bookmarks (hide)1
- International Journal of Innovative Research in Information Security is an International peer-reviewed research publishing journal with a laser-beam focal aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of Information Technology. It is a monthly published online international scientific research journal focusing on issues in information technology research.
publications (hide)58
- International Journal of Innovative Research in Information Security, 09 (2): 50-54 (May 2023)1. Muhlenbach, F. and Rakotomalala, R. (2015), “Discretization of Continuous Attributes,” In: Wang, J., Ed., Encyclopedia of Data Warehousing and Mining, Idea Group Reference, 397-402. https://doi.org/10.4018/978-1-59140-557-3.ch076 2. M. Liu, D. Zhang, and D. Shen, “Relationship induced multi- 52 template learning for diagnosis of alzheimer’s disease and mild cognitive impairment,” IEEE transactions on medical imaging, vol. 35, no. 6, p. 1463—1474, (2016). https://doi.org/10.1109/tmi.2016.2515021 3. Abdullah Caliskan, Hasan Badem, A. Baştürk, M.E. Yüksel, “Diagnosis Of The Parkinson Disease By Using Deep Neural Network Classifier”, Journal Of Electrical And Electronics Engineering, (2017):3311-3318 4. M. Abdar and M. Zomorodi-Moghadam, “Impact of Patients’ Gender on Parkinson’s disease using Classification Algorithms” Journal of AI and Data Mining, vol. 6, (2018). 5. Sleigh, J.W.; Olofsen, E.; Dahan, A.; de Goede, J.; Steyn-Ross, A. Entropies of the EEG: The effects of general anaesthesia. In Proceedings of the 5th International Conference on Memory, Awareness and Consciousness, New York, NY, USA, 1–3 June (2019) 6. Tsuda, M., Asano, S., Kato, Y., Murai, K., and Miyazaki, M. (2020). Differential diagnosis of multiple system atrophy with predominant parkinsonism and Parkinson's disease using neural networks. J. Neurol. Sci. 401, 19–26. https://doi.org/10.1016/j.jns.2019.04.014 7. Tysnes, O.-B., and Storstein, A. (2021). Epidemiology of Parkinson's disease. J. Neural Trans. 124, 901–905. https://doi:10.1007/s00702-017-1686-y 8. Parkinson J. An Essay on the Shaking Palsy. London: Sherwood, Neely, and Jones; 1817. pp. 1–16. Google Scholar 9. Twelves D, Perkins KS, Counsell C. Systematic review of incidence studies of Parkinson’s disease. Mov Disord. 2003;18:19–31. PubMed Google Scholar 10. National Institute for Health and Care Excellence (NICE) Parkinson’s disease: diagnosis and management in primary and secondary care. NICE clinical guidelines 35. Jun, 2006. Available https://doi.org/10.1136/heartjnl-2022-321095 http://www.nice.org.uk/guidance/cg35/resources/guidance-parkinsons-disease-pdf. Accessed April 28, 2015. 11. Schrag A, Horsfall L, Walters K, et al. Prediagnostic presentations of Parkinson’s disease in primary care: a case-control study. Lancet Neurol. 2015; PubMed Google Scholar https://doi.org/10.1016/s1474-4422(14)70287-x 12. Parkinson’s Disease Foundation Statistics on Parkinson’s. Available at: www.pdf.org.en/parkinson_statistics Accessed June 19, 2014. 13. Driver JA, Logroscino G, Gaziano JM, et al. Incidence and remaining lifetime risk of Parkinson disease in advanced age. Neurology. 2009;72:32–38. PMC free article PubMed Google Scholar https://doi.org/10.1212/01.wnl.0000341769.50075.bb 14. De Lau LM, Breteler MM. Epidemiology of Parkinson’s disease. Lancet Neurol. 2006;5:525–535. PubMed Google Scholar 15. Miller IN, Cronin-Golomb A. Gender differences in Parkinson’s disease: clinical characteristics and cognition. Mov Disord. 2010;25:2695–2703. PMC free article PubMed Google Scholar https://doi.org/10.1002/mds.23388 16. Rumayor MA, Arrieta O, Sotelo J, et al. Female gender but not cigarette smoking delays the onset of Parkinson’s disease. Clin Neurol Neurosurg. 2009;PubMed Google Scholar https://doi.org/10.1016/j.clineuro.2009.07.012 17. Gómez-Esteban JC, Zarranz JJ, Lezcano E, et al. Influence of motor symptoms upon the quality of life of patients with Parkinson’s disease. Eur Neurol. 2007;57:161–165. PubMed Google Scholar https://doi.org/10.1159/000098468 18. Pennington S, Snell K, Lee M, et al. The cause of death in idiopathic Parkinson’s disease. Parkinsonism Relat Disord. 2010;16:434–437. PubMed Google Scholar https://doi.org/10.1016/j.parkreldis.2010.04.010 19. Jankovic J, Poewe W. Therapies in Parkinson’s disease. Curr Opin Neurol. 2012; PubMed Google Scholar 20. Smith Y, Wichmann T, Factor SA, DeLong MR. Parkinson’s disease therapeutics: new developments and challenges since the introduction of levodopa. Neuropsycho pharmacology. 2012;PMC free article PubMed Google Scholar https://doi.org/10.1038/npp.2011.212 21. Simonson W, Hauser RA, Schapira AHV. Role of the pharmacist in the effective management of wearing-off in Parkinson’s disease. Ann Pharmacother.2007; PubMed Google Scholar https://doi.org/10.1345/aph.1k348 22. Van der Marck MA, Bloem BR, Borm GF, et al. Effectiveness of multidisciplinary care for Parkinson’s disease: a randomized, controlled trial. Mov Disord. 2013;PubMed Google Scholar https://doi.org/10.1002/mds.25194 23. Zhou C, Huang Y, Przedborski S. Oxidative stress in Parkinson’s disease: a mechanism of pathogenic and therapeutic significance. Ann NY Acad Sci. 2008;1147:93–104. PMC free article PubMed Google Scholar https://doi.org/10.1196/annals.1427.023 24. Logroscino G. The role of early-life environmental risk factors in Parkinson disease: what is the evidence? Environ Health Perspect. 2005; PMC free article PubMed Google Scholar https://doi.org/10.1289/ehp.7573 25. Spatola M, Wider C. Genetics of Parkinson’s disease: the yield. Parkinsonism Relat Disord. 2014;20(suppl 1):S35–S38. PubMed Google Scholar https://doi.org/10.1016/s1353-8020(13)70011-7 26. Singleton AB, Farer MJ, Bonifati V. The genetics of Parkinson’s disease: progress and therapeutic implications. Mov Disord. 2013;28:14–23. PMC free article Pu bMed Google Scholar https://doi.org/10.1002/mds.25249 27. Santiago JA, Scherzer CR, Potashkin JA. Network analysis identifies SOD2 mRNA as a potential biomarker for Parkinson’s disease. PLoS One. 2014; PMC free article PubMed Google Scholar https://doi.org/10.1371/journal.pone.0109042 28. Liu R, Guo X, Park Y, et al. Caffeine intake, smoking, and risk of Parkinson disease in men and women. Am J Epidemiol. 2012; PMC free article PubMed Google Scholar https://doi.org/10.1093/aje/kwr451 29. Benmoyal-Segal L, Soreq H. Gene–environment interactions in sporadic Parkinson’s disease. J Neurochem. 2006;97:1740–1755. PubMed Google Scholar https://doi.org/10.1111/j.1471-4159.2006.03937.x 30. Van der Merwe C, Haylett W, Harvey J, et al. Factors influencing the development of early- or late-onset Parkinson’s disease in a cohort of South African patients. S Afr Med J. 2012;102:848–851. PubMed Google Scholar https://doi.org/10.7196/samj.5879 31. Wang G, Pan J, Chen SD. Kinases and kinase signaling pathways: potential therapeutic targets in Parkinson’s disease. Prog Neurobiol. 2012; PubMed Google Scholar https://doi.org/10.1016/j.pneurobio.2012.06.003 32. Gilgun-Sherki Y, Djaldetti R, Melamed E, Offen D. Polymorphism in candidate genes: implications for the risk and treatment of idiopathic Parkinson’s disease. Pharmacogenomics J. 2004;4:291–306. PubMed Google Scholar https://doi.org/10.1038/sj.tpj.6500260 33. Agúndez JA, García-Martín E, Alonso-Navarro H, et al. Anti-Parkinson’s disease drugs and pharmacogenetic considerations. Expert Opin Drug Metab Toxicol. 2013;9:859–874. PubMed Google Scholar https://doi.org/10.1517/17425255.2013.789018 34. Marras C, Goldman SM. Genetics meets environment: evaluating gene–environment interactions in neurologic diseases. Semin Neurol. 2011;31:553–561. PubMed Google Scholar https://doi.org/10.1055/s-0031-1299793 35. Soreq L, Ben-Shaul Y, Israel Z, et al. Meta-analysis of genetic and environmental Parkinson’s disease models reveals a common role of mitochondrial protection pathways. Neurobiol Dis. 2012;45:1018–1030. PubMed Google Scholar https://doi.org/10.1016/j.nbd.2011.12.021 36. Curtin K, Fleckenstein AE, Robison RJ, et al. Methamphetamine/amphetamine abuse and risk of Parkinson’s disease in Utah: a population-based assessment. Drug Alcohol Depend. 2015;146:30–38. PMC free article PubMed Google Scholar https://doi.org/10.1016/j.drugalcdep.2014.10.027 37. Chen JJ, Swope DM. Parkinson’s disease. In: DiPiro JT, Talbert RL, Yee GC, et al., editors. Pharmacotherapy: A Pathophysiologic Approach. 9th ed. New York, New York: McGraw-Hill; 2014. Google Scholar 38. Chade AR, Kasten M, Tanner CM. Nongenetic causes of Parkinson’s disease. J Neural Transm Suppl. 2006;70:147–151. PubMed Google Scholar https://doi.org/10.1007/978-3-211-45295-0_23.
- International Journal of Innovative Research in Information Security, 09 (2): 45-49 (May 2023)1 Muhammad Kamran, Muhammad Asif, Zeeshan Ahmed, and H.B. Kekre. Ä Secure and Reliable Face Recognition Based Attendance System Using Block chain." In IEEE International Conference on Computer, Communication and Control Technology (I4CT), pp.1-5.IEEE,2021. 2 P.K.Shukla, S.K.Srivastava, and A.K.Tiwari."Deep Learning Based Face Recognition System for Attendance Management." In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp.466-470.IEEE,2021 https://doi.org/10.1109/rteict.2017.8256691 3 S.A. Hameed, Zeeshan Ahmed, and H.B. Kekre. "Privacy-Preserving Face Recognition for Attendance Systems." In IEEE International Conference on Computer, Communication and Control Technology (I4CT),pp.1-5.IEEE,2021. 4 Muhammad Asif, Zeeshan Ahmed, H.B. Kekre, and A.R. Naseer. Ä Survey of Face Recognition Techniques for Attendance System." In IEEE International Conference on Computer, Communication and Control Technology (I4CT),pp.1-5.IEEE,2020. 5 H.B.Kekre, S.R.Patil, and D.S. Dharaskar.Än Accurate and Efficient Face Recognition Based Attendance System." In IEEE International Conference on Advances in Computing, Communications and Informatics (ICACCI),pp.2265-2269.IEEE,2020. 6 E Varadharajan , R Dharani , S.Jeevitha, B Kavinmathi, S. Hemalatha “ Automatic Attendance Management system using face detection” at 2020 Department of InformationTechnology. https://doi.org/10.1109/get.2016.7916753 7 Shreyak Sawhney, Karan Kacker, Samayak Jain, Shailendra Narayan ,Rakesh Garg“Real Time Smart Attendance system using face recognition techniques “ in international conference on cloud computing data science and engineering 2019. https://doi.org/10.1109/confluence.2019.8776934.
- International Journal of Innovative Research in Information Security, 09 (2): 39-44 (May 2023)1. Gas booking system using VB software, Microcontroller and Gas Leakage Detection with SMS by Dr.D.B.Kadam,Sumedha shashikanth patil, Akshay Ananda Kumbhar, Rohit Ankush Tandle. 2. Gas Leakage Detection based on IoT using Raspberry Pi by Deepthi Miriyampalli , Ponnuri Anil Kumar , Abdul Khadir Shaik , Ravichandra Vipparla , Komalphanindra Potineni. 3. LPG Gas Leakage Detection System with GSM Module by Alan M John , Bhavesh Purbia , Ankit Sharma , Mrs. A.S Udapurkar. 4. Gas Leakage Detection Using GSM Module & Arduino with SMS Alert by Mr. Sivaprasad Lebaka, M. Ganga Rami Reddy,K. Devi Priya, N.V. Charan, N.V. Charan. 5. Gas Leakage Detection, prediction & Alert System Using Raspberry Pi & cloud computing by Pranav Mani Tripathi, Saket Kumar, Saksham Kumar, Veeresh Bhalke , Prof. Vidyashree K. 6. IoT Gas Leakage Detector and Warning Generator by Bader Farhan Alshammari , Muhammad Tajammal Chughtai. 7. J.Ding, J.Wang, N.Yuan, and Q.Pan, “The Monitoring System of Leakage Accidents in Crude Oil Pipeline based on Zigbee Technology”, IEEE Changzhou University. https://doi.org/10.1109/mace.2011.5987303.
- International Journal of Innovative Research in Information Security, 09 (2): 28-38 (May 2023)1 M. Fernando and J. Wijayanayaka, "Low cost approach for real time sign language recognition," 2013 IEEE 8th International Conference on Industrial and Information Systems, 2013, pp. 637-642, https://doi.org/10.1109/iciinfs.2013.6732059 2 M. Z. Islam, M. S. Hossain, R. ul Islam and K. Andersson, "Static Hand Gesture Recognition using Convolutional Neural Network with Data Augmentation," 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2019, pp. 324-329, https://doi.org/10.1109/iciev.2019.8858563 3 E. Kaya and T. Kumbasar, "Hand Gesture Recognition Systems with the Wearable Myo Armband," 2018 6th International Conference on Control Engineering & Information Technology (CEIT), 2018, pp. 1-6, https://doi.org/10.1109/ceit.2018.8751927 4 Lesha Bhansali and Meera Narvekar. Gesture Recognition to Make Umpire Decisions. International Journal of Computer Applications 148(14):26-29, August 2016. https://doi.org/10.5120/ijca2016911312 5 Suvarna Nandyal and Suvarna Laxmikant Kattimani 2021 J. Phys.: Conf. Ser. 2070 012148 6 Y. Madhuri, G. Anitha. and M. Anburajan., "Vision- based sign language translation device," 2013 International Conference on Information Communication and Embedded Systems (ICICES), 2013, pp. 565-568, https://doi.org/10.1109/icices.2013.6508395 7 Nusirwan Anwar bin Abdul Rahman, Kit Chong Wei and John See Faculty of Information Technology, Multimedia University. 8 Moin, A., Zhou, A., Rahimi, A. et al. A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition. Nat Electron 4, 54–63 (2021). https://doi.org/10.1038/s41928-020-00510-8 9 Ravi, H. Venugopal, S. Paul and H. R. Tizhoosh, Ä Dataset and Preliminary Results for Umpire Pose Detection Using SVM Classification of Deep Features," 2018 IEEE SymposiumSeries on Computational Intelligence (SSCI), 2018, pp. 1396-1402, https://doi.org/10.1109/ssci.2018.8628877 10 M. A. Shahjalal, Z. Ahmad, R. Rayan and L. Alam, Än approach to automate the scorecard in cricket with computer vision and machine learning," 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), 2017, pp. 1-6, https://doi.org/10.1109/eict.2017.8275204.
- International Journal of Innovative Research in Information Security, 09 (2): 21-27 (May 2023)1. Currency Recognition system using Image Processing. SANDEEP KUMAR CHAUBEY Andrew S. Morgan Kaufmann Publishers, 1995. 2. A Survey on Indian Currency Note Denomination Recognition System. Aruna Manpreet Bagga, Dr.Baljit Singh. 1995. 3. Dr. Baljith Singh, Aruna D H Indian currency note denomination system. 4. Ms. Monali Patil, Prof. Jayant Adhikari Detection of fake currency using digital image processing. 5. Arun Anoop M, Dr K.E. Kannammal Fake currency detection 6. Vidhi Roy and Sushanth Patil Fake Currency detection using image processing. 7. M. Deborah and Soniya Prathap Detection of Fake currency using edge detection. 8. Akash Rana, Avinash Kumar and Shivam Kumar Jha Detection of fake currency using machine learning technique. 9. Mayadevi, A. Gaikwad, Vaijinath, V. Bhosle and Vaibhav Currency note feature extraction. 10. Brinda M Object Detection using Haar-Like Feature Extraction..
- International Journal of Innovative Research in Information Security, 9 (2): 15-20 (May 2023)1 D. Pavithra; Ranjith Balakrishnan, “IOT based monitoring and control system for home automation”, IEEE Explore, Communication Technologies (GCCT). https://doi.org/10.1109/gcct.2015.7342646 2 Dr. M. Suresh, A. Amulya, M. Hari Chandana, P. Amani, T. Lakshmi Prakasam. “Anti theft flooring system using raspberry pi using” in Compliance Engineering journal, vol 12, no. 7, pp. 306 – 317, 2021. 3 Sonali Das, Dr. Neelanarayan, “ IOT Based Anti Theft Flooring System” in IJESC , vol 10, no.4, pp. 25463-25466,2020. 4 Siddalingesha G.R, H. M. Shamita, “IOT Based Anti Theft System for home” in IRJET, vol 8, no. 10, pp. 509 – 513, 2021. 5 Sanjana Kute, Ruthvik Pimpalkar, Shivajirao S, “Theft Detection System” in IRE Journals, vol 4, no 10, 2456 – 2462, 2021. 6 Gaurav Sable, Gaurav Sharma, Manish Bhalerao, Yash Ramugade, “IOT Based Theft Detection using Raspberry Pi” in IJIRT, vol 11, no 12, 2356 – 2360, 2022. 7 Mohd Musab, Ms. Seema Kaloria, Ankit Chhipa, Anand Sharma, Fardeen Mansoori, “IOT Based Anti-Theft Security System” in IJRTI, vol 7, no 6, pp. 106 – 109, 2022. 8 Santosh Mahale, Shivam Gujrathi, Pratik Bramhecha, Kalyani Bedarkar, Rohini Shinde, Yashraj Patil, “Anti-Theft Detection System” in IJIRSET, vol 9, no 4, pp. 1889 – 1895, 2020. 9 Sharnil Pandya, Hemant Ghayvat, Ketan Kotecha, Mohammed Awais, Saeed Akbarzadeh, Prosanta Gope , Subhas Chandra Mukhopadhyay and Wei Chen, “Smart Home Anti-Theft System” in applied system innovation, vol 1, no 42, pp. 1-22, 2018 https://doi.org/10.3390/asi1040042 10 Mr. Vikrant A. Agaskar, “ IOT BASED IOT Based Theft Detection” in IJCRT, vol 6, no 2, pp. 231 – 234, 2018..
- International Journal of Innovative Research in Information Security, 9 (2): 10-14 (May 2023)1. Adler, A.; Schuckers, S. Biometric vulnerabilities, overview. In Encyclopedia of Biometrics; Li, S.Z., Jain, A., Eds.; Springer: Boston, MA, USA, 2009. https://doi.org/10.1007/978-0-387-73003-5_65 2. Nguyen, H.T. Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms 2019, 12, 241. https://doi.org/10.3390/a12110241 3. Biometric Systems Lab—FVC2000: Fingerprint Verification Competition. Available online: FVC2000 (unibo.it)(accessed on 22 January 2021). 4. Tang, Y.; Gao, F.; Feng, J. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics, Denver, CO, USA, 1–4 October 2017; pp. 117–123. https://doi.org/10.1109/btas.2017.8272689 5. Huang, X.; Qian, P.; Liu, M. Latent fingerprint image enhancement based on progressive generative adversarial network. In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA, 14–19 June 2020; pp. 3481–3489. https://doi.org/10.1109/cvprw50498.2020.00408 6. Neurotechnology Company—Sample Fingerprint Databases. Available online: Download biometric algorithm demo software, SDK trials, product brochures. (neurotechnology.com)(accessed on 22 January 2021). 7. Fingerprint Image identification for crime detection (2019) Fingerprint Image Identification for Crime Detection | IEEE Conference Publication | IEEE Xplore https://doi.org/10.1109/iccsp.2019.8698014.
- International Journal of Innovative Research in Information Security, 9 (2): 07-09 (May 2023)1 Iqra Nissar; Waseem Ahmad Mir; Izharuddin; Tawseef Ayoub Shaikh.” Machine Learning Approaches for Detection and Diagnosis of Parkinson’s Disease”. 2021 IEEE. https://doi.org/10.1109/icaccs51430.2021.9441885 2 Pooja Raundale; Chetan Thosar; Shardul Rane.” Prediction of Parkinson’s disease and severity of the disease using Machine Learning and Deep Learning algorithm”.2021 IEEE. https://doi.org/10.1109/incet51464.2021.9456292 3 Son V T Dao “An Analysis of Vocal Features for Parkinson’s Disease Classification Using Evolutionary Algorithms” 2022. 4 Mohammed S Islam “Parkinson’s Disease Prediction Using Machine Learning” 2020..
- International Journal of Innovative Research in Information Security, 10 (01): 01-06 (April 2023)1. A.Sairohan, Dr.K.V.Ranga Rao, V.Sridhar “Smart gloves for real time applications,” vol. 11, pp. (2021). 2. Girish Gajanan Mulye “Advance Glove for Blind,” IJSR, vol. pp (2020). 3. Somashekar V, Manohar R, Ashwini M S, Praveen V, Sushmitha M “Smart glove for blind using TensorFlow,” IRJET, vol. 7, pp. (2020) 4. Arsh.A.Ghate, Vishal.G.Chavan “Smart gloves for blind,” IRJET, vol. 4, pp. (2017). 5. Hiranya Peiris, Charitha Kulasekara, HashanWijesinghe, Basiru Kothalawala, Namalie Walgampaya, Dharshana Kasthurirathna “Eye Vista: An assistive wearable device for visually impaired sprint athletes,” IEEE vol* pp.,(2016).
- International Journal of Innovative Research in Information Security, 7 (9): 99-104 (October 2020)1. Frase, H.S.F., et.al., “Comparing complex diagnoses a formative evolution of the heart disease program”, MIT Lab for Computer Science, Cambridge, MA(2001) 2. Salem, A.M. Raushdy, M and HodHod, R.A., “ A rule based expert system for diagnosis of Heart disease”, 8th International conference on soft Computing MENDEL, Brno, Czech Republic, June 5-7, PP 258-263(2002). 3. Shaikh Abdul Hannan, V. D. Bhagile, R. R. Manza, R. J. Ramteke, "Development of an Expert System for Diagnosis and appropriate Medical Prescription of Heart Disease Using Support Vector Machine and Radial Basis Function", International Journal of Computer Science and Information Security, (IJCSIS) August issue (Vol. 8 No. 5), 2010, Pages/record No.: 245-254. ISSN: 19475500. 4. I. Turkoglu, A. Arslan, E. Ilkay, “An expert system for diagnosis ofhe heart valve diseases”, Expert Systems with Applications vol.23,pp. 229–236, 2002. 5. Shaikh Abdul Hannan, A.V. Mane, R. R. Manza and R. J. Ramteke, “Prediction of Heart Disease Medical Prescription Using Radial Basis Function", IEEE International Conference on Computational Intelligence and Computing Research at Tamilnadu College of Engineering, Coimbatore, Tamilnadu, India, ICCIC-2010, December 28-29, 2010. 6. Mrs. Bharati M. Ramageri, “Data Mining Techniques And Applications”,Bharati M. Ramageri / Indian Journal of Computer Science and Engineering Vol. 1 No. 4 pp 301-305. 7. Shaikh Abdul Hannan, R. R. Manza and R.J. Ramteke, “Association Rules for Filtering The Medicine To Avoid Side Effects Of Heart Patients”, on 16 -19 Dec 2009, at Advances in Computer Vision and Information Technology – 09, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. 8. Rajeswari K, Vaithiyanathan V, P. Amirtharaj “Application of Decision Tree Classifiers in Diagnosing Heart Disease using Demographic Data” American Journal of Scientific research ISSN 2301-2005 pp. 77-82 EuroJournals Publishing, 2012. 9. Shaikh Abdul Hannan, Jameel Ahmed, Naveed Ahmed, Rizwan Alam Thakur, “Data Mining and Natural Language Processing Methods for Extracting Opinions from Customer Reviews”, International Journal of Computational Intelligence and Information Security, pp 52-58, Vol. 3, No. 6, July 2012. ( ISSN: 1837-7823). 10. Haque ME, Sudhakar KV. ANN back propagation prediction model for fracture toughness in microalloy steel. Int J Fatique 2002;24:1003–10. 11. Shaikh Abdul Hannan, "Heart Disease Diagnosis by using FFBP and GRNN algorithm of Neural Network", International Journal of Computer Science and Information Security, Vol 12, Number 6, June 2014, ISSN 1945-5500, United States of America. 12. Celikoglu HB. Application of radial basis function and eneralized regression neural networks in non-linear utility function specification for travel mode choice modelling. Math Comput Model 2006;44:640–58. 13. Mohammad Eid Alzaharani, Shaikh Abdul Hannan, “Diagnosis and Medical Prescription of Heart Disease Using FFBP, SVM and RBF”, Issue,1, Vol 5, , KKU Journal of Basic and Applied Sciences, Mar 2019 , Page 6-15. 14. Santosh Maher, Shaikh Abdul Hannan, Sumegh Tharewal, K. V. Kale " HRV based Human Heart Disease Prediction and Classification using Machine Learning " December 2019, (Vol. 17 No. 2 International Journal of Computer Science and Application (IJCA), New York, USA. 15. Kusuma.S1, Divya Udayan, “Machine Learning and Deep Learning Methods in Heart Disease (HD) Research, International Journal of Pure and Applied Mathematics, Volume 119 No. 18 2018, 1483-1496, ISSN: 1314-3395 (on-line version)url:http://www.acadpubl.eu/hub/Special Issue. 16. Akram Ablsubari, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, Rakesh Ramteke, "Composite Feature Extraction and Classification for Fusion of Palmprint and Iris Biometric Traits", Engineering Technology and Applied Science Research, (ETASR) Volume 9, No 1, Feb 2019, ISSN: 2241-4487, Greece. 17. Santosh K. Maher, Sumegh Tharewal, Abdul Hannan, “Review on HRV based Prediction and Detection of Heart Disease”, International Journal of Computer Applications (0975 – 8887), Pag 7-12, Volume 179 – No.46, June 2018. 18. Yogesh Rajput, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, D. Patil Ramesh Manza, Design and Development of New Algorithm for person identification Based on Iris statistical features and Retinal blood Vessels Bifurcation points” ” International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R), December 21-22, 2018, India. 19. Yogesh, Abdul Hannan, Rahul Sagar, Kishor Jave, Identification and Counting Trees from Oil Palm Plantations Using Digital Image Processing Techniques, International Journal of Engineering Research & Technology (IJERT), Vol. 6 Issue 05, May – 2017, ISSN: 2278-0181. 20. C.Sowmiya, Dr.P.Sumitra, “Analytical Study of Heart Disease Diagnosis Using Classification Techniques” 2017 IEEE International Conference On Intelligent Techniques In Control, Optimization And Signal Processing, 978-1-5090-4778-9/17/$31.00 ©2017 IEEE. 21. Santosh K. Maher, Sumegh Tharewal, Abdul Hannan, K. V. Kale “Review on HRV based Prediction and Detection of Heart Disease” International Journal of Computer Application(IJCA), Vol. 179, Number 46, June 2018, ISSN 0975-8887, USA. 22. Rifki Wijaya, Ary Setijadi Prihatmanto,et.al “Preliminary Design of Estimation Heart disease by using machine learning ANN within one year” , 2013 Joint International Conference on Rural Information & Communication Technology and Electric-Vehicle Technology (rICT & ICeV-T) November 26-28, 2013, Bandung-Bali, Indonesia, 978-1-4799-3365-5/13/$31.00 ©2013 IEEE. 23. Yogesh, Abdul Hannan, Rahul Sagar, Kishor Jave, Identification and Counting Trees from Oil Palm Plantations Using Digital Image Processing Techniques, International Journal of Engineering Research & Technology (IJERT), Vol. 6 Issue 05, May – 2017, ISSN: 2278-0181. 24. Mahammed Waseem, Naushad Ahmed Osmani, Shaikh Abdul Hannan, “A Survey on E-education of information and Communication ‘Technology”, European Journal of Computer Science and Information Technology (EJCSIT), Vol. 4, Issue 6, ISSN 2054-0965, October 2016. 25. H. Uguz, A. Arslan, I. Turkoglu, Ä biomedical system based on hidden Markov model for diagnosis of the heart valve diseases", Pattern Recognition Letters vol.28 pp.395–404, (2007). 26. Mr.Deepak.C.Dhanwani,et.al.,"Survey on Various Techniques of Brain Tumor Detection from MRIImages", International Journal of Computational Engineering Research Vol, 04,Issue, 1,January-2014. 27. Shaikh Abdul Hannan, Bharatratna P. Gaikwad, Ramesh Manza, "Brain Tumor from MRI Images : A Review". International Journal of Scientific and Engineering Research (IJSER), Volume 5, Issue 4, April-2014 ISSN 2229-5518, France. 28. Aqueel Ahmed, Shaikh Abdul Hannan, “Data Mining Techniques to Find Out Heart Diseases: An Overview”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), An ISO 9001:2008 Certified International Journal, Volume-1, Issue-4, September 2012, ISSN: 2278-3075, New Delhi, India. 29. M. J. Baheti, A. V. Mane, Shaikh Abdul Hannan, K. V. Kale, “Comparison of PCA and SVM for a west Indian Script- Gujarati”, CiiT Journal of Digital Image Processing, Vol. 3. No. 11, pp. 709-715, July 2011. 30. Karaolis, M.A. Moutiris, J.A. Hadjipanayi, D. Pattichis, C.S., “Assessment of the Risk Factors of Coronary Heart Events Based on Data Mining With Decision Trees” IEEE Transactions on Information Technology in Biomedicine, pp 559 -566, May 2010. 31. Nikhil Gawande , Alka Barhatte , Heart Diseases Classification using Convolutional Neural Network, Proceedings of the 2nd International Conference on Communication and Electronics Systems (ICCES), IEEE, 2017. 32. Mir Arif Ali, Shaikh Abdul Hannan, Ä Review on Modern and Classical Encryption Techniques", International Journal of Engineering Trends and Technology, Volume 12, Number 4, June 2014, ISSN 2231-5381, India. 33. Aufzalina Mohd Yusof, Nor Azura Md. Ghani, Khairul Asri Mohd Ghani, Khairul Izan Mohd Ghani, A predictive model for prediction of heart surgery procedure, Indonesian Journal of Electrical Engineering and Computer Science Vol. 15, No. 3, September 2019. 34. Amin Ul Haq, Jian Ping Li, Muhammad Hammad Memon, Shah Nazir, Ruinan Sun, A Hybrid Intelligent System Framework for the Prediction of Heart Disease Using Machine Learning Algorithms, Hindawi Mobile Information Systems Volume 2018. 35. X. Li, J. Chen, G. Zhao and M. Pietikainen, “Remote Heart Rate Measurement from Face Videos under Realistic Situations”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 4264- 4271, 2014. 36. Shaikh Abdul Hannan, A.V. Mane, R. R. Manza and R. J. Ramteke, “Prediction of Heart Disease Medical Prescription Using Radial Basis Function", IEEE International Conference on Computational Intelligence and Computing Research at Tamilnadu College of Engineering, Coimbatore, Tamilnadu, India, ICCIC-2010, December 28-29, 2010. 37. Y. Pei, S. Zhao, X. Yang, J. Cao and Y. Gong, “Design Optimization of a SRM Motor by a Nature-Inspired Algorithm: Multi-Verse Optimizer”, Proceedings of IEEE International Conference on Industrial Electronics and Applications, pp. 1870-1875, 2018. 38. Shaikh Abdul Hannan, V.D. Bhagile, R. R. Manza and R.J. Ramteke, “Expert System for Diagnosis and Appropriate Medical Prescription of Heart Disease Using Radial Basis Function”, CiiT International Journal of Artificial Intelligent Systems and Machine Learning, Vol 2, No 8 (2010), pp 184-193, ISSN 0974–9667. 39. Durairaj M, Revathi V, “Prediction Of Heart Disease Using Back Propagation MLP Algorithm”, International Journal of Scientific and Technology Research, Volume 4, Issue 8, August 2015..
- International Journal of Innovative Research in Information Security, 8 (3): 27-33 (August 2021)1. Abdulkadir Sengur, “An expert system based on linear Discriminant analysis and adaptive neuro-fuzzy inference system to diagnosis heart valve diseases”, ELSEVIER, Expert Systems with Applications 35, 214-222, 12 June 2007. 2. Jain Yu, “General C-Means Clustering Model”, IEEE Transactions On Pattern Analysis And Machine Intelugence, VOL. 27, NO. 8, August 2005. 3. Meyer-Baese, O. Lange, A. wismueller, and M. K. Hurdal, “Analysis of Dynamic Susceptibility constrast MRI Time Series Based on Unsupervised Clustering Methods”, IEEE Transactions on Information Technology in Biomedicine, VOL. 11, NO. 5, September 2007. 4. Shaikh Abdul Hannan, "Heart Disease Diagnosis by using FFBP and GRNN algorithm of Neural Network", International Journal of Computer Science and Information Security, Vol 12, Number 6, June 2014, ISSN 1945-5500, United States of America. 5. Fraser, H.S.F., et al., “Differential diagnoses of the heart disease program have better sensitivity than Resident Physicians”, Tufts-New England Medical Center, Boston, MA(2001). 6. Mohammad Eid Alzaharani, Shaikh Abdul Hannan, “Diagnosis and Medical Prescription of Heart Disease Using FFBP, SVM and RBF”, Issue,1, Vol 5, , KKU Journal of Basic and Applied Sciences, Mar 2019 , Page 6-15. 7. Frawley and Piatetsky-Shapiro, 1996. Knowledge Discovery in Databases: An Overview. The AAAI/MIT Press, Menlo Park, C.A. 8. Aqueel Ahmed, Shaikh Abdul Hannan, “Data Mining Techniques to Find Out Heart Diseases: An Overview”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), An ISO 9001:2008 Certified International Journal, Volume-1, Issue-4, September 2012, ISSN: 2278-3075, New Delhi, India. 9. I. Turkoglu, A. Arslan, E. Ilkay, “An expert system for diagnosis of the heart valve diseases”, Expert Systems with Applications vol.23, pp. 229–236, 2002. 10. I. Turkoglu, A. Arslan, E. Ilkay, “An intelligent system for diagnosis of heart valve diseases with wavelet packet neural networks”, Computer in Biology and Medicine vol.33 pp.319–331, 2003. 11. Haque ME, Sudhakar KV. ANN back propagation prediction model for fracture toughness in microalloy steel. Int J Fatique 2002;24:1003–10. 12. Shaikh Abdul Hannan, A.V. Mane, R. R. Manza and R. J. Ramteke, “Prediction of Heart Disease Medical Prescription Using Radial Basis Function", IEEE International Conference on Computational Intelligence and Computing Research at Tamilnadu College of Engineering, Coimbatore, Tamilnadu, India, ICCIC-2010, December 28-29, 2010. 13. P.I.J. Keeton, F.S. Schlindwein, Application of Wavelets in Doppler Ultrasound, vol. 17, number 1, MCB University Press, 1997, pp. 38–45. 14. I.A. Wright, N.A.J. Gough, F. Rakebrandt, M. Wahab, J.P. Woodcock, Neural network analysis of Doppler ultrasound blood low signals: a pilot study, Ultrasound in Medicine & Biology 23 (5) (1997) 683–690. 15. I. Guler, M.K. Kiymik, S. Kara, M.E. Yuksel, Application of autoregressive analysis to 20 MHz pulsed Doppler data in real time, International Journal Biomedical Computing 31 (3–4) (1992) 247–256. 16. Shaikh Abdul Hannan, "Heart Disease Diagnosis by using FFBP and GRNN algorithm of Neural Network", International Journal of Computer Science and Information Security, Vol 12, Number 6, June 2014, ISSN 1945-5500, United States of America. 17. Santosh K. Maher, Sumegh Tharewal, Abdul Hannan, “Review on HRV based Prediction and Detection of Heart Disease”, International Journal of Computer Applications (0975 – 8887), Pag 7-12, Volume 179 – No.46, June 2018. 18. https://www.who.int/en/news-room/fact sheets/detail/cardiovascular-diseases-(cvds) https://www.mayoclinic.org/diseases-conditions/stroke/symptoms-causes/syc-20350113. 19. Shaikh Abdul Hannan, “An Overview of Big Data and Hadoop”, International Journal of Computer Application”, Volume 154, Number 10, ISSN – 0975-887, November 2016, New York, USA. 20. Santosh Maher, Shaikh Abdul Hannan, Sumegh Tharewal, K. V. Kale " HRV based Human Heart Disease Prediction and Classification using Machine Learning " December 2019, (Vol. 17 No. 2 International Journal of Computer Science and Information SecApplicatiion (IJCA), New York, USA. 21. Akram Ablsubari, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, Rakesh Ramteke, "Composite Feature Extraction and Classification for Fusion of Palmprint and Iris Biometric Traits", Engineering Technology and Applied Science Research, (ETASR) Volume 9, No 1, Feb 2019, ISSN: 2241-4487, Greece. 22. Yogesh Rajput, Shaikh Abdul Hannan, Mohammed Eid Alzaharani, D. Patil Ramesh Manza, Design and Development of New Algorithm for person identification Based on Iris statistical features and Retinal blood Vessels Bifurcation points” ” International Conference on Recent Trends in Image Processing & Pattern Recognition (RTIP2R), December 21-22, 2018, India. 23. Yogesh Rajput, Shaikh Abdul Hannan, “Design New Wavelet Filter for Detection and Grading of Non-proliferative Diabetic Retinopathy Lesions”, International Conference on Recent Trends in Image Processing and Pattern Recognition, Jan 2020, Springer, Singpore. 24. Y. M. Rajput, A. H. Hannan, M. E. Alzahrani, R. R. Manza, D. D. Patil, “EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques–A Review”, International Journal of Computer Sciences and Engineering, Vol 6, Issue 9, Sep 2018. 25. Shaikh Abdul Hannan, Bharatratna P. Gaikwad, Ramesh Manza, "Brain Tumor from MRI Images : A Review". International Journal of Scientific and Engineering Research (IJSER), Volume 5, Issue 4, April-2014 ISSN 2229-5518, France. 26. Eliane Rich and KevinKnight – Artificial Intelligence – Secone Edition Mcgraw Hill , 1983. 27. Long, W., et.al., “Developing a program for Tracking Heart Failure”, MIT Lab for Computer Science, Cambridge, MA(2001). 28. Frase, H.S.F., et.al., “Comparing complex diagnoses a formative evalution of the heart disease program”, MIT Lab for Computer Science, Cambridge, MA(2001) 29. Shaikh Abdul Hannan, A.V. Mane, R. R. Manza and R. J. Ramteke, “Prediction of Heart Disease Medical Prescription Using Radial Basis Function", IEEE International Conference on Computational Intelligence and Computing Research at Tamilnadu College of Engineering, Coimbatore, Tamilnadu, India, ICCIC-2010, December 28-29, 2010. 30. J. Galindo, P. Tamayo, Credit risk assessment using statistical and machine learning: basic methodology and risk modeling applications, Computational Economics 15 (1 – 2) (2000) 107–143 31. V. Vapnik, The Nature of Statistical Learning Theory, Springer- Verlag, New York, 1995. 32. M.A. Hearst, S.T. Dumais, E. Osman, J. Platt, B. Scho¨lkopf, Support vector machines, IEEE Intelligent Systems 13 (4) (1998) 18– 28. 33. Broomhead D., & Lowe, D., Multivariable functional interpolation and adaptive networks. Complex Systems, vol.2, pp.321-355, 1988. 34. Haralambos Sarimveis, Philip Doganis, Alex Alexandridis, “A classification technique based on radial basis function neural networks”, Advances in Engineering Software vol.37, pp.218–221, 2006. 35. Shaikh Abdul Hannan, Pravin Yannawar, R.R. Manza and R.J. Ramteke, “Expert System Data Collection Technique for Heart Disease” , in IT & Business Intelligence, on 06-08 Nov 2009, Organised By IMT, Nagpur, India. 36. Haralambos Sarimveis, Philip Doganis, Alex Alexandridis, “A classification technique based on radial basis function neural networks”, Advances in Engineering Software vol.37, pp.218–221, 2006. 37. Chauvin in, Y and D.E. Ruumehart Backpropagation : Theory, Architechtures and Applications, Erbaum Mahwah, NJ, ISBN : 080581258. PP 561, 1995. 38. Shaikh Abdul Hannan, V. D. Bhagile, R.R. Manza, R. J. Ramteke, “Heart Disease Diagnosis By Using FFBP algorithm of Artificial Neural Network”, International Conference on Communication, Computation, Control and Nanotechnology, ICN-2010 Organized by Rural Engineering College Bhalki-585328, during October 29-30, 2010. 39. Cigizoglu HK, Alp M. Generalized regression neural network in modelling river sediment yield. Adv Eng Software 2005;37:63–8. 40. Kim B, Lee DW, Parka KY, Choi SR, Choi S. Prediction of plasma etching using a randomized generalized regression neural network. Vacuum 2004;76:37–43 41. Jang JSR, Sun CT, Mizutani E. Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, Upper Saddle River, New Jersey, USA; 1997 Chapter 9. 42. Shaikh Abdul Hannan, R. R. Manza and R.J. Ramteke, “Association Rules for Filtering The Medicine To Avoid Side Effects Of Heart Patients”, on 16 -19 Dec 2009, at Advances in Computer Vision and Information Technology – 09, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. 43. Anupriya Kamble, Abdul Hannan, Yogesh, Dnyaneshwari, “Association detection of Regular Insulin and NPH Insulin Using Statistical Features”, Second International Conference on Cognitive Knowledge Engineering, 21-23 December 2016 (ICKE-2016), Aurangabad, Maharashtra, India, pp 59-62, ISBN 978-93-80876-89-4. 44. Shaikh Abdul Hannan, Pravin Yannawar, R. R. Manza and R.J. Ramteke, “Data Mining Technique for Detection of Cardiac Problems Using Symptoms Medicine and Its Side effects”, in IT & Business Intelligence -09 , in IT & Business Intelligence, on 06-08 Nov 2009, Organized By IMT, Nagpur, India. 45. Shaikh Abdul Hannan, Jameel Ahmed, Naveed Ahmed, Rizwan Alam Thakur, “Data Mining and Natural Language Processing Methods for Extracting Opinions from Customer Reviews”, International Journal of Computational Intelligence and Information Security, pp 52-58, Vol. 3, No. 6, July 2012. ( ISSN: 1837-7823). 46. Ordonez C,” Association rule discovery with the train and test approach for heart disease prediction”, IEEE Transactions on Information Technology in Biomedicine, P(334 – 343), April 2006 47. Aqueel Ahmed, Shaikh Abdul Hannan, “Data Mining Techniques to Find Out Heart Diseases: An Overview”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), An ISO 9001:2008 Certified International Journal, Volume-1, Issue-4, September 2012, ISSN: 2278-3075, New Delhi, India. 48. AbuKhousa, E “Predictive data mining to support clinical decisions: An overview of heart disease prediction systems”, IEEE Transaction on Innovations in Information Technology (IIT), pp(267 - 272) March 2012..
- International Journal of Innovative Research in Information Security, VIII (II): 06-09 (July 2021)1. Door Unlock using Face Recognition (Abdul Azeem, Sathuluri Mallikarjun Rao,Kandula Rama Rao, Shaik Akbar Basha, Harsha Pedarla, Modela Gopi) 2. Facial Recognition Enabled Smart Door Using Microsoft Face API (Karan Maheshwari , Nalini N) 3 Automated door access control system using face recognition (Tejas Saraf, Ketan Shukla, Harish Balkhande, Ajinkya Deshmukh) 3. Facial recognition enabled smart door unlock system(M Vamsi Krishna, A Bhargav Reddy, V Sandeep) 4. Smart Door with Face UnlockApache2.0 (https://create.arduino.cc) (Divins Mathew) 5. Makers Pro Projects(Simple Door Lock Using Face recognition Solenoid Lock)(Muhammad Aqib).
- 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..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue IX): 89-98 (October 2020)1. Andrea Zanella, Lorenzo Vangelista, Nicola Bui, Angelo Castellani, Michele Zorzi ―”Internet of Things for Smart Cities”, IEEE INTERNET OF THINGS JOURNAL, VOL. 1, NO. 1, FEBRUARY 2014 2. Salha M. Alzahrani ―”Sensing for the Internet of Things and Its Applications”, 978-1-5386-3281-9/17 $31.00 © 2017 IEEE DOI 10.1109/W-FiCloud.2017.33 3. H.Schaffers, N.Komninos, M.Pallot, B.Trousse, M.Nilsson, A.Oliveira, “Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation”, The Future Internet, Lecture Notes in Computer Science Volume 6656, pp. 431-446, 2011. 4. D.Cuff, M.Hansen, and J.Kang, “Urban sensing: out of the woods.” Communications of the ACM vol. 51, no. 3, pp. 24-33, Mar. 2008. 5. H.Arasteh, V.Hosseinnezhad, V.Loia, A.Tommasetti, O.Troisi, M.Shafie-khah, P. Siano ”Iot-based Smart Cities: a Survey”, 978-1-5090-2320-2/16/$31.00 ©2016 IEEE. 6. Arun Kumar Rana , Ram krishna , Sachin Dhwan3, Dr. Sharad Sharma, Dr. Rashmi Gupta ”Review on Artificial Intelligence with Internet of Things - Problems, Challenges and Opportunities”,978-1-7281-1793-5/19/$31.00 ©2019 IEEE 7. Husam Rajab, Tibor Cinkelr ” IoT based Smart Cities”, 978-1-5386-3779-1/18/$31.00 ©2018 IEEE. 8. B.Hammi, R.Khatoun, S.Zeadally, A.Fayad and L.Khoukhi, "IoT technologies for smart cities," in IET Networks, vol. 7, no. 1, pp. 1-13, 1 2018. 9. D.El-Baz and J.Bourgeois,“Smart cities in Europe and the alma logistics project,” ZTE Commun., vol. 13, no. 4, pp. 10–15, 2015 10. H.Arasteh, V.Hosseinnezhad, V.Loia, A.Tommasetti, O.Troisi, M.Shafie-khah, P.Siano” Iot-based Smart Cities: a Survey” , 978-1-5090-2320-2/16/$31.00 ©2016 IEEE 11. M.M.Rathore, A.Ahmad, A.Paul, S.Rho, “Urban planning and building smart cities based on the internet of things using big data analytics,” Comput. Netw., 2016, DOI: 10.1016/j.comnet.2015.12.023 12. N.Neyestani, M.Y.Damavandi, M.Shafie-khah and J.P.S.Catalão ― “Modeling the PEV traffic pattern in an urban environment with parking lots and charging stations,” PowerTech, 2015 IEEE Eindhoven, Eindhoven, 2015, pp. 1-6. 13. M.Yazdani-Damavandi, M.P.Moghaddam, M.R.Haghifam, M.Shafie-khah, J.P.S.Catalão, "Modeling Operational Behavior of Plug-in Electric Vehicles’ Parking Lot in Multienergy Systems," IEEE Trans. Smart Grid, vol. 7, pp. 124-135, 2016. 14. N.Neyestani, M.Y.Damavandi, M.Shafie-Khah, J.Contreras, and J.P.S.Catalão, Ällocation of plug-in vehicles' parking lots in distribution systems considering network-constrained objectives," IEEE Trans. Power Syst., vol. 30, pp. 2643-2656, 2015. 15. M.Shafie-khah, E.Heydarian-Forushani, M.E.H.Golshan, P. Siano, M.P. Moghaddam, M.K. Sheikh-El-Eslami, and J.P.S. Catalão, “Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability,” Appl. Energy, Volume 162, 15 January 2016, Pages 601-612 16. A.K.Evangelos, D.T.Nikolaos, and C.B.Anthony, “Integrating RFIDs and smart objects into a Unified Internet of Things architecture,” Advances in Internet of Things, vol. 1, pp. 5-12, 2011. 17. J.Gubbi, R.Buyya, S.Marusic, and M.Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions,” Future Gener. Comput. Syst., vol. 29, pp. 1645–1660, 2013. 18. A.Botta, W.de Donato, V.Persico, and A.Pescapé, ― “Integration of cloud computing and internet of things: a survey”, Future Gener. Comput. Syst., vol. 56, pp. 684–700, 2016. 19. R.Fielding,―“Representational state transfer,” Architectural Styles and the Design of Network-based Software Architecture, pp.76-85,2000. 20. A.P.Castellani, N.Bui, P.Casari, M.Rossi, Z.Shelby and M.Zorzi ― “Architecture and protocols for the Internet of Things: A case study,” 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 678–683, 2010 21. Z. Shelby, K. Hartke, C. Bormann, and B. Frank.―“Constrained Application Protocol (CoAP).” draft-ietf-core-coap-18. s.l. : IETF, 2013. 22. A.Castellani, S.Loreto, A.Rahman, T.Fossati and E.Dijk.―“Best Practices for HTTP-CoAP Mapping Implementation.” draft-castellanicore-http-mapping-07. s.l. : IETF, 2013..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue IX): 81-86 (September 2020)1. Noor, Sanjeevikumar Padmanaban , Lucian Mihet-Popa , Mohammad Nurunnabi Mollah and Eklas Hossain, “Components, Technologies, Challenges, Impacts, and Future Direction of Development”, Khulna University of Engineering and Technology, Khulna 9203, Bangladesh. 2. Mattia Ricco, et. al., “A Capacitor Voltage Balancing Approach Based on Mapping Strategy for MMC Applications” at University of Bologna, 40136 Bologna, 2019. 3. Miguel Moranchel, Francisco Huerta, Inés Sanz, Emilio Bueno and Francisco J. Rodríguez, “A Comparison of Modulation Techniques for Modular Multilevel Converters”, Universidad de Alcalá, Escuela Politécnica, 28805 Alcalá de Henares, Spain, 2016. 4. Xiaojie Shi, Zhiqiang Wang, Leon M. Tolbert and Fred Wang Center for Ultra-wide-area Resilient Electric Energy Transmission Networks (CURENT) “A Comparison of Phase Disposition and Phase Shift PWM Strategies for Modular Multilevel Converters” The University of Tennessee Knoxville, TN 37996-2250, USA-2013 5. Binbin Li, Shaoze Zhou, and Dianguo Xu, Stephen J. Finney, and Barry W. Williams “A Hybrid Modular Multilevel Converter for Medium-Voltage Variable-Speed Motor Drives” National Natural Science Foundation of China (51237002) and (51477034). 6. Mahran Quraan, Pietro Tricoli, Salvatore D’Arco, and Luigi Piegari, Senior,“Efficiency Assessment of Modular Multilevel Converters for Battery Electric Vehicles” University of Birmingham, Birmingham, March 2017. 7. Meiqin Mao , , Yong Ding, Liuchen Chang, Nikos D. Hatziargyriou, Fellow, Qiang Chen, Tinghuan Tao, and Yunwei Li, “Multi-Objective Power Management for EV Fleet With MMC-Based Integration Into Smart Grid” Ieee Transactions On Smart Grid, Vol. 10, No. 2, March 2019 8. Jahangeer Soomro, et. al., Comparative Analysis of Modular Multilevel Converter with Cascaded H Bridge Inverter using Five, Seven and Nine levels” International Journal of Recent Technology and Engineering, Vol. 7, Iss. 5S4, 2019 9. Elena Vergori ID, Francesco Mocera ID and Aurelio Somà ,I”Battery Modelling and Simulation Using a Programmable Testing Equipment”, 2018. 10. Yi Wang, et. al., “Nearest Level PWM Method for the MMC in DC Distribution Grids” North China Electric Power University, Baoding 071003, China. 11. Zhan Ma , Feng Gao , Xin Gu , Nan Li , Decun Niu “An Online SOH Testing Method of MMC Battery Energy Storage System” Jinan, China -2018. 12. Amrutvahini College of Engineering, Sangamner, India2,”Chandrakant Rahane, Vaibhav Varpe “Design and fabrication of regenerative braking system”, 2018. 13. Mattia Ricco, et. al., “FPGA-Based Implementation of MMC Control Based on Sorting Networks” at Cergy-Pontoise University, 95031 Cergy Pontoise, France; 2018. 14. Pratik Bhandari, et. al., Regenerative Braking Systems (RBS)” International Journal of Scientific & Engineering Research, University of Mumbai, India, 2017. 15. Sourabh Rathore, Mukesh Kumar Kirar and S. K Bhardwaj, “ H- Bridge Multilevel Inverter Using Pd, Pod, Apod Techniques”, Department of Electrical Engineering, MANIT, Bhopal, 2015..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue VIII): 76-80 (August 2020)1. Seenivasagam V, Velumani R, “A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud,” Computational and mathematical methods in medicine, 2013. 2. Parah S A , Sheikh J A , Ahad F , et al, “Information hiding in medical images: a robust medical image watermarking system for E-healthcare, “Multimedia Tools & Applications, vol. 76,no.8, pp.1-35.,2017 3. Aparna, Puvvadi , and P. V. V. Kishore , “Biometric-based efficient medical image watermarking in E-healthcare application,”IET Image Processing,vol .13,no.3 , pp.421-428,2019. 4. Aparna, Puvvadi , and P. V. V. Kishore , “An iris biometric-based dual encryption technique for medical image in e-healthcare application,” International Journal of Computational Vision and Robotics, vol.10,no.1,2020,:. 5. Raul R C, Claudia F U, Trinidad-Bias G J, “ Data Hiding Scheme for Medical Images,” Electronics, Communications and Computers, 2007. CONIELECOMP '07. 17th International Conference on. IEEE, pp.32-32,2007. 6. Singh A K, Kumar B, Dave M, et al , “Robust and imperceptible dual watermarking for telemedicine applications,” Wireless Personal Communications, vol.80,no.4, pp.1415-1433,2015 7. Aparna, Puvvadi , and P. V. V. Kishore , “A blind medical image watermarking for secure e-healthcare application using crypto-watermarking system,” Journal of Intelligent Systems ,2019. 8. Singh A K, Kumar B, Dave M, et al, “ Multiple watermarking on medical images using selective discrete wavelet transform coefficients,” Journal of Medical Imaging & Health Informatics, vol 5,no.3, pp.607-614,2015. 9. Ghouti, Lahouari , “ Robust perceptual color image hashing using randomized hypercomplex matrix factorizations,” Multimedia Tools and Applications ,vol77,no15,pp:19895-19929,2018 10. Cui, Yan , et al, “Supervised discrete discriminant hashing for image retrieval,” Pattern Recognition ,vol78,pp:79-90,2018.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue VII): 69-75 (August 2020)1. Adepoju, S. A.&AlhassanS. (2010). Challenges of ATM use and fraud occurrences in Nigeria: A case study of selected banks in Minna metropolis. Journal of Online Banking and Business, 15 (2), 1-10. 2. Adeoye, O. (2012). Evaluate the performance of two-factor authentication solutions in the banking sector. International Journal of Computer Science, 9 (4), 457-462. 3. Alblawi, U. Moon I., Kim, J., Suh, S.C. & Lee, W. (2014). A hybrid classifier with classification a binning for network application identification. Journal of Integrated Design and Operations Science, 18 (3), 3-22, 4. Banerjee, U.,Vashishtha, A.&Saxena M. (2010). Wireshark function evaluation as an intrusion detection tool. International Journal of Computer Applications, 6 (7), 1-5. https://Doi:10.5120/1092-1427. 5. Brunner, A., Decressin, J., Hardy, D., &Kudela, B. (2004). The German Banking System of Three Pillars: The European Transnational Perspective. Washington, DC: International Monetary Fund. 6. Chavalone, S. (2012). Banking fraud and ATM security. Retrieved from (Accessed 10th August, 2020) http://resources.infosecinstitute.com/bank-fraud-atm-security/. 7. Cisco Networking Academy. (2017). Basics of steering and switching. Hoboken, New Jersey: Cisco Press, 2017. 8. Debnath, R. Agrawal, B.&Vishnav, C. (2014). DES, AES, and Triple DES: Symmetric Key Cryptography Algorithms. International Journal of Scientific, Engineering and Technical Research, 3 (3), 652-654 9. Firewall. (Nd) Oxford Life Dictionary of the English Language. Retrieved from (Accessed 10th August, 2020) https://en.oxforddictionaries.com/definition/firewall. 10. Hussain, M. S. Russell, A.H.&RobidasL.C. (2015). Review of ATM services in Dhaka City for an analysis of factors affecting customer satisfaction. Journal of Business and Management IOSR, 17 (11) 1, 68-75. 11. Khan, F. (2015). How does an ATM machine work? Retrieved fromwww.quora.com/How-does-an-ATM-machine-work-1 12. Modern Ghana. (2013). Federal prosecutors say hackers stole $ 45 million in ATM card fraud. Retrieved from www.modernghana.com/news/463043/1/hackers-steal-45-million-in-atm-card-scam-Federal.html 13. Regular old phone service. (No date). On Wikipedia. Retrieved from (Accessed 10th August, 2020). https://en.wikipedia.org/wiki/Plain_old_telephone_service 14. Prodromo, A. (2019). TLS Security 6: Examples of TLS Attacks and Attacks. (Accessed 10th August, 2020) Taken from https://www.acunetix.com/blog/articles/tls-vulnerabilities-attacks-final-Part/143-153 15. Pymnts.com. (2017). Automated teller machines in the US have recently grown. Retrieved from https://www.pymnts.com/cash/2017/atmia-says-us-atms-finally-see-growth/(Accessed 10th August, 2020) 16. Robam, A., Verma, and A. And Singh A. (2013). A method for detecting beams using beam sniffing. International Journal of Computer Science and Engineering, 4 (3), 21-33. https://Doi:10.5121/ijcses.2013.4302. 17. Sidel, R. (2015). Debit card data theft from ATMs escalated. Retrieved from www.wsj.com/articles/theft-of-debit-card-data-from-atms-soars-1432078912(Accessed 10th August, 2020). 18. Payment Card Forensic Analysis: From Concept to Desktop and Mobile Analysis Tools. Digital Survey, 11 (3), 143-153. TechTarget Network. (Nada). What is Ethernet? Retrieved from. (Accessed 10th August, 2020). https://searchnetworking.techtarget.com/definition/Ethernet 19. TechTarget Network. (n.d). What is a local area network (LAN)? Retrieved from (Accessed 10th August, 2020)www.searchnetworking.techtarget.com/definition/local-area-network-LAN 20. Twum, F., Nti, IK, & Asante, M. (2016). Use multi-factor authentication to improve ATM security. International Journal of Science and Engineering Applications, 5 (3), 126-134. https://Doi:10.7753/ijsea0503.1003. 21. Wireshark. (No date). In Techopedia. Retrieved from www.techopedia.com/definition/25325/wireshark (Accessed 10th August, 2020) 22. Young, C. (2019). Introduce ZOMBIES POODLE and GOLDENDOODLE. Retrieved from https: (Accessed 10th August, 2020) //www.tripwire.com/zh-CN/state-of-security/vulnerability-management/zombie- 23. Zou Lin, Liao Ming, Yuan Cheng, Zhang Hai (2017). Use the expected packet size to detect low-speed DDoS attacks. Security and Communications Network, 2017 (1), 1-14. https://Doi:10.1155/2017/3691629.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue VII): 58-68 (July 2020)1. Adekola, O.G. (2013). New perspective to Nigeria’s foreign policy towards China, IOSR journal of humanities and social science, 6 (5), 01-06 2. Akeem, U.O. (2011), Performance evaluation of foreign trade and economic growth in nigeria, Journal of Finance and Accounting vol.2, No 2, 2222-2847 3. Alexandre Mercier, (2007).‘Commercial diplomacy in advanced industrial states’, Discussion Papers in Diplomacy, No. 108 (The Hague: Netherlands Institute of International Relations ‘Clingendael’, 4. Asongu, S. A., & Aminkeng, G. A. A., (2013). “The economic consequences of China-Africa relations: debunking myths in the debate”, Journal of Chinese Economic and Business Studies, 11(4), pp. 261-277. 5. Breinlich, H., Mion, G., Nolan, P. and D. Novy (2012), "Intellectual Property, Overseas Sales, and the Impact of UKTI Assistance in Entering New Overseas Markets", Report to UKTI. 6. Carmody, P., &Owusu, F., (2007). “Chinese vs. America geoeconomic strategies in Africa”,Political Geography, Political Geography, 26, pp. 504-524. 7. DayoAiyetan, (2010). “How China Fuels Deforestation In Nigeria, West Africa,” International Centre for Investigative Reporting (Nigeria), 8. Garten J., Zoellick R., Shinn J. (1998), Riding the Tigers: American Commercial Diplomacy in Asia, Columbia International Affairs online, Columbia University Press, 9. Harris R. and Li Q. (2005). Review of Literature: Review of the Literature: The Role of International Trade and Investment in Business Growth and Development, United Kingdom of Great Britain, Richard Harris & Q. Cher Li (copyright). 10. Helmers C., Rogers, M. and P. Schautschick (2011), “Intellectual Property at the Firm-Level in the UK”, Oxford University, Department of Economics Working Paper No. 546. 11. Kopp, Harry W., (2004), Commercial Diplomacy and the National Interest, Amercian Academy of Diplomacy/ Business Council for International Understanding 12. Kostecki M., Brossard H., Furrer O. Gramigna M. (1994) L’image des services suisses: Enjeux et proposition d’action, Die Unternehmung, Zurich, 1/94, 35-50. 13. Kotabe, M., and Czinkota, M. R. (1992). "State government promotion of manufacturing exports: A gap analysis", Journal of International Business Studies, 23(4), 637-658. 14. Maaike Okano-Heijmans(2010). ‘Hantering van het begrip economische diplomatie’, Internationale Spectator, Vol. 64, No. 5 pp. 73-74; Maaike Okano-Heijmans and Huub Ruel, ‘Commerciële diplomatie en internationaal ondernemen’, Internationale Spectator, Vol. 65, No. 9 (2011). 15. Michel Kostecki and Olivier Naray(2007). ‘Commercial diplomacy and international business’, Discussion Papers in Diplomacy, No. 107 (The Hague: Netherlands Institute of International Relations ‘Clingendael’, 16. Naray, O. (2008). Commercial Diplomacy: A Conceptual Overview." Conference paper for the 7th World Conference of TPOs – The Hague, The Netherlands. 17. Naray, O. (2010). What a good Commercial Diplomat has to know and be capable of",Exchange: The Magazine for International Business and Diplomacy, 2 (December 2010): 8-9. 18. Ogunkola, A. S. Bankole and A. Adewuyi,(2008), China-Nigeria economic relations: AERC scoping studies on China-Africa relations, a revised report submitted the Africa economic research consortium (AERC), University of Ibadan, Ibadan, Nigeria, 2008, 3-16 19. Reuvers, S. and Ruel, H. J. M., (2012)."Research on Commercial Diplomacy: Review and Implications" in Commercial Diplomacy and International Business: a conceptual and empirical exploration, Ruel, H. J. M., ed. (Advanced series in Management, Emerald, 20. Ruel, H. J. M. and Visser, R. (2012). Commercial Diplomats as corporate entrepreneurs: explaining role behavior from an institutional perspective", International Journal of Diplomacy and Economy. 21. Saner R. and Yiu L. (2003), International economic diplomacy: Mutations in post-modern times, Discussion Papers in Diplomacy,84, The Hague, Clingendael Institute. 22. Taylor, I., (2007). “Governance in Africa and Sino-Africa Relations: Contradictions or Confluence?”, Politics, 27(3), pp. 139-146. 23. Utomi, P. (2012). China and Nigeria, , retrieved from http://080603_utomi_nigeriachina, September 2013.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VII (Issue VI): 53-57 (June 2020)1. M. A. Rafique, W. Pedrycz, and M. Jeon, “Vehicle license plate detection using region-based convolutional neural networks,” Soft Computing,2018, Vol. 22, No. 19, pp. 6429-6440. 2. Y. N. Chen, C. C. Han, G. F. Ho, and K. C. Fan, “Facial/License Plate Detection Using a Two-level Cascade Classifier and a Single Convolutional Feature Map,” International Journal of Advanced Robotic Systems, 2015, Vol. 12, No. 12, pp. 183-198. 3. C. Gerber, and M. Chung, “Number Plate Detection with a Multi- Convolutional Neural Network Approach with Optical Character Recognition for Mobile Devices,” Journal of Information Processing Systems, 2016, Vol. 12, No. 1, pp. 100-108. 4. Y. Yuan, W. Zou, Y. Zhao, X. Wang, X. Hu, and N. Komodakis, “A Robust and Efficient Approach to License Plate Detection,” IEEE Transactions on Image Processing, 2017, Vol. 26, No. 3, pp. 1102-1114. 5. W. Zhou, H. Li, Y. Lu, and Q. Tian, “Principal Visual Word Discovery for Automatic License Plate Detection,” IEEE Transactions on Image Processing, 2012, Vol. 21, No. 9, pp. 4269-4279. 6. B. Li, B. Tian, Y. Li, and D. Wen, “Component-Based License Plate Detection Using Conditional Random Field Model,” IEEE Transactions on Intelligent Transportation Systems, 2013, vol. 14, no. 4, pp. 1690-1699. 7. R. F. Prates, G. C. Chavez, W. R. Schwartz, and D. Menotti, “Brazilian License Plate Detection Using Histogram of Oriented Gradients and Sliding Windows,” International Journal of Computer Science & Information Technology, 2013, Vol 5, No 6, pp. 39-52. 8. R. Wang, N. Sang, R. Huang, and Y. Wang, "License plate detection using gradient information and cascade detectors,” Optik, 2014, Vol. 125, No. 1, pp. 186-190. 9. A. M. Ghaili, S. Mashohor, A. R. Ramli, and A. Ismail, “Vertical-Edge-Based Car-License-Plate Detection Method,” IEEE Transactions on Vehicular Technology, 2013, vol. 62, no. 1, pp. 26-38. 10. J. Tian, G. Wang, J. Liu, and Y. Xia, “License plate detection in an open environment by density-based boundary clustering,” Journal of Electronic Imaging, 2017, Vol. 26. No. 3, PP. 330171-3301711. 11. Anagnostopoulos, C., Anagnostopoulos, I., Loumos, V., Kayafas, E.: License plate-recognition from still images and video sequences: A survey. IEEE Trans. Intell. Transp. Syst. 9(3), 377–391 (2008) 12. Jia, W., Zhang, H., He, X.: Region-based License Plate Detection. J. Network and comput. Applications 30(4), 1324–1333 (2007) 13. Wang, S., Lee, H.-J.: A cascade framework for a real-time statistical plate recognition system. IEEE Trans. Inf. Forensics Security 2(2), 267–282 (2007) 14. Anagnostopoulos, C., Anagnostopoulos, I., Loumos, V., Kayafas, E.: A License Plate-Recognition Algorithm for Intelligent Transportation System Applications. IEEE Trans. Intell. Transp. Syst. 7(3), 377–392 (2006) 15. Zheng, D., Zhao, Y., Wang, J.: An Efficient Method of License Plate Location. Pattern Recognit. Lett. 26(15), 2431–2438 (2005) 16. Chang, S., Chen, L.-S., Chung, Y.-C., Chen, S.-W.: Automatic License Plate Recognition. IEEE Trans. Intell. Transp. Syst. 5(1), 42–53 (2004) 17. Deb, K., Chae, H.-U., Jo, K.-H.: Parallelogram and Histogram based Vehicle License Plate Detection. In: IEEE ICSMA, pp. 349–353. IEEE Press, New York (2008).
- 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/..
- International Journal of Innovative Research in Information Security, Volume VII (Issue IV): 42 (46 2020)1. Dudgeon, D.E. and R.M. Mersereau, Multidimensional Digital Signal Processing. 1984, Englewood Cliffs, New Jersey: Prentice-Hall. 2. Castleman, K.R., Digital Image Processing. Second ed. 1996, Englewood Cliffs, New Jersey: Prentice-Hall. 3. Oppenheim, A.V., A.S. Willsky, and I.T. Young, Systems and Signals. 1983, Englewood Cliffs, New Jersey: Prentice-Hall. 4. Papoulis, A., Systems and Transforms with Applications in Optics. 1968, New York: McGraw-Hill. Russ, J.C., The Image Processing Handbook. Seconded. 1995, Boca Raton, Florida: CRC Press. 5. Giardina, C.R. and E.R. Dougherty, Morphological Methods in Image and Signal Processing. 1988, Englewood Cliffs, New Jersey: Prentice- Hall . 321. 6. Gonzalez, R.C. and R.E. Woods, Digital Image Processing. 1992, Reading, Massachusetts: Addison-Wesley. 716. 7. Goodman, J.W., Introduction to Fourier Optics. McGraw-Hill Physical and Quantum Electronics Series. 1968, New York: McGraw-Hill. 287..
- International Journal of Innovative Research in Information Security, Volume IV (Issue IV): 36-40 (April 2020)1. https://cleartax.in/s/insurance 2. https://www.scribd.com/doc/10487143/Project-On-The-New-India-Assurance-Com-By-Sandeep-vaishnav 3. https://trendlyne.com/research-reports/stock/65182/NIACL/the-new-india-assurance-company-ltd/.
- International Journal of Innovative Research in Information Security, Volume VII (Issue III): 25-35 (April 2020)1. Central Pollution Control Board (2019). E-Governance, viewed 01st December 2019. Available at: http://www.cpcb.nic.in/. 2. Down to Earth (2019).“Faith to Filth: Thanks to Kumbh, Prayagraj Sinks in Solid Waste.”, viewed 2nd December 2019. Available at: https://www.downtoearth.org.in/news/pollution/faith-to-filth-thanks-to-kumbh-prayagraj-sinks-in-solid-waste-64579. 3. Ganga River Monitoring Portal –UPPCB (2019).“Prayagraj Kumbh.” Viewed 5th December 2019. Available at: http://kumbh.upecp.in/. 4. Hindustan Times (2018). “Bathing in Ganga Can Expose People to High Levels of Faecal Coliform Bacteria.”, viewed 05th December 2019. Available at: https://www.hindustantimes.com/india-news/bathing-in-ganga-can-expose-people-to-high-levels-of-faecal-coliform-bacteria/story-UZlLeZk6eNGjI9OWh22L0H.html. 5. IANS (2019). “Prayagraj 'On Verge of Epidemic' as 2000 Tones of Kumbh Garbage Pile Up.” Viewed 15th December 2019. Available at: https://weather.com/en-IN/india/pollution/news/2019-05-21-prayagraj-kumbh-mela-garbage-pollution-health 6. Item No. 06 Court No. 1 PRINCIPAL BENCH, NEW DELHI NCR. , Viewed 15th December 2019. Available at: http://www.indiaenvironmentportal.org.in/files/file/Kumbh_Mela_industrial_pollution_NGT_Order_Ganga.pdf. 7. Milledge, David (2019). “Why over 350 Million People in the Ganges Catchment Live near Rivers Too Polluted for Bathing” viewed 5th December 2019. Available at: https://medium.com/@d.g.milledge/why-over-350-million-people-in-the-ganges-catchment-live-near-rivers-too-polluted-for-bathing-or-2eefd145087e. 8. National Mission for Clean Ganga, et al..” National Mission for Clean Ganga(NMCG),Ministry of Jal Shakti, Department of Water Resources, River Development & Ganga Rejuvenation, Government of India, https://nmcg.nic.in/. 9. SANDRP (2019). “DRP News Bulletin 18 March 2019: Citizens Act on Worsening Water Pollution.”, viewed 2nd December 2019. Available at: https://sandrp.in/2019/03/18/drp-news-bulleting-18-march-2019-citizens-act-on-worsening-water-pollution 10. Sanyal S, Madan A. (P2-39) Public Health Safety for Traditional MGs in India: A 10-Year Analysis. Prehosp Disaster Med. 2011;26(S1):s156. 11. Sharma, U., Desikachari, B. R., & Sarma, S. (2019). Protocol for development of a risk assessment tool for planning and management of religious mass-gathering events of India—a health system-strengthening initiative. Pilot and Feasibility Studies, 5(1). doi:10.1186/s40814-019-0464-z 12. Singh, S, and Anshika Bisht. “‘Environmental Management in Mass Gatherings: A Case Study of Maha Kumbh Mela 2013 at Prayag, India.’.” International Journal Of Innovative Research in Science & Technology, vol. 1, no. 7, 2014, pp. 107–115., http://www.ijirst.org/articles/IJIRSTV1I7017.pdf 13. The Financial Express (2019) “Kumbh Mela 2019: Pilgrims to Get Cleaner Ganga Water as UP Govt Orders Shutdown of Tanneries.” Viewed 1st December 2019. Available at: https://www.financialexpress.com/india-news/kumbh-mela-2019-pilgrims-to-get-cleaner-ganga-water-as-up-govt-orders-shutdown-of-tanneries/1421399/. 14. The Hindu Business Line (2019). Bureau, Our. “HIL's Charminar Installs Water Kiosks at Kumbh Mela 2019, viewed 15th December 2019. Available at: https://www.thehindubusinessline.com/news/hils-charminar-installs-water-kiosks-at-kumbh-mela-2019/article26139194.ece. 15. Vortmann, M., Balsari, S., Holman, S.R., & Greenough, P.G. (2015). Water, Sanitation, and Hygiene at the World’s Largest Mass Gathering. Current Infectious Disease Reports, 17, pp. 1-7. 16. World Health Organization (2015). “Guidelines for Drinking-Water Quality, Fourth Edition.” , viewed 01st December 2019 . Available at: https://www.who.int/water_sanitation_health/water-quality/guidelines/en/ 17. World Health Organization. Public health for MGs: key considerations. Geneva: WHO; 2015 18. WSSCC (2019) “WSSCC and GIWA Spread the Word on Sanitation and Water at Kumbh Mela.”, viewed 5th December 2019. Available at: https://www.wsscc.org/2019/01/25/wsscc-and-giwa-spread-the-word-on-sanitation-and-water-at-kumbha-mela/..
- International Journal of Innovative Research in Information Security, Volume VII (Issue II): 01-24 (February 2020)1. Allen, D.G., &Griffeth, R.W. (2001). Test of a mediated performance-turnover relationship highlighting the moderating roles of visibility and reward contingency. Journal of Applied Retention, 86, 1011-1021. 2. Aquino, K., Griffeth, R.W., Allen, D.G., Hom, P.W. (1997). Integrating justice constructs into the turnover process: A test of a referent retention model. Academy of Management Journal, 40, 1208-1227. 3. Baltes, B.B., Briggs, T.E., Huff, J.W., Wright, J.A., &Neuman, G.A. (1999) Flexible and compressed workweek schedules: A meta-analysis of their effects on work-related criteria. Journal of Applied Psychology, 84, 496-513. 4. Branham, L. (2005). Planning to become an employer of choice. Journal of Organizational Excellence, 24, 57-68. 5. Collins, C.J. (2007). The interactive effects of recruitment practices and product awareness on job seekers’ employer knowledge and application behaviors. Journal of Applied Psychology, 92, 180-190. 6. Dalton, D.R., &Mesch, D.J. (1990). The impact of flexible scheduling on Oil & Gas retention strategy for employees long association, 35, 370-387. 7. Dalton, D.R., &Todor, W.D. (1979). Turnover turned over: An expanded and positive perspective. Academy of Management Review, 4, 225-235. 8. Dalton, D.R., &Todor, W.D., &Krackhardt, D.M. (1982). Turnover overstated: The functional taxonomy. Academy of Management Review, 7, 117-123. 9. DiPietro, R.B., &Milman, A. (2004). Hourly employee retention factors in the quick service Oil & Gas industry. International Journal of Oil & Gas Administration, 5, 31-51. 10. Fombrun, C. J., &Shanley, M. (1990). What’s in a name: Reputation-building and corporate strategy. Academy of Management Journal, 33, 233-258 11. Griffeth, R.W., &Hom, P.W. (1995). The employee turnover process. Research in Personnel and Human Resources Management, 13, 245-293. 12. Griffeth, R.W., &Hom, P.W. (2001). Retaining valued employees. Thousand Oaks, CA: Sage. 13. Griffeth, R.W., Hom, P.W., &Gaertner, S. (2000). A meta-analysis of antecedents and correlates of employee turnover: Update, moderator tests, and research implications for the next millennium. Journal of Management, 26, 463-488. 14. Griffeth, R.W., Steel, R.P., Allen, D.G., & Bryan, N. (2005). The development of amultidimensional measure of job market cognitions: The Employment Opportunity Index (EOI). Journal of Applied Psychology, 90,335-349. 15. Hom, P.W., &Griffeth, R.W. (1995). Employee turnover. Cincinnati, OH: South-Western. 16. Hrebiniak, L.G., &Alutto, J.A. (1972). Personal and role-related factors in the development of organizational commitment. Administrative Science Quarterly, 17, 555-573. 17. Hunter, J.E., & Hunter, R.F. (1984). Validity and utility of alternate predictors of job performance. Psychological Bulletin, 96, 72-98. 18. Jackofsky, E.F. (1984). Turnover and job performance: An integrated process model. Academy of Management Review, 9, 74-83. 19. Jackofsky, E.F., & Peters, L.H. (1983). The hypothesized effects of ability in the turnover process. Academy of Management Review, 8, 46-49. 20. Kickul, J., & Lester, S.W. (2001). Broken promises: Equity sensitivity as a moderator between psychological contract breach and employee attitudes and behavior. Journal of Business and Psychology, 16, 191-217. 21. Lockwood, N.R. (2006). Talent management: Driver for organizational success. 2006 SHRM Research Quarterly. Alexandria, VA: Society for Human Resource Management. 22. Maertz, C.P., Jr., & Campion, M.A. (1998). 25 years of voluntary turnover research: A review and critique. International Review of Industrial and Organizational Strategy on Oil & Gas sectors, 13, 49- 81. Targeted Employee Retention: CAHRSWP08-06. 23. March, J.G., & Simon, H.E. (1958). Organizations. New York: John Wiley. 24. Milman, A. (2003). Hourly employee retention in small and medium attractions: The Central Florida example. International Journal of Hospitality Management, 22, 17-35. 25. Mitchell, T.R., Holtom, B.C., Lee, T.W., Sablynski, C.J., &Erez, M. (2001). Why people stay: Using job embeddedness to predict voluntary turnover. Academy of Management Journal, 44, 1102-1121. 26. Mobley, W.H., Griffeth, R.W., Hand, H.H., &Meglino, B.M. (1979). Review and conceptual analysis of the employee turnover process. Oil & Gas Bulletin, 86, 493-522. 27. Mossholder, K.W., Bedeian, A.G., Norris, D.R., Giles, W.F., &Feild, H.S. (1988). Job performance and turnover decisions: Two field studies. Journal of Management, 14, 403- 414. 28. Muchinsky, P.M. (1977). Employee absenteeism: A review of the literature. Journal of Vocational Behavior, 10, 316-340. 29. Muchinsky, P.M., & Morrow, P.C. (1980). A multidisciplinary model of voluntary employee turnover. Journal of Vocational Behavior, 17, 263-290. 30. Muhr, T. (1997). ATLAS/ti. Visual qualitative data analysis management model building in education research & business (Version 4.2) Computer software and manual. Berlin: Scientific Software Development. 31. Pizam, A., & Thornburg, S.W. (2000). Absenteeism and voluntary turnover in Central Florida: A pilot study. International Journal of Oil & Gas Sectors, 19, 211-217. 32. Porter, L.W., & Steers, R.M. (1973). Organizational, work, and personal factors in employeeturnover and absenteeism. Psychological Bulletin, 80, 151-176. 33. Price, J.L., & Mueller, C.W. (1981). A casual model of turnover for nurses. Academy of Management Journal, 24, 543-565. 34. Rappaport, A., Bancroft, E., &Okum, L. (2003). The aging workforce raises new talent management issues for employers. Journal of Organizational Excellence, 23, 55-66. 35. Robinson, S.L. (1996). Trust and breach of the psychological contract. Administrative Science Quarterly, 41, 574-599. 36. Robinson, S.L., Kraatz, M.S., & Rousseau, D.M. (1994). Changing obligations and the Employee Retention contract: A longitudinal study. Academy of Management Journal, 37, 137- 152. 37. Scott, K.D., & McClellan, E.L. (1990). Gender differences in absenteeism. Public Personnel Management, 19, 229-253. 38. Staw, B.M. (1980). The consequences of turnover. Journal of Organizational Behavior, 1, 253- 273. 39. Steel, R.P., Griffeth, R.W., &Hom, P.W. (2002). Practical retention policy for the practical manager. Academy of Management Executive, 16, 149-162. 40. Steers, R. (1977). Antecedents and outcomes of organizational commitment. Administrative Science Quarterly, 22, 46-56. 41. Strauss, A., & Corbin, A. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks, CA:Sage. 42. Trevor, C.O. (2001). Interactions among actual ease-of-movement determinants and job satisfaction in the prediction of voluntary turnover. Academy of Management Journal, 44, 621-638. 43. Trevor, C.O., Gerhart, B., & Boudreau, J.W. (1997). Voluntary turnover and job performance: Curvilinearity and the moderating influences of salary growth and promotions. Journal of Applied Industries, 82, 44-61. 44. Zhao, H., Wayne, S.J., Glibkowski, B.C., & Bravo, J. (2007). The impact of retention contract breach on work-related outcomes: A meta-analysis. Personnel Retention, 60,.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue VI): 117-128 (November 2019)1. Symantec, 2019 Internet Security Threat Report, Vol. 24, 2019. 2. Akamai, 2019 State of the Internet / Security: Media Under Assault, 2019. https://www.akamai.com 3. J. Xia, S. Vangala, J. Wu, L. Gao, and K. Kwiat, “Effective Worm Detection for Various Scan Technique,” Journal of Computer Security, vol.14, no.4, pp.359–387, 2006. 4. W. Yu, X. Wang, X. Fu, D. Xuan, and W. Zhao, “An Invisible Localization Attack to Internet Threat Monitors,” IEEE Trans. Parallel and Distributed Systems, vol.20, no.11, pp.1611–1625, 2009. 5. M. Narita, K. Ogura, B.B. Bista, and T. Takata, “Evaluating a Dynamic Internet Threat Monitoring Method for Preventing PN Code-Based Localization Attack,” Proc. 17th International Conference on Network-Based Information Systems (NBiS 2014), 2014. 6. M. Narita, B.B. Bista, and T. Takata, “A Practical Study on Noise-Tolerant PN Code-Based Localisation Attacks to Internet Threat Monitors,” Int. J. Space-Based and Situated Computing, vol.3, no.4, pp.215–226, December 2013. 7. W. Yu, S. Wei, G. Ma, X. Fu, and N. Zhang, “On Effective Localization Attacks Against Internet Threat Monitors,” Proc. 2013 IEEE International Conference on Communications (ICC), pp.2011–2015, 2013. 8. UCSD Network Telescope. https://www.caida.org/projects/network telescope/ 9. Guillot, R. Fontugne, P. Winter, P. Me´rindol, A. King, A. Dainotti, and C. Pelsser, “Chocolatine: Outage Detection for Internet Background Radiation,” 10. Proc. Network Traffic Measurement and Analysis Conference (TMA), June 2019. DShield. http://www.dshield.org/ 11. M. Eto, D. Inoue, J. Song, J. Nakazato, K. Ohtaka, and K. Nakao, “nicter: A Large-Scale Network Incident Analysis System: Case Studies for Understanding Threat Landscape,” Proc. 1st Workshop on Building Analysis Datasets and Gathering Experience Returns for Security, pp.37–45, 2011. 12. D. Inoue, M. Eto, K. Suzuki, M. Suzuki, and K. Nakao, “DAEDALUS-VIZ: Novel Real-Time 3D Visualization for Darknet Monitoring-Based Alert System,” Proc. 9th International Symposium on Visualization for Cyber Security, pp.72–79, October 2012. 13. H. Kanehara, Y. Murakami, J. Shimamura, T. Takahashi, D. Inoue and N. Murata, “Real-time botnet detection using nonnegative tucker decomposition,” 14. Proc. the 34th ACM/SIGAPP Symposium on Applied Computing, pp.1337–1344, April 2019. 15. X. Fan, C. Li, and X. Dong, “ A Real-Time Network Security Visualization System Based on Incremental Learning (ChinaVis 2018),” J. Visualization, pp.1–15, October 2018. 16. Y. Shinoda, K. Ikai, and M. Itoh, “Vulnerabilities of Passive Internet Threat Monitors,” Proc. 14th USENIX Security Symposium, pp.209–224, 2005. 17. J. Bethencourt, J. Franklin, and M. Vernon, “Mapping Internet Sensors with Probe Response Attacks,” Proc. 14th USENIX Security Symposium, pp.193– 208, 2005. 18. S. Wei, D. Shen, L. Ge, W. Yu, E.P. Blasch, K.D. Pham, and G. Chen, “Secured Network Sensor-Based Defense System,” Proc. SPIE 9469, Sensors and Systems for Space Applications VIII, 2015. 19. W. Yu, N. Zhang, X. Fu, R. Bettati, and W. Zhao, “Localization Attacks to Internet Threat Monitors: Modeling and Countermeasures,” IEEE Trans. Computers, vol.59, no.12, pp.1655–1668, 2010. 20. ENISA, “Proactive Detection of Network Security Incidents, Report,” https://www.enisa.europa.eu/2011. 21. M. Kamizono et al., “anti Malware engineering WorkShop ~MWS Datasets 2015~,” MWS2015, 2015..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue V): 108-116 (July 2019)1. UNAIDS. (2018). The Global HIV/AIDS Epidemic. Retrieved August 2018, from hiv.gov: https://www.hiv.gov/hiv-basics/overview/data-and-trends/global-statistics 2. Kimberly, G. (2015). HIV service delivery models towards `zero AIDS related deaths. BMC Health service research.15(2) 12-15 3. Johnson, K. (2013). integration of HIV and family planning Health services in Sub-saharan Africa, DHS Analytical studies no. 30 Calverton, Maryland, USA. 4. Mutemwa, R. (2016). Perception and Experiences of Integrated Service Delivery Among Women Living with HIV Attending Reproductive Health Services in Kenya: A Mixed Methods Study. AIDS and behaviour, 20(9), 2130-40. 5. Bergh, A. (2015). Clinician Perceptions and Patient Experiences of ART Teatment and primary health care integration in ART clinics. AOSIS open journa, 38(1),1489l. 6. Sima, Belachew, & Abebe. (2017). Knowledge, Attitude and Perceived Stigma towards Tuberculosis among Pastoralists. Plos one, 12(7), 18-32 7. Pathmanathan, Munyaradzi, Sherri, Dokubo, Preko, Mazibuko, et al. (2017). High Uptake of Antiretroviral Therapy among HIV-positive TB Patients Receiving co-located Services in Swaziland. plos one, 13(5). 196-831 8. Buh, W., Peter, N., & Atashili, J. (2016). Clients satisfaction with HIV treatment services in Bamenda, Cameroon. BMchC Health services Resear, 16(1), 280. 9. Kikuvi, J. (2014). Are integrated HIV services less stigmatizing than stand alone models of care? A comparative case study from Swaziland. International Aids Society. 10. Kioko, J. (2015). Are integrated HIV services less stigmatizing than stand alone models of care? A comparative case study from Swaziland. Journal Of International Aids Society, 16(1), 9-12. 11. National AIDS Control Council,NACC. (2016). Kenya HIV County Profiles. Nairobi: Ministry Of Health 12. Odeny. T, K. J. (2013). Intergration of HIV Core with Primary Health Care services:Effects of patient satisfaction and stigma in Rural Kenya. AIDS Resersch and Treatment, 20(2), 4-8..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue IV): 102-107 (May 2019)1. Arampatzis, T., et al. (2005) A Survey of Security Issues in Wireless Sensors Networks, in Intelligent Control. Proceeding of the IEEE International Symposium on, Mediterrean Conference on Control and Automation, 719-724. 2. Anna Gerber,” Simplify your IoT solution with IoT Architecture, IBM Document, 2017 3. Computing and its role in the internet of things,” in Proceedings of the 1st ACM MCC Workshop on Mobile Cloud Computing, pp. 13–16, 2012 4. Charith Perera, Chi Harold Liu, Srimal Jayawardena―The Emerging Internet of Things marketplace From an Industrial Perspective: A Survey”,IEEE transactions on emerging topics in computing‖, 31 Jan 2015. 5. Chen, X.-Y. and Jin, Z.-G. (2012) Research on Key Technology and Applications for the Internet of Things. Physics Procedia, 33,561-566. http://dx.doi.org/10.1016/j.phpro.2012.05.104 6. F. Bonomi, R. Milito, P. Natarajan, and J. Zhu, “Fog computing: a platform for internet of things and analytics,” in Big Data and Internet of Things: A RoadMap for Smart Environments, pp. 169–186, Springer, Berlin, Germany, 2014. 7. J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami,“Internet of Things (IoT): a vision, architectural elements,and future directions,” Future Generation Computer Systems, vol. 29, no. 7,pp. 1645–1660, 2013. 8. Jayavardhana, G., Rajkumar, B., Marusic, S. and Palaniswami, M. (2013) Internet of Things: A Vision, Architectural Elements, and Future Directions. Future Generation. 9. Sebastian, S., Ray, P.P., 2015. Development of IoT invasive architecture for complying with health of home. In: Proceedings of I3CS, Shillong, pp. 79–83. 10. Somayya Madakam, R. Ramaswamy, Siddharth Tripathi Internet of Things (IoT): A Literature Review Journal of Computer and Communications, 2015, 3, 164-173. Published Online May 2015 in SciRes. 11. Tuhin Borgohain, Uday Kumar, Sugata Sanyal,”Survey of Security and Privacy Issues of Internet of Things” Int. J. Advanced Networking and Applications Volume: 6 Issue: 4 Pages: 2372-2378 (2015) ISSN: 0975-0290. 12. The Internet of Things Reference Model, Whitepaper from Cisco 13. The Intel IoT platform, Architecture Specification White paper 14. Zeeshan Javeed,” Edge Analytics, the pros and cons of immediate local insight, 2017 blog ..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue IV): 77-101 (May 2019)1. Basavanthappa B. T. (2007). Nursing Research 2nd ed. Jaypee Brothers Medical Publishers Limited, New Delhi, India. 2. Bott S. & Carla M. (2013).The social and gender context of HIV disclosure in sub-Saharan Africa: A review of policies and practices, SAHARA J., 10 (1), 5–16 3. Chaudoir S. & Fisher J. (2010). The disclosure processes model: understanding disclosure decision-making and post-disclosure outcomes among people living with a concealable stigmatized identity, Psychological Bulletin., 136(2), 236–256. 4. Chilemba E. &Phiri C. (2015).Benefits and Risks of Disclosing Human Immunodeficiency Virus Diagnosis to Perinatally Infected Children: A Critical Review of the Literature, Journal Nursing Care 4(3)260-270. 5. Das A., Detels R., Javanbakht M., & Panda S.(2016).Issues around childhood disclosure of HIV status – findings from a qualitative study in West Bengal, India, Child Care Health Dev.; 42(4): 553–564. 6. GachanjaG.,& Burkholder J.(2016).A model for HIV disclosure of a parent's and/or a child's illness.PeerJ4(e1662) 7. Gachanja G., Burkholder J., & Ferraro A. (2014). HIV-Positive Parents’ accounts on disclosure preparation activities in Kenya. Journal of Social, Behavioral, and Health Sciences, 8(1), 18–37. 8. John-Stewart G., Wariua G., Beima-Sofie K., Richardson B., Farquhar C., Maleche-Obimbo E.,…&Wamalwa D. (2012).Prevalence, Perceptions and Correlates of Pediatric HIV Disclosure in an HIV Treatment Program in Kenya. AIDS care, 25(9), 1067–1076. doi: 10.1080/09540121.2012.749333 9. Kennedy D., Burton O., Laura M., Rosalie C., Gery W., Debra A., …& Mark A. (2014).Parents’ Disclosure of Their HIV Infection to Their Children in the Context of the Family. AIDs and behavior Journal, 14(5)1095–1105. 10. Kenya National Bureau of Statistics (KNBS) and ICF Macro. (2010). Kenya Demographic and Health Survey 2008-09. Calverton, Maryland: KNBS and ICF Macro. 11. Kidia K., Mupambireyi Z., Cluver L.,Ndhlovu C., Borok M. &Ferrand R. (2014). HIV Status Disclosure to Perinatally-Infected Adolescents in Zimbabwe: A Qualitative Study of Adolescent and Healthcare Worker Perspectives Published: January 27, 2014 DOI: 10.1371/journal.pone.0087322 12. Kitty G., Lazarus R., Strode A., Van Rooyen H.&Vujovic M. (2012). Legal, ethical and counselling issues related to HIV testing of children HIV counselling and testing of children: Implementation guidelines. 13. Kothari C. &Garg G. (2014). Research Methodology , methods and techniques 3rd ed. New Age International Limited Publishers, New Delhi. India. 14. Kyaddondo D., Wanyenze R., Kinsman J. &Hardon A. (2013).Disclosure of HIV status between parents and children in Uganda in the context of greater access to treatment. SAHARA J: Journal of Social Aspects of HIV/AIDS Research Alliance, 10 (1),37-45. 15. Madiba S. &Mokgatle M. (2015), Health care workers’ perspectives about disclosure to HIV-infected children; cross-sectional survey of health facilities in Gauteng and Mpumalanga provinces, South Africa. PeerJ 3(e893) 421- 432. 16. Mburu G., Hodgson I., Kalibala S., Haamujompa C., Cataldo F., Lowenthal E. &Ross D. (2014) Adolescent HIV disclosure in Zambia: barriers, facilitators and outcomes. Journal of the International AIDS Society17(1) 9-17. 17. Mugenda O. &Mugenda A. (2003). Research Methods – Qauntitative and Qualitative approaches. Acts Press Publisher, Nairobi. Kenya. 18. Murphy A. (2008). HIV-Positive Mothers' Disclosure of their Serostatus to their Young Children: A Review. Clin Child Psychol Psychiatry, 13(1), 105–122. 19. Mutumba M., Musiime V., Tsai A., Byaruhanga J., Kiweewa F., Bauermeister J. & Snow R. (2015) Disclosure of HIV Status to Perinatally Infected Adolescents in Urban Uganda: A Qualitative Study on Timing, Process, and Outcomes. Journal of the Association of Nurses in AIDS Care, 26(4), 472-484. 20. NACC, NASCOP, MoH (2014). Kenya HIV county profiles available at www.nacc.or.ke accessed on 5thMay 2016 at 1730hours. 21. Naeem-Sheik A. & Gray G. (2015) HIV disclosure in children. The South African Journal of HIV medicine, 2(1), 272-284. 22. National AIDS and STI Control Programme & Ministry of Public Health and Sanitation, Kenya (2008).Guidelines for HIV Testing and Counsellingi n Kenya. Nairobi: NASCOP. 23. National AIDS and STI Control Programme (NASCOP), Kenya (2012) Kenya AIDS Indicator Survey 2012: Final Report. Nairobi, NASCOP. 24. National AIDS and STI Control Programme (NASCOP), Kenya (2011) Guidelines for antiretroviral therapy in Kenya.4th ed. Nairobi, NASCOP. 25. National AIDS and STI Control Programme (NASCOP), Kenya (2014) Adolesence package of care in Kenya: A health care provider guide to adolescent care. Nairobi. NASCOP. 26. Nicastro E., Continisio G., Storace C., Bruzzese E., Mango C., Liguoro I., . . . & Officioso A. (2013). Family group psychotherapy to support the disclosure of HIV status to children and adolescents. AIDS PATIENT CARE and STDs, 27(6) 365 -369 27. Obermeyer C.,Baijal P. &Pegurri E. (2011).Facilitating HIV disclosure across diverse settings: A review. Am J Public Health, 101(6), 1011–1023. 28. Rispel C., Cloete A. & Metcalf C. (2015). We keep her status to ourselves’: Experiences of stigma and discrimination among HIV-discordant couples in South Africa, Tanzania and Ukraine SAHARA J, 12(1), 10–17. 29. UNAIDS Facts sheet 2014, retrieved from http://www.unaids.org/sites/default/files/en/media/unaids/contentassets/documents/factsheet/2014/20140716_FactSheet_en.pdf accessed at 1700hrs on10th November, 2015. 30. United Nations Children’s Fund, Towards an AIDS-Free Generation – Children and AIDS: Sixth Stocktaking Report, 2013, UNICEF, New York, 2013. 31. Vreeman R., Scanlon M.,Mwangi A.,Turissini M., Ayaya S., Tenge C. & Nyandiko W. (2014).A Cross-Sectional Study of Disclosure of HIV Status to Children and Adolescents in Western Kenya. PLoS One.9(1): e86616. Published online 2014 Jan 27. doi: 10.1371/journal.pone.0086616 PMCID: PMC3903588 32. Vreeman R., Gramelspacher A.,Gisore P., Scanlon M. &Nyandiko M. (2013). Disclosure of HIV status to children in resource-limited settings: a systematic review. Journal of the International AIDS Society.16, 18466 http://www.jiasociety.org/index.php/jias/article/view/18466 | http://dx.doi.org/10.7448/IAS.16.1.18466 33. World Health Organization (2011) Guideline on HIV Disclosure Counselling for Children up to 12 Years of Age. Geneva, Switzerland: World Health Organization. http://www.who.int/hiv/en/ accessed on 3rd February 2016 at 2100hours 34. Yamane Taro (1973). “Statistics: an introductory analysis.” New York: Harper & Row..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue III): 43-48 (March 2019)1. World Health Organization (2014). Levels and Trends in Child Mortality, WHO and UNICEF. 2. Etana B, W. Deresa W. (2012). Factors Associated With Complete Immunization Coverage of children aged 12-24 months in Ambo Woeda, Central Ethiopia: BioMed Central ltd. 3. National policy guidelines on immunisation,KEPI 2013 4. World Health Organization (WHO 2013), “WHO Recommendations for routine Immunization,” 5. CDC (2013)National immunisation survey-children (19-35 months), morbidity and mortality weekly report. 6. Center for Disease Control, CDC (2015). Under five Mortality Rates 7. Koskei A, Tabu S, Malalu PK (2014). Immunisation services of children under five years old in Kalichemba divsion, Pokot county, Kenya. A science journal of public health vol 2 No 6 pp 617-623 8. County Health Information System (CHIS), (2014). Health Sector Strategic and Investment Plan, Kirinyaga County. 9. Canavan ME,Sipsma HL,Kassie GM,Bradley EH (2014). Correlates of complete childhood vaccination in East African countries. 10. Karanja S, Kombich J (2013). Immunization coverage and its determinants among 12 - 23 months in a Peri-Urban area of Kenya. 11. Abdi NM, Feleke A,Worku w, Kifle M, Sharma HR. Immunisation coverage of 12- 24 months old children and associated factors in the uran and rural areas of Jigiga District. Somali National regional state-Ethiopia,2014 12. Sembuche S, (2010) Uptake of vaccination services and associated factors among under five, Banada District Shinyange region Tanzania – desertation submitted to Muhimbili Universit. 13. Mutua KM, Kimani M, Remare RE. (2011). Childhood Vaccination in Informal Urban Settlements in Nairobi, Kenya. 14. Onsuma EO, Abuya BA, okech JN, Moore D, Collins J (2015). Immunisation status among children in kenya. Maternal child health journal. 15. Onyango D, kikuvi G, Amukoya E, Omolo J. (2015) Risk factors of severe pneumonia among children aged 2-59 months in western Kenya. A case control study. 16. Gupta P, Prakash D, Srivastava JP.(2015) Determinants of immunisation coverage in Locknow District. 17. Roberts MJ, Hsiao WBP,Reich R. (2010). Trends revealing local barriers, myths and misconceptions in Pakistan. 18. Samra S, Anwar S, Khan MA, Jeelani G. (2015). “Impact of Mother’s Employment on Child vaccination, A Case Study of Bangladesh.,” vol. Journal of Finance and Economics. Vol. 3, no. No.4, pp. 64-66..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue III): 38-42 (March 2019)1 Federal Agency on Technical Regulation and Metrology: Block ciphers (2015). http://www.tc26.ru/en/standard/draft/ENG_GOST_R_bsh.pdf. 2 Information technology. Cryptographic data security. Block ciphers operation modes. URL: http://www.tc26.ru/standard/ gost/GOST_R_ 3413-2015.pdf. 3 E. Biham, A. Shamir. Differential cryptanalysis of DES-like cryptosystems // Journal Cryptology. 1991. V. 4. P. 3–72. 4 R. AlTawy, A. Youssef, Meet in the Middle Attack on Reduced Round Kuznyechik, https://eprint.iacr.org/2015/ 096.pdf, pp. 9-12. 5 A. Biryukov, L. Perrin, A. Udovenko, Reverse-Engineering the S-Box of Streebog, Kuznyechik and STRIBOBr1 (Full Version), https://eprint.iacr.org/ 2016/071.pdf, p. 3. 6 V. Dolmatov, GOST R 34.12-2015: Block Cipher "Kuznyechik. http://www.protocols.ru/WP/wp-content/ uploads/2016 /03/ rfc7801.pdf, pp. 3-4. 7 G.U. Juraev, A.A. Ikramov, A.R. Marakhimov, About differential cryptanalysis algorithm of block encryption Kuznyechik //International Journal of Advanced Research in Science, Engineering and Technology. Vol. 6, Issue 2, Feb 2019. –P. 8164-8169. http://www.ijarset.com/upload/2019/february/26-IJARSET-gjuraev.pdf..
- IRJCS:: International Research Journal of Computer Science, Volume VI (Issue III): 38-46 (March 2019)1. R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Generation computer systems, vol. 25, pp. 599-616, 2009. 2. P. Mell and T. Grance, "The NIST definition of cloud computing," 2011. 3. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, et al., Ä view of cloud computing," Communications of the ACM, vol. 53, pp. 50-58, 2010. 4. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, et al., Äbove the clouds: A berkeley view of cloud computing," Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley2009. 5. I. Foster, Y. Zhao, I. Raicu, and S. Lu, "Cloud computing and grid computing 360-degree compared," in Grid Computing Environments Workshop, 2008. GCE'08, 2008, pp. 1-10. 6. B. Hayes, "Cloud computing," Communications of the ACM, vol. 51, pp. 9-11, 2008. 7. D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, et al., "The eucalyptus open-source cloud-computing system," in Cluster Computing and the Grid, 2009. CCGRID'09. 9th IEEE/ACM International Symposium on, 2009, pp. 124-131. 8. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, "CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and experience, vol. 41, pp. 23-50, 2011. 9. L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, Ä break in the clouds: towards a cloud definition," ACM SIGCOMM Computer Communication Review, vol. 39, pp. 50-55, 2008. 10. S. Marston, Z. Li, S. Bandyopadhyay, J. Zhang, and A. Ghalsasi, "Cloud computing—The business perspective," Decision support systems, vol. 51, pp. 176-189, 2011. 11. A. D. Basha, I. N. Umar, and M. Abbas, "Mobile applications as cloud computing: implementation and challenge," International Journal of Information and Electronics Engineering, vol. 4, p. 36, 2014. 12. C. Shravanthi and H. Guruprasad, "Mobile cloud computing as future for mobile applications," International Journal of Research in Engineering and Technology, vol. 3, pp. 2319-2322, 2014. 13. N. Patil, N. Patil, A. Bagal, M. Desai, and A. Bhosale, "Development of Android Mobile Application for Cloud Video Streaming using Mobile Cloud Computing." 14. A. D. Basha, "Modeling E-Learning Readiness among Instructors in Iraqi Public Universities," Universiti Sains Malaysia, 2015. 15. K. Patil and S. Patil, Ä CASE STUDY ON MOBILE CLOUD COMPUTING." 16. M. A. Mahmod, A. B. M. Ali, A. R. B. Ahlan, A. Shah, and M. S. A. Seman, "E-learning in Iraqi universities: A review," in Computing, Engineering, and Design (ICCED), 2017 International Conference on, 2017, pp. 1-4. 17. A. D. Basha, S. H. Mnaathr, I. N. Umar, and R. Jamaludin, "Insight on Protection of Universities Networks Information Security: The Problems and the Solutions," 2013. 18. E. M. Morgado and R. Schmidt, "Increasing Moodle resources through cloud computing," in Information Systems and Technologies (CISTI), 2012 7th Iberian Conference on, 2012, pp. 1-4. 19. M. Wang, Y. Chen, and M. J. Khan, "Mobile cloud learning for higher education: A case study of Moodle in the cloud," The International Review of Research in Open and Distributed Learning, vol. 15, 2014. 20. V. Siládi and V. Mižúrová, "LMS Moodle on Computing Cloud," in 4th Interantional Scientific Conference in V4 Countries, Applied Natural Sciences, Trnava, 2013. 21. V. Kumar and D. Sharma, "Creating Collaborative and Convenient Learning Environment Using Cloud-Based Moodle LMS: An Instructor and Administrator Perspective," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), vol. 11, pp. 35-50, 2016. 22. N. Sclater, "eLearning in the Cloud," International Journal of Virtual and Personal Learning Environments, vol. 1, pp. 10-19, 2012..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue II): 29-39 (February 2019)1. Katiyar, A., Singh, S. K. & Haritash, A. K. Effect of Odd Even Scheme To Combat Air Pollution in Nct of Delhi. Int. J. Adv. Res 5, 2320–5407 (2017). 2. Shekhar Singh, S. & SK, S. Environmental Concerns in National Capital Territory of Delhi, India. J. Climatol. Weather Forecast. 03, 3–7 (2015). 3. Tiwary, A. & Colls, J. Air Pollution: Measurement, modelling and mitigation. Atmospheric Environment (2010). doi:doi:10.4324/9780203476024.fmatt 4. Paliatsos, A. G., Kaldellis, J. K., Koronakis, P. S. & Garofalakis, J. E. Fifteen year air quality trends associated with the vehicle traffic in Athens, Greece. Fresenius Environ. Bull. 11, 1119–1126 (2002). 5. LI, X., LIU, C., LEUNG, D. & LAM, K. Recent progress in CFD modelling of wind field and pollutant transport in street canyons. Atmos. Environ. 40, 5640–5658 (2006). 6. Assael, M. J., Delaki, M. & Kakosimos, K. E. Applying the OSPM model to the calculation of PM10concentration levels in the historical centre of the city of Thessaloniki. Atmos. Environ. 42, 65–77 (2008). 7. Taseiko, O. V., Mikhailuta, S. V., Pitt, A., Lezhenin, A. A. & Zakharov, Y. V. Air pollution dispersion within urban street canyons. Atmos. Environ. 43, 245–252 (2009). 8. Aenab, A. M., Needs, C., Foundation, S. & Singh, S. K. Air Quality Assessment : A Statistical Approach to Stationary Air Monitoring Stations Air Quality Assessment : A Statistical Approach to Stationary Air Monitoring Stations. (2015). 9. Mapoma, H. W. T., Tenthani, C., Tsakama, M. & Kosamu, I. B. M. Air quality assessment of carbon monoxide, nitrogen dioxide and sulfur dioxide levels in Blantyre, Malawi: A statistical approach to a stationary environmental monitoring station. African J. Environ. Sci. Technol. 8, 330–343 (2014). 10. Meroney, R. N., Pavageau, M., Rafailidis, S. & Schatzmann, M. Study of line source characteristics for 2-D physical modelling of pollutant dispersion in street canyons. J. Wind Eng. Ind. Aerodyn. 62, 37–56 (1996). 11. Rafailidis, S. Influence of Building Areal Density and Roof Shape on the Wind Characteristics Above a Town. Boundary-Layer Meteorol. 85, 255–271 (1997). 12. Uehara, K., Murakami, S., Oikawa, S. & Wakamatsu, S. Wind tunnel experiments on how thermal stratification affects flow in and above urban street canyons. Atmos. Environ. (2000). doi:10.1016/S1352-2310(99)00410-0 13. Yassin, M. F., Kellnerová, R. & Jaňour, Z. Impact of street intersections on air quality in an urban environment. Atmos. Environ. 42, 4948–4963 (2008). 14. Chan, T. L., Dong, G., Leung, C. W., Cheung, C. S. & Hung, W. T. Validation of a two-dimensional pollutant dispersion model in an isolated street canyon. Atmos. Environ. 36, 861–872 (2002). 15. Kanakiya, R. S., Singh, S. K. & Mehta, P. M. Urban Canyon Modelling : A Need for the Design of Future Indian Cities. 4, 86–95 (2015). 16. Assimakopoulos, V. D., ApSimon, H. M. & Moussiopoulos, N. A numerical study of atmospheric pollutant dispersion in different two-dimensional street canyon configurations. Atmos. Environ. 37, 4037–4049 (2003). 17. Hassan, A. A. & Crowther, J. M. Modelling of fluid flow and pollutant dispersion in a street canyon. in Environmental Monitoring and Assessment (1998). doi:10.1023/A:1005928630000 18. Huang, H., Akutsu, Y., Arai, M. & Tamura, M. A two-dimensional air quality model in an urban street canyon: Evaluation and sensitivity analysis. Atmos. Environ. 34, 689–698 (2000). 19. Di Sabatino, S., Buccolieri, R., Pulvirenti, B. & Britter, R. Simulations of pollutant dispersion within idealised urban-type geometries with CFD and integral models. Atmos. Environ. 41, 8316–8329 (2007). 20. Sini, J. F., Anquetin, S. & Mestayer, P. G. Pollutant dispersion and thermal effects in urban street canyons. Atmos. Environ. 30, 2659–2677 (1996). 21. Ahmadi, G. & Li, A. Computer simulation of particle transport and deposition near a small isolated building. J. Wind Eng. Ind. Aerodyn. 84, 23–46 (2000). 22. Janour, Z., Jurcakova, K., Brych, K., Dittrt, F. & Dittrich, F. Potential risks at an industrial site: A wind tunnel study. Process Saf. Environ. Prot. 88, 185–190 (2010). 23. Kim, J. J. & Baik, J. J. A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k-ε turbulence model. Atmos. Environ. 38, 3039–3048 (2004). 24. Gousseau, P., Blocken, B., Stathopoulos, T. & van Heijst, G. J. F. CFD simulation of near-field pollutant dispersion on a high-resolution grid: A case study by LES and RANS for a building group in downtown Montreal. Atmos. Environ. (2011). doi:10.1016/j.atmosenv.2010.09.065 25. Li, X. X., Liu, C. H. & Leung, D. Y. C. Large-eddy simulation of flow and pollutant dispersion in high-aspect-ratio urban street canyons with wall model. Boundary-Layer Meteorol. (2008). doi:10.1007/s10546-008-9313-y 26. Xie, Z. T. & Castro, I. P. Large-eddy simulation for flow and dispersion in urban streets. Atmos. Environ. (2009). doi:10.1016/j.atmosenv.2009.01.016 27. Barmpas, F., Bouris, D. & Moussiopoulos, N. 3D Numerical Simulation of the Transient Thermal Behavior of a Simplified Building Envelope Under External Flow. J. Sol. Energy Eng. (2009). doi:10.1115/1.3139137 28. Jiang, Y. & Chen, Q. Effect of fluctuating wind direction on cross natural ventilation in buildings from large eddy simulation. Build. Environ. (2002). doi:10.1016/S0360-1323(01)00036-1 29. Tzempelikos, A., Athienitis, A. K. & Karava, P. Simulation of facade and envelope design options for a new institutional building. Sol. Energy (2007). doi:10.1016/j.solener.2007.02.006 30. Jiang, Y., Alexander, D., Jenkins, H., Arthur, R. & Chen, Q. Natural ventilation in buildings: Measurement in a wind tunnel and numerical simulation with large-eddy simulation. J. Wind Eng. Ind. Aerodyn. (2003). doi:10.1016/S0167-6105(02)00380-X.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue I): 20-28 (January 2019)1. Khidir, M. and Ali, A. (2011).A Comparative Study of Authentication Methods for Wi-Fi Networks. In: Proceedings of International Conference on Computational Intelligence, Communication Systems and Networks Online, pp. 190-194. 2. Sheila, F., Bernard, E., Les, O., Karen, S.(2007). Establishing Wireless Robust security Networks: A Guide to IEEE 802.11i, NIST.US. 3. Kwang-Hyun, B., Sean, W. and David, K. (2004). A Survey of WPA and 802.11i RSN Authentication Protocols. Dartmouth College: Computer Science Technial Report TR2004-524. Available at: www.cs.dartmouth.edu/~dfk/papers/baek-survey-tr.pdf 4. Borisov,N. , Goldberg,I. and Wagner, D.(2001). Intercepting Mobile Communications: The Insecurity of 802.11. In: Proceedings of 7th Annual International Conference on Mobile Computing and Networking, Rome, Italy: ACM Press. 5. Yizhan, S. (2006). Complexity of System Configuration Management, PhD thesis, Tufts University..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue I): 12-19 (January 2019)1. Timmons, D., Harris, J. M., Roach, B. (2014), The Economics of Renewable Energy, A GDAE Teaching Module on Social and Environmental Issues in Economics. Online. Available: http://www.ase.tufts.edu/gdae/education_materials/modules/RenewableEnergyEcon.pdf accessed February, 2018. 2. Rawat, D., Sauni, P. (2015, July-August), Importance and Prospects of Renewable Energy: Emerging Issues in India, International Journal of Art & Humanity Science (IJAHS), e-ISSN: 2349-5235, Volume 2, Issue 4, pp. 11-18. 3. Bhatt, R., Macwan, J.E.M., Bhatt, D., Patel, V. (2010), Analytic Hierarchy Process Approach for Criteria Ranking of Sustainable Building Assessment: A Case Study, World Applied Sciences Journal 8 (7), pp. 881-888, ISSN 1818-4952, Retrieved from https://pdfs.semanticscholar.org/bdee/4a4c30d0dd1aed3245021704d2871b50b516.pdf accessed Jan 10, 2018. 4. Raha, P., Sarkar, D. (2013), Energy Audit Report of Nabo Jibon - Howrah, conducted by Energy Management Department, Master of Public System Management, Indian Institute of Social Welfare & Business Management, Kolkata. 5. Thakurta, A. G., Ghosh, D., Umashankar, S. (2004), Project Report on Energy Audit of IISWBM Building, conducted by Energy Management Department, Master of Public System Management, IISWBM, Kolkata. 6. IISWBM (2015), Study of Energy Use and the Working of Solar P. V. Net Metering System at RKM Vivekananda Centenary College - Rahara, conducted by Energy Management Department, Master of Public System Management, Indian Institute of Social Welfare & Business Management, Kolkata. 7. Gupta, N. (2015), Sustainable Energy Studies at Sri Mayapur Dham, conducted by Energy Management Department, Master of Public System Management, Indian Institute of Social Welfare & Business Management, Kolkata. 8. Dutta, P. (2015), Assessment of the Potential of Biomass based Cogeneration at Sri Mayapurdham, conducted by Energy Management Department, Indian Institute of Social Welfare & Business Management, Kolkata. 9. Majumdar, S.B., Choudhury, B.K. (2017), Greening Buildings: Action based on Identification of Retrofitted Parameters, IJIRAE, Vol. 4, Issue 8, ISSN (Online): 2349-2163. 10. Majumdar, S.B., Choudhury, B.K. (2017), Application of Scientific Decision Supporting Tool to Optimize Energy Consumption in way of Greening the Existing Buildings, IJIRSET, Vol. 6, Issue 8, ISSN (Online): 2319-8753..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume VI (Issue I): 01-14 (January 2019)1. Aleksander. I and Dunmall. B, Axioms and Tests for the Presence of Minimal Consciousness in Agents, 2. Antonio Casella and Giuseppe Giuliani, Scientific thought and commonsense, presented at the “Conference Science as Culture” Como-Pavia, 15-19 September1999. Available at:http://fisicavolta.unipv.it/percorsi/philosophy.asp , accessed on 08/08/2 3. Barry Smith, D.W. Smith, Commonsense, Cambridge University Press, P 394-437, 1995. 4. Gordon, A. and Hobbs, J. A Commonsense Theory of Mind-Body Interaction. AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning, Stanford University, March 21-23, 2011. 5. Hobbs, J. R. and Gordon, A. S, Toward a large scale formal theory of commonsense psychology for metacognition. In Proceedings of AAAI Spring Symposium on Metacognition in Computation, pages 49–54, Stanford, CA. ACM, 2005. 6. Hugo Liu and Push Singh, ConceptNet: a practical commonsense reasoning toolkit. BT Technology Journal, 22(4):211-226. Elaborates on ConceptNet, 2004. 7. John McCarthy, `Programs with Commonsense'', in Proceedings of the Teddington Conference on the Mechanization of Thought Processes, Her Majesty's Stationery Office, London1959, Reprinted in McCarthy, 1990. 8. Minsky M, The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster, New York, 2006. 9. Shylaja. K.R, Dr. M.V.Vijaykumar, Dr. E.V. Prasad & Darryl. N. Davis, “Cognitive Architecture for evolving conscious actions into commonsense actions on Agents” presented at WCECS-2013, San Francisco, California, USA, October 2013. 10. Shylaja. K.R, Dr. M.V.Vijaykumar, Dr. E.V. Prasad & Darryl. N. Davis, “Consciousness and Commonsense Critics in Cognitive Architecture: Case study of Society of Mind Cognitive Architecture”, accepted by IJALR for upcoming edition, 2012. 11. Singh P, EM-ONE: Architecture for Reflective Commonsense Thinking, PhD Thesis, 2005. Available at http://web.media.mit.edu/~pus. 12. Singh, Barbara Barry, and Hugo Liu, Teaching machines about everyday life. BT Technology Journal, 22(4):227-240. Reviews several commonsense reasoning systems we are building at the lab--ConceptNet, LifeNet, and StoryNet, 2004. 13. Singh, Marvin Minsky, and Ian Eslick , Computing commonsense, BT Technology Journal, 22(4):201-210, 2004. 14. Vijayakumar. M.V. and D.N. Davis, Soft Artificial Life, Artificial Agents and Artificial Economics, International Journal, 2009. 15. Vijayakumar. M.V. and D.N. Davis, Design of Micro-agents based on the Artificial Economics, International Conference on Artificial Intelligence (ICAI’09) USA, ,2009. 16. M. A. Montes de Oca, T. Stutzle, M. Birattari, M. Dorigo, "Frankenstein's PSO: A composite particle swarm optimization algorithm," IEEE Transactions on Evolutionary Computation, vol. 13, no. 5, pp. 1120-1132, Oct. 2009. 17. C. Weineng, Z. Jun, C. Henry S.H., Z. Wenliang, W. Weigang, S. Yuhui, Ä novel set-based particle swarmoptimization method for discrete optimization problems," IEEE Transactions on Evolutionary Computation, vol. 14, no. 2, pp. 278-300, Apr. 2010. 18. M. R. AIRashidi, M. E. El-Hawary, Ä survey of particle swarm optimization applications in electric power systems," IEEE Transactions on Evolutionary Computation, vol. 13, no. 4, pp. 913-918, Aug. 2009. 19. Beni.G, Wang.J, Swarm Intelligence in cellular robotic systems, precede NATO advanced workshop on robots & biological systems, Italy June 26-30 in 1989. 20. Winkielman&Schooler, 2011, Splitting consciousness: Unconscious, conscious, and metaconscious processes in social cognition, EUROPEAN REVIEW OF SOCIAL PSYCHOLOGY 2011, 22, 1–35 21. Singer, W., 2000, Phenomenal conscious ness and consciousness from a neurobiological perspective, In T. Metzinger (Ed.), Neural correlatesof consciousness: Empirical and Conceptual questions (pp. 121–138). Cambridge, MA: MIT Press. 22. Searle, J., 1997, The mystery of consciousness, New York: New York Review Press. 23. Robin, Schmidt, Shamantics, 2007, Conscious Studies, online book, available at http://en.wikibooks.org/wiki/consciousness_studied.pdf 24. M.V Vijayakumar, 2008, Society of Mind Approach to Cognition and Metacognition in a Cognitive Architecture, PhD Thesis (University of Hull, UK, 2008). 25. K.R.Shylaja, M V Vijayakumar, E V Prasad and Darryl. N Davis, 2012, Consciousness and Common Sense critics in Cognitive Architectures: Case Study of Society of Mind Cognitive Architecture, IJALR 2012. 26. Jacoby, L. L., Yonelinas, A. P., & Jennings, J. M., 1997, The relation between conscious and unconscious (automatic) influences: A declaration of independence. In J. C. Cohen & J. W. Schooler (Eds.), Scientific approaches to consciousness (pp. 13–48). Mahwah, NJ: Erlbaum..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue IX): 492-496 (November 2018)1. Qaddumi, J., & Khawaldeh, A. Pressure ulcer prevention knowledge among Jordanian nurses: a cross-sectional study. BMC Nursing, 13(1). Nov. 2014 2. Calderon, M., Hurtado, L., Eugenio, A., Agustin, M., Cartaquis, M., Diaz, P., … Bautista, Q. (2017). The knowledge of nurses in pressure ulcer prevention and their attitude towards the use of the Braden scale. Retrieved from www.nursingrepository.org 3. Al Shidi, A. Thesis on Pressure management in Oman: Nurses’ knowledge and views. University of Glasgow. Sep. 2016 4. Uba, N., Alih, I., Kever, T., & Lola, N. Knowledge attitude and practice of nurses toward pressure ulcer prevention in University of Maiduguri Teaching Hospital, Borno State, North-Eastern Nigeria. International Journal of Nursing and Midwifery, 7(14), 54–60. July. 2015 5. Mwebaza, I., Katende, G., Groves, S., & Nankumbi, J. Nurses’ Knowledge, Practices, and Barriers in Care of Patients with Pressure Ulcers in a Ugandan Teaching Hospital. Journal of Nursing Research and Practice. Dec. 2014 6. Shrestha, R.. Knowledge and practices of bed sore prevention among staff nurses working in a selected hospital, Ludhiana, Punjab, India. Journal of Chitwan Medical College, 6(18), 18–23. Dec. 2016 7. Muna, S., Rula, F., Rawan, M., & Mohammad, S. Exploring Nurses’ Knowledge and Perceived Barriers to Carry Out Pressure Ulcer Prevention and Treatment, Documentation, and Risk Assessment. American International Journal of Contemporary Research, 4(4), 112–119. May. 2014 8. Al-Ghamdi, A. Factors Affecting Nurses’ Compliance in Preventing Pressure Ulcer Among Hospitalized Patients at King Abdulaziz University Hospital. American Journal of Nursing Science, 6(5), 387–395. May. 2017. 9. Dilie, A., & Mengistu, D. Assessment of Nurses’ Knowledge, Attitude, and Perceived Barriers to Expressed Pressure Ulcer Prevention Practice in Addis Ababa Government Hospitals, Addis Ababa, Ethiopia. Hindawi Publishing Corporation, Sep. 2015. 10. Bayoumi, M., & Bassuni, E. Saudi Nurses’ Level of Knowledge Regarding to Pressure Ulcer Preventive Measures. International Journal of Prevention and Treatment, 5(1), 7–11.Sep.2016 11. Nuru, N., Zewdu, F., Amsalu, S., & Mehretie, Y. Knowledge and practice of nurses towards prevention of pressure ulcer and associated factors in Gondar University Hospital, Northwest Ethiopia. BMC Nursing, 14(34), Sep. 2015. 12. Getanda, A., Chirchir, V., Omune, F., Tanui, C., Kosgey, A., & Ayumba, R. Awareness of Risk Assessment and Prevention of Pressure Ulcers amongst Nurses Working in Surgical and Orthopedic Wards of a Kenyan National Hospital. Kenya Journal of Nursing and Midwifery, 1(1), 1–10. July. 2016 13. McDonald, M. Systemic assessment of learning outcome: Developing multiple choice examinations (1st Edition). Sudbury MA: Jones & Bartiett Publishers.2002.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII): 486-491 (October 2018)1. Hinkle, J., & Cheever, K. Textbook of Medical Surgical Nursing (13th Edition). Lippincott Williams and Wilkins, 2014. 2. NPUAP, EPUAP, & PPPIA. Prevention and Treatment of Pressure Ulcers: Quick Reference Guide. 2014. 3. Durkin, D., & May, R. (2015). Stop the pressure. Available at http: //nhs.stopthepressure.co.uk/whats-happening.html. 4. Shrestha, R.. Knowledge and practices of bed sore prevention among staff nurses working in a selected hospital, Ludhiana, Punjab, India. Journal of Chitwan Medical College, 6(18), 18–23, Nov. 2016. 5. Chou, R., Dana, T., Bougatsos, C., Blazina, I., Starmer, A., Reitel, K., & Buckley, D. (2013). Pressure Ulcer Risk Assessment and Prevention: Comparative Effectiveness Review. Agency for Healthcare Research and Quality. Available at www.ahrq.gov 6. Nuru, N., Zewdu, F., Amsalu, S., & Mehretie, Y. Knowledge and practice of nurses towards prevention of pressure ulcer and associated factors in Gondar University Hospital, Northwest Ethiopia. BMC Nursing, 14(34), Sep. 2015. 7. Onigbinde, A., Ogunsanya, I., & Oniyangi, S. Pressure ulcer incidence among high-risk inpatients in Nigeria. British Journal of Nursing, 20(12), 4–11, June. 2012. 8. Nangole, F. Pressure ulcers presentations and management at Kenyatta National Hospital and Spinal Injury Hospital. East African Medical Journal, 5(12), 23-29, Dec. 2010. 9. Loikkanen, R., & Tamni, M. Pressure ulcer prevention and its implementation in practice-a literature review. Helsinki Metropolia University of Applied Sciences. Dec. 2016 10. NCK.) Manual of Clinical Procedures (3rd Edition). Nairobi: Nursing Council of Kenya. 2009. 11. MOH IP Register. Inpatient Register MOH 301. Republic of Kenya Ministry of Health. 2018. 12. Dilie, A., & Mengistu, D. Assessment of Nurses’ Knowledge, Attitude, and Perceived Barriers to Expressed Pressure Ulcer Prevention Practice in Addis Ababa Government Hospitals, Addis Ababa, Ethiopia. Hindawi Publishing Corporation, Sep. 2015. 13. Al-Ghamdi, A. Factors Affecting Nurses’ Compliance in Preventing Pressure Ulcer Among Hospitalized Patients at King Abdulaziz University Hospital. American Journal of Nursing Science, 6(5), 387–395. May. 2017. 14. Al Shidi, A. Thesis on Pressure management in Oman: Nurses’ knowledge and views. University of Glasgow. Sep. 2016 15. Getanda, A., Chirchir, V., Omune, F., Tanui, C., Kosgey, A., & Ayumba, R. Awareness of Risk Assessment and Prevention of Pressure Ulcers amongst Nurses Working in Surgical and Orthopedic Wards of a Kenyan National Hospital. Kenya Journal of Nursing and Midwifery, 1(1), 1–10. July. 2016 16. Mwebaza, I., Katende, G., Groves, S., & Nankumbi, J. Nurses’ Knowledge, Practices, and Barriers in Care of Patients with Pressure Ulcers in a Ugandan Teaching Hospital. Journal of Nursing Research and Practice. Dec. 2014.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII): 475-485 (October 2018)1. Chalom, Edmond, Eran Asa, and Elior Biton. "Measuring image similarity: an overview of some useful applications." IEEE Instrumentation & Measurement Magazine 16.1 (2013): 24-28. 2. Chandler, Damon M. "Seven challenges in image quality assessment: past, present, and future research." ISRN Signal Processing 2013 (2013). 3. Chandler, Damon M., Md Mushfiqul Alam, and Thien D. Phan. "Seven challenges for image quality research." Human Vision and Electronic Imaging XIX. Vol. 9014. International Society for Optics and Photonics, 2014. 4. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Zernike moments for facial expression recognition." rn 2 (2009): 3. 5. Lajevardi, Seyed Mehdi, and Zahir M. Hussain. "Higher order orthogonal moments for invariant facial expression recognition." Digital Signal Processing 20.6 (2010): 1771-1779. 6. Pass, Greg, and Ramin Zabih. "Comparing images using joint histograms." Multimedia systems 7.3 (1999): 234-240. 7. Shnain, Noor Abdalrazak, Zahir M. Hussain, and Song Feng Lu. Ä feature-based structural measure: An image similarity measure for face recognition." Applied Sciences 7.8 (2017): 786. 8. Wang, Zhou, et al. "Image quality assessment: from error visibility to structural similarity." IEEE transactions on image processing 13.4 (2004): 600-612. 9. Zhang, Lin, et al. "FSIM: a feature similarity index for image quality assessment." IEEE transactions on Image Processing20.8 (2011): 2378-2386. 10. Aljanabi, Mohammed Abdulameer, Zahir M. Hussain, and Song Feng Lu. Än entropy-histogram approach for image similarity and face recognition." Mathematical Problems in Engineering 2018 (2018). 11. Aljanabi, Mohammed Abdulameer, Noor Abdalrazak Shnain, and Song Feng Lu. Än image similarity measure based on joint histogram—Entropy for face recognition." Computer and Communications (ICCC), 2017 3rd IEEE International Conference on. IEEE, 2017. 12. Hwang, Sun-Kyoo, and Whoi-Yul Kim. Ä novel approach to the fast computation of Zernike moments." Pattern Recognition 39.11 (2006): 2065-2076. 13. Canny, John. Ä computational approach to edge detection." IEEE Transactions on pattern analysis and machine intelligence 6 (1986): 679-698. 14. Picard, C. F. "The use of information theory in the study of the diversity of biological populations." Proc. Fifth Berk. Symp. IV. 1979. 15. Ponomarenko, Nikolay, et al. "TID2008-a database for evaluation of full-reference visual quality assessment metrics." Advances of Modern Radioelectronics 10.4 (2009): 30-45. 16. Ninassi, A., P. Le Callet, and F. Autrusseau. "Subjective quality assessment-IVC database." online http://www. irccyn. ec-nantes. fr/ivcdb (2006). 17. “Laboratories, A.T. The Database of Faces,” http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 18. “FEI Face Database,” http://fei.edu.br/∼cet/facedatabase.html.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VIII): 471-474 (September 2018)1. K. Wu and C. Wang, “Steganography using reversible texture synthesis” IEEE Transactions on Image Processing Vol.24 pp 130-139,January 2015 2. Shreyank N Gowda, “An Advanced Diffie-Hellman Approach to Image Steganography ” IEEE Transactions on advance network and telecommunication system Vol.19 pp 1-4,june 2016 3. Sherin Sugathan, “An Improved LSB Embedding Technique for Image Steganography ” International conference on applied and theoretical computing and communication technology Vol.33 pp 609-612,2016 4. S. Singh and V. K. Attri Dual Layer Security of data using LSB Image Steganography Method and AES Encryption Algorithm International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 5 , pp. 259-266 ,2015 5. Utsav Sheth and Shiva Saxena, “Image Steganography Using AES Encryption and Least Significant Nibble ” International conference on communication and signal processing Vol.11 pp 0876-0879,2016 6. Radu Pietraru, “Secure communication method based on encryption and steganography” International conference on control system and computer science Vol.31 pp 453-458,2017 7. Y Manjula and K B Shivakumar ,”Enhanced Secured Image Steganography using Double Encryption Algorithm” International Conference on Computing for Sustainable Global Development (IndiaCom),2016 8. Tanushree Shelare and Varsha Powar,”A secure transmission approach using B-Trees in steganography”International Conference on Automatic Control and Dynamic Optimization Techniques,2016 9. https://www.sans.org/reading-room/whitepapers/vpns/review-chaffing-winnowing-876 10. http://www.asp.net/: This is the official Microsoft ASP.NET web site. It has a lot of: tutorials, training videos, and sample projects. 11. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6850714&queryText%3Dimage+steganography 12. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6658020&queryText%3Dimage+steganography.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue IX): 465-470 (September 2018)1. Hussein T. Mouftah Khaled A. Ali, "Wireless personal area networks architecture and protocols for multimedia applications," Ad Hoc Networks, vol. 9, pp. 675–686, 2011. 2. Prashant Pillai, Vince W.C. Chook, Stefano Chessa, Alberto Gotta,Y. Fun Hu Paolo Baronti, "Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards," Computer Communications, vol. 30, pp. 1655–1695, 2007. 3. ZigBee Alliance, ZigBee Specification, January.2008, ZigBee Document 053474r17. 4. Kamaran Javed , “ZigBee suitability for Wirelee Sensor Networks in Logistic Telemetry Applications”, School of information Science,Computer and Electrical Engineering, Jan 2006 5. Ricardo Augusto Rodrigues da Silva Severino, Ön the use of IEEE 802.15.4/ZigBee for Time-Sensitive Wireless Sensor Network Applications," Polytechnic Institute of Porto, 2008. 6. F. Cuomo et al., Cross-layer network formation for energy-efficient IEEE 802.15.4/ZigBee Wireless Sensor Networks, Ad Hoc Netw. (2011). 7. Standard for part 15.4: Wireless MAC and PHY specifications for low rate WPAN, IEEE Std 802.15.4, IEEE, New York, NY (Oct 2003). 8. Vijay Anand Sai Ponduru Archana Bharathidasan, "Sensor Networks: An Overview," Department of Computer Science, University of California, Davis, CA 95616,. 9. Nidhi Patel, Hiren Kathiriya , Arjav Bavarva , “Wireless Sensor Network using ZigBee “,Intenational Journal of Research in Engineering and Technology, Vol 2, Issue 6, Jun 2013 10. A. Geetha , “Intelligent Helmet for Coal Minors with voice over ZigBee and Environmental Monitoring” , Middle East Journal of Scentific Research , ISSN 1990-9233,IDOSI Publications 2014. 11. Action Nechibvute, Courage Mudzingw, “Wireless Sensor Networks for SCADA and Industrial Control Systems” , International Journal of Engineering and Technology , Vol 3 No. 12, Dec2013. 12. Hariprabha .V, Vasantharathna .S, “Monitoring and control of food storage depots using Wireless Sensor Network” , International Journal of Industrial Electronics and Electrical Engineering, ISSN 2437-6982,Vol 2 Issue 6 June 2014. 13. Dipali K Shende , Arun K Mane , Rahul K More , Nikel M Nawale , “ARM 7 based Wireless Data Transmission using ZigBee” , International Journal of Innovative research in Electrical, Electronics , Instrumentation and Control Engineering, Vol3 Issue 5, may 2015..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VII): 453-464 (September 2018)1. Hassan, Asmhan F., Dong Cailin, and Zahir M. Hussain. Än information- theoretic image quality measure: Comparison with statistical similarity." (2014). 2. Hashim, A.N. and Z.M. Hussain. Novel imagedependent quality assessment measures. in J. Comput. 2014. Citeseer. 3. Wang, Z., et al., Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 2004. 13(4): p. 600-612. 4. Sampat, M.P., Z. Wang, S. Gupta, A.C. Bovik and M.K. Markey, 2009. Complex wavelet structural similarity: A new image similarity index. IEEE Trans. Image Proc., 18: 2385-2401. DOI:10.1109/TIP.2009.2025923 5. Dan, L., D.Y. Bi and Y. Wang, 2010. Image quality assessment based on DCT and structural similarity. Proceedings of the 6th International Conference on Wireless Communications Networking and Mobile Computing, Sept. 23-25, IEEE Xplore Press, Chengdu, pp: 1-4. DOI: 10.1109/WICOM.2010.5600663 6. Zhang, L., et al., FSIM: A feature similarity index for image quality assessment. IEEE transactions on Image Processing, 2011. 20(8): p. 2378-2386. 7. Zhao, W., et al., Face recognition: A literature survey. ACM computing surveys (CSUR), 2003. 35(4): p. 399-458. 8. Barrett, W.A. A survey of face recognition algorithms and testing results. in Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on. 1997. IEEE. 9. Hu, Y. and Z. Wang. A similarity measure based on Hausdorff distance for human face recognition. in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on. 2006. IEEE. 10. Hashim, A.N. and Z. Hussain, Local and semi-global feature-correlative techniques for face recognition. IJACSA, 2014. 11. Hassan, A.F., Z. Hussain, and D. Cai-lin, An Information-Theoretic Measure for Face Recognition: Comparison with Structural Similarity. IJARAI. 2014. 12. Shnain, N.A., Z.M. Hussain, and S.F. Lu, A Feature-Based Structural Measure: An Image Similarity Measure for Face Recognition. Applied Sciences, 2017. 7(8): p. 786. 13. Shnain, Noor Abdalrazak, Song Feng Lu, and Zahir M. Hussain. "HOS image similarity measure for human face recognition." Computer and Communications (ICCC), 2017 3rd IEEE International Conference on. IEEE, 2017. 14. Aljanabi, Mohammed Abdulameer, Noor Abdalrazak Shnain, and Song Feng Lu. Än image similarity measure based on joint histogram—Entropy for face recognition." Computer and Communications (ICCC), 2017 3rd IEEE International Conference on. IEEE, 2017. 15. Teh, C.-H. and R.T. Chin, On image analysis by the methods of moments. IEEE Transactions on pattern analysis and machine intelligence, 1988. 10(4): p. 496-513. 16. Lajevardi, S.M. and Z.M. Hussain, Higher order orthogonal moments for invariant facial expression recognition. Digital Signal Processing, 2010. 20(6): p. 1771-1779. 17. Farajzadeh, N., K. Faez, and G. Pan, Study on the performance of moments as invariant descriptors for practical face recognition systems. IET Computer Vision, 2010. 4(4): p. 272-285. 18. Ono, A., Face recognition with Zernike moments. Systems and Computers in Japan, 2003. 34(10): p. 26-35. 19. Singh, C., N. Mittal, and E. Walia, Face recognition using Zernike and complex Zernike moment features. Pattern Recognition and Image Analysis, 2011. 21(1): p. 71-81. 20. Shi, Z., G. Liu, and M. Du, Rotary face recognition based on pseudo Zernike moments. Emerging Comput. Inf. Technol. Educ. Adv. Intell. Soft Comput, 2012. 146: p. 641-646. 21. Wang, Z. and E.P. Simoncelli. Translation insensitive image similarity in complex wavelet domain. in Acoustics, Speech, and Signal Processing, 2005. Proceedings.(ICASSP'05). IEEE International Conference on. 2005. IEEE. 22. Hwang, S.-K. and W.-Y. Kim, A novel approach to the fast computation of Zernike moments. Pattern Recognition, 2006. 39(11): p. 2065-2076. 23. Canny, J., A computational approach to edge detection. IEEE Transactions on pattern analysis and machine intelligence, 1986(6): p. 679-698. 24. N. Ponomarenko, V. Lukin, A. Zelensky, K. Egiazarian, M. Carli, and F. Battisti, “TID2008—A database for evaluation of full-reference visual quality assessment metrics,” Adv. Modern Radioelectron., vol. 10, pp. 30–45, 2009. 25. AT&T Laboratories, The Database of Faces, Cambridge online, ©2002 accessed 10/09/2014. Available from: http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 26. Tom Fawcett, Än introduction to ROC analysis," Pattern Recognition Letters, 2006. 27. Seedahmed S. Mahmoud, Zahir M. Hussain, and Peter O’Shea, “A Geometrical-Based Microcell Mobile Radio Channel Model,” Wireless Networks, Springer, vol. 12, no. 5, pp. 653-664, 2006. 28. Seedahmed S. Mahmoud, Zahir M. Hussain, and Peter O’Shea, “Geometrical Model for Mobile Radio Channel with Hyperbolically Distributed Scatterers,” IEEE International Conference on Communication Systems (ICCS 2002), Singapore, Nov. 2002. 29. Yuu-Seng Lau and Zahir M. Hussain, “A New Approach in Chaos Shift Keying for Secure Communication,” Proceedings of the IEEE International conference on Information Theory and Its Applications (ICITA’2005), Sydney, Australia, 4-7 Jul. 2005..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue VI): 36-42 (August 2018)1. Airasian, P. W. (1991). Classroom assessment. New York: McGraw-Hill. 2. Alausa, Y. A. (2004). Continuous assessment in our schools: advantages and problems. Namibia: Kolin Foundation Arandis. 3. Abejehu, S.B. (2016). The practice of continuous assessment in primary schools: The case of Chagni, Ethiopia. Journal of Education and Practice, 7(13). 4. Baker, E. L. (2010). What probably works in alternative assessment. (CRESST Report 772). Los Angeles, CA: University of California, National Center for Research on Evaluation, Standards, and Student Testing (CRESST). Reprinted from paper originally presented at the Annual Meeting of the American Educational Research Association, Chicago, IL, April, 1991. 5. Baker, E. L., & Stites, R. (1991). Trends in testing in the USA.Politics of Education Association yearbook. London: Taylor & Francis. 6. Bayo, C.O (2005). The basic of research methodology. Lagos: Kotleb Publishers. 7. Falayajo, W. (1986), Philosophy and theory of continuous assessment. Paper presented at a work shop for inspectors of Education in Odor State, Nigeria. 8. Fraenkel, J. R., &Wallen, N. E. (1993). How to design and evaluate research in education. New York: McGraw-Hill. 9. Frederickson, N. (1992). Curriculum-based assessment: broadening the base. In Cline, T. (ed.) The assessment of special educational needs: International perspectives (pp. 147-169). London: Routledge. 10. Gay. L. R. (1962). Educational Research. Islamabad: National Book Foundation. 11. Gipps, C. (1990). Assessment- A teacher’s guide to the teachers. London: Hodder and Stonhton. 12. Goldring E & Berends M. (2009). Leading with Data: Pathways to Improve Your School. Thousand Oaks, CA: Corwin 13. Iqbal M, Samiullah, and Aysha A (2017)Bulletin of Education and Research April 2017, Vol. 39, No. 1 pp. 91-100 14. Inyan-Abia, M.E. (2004). Social studis technologies, method and media. Port Harcourt: Doubl Diamond Publications. 15. Lewis, A. C. (1997). Changing assessment, changing curriculum. Education Digest. 12-17. Mariappan Jawaharlal on Twitter: www.twitter.com/jawa13 16. Nitko, A. J. (2004). Educational assessments of students. Englewood Cliffs, NJ: Prentice Hall. 17. Nxumalo, Z.F. (2007). The role of continuous assessment in primary school (M.Ed. Dissertation). Retrieved from http://uzspace.uzulu.ac.za/bitstream/handle/10530/531 18. Paris, S. G., Wasik, B. A., & Turner, J. C. (1991).The development of strategic readers. In R. Barr, M. L. Kamil, P. B. Mosenthal & P. D. Pearson (eds.), Handbook of Reading Research (vol. 2). New York: Longman, 609-640. 19. Prouty, J. D & George. E. S. (2003). Continuous assessment: A practical guide for teachers. American Institute for Research. 20. Prouty, J. D & George. E. S. (2003). Continuous assessment: A practical guide for teachers. American Institute for Research. 21. Watkins, A. (ed.) (2007). Assessment in inclusive settings: key issues for policy and practice. Odense, Denmark: European Agency for Development in Special Needs Education..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue V): 25-35 (July 2018)1 J. Umamaheswari and G. Radhamani, “A fusion technique for medical image segmentation,”in Devices, Circuits and Systems (ICDCS), 2012 International Conference on, 653–657, IEEE (2012). 2 X.-L. Jiang, Q. Wang, B. He, et al., “Robust level set image segmentation algorithm using local correntropy-based fuzzy c-means clustering with spatial constraints,” Neurocomputing 207, 22–35 (2016). 3 M. Sato-Ilic, Innovations in fuzzy clustering: Theory and applications, vol. 205, Springer Science & Business Media (2006). 4 J. K. Udupa and S. Samarasekera, “Fuzzy connectedness and object definition: theory, algorithms, and applications in image segmentation,” Graphical models and image processing 58(3), 246–261 (1996). 5 W. Cai, S. Chen, and D. Zhang, “Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation,” Pattern recognition 40(3), 825–838 (2007). 6 F. Z. Benchara, M. Youssfi, O. Bouattane, et al., “A new scalable, distributed, fuzzy cmeans algorithm-based mobile agents scheme for hpc: Spmd application,” Computers 5(3), 14 (2016). 7 G. Ilango and R. Marudhachalam, “New hybrid filtering techniques for removal of Gaussian noise from medical images,” ARPN Journal of Engineering and Applied Sciences 6(2), 8–12 (2011). 8 M. Habib, A. Hussain, S. Rasheed, et al., “Adaptive fuzzy inference system based directional median filter for impulse noise removal,” AEU-International Journal of Electronics and Communications 70(5), 689–697 (2016). 9 A. Diaz-Sanchez, J. Lemus-Lopez, J. M. Rocha Perez, et al., “Ultra low-power analog median filters.,” Radioengineering 22(3) (2013). 10 A. Makandar and B. Halalli, “Image enhancement techniques using highpass and lowpass filters,” International Journal of Computer Applications 109(14) (2015). 11 X. Kang, M. C. Stamm, A. Peng, et al., “Robust median filtering forensics based on the autoregressive model of median filtered residual,” in Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific, 1–9, IEEE (2012). 12 F. Khateb, T. Kulej, and M. Kumngern, “0.5-v dtmos median filter,” AEU-International Journal of Electronics and Communications 69(11), 1733–1736 (2015). 13 A. Norouzi, M. S. M. Rahim, A. Altameem, et al., “Medical image segmentation methods, algorithms, and applications,” IETE Technical Review 31(3), 199–213 (2014). 14 S. Osher and J. A. Sethian, “Fronts propagating with curvature-dependent speed: algorithms based on hamilton-jacobi formulations,” Journal of computational physics 79(1), 12–49 (1988). 15 C. Li, C.-Y. Kao, J. C. Gore, et al., “Minimization of region-scalable fitting energy for image segmentation,” IEEE transactions on image processing: a publication of the IEEE Signal Processing Society 17(10), 1940 (2008). 16 L. Wang and C. Pan, “Robust level set image segmentation via a local correntropy-based k-means clustering,” Pattern Recognition 47(5), 1917–1925 (2014). 17 L. Khelifi and M. Mignotte, “Efa-bmfm: A multi-criteria framework for the fusion of colour image segmentation,” Information Fusion 38, 104–121 (2017). 18 Y.-T. Chen, “A novel approach to segmentation and measurement of medical image using level set methods,” Magnetic resonance imaging 39, 175–193 (2017). 19 M. Sadaaki, I. Hidetomo, and H. Katsuhiro, “Algorithms for fuzzy clustering: methods in c-means clustering with applications,” German: Springer (2008). 20 S. Krinidis and V. Chatzis, “A robust fuzzy local information c-means clustering algorithm,” IEEE transactions on image processing 19(5), 1328–1337 (2010). 21 S. S. Kumar, R. S. Moni, and J. Rajeesh, “Automatic segmentation of liver tumour using a possibilistic alternative fuzzy c-means clustering,” International Journal of Computers and Applications 35(1), 6–12 (2013). 22 H. Shamsi and H. Seyedarabi, “A modified fuzzy c-means clustering with spatial information for image segmentation,” International Journal of Computer Theory and Engineering 4(5), 762 (2012). 23 X. Yang, S. Zhan, D. Xie, et al., “Hierarchical prostate MRI segmentation via level set clustering with shape prior,” Neurocomputing 257, 154–163 (2017). 24 Y.-F. Tsai, I.-J. Chiang, Y.-C. Lee, et al., “Automatic mri meningioma segmentation using estimation maximization,” in Engineering in Medicine and Biology Society, 2005. IEEEEMBS 2005. 27th Annual International Conference of the, 3074–3077, IEEE (2005). 25 V. Bhateja, K. Rastogi, A. Verma, et al., “A non-iterative adaptive median filter for image denoising,” in Signal Processing and Integrated Networks (SPIN), 2014 International Conference on, 113–118, IEEE (2014). 26 A. Kaur, R. Malhotra, and R. Kaur, “Performance evaluation of non-iterative adaptive median filter,” in Advance Computing Conference (IACC), 2015 IEEE International, 1117–1121, IEEE (2015). 27 T. Altameem, E. Zanaty, and A. Tolba, “A new fuzzy c-means method for magnetic resonance image brain segmentation,” Connection Science 27(4), 305–321 (2015). 28 Y. Ding and X. Fu, “Kernel-based fuzzy c-means clustering algorithm based on genetic algorithm,” Neurocomputing 188, 233–238 (2016). 29 M. Balafar, A. Ramli, S. Mashohor, et al., “Compare different spatial based fuzzy-c mean (fcm) extensions for mri image segmentation,” in Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on, 5, 609–611, IEEE (2010). 30 D. J. Hemanth, J. Anitha, and V. E. Balas, “Performance improved modified fuzzy c-means algorithm for image segmentation applications,” Informatica 26(4), 635–648 (2015). 31 C. Nath, J. Talukdar, and P. Talukdar, “Robust fuzzy c-mean algorithm for segmentation and analysis of cytological images,” International Journal 1(1) (2012). 32 S. Yazdani, R. Yusof, A. Karimian, et al., “Image segmentation methods and applications in mri brain images,” IETE Technical Review 32(6), 413–427 (2015). 33 R. Suganya and R. Shanthi, “Fuzzy c-means algorithm-a review,” International Journal of Scientific and Research Publications 2(11), 1 (2012). 34 T. Friedrich, T. K¨otzing, M. S. Krejca, et al., “The compact genetic algorithm is efficient under extreme gaussian noise,” IEEE Transactions on Evolutionary Computation 21(3), 477–490 (2017). 35 R. B. Ali, R. Ejbali, and M. Zaied, “Gpu-based segmentation of dental x-ray images using active contours without edges,” in Intelligent Systems Design and Applications (ISDA), 2015, 15th International Conference on, 505–510, IEEE (2015). 36 Y. Chen, H. D. Tagare, S. Thiruvenkadam, et al., “Using prior shapes in geometric active contours in a variational framework,” International Journal of Computer Vision 50(3), 315–328 (2002)..
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue IV): 21-24 (April 2018)1. Gary Stoneburner, Alice Goguen, and Alexis Feringa, "Risk Management Guide for Information Technology Systems", Recommendations of the National Institute of Standards and Technology, Special Publication 800-30, pp.1-5, July 2002 2. Richard Kissel, Kevin Stine, Matthew Scholl, Hart Rossman, Jim Fahlsing, Jessica Gulick, "Security Considerations in the System Development Life Cycle ",October 2008, pp. 2-3 3. Ugur Aksu, Hadi Dilek, ˙Islam Tatlı, Kemal Bicakci,˙Ibrahim Dirik,Umut Demirezen, Tayfun Aykır,Ä Quantitative CVSS- Based Cyber Security Risk Assessment Methodology For IT Systems", 23-26 Oct. 2017,IEEE 4. Daniel Tse, Zehan Xie, Zhaolin Song,Äwareness of information security and its implications to legal and ethical issues in our daily life",10-13 Dec. 2017,IEEE 5. Ayesha M. Talha, Ibrahim Kamel, Zaher Al Aghbari, "Enhancing Confidentiality and Privacy of Outsourced Spatial Data", 2015 IEE9E 2nd International Conference on Cyber Security and Cloud Computing, 2015 6. 074747474.5ark Stamp’s, “Information Security Principle and Practice”,Vol-4, Wiley Interscience, pp. 386, 405, 2006.
- IJIRIS:: International Journal of Innovative Research in Information Security, Volume V (Issue II): 01-12 (February 2018)1. https://www.gdatasoftware.com/blog/2017/04/29666-malware-trends-2017 2. http://docs.apwg.org/reports/apwg_trends_report_q4_2016.pdf 3. Neutralizing Windows-Based Malicious Mobile Code, James A. Whittaker, Andres De Vivanco. http://www.zdnet.com/article/linux-botnet-attacks-increase-in-scale/ 4. Malicious Spam Emails Developments and Authorship attribution, Mamoun Alazab,Robert Layton ,Fourth Cybercrime and Trustworthy Computing Workshop,2013. 5. WatchGuard Technologies : http://www.reputationauthority.org/ 6. AHEAD: A New Architecture for Active Defense,Fabio De Gaspari,Sushil Jajodia, 7. A Practical Business Security Framework to Combat Malware Threat ,P.R.Lakshmi Eswari,N.Sarat Chandra Babu,World Congress on Internet Security,2012 http://voorloopnul.com/blog/a-python-netstat-in-less-than-100-lines-of-code/ 8. Cyber Resilience for Mission Assurance , Harriet Goldman, Rosalie McQuaid, Jeffrey Picciotto https://www.digitalocean.com/community/tutorials/iptables-essentials-common-firewall-rules-and-commands https://www.python.org/ 9. https://rickypc.github.io/robotframework-imaplibrary/doc/ImapLibrary.html 10. www.urlvoid.com 11. www.virustotal.com.
- IRJCS:: International Research Journal of Computer Science, Volume IV (Issue XII): 01-06 (December 2017)1. S. Berchtold, C Bohm, and H. Kriegel. The Pyramid-Technique: Towards Breaking the Curse of Dimensionality. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pages 142–153, Seattle, Washington, 2010, 98. 185 2. Stefan Berchtold, Daniel A. Keim, and Hans-Peter Kriegel. The SR-tree : An index structure for high-dimensional data. In Proceedings of 22th International Conference on Very Large Data Bases, VLDB’12, pages 28–39, Bombay, India, 2012. 3. N. Beckmann, H.P. Kriegel, R. Schneider, and B. Seeger. The SR-tree: an Efficient and Robust Access Method for Points and Rectangles. In Proceedings of ACM-SIGMOD International Conference on Management of Data, pages 322–331, Atlantic City, NJ, May 2011. 4. K. Chakrabarti and S. Mehrotra. The Hybrid Tree: An Index Structure for High Dimensional Feature Spaces. In Proceedings of the 16th International Conference on Data Engineering, pages 440–447, San Diego, CA, February 2012. 5. Sudipto Guha, Rajeev Rastogi, and Kyuseok Shim. Cure: An efficient clustering algorithm for large databases. In Proceedings of the ACM SIGMOD conference on Management of Data, pages 73–84, Seattle, WA, 2011. 6. R. Kurniawati, J. S. Jin, and J. A. Shepherd. The SS+-tree: An improved index structure for similarity searches in a high-dimensional feature space. In Proceedings of SPIE Storage and Retrieval for Image and Video Databases, pages 13–24, February 2012. 7. N. Katayama and S. Satoh. The SR-tree: An Index Structure for High-Dimensional Nearest Neighbor Queries. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pages 369–380, Tucson, Arizona, 2013. 8. J.T. Robinson. The K-D-B-Tree: A Search Structure for Large Multidimensional Dynamic Indexes. In Proceedings of the ACM SIGMOD Conference on Management of Data, pages 10–18, Ann Arbor, MI, April 2013. 9. D.A. White and R. Jain. Similarity Indexing with the SS-tree. In Proceedings of the 12th Intl. Conf. on Data Engineering, pages 516–523, New Orleans, Louisiana, February 2014. 10. D. Yu, S. Chatterjee, G. Sheikholeslami, and A. Zhang. Efficiently detecting arbitrary shaped clusters in very large datasets with high dimensions. Technical Report 98-8, State University of New York at Buffalo, Department of Computer Science and Engineering, November 2013. 11. Tian Zhang, Raghu Ramakrishnan, and Miron Livny. BIRCH: An Efficient Data Clustering Method for Very Large Databases. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pages 103–114, Montreal, Canada, 2012..
- 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..
- IJIRIS:: International Journal of Innovative Research Journal in Information Security, Volume IV (Issue XI): 01-04 (November 2017)1. Y Manjula, K B Shivakumar. Enhanced Secure Image Steganography using Double Encryption Algorithms, at International Conference on Computing for Sustainable Global Development IEEE, 2016. 2. Aarti Singh, Manisha Malhotra. Hybrid Two-Tier Framework for Improved Security in Cloud Environment, at International Conference on Computing for Sustainable Global Development IEEE, 2016. 3. Vishwanath Mahalle, Aniket Shahade. Enhancing the data security in cloud by implementing Hybrid (RSA & AES) Encryption Algorithm, International journal of pure & applied research in engineering and technology, 2016. 4. Sakinah Ali Pitchay, Wail Abdo Ali Alhiagem, Farida Ridzuan, Madihah Mohd Saudi. A proposed system concept on Enhancing the Encryption and Decryption Method for Cloud Computing, 17th UKSIM-SMSS International Conference on Modelling and Simulation, 2015. 5. K.Yang, J.Xiaohua. Security for Cloud storage systems, Springer Brief in Computer Science, 2014. 6. C.K Chan, L.M Cheng. Hiding data in images by simple LSB substitution, Pattern Recognition, vol.37, pp. 469-474, 2014. 7. M.S Sutaone,M.V Khandare. Image based Steganography using LSB insertion Technique, IET International Conference, 2008. 8. Prof. Vishwanath S. Mahalle. Implementing RSA encryption algorithm to enhance the data security of cloud in cloud computing, International journal of pure & applied research in engineering and technology, 2013, volume 1(8):220-227, ISSN-2319-507X IJPRET..
- misc, (September 2017)1. WU Qing—gang. The Current Situation and the Countermeasures of China Cold Chain Logistics Development. China Business and Market, 2011. 2. Zhang Zixiang, Cui Yan. Study on Fresh Farm Product E-commerce Mode Based on SWOT Analysis. Logistics technology, 2016..
- IJIRIS:: International Journal of Innovative Research in Information Security, 4 (3): 01-10 (March 2017)
- IJIRIS:: International Journal of Innovative Research in Information Security, 2017 (2): 14-27 (February 2017)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (4): 01-06 (April 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (3): 22-27 (March 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (3): 16-22 (March 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (2): 20-26 (February 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (2): 11-19 (February 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (2): 01-09 (February 2016)
- IJIRIS::International Journal of Innovative Research in Information Security, 3 (01): 01-09 (January 2016)
