 PM
Elonheimo, T. (2021). Comprehensive security approach in response to russian hybrid warfare. Strategic Studies Quarterly, 15(3).  
9/21/21, 2:27 PM
Fenstermacher, L., Perez, M., Larson, K., & Rice, K. 2021, A playbook for characterization of multi-domain information. Paper presented at Signal Processing, Sensor/Information Fusion, and Target Recognition XXX.  
9/15/21, 1:49 PM
Ferreira, P. V. R., Paffenroth, R., Wyglinski, A. M., Hackett, T. M., Bilen, S. G., & Reinhart, R. C., et al.. (2018). Multiobjective reinforcement learning for cognitive satellite communications using deep neural network ensembles. IEEE Journal on Selected Areas in Communications, 36(5), 1030–1041.  
4/26/21, 9:21 AM
Fugate, S., & Ferguson-Walter, K. (2019). Artificial intelligence and game theory models for defending critical networks with cyber deception. AI Magazine, 40(1), 49–62.  
10/28/20, 1:50 PM
Gadepally, V. N., Hancock, B. J., Greenfield, K. B., Campbell, J. P., Campbell, W. M., & Reuther, A. I. (2016). Recommender systems for the department of defense and intelligence community. Lincoln Laboratory Journal, 22(1), 74–89.  
12/11/22, 1:33 PM
Gia, T. N., Nawaz, A., Querata, J. P. N., Tenhunen, H., & Westerlund, T. 2019, Artificial intelligence at the edge in the blockchain of things. Paper presented at International Conference on Wireless Mobile Communication and Healthcare.  
8/12/20, 9:42 AM
Graber, M. M. (2021). Using artificial intelligence and machine learning to tackle big data. ISR Research Task Force - ACSC.  
12/7/21, 3:27 PM
Grooms, G. B. (2019). Artificial intelligence applications for automated battle management aids in future military endeavors Naval Postgraduate School Monterey United States.  
11/4/20, 10:23 AM
Gu, T., Dolan-Gavitt, B., & Garg, S. (2017). Badnets: Identifying vulnerabilities in the machine learning model supply chain. arXiv preprint arXiv:1708.06733.  
11/18/20, 11:34 AM
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WIKINDX 6.7.0 | Total resources: 1610 | Username: -- | Bibliography: WIKINDX Master Bibliography | Style: American Psychological Association (APA)