Category Archives: Engineering and Scientific International Journal (ESIJ)

Response of a Permanent Magnet Moving Coil Instrument via the Application of Rohit Transform

Author
Rohit Gupta, Rahul Gupta, Anamika
Keywords
Response; Rohit Transform; Permanent Magnet Moving Coil Instrument
Abstract
In this paper, a new integral transform called Rohit transform is presented for the analysis of a Permanent Magnet Moving Coil (PMMC) instrument. A permanent magnet moving coil instrument is an electromagnetic device that is used to measure small values of electric currents. When some current is passed through the permanent-magnet moving-coil (PMMC) instrument, its coil may suffer a few back and forth oscillations about its final mean position before coming to rest. The PMMC instrument is also known as moving coil galvanometer and its mathematical analysis is usually done by an ordinary calculus approach. This paper presents the use of Rohit transform for mathematical analysis of a PMMC instrument and hence, for obtaining its response. The response obtained provides the deflection of the coil of the PMMC instrument from its mean position. In this paper, the response of a PMMC instrument is provided as a demonstration of the application of the new integral transform called Rohit transform.
References
[1] Basic Electrical Engineering, C. L. Wadhwa. Publisher: New Age International Pvt. Ltd. 2nd edition, 2011.
[2] Electrical Measurements and Measuring Instruments by U. A. Bakshi and A.V. Bakshi. Publisher: Technical Publications, 2008.
[3] A Text Book of Engineering Physics by M.N. Avadhanulu and P.G. Kshirsagar.Publisher: S. Chand Publishing, 11th edition, 2018.
[4] The Physics of Wave and Oscillations by N.K. Bajaj. Publisher: Tata Mc-Graw Hill Publishing Co. Ltd., 1988.
[5] Rohit Gupta , Rahul Gupta, Residue approach to mathematical analysis of the moving coil galvanometer, International Journal of Advanced Trends in Engineering and Technology, 4(1), 2019, pp. 06-10.
[6] Rohit Gupta, On Novel Integral Transform: Rohit Transform and Its Application to Boundary Value Problems, “ASIO Journal of Chemistry, Physics, Mathematics and Applied Sciences”, 4(1), 2020: 08-13.
[7] Rohit Gupta, Rahul Gupta, Dinesh Verma, Solving Schrodinger equation for a quantum mechanical particle by a new integral transform: Rohit Transform, “ASIO Journal of Chemistry, Physics, Mathematics and Applied Sciences”, 4(1), 2020: 32-36.
[8] Rohit Gupta, Rahul Gupta, Analysis of RLC circuits with exponential excitation sources by a new integral transform: Rohit Transform, “ASIO Journal of Engineering and Technological Perspective Research”, 5(1), 2020, pp.22-24.
[9] Rohit Gupta, Yuvraj Singh, Dinesh Verma, Response of a basic series inverter by the application of convolution theorem, “ASIO Journal of Engi. and Technological Perspective Research”, 5(1), 2020, pp. 14-17.
[10] Anamika, Rohit Gupta, Analysis Of Basic Series Inverter Via The Application Of Rohit Transform, “International Journal of Advance Research and Innovative Ideas in Education”,6(6), 2020, pp. 868-873.
[11] Loveneesh Talwar, Rohit Gupta, Analysis of Electric Network Circuits with Sinusoidal Potential Sources via Rohit Transform, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Volume 9, Issue 11, November 2020, pp. 3929-3023.
[12] Neeraj Pandita, Rohit Gupta, Analysis Of Uniform Infinite Fin Via Means Of Rohit Transform, “International Journal Of Advance Research And Innovative Ideas In Education”, 6(6), 2020, pp. 1033-36.
[13] Neeraj Pandita and Rohit Gupta,Heat Conducted Through Fins Of Varying Cross-Sections Via Rohit Transform, “EPRA Journal Of Research And Development”, 5(12), 2020, pp. 222-226.
[14] A Study of Electromagnet Moving Coil Galvanometers for Use in Alternating-current Measurements by Ernest Edward Weibel. Publisher: U.S. Government Printing Office, 1918.
[15] Rahul Gupta and Rohit Gupta, Impulsive Responses of Damped Mechanical and Electrical Oscillators, “International Journal ofScientific and Technical Advancements”, 6(3), 2020, pp. 41-44.
[16] Rahul Gupta, Rohit Gupta, Dinesh Verma, Application of Convolution Method to the Impulsive Response of A Lightly Damped Harmonic Oscillator, International Journal of Scientific Research in Physics and Applied Sciences ,Vol.7, Issue.3, pp.173-175, June (2019).
[17] Rohit Gupta, Rahul Gupta, Sonica Rajput, Analysis of Damped Harmonic Oscillator by Matrix Method, Inter. Journal of Research and Analytical Reviews, Volume 5, Issue 4, October 2018, pp. 479-484.
[18] Rahul Gupta, Rohit Gupta, Dinesh Verma, Application of Novel Integral Transform: Gupta Transform to Mechanical and Electrical Oscillators, “ASIO Journal of Chemistry, Physics, Mathematics and Applied Sciences”, 4(1), 2020: 04-07.
[19] Engineering Physics by R.K. Gaur and S.L. Gupta. Publisher: Dhanpat Rai publications, 8th edition, 2008.

Received: 26 January 2021
Accepted: 02 April 2021
Published: 08 April 2021
DOI: 10.30726/esij/v8.i2.2021.82010

Calculation of Gamma-ray Mass Absorption Coefficients for some Geological Compounds for Energy of 10–150 keV

Author
Samir A. Hamouda, Essam al-Talhi, Mohamed B. Abdelmalik
Keywords
Mass Absorption Coefficients; Gamma-Ray Spectroscopy; Geology; Mixtures
Abstract
Information about gamma-ray mass absorption coefficients in different geological compounds with different percentage to their rations is vital for accurate gamma-ray spectroscopy analysis. In this paper, gamma-ray absorption coefficients for energy (10-150 keV) were calculated for Corundum (AL2O3), Quartz (SiO2), Calcite (CaCO3), Hematite (Fe2O3), and Magnetite (Fe3O4) compounds with their % mixtures.
References
[1] W. Heitler, (1955), “Quantum Theory of Radiation”, Sec. 26, Oxford
[2] R. D. Evans, (1955), “The atomic nucleus”, McGraw Hill Book Company, Inc., New York.
[3] C. M. Davisson and R. D. Evans, (1952), “Gamma-ray absorption coefficient‟. Rev. Mod. Phys, V24,79-103.
[4] Harvey Hall, (1936), “The theory of photoelectric absorption for x-rays and Gamma-rays”, Reviews of modern physics, Vol 8, pp358-377.
[5] J. Hubbel , (1982), “Photon mass Attenuation and Energy-Absorption Coefficients from 1keV to 20keV”, Int. J. appl. radiat. isot, .vol 33 ,1269-1290.
[6] National Bureau of Standarads,(1969), “Photon Cross Sections, Attenuation Coefficient, and Energy Absorption Coefficients From 10 keV to 100 GeV”, U.S. Department of Commerce.

Received : 01 March 2021
Accepted : 02 April 2021
Published : 08 April 2021
DOI: 10.30726/esij/v8.i2.2021.82009

Solving the Half-Infinite Potential Well Problem via the Application of Matrix Method

Author
Rohit Gupta, Rahul Gupta
Keywords
Matrix Method; Schrodinger’s Equation; Half-Infinite Potential Well
Abstract
This paper adds up how the matrix method can be used for solving the one-dimensional time-independent Schrodinger’s equation for some specific potential energy variation like half-infinite potential well. The matrix method is illustrated to obtain solution of the time-independent Schrodinger’s equation for half-infinite potential well, which is generally done by ordinary algebraic and analytical methods. The transcendental equation determining the discrete eigenvalues for bound state and the corresponding eigenwave functions are obtained by the time-independent Schrodinger’s equation for half-infinite potential well via the application of matrix method.
References
[1] N. Zettili, “Quantum Mechanics; Concepts and Applications”.Publisher: Wiley India Pvt. Ltd.
[2] J. Griffiths, “Introduction to Quantum Mechanics”. 2nd edition. Publisher: Cambridge University Press, 2017.
[3] B.N. Srivastava, “Quantum Mechanics”. 16th edition, 2017. Publisher, Pragati Prakashan, 1980.
[4] H. K. Dass, ‘Advanced Engineering Mathematics’, 2014. Publisher: S. Chand Publications.
[5] Rohit Gupta, Rahul Gupta, Matrix Method For Solving The Schrodinger’s Time – Independent Equation To Obtain The Eigen Functions And Eigen Energy Values of A Particle Inside The Infinite Square Well Potential, IOSR Journal of Applied Physics (IOSR-JAP), Volume 10, Issue 5 Ver. I (Sep. – Oct. 2018), PP. 01-05.
[6] Rohit Gupta, Rahul Gupta, “Matrix method approach for the temperature distribution and heat flow along a conducting bar connected between two heat sources”, Journal of Emerging Technologies and Innovative Research, Volume 5 Issue 9, September 2018, PP. 210-214.
[7] Rohit Gupta, Rahul Gupta, “Matrix method for deriving the response of a series Ł- Ϲ- Ɍ network connected to an excitation voltage source of constant potential”, Pramana Research Journal, Volume 8, Issue 10, 2018.
[8] Rohit Gupta, Rahul Gupta, Sonica Rajput “Response of a parallel Ɫ- Ϲ- ℛ network connected to an excitation source providing a constant current by matrix method”, International Journal for Research in Engineering Application & Management (IJREAM), Vol-04, Issue-07, Oct 2018.
[9] Rohit Gupta, Tarun Singhal, Dinesh Verma, Quantum mechanical reflection and transmission coefficients for a particle through a one-dimensional vertical step potential, International Journal of Innovative Technology and Exploring Engineering, Volume-8, Issue-11, September 2019, PP 2882-2886.
[10] Rohit Gupta, Yuvraj Singh Chib, Rahul Gupta, Design of the resistor-capacitor snubber network for a d. c. circuit containing an inductive load, Journal of Emerging Technologies and Innovative Research (JETIR), Volume 5, Issue 11, November 2018, pp. 68-71.
[11] Rohit Gupta, Rahul Gupta, Sonica Rajput, Analysis of Damped Harmonic Oscillator by Matrix Method, International Journal of Research and Analytical Reviews (IJRAR), Volume 5, Issue 4, October 2018, pp. 479-484.
[12] Rohit Gupta, Rahul Gupta, Heat Dissipation From The Finite Fin Surface Losing Heat At The Tip, International Journal of Research and Analytical Reviews, Volume 5, Issue 3, September 2018, pp. 138-143.
[13] P.A.M. Dirac, ‘Principles of quantum mechanics’. Reprint 2016. Publisher: Snowball Publishing (2012).
[14] P. M. Mathews, ‘A Textbook of Quantum Mechanics’. Publisher: Tata McGraw Hill Education Private Limited, 2010.
Received: 08 November 2020
Accepted: 14 February 2021
Published: 20 February 2021
DOI: 10.30726/esij/v8.i1.2021.81008

Research in Construction – Lab to Land

Author
Zacharia George
Keywords
Funicular Shells; Brick Shells; Lift Slab; Filler Slabs; Concrete Reinforcing Bars; 3 D Steel Structures; Space Frames; Braced Domes; Hyperbolied Shells; Large Panel Prefabrication; Reinforced Earth Design of RCC Elements.
Abstract
Construction sector is a down to earth activity. Any industrial research in this sector should end up as results applicable in field are it in design or construction. Author describes a number of products / processes he developed as Researcher at CSIR-SERC and applied extensively in India at projects of technology transfer, from SERC and later in his career as Consultant in the Industry. These were to increase productivity, improve quality and to optimize use of critical materials as also to save construction time.
References
[1] Zacharia George, N. Sethuraman Waffle Shells – SERC Publications,1975
[2] Zacharia George, K Mani, Brick Shells on Moveable Forms for Single Storey Buildings,Indian Concrete Journal 1978
[3] Zacharia George, K Mani , Large Panel Prefabrication, UNDP Workshop SERC, Chennai 1978.
[4] Zacharia George et al, Concrete reinforcement State of the Art Report , International Symposiums (SERC) , Chennai 1982
[5] Zacharia George Structural Engineering in India, Journal of Structural Engineering Practices Vol 1 1982, USA
[6] Zacharia George , Cost Effective Construction Methods- FIP Bulletin , 1982
[7] Zacharia George, Cathedral Building At Varanasi, Indian Concrete Journal, 1990
[8] Zacharia George, et al Concrete Constructions Practices, including Formwork ICI –IWC 1993, Bangalore
[9] Zacharia George, Damages to Concrete and Repairs thereon CIPET Conference, Ahemdabad, 1995
[10] Zacharia George, Civil Engineering – Practical Approach IE(I) TNSC Seminar 2014
[11] Zacharia George, P.D Gupta, N. Balachander, IE(I) Annual Technical Volume – Architectural Engineering 2019
[12] Zacharia George, My 30 years of R&D with CSIR, SERC and its Social Relevance, CPWA Annual Convention , Chennai 2020

Received : 10 October 2020
Accepted : 11February 2021
Published : 20 February 2021
DOI: 10.30726/esij/v8.i1.2021.81007

Cervical Cancer Cell Prediction using Machine Learning Classification Algorithms

Author
Prianka R R, Prof. Celine Kavida A and Bibin M R
Keywords
Prediction; Decision Stump; C4.5; AODE; Cervical Cancer
Abstract
In cancer identification, extrapolation of cervical cancer in patients shows a vital role. To save people from the cancer field of cancer detection, machine learning can play a big role in saving lives. In this paper, to make the detection process a portion faster and accurate machine learning techniques such as Decision Stump, C4.5 and Averaged One Dependence Estimators (AODE) for novel NCBI cervical cancer data set are made. Classification and Regression Tree (CART) is a simple decision tree algorithm that is used to create a decision tree of a given set. Here, a top-down Greedy search is used in order to check each attribute at every tree node. For building a Decision Stump algorithm, a decision tree which consists of nodes and an arc that connects nodes with the Entropy concept is used. The extension of the basic Decision Stump algorithm is the C4.5 algorithm on selecting the optimal split it recursively visits each decision node. The process gets continued until there is no further split is possible. In this way, the prediction is possible for the given data set. Bayesian methods are those that explicitly apply Bayes’ Theorem for problems such as classification algorithms acts as a quick method for the creation of a statistical predictive model. AODE are based on the Bayesian theorem which is commonly used to solve prediction problems for ease usage in the medical field. In this research Decision Stump, C4.5, and AODE are implemented with help of the training set. The basic designs are used to predict whether a feminine is having cervical cancer or not.
References
[1] R.Vidhya, G.M.Nasira. ” Predicting Cervical Cancer using Machine Learning Techniques- An Analysis” Global Journal of Pure and Applied Mathematics • ISSN 0973-1768 Volume 12, Number 3 (2016).
[2] Walboomers, Jan MM, et al. “Human papillomavirus is a necessary cause of invasive cervical cancer worldwide” The .Journal of pathology 189 1 (1999): 12-19.
[3] Clifford, G. M., et a1. “Human papillomavirus types in invasive cervical cancer worldwide: ameta-analysis” British journal of cancer 88.1 (2003): 63-73.
[4] Peto, Julian, et al.”The cervical cancer epidemic that screening has prevented in the UK” The Lancet 364.9430 (2004): 249-256.
[5] Kononenko, Igor. “Machine learning for medical diagnosis: history, state of the art and perspective” Artificial Intelligence in medicine 23.1 (2001): 89-109.
[6] Quinlan, J. Ross. “Induction of decision trees” Machine learning I.I (1986): 81-106.
[7] Kononenko, Igor. “Inductive and Bayesian learning in medical diagnosis”Applied Artificial Intelligence an International Journal 7.4 11993): 317-337.
[8] Buntine, Wray. “Learning rules using Bayes” Proceedings of the sixth international workshop on Machine learning. 2014.
[9] Quinlan, J. Ross. C4. 5: prograirs for machine leaming. Elsevier, 2014.
[10] Dey, Monali, and SiddharthSwarajRautaray. “Study and Analysis of Data mining Algorithms for Healthcare Decision Support System” planning 5 (2014).
Received : 01 October 2020
Accepted : 05 February 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81006

Antimicrobial Resistance: A Menace to Food Chain

Author
Siddhartha N. Joardar
Keywords
Antimicrobial Resistance (AMR); Food Animals; Food Chain; Growth Promoter.
Abstract
Food animals including poultry are the important reservoirs of human enteric pathogens. Moreover, it is observed that many human infections are associated with consumption of food products of animal origin. In fact, there is a chance of indirect transmission of commensal and opportunistic bacteria of Enterobacteriaceae group present in poultry and pig gut to human through the food chain. Antimicrobials are often used in food animals for their treatment and prevention of diseases besides they are used as a growth promoter. The commensal bacteria, present in the livestocks are challenged by antimicrobial agents; thereby develop their survival strategies through mutations and adaptations. Thus antimicrobial resistance (AMR) emerges from the use of antimicrobials in animals that subsequently causes transfer of resistance genes and bacteria among animals/animal products entering in the food web. Potential routes of entry of bacteria having AMR property in different animal rearing systems, viz. broiler, kuroiler and indigenous poultry, duck, pig, goat, buffalo and cattle have been investigated at local levels in West Bengal, an eastern state of India. Evidence strongly suggests that besides conventional source of antibiotics for therapeutic intervention, use of antibiotic growth promoter (AGP) at sub-therapeutic doses might be an additional source of generation of AMR in backyard system, a menace to food chain.
References
[1] McEwen SA and Fedorka-Cray, P J. Antimicrobial use and resistance in animals. Clin Infect Dis. 34; 2002:S93-106.
[2] Kumar S and Singh BR. An overview of mechanisms and emergence of antimicrobials drug resistance. Adv Anim Vet Sci. 1; 2013: 7-14.
[3] Schwarz S and Chaslus-Dancla E. Use of antimicrobials in veterinary medicine and phenomenon of resistance. Vet Res. 32; 2001: 201-225.
[4] Sullivan R, Schaus D, John M and Delport JA. Extended spectrum beta-lactamases: a miniriview of clinical relevant groups. J Med Microb Diagn, 4; 2015: 403-405.
[5] Sirot D. Extended-spectrum plasmid mediated b-lactamase. J Antimicrob Chemother. 36; 1995: 19-34.
[6] Livermore DM. β-lactamase in laboratory and clinical resistance. Cli Microbiol Rev. 8; 1995: 557-584.
[7] EFSA Panel on Biological Hazards. Scientific opinion on the public health risks of bacterial strains producing extended-spectrum β –lactamases and/or AmpC β-lactamases in food and food-producing animals. EFSA J., 9; 2011: 2322.
[8] Nobrega B and Brocchi M. An overview of extended-spectrum beta-lactamases in veterinary medicine and their public health consequences. J Infect Dev Ctries, 8; 2014: 954-960.
[9] DeSchrijver R, Moreels A and Fremaut D. Supplementing salinomycin to diets for growing-finishing pigs. Dtsch Tierarztl Wochenschr, 97 (12); 1990: 520-523.
[10] Harada S, Ishii Y and Yamaguchi K. Extended-spectrum β lactamases: Implications for the clinical laboratory and therapy. Korean J Lab Med. 28; 2008: 401-412.
[11] Visek W. The mode of growth promotion by antibiotics. J Anim Sci. 46; 1978: 1447-1469.
[12] Samanta I. Joardar SN, Das PK, Sar T K, Bandyopadhyay S, Dutta TK and Sarkar S. Prevalence and antibiotic resistance profiles of Salmonella serotypes isolated from backyard poultry flocks in West Bengal, India. J Appl Poult Res. 23; 2014: 1-10.
[13] Mahanti A, Ghosh P, Samanta I, Joardar SN, Bandyopadhyay S, Bhattacharyya D, Banerjee J, Batabyal S, Sar TK and T.K. Dutta. Prevalence of CTX-M-producing Klebsiella spp. in broiler, kuroiler and indigenous poultry in West Bengal state, India. Microbial drug resistance. 24; 2018: 299-306.
[14] Ghosh P, Mahanti A , Samanta I, Joardar SN, Batabyal K, Dey S, Tarafder S and Isore DP. Occurrence of extended-spectrum cephalosporinase-producing Escherichia coli in kuroiler birds. Vet Archiv, 87; 2017: 745-757.
[15] Banerjee A, Bardhan R, Chowdhury S, Joardar SN, Isore DP, Batabyal K, Sar SK, Bandyopadhyay S, Dutta TK and Samanta I. Characterization of beta-lactamase and biofilm producing Enterobacteriaceae isolated from organized and backyard farm ducks.Letters Appl Microbial. 69; 2019: 110-115
[16] Samanta I, Joardar SN, Mahanti A, Bandyopadhyay S, Sar T K, and Dutta TK. Approaches to characterize extended spectrum beta-lactamase/beta-lactamase producing Escherichia coli in healthy organized vis-à-vis backyard farmed pigs in India. Infect Gen Evol. 36; 2015: 224-230.
[17] Samanta A, Mahanti A, Chattaerjee S, Joardar SN, Bandyopadhyay S, Sar TK, Mandal GP, Dutta TK and Samanta I. Pig farm environment as a source of beta-lactamase or AmpC-producing Klebsiella pneumonia and Escherichia coli. Ann Microbiol. 68; 2011: 781-791.
[18] Mahanti A, Samanta I, Bandyopadhyay S and Joardar SN. Molecular characterization and antibiotoic susceptibility pattern of caprine shiga toxin producing-Escherichia coli (STEC) isolates from India. Iran J Vet Res. 16; 2015: 31-35.
[19] Mahanti A, Samanta I, Bandyopadhyay S, Joardar SN, Dutta TK, Batabyal S, Sar TK, Isore DP. Isolation, molecular characterization and antibiotic resistance of shiga toxin-producing Escherichia coli (STEC) from buffalo in India. Letters Appl Microbial. 56; 2013: 291-298.
[20] Batabyal K., Banerjee A, Pal S, Dey S, Joardar SN, Samanta I, Isore DP, Singh AD. Detection, characterization and anti-biogram of extended-spectrum beta-lactamase Escherichia coli isolated from bovine milk samples in West Bengal. Vet World. 11; 2018: 1423-1427.
Received : 30 October 2020
Accepted : 02 February 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81005

Endophytic Fungi and their Metabolites Isolated from Bauhinia Racemosa Lamk Plant

Author
Venkatesan Govindan
Keywords
Bauhinia Racemosa; Bioactive Metabolites; Endophyte Fungi; Tissues Specificity.
Abstract
Bauhinia racemosa family, Caesalpiniaceae is one of the precious resources of the earth. It is traditionally used in the indigenous system of medicine Ayurveda, Unani, and Sidha for the treatment of several ailments like headache, fever, skin and blood diseases, jaundice, chronic dysentery, diarrhea, and leucorrhoea, infection of malaria, boil, glandular swelling, tumors, and cancer. It is also used to cure scorpion bite, to relieve food poisoning in cattle and as a contraceptive by women. Endophytic fungi live in leafage of medicinally important plants are diverse and abundant; also little is known of their terrestrial and habitat variation. Age differences in endophyte infections on young, mature, and senescent leaves of a medicinal plant Bauhinia racemosa were studied. Enzyme evaluation, it was observed that the endophytic fungi species Phyllosticta sp., Colletotrichum sp., Aspergillus species were presented four enzymes amylase, pectinase, lipolytic, and cellulose activity. Particularly have indicated only cellulose was produced in Aspergillus niger. The endophytic fungus was tested against standard bacterial and fungal cultures. In vitro antimicrobial test was carried out by the agar well diffusion method. The minimum inhibitory concentration test was performed by the modified agar well diffusion method. Endophytic fungi showed a broad spectrum of antimicrobial activity as it inhibited Gram-positive bacteria in Bacillus, and fungi in Colletotrichum.
References
[1] Strobel G, Daisy B. Bioprospecting for microbial endophytes and their natural products. Microbiology and Molecular Biology Reviews. 67(4); 2003: 491–502.
[2] Schmit JP, Mueller GM. An estimate of the lower limit ofglobal fungal diversity. Biodiversity Conservation. 16; 2007: 99-111.
[3] Arnold AE, Maynard Z, Gilbert GS, Coley PD, Kursar TA. Aretropical fungal endophytes hyperdiverse?. Ecology Letter. 3; 2000: 267-274.
[4] Suryanarayanan TS, Kumaresan V, Johnson JA. Foliar Fungal endophytes from two species of the mangrove Rhizophora. Canadian Journal of Microbiology. 44; 1998: 1003-1006.
[5] Suryanarayanan TS, Kumaresan V. Endophytic fungi of some halophytes from an estuarine mangrove forest. Mycological Research. 104; 2000: 1465-1467.
[6] Venkatesan G, Arun G. Endophytes Fungi Associated with a water Hyacinth of Eichhornia Crassipes (Mart.) Solms. International Journal of Scientific Research in Biological Sciences. 7(3); 2020: 62-66.
[7] Suryanarayanan TS, Murali TS, Venkatesan G. Occurrence and distribution of fungal endophytes in tropical forests across a rainfall gradient. Canadian Journal of Microbiology. 80; 2002: 818-826.
[8] Murali TS, Suryanarayanan TS, Venkatesan G. Fungal endophyte communities in two tropical forests of southern India: diversity and host affiliation. Mycological Progress, 6(3); 2007: 191-199.
[9] Suryanarayanan TS, Murali TS, Thirunavukkarasu N, Rajulu MBG, Venkatesan G, Sukumar R. Endophytic fungal communities in woody perennials of three tropical forest types of the Western Ghats, southern India. Biodiversity Conservation. 20; 2011: 913-928.
[10] Petrini O. Taxonomy of of endophytic fungi of aerial plant tissues. In: Microbiology of the Phyllosphere (eds. N.J. Fokkema, J.Van den Heuvel). 1986: pp 175-187. Cambridge University Press, Cambridge.
[11] Gunatilaka AAL. “Natural products from plant-associated micro-organisms: Distribution, structural diversity, bioactivity, and impli-cations of their occurrence”. Journal of Natural Product. 69; 2006: 509-526.
[12] Prabavathy D, Valli Nachiyar C. Screening for Extracellular Enzymes and Production of Cellulase by an Endophytic Aspergillus sp, Using Cauliflower Stalk as substrate. International Journal on Applied Bioengineering. 6(2); 2012: 40-48 .
[13] Bills GF, Polishook JD. Recovery of endophytic fungi from Chamaecyparis thyoides. Sydowia. 44; 1992: 1-12.
[14] Suryanarayanan TS. Light incubation: a neglected procedure in mycology. The Mycologist. 6; 1992: 144.
[15] Hata K, Futai K. Endophytic fungi associated with healthy pine needles and needles infested by the pine needles gall midge, Thecodiplosis japonesis. Canadian Journal of Botany. 73; 1995: 384-390.
[16] Hankin L, Anagnostakis SL. The use of solid media for detection of enzyme production by fungi. Mycologia. 67; 1975: 597-607.
[17] Arnold AE, Edward Allen H. Canopy cover and leaf age affect colonization by tropical fungal endophytes: Ecological pattern and process in Theobroma cacao (Malvaceae). Mycologia. 95(3); 2003: 388–398.
[18] Narasimha G, Reddi Pradeep M, Sridevi A. Chemical Pretreatment of Agricultural Feedstock for Enhanced Production of Cellulase by Mutant Fungus, Aspergillus Niger. Journal of Applied Biotechnol Bioeng. 1(1); 2016: 01-05.
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[20] Venkatesan G, Ramesh Kumar J. Diversity of endophytes fungi assemblages in an aquatic eel weed plant of Vallisneria spiralis L, International Journal of Life Sciences. 8(2); 2020: 299-307.
Received : 19 October 2020
Accepted : 30 January 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81004

Enabling a Smart Farming System for the Indian Floriculture Industry

Author
Dr. Indumathi S K
Keywords
Smart Fertigation; Sensors Network; Internet of Things.
Abstract
Indian floriculture industry has grown by multiple folds in the past decade and has become one of the top ten leading producers of varieties of flower production. This tremendous growth of floriculture industry has proportionally also contributed to the depletion of environmental system. The paper proposes a technology-based fertilizer application infrastructure has been designed for an optimal growth of plants under a controlled usage of fertilizers. The model assures a fertigation process with reduced intervals of fertilization and a reduced consumption of water. A technology for fertilizer application infrastructure is based on Internet of Things (IoT) that helps to achieve an optimal growth of plants under a controlled usage of fertilizers and a promised environmental sustainability.
References
[1] P. Rajalakshmi, S. Devi Mahalakshmi , “IOT Based Crop-Field Monitoring And Irrigation Automation” in 10th International conference on Intelligent systems and control (ISCO) 7–8 Jan 2016, published in IEEE Xplore,Nov2016.
[2] Sujatha Anand et.al, “Monitoring of soil nutrients using iot for optimizing the use of fertilizers,” International Journal of Science, Engineering and Technology Research (IJSETR) Volume 8,Issue 4,April 2019, ISSN:2278-7798
[3] Tadeli Yeshiwas, “Social, Economical and Environmental Issues of Floriculture Sector Development in Ethiopia”, J. Mod. Sim. Mater., vol. 1, no. 1, pp. 1-2, https://www.researchgate.ne t/publication /329912312
[4] Dr.B. Mathivanan, “A study on rose cultivation and marketing pattern,” Journal of Exclusive Management Science –December 2013-Vol 2 Issue 12 – ISSN 2277 – 5684
[5] Sweksha Goyal et al, “Smart Agriculture using IOT”, International Journal of Computer Science and Mobile Computing, Vol.8 Issue.5, May- 2019, pg. 143-148
[6] Mohanraj I et. al, “Field Monitoring and Automation using IOT in Agriculture Domain”, Proceedings of 6th International Conference On Advances In Computing & Communications, ICACC 2016, 6-8 September 2016, Cochin, India
[7] Balaji. G, “Survey of IOT in agriculture” IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 10, Issue 11, November 2020, Series –I, PP 26-32
[8] Aman Kumar Dewangan “Application of IoT and Machine Learning in Agriculture”, International Journal of Engineering Research & Technology, Volume-09-Issue-07-July-2020
[9] 1 Priyadharsnee.K et.al, “AN Iot Based Smart Irrigation System”, International Journal of Scientific & Engineering Research Volume 8, Issue 5, May-2017 44 ISSN 2229-5518
[10] Pavan Kumar Naik et. al, “Arduino Based Automatic Irrigation System Using IoT”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology Volume 2 Issue 3| ISSN : 2456-3307
Received : 21 October 2020
Accepted : 28 January 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81003

Heat and Mass Transfer of Steady Hydromagnetic Flow on a Continuously Moving Surface with Soret Effect and Thermophoretic Effect

Author
Govind Pathak
Keywords
Heat Transfer; Mass Transfer; Hydromagnetic Flow; Soret Number; Thermophoretic Parameter
Abstract
In the present research paper Thermophoretic and Soret effects in steady free convection flow with magnetic field along with moving surface is studied. Thermophoresis effects is not negligible due to its important applications in engineering mainly for removing small particles from gas streams, in determining exhaust gas particle trajectories from combustion devices and in studying the material deposition on turbine blades. The non-linear boundary layer equations are converted into ordinary differential equation and applying Runge-Kutta shooting method. The effects of non-dimensional temperature parameter, Prandtl number, temperature exponent, magnetic parameter, Eckert number, Lewis number, Soret number and thermophoretic parameter have been studied. The velocity profile, temperature distribution and concentration distribution graphs are plotted and discuss in details.
References
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Received : 13 November 2020
Accepted : 17 January 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81002

Implementation of U-Shaped Probe in the Construction of a Fiber Optic Sensor to Determine the Refractive Index of Liquids in the dynamic Range of 300C to 600C

Author
Dr. S. Venkateswara Rao
Keywords
Sensing Probe; Intensity Variation; Range of Temperatures; Dynamic Range; U-Shaped Probe
Abstract
The whole nature of most of the substances is determined by the study of measurement of especially the refractive index, which decides their applicability and utility in different fields at various occasions. A uniform U-shaped glass probe of very fine dimension is shown to sense the refractive index of a liquid in which the U-shaped glass rod is immersed at various temperatures. In the present paper, the refractive index of liquids such as methanol mixed in benzene and propanol mixed in benzene was studied over a wide range of temperatures ranging between 300C to 600C using a U-shaped glass sensing probe. With increase in the temperature of the active medium surrounding the glass probe, the slope of the sensor response is found to be dramatically increased in terms of light reception. The U-shaped glass rod is sensitive to the presence of absorption at the wavelengths at which the refractive index is being measured and to the chemical nature of the solute. The output power variations in the intensity of the light with changes in the temperature ranging between 300C to 600C have been recorded. The sensor so developed can be used to determine the refractive index of liquids either transparent or dark whose refractive index values lie between 1.33nD and1.50nD and the dynamic range of temperatures between 300C to 600C at the wavelength of 633nm.
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Received : 29 September 2020
Accepted : 24 January 2021
Published : 11 February 2021
DOI: 10.30726/esij/v8.i1.2021.81001