H. Hilowle, and D. Basar. IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue X):
99-103(December 2020)1. Argyris, C., & Schon, D., (1978). Organizational Learning: A Theory of Action Perspective, Addison-Wesley, Reading, MA. 2. Argyris, C., Putman, R., and McLain Smith, D., (1985). Action Science, Concepts, Methods, and Skills for Research and Intervention, San Francisco, Jossey Bass 3. Bapuji, H., and Crossan, M. (2004). From Raising Questions to Providing Answers: Reviewing Organizational Learning Research, Management Learning, Vol. 35, No.4, PP. 397-417. 4. Bhattacherjee, A. (2012). Social Science Research: Principles, Methods, and Practices (2nd ed.). Textbooks Collection. Book 3. http://scholarcommons.usf.edu/oa_textbooks/3 5. C. Mausolff., (2004). Learning from feedback in performance measurement systems. Public Performance and Management Review, 28: 9-29 4. 6. C.M. Graham and F.M. Nafukho. (2007). Culture, organizational learning, and selected employee background variables in small size business enterprises. Journal of European Industrial Training, 31:127-144 6. 7. Chiva, R., Grandío, A., & Alegre, J., (2010). Adaptive and Generative Learning: Implications from Complexity Theories, International Journal of Management Reviews, Vol. 12, No. 2, PP. 114-129. 8. De Geus, A.p. (1988). Planning as learning Harvard Business Review,66(2),70-74. 9. Dimovski, V., (1994). Organizational Learning and Competitive Advantage, Ph.D. Thesis, Cleveland, Ohio 10. Farago, J., and Skyrme, D., (1995). The Learning Organization, (On-line), Available at http://www.skyrme.com/insight/3lrnorg.htm 11. Farago, J., and Skyrme, D., (1995). The Learning Organization, (On-line), Available at http://www.skyrme.com/insight/3lrnorg.htm. fifth edition (5th ed.). Edinburgh Gate, Harlow, Pearson Education Limited. 12. Finger, M., & Brand, S., (1999). The Concept of The Learning Organization, Applied To The Transformation of The Public Sector, In M. Easterby-Smith, L. Araujo and J. Burgoyne, Organizational Learning and The Learning Organization, London: Sage, P.2..
Nayana, Rugmani, and Prof.Raghi. IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue IV):
48-52.(June 2020)1. Be My Eyes: Android Voice Application for Visually Impaired People by RuchaDoiphode, MayuriGanore, AshwiniGarud, TejaswiniGhuge, Parminder Kaur (Guide) Department Of Computer Science Engineering Dr.Babasaheb Ambedkar Marathwada University, Jawaharlal Nehru Engineering College, Aurangabad, India 2. A new Android application for blind and visually impaired people by PiotrKardyś, Adam Dąbrowski Division of Signal Processing and Electronic Systems Poznan University of Technology, Poznan, Poland. 3. P.Kardyś,A.Dąbrowski,“Standard Bluetooth Natlebezprzewodowy chsystemów telekomunikacy jnychkrót kiegozasięgu w aplikacjach bio-itelemedycznych”, Elektronika 52 (5), 5/2011, pp. 56–59. 4. R. E. Sorace, V. S. Reinhardt, and S. A. Vaughn, “High-speed digital-to-RF converter,” U.S. Patent 5 668 842, Sept. 16, 1997. (2002) The IEEE website. Online. Available: http://www.ieee.org/..
H. TARIQ, W. YANG, I. HAMEED, B. AHMED, and R. KHAN. IJIRIS:: International Journal of Innovative Research Journal in Information Security, Volume IV (Issue XII):
01-07(December 2017)1 Hugh A. Chipman, Edward I. George, and Robert E. McCulloch. “Bayesian CART Model Search.” Journal of the American Statistical Association, Vol. 93(443), pp 935–948, September 1998. 2 Sujata Garera, Niels Provos, Monica Chew, and Aviel D. Rubin. “A framework for detection and measurement of phishing attacks.” In Proceedings of the 2007 ACM workshop on Recurring malicious code - WORM ’07, page 1, 2007. 3 Abhishek Gattani, AnHai Doan, Digvijay S. Lamba, NikeshGarera, Mitul Tiwari, Xiaoyong Chai, Sanjib Das, Sri Subramaniam, AnandRajaraman, and VenkyHarinarayan. “Entity extraction, linking, classifica- tion, and tagging for social media.” Proceedings of the VLDB Endowment, Vol. 6(11), pp 1126–1137, August 2013. 4 David D. Lewis. Naive (Bayes) at forty: The independence assumption in information retrieval. pages 4–15. 1998. 5 Justin Ma, Lawrence K. Saul, Stefan Savage, and Geoffrey M. Voelker. “Learning to detect malicious URLs.” ACM Transactions on Intelligent Systems and Technology, Vol. 2(3), pp 1–24, April 2011. 6 FadiThabtah Maher Aburrous, M.A.Hossain, KeshavDahal. “Intelligent phishing detection system for e-banking using fuzzy data mining.” Expert Systems with Applications, Vol. 37(12), pp 7913–7921, Dec 2010. 7 AnkushMeshram and Christian Haas. “Anomaly Detection in Industrial. Networks using Machine Learning: A Roadmap.” In Machine Learning for Cyber Physical Systems, pages 65–72. Springer Berlin Heidelberg, Berlin, Heidelberg, 2017. 8 Xuequn Wang Nik Thompson,Tanya Jane McGill. “Security begins at home: Determinants of home computer and mobile device security behavior.” Computers & Security, Vol. 70, pp 376–391, Sep 2017. 9 Dan Steinberg and Phillip Colla. “CART: Classification and Regression Trees.” The Top Ten Algorithms in Data Mining, pp 179–201, 2009. 10 D. Teal. “Information security techniques including detection, interdiction and/or mitigation of memory injection attacks,” Google patents. Oct 2013. 11 Kurt Thomas, Chris Grier, Justin Ma, Vern Paxson, and Dawn Song. “Design and Evaluation of a Real-Time URL Spam Filtering Service.” In 2011 IEEE Symposium on Security and Privacy, pp 447–462. May 2011. 12 Sean Whalen, Nathaniel Boggs, and Salvatore J. Stolfo. “Model Aggregation for Distributed Content Anomaly Detection.” In Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop - AISec ’14, pp 61–71, New York, USA, 2014. ACM Press. 13 Ying Yang and Geoffrey I. Webb. “Discretization for Naive-Bayes learning: managing a discretization bias and variance.” Machine Learning, Vol. 74(1), pp 39–74, Jan 2009..