Volume-8 , Issue-4 , Aug 2020, ISSN 2321-3256 (Electronic Version) Go Back

• Open Access   Article

  Smart Parking Application Using Deep Learning Framework

  R. Senthil Kumar, B. Surya

  Research Paper | Journal (IJSRNSC)

  Vol.8 , Issue.4 , pp.1-5, Aug-2020

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  Abstract
  Smart parking application is comprised by using Python and Deep Learning Frameworks (DLF). It provides an efficient way of improving the monitoring systems and make use of the data provided by them. By using this system, it is possible to reduce the vital information loss by the operator handling and thus reduce the human processed systems. Images are monitor through the monitoring systems and image processing technique, the data is handled by the Artificial Intelligence (AI) system and then a deciding is generated. This generated Deciding is passed with an image and vehicle information to proper personnel. Now a days, Deep Learning (DL) and AI systems are deployed for automating human handled process using AI and Hardware Integration. The Systems are able to make decisions in various environments and conditions above all affecting factors similar to intelligence expressed by human beings. The decisions made by the systems using deep learning and artificial intelligence methods can even make decisions superior to human intelligence. Integrating the methods of image processing and AI to automate the manned systems in the manner of scaling for any automated systems helps in removing the third-party operators from the control of informant and action. Our proposed idea was reduces the duration of information gathering and deciding of the operator to the information provided and increases the chance of positive results in terms of machine automated results.

  Key-Words / Index Term
  Deep Learning (DL), Artificial Intelligence (AI), TensorFlow, Performance

  References
  [1] Jonathan Barker and Sabih Rehman ,?Investigating the use of Machine Learning for Smart Parking Applications?, 11th International Conference on Knowledge and Systems Engineering (KSE), IEEE,ISSN: 2164-2508, 2019 .
  [2] Jaspreet Kaur ,?International Journal of Scientific Development and Research?, Volume 4, Issue 8, ISSN: 2455-2631,pp-284-290, 2019.
  [3], MuhammadAdnan ,KhancSagheerAbbasal, ?Smart occupancy detection for road traffic parking using deep extreme learning machine?, Journal of King Saud University - Computer and Information Sciences, 6th February 2020
  [4]Khaoula Hassoune , Wafaa Dachry , Fouad Moutaouakkil, Hicham Medromi, ?Smart Parking Systems: A Survey?, 11th International Conference on Intelligent Systems: Theories and Applications (SITA), 2016.
  [5] Faheem1, S.A. Mahmud1, G.M. Khan1, M. Rahman1, H. Zafar2, ?A Survey of Intelligent Car Parking System?, Vol. 11. Issue 5, pages 714-726 , 2013.
  [6] Faiz Shaikh , Nikhilkumar B.S, Omkar Kulkarni , Pratik Jadhav ,Saideep Bandarkar Hadapsar, ?International Journal of Innovative Research in Science, Engineering and Technology (IJRSET)? Vol. 4, Issue 10, 2015.
  [7] Noor HazrinHanyMohamadHanif, Mohd Hafiz Badiozaman, HanitaDaud, ?Smart parking reservation system using short message services (SMS)? , IEEE, 2009
  [8] Shruti Admane, Saurabh Kalmegh, Amit Bhende, Prof. Nutan Dhande, ?International Journal For Engineering Applications and Technology?, Issue12 vol 3ISSN: 2321-8134, pp-66-69, 2018

  Citation
  R. Senthil Kumar, B. Surya, "Smart Parking Application Using Deep Learning Framework," International Journal of Scientific Research in Network Security and Communication, Vol.8, Issue.4, pp.1-5, 2020

• Open Access   Article

  Impact of COVID-19 Pandemic Lockdown on Mental Well-Being amongst Individuals in Society

  Amit Nath

  Review Paper | Journal (IJSRNSC)

  Vol.8 , Issue.4 , pp.6-9, Aug-2020

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  The main objective of this study is to find out the impact of COVID-19 pandemic lockdown on mental well-being amongst individuals in society, reasons for psychological impact and to search out the solutions for the recovery from negative impact, if any. The survey is conducted on students, employees from different sectors, housewives, professionals and is also based upon secondary data. The findings of this study shows that the Lockdown as a result of the covid-19 pandemic has seriously affected the mental health of people and almost every section of society has suffered ranging from people residing in small town to metro cities and male or female population, people belonging to whatever age group and people belonging to nuclear family or joint family. But the sections of people which have been worse hit are young generations belonging to nuclear family and residing in big metro cities. The negative impact has resulted in suicide and has given birth of many severe diseases. But this lockdown has also had positive impact in life. The study recommends that Authorities must take into consideration not only the economic impact of social isolation, but also the mental impact on the society and must implement appropriate measures. People need to consult their psychiatrist and follow the remedies as prescribed in their daily routine life.

  Key-Words / Index Term
  Covid-19 pandemic, mental well being, masses boredom, lockdown, psychological problems

  References
  [1]. Mohammad Alradhawi , Nour Shubber, Jack Sheppard, Yousif Ali , ?Effects of the COVID-19 pandemic on mental well-being amongst individuals in society?, International Journal of Surgery, Vol.78, pp.147-148, 2020.
  [2]. Mohit Varshney ,Jithin Thomas Parel,Neeraj Raizada,Shiv Kumar Sarin, ?Initial psychological impact of COVID-19 and its correlates in Indian Community: An online (FEEL-COVID) survey?, PLOS ONE, Vol.15, Issue 5, 2020.

  Citation
  Amit Nath, "Impact of COVID-19 Pandemic Lockdown on Mental Well-Being amongst Individuals in Society," International Journal of Scientific Research in Network Security and Communication, Vol.8, Issue.4, pp.6-9, 2020

• Open Access   Article

  A Novel Based Approach to Detect and Take Action Against Network Intrusion in Virtual Machine Network System

  Keesara.Sravanthi, A. Srinivas, G. Narsing Rao, T. Raghu, P. Rakesh

  Research Paper | Journal (IJSRNSC)

  Vol.8 , Issue.4 , pp.10-13, Aug-2020

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  Abstract
  The design of intrusion detection systems (IDS) has received significant attention in the field of computer sciences with the massive number of network traffic and security risk. While various methods and strategies have been proposed for tracking Client and company behaviour and analyzed together to detect network intrusion. As there is latent information on further research in the classification and clustering of network packet signatures. We propose that the system of intrusion detection based on network signatures and system studies should be supported in this article. We include a KDDCUPSET which is used to store different modes of attacks and a multi - phase detector to identify potential intruders more effectively and a text-based query generation framework to challenge the detector module`s suspended requesters. If qualities of a received System Packet contest are certified, the classification alerts the admin to the potential precaution with the basis of cruel behavior and the classification must be above 90 percent accurate

  Key-Words / Index Term
  Machine Learning algorithm, NIDS, Clustering, Packet signatures

  References
  [1] Hoque, Nazrul, et al. "Network attacks: Taxonomy, tools and systems", Journal of Network and Computer Applications 40 (2014): 307-324.
  [2] Girardin, Luc. "An Eye on Network Intruder-Administrator Shootouts?, In the Proceedings of the Workshop on Intrusion Detection and Network Monitoring. 1999.
  [3] Lee, Wenke, and Salvatore J. Stolfo. "A framework for constructing features and models for intrusion detection systems?, ACM transactions on Information and system security (TiSSEC) 3.4 (2000): 227-261.
  [4] R. Lippmann, J. Haines, D. Fried, J. Korba and K. Das. ?The 1999 DARPA off-line intrusion detection evaluation?. Computer networks, vol. 34, no. 4, pp. 579 595, 2000. DOI http://dx.doi.org/10.1016/S13891286(00)00139-0.
  [5] Shankar, Umesh, and Vern Paxson. ?Active mapping: Resisting NIDS evasion without altering traffic.? 2003 Symposium on Security and Privacy, 2003. IEEE, 2003.
  [6] Weijian Huang, Yan An and Wei Du, "A Multi-Agent-Based Distributed Intrusion Detection System," 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), Chengdu, 2010, pp. V3-141-V3-143, doi: 10.1109/ICACTE.2010.5579686.

  Citation
  Keesara.Sravanthi, A. Srinivas, G. Narsing Rao, T. Raghu, P. Rakesh, "A Novel Based Approach to Detect and Take Action Against Network Intrusion in Virtual Machine Network System," International Journal of Scientific Research in Network Security and Communication, Vol.8, Issue.4, pp.10-13, 2020