Volume-10 , Issue-1 , Mar 2022, ISSN 2321-3256 (Electronic Version) Go Back

• Open Access   Article

  Application of Shell Model Calculations with Modified Surface Delta Interaction For the Two Nuclei

  N.G. Alhoulami

  Research Paper | Journal (IJSRNSC)

  Vol.10 , Issue.1 , pp.1-5, Mar-2022

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  Abstract
  By applying Shell model with Modified Surface Delta Interaction on Tellurium nucleus and Tin nucleus , that have two valence nucleons outside the closed core , we obtained the values of the energy levels and excitation energies of the two nuclei, after determining the value of the two constants and for Modified Surface Delta Interaction by least square fitting method. When we comparing the value of standard deviation of our calculated excitation energies with some previous studies calculated in different ways, we found that nucleus shows good agreement with experimental values compared to these studies, while nucleus does not show a good agreement. Therefore the application of the Shell model with Modified Surface Delta Interaction, in its present form, on nuclei whose valence nucleons are located after the magic number N = 82, needs to be modified, such as taking into account the excitation closed core and configuration mixing.

  Key-Words / Index Term
  Shell Model, Modified Surface Delta Interaction, closed core, Valance Space.

  References
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  [7] H. Wattar, M. Farah and N. Alhoulami, "Excited States and Beta Decay for 58Cu 58Zn and 58Cu Calculated Using Shell Model and BCS Theory". International Journal of Scientific & Engineering Research, Vol. 8, Issue.1, pp. 1-7, 2017
  [8] M. Honma, T. Mizusaki, and M. Hjorth-Jensen,"New effective interaction for f5 pg9-shell nuclei". PHYSICAL REVIEW C, Vol. 064323, pp. 1-36, 2009.
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  [13] A.K. Alfatlawi, "Shell Model Description for Some Nuclei Around Double Magic Nucleus 132Sn", International Journal of Current Research, Vol. 8, Issue. 6, pp. 1-5, 2016.
  [14] B. Larson,"T he S tructure of The Ighter N = 82 ". Nuclei Physical Etters, Vol.37B, Issue. 3, pp. 266-268, 1971.
  [15] R. M. Ramadhan, and A. A. Al-Rabeia, "Calculation the Electromagnetic Properties of 134Sn ", Nucleus Basrah Journal of Science ( A ), Vol. 53, Issue. 1, pp. 61 - 27. 2017.

  Citation
  N.G. Alhoulami, "Application of Shell Model Calculations with Modified Surface Delta Interaction For the Two Nuclei," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.1, pp.1-5, 2022

• Open Access   Article

  Real-Time Monitoring and Smart Transformer Protection by Using IoT

  Satyajit S. Chopade

  Research Paper | Journal (IJSRNSC)

  Vol.10 , Issue.1 , pp.6-10, Mar-2022

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  Abstract
  Transformers is the basic design of the electrical device which provides power transmission by transforming induced current from one circuit to another. The induced current can be converted step up or step down of current or voltage. This application mainly concentrates on the distribution as well as power transformers which are used in between the electrical Power system. Real-time monitoring and protection are done for basic features like oil level, temperature, over-voltage, over-current, under-voltage, maintenance, etc. These features are essential for effective power transmission and the long life of transformers. The monitoring and protection of the transformer are done by using an ATmega16L microcontroller, IoT, and sensors which check the level of oil, over-voltage, smoke detect and maintain temperature by continuous real-time monitoring. There are various transformer maintenance techniques, but this kit gives real-time monitoring and control of transformers by using the ATmega16L microcontroller. The design is to sense the parameters of the transformer and send the parametric information regularly to the control room. So, this design makes it possible to attain real-time protection and monitoring by using IoT. This project gives us an efficient system as well as we are connected all the power system transformers online for regular monitoring and get uninterrupted power supply to the consumer.

  Key-Words / Index Term
  Transformer, Faults, Protection, Inrush Current, Relay, IOT module, Monitoring & protection, microcontroller.

  References
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  [8]. Kasztenny, B.; Kezunovic, M.; “An Improved Transformer Inrush Restraint Algorithm”, Computer Applications in Power, IEEE, Volume: 11, Issue: 4, pp: 39 – 45, Oct. 1998.
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  [10]. Piyali Sarkar, Sandhya Upreti, Sumeet Singh, “Study on methods of transformer protection”, Dronacharya college of engineering, Haryana, India, 2014 IJIRT.
  [11]. REAL-TIME MONITORING AND CONTROLLING TRANSFORMER, by S. Dharanya, M. Priyanka, R. Rubini, A. Umamakeswari, Journal Of Artificial Intelligence ISSN 1994-5450/DOI: 10.3923
  [12]. Transformer Protection And Parameters Monitoring, by Nitesh Saroha, Anil Kumar Suthar, Moses Lalbiaknunga, Prof. S. B. Patil, International Research Journal Of Multidisciplinary Studies & Sppp`s, Karmayogi Engineering College, Pandharpur Organize National Conference Special Issue March 2016, Vol. 2, Special Issue 1, March 2016. ISSN (Online): 2454-8499 Impact Factor: 1.3599(GIF), 0.679(IIFS)
  [13]. Simulation of Power Transformer Protection Using Microcontroller Relay, by Arpit Rana, Jeet Shah, Anuradha Deshpande, International Journal of Scientific Engineering and Technology ISSN: 2277- 1581 Volume No.4 Issue No.6, pp: 352-355 01 June 2015.

  Citation
  Satyajit S. Chopade, "Real-Time Monitoring and Smart Transformer Protection by Using IoT," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.1, pp.6-10, 2022

• Open Access   Article

  Air Quality Measurement: Digital Dashboard Using Smartphone

  R. Deepalakshmi, R. Vanitha, M. Shivashankari, J. Jeyarani, S. Shanthi

  Research Paper | Journal (IJSRNSC)

  Vol.10 , Issue.1 , pp.11-16, Mar-2022

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  Abstract
  — In cities all over the globe are transforming into smart cities. Smart cities initiatives need to address environmental concerns such as air pollution to provide clean air. A scalable and cost-effective air monitoring system is imperative to monitor and control air pollution for smart city development. Air pollution has notable effects on the well-being of the population a whole, global atmosphere, and worldwide economy. This paper presents a scalable smart air quality monitoring system with low cost sensors and long-range communication protocol. The sensors collect four parameters, temperature, humidity, dust and carbon dioxide in the air. The proposed end-to-end system has been implemented and deployed in Yangon, the business capital of Myanmar, as a case study since Jun 2018. The system allows the users to log in to an online dashboard to monitor the real-time status. In addition, based the collected air quality parameters for the past two months, a Machine Learning model has been trained to make predictions of parameters such that proactive actions can be taken to alleviate the impacts from air pollution.

  Key-Words / Index Term
  Temperature, Humidity, Dust and Carbon dioxide, Machine Learning omponent, Formatting, Style, Styling, Insert

  References
  [1] S. Chowdhury, M. S. Islam, M. K. Raihan and M. S. Arefin, "Design and Implementation of an IoT Based Air Pollution Detection and Monitoring System," 5th International Conference on Advances in Electrical Engineering (ICAEE), pp. 296-300, 2019.
  [2] Yamunathangam, K. Pritheka, P. Varuna , “IOT Enabled Air Pollution Monitoring and Awareness Creation System”, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-7 Issue-4S, November 2018.
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  [6] Gyu-Sik Kim, Youn-Suk Son, Jai-Hyo Lee, In-Won Kim, Jo-Chun Kim, Joon-Tae Oh and Hiesik Kim, "Air Pollution Monitoring and Control System for Subway Stations Using Environmental Sensors," Hindawi Publishing Corporation Journal of Sensors Volume 2016, Article ID 1865614, 10 pages, 2016.
  [7] S. S. Alam, A. J. Islam, M. M. Hasan, M. N. M. Rafid, N. Chakma and M. N. Imtiaz, "Design and Development of a Low-Cost IoT based Environmental Pollution Monitoring System," 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT), Dhaka, Bangladesh, 2018, pp. 652-656, 2018.
  [8] A. J. Islam, M. M. Farhad, S. S. Alam, S. Chakraborty, M. M. Hasan, and M. S. B. Nesar. Design, Development and Performance Analysis of a Low-Cost Health-Care Monitoring System using an Android Application. International Conference on Innovations in Science, Engineering and Technology (ICISET), Chittagong, pp. 1-6, 2018.
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  [10] V. Barot and V. Kapadia, "Air Quality Monitoring Systems using IoT: A Review," 2020 International Conference on Computational Performance Evaluation (ComPE), pp. 226-231, 2020.
  [11] Neri, Giovanni and Donato, Nicola,” Resistive Gas Sensors” in Wiley Encyclopedia of Electrical and Electronics Engineering: American Cancer Society, pp. 1-12, 2016.
  [12] R. Baron and J. Saffell, "Amperometric gas sensors as a low-cost emerging technology platform for air quality monitoring applications: A review," in ACS sensors, vol. 2, no. 11, pp. 1553- 1566, 2017.
  [13] Firdhous, M.; Sudantha, B.; Karunaratne, P. IoT enabled proactive indoor air quality monitoring system for sustainable health management. In Proceedings of the 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), Chennai, India, 23–24 IEEE: Piscataway, NJ, USA, 2017; pp. 216–221, February 2017.
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  [15] P. M. Linh and T. Kim, "A Study of the Z-Wave Protocol: Implementing Your Own Smart Home Gateway", 2018 3rd International Conference on Computer and Communication Systems (ICCCS), pp. 411-415, 2018.
  [16] B. Maag, Z. Zhou and L. Thiele, "A Survey on Sensor Calibration in Air Pollution Monitoring Deployments", IEEE Internet of Things Journal, vol. 5, no. 6, pp. 4857-4870, Dec. 2018.
  [17] F Karagulian, M Barbiere, A Kotsev, L. Spinelle, M. Gerboles, F. Lagler, et al., "Review of the Performance of Low-Cost Sensors for Air Quality Monitoring", Atmosphere, vol. 10, no. 9, pp. 506:1-506:41, 2019.
  [18] A. Boubrima, W. Bechkit and H. Rivano, "Optimal WSN Deployment Models for Air Pollution Monitoring", IEEE Transactions on Wireless Communications, vol. 16, no. 5, pp. 2723-2735, May 2017.
  [19] M. Y. Thu, W. Htun, Y. L. Aung, P. E. E. Shwe and N. M. Tun, "Smart Air Quality Monitoring System with LoRaWAN", IEEE International Conference on Internet of Things and Intelligence System (IOTAIS), pp. 10-15, 2018
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  Citation
  R. Deepalakshmi, R. Vanitha, M. Shivashankari, J. Jeyarani, S. Shanthi, "Air Quality Measurement: Digital Dashboard Using Smartphone," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.1, pp.11-16, 2022

• Open Access   Article

  Optimizing Resource Utilization in Cloud Networks: An Analysis of VM Selection and Placement Policies

  Vikas Mongia

  Research Paper | Journal (IJSRNSC)

  Vol.10 , Issue.1 , pp.17-20, Mar-2022

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  Abstract
  Cloud computing enables on-demand computing, providing users with elastic resources on a pay-as-you-go basis. The proliferation of data-driven applications and services has led to increased demand for computational resources, prompting the deployment of large data centers that consume significant amounts of energy and emit CO2 into the environment. As VM placement and selection significantly impact energy consumption, this paper explores various benchmark algorithms for VM selection and placement policies, evaluating their performance based on SLA violations, energy consumption, and the number of migrations. The study utilizes the cloudsim toolkit and analyzes real workloads from the CoMon project.

  Key-Words / Index Term
  Energy efficiency, VM selection, VM placement, service level agreement, number of migrations

  References
  [1] Beloglazov, A., & Buyya, R, “Energy efficient resource management in virtualized cloud data centers,” Proceedings of the IEEE/ACM international conference on cluster, cloud and grid computing, pp. 826-831,2010.
  [2] Koot M, Wijnhoven F. Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy. 2021 Jun 1;291:116798.
  [3] C. Belady, “Projecting Annual New Datacenter Construction Market Size,” no. March, 2011.
  [4] M. Mills, “The Cloud begins with Coal: Big data, big networks, big infrastructure, and big power.,” vol. 1387, no. 2006,pp. 407–436, 2013.
  [5] K.Kawamoto, et.al., "Electricity used by office equipment and network equipment in the U.S.: Detailed Report and Appendices" , Lawrence Berkeley National Laboratory, Berkeley, CA. 2000.
  [6] J.M.Jackson, et.al., " National and regional implications of internet data center growth", Resources, Conservation, and Recycling (also LBNL50534) , pp. 175–185,2002
  [7] K.Roth, et.al., "Energy Consumption by Office and Telecommunications Equipment in Commercial Buildings", vol I: Energy Consumption Baseline. Washington,DC, 2002
  [8] A. Beloglazov and R. Buyya, “Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers,” John Wiley Sons, Ltd, pp. 1397 1420, 2012.
  [9] A. Beloglazov, et.al., “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, ”Software: Practice and Experience, vol. 41, no.1, pp.23–50,2011.
  [10] PlanetLab,http://planet-lab.org/.
  

  Citation
  Vikas Mongia, "Optimizing Resource Utilization in Cloud Networks: An Analysis of VM Selection and Placement Policies," International Journal of Scientific Research in Network Security and Communication, Vol.10, Issue.1, pp.17-20, 2022