Journal Vol – 15 No -8, August 2020

Abstract:

COVID-19, caused by a coronavirus, has led to a pandemic that threatens everyone. Everyone in the world is worrying about COVID-19 (Corona Virus Disease-19). In late December 2019 an unidentified Corona virus, currently named as COVID-19 emerged from Wuhan, China. In this paper a brief description is given on Corona virus, its effects, safety measures and various modes of transmission of virus. A comparative study also done on the situation and safety measures of various countries to control the pandemic. In our study, it is observed that this virus is not a living organism and it has a genetic material inside an envelope. It is covered with the fat envelope known as lipid envelope. There are two different types of viruses namely Endemic and Pandemic. Endemic is something belongs to a particular people or country where as Pandemic is an epidemic that spread’s over different countries and continents. An Epidemic is a disease which affects a large number of populations within the region. Many researchers are working on these viruses. Corona virus is an Epidemic initially as it was born in Wuhan, China but its geographical Spread turned it as Pandemic declared by World Health Organization (WHO)[XIII]. 200 plus countries effected with this Virus. Long ago the similar kind of RNA sequences was circulated in Bats also known as SARS- COV (1) which created severe acute respiratory problems to the victim. After few years another virus MERS- COV was identified[XVIII, XV].

Keywords:

Corona Virus,COVID 19,Respiratory Syndrome,corona effects,Transmission of corona,effects of corona,

Refference:

I. Casanova, L. M., Jeon, S., Rutala, W. A., Weber, D. J., & Sobsey, M. D. (2010). Effects of Air Temperature and Relative Humidity on Coronavirus Survival on Surfaces. Applied and Environmental Microbiology, 76(9), 2712–2717.
II. Chang MH, Wu HH, Shih CI, et al. Association between influenza vaccination and reduced risks of major adverse cardiovascular events in elderly patients. Am Heart J 2017; 193:1–7.
III. Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., … Zhang, L. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.
IV. Cohen, J., & Kupferschmidt, K. (2020, March 20). Countries test tactics in ‘war’ against COVID-19. Retrieved April 1, 2020.
V. Di Pasquale G. Coronavirus COVID-19: quali implica- zioniperlacardiologia?GItalCardiol2020;21:243–245.
VI. Doremalen, N. V., Bushmaker, T., Morris, D. H., Holbrook, M. G., Gamble, A., Williamson, B. N., … Munster, V. J. (2020). Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1. New England Journal of Medicine.
VII. Grady, D. (2020, February 6). China Begins Testing an Antiviral Drug in Coronavirus Patients. Retrieved February 11, 2020.
VIII. Griffiths, J. (2020, January 27). Wuhan coronavirus: Thousands of cases confirmed as China goes into emergency mode. Retrieved April 1, 2020.
IX. Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., … Zhong, N.-S. (2020). Clinical characteristics of 2019 novel coronavirus infection in China.
X. Holshue, M. L., Debolt, C., Lindquist, S., Lofy, K. H., Wiesman, J., Bruce, H., … Pillai, S. K. (2020). First Case of 2019 Novel Coronavirus in the United States. New England Journal of Medicine.
XI. Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., … Cao, B. (2020). Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.
XII. Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., … Feng, Z. (2020). Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. New England Journal of Medicine.
XIII. Munster VJ, Koopmans M, van Doremalen N, et al. A novel coronavirus emerging in China — key questions for impact assessment. N Engl J Med 2020; 382(8):692–694.
XIV. Pittet D, Allegranzi B and Boyce J. The World Health Organization guidelines on hand hygiene in health care and their consensus recommendations. Infect Control Hosp Epidemiol 2009; 30:611–622.
XV. Song, Z., Xu, Y., Bao, L., Zhang, L., Yu, P., Qu, Y., … Qin, C. (2019). From SARS to MERS, Thrusting Coronaviruses into the Spotlight. Viruses, 11(1), 59.
XVI. Tapiwa, G., Cécile, K., Dongxuan, C., Andrea, T., Christel, F., Jacco, W., and Niel, H., Estimating the generation interval for COVID-19 based on symptom onset data.
XVII. Tindale, L., Coombe M., Stockdale, J., Garlock, E., Lau W., Saraswat M., … Colijn, C. (2020). Transmission interval estimates suggest pre-symptomatic spread of COVID-19.
XVIII. Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus- infected pneumonia in Wuhan, China. JAMA 2020. Epub ahead of print, 7th February 2020. DOI: 10.1001/ jama.2020.1585.
XIX. Wang, M., Cao, R., Zhang, L. et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res (2020).
XX. Wu, J. T., Leung, K., & Leung, G. M. (2020). Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.

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Abstract:

Novel Corona virus disease (COVID-19) is an infectious disease caused by severe acute respiratory syndrome corona virus 2. It was first identified in the month of December in the year 2019.It was identified in Wuhan, China and spreading globally and there has been no ending yet. It has been spread to all over world and in the month of January, 2020 it has reached India and started spreading. Initially the Government of India has not expected the huge cases further, but due to rapid growth of heavy cases, the government of India has started lock down in the month of March with curfew on March 22, 2020. Total 6 lockdowns have been announced from March 25^th to 31^st Julywith drastic changes and twenty four reports given to Indian government by World Health Organization regarding COVID-19. Government of India could saturate the panic situations bringing social awareness among people saying preventive measures to be taken, in spite where few people could suffer during migrating. The leading role fellows during COVID-19 period also affected with COVID is the most panic situation India faced whereby Indian Government has taken a strong decision on 7^th June, 2020 that the COVID patients had to stay at home and take the treatment themselves. Social distancing among the public in all places, wearing masks and using sanitizers found the main preventive measures for the controlling of Corona virus. The total number of cases registered in India was 10.5 Lakhs as on 18-07-2020.

Keywords:

COVID-19,corona virus,W.H.O,Migrants,Indian Government,Lockdown,Affect,

Refference:

I. C.Wang,Horby PW,Hayden FG, Gao GF.A novel corona virus outbreak of global health concern Lancet.2020.https://doi.org/10.1016/S0140-6736(20)30185-9.

II. C Huang, Wang Y,LiX,et al.Clinical features of patients infected with 2019.

III. D,Xu V.Chang H,Rebaza A,Sharma L,Dela Cruz CS.Protecting health-care workers from subclinical coronavirus infection.Lancet Respir Med.2020.https://doi.org/10.1016/S2213-2600(20)30066-7

IV. Richman DD,Whitley RJ, Hayden FG.Clinical Virology, 4th ed.Washington:ASM Press;2016.

V. Xinha.China’s CDC detects a large number of new corona viruses in the South China seafood market in Wuhan. Available at:https://www.xinhuanet.com/202001/27/c_1125504355.htm.Accessed20 Feb2020.

VI. Jump up to:Gettleman,Jeffrey;Schultz,Kai(24 March 2020).”Modi Orders 3-Week Total Lockdown for All 1.3 Billion Indians”. The New York Times.ISSN 0362-4331.

VII. ”Close Schools, all religious activities, extend lockdown: states tell Centre”. India Today. 7 April 2020.

VIII. Jump up to:”PM Modi announces extension of lockdown till 3 May.”Live mint 14 April 2020.

IX. A 2 More Weeks of Lockdown starting May 4”.NDTV.com.Retrieved 1 May 2020.

X. “Centre extends nationwide lockdown till May 31, new guidelines issued”.Tribuneindia News Service. 17 May 2020.Retrieved 17 May 2020.

XI. Jump up to: Sharma, Neeta (30 May 2020). Ghosh Deepshikha(ed.).””Unlock1”.Malls, Restaurants, Places of Worship to reopen June 8”.NDTV.Retrieved 30 May 2020.

XII. https://www.who.int/docs/default-source/wrindia/india-situation-report-1.pdf?sfvrsn=5ca2 a672_0.

XIII. https://www.who.int/docs/default-source/wrindia/india-situation-report-2.pdf?sfvrsn=962f 294b 0.
XIV. https://www.who.int/southeastasia/outbreaks-amd-emergencies/novel-coronavirus-2019/ protective-measures/stay-healthy-at-home.

XV. https://www.poynter.org/?ifcn_misinformation=putin-has-stated-russian-citizens-have -2-options-stay-home-for-15-days-or-in-jail-for-5-years.

XVI. https://en.wikipedia.org/wiki/Aarogya_Setu.

XVII. https://en.wikipedia.org/wiki/Indian_migrant_workers_during_the_COVID-19_pandemic.

XVIII. https://www.wsj.com/articles/worse-than-a-war-zone-covid-19-batters-indias-mumbai-city-11591531201.

XIX. https://www.ap7am.com/lv-330689-198-variants-of-coronavirus-identified-in-india.

XX. https://www.deccanchronicle.com/nation/in-other-news/050620/heres-how-doctors-are-being-put-to-risk-in-telangana-im-one-of-48-p.html.

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Abstract:

The study investigated variational inequality of the elliptic to the second type of "A Simplified Friction Problem". The operator of the second arrangement partial differential was coupled within elliptic variational inequality. It gives the mathematical and physical demonstration and some characteristics of the solution. The study highlighted the presence, singularity and the second type of EVI solutions characteristic.

Keywords:

Variational inequality,EVI first type,EVI second type,Friction Problem,Convex series,

Refference:

I. Armstrong-Hélouvry, Brian (1991). Control of machines with friction. Springer .
II. Brezis,H.(1968), Equations et Inequations Non Lineaires dans les EspacesVectorielsenDualite. Ann.Inst.Fourier,vol.18,pp. 115-175.
III. Dowson, Duncan (1997). History of Tribology, 2nd Edition. Wiley; 2 edition (March 6, 1998).
IV. J. L. Lions and G. Stampacchia.(1967), variational Inequalities, comm.on Pure and Applied Math., Vol XX, PP.493-519.
V. M. Chipotand G., Michaille, (1989), Uniqueness results and monotonicity properties for strongly nonlinear elliptic variational inequalities, AnnalidellaScuolaNormaleSuperiore di Pisa,4(16), pp. 137-166.
VI. Meriam, J. L and L. G. Kraige. (2002), Engineering Mechanics (fifth ed.). John Wiley & Sons.
VII. R. C. Hibbele, (2007). Engineering Mechanics, (Eleventh ed.). Pearson, Prentice Hall.
VIII. Ruina, Andy and Rudra Pratap (2002). Introduction to Statics and Dynamics. Oxford univiristy press.
IX. Stuart S. Antman,(1983),” The Influence of Elasticity in Analysis :Modern Developments”, American Mathematical society 9 (3), pp 267-291.
X. Van Beek, Anton. “History of Science Friction”. tribology-abc.com.

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Abstract:

Surveys and statistics showing majority of rural areas and remote places in third world countries are far from accessing electricity and facing power shortage. One important reason for this circumstance is power generating plants distant from rural areas. Despite of AC utility grid most of the loads requires power converters to obtain regulated DC. Also power conversions required in DC grids are less when compared with AC grids. Abundant Renewable energy like solar photovoltaic has potential to provide solution for the rural electrification through DC micro grid. This article presents the design, analysis and simulation of photovoltaic based DC micro grid system with low cost DC household which is not connected to utility Grid. The proposed system suited for running approximately 125 watts loads useful for daily routine. The Proposed system utilizes Boost converter as front-end converter to regulate required DC bus voltage for forming DC micro grid. Fly-back converter is used as point of load converters to meet different load specifications. Simulation study of the proposed system is done in PSIM 9.0.

Keywords:

DC micro-grid,Rural Electrification,Solar,Photovoltaic,Front-end Converter,POL Converter,

Refference:

I. A.Sieminski, A. Annual Energy Outlook 2015; US Energy Information Administration: Washington, DC, USA, 2015.
II. Chandel, S.S.; Shrivastva, R.; Sharma, V.; Ramasamy, P. Overview of the initiatives in renewable energy sector under the national action plan on climate change in India. Renew. Sustain. Energy Rev. 2016, 54, 866–873. [Cross Ref]
III. Devendra Patil, Akshay K. Rathore, Dipti Srinivasan, and Sanjib K.Panda, High Frequency Soft-switching LCC Resonant Current-fed DC/DC converter with High Voltage Gain for DC Microgrid Application , 40th Annual Conference of the IEEE Industrial Electronics Society, 2014, pp. 4293 – 4299.
IV. Global Buildings Performance Network. Residential Buildings in India: Energy Use Projections and Savings Potentials; Global Buildings Performance Network: Ahmedabad, India, 2014.
V. Hussain Athab, Amirnaser Yazdani, and BinWu, A Transformerless DC–DC Converter With Large Voltage Ratio for MV DC Grids, IEEE Transactions On Power Delivery 29(4) (2014).
VI. Jhunjhunwala, A.; Aditya, L.; Prabhjot, K. Solar-dc microgrid for Indian homes: A transforming power scenario. IEEE Electrif. Mag. 2016, 4, 10–19. [Cross Ref]
VII. Kaur, P.; Jain, S.; Jhunjhunwala, A. Solar-DC deployment experience in on-grid and near on-grid homes: Economics, technology and policy analysis. In Proceedings of the IEEE First International Conference on DC Microgrids (ICDCM), Atlanta, GA, USA, 7–10 June 2015; pp. 26–31.
VIII. Loomba, P.; Asgotraa, S.; Podmore, R. DC solar microgrids—A successful technology for rural sustainable development. In Proceedings of the IEEE PES Power Africa, Livingstone, Zambia, 28 June–2 July 2016; pp. 204–208.
IX. Li, W.; Mou, X.; Zhou, Y.; Marnay, C. On voltage standards for DC home microgrids energized by distributed sources. In Proceedings of the 7th International Power Electronics and Motion Control Conference (IPEMC),Harbin, China, 2–5 June 2012; Volume 3, pp. 2282–2286.
X. Makarabbi, G.; Gavade, V.; Panguloori, R.B.; Mishra, P.R. Compatibility and performance study of home appliances in a DC home distribution system. In Proceedings of the IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Mumbai, India, 16–19 December 2014.
XI. Nilsson, D.; Sannino, A. Efficiency analysis of low and medium-voltage DC distribution systems. In Proceedings of the Power Engineering Society General Meeting, Denver, CO, USA, 6–10 June 2004; pp. 2315–2321.
XII. Otero, R.; Angel, M. Power quality issues and feasibility study in a DC residential renewable energy system. Mast. Abstr. Int. 2009, 47
XIII. PongsakornSintupatsuk,SurinKhomfoi, and PrapartPaisuwanna, A dc to dc Multilevel Modular Capacitor Clamped Converter with Electrical Grounding Isolation and Bidirectional Power Flow for a dc Microgrid Application, 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2012, pp. 1 – 4
XIV. Panguloori, R.B.; Mishra, P.R.; Boeke, U. Economic viability improvement of solar powered Indian rural banks through DC grids. In Proceedings of the Annual IEEE India Conference (INDICON), Hyderabad, India, 16–18 December 2011.
XV. Rajesh, M.P.; Pindoriya, N.M.; Rajendran, S. Simulation of DC/DC converter for DC nano-grid integrated with solar PV generation. In Proceedings of the IEEE Innovative Smart Grid Technologies-Asia (ISGT ASIA), Bangkok, Thailand, 3–6 November 2015.
XVI. Rodriguez-Diaz, E.; Vasquez, J.C.; Guerrero, J.M. Intelligent DC homes in future sustainable energy systems: When efficiency and intelligence work together. IEEE Consum. Electron. Mag. 2016, 5, 74–80. [Cross Ref]
XVII. Rodriguez-Otero, M.A.; O’Neill-Carrillo, E. Efficient home appliances for a future DC residence. In Proceedings of the IEEE Energy 2030 Conference, Atlanta, GA, USA, 17–18 November 2008; pp. 1–6.
XVIII. Starke, M.; Tolbert, L.M.; Ozpineci, B. AC vs. DC Distribution: A loss comparison. In Proceedings of the IEEE/PES Transmission and Distribution Conference and Exposition, Chicago, IL, USA, 21–24 April 2008; pp. 1–7.
XIX. Sungsik Park, and Sewan Choi, Soft-Switched CCM Boost Converters With High Voltage Gain for High-Power Applications, IEEE Transactions On Power Electronics 25 (5) (2010).

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Abstract:

Nowadays,cloud computing services have been an embracing computing technology by some organisations, academia and entrepreneurs.Cloud Service Providers (CSP) are constrained to specific resources, missing some of the resources their clients need;this triggers the need for many and specific interconnections of homogeneous or heterogeneous computing clouds by their protocols and architectures to interoperate and share available resources among them. Clouds interconnection can be with various functions and schemes. In this study, we deployed exploratory and Design Science research approaches and Cloud-Analyst to simulate interconnections and interoperability within heterogeneous cloud service providers. The study cannot be conducted with real cloud computing environments due to the high cost that may incur and authorizations from CSPs that may not be secured. In this paper, we built a system and algorithm that can handle the variability and complexities of the different clouds during the management of inter-cloud resources. The experiment result shows that the USER-BASE (UB1) can subscribe to Data Center1(DC1) through Data Center 3 (DC3) that it initially subscribed with average time 301.05 with insignificant differences when utilizing resources from Data Center 3 (DC3).

Keywords:

Cloud Resources,Clouds Heterogeneity,Algorithm,Cloud Service Providers,

Refference:

I.Aslam, S., & Shah, M. A. (2016). Load balancing algorithms in cloud computing: ASLMAA survey of modern techniques. In 2015 National Software Engineering Conference, NSEC 2015 (pp. 30–35). https://doi.org/10.1109/NSEC.2015.7396341
II. Demchenko, Y., Turkmen, F., Laat, C. De, & Slawik, M. (2017). Defining Intercloud Security Framework and Architecture Components for Multi-Cloud Data Intensive Applications, 945–952. https://doi.org/10.1109/CCGRID.2017.144
III. Garrison, C. p. (2010). Digital forensics for network, internet and cloud computing. Elsevier Inc.
IV. Ghomi, E. J., & Rahmani, A. M. (2017). Load-balancing algorithms in cloud computing : A survey. Journal of Network and Computer Applications, 88 (March), 50–71. https://doi.org/10.1016/j.jnca.2017.04.007
V. Goudarzi, Z., & Faraahi, A. (2014). Effective load balancing in cloud computing. International Journal of Intelligent Information Systems, 3 (6), 1–9. https://doi.org/10.11648/j.ijiis.s.2014030601.11
VI. Hwang, J., Wu, S. Z. and F. y, & Wood, T. (2013). Benefits and Challenges of Managing Heterogeneous Data Centers. In 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013) (p. 7).
VII. Joshi, R. (2018). Study and Comparison of VM Scheduling Algorithm in Cloud Computing Using CloudSim Simulator. International Journal for Research in Applied Science and Engineering Technology, 6 (5), 1751–1757. https://doi.org/10.22214/ijraset.2018.5285
VIII.Kanungo, P. (2016). Design Issues in Federated Cloud Architectures. International Journal of Advanced Research in Computer and Communication Engineering, 5 (5), 937–939. https://doi.org/10.17148/IJARCCE.2016.55229
IX. Kuechler, B., & Petter, S. (2004). DESIGN SCIENCE RESEARCH IN INFORMATION SCIENCE.
X. Makwe, A., & Kanungo, P. (2016). A Survey of Scheduling Policies in Cloud Computing Environment. International Journal of Computer Trends and Technology, 34 (4), 169–173. https://doi.org/10.14445/22312803/ijctt-v34p131
XI. Prajapati, K., Raval, P., Karamta, M., & Potdar, M. (2013). Comparison of Virtual Machine Scheduling Algorithms in Cloud Computing. International Journal of Computer Applications, 83 (15), 12–14. https://doi.org/10.5120/14523-2914

XII. Singh, A. (2015). A Review on Existing Load Balancing Techniques in Cloud Computing. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 4 (7), 16–24. https://doi.org/10.5120/ijca2015905539
XIII. Smit, M., Simmons, B., & Litoiu, M. (2013). Distributed , Application-level Monitoring for Heterogeneous Clouds using Stream Processing.
XIV. Thakur, P., & Shrivastava, D. K. (2015). Interoperability Issues and Standard Architecture for Service Delivery in Federated Cloud : A Review. In ks 2015 International Conference on Computational Intelligence and Communication Networks (pp. 908–912). https://doi.org/10.1109/CICN.2015.179
XV. Toosi, A. N., Calheiros, R. N., & Buyya, R. (2014). Interconnected Cloud Computing Environments: Challenges, Taxonomy, and Survey. ACM Computing Surveys, 47 (7), 57.

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Abstract:

Adders are the fundamental building blocks for any digital processors in VLSI design. Thepropagation delay should be low for high level applications and thus the speed is depends on the propagation delay of the full adders.Hence, the efficientdesign of the full adder is one of the major concerns in fulfilling the requirements of latest applications. As there is lot of research is carrying on full adder designs, still there is a scope of improvement. This paper aimed at design of high performance Carry Save Adder (CSA) using a modified 1-bit full adder. Initially, the basic building blocki.e., a full adder is discussed using existing and proposed Modified Gate Diffusion Input (Modified GDI) techniques. Later, by using this proposed adder the CSA have been designed and compared its performance with respect to speed, Power dissipation and area. All the proposed designs are designed in mentor graphics tools at 90nm technology.

Keywords:

1-bit full adder,Carry Save Adder,Gate Diffusion Input,Power Dissipation,Propagation Delay,

Refference:

I. Morgenshtein A. Fish, I.A. Wagner. “GateDiffusion Input (GDI) – A Power Efficient Method forDigital Combinational Circuits”, IEEE Transactions on VLSI, Vol.10, No. 5, pp 566-581(2002).

II. Pinninti Kishore, P.V. Sridevi, K. Babulu, “LowPower and Optimized Ripple Carry Adder and CarrySelect Adder Using MOD-GDI Technique”,Proceedings of Microelectronics, Electromagneticsand Telecommunications, Lecture Notes in ElectricalEngineering, Springer India. pp 159-171(2016).

III. Kiat -Seng Yeo, Kaushik Roy, “Low -Voltage,Low- Power VLSI Subsystems” Tata McGraw-HilEdition, pp. 83-85(2009).

IV. T.Kim, W. Jao, S. Tjiang, “Arithmeticoptimization using carry save adders”, Proceedings of Designautomation Conference, pp 433-438(1998).

V. T. Kim, W. Jao, S.Tjiang, “Circuitoptimization using carry saver adder cells”, IEEETransanctions on Computer Aided design of integrated circuitsand systems, Vol. 17, No. 10, pp 974-984(1998).

VI. Pinninti Kishore, P.V. Sridevi, K. Babulu, K.S.Pradeep Chandra, “A Novel Low Power andArea Efficient Carry-Lookahead Adder using Mod-GDI Technique”, International Journal of Scientificand Research, Vol. 4, No. 5, pp 1205-1210(2015).

VII. S. Hanson, B. Zhai, K. Bernstein, D. Blaauw, A.Bryant, L. Chang, K. K. Das, W. Haensch, E. J Nowak, D. Sylvester, “Ultralow-voltage,minimum-energy CMOS”, IBM Journal of Researchand Development, Vol. 50, No.5, pp 469-490(2006).

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Abstract:

Laser drilling is one of the earliest applications of lasers in materials processing. Less than 0.25mm in diameter is difficult to drill mechanically. Laser drilling offers good choices for small hole drilling, especially for hard and brittle materials, such as ceramics, but cracks appearance is one of the most difficulties that appears in this drilling. Therefore, this paper aims to study the effect of exposure time on the drilling of soda lime glass (SLG) using under water laser drilling technique. A 1.15 mm thickness SLG sheets were immersed 1mm below the water surface, then irradiated with CW CO₂ laser. The laser parameters used were (24, 25 and 26) W power, (5, 7.5 and 10) sec exposure time and (1, 2and 3) pulses. The drilled points were investigated under optical transmission microscope. Then the upper diameter, lower diameter, crack length and taper angle for these drilled holes were measured by analyzing the OM images using ImageJ software. Clearly appeared that hole diameter and the crack lengths could be controlled by the laser power and exposure time. When power or time were increased, the hole diameter increased. While the length of cracks is increased with increasing time and power. The good results found at laser power 24 W, five sec. and one pulse for hole diameter, while the minimum crack length was found at three pulses, five sec. and 24 W power.

Keywords:

Laser Drilling,Soda Lime Glass,Brittle Materials Drilling,Under Water Laser Process,CO₂ Laser,

Refference:

I. Asibu, E. (2009). Principles of Laser Materials Processing (Vol. 4). New Jersey, Canada: John Wiley & Sons.
II. B.Nafissa, & A.walid. (2015, september 28). Optimization of Parameters CO2 Laser for Drilling Different Types of Glass. new journal of glass and ceramics, 5, 87-83.
III. Corcorn A, S. L. (2002). “The Laser drilling of multi-layer aerospace material systems. Journal of materials systems, 123(1), 100-106.
IV. E. Kacar, M. M. (2009, April 25). Characterization of the drilling alumina ceramic using Nd:YAG pulsed laser. Journal of Materials Processing Technology, 209, 2008-2014.
V. Fenga, W., Guob, J., Yana, W., Wana, Y. C., & Zhenga, H. (2019, February 16). Deep channel fabrication on copper by multi-scan underwater laser machining. Optics and Laser Technology, 111, 653-663.
VI. Maini.K.A. (2013). Lasers and Optoelectronics;Fundamentals,Devices and Applications. United Kingdom: John Wiley &Sons.
VII. Ogura, H., & Yoshida, Y. (2003, May). Hole Drilling of Glass Substrates with a CO2 Laser. Jpn. J. Appl. Phys., 42(Part 1, 5A), 2881–2886.
VIII. Richard . H, J. .. (1998). Laser Ablation and Desorption (Vol. 30). San Diego, USA: Academic Press.
IX. Sun, X., Zhou, J., Duan, J.-A., D, H., & Cui., D. (2018, November 27). Experimental research on ultrasound-assisted under water femtosecond laser drilling. Cambridge University Press, 36, 487-493.
X. Sushant. D, N. S. (2006). A review on laser drilling and its techniques. International Conference on Advances in Mechanical Engineering (AME 2006). Fatehgarh Sahib , Pungab , India.
XI. Tsai, C., & Li, C. (2009, june 22). Investigation of underwater laser drilling for brittle substrates. Journal of materials processing technology, 2838_2846.
XII. Yoshiki.K. (2017). High-aspect ratio laser drilling of glass assisted by supercritical carbon dioxide. proceedings of spie, 10092. san francisco,california,united states.
XIII. Wanga, H., Xub, G., Zhua, S., Zhouc, W., Rena, N., & Xiaa, K. (2018, October 4). Comparison of percussion laser drilling quality with and without water based ultrasonic assistance. Journal of Manufacturing Processes, 36, 175-180.

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Abstract:

Since the problem of global warming and heat waves are the burning issues and became challenge for scientists in this era. Current analysis is also an attempt to solve this problem in Karachi Pakistan. This effort is to analyze frequency distribution by using daily maximum temperature data and then to find the best fitted probabilistic model for yearly maximum temperature series to see the possible return levels of maximum temperature in Karachi.After passing through a number of goodness of fit tests the Log-Logistic [3P] distribution is found to be the best fitted model to calculate return levels. Analysis also indicates that there is a chance of getting 44.3  temperature return level in the next coming 5 years, 45.8  in coming 20 yearsand 46.5  return levels in coming 50 years return period. These return levels propose that the Government officials and planners to take notice on plantation, water supply system, to facilitate better public transport to reduce the number of vehicles, to update health system, to increase electricity production etc.The results of this analysis are also useful to agricultural and environmental research.

Keywords:

Return level,Maximum Temperature,Return Periods,Heat waves,probabilistic model ,

Refference:

I Abbas, F., Rehman, I., Adrees, M., Ibrahim, M., Saleem, F., Ali, S., …&Salik, M. R. (2018). Prevailing trends of climatic extremes across Indus-Delta of Sindh-Pakistan. Theoretical and applied climatology, 131(3-4), 1101-1117.

II Arreyndip, N. A., & Joseph, E. (2015). Extreme temperature forecast in Mbonge, Cameroon, through return level analysis of the generalized extreme value (GEV) distribution. International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, 9(6), 343-348.

III Chaudhry, Q. Z., Rasul, G., Kamal, A., Mangrio, M. A., &Mahmood, S. (2015). Technical report on Karachi heat wave June 2015. Islamabad: Government of Pakistan Ministry of Climate Change.

IV Coles, S., Bawa, J., Trenner, L., &Dorazio, P. (2001). An introduction to statistical modeling of extreme values (Vol. 208, p. 208). London: Springer.

V Field, C. B., Barros, V., Stocker, T. F., &Dahe, Q. (Eds.). (2012). Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change. Cambridge University Press.

VI Grant, K., Kreyling, J., Heilmeier, H., Beierkuhnlein, C., &Jentsch, A. (2014). Extreme weather events and plant–plant interactions: shifts between competition and facilitation among grassland species in the face of drought and heavy rainfall. Ecological Research, 29(5), 991-1001.

VII Gumbel, E. J. (1958). Statistics of Extremes, Columbia Univ. Press, New York, 201.

VIII Hatfield, J. L., &Prueger, J. H. (2015). Temperature extremes: Effect on plant growth and development. Weather and climate extremes, 10, 4-10.

IX Imtiaz, S., &Rehman, Z. U. (2015). Death Toll From Heat Wave in Karachi, Pakistan, hits 1000. New York Times, available at: http://www.nytimes.com/2015/06/26/world/asia/karachi-pakistan-heat-wave-deaths.html.

X Iqbal, M. J., & Ali, M. (2013). A probabilistic approach for estimating return period of extreme annual rainfall in different cities of Punjab. Arabian Journal of Geosciences, 6(7), 2599-2606.

XI Katz, R. W., Parlange, M. B., &Naveau, P. (2002). Statistics of extremes in hydrology. Advances in water resources, 25(8-12), 1287-1304.

XII Kayes, I., Shahriar, S. A., Hasan, K., Akhter, M., Kabir, M. M., & Salam, M. A. (2019). The relationships between meteorological parameters and air pollutants in an urban environment. Global Journal of Environmental Science and Management, 5(3), 265-278.

XIII Mayooran, T., &Laheetharan, A. (2014). The statistical distribution of annual maximum rainfall in Colombo district. Sri Lankan Journal of Applied Statistics, 15(2), 1765-1784.

XIV Meehl, G. A., & Tebaldi, C. (2004). More intense, more frequent, and longer lasting heat waves in the 21st century. Science, 305(5686), 994-997.

XV Mothupi, T., Thupeng, W. M., Mashabe, B., &Mokoto, B. (2016). Estimating Extreme Quantiles of the Maximum Surface Air Temperatures for the Sir SeretseKhama International Airport Using the Generalized Extreme Value Distribution. American Journal of Theoretical and Applied Statistics, 5(6), 365-375.

XVI Omer, M. A., Salh, S. M., & Ahmed, S. A. (2019). Statistical Distribution of Rainfall in Kurdistan-Iraq Region. Al-Mustansiriyah Journal of Science, 30(4), 18-28.

XVII Orlowsky, B., &Seneviratne, S. I. (2012). Global changes in extreme events: regional and seasonal dimension. Climatic Change, 110(3-4), 669-696.

XVIII Pal, J. S., &Eltahir, E. A. (2016). Future temperature in southwest Asia projected to exceed a threshold for human adaptability. Nature Climate Change, 6(2), 197.

XIX Parey, S., Hoang, T. T. H., &Dacunha‐Castelle, D. (2010). Different ways to compute temperature return levels in the climate change context. Environmetrics, 21(7‐8), 698-718.

XX Raza, A., Razzaq, A., Mehmood, S. S., Zou, X., Zhang, X., Lv, Y., &Xu, J. (2019). Impact of climate change on crops adaptation and strategies to tackle its outcome: A review. Plants, 8(2), 34.

XXI Rizwan, M., Guo, S., Xiong, F., & Yin, J. (2018). Evaluation of various probability distributions for deriving design flood featuring right-tail events in pakistan. Water, 10(11), 1603.

XXII Rootzén, H., & Katz, R. W. (2013). Design life level: quantifying risk in a changing climate. Water Resources Research, 49(9), 5964-5972.

XXIII Rust, H. W., Kallache, M., Schellnhuber, H. J., &Kropp, J. P. (2011). Confidence intervals for flood return level estimates assuming long-range dependence. In In Extremis (pp. 60-88). Springer, Berlin, Heidelberg.

XXIV Rust, H. W., Kallache, M., Schellnhuber, H. J., &Kropp, J. P. (2010). Confidence intervals for flood return level estimates assuming long-range dependence. Springer-Verlag, Berlin.

XXV Salim, M., &Mahmood-ul-Hassan, M. (2015). Distribution of Indian flying foxpteropusgiganteusbrünnich, 1782 in four districts of khyberpakhtunkhwa. The Journal of Animal & Plant Sciences, 25(3 suppl 2), 446-449.

XXVI Sharma, S., Sharma, P., Khare, M., &Kwatra, S. (2016). Statistical behavior of ozone in urban environment. Sustainable Environment Research, 26(3), 142-148.

XXVII Sheridan, S. C., & Allen, M. J. (2015). Changes in the frequency and intensity of extreme temperature events and human health concerns. Current Climate Change Reports, 1(3), 155-162.

XXVIII Sherwood, S. C., & Huber, M. (2010). An adaptability limit to climate change due to heat stress. Proceedings of the National Academy of Sciences, 107(21), 9552-9555.

XXIX Smith, R. L. (1989). Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. Statistical Science, 367-377.

XXX Zahid, M., Blender, R., Lucarini, V., &Bramati, M. C. (2017). Return levels of temperature extremes in southern Pakistan. Earth System Dynamics, 8(4), 1263-1278.

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Abstract:

Let will represent a semiprime inverse semiring with -torsion free and has identity element, where . An additive mapping  from  in to itself satisfying fulfilled for all  and   be distinct integers,forces  to be centralizer. Moreover one more result involving centralizer has also been discussed.

Keywords:

Semiprime Semiring,Inverse Semiring,Commutator,Centralizer,Left (right) Centralizer,

Refference:

I. Bandlet H.J and Petrich M, Subdirect products of rings and distributive lattics, Proceedings of the Edinburgh Mathematical Society,25, 155 – 171 (1982).
II. Golan J.S.,Theory of semirings with applications in math., and theoretical comp., sci. Longman Scientific & Technical; New York: Wiley (1992).
III. Irena Kosi-Ulbl, A Remark on Centralizers in Semiprime Rings, Glasnik Matematicki, Vol. 39(59), 21 – 26 (2004).
IV. Javed M.A, Aslam M and Hussain M., On Condition (A2) of Bandlet and Petrich for inverse semirings, International Mathematical Forum, Vol. 7, 2903 – 2914 (2012).
V. Karvellas P.H., Inversive semirings, J. Aust. Math. Soc., 18, 277 – 288 (1974).
VI. Kosi-Ulbl I and Vukmanon J., Centralizers of Standard Operator Algebras and Semisimple H* -Algebras, Acta Math. Hungar, 110 (3), 217–223 (2006).
VII. Sara S, Aslam M and Javed M.A, On centralizer of semiprime inverse semiring, Discussiones Mathematicae, General Algebra and Applications, 36, 71 – 84 (2016).
VIII. Sen M.K and Maity S.K.,Regular additively inverse semirings, Acta Math. Univ. Comenianae. 1, 137-146 (2006).
IX. Vukman J., An identity related to centralizers in semiprime rings, Comment. Math. Univ. Carolin. 40, 3, 447–456 (1999).
X. Zalar B., on centralizers of semiprime rings, Comment. Math. Univ. Carolin. 32, 609 – 614 (1991).

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Abstract:

In this paper the transversal vibrations of axially moving string under structural damping are studied. The focus on the possibility of truncation method has been discussed. Governing equations of motion is modeled as second order linear homogeneous partial differential equation with constant coefficients.  The string is taken to be fixed at both ends. To construct the asymptotic approximations, the Fourier expansion method in conjunction with the two timescales perturbation method is employed. Amplitude-response of individual mode is computed under the effect of various structural damping parameter values. It is obtained that the response of individual-mode decays as the time increases. Furthermore, to investigate the applicability of truncation method, the method of characteristic coordinates and two timescales perturbation method are used in conjunction with each other. The amplitude-response subject to the specific initial conditions under the effect of various structural damping parameter values is computed. It turned out that amplitude-response decay as the time increases. Energy of the system is also computed and found to be decaying as the time progresses. From the amplitude-response of the system and individual mode amplitude-response, it is found out that the mode-truncation is allowed in the structural damping case.

Keywords:

Transverse vibrations,asymptotic approximations,structural damping,perturbation method.,

Refference:

I. A. A. Maitlo, S. H. Sandilo, A. H. Sheikh, R. A. Malookani, and S. Qureshi, “On aspects of viscous damping for an axially transporting string”, Sci. Int. Lahore, Vol. 28, Issue. 04, pp. 3721–3727, 2016

II. Darmawijoyo and W. T. Van Horssen, “On the weakly damped vibrations of a string attached to a spring mass dashpot system”, JVCJournal Vib. Control, Vol. 9, Issue. 11, pp. 1231–1248, 2003

III. E. W. Chen, J. Wang, K. Zhong, Y. Lu, and H. Wei, “Vibration dissipation of an axially traveling string with boundary damping”, J. Vibroengineering, Vol. 19, Issue. 8, pp. 5780–5795, 2017

IV. G. Suweken and W. T. Van Horssen, “On the transversal vibrations of a conveyor belt with a low and time-varying velocity”. Part I: the string-like case, J. Sound Vib., Vol. 264, Issue. 1, pp. 117–133, 2003

V. J. A. Wickert, “Analysis of Self-excited Longitudinal Vibration ofA Moving Tape”, J. Sound Vib., Vol. 160, Issue. 3, pp. 455–463, 1993

VI. Zhang, Dynamic Analysis of Viscoelastic Serpentine Belt Drive Systems, 1999

VII. M. H. Ghayesh and N. Moradian, “Nonlinear dynamic response of axially moving, stretched viscoelastic strings”, Arch. Appl. Mech., Vol. 81, Issue. 6, pp. 781–799, 2011

VIII. M. Pakdemirli, A. G. Ulsoy, and A. Ceranoglu, “Transverse Vibration of an Axially Accelerating String”, J. Sound Vib.,Vol. 169 (1994), Issue. 2, pp. 179–196, 1994

IX. N. V. Gaiko and W. T. Van Horssen, “On the transverse, low frequency vibrations of a traveling string with boundary damping”, J. Vib. Acoust. Trans. ASME, Vol. 137, Issue. 4, pp. 9–11, 2015

X. Peter Hagedorn and Anirvan DasGupta, Vibrations and Waves in Continuous Mechanical Systems. John Wiley & Sons, Ltd, 2007

XI. Q. C. Nguyen and K. Hong, “Longitudinal and transverse vibration control of an axially moving string”, IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS), pp. 24–29, 2011

XII. R. A. Malookani and W. T. van Horssen, “On resonances and the applicability of Galerkin׳ s truncation method for an axially moving string with time-varying velocity”, J. Sound Vib., Vol. 344, pp. 1–17, 2015

XIII. R. A. Malookani and W. T. van Horssen, “On the asymptotic approximation of the solution of an equation for a non-constant axially moving string”, J. Sound Vib., Vol. 367, pp. 203–218, 2016

XIV. R. A. Malookani and W. T. van Horssen, “On Parametric Stability of a Nonconstant Axially Moving String near Resonances”, J. Vib. Acoust., Vol. 139, Issue. 1, pp. 011005-12, 2017

XV. R. A. Malookani, S. H. Sandilo, and A. Hanan, “On (Non) Applicability of a Mode-Truncation of a Damped Traveling String,” Mehran Univ. Res. J. Eng. Technol., Vol. 38, Issue. 2, pp. 471–478, 2019

XVI. R. A. Malookani, S. Dehraj, and S. H. Sandilo, “Asymptotic Approximations of the Solution for a Traveling String under Boundary Damping”, J. Appl. Comput. Mech., Vol. 5 Issue. 5, pp. 918-925, 2019

XVII. R. A. Malookani and W. T. van Horssen, “On the asymptotic approximation of the solution of an equation for a non-constant axially moving string”, J. Sound Vib., Vol. 367, pp. 203–218, 2016

XVIII. R. F. Steidel, An introduction to mechanical vibrations, 3rd ed. New York: Wiley, 1989

XIX. S. Dehraj, S. H. Sandilo, and R. A. Malookani, “On applicability of truncation method for damped axially moving string”, J. Vibroengineering, Vol. 22, Issue. 2, pp. 337–352, 2020

XX. S. H. Sandilo, S. Dehraj, and R. A. Malookani, “On Time-Varying Velocity for an Axially Moving String under Viscous Damping”, presented at the ENOC, Hungary, 2018

XXI. W. D. Zhu and C. D. Mote, “Free And Forced Response Of An Axially Moving String Transporting A Damped Linear Oscillator”, J. Sound Vib., Vol. 177, Issue. 5, pp. 591–610, 1994

XXII. Y.Q. Tang, Y.-X. Zhang, and X.-D. Yang, “On Parametric Instability Boundaries of Axially Moving Beams with Internal Resonance”, Acta Mech. Solida Sin., Vol. 3, Issue. 4, pp. 470–483, 2

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Abstract:

A set  of vertices of a graph  is said to be a decycling set if  is acyclic. The size of a minimum decycling set of  is called the decycling number of  and it is denoted by In this paper, our chief objectives areto obtain the upper bound of the decycling number of a graph by using graph chromatics number and its order. The relation of the genus of the surface  and the decycling number of a graph embedded in surface  is studied. The decycling number of a planar graph with  vertices is conjectured to be , which is shown in this paper if the girth of the graph is at least four. The decycling number of a graph with  vertices and maximum degree three is proved to be at most Also, we completely investigatethe decycling number of the hypercube .

Keywords:

Decycling number,Chromatic number,Maximum degree,Embedding,Girth,hypercube,

Refference:

I Albertson M and Berman D., The acyclic chromatic number, Congr. Number., 17(1976),51-69.
II BauS and Beineke L., The decycling number of graphs, Australas J. Combin., 25(2002),285-298.
III Beineke L and Vandell R., Decycling graphs, J.Graph Theory, 25(1997), No.1:59-77.
IV Beineke L and Harary F., The genus of the n-cube, Canad. J.Math.17(1965),494-496.
V Bondy J.A and Murty U.S.R., Graph Theory, Springer, 2008.
VI Brooks R.L, on coloring the nodes of a network, Proc. Cambridge Philos. Soc.37(1941),194-197.
VII Chartrand G, Kronk H.V and Wall C.E., The point-arboricity of a graph, Israel J. Math. (1968) 6:169C175.
VIII ErdÖs P, Saks M and Sós V, Maximum induced trees in graphs, J. Combin. Theory Ser.B,41(1986),61-79.
IX Festa P,Pardalos P.M and Reseude M.G.C., Feedback set problem, in Handbook ofCombinatorial Optimization, Supplement Vol. A Kluwer, Dordrecht, (1999),209-258.
X Heahood P.J., Map-colour theorem, Quart. J.Pure Appl.Math.24(1890),332-338.
XI Karp R.M, Miller R.E., and Thatcher J.M., Reducibility among combinatorial problems. J.Symb. Log.40(1975):618C619.
XII Kirchhoff K, Über die Auflösung der Gleichungen, auf welche man bei derUntersuchung der linearen VerteilunggalvanischerStrömeGfϋhrtwird, Ann.Phy. Chem, 72 (1847) 497-508.
XIII Liu J.P and Zhao C, A new bound on the feedback vertex sets in cubic graphs, Discrete Math., 184(1996), 119-131.
XIV Long S.D., Ren H, The decycling number and maximum genus of cubic graphs, Journal of GraphTheory, 88 (2018),375 C384.
XV Pike D.A, Decycling hypercubes, Graphs and Combin., 19(2003),547-550.

XVI Pike D.A and Zou Y., Decycling cartesian products of two cycles, SIAM J. Discrete Math. 19(2005),No. 3:651-663.
XVII Punnim N, Decycling connected regular graphs, Austral. J. Combin., 35(2006), 155 169.
XVIII Punnim N, The decycling number of regular graphs, Thai J. Math.,4(2006),145-161.
XIX Ren H, Yang C., and T.X Zhao, A new formula for the decycling number of regular graphs, DiscreteMath. 340(2017),3020-3031.
XX Thomassen C, Five-coloring maps on surfaces, J.Combin. Theory Ser.B,59(1993),89-105.
XXI White A.T, Graphs of groups on surfaces, Elsevier, Amsterdam, London, New York, Oxford, Paris, Shannon, Tokyo, 2001.
XXII Wilson R.J, Introduction to graph theory 4th Ed., Addison –Wesley Longman, Reading MA. (1996).
XXIII Zheng M and Lu X, On the maximum induced forests of a connected cubic graph without triangles, Discrete Math.,85(1990), 89-96.

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Abstract:

According to the organizations like NCRB-social government and the reports of WHO, 35% women are subjected to physical harassment, abuse and violence that occur even in public places such as cabs, hospitals, public transport, public parks, in and around schools, railway-bus stands, foot paths, and worse in the very own neighbors. Changing dynamics of working environment also forces many to work in night shifts which make them to move out in vulnerable timings. In India, according to amendment to the Factories Act 1948, it was allowed under the law for women to work night shifts which enabled many women to work through shifts but also put them in risk. Most of the women are working in nightshiftsimply there is an increase in their productivity, quality and international competitiveness because of which many women tend to work nowadays and support their families. Companies always provide necessary security measures in place to ensure women safety, yet in several situations incidents happened to prove the vulnerability of them due to several attributes. Research works were being undertaken to device strategies, protocols, policies to protect women workforce from being vulnerable.   In this paper an attempt is made to make a device for the women security where the device provides the safety measure in public places, public transports such as cabs, schools, buses and company vehicle etc. We propose an advanced model, which aims to provide a safe environment for women in the society through live video streaming by embedding sensors with a processor chip. The core of the entire system is raspberry pi, Pi Camera which is used for video data which will be collected by the embedded system and sent to the cloud by wireless network. Through this device a live video camera is implemented in the device which feds the live video through a GPS module that can be used to trace the whereabouts and the issues a woman may face which can be used to rescue under distress situation.

Keywords:

Raspberry Pi,Embedded System,Pi camera, Image Capture,Video Streaming,

Refference:

I. A Research Study on “Night Shift for Women: Growth & Opportunities” Conducted by theAssociated Chambers of Commerce & Industry of India (ASSOCHAM), New Delhi; 2016;www.ncw.nic.in.

II. Arabelli, R.R. &Rajababu, D. 2019, “Transformer optimal protection using internet of things”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 11, pp. 2169-2172.

III. Arabelli, R.R.&Revuri, K. 2019, “Fingerprint and Raspberri Pi based vehicle authentication and secured tracking system”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 5, pp. 1051-1054.

IV. Ashlesha Wankhede, Ashwini velankar, Priyanka Shinde “PORTABLE DEVICE FOR WOMEN SECURITY”. IJRET, eISSN:2319-1163|p ISSN:2321-7308.

V. C. Garcia-Moreno, H. A. Jansen, M. Ellsberg, L. Heise, and C. H. Watts, “Prevalence of intimate partner violence: findings from the WHO multi-country study on women’s health and domestic violence,” The Lancet, vol. 368, no. 9543, pp. 1260–1269, 2006.View at: Publisher Site | Google Scholar

VI. C. Garcia-Moreno, L. Heise, H. A. F. M. Jansen, M. Ellsberg, and C. Watts, “Violence against women,” Science, vol. 310, no. 5752, pp. 1282–1283, 2005.View at: Publisher Site | Google Scholar

VII. Chheda, Dhaval, et al. “Smart Projectors Using Remote Controlled Raspberry Pi.” International Journal of Computer Applications, vol. 82, no. 16, Nov. 2013, pp. 6–11. DOI.org (Crossref), doi:10.5120/14245-2250.

VIII. “Dynamic Smart Alert Service for Women Safety System.” International Journal of Communication and Computer Technologies, vol. 5, no. 2, Jan. 2019. DOI.org (Crossref), doi:10.31838/ijccts/05.02.05.

IX. Guruge, Sepali,et al. “Violence against Women: An Exploration of the Physical and Mental Health Trends among Immigrant and Refugee Women in Canada.” Nursing Research and Practice, vol. 2012, 2012, pp.1-15.DOI.org (Crossref), doi:10.1155/2012/434592.

X. H. Crawley and T. Lester, Comparative Analysis of Gender-Related Persecution in National Asylum Legislation and Practice in Europe, United Nations High Commissioner for Refugees Evaluation and Policy Analysis Unit, Department of International Protection, and Regional Bureau for Europe, Geneva, Switzerland, 2004.

XI. Heise, Lori, et al. Violence against Women: The Hidden Health Burden. World Bank, 1994.

XII. Huu-Quoc Nguyen, et al. “Low Cost Real-Time System Monitoring Using Raspberry Pi.” 2015 Seventh International Conference on Ubiquitous and Future Networks, IEEE, 2015, pp. 857–59. DOI.org (Crossref), doi:10.1109/ICUFN.2015.7182665.

XIII. John Lekan, Akinode. (2011). IMPROVING NATIONAL SECURITY USING GPS TRACKING SYSTEM TECHNOLOGY.

XIV. R. Sundaramurthy and V. Nagarajan, “Design and implementation of reconfigurable virtual instruments using Raspberry Pi core,” 2016 International Conference on Communication and Signal Processing (ICCSP), India, 2016, pp. 2309-2313.

XV. T. H. Mahony, Women in Canada: A Gender-Based Statistical Report, Statistics Canada, Ottawa, Canada, 2011.

XVI. Video surveillance using raspberry Pi architecture, R Shete, M Sabale – The International Daily journal ISSN, 2015 – researchgate.net

XVII. Vinay Sagar KN, Kusuma S M, “Home automation using Internet of things”, International research journal of Engineering and Technology (IRJET) Volume: 02 Issue: 03- June-2015.

XVIII. WHO, Violence against Women. Health Consequences, World Health Organization, Geneva, Switzerland, 1997.

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Abstract:

Analysis of single machine infinite bus system is made by considering single Kaplan turbine-generator with exciter and governor for the small-signal stability. In this research paper a scientific approach was adopted to minimize the settling time along with the stability of the given power system. Kaplan turbine generators were predominantly implemented in hydroelectric power plants with lower heads. However, dual regulation of such turbines in the plants are renowned in the current research trends. The dual regulation of hydro-turbine is incorporated through the operation of both wicket gate and runner blade position. In a worldwide scenario Kaplan turbine-generators play a vital role in power and energy generation. Whereas the life of these generator gates or runner blades depends on speed deviations. In this context, a PID controller has been designed for the extended single machine infinite bus system to improve the speed deviation. The results of the extended single machine infinite bus system are compared with and without PID controller for the enhancement of speed deviation.

Keywords:

Power System,Extended SMIB,Governor,Speed deviation,PID controller,

Refference:

I. Amar President, O., Hocine Supervisor, L., & Nadia Examiner MCB, B. (2019). People’s Democratic Republic of Algeria Ministry of Higher Education and Scientific Research THEME: Study of a Grid-Connected Photovoltaic System.
II. Bharatiraja, C., Kasilingam, G., Pasupuleti, J., Bharatiraja, C., & Adedayo, Y. (n.d.). Single Machine Connected Infinite Bus System Tuning Coordination Control using Biogeography-Based Optimization Algorithm. scindeks.ceon.rs.
III. Björk, J., & Johansson, K. (2019). Control Limitations due to Zero Dynamics in a Single-Machine Infinite Bus Network.
IV. Bux, R., Xiao, C., Hussain, A., & Wang, H. (2019, 11 16). Study of Single Machine Infinite Bus System with VSC Based Stabilizer. dl.acm.org, 159-163.
V. Chaib, H., Allaoui, T., Brahami, M., & Denai, M. (n.d.). Modelling, Simulation and Fuzzy Self-Tuning Control of D-STATCOM in a Single Machine Infinite Bus Power System.
VI. Chan, Z., & Aung, Z. (2020). Zar Ni Aung.
VII. Chen, J., & Engeda, A. (n.d.). IOP Conference Series: Earth and Environmental Science Design considerations for an ultra-low-head Kaplan turbine system Design considerations for an ultra-low-head Kaplan turbine system. iopscience.iop.org.
VIII. Czeslaw Banka, J. (2017). A RESEARCH PLAN FOR ASSESSING THE POWER AND ENERGY CAPABILITY OF A RIVER NETWORK UNDER AN INTEGRATED WIND/HYDRO-ELECTRIC DISPATCHABLE RÉGIME.
IX. Garbin, D. (2018). Analysis for the assessment of the wave energy and ISWEC productivity along the argentinian coast.
X. Ghosh, A., Das, A., & Sanyal, A. (2019, 10 1). Transient Stability Assessment of an Alternator Connected to Infinite Bus Through a Series Impedance Using State Space Model. Journal of The Institution of Engineers (India): Series B, 100(5), 509-513.
XI. GROULT, M. (2018). Optimization of Electromechanical Studies for the Connection of Hydro Generation MATHIEU GROULT KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING.
XII. Guo, B. (2019). Modelling and advanced controls of variable speed hydro-electric plants.
XIII. Haghighi, M., Mirghavami, S., Chini, S., energy, A.-R., & 2019, u. (n.d.). Developing a method to design and simulation of a very low head axial turbine with adjustable rotor blades. Elsevier.
XIV. Haghighi, M., Mirghavami, S., Ghorani, M., Energy, A.-R., & 2020, u. (n.d.). A numerical study on the performance of a superhydrophobic coated very low head (VLH) axial hydraulic turbine using entropy generation method. Elsevier.
XV. Houde, S., & Deschênes, C. (2019). Numerical investigation of flow in a runner of low-head bulb turbine and correlation with PIV and LDV measurements.
XVI. J French – US Patent 9, 8., & 2018, u. (2018). DIE K A N I K A N AT A UN.
XVII. Jacobsen, T. (2019). Distributed Renewable Generation and Power Flow Control to Improve Power Quality at Northern Senja, Norway.
XVIII. Kim, S. (2019, 9 17). Proportional-type non-linear excitation controller with power angle reference estimator for single-machine infinite-bus power system. IET Generation, Transmission and Distribution, 13(18), 4029-4036.
XIX. Komlanvi, A. (2018). Computer aided design of 3D of renewable energy platform for Togo’s smart grid power system infrastructure Item Type Thesis.
XX. Machowski, J., Bialek, J., & Bumby, J. (2020). POWER SYSTEM DYNAMICS Stability and Control Second Edition.
XXI. Mashlakov, A. (2017). SIMULATION ON DISPERSED VOLTAGE CONTROL IN DISTRIBUTION NETWORK.
XXII. Masson, P., Weil, B., & Hatchuel, A. (2017). Design Theory.
XXIII. Mazhari, I. (2017). DC MICROGRID WITH CONTROLLABLE LOADS.
XXIV. Mukherjee, P., Das, A., & Bera, P. (2020). Design of P-I-D Power System Stabilizer Using Oppositional Krill Herd Algorithm for a Single Machine Infinite Bus System. In P. Mukherjee, A. Das, & P. Bera.
XXV. Naoe, N., on, A.-2., & 2019, u. (n.d.). A Three-Phase PM Generator with Double Rotors for Low-Head Hydropower–Trial Structure and Basic Characteristics. ieeexplore.ieee.org.
XXVI. Nichols, C. (2019). The Design of an In-Conduit Hydropower Plant with a Seal-Free Magnetic Transmission.
XXVII. Nygren, L., Ahola, J., & Ahonen, D. (2017). Programme in Electrical Engineering HYDRAULIC ENERGY HARVESTING WITH VARIABLE-SPEED-DRIVEN CENTRIFUGAL PUMP AS TURBINE.
XXVIII. Oo, M. (2019). Design of 50 kW Kaplan Turbine for Micro hydro Power Plant.
XXIX. Roca, W. (1675). MSc Dissertation Thesis MSc in Sustainable Energy Systems Modelling and Cost Analysis of a Hybrid Wind Turbine and Water Tower System as a Means of Energy Storage.
XXX. Ramana Rao KV, Nagendrababu, M., Valanginisarat, P., & Kallempudi Vahini. (2020). Implementation strategy to minimize the speckle noise from polarimetric sar data. International Journal of Mechanical and Production Engineering Research and Development, 10(3), 5455–5466. https://doi.org/10.24247/ijmperdjun2020520
XXXI. Salehghaffari, H. (n.d.). Hardware-In-The-Loop Vulnerability Analysis of a Single-Machine Infinite-Bus Power System.
XXXII. Shah, N., & Joshi, S. (2019, 3 1). Utilization of DFIG-based wind model for robust damping of the low frequency oscillations in a single SG connected to an infinite bus. International Transactions on Electrical Energy Systems, 29(3).
XXXIII. Shah, N., Electrical, S.-I., & 2019, u. (n.d.). Utilization of DFIG‐based wind model for robust damping of the low frequency oscillations in a single SG connected to an infinite bus. Wiley Online Library.
XXXIV. Shahgholian, G., Hamidpour, H., & Movahedi, A. (2018). Transient Stability Promotion by FACTS Controller Based on Adaptive Inertia Weight Particle Swarm Optimization Method. advances.vsb.cz.
XXXV. Smil, V. (2019). Growth: from microorganisms to megacities.
XXXVI. Yang, W. (2017). Hydropower plants and power systems Dynamic processes and control for stable and efficient operation.
XXXVII. Ye, H., Pei, W., Kong, L., Power, T.-I., & 2018, u. (n.d.). Low-Order Response Modeling for Wind Farm-MTDC Participating in Primary Frequency Controls. ieeexplore.ieee.org.

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Abstract:

This paper exploring the stability to be achieved in the stochastic processes and operations which are called the autoregressive moving average and symbolized by ARMA Model(the roots of the equation should be out of this model circle.  Although these models are not stable and become stable after so many conversions and differences. These new models called the autoregressive methods for integrated moving average which is symbolized ARFIMA (p, d, q) and these differences would be integers or fractional numbers. It is worth to be mentioned that the time series which depending on the long term (long memory) so this stability achieved by snapping the fractional differences which are located within the enclosed period (-0.5, 0.5) and are referred shortly ((ARFIMA (p,d,q))). Models which are located within the enclosed period (-0.5, 0.5). This search aims to estimate the parameter of fractional differences (d), three ways by using real data from the Ministry of Environment that include the rates of air pollution in Baghdad City with Nitrogen oxides(NO²), Ozone(Oᶟ) materials…these ways are: firstly, the way logarithm periodogram chart regression method which is called (Geweke and Porter- Hudak), symbolized (GPH) Secondly, smoothed periodogram regression. Thirdly, the way that called (KASHYAP AND EOM) and it has been used the standard error squares and standard error (SD) as two scale standards among these three ways to estimate the parameter. Akaike standard has been used for choosing the best model of linear models assumed.In this study, we will be dealt with the fractional differences

Keywords:

ARFIMA (p,d,q) models,long term memory,smoothed periodogram method,air pollution,spectrum function,

Refference:

I. Baillie, R. T. (1996). Long memory processes and fractional integration in econometrics. Journal of Econometrics,73(1), 5-59. doi:10.1016/0304-4076(95)01732-1

II. Franco, G. C., & Reisen, V. A. (2007). Bootstrap approaches and confidence intervals for stationary and non-stationary long-range dependence processes. Physica A: Statistical Mechanics and Its Applications,375(2), 546-562. doi:10.1016/j.physa.2006.08.027

III. Hassler, U. (1993). Regression of Spectral Estimators with Fractionally Integrated Time Series. Journal of Time Series Analysis,14(4), 369-380. doi:10.1111/j.1467-9892.1993.tb00151.

IV. Karemera, D., & Kim, B. J. (2006). Assessing the forecasting accuracy of alternative nominal exchange rate models: The case of long memory. Journal of Forecasting,25(5), 369-380. doi:10.1002/for.994

V. KASHYAP,R.L. and EOM,B.(1988) Estimation in long memory time series models J.time series Anal.9,35-41 long-memory parameter”.Department of Statistics, UFES, ES, UFMG, MGBrazil.

VI. Mandelbrot, B. B., & Wallis, J. R. (1968). Noah, Joseph, and Operational Hydrology. Water Resources Research, 4(5), 909-918. doi:10.1029/wr004i005p00909

VII. Ministry of Environment, records Waziriya station, daily readings of the station during the days of actual work for two years 2017.2018, Iraq – Baghdad 0.2019.

VIII. Porter, Hudak, S. (1982). Long – Term Memory: Modelling A simplified Spectral Approach. Unpublished Ph.D Dissertation, University of Wisconsin

IX. Reisen, V. A., Cribari-Neto, F., & Jensen, M. J. (2003). Long Memory Inflationary Dynamics: The Case of Brazil. Studies in Nonlinear Dynamics & Econometrics,7(3). doi:10.2202/1558-3708.1157

X. Reisen.V.A. (1993) “Estimation of the fractional difference parameter in the ARIMA(p,d,q) model using the smoothed periodogram”. Journal of time series analysis .Vol.15,No.3.

XI. Reisen.V.A.&Franco.G.C.(2006).”Log average sample spectral estimators oflong-memory parameter”.Department of Statistics, UFES, ES, UFMG, MGBrazil.

XII. RichardT.Baillie (1996) “long memory processes and fractional integration in econometric” department of Economics,Michigan state university,USA.

XIII. Wei, William W. S. – 1990 – (Time Series Analysis) – Addison – Wesley publishing Company p:278.

XIV. Wilkins, N. (2003). Fractional Integration at a Seasonal Frequency with an Application to Quarterly Unemployment Rates. School of Finance and Economics University of Technology, Sydney, 1-32.

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Abstract:

The research study aim to improve the performance of fruit quality by two approaches, first by applying kernel technique combined with specific classification method support vector machine (SVM) with error-correcting output codes for fruit categorization and then by cross validation . It is measured by analyzing the different mention kernel selection on color and shape features. Two coding design method such as one-vs.-one and one- vs.- all are examined with three commonly used kernel function linear, polynomial (cubic) and Radial Basis Function (Gaussian). The Experiment was conducted on fruit dataset created from fruit 360 dataset with six categories such as Apples, Avacados, Bananas, Cherrys, Grapes and lemons. The accuracy obtained for the fruit category with 98% accuracy was enhanced by the proposed method by the use of kernel technique selection resulted to 99%. However kernel choice highly depends on the parameter used for fruit categorization is introduced and discussed. The Experiments was carried out to find the best SVM kernel among linear, cubic and Gaussian for fruit categorization. The Experiment also focuses on evaluation process using cross validation methods kfold and hold out which resulted in a better accuracy for the classification model.  The results show that the proposed method provides very stable and successful fruit classification performance over six categories of fruits. The coding design one- vs. - one performed better when compared to one- vs. - all with respect to accuracy and training speed.

Keywords:

Multiclass SVM,ECOC,kernel technique,KFold validation,

Refference:

I A.Bhargava, A.Bansal, Fruits and vegetables quality evaluation using computer vision: A review. Journal of King Saud University – Computer and Information Sciences (2018), https://doi.org/10.1016/j.jksuci.2018.06.002

II C.Maaoui, & A.Pruski, (2008, July). A comparative study of SVM kernel applied to emotion recognition from physiological signals. In 2008 5th International Multi-Conference on Systems, Signals and Devices (pp. 1-6). IEEE.

III C.Ouyang, D.Li, J.Wang, S.Wang, & Y.Han, (2012, October). The research of the strawberry disease identification based on image processing and pattern recognition. In International Conference on Computer and Computing Technologies in Agriculture (pp. 69-77). Springer, Berlin, Heidelberg.

IV C. Sammut and G. I. Webb, Eds., “Holdout Evaluation,” in Encyclopedia of Machine Learning and Data Mining, Boston, MA: Springer US, 2017, p. 624.

V Donahue, Jeff, et al. “Decaf: A deep convolutional activation feature for generic visual recognition.” arXiv preprint arXiv:1310.1531 (2013).

VI EzgiiErturk, Ebru AkapinarSezer “A comparision of some soft computing methods for software fault prediction” Expert system with applications,Elsevier, pp1872-1879,vol.42, 2015.

VII F.Al-Shargie, T.B.Tang, N.Badruddin, & M.Kiguchi, (2018). Towards multilevel mental stress assessment using SVM with ECOC: an EEG approach. Medical & biological engineering & computing, 56(1), 125-136.

VIII Fruits 360 Dataset on Kaggle. https://www.kaggle.com/moltean/fruits. last visited on 06.07.2019

IX G.Muhammad, (2015). Date fruits classification using texture descriptors and shape-size features. Engineering Applications of Artificial Intelligence, 37, 361-367.

X H. M.Zawbaa, M.Abbass, M.Hazman, & A. E.Hassenian, (2014, November). Automatic fruit image recognition system based on shape and color features. In International Conference on Advanced Machine Learning Technologies and Applications (pp. 278-290). Springer, Cham.

XI L.Qiang, C.Jianrong, L.Bin, D.Lie, & Z.Yajing, (2014). Identification of fruit and branch in natural scenes for citrus harvesting robot using machine vision and support vector machine. International Journal of Agricultural and Biological Engineering, 7(2), 115-121.

XII M.Achirul Nanda, K. Boro Seminar, D. Nandika, & A. Maddu, (2018). A comparison study of kernel functions in the support vector machine and its application for termite detection. Information, 9(1), 5.

XIII P. Refaeilzadeh, L. Tang, and H. Liu, “Cross-Validation,” in Encyclopedia of Database Systems, L. LIU and M. T. ÖZSU, Eds. Boston, MA: Springer US, 2009, pp. 532–538.

XIV R. S. Chora’s, “Image Feature Extraction Techniques and their Applications for CBIR and Biometrics Systems”.International Journal of Biology and Biomedical Engineering, 2007, 1(1), 6–16.

XV S.Fatima, and M. Sesehashayee, (2020). Healthy Fruits Image Label Categorization through Color Shape and Texture Features Based on Machine Learning Algorithm, International Journal of Innovative Technology and Exploring Engineering, ISSN: 2278-3075, Volume-9 Issue-3.

XVI S. R.Dubey, & A. S. (2012). Robust approach for fruit and vegetable classification. Procedia Engineering, 38, 3449-3453.

XVII S. M. Iqbal, A.Gopal, P. E., Sankaranarayanan, & A. B. Nair, (2016). Classification of selected citrus fruits based on color using machine vision system. International journal of food properties, 19(2), 272-288.

XVIII Shepperd, D. Bowes, and T. Hall, “Researcher bias: The use of machine learning in software defect prediction,” Software Engineering, IEEE Transactions on, vol. 40,no. 6, pp. 603-616, 2014.

XIX S.Ibrahim, N. A.Zulkifli, N.Sabri, A. A.Shari, & M. R. M.Noordin, (2019). Rice grain classification using multi-class support vector machine (SVM). IAES International Journal of Artificial Intelligence, 8(3), 215.

XX T. G. Dietterich, G.Bakiri, 1995. Solving Multiclass Learning Problems via Error-Correcting Output Codes. Journal of Artificial Intelligence Research, 2, pp. 263-286.

XXI Y.Zhang, & L. Wu, (2012). Classification of fruits using computer vision and a multiclass support vector machine. Sensors, 12(9), 12489-12505.

XXII Z.Wen, B.Li, R.Kotagiri, J.Chen, Y.Chen, & R.Zhang, (2017, February). Improving efficiency of SVM k-fold cross-validation by alpha seeding. In Thirty-First AAAI Conference on Artificial Intelligence.

XXIII Z.Yan, Y.Yang, (2014). Application of ecocsvms in remote sensing image classification. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(2), 191.

XXIV Z.Yan, & Y.Yang, (2014). Performance analysis and coding strategy of ECOC SVMs. International Journal of Grid and Distributed Computing, 7(1), 67-76

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