Archive

Abstract:

Today communication needs huge operational speed. This will be accomplished in case the conventional carrier of data, i.e. electron is supplanted by a photon for gadgets based on switching and logic. Gates are the basic building pieces of advanced frameworks. Different logic and arithmetic operations can be done using this gate. Optical logic and arithmetic operations are exceptionally much anticipated in high-speed communication frameworks. In this paper, we have presented parallel models to perform the addition of two binary digits based on terahertz optical asymmetric demultiplexer (TOAD)/semiconductor optical amplifier (SOA)-assisted Sagnac gates. Using only two TOAD-based switches we have designed a parallel half adder. This optical circuit increases the speed of calculation and is also capable of synthesizing light as an input to form the output.  The most advantage of this parallel circuit is that no synchronization is required for distinctive inputs. The circuit is hypothetically planned and confirmed by numerical simulations.

Keywords:

Terahertz optical asymmetric demultiplexer,semiconductor optical amplifier,half adder,optical logic,

Refference:

I. Bhattacharyya A, Gayen D. K and Chattopadhyay T, “Alternative All-optical Circuit of Binary to BCD Converter Using Terahertz Asymmetric Demultiplexer Based Interferometric Switch”, Proceedings of 1st International Conference on Computation and Communication Advancement, 2013.
II. Gayen D. K, Roy J. N, Taraphdar C, and Pal R. K, “All-optical reconfigurable logic operations with the help of terahertz optical asymmetric demultiplexer”, International Journal for Light and Electron Optics. vol. 122, pp: 711-718, 2011.
III. Gayen D. K, Chattopadhyay T, Das M. K, Roy J. N and Pal R. K, “All-optical binary to gray code and gray to binary code conversion scheme with the help of semiconductor optical amplifier -assisted sagnac switch”, IET Circuits, Devices & Systems. vol. 5, pp: 123-131, 2011.
IV. Ghosh P, Kumbhakar D, Mukherjee A. K and Mukherjee K, “An all-optical method of implementing a wavelength encoded simultaneous binary full-adder-full-subtractor unit exploiting nonlinear polarization rotation in semiconductor optical amplifier International”, Journal for Light and Electron Optics. vol. 122, pp: 1757-1763, 2011.
V. Kim J. H, Kim S. H, Son C. W, Ok S. H. Ok, Kim S. J, Choi J. W, Byun Y. T, Jhon Y. M Jhon, Lee S, Woo D. H and Kim S. H. Kim, “Realization of all-optical full-adder using cross-gain modulation”, Proceedings of the Conference on Semiconductor Lasers and Applications. SPIE. vol. 5628, pp: 333-340, 2005.
VI. Li P, Huang D, Zhang X and Zhu G, “Ultra-high speed all-optical half-adder based on four wave mixing in semiconductor optical amplifier” Optics Express. vo1.14, pp: 11839-47, 2006.
VII. Minh H. L., Ghassemlooy Z., and Ng W. P, “Characterization and performance analysis of a TOAD switch employing a dual control pulse scheme in high speed OTDM demultiplexer” IEEE Communications Letters. vol.12, pp: 316-318, 2008.
VIII. Mukhopadhyay S and Chakraborty B, “A method of developing optical half- and full-adders using optical phase encoding technique”, Proceedings of the Conference on Communications, Photonics and Exhibition (ACP). TuX6 1-2, 2009.
IX. Mukherjee K, “Method of implementation of frequency encoded all-optical half- adder, half-subtractor, and full-adder based on semiconductor optical amplifiers and add drop multiplexers”, International Journal for Light and Electron Optics. vol. 122, pp: 1188-1194, 2011.

X. Poustie A, Blow K. J, Kelly A. E and Manning R. J, “All-optical full-adder with bit differential delay”, Optics Communications. vol. 168, pp: 89-93, 1999.
XI. Sokoloff J. P, Prucnal P. R, Glesk I and Kane M, “A terahertz optical asymmetric demultiplexer (TOAD)”, IEEE Photonics Technology Letters. vol. 5, pp: 787-790, 1993.
XII. Suzuki M and H. Uenohara, “Invesigation of all-optical error detection circuitusing SOA-MZI based XOR gates at 10 Gbit/s”, Electronics Letters. vol. 45, pp: 224-225, 2009.
XIII. Wang B, Baby V, Tong W, Xu L, Friedman M, Runser R, Glesk I and Prucnal P, “A novel fast optical switch based on two cascaded terahertz optical asymmetric demultiplexers (TOAD)”, Optics Express. vol. 10 15-23, 2002.
XIV. Zoiros K. E, Vardakas J, Houbavlis T and Moyssidis M, “Investigation of SOA-assisted Sagnac recirculating shift register switching characteristics”, International Journal for Light and Electron Optics. vol. 116, pp: 527-541, 2005.
XV. Zoiros K. E, Avramidis P and Koukourlis C. S, “Performance investigation of semiconductor optical amplifier based ultra-fast nonlinear interferometer in nontrivial switching mode”, Optical Engineering. vol. 47, pp: 115006-11, 2008.

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Abstract:

In this paper, we have introduced and studied some new notions of  T₀ separation axiom in fuzzy soft topological spaces using quasi-coincident relation for fuzzy soft points. We have shown a relationship between ours and other counterparts and observed that all these notions satisfy good extension, hereditary, productive, and projective properties. Moreover, we have also shown that these notions are preserved under one-one, onto, and fuzzy soft continuous mappings. Finally, initial and final soft topologies are studied also.

Keywords:

Fuzzy soft set,Fuzzy Soft Topological Spaces,Quasi-coincidence,Fuzzy Soft T₀Topological Space,Initial and Final Fuzzy Soft Topology,

Refference:

I. A. Aygunglu, H. Aygun, Introduction to Fuzzy Soft Groups, Comput. Math. Appl., 58, (2009), pp 1279-1286.
II. A. S. Atmaca, I. Zorlutuna, On Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), (2013), pp 377-386.
III. Aziz-ul-Hakim, H. Khan, I. Ahmad, A. Khan, Fuzzy Bipolar Soft Semiprime Ideals in Ordered Semigroups, Heliyon, 7, (2021).
IV. B. Ahmad, A. Kharal, On Fuzzy Soft Sets, Hindawi Publishing Corporation, Advances in Fuzzy Systems Article ID 586507, (2009).
V. B. P. Varol, H. Aygun, Fuzzy Soft Topology, Hacettepe Journal of Mathematics and Statistics, 41 (3), (2012), pp 407-419.
VI. B. Tanay, M. B. Kandemir, Topological Structure of Fuzzy Soft Sets, Computer and Mathematics with Applications, 61, (2011), pp 2952-2957.
VII. D. Chen, E. C. C. Tsang, D. S. Yeung, X. Wang, The parameterization Reduction of Soft Set and Its Application, Computers and Mathematics with Applications, 49, (2005), pp 757-763.
VIII. D. Molodtsov, Soft Set Theory First Results, Comput. Math. Appl., 37 (4-5), (1999), pp 19-31.
IX. H. Aktas, N. Cagman, Soft Sets and Soft Group, Information Science, 177 (2007), pp 2726-2735.
X. K. V. Babitha, J. J. Sunil, Soft Set Relations and Functions, Comput. Math. Appl., 60 (7), (2010), pp 1840-1849.
XI. M. I. Ali, M. Shabir, Comments on De Morgan’s Law in Fuzzy Soft Sets, Int. J. Fuzzy Math. 18, (2010), pp 679-686.
XII. M. R. Amin, M. S. Hossain, S. S. Miah, Fuzzy Pairwise Regular Bitopological Space in Quasi-coincidence Sence, J. Bangladesh Acad. Sci., 42 (2), (2020), pp 139-143.
XIII. M. Shabir, M. Naz, On Soft Topological Spaces, Comput. Math. Appl., 61, (2011), pp 1786-1799.
XIV. M. Terepeta, On Separating Axioms and Similarity of Soft Topological Spaces, Soft Comput., 23, (2019), pp 1049-1057.
XV. O. Gocur, A. Kopuzlu, On Soft Separation Axioms, Ann. Fuzzy Math. Inform., 9 (5), (2015), pp 817-822.
XVI. P. K. Maji, R. Biswas, A. R. Roy, Fuzzy Soft Sets, J. Fuzzy Math., 9 (3), (2001), pp 589-602.
XVII. R. Amin, R. Islam, New Concepts on 𝑅1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math., 22 (2), (October 2021), pp 123-132.
XVIII. S. Al Ghour, A. B. Saadon, On Some Generated Soft Topological Spaces and Soft Homogeneity, Heliyon, 5 (2009).
XIX. S. Hussain, B. Ahmad, Soft Separation Axioms in Soft Topological Spaces, Hacettepe Journal of Mathematics and Statistics, 44 (3), (2015), pp 559-568.
XX. S. Mishra, R. Srivastava, Hausdorff Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 9 (2), (2015), pp 247-260.
XXI. S. Mishra, R. Srivastava, On 𝑇0 and 𝑇1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 10 (4), (2015), pp 591-605.
XXII. S. Nazmul, S. K. Samanta, Soft Topological Groups, Kochi J. Math., 5, (2010), pp 151-161.
XXIII. S. Roy, T. K. Samanta, A Note on Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), (2012), pp 305-311.
XXIV. S. S. Miah, M. R. Amin, Certain Properties on Fuzzy (𝑅0) Topological Spaces in Quasi-coincidence Sense, Annals of Pure and Applied Mathematics, 14 (1), (2007), pp 125-131.
XXV. S. S. Miah, M. R. Amin, M. Jahan, Mappings on Fuzzy (𝑇0) Topological Spaces in Quasi-coincidence Sense, J. Math. Comput. Sci., 7 (5), (2007), pp 883-894.
XXVI. S. S. Miah, M. R. Amin, M. Shahjala, Separation Axiom (𝑇0) on Fuzzy Bitopological Space in Quasi-coincidence Sense, GANIT J. Bangladesh Math. Soc., 40 (2), (2020), pp 156-162.
XXVII. S. Saleh, A. M. Abd El-Latif, A. Al-Salemi, On Separation Axioms in Fuzzy Soft Topological Spaces, South Asian Journal of Mathematics, 8 (2), (2018), pp 92-109.

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Abstract:

Given any space-time field, Empirical orthogonal function (EOF) analysis finds a set of orthogonal spatial patterns along with a set of associated uncorrelated time series or principal components (PCs). Spatial orthogonality and temporal uncorrelation of EOFs and PCs respectively impose limits on the physical interpretability of EOF patterns. This is because physical processes are not independent, and therefore physical modes are expected in general to be non-orthogonal. Rotated empirical orthogonal functions (REOF) were introduced to generate general localized structures by compromising some of the EOF properties such as orthogonality. EOF and REOF analysis are carried out for the significant wave height (SWH) data for the Bay of Bengal (BOB) region for the period 1958 to 2001. Separate experiments were conducted for all the months together and also for July and December representing the southwest and northeast monsoon periods. The first eigenmodes account for 84%, 68%, and 59% of the total variability for the above three cases respectively. The REOF proved to be more effective than EOF for the above region.

Keywords:

Rotated empirical orthogonal functions,Principal components,Data analysis,Significant wave height,Bay of Bengal,

Refference:

I. Craddock, J. M., 1973: Problems and prospects for eigenvector analysis in meteorology. The statistician, 22, 133-145.
II. Crommelin, D. T., and A. J. Majda, 2004: Strategies for model reduction: Comparing different optimal bases. J. Atmos. Sci., 61, 2206–2217.
III. Farrell, B. F., and P. J. Ioannou, 1996: Generalized stability theory. Part I: Autonomous operators. J. Atmos. Sci., 53, 2025–2040.
IV. Hannachi, A., I. Joliffe, and D. Stephenson, 2007: Empirical orthogonal functions and related techniques in atmospheric science: Areview. Int. J. Climatol., 27, 1119–1152, doi:10.1002/joc.1499.
V. Hotelling, H., 1933: Analysis of a complex of statistical variables into principal components. J. Educ. Psych,, 24, 417-520.
VI. Jolliffe, I. T., 2002: Principal Component Analysis. Springer-Verlag, 2nd Edition, New York.
VII. Kleeman, R., 2008: Stochastic theories for the irregularity of ENSO. Philos. Trans. Roy. Soc., 366A, 2509–2524, doi:10.1098/rsta.2008.0048.
VIII. Kutzbach, J. E., 1967: Empirical eigenvectors of sea-level pressure, surface temperature and precipitation complexes over North America. J. Appl.Meteor., 6, 791-802.
IX. Lo`eve, M., 1978: Probability theory, Vol II, 4’th ed., Springer-Verlag, 413pp.
X. Lorenz, E. N., 1956: Empirical orthogonal functions and statistical weather prediction. Technical report, Statistical Forecast Project Report 1, Dept. of Meteor., MIT, 1956. 49pp.
XI. Monahan, A. H., and A. Dai, 2004: The spatial and temporal structure of ENSO nonlinearity. J. Climate, 17, 3026–3036.
XII. North, G. R., T. L., Bell, R. F. Cahalan, and F. J. Moeng, 1982: Sampling errors in the estimation of empirical orthogonal functions. Mon.Weather Rev., 110, 699-706.
XIII. North, G. R., 1984: Empirical orthogonal functions and normal modes. J. Atmos. Sci., 41, 879–887.
XIV. Penland, C., 1996: A stochastic model of Indo-Pacific sea surface temperature anomalies. Physica D, 98, 534–558.
XV. von Storch, H., and F. W. Zwiers, 1999: Statistical Analysis in Climate research, Cambridge University Press, Cambridge.
XVI. Weare, B. C., and J. S. Nasstrom, 1982: Examples of extended empirical orthogonal function analysis. Mon. Weath. Rev., 110, 481-485.
XVII. Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences. Academic Press, San Diego.

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Abstract:

This paper aims to establish the para-compactness concept in intuitionistic fuzzy topological space. Here we give three new notions related to para-compactness and one new notion of IF--compactness in intuitionistic fuzzy topological space. Also, we discuss separation axioms in intuitionistic fuzzy para-compactness and some of its features. Furthermore, using some provisos we will find a relation among second countable, para-compactness, and IF--compactness in intuitionistic fuzzy topological spaces.

Keywords:

Fuzzy set,Intuitionistic fuzzy set,Intuitionistic fuzzy topological space,Intuitionistic fuzzy compactness,Intuitionistic fuzzy para-compactness,

Refference:

I. Ahmed, E., Hossain, M.S. and Ali, D.M. (2014). On Intuitionistic Fuzzy T0 Spaces, Journal of Bangladesh Academy of Sciences, 38(2) 197-207.
II. Ahmed, E., Hossain, M.S. and Ali, D.M. (2015). On Intuitionistic Fuzzy R0 Spaces, Annals of Pure and Applied Mathematics, 10(1), 7-14.
III. Ahmed, E., Hossain, M.S. and Ali, D.M. (2015). On Intuitionistic Fuzzy R1 Spaces, J. Math. Comput. Sci, 5(5), 681-693.
IV. Ahmed, E., Hossain, M.S. and Ali, D.M. (2014). On Intuitionistic Fuzzy T1 Spaces, Journal of Physical Sciences, 19, 59-66.
V. Ahmed, E., Hossain, M.S. and Ali, D.M. (2014). On Intuitionistic Fuzzy T2 Spaces, IOSR Journal of Mathematics (IOSR-JM), 10(6), 26-30.
VI. Ahmad, M.K., Salahuddin. (2013). Fuzzy Generalized Variational Like Inequality problems in Topological Vector Spaces, Journal of Fuzzy Set Valued Analysis Volume 2013, doi:10.5899/2013/jfsva-00134.
VII. Ali, A.M., Senthil, S., Chendralekha, T. (2016). Intuitionistic Fuzzy Sequences in Metric Space, International Journal of Mathematics and its Applications Volume 4, Issue 1–B, 155–159.
VIII. Ali, A.M., Kanna, G.R. (2017). Intuitionistic Fuzzy Cone Metric Spaces and Fixed Point Theorems, International Journal of Mathematics and its Applications Volume 5, Issue 1–A, 25–36.
IX. Atanassov, K.T. (1986) Intuitionistic fuzzy sets,Fuzzy Sets and Systems, 20(1), 87-96.
X. Atanassov, K.T., Stojanova D., Cartesian products over intuitionistic fuzzy sets, Methodology of Mathematical Modelling, vol.1, Sofia, 1990, No.1.
XI. Barile, M. To space, Retrived from http://mathworld.wolfarm.com/T0-space.html.
XII. Bayhan, S. and Coker, D. (1996).On fuzzy separation axioms in intuitionistic fuzzy topological space, BUSEFAL, 67, 77-87.
XIII. Bayhan, S., Coker, D. (2005). Pairwise Separation axioms in intuitionistic topological Spaces, Hacettepe Journal of Mathematics and Statistics, 34, 101-114.
XIV. Chang, C.L. (1968). Fuzzy Topological Space, J. of Mathematical Analysis and Application, 24, 182-90.
XV. Coker, D. (1996). A note on intuitionistic sets and intuitionistic points, Tr. J. of Mathematics, 20(3), 343-351.
XVI. Coker, D. (1997). An introduction to intuitionistic fuzzy topological spaces, Fuzzy Sets and Systems, 88(1), 81-89.
XVII. Coker, D. and Bayhan, S. (2001). On Separation Axioms in Intuitionistic Topological Space, Int. J. of Math. Sci., 27(10), 621-630.
XVIII. Coker, D. and Bayhan, S. (2003). On T1 and T2 Separation Axioms in Intuitionistic fuzzy Topological Space, Journal of Fuzzy Mathematics, 11(3), 581-592.
XIX. Das, S. (2013). Intuitionistic Fuzzy Topological Spaces (MS Thesis Paper), Dept. of Math, National Inst. of Tech.
XX. Fang, J. & Guo, Y. (2012). Quasi-coincident neighbourhood structure of relative I-fuzzy topology and its applications, Fuzzy Sets and Systems, 190, 105-117.
XXI. Hassan, Q.E. (2007).On some kinds of fuzzy connected spaces, Applications Of Mathematics, 52, N0.4, 353-361.
XXII. Immaculate, H.J., Arockiarani, I. (2015). A new class of connected spaces in intuitionistic topological spaces, Int. J. of Appl. Research, 1(9), 720-726.
XXIII. Islam, R., Hossain, M.S. and Hoque, M.F. (2020). A study on L-fuzzy T1 Spaces, Notes on Intuitionistic Fuzzy Set, 26(3), 33-42.
XXIV. Islam, M.S., Hossain, M.S. and Asaduzzaman, M. (2017). Level Seperation on Intuitionistic Fuzzy T0 spaces, Intern. J. of Fuzzy Mathematical Archive, 13(2),123-133.
XXV. Islam, M.S., Hossain, M.S. and Asaduzzaman, M. (2018). Level separation on Intuitionistic fuzzy T2 spaces; J. Math. Compu. Sci., 8(3), 353-372.
XXVI. Lee, S.J. and Lee, E.P. (2000). The Category of Intuitionistic Fuzzy Topological Space, Bull. Korean Math. Soc., 37(1), 63-76.
XXVII. Lee, S.J. and Lee, E.P. (2004). Intuitionistic Fuzzy Proximity Spaces, IJMMS, 49, 2617-2628.
XXVIII. Mahbub, M.A., Hossain, M.S. and Hossain, M.A. (2018). Some Properties of Compactness in Intuitionistic Fuzzy Topological Spaces, Intern. J. of Fuzzy Mathematical Archive, 16(1), 39-48.
XXIX. Mahbub, M.A., Hossain, M.S. and Hossain, M.A. (2019). Separation Axioms in Intuitionistic Fuzzy Compact Topological Spaces, ISPACS, 2019(1), 14-23.
XXX. Mahbub, M.A., Hossain, M.S. and Hossain, M.A. (2019). ON Q-COMPACTNESS IN INTUITIONISTIC FUZZY TOPOLOGICAL SPACES, J. of Bangladesh Acad. Sci., 43(2), 197-203.
XXXI. Mahbub, M. A., M.S. Hossain and M. Altab Hossain, 2021. Connectedness concept in intuitionistic fuzzy topological spaces, Notes on Intuitionistic Fuzzy Sets, 27(1), 72-82.
XXXII. Minana, J.J. and Sostak, A. (2016). Fuzzifying topology induced by a strong fuzzy metric, Fuzzy Sets and Systems, 300, 24-39.
XXXIII. Ramadan, A.A., Abbas, S.E., Abd El-Latif, A.A. (2005). Compactness in Intuitionistic Fuzzy Topological Spaces, Int. J. of Math. And Mathematical Sciences, 2005(1), 19-32.
XXXIV. Singh, A.K. and Srivastava, R. (2012). SeparationAxioms in Intuitionistic Fuzzy Topological Spaces, Advances in Fuzzy Systems, 2012, 1-7.
XXXV. Ying-Ming, L. and Mao-Kang, L. (1997). Fuzzy Topology, World Scientific Publishing Co. Pte. Ltd..
XXXVI. Zadeh, L.A. (1965). Fuzzy sets, Information and Control, 8(3), 338-353.

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Abstract:

This work presents a computational investigation of turbulent flow inside a mixing elbow pipe and this study focus on the behaviour of fluid flow in a mixing elbow. Mixing elbow is a region where two types of fluid flow with different parameters and high Reynolds number is intensively mixed together and is among typical geometries exactly where velocity, as well as temperature fluctuation, happen. A CFD model of turbulent flow in the elbow pipes is implemented using the ANSYS tool. RANS turbulent models, the k-ε model are used for the simulation and the variation of axial velocity, wall shear stress, and turbulent intensity along the length of the elbow pipes are studied. The fluid used for this purpose is water. The simulations are carried out with different Reynolds numbers rangings from 2,500 to 10,000.

Keywords:

Turbulent Flow,Mixing Elbow,k-ε Model.,

Refference:

I. Bhatia, S. S., Nishad, R., Patil, S. R., Dewangan, M. K., et. al. [2015]. “Elbow Mixture Analysis”, “International Journal of Advances in Production and Mechanical Engineering (Ijapme)”, PP 2394-6210.
II. Dutta, P., Saha, S. K., Nandi, N., Pal, N., [2016]. “Numerical study on flow separation in 90° pipe bend under high Reynolds number by k-ε modeling” “Engineering Science and Technology, an International Journal”, PP 904–910.
III. Forney, L. J., and H. C., Lee,[1982] “Optimum Dimensions for Pipeline Mixing at a T Junction”, AIChE J., 28(6), 980-987.
IV. Hutli E. et al, [2014]. “Experimental Approach to Investigate the Dynamics of Mixing Coolant Flow in Complex Geometry using PIV and PLIF Techniques”, “Thermal Science International Scientific Journal”, DOI,REFERENCE:10.2298/TSCI130603051H.
V. M. Nematollahi, B. Khonsha, [2012] “Comparison of T-junction flow pattern of water and sodium for different geometries of power plant piping systems”. Annals of Nuclear Energy 39, pp 83–93.
VI. Mazumder, H. Q., [2012]. “CFD Analysis of the Effect of Elbow Radius on Pressure Drop in Multiphase Flow”, Hindawi Publishing Corporation Modelling and Simulation in Engineering, Article ID 125405, PP 8. doi:10.1155/2012/125405.
VII. Nematollahi M., et al, [1985] “Effect of Bend Curvature Ratio on Flow Pattern at a Mixing Tee after a 90 Degree Bend”, “International Journal of Engineering (IJE)”, pp.478-487
VIII. Patankar S. V.,[1980] “Numerical heat transfer and fluid flow”. USA, McGRAW-HILL Book Company, 197 p.
IX. Seyed Mohammad Hosseini, Kazuhisa Yuki, Hidetoshi Hashizume, [2008] “Classification of turbulent jets in a T-junction area with a 90-deg bend upstream”, “International Journal of Heat and Mass Transfer 5”, pp 2444–2454.

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Abstract:

In this paper, three notions of  property in fuzzy soft bitopological spaces in the sense of quasi-coincidence for fuzzy soft points has been introduced and studied. Hereditary, productive, and projective properties are satisfied by these notions. Moreover, it is observed that all these concepts are preserved under one-one, onto, fuzzy open, and FSP continuous mappings.

Keywords:

Fuzzy soft set,Fuzzy soft bitopological Spaces,Quasi-coincidence,Fuzzy Soft R₁ bitopological Space,Mappings,

Refference:

I. D. Molodtsov, Soft Set Theory First Results, Comput. Math. Appl., 37 (4-5), (1999), pp 19-31.
II. P. K. Maji, R. Biswas, A. R. Roy, Fuzzy Soft Sets, J. Fuzzy Math., 9 (3), (2001), pp 589-602.
III. D. Chen, E. C. C. Tsang, D. S. Yeung, X. Wang, The parameterization Reduction of Soft Set and Its Application, Computers and Mathematics with Applications, 49, (2005), pp 757-763.
IV. B. Ahmad, A. Kharal, On Fuzzy Soft Sets, Hindawi Publishing Corporation, Advances in Fuzzy Systems Article ID 586507, (2009).
V. S. Al Ghour, A. B. Saadon, On Some Generated Soft Topological Spaces and Soft Homogeneity, Heliyon, 5 (2009).
VI. H. Aktas, N. Cagman, Soft Sets and Soft Group, Information Science, 177 (2007), pp 2726-2735.
VII. Aziz-ul-Hakim, H. Khan, I. Ahmad, A. Khan, Fuzzy Bipolar Soft Semiprime Ideals in Ordered Semigroups, Heliyon, 7, (2021).
VIII. A. Aygunglu, H. Aygun, Introduction to Fuzzy Soft Groups, Comput. Math. Appl., 58, (2009), pp 1279-1286.
IX. S. Nazmul, S. K. Samanta, Soft Topological Groups, Kochi J. Math., 5, (2010), pp 151-161.
X. B. P. Varol, H. Aygun, Fuzzy Soft Topology, Hacettepe Journal of Mathematics and Statistics, 41 (3), (2012), pp 407-419.
XI. B. Tanay, M. B. Kandemir, Topological Structure of Fuzzy Soft Sets, Computer and Mathematics with Applications, 61, (2011), pp 2952-2957.
XII. S. S. Miah, M. R. Amin, M. Jahan, Mappings on Fuzzy (𝑇0) Topological Spaces in Quasi-coincidence Sense, J. Math. Comput. Sci., 7 (5), (2007), pp 883-894.
XIII. S. S. Miah, M. R. Amin, Certain Properties on Fuzzy (𝑅0) Topological Spaces in Quasi-coincidence Sense, Annals of Pure and Applied Mathematics, 14 (1), (2007), pp 125-131.
XIV. S. S. Miah, M. R. Amin, M. Shahjalal, Separation Axiom (𝑇0) on Fuzzy Bitopological Space in Quasi-coincidence Sense, GANIT J. Bangladesh Math. Soc., 40 (2), (2020), pp 156-162.
XV. M. R. Amin, M. S. Hossain, S. S. Miah, Fuzzy Pairwise Regular Bitopological Space in Quasi-coincidence Sence, J. Bangladesh Acad. Sci., 42 (2), (2020), pp 139-143.
XVI. S. Saleh, A. M. Abd El-Latif, A. Al-Salemi, On Separation Axioms in Fuzzy Soft Topological Spaces, South Asian Journal of Mathematics, 8 (2), (2018), pp 92-109.
XVII. M. Terepeta, On Separating Axioms and Similarity of Soft Topological Spaces, Soft Comput., 23, (2019), pp 1049-1057.
XVIII. M. Shabir, M. Naz, On Soft Topological Spaces, Comput. Math. Appl., 61, (2011), pp 1786-1799.
XIX. S. Hussain, B. Ahmad, Soft Separation Axioms in Soft Topological Spaces, Hacettepe Journal of Mathematics and Statistics, 44 (3), (2015), pp 559-568.
XX. O. Gocur, A. Kopuzlu, On Soft Separation Axioms, Ann. Fuzzy Math. Inform., 9 (5), (2015), pp 817-822.
XXI. S. Mishra, R. Srivastava, On 𝑇0 and 𝑇1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 10 (4), (2015), pp 591-605.
XXII. R. Amin, R. Islam, New Concepts on 𝑅1 Fuzzy Soft Topological Spaces, Ann. Fuzzy Math., 22 (2), (October 2021), pp 123-132.
XXIII. S. Mishra, R. Srivastava, Hausdorff Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 9 (2), (2015), pp 247-260.
XXIV. S. Roy, T. K. Samanta, A Note on Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), (2012), pp 305-311.
XXV. A. S. Atmaca, I. Zorlutuna, On Fuzzy Soft Topological Spaces, Ann. Fuzzy Math. Inform., 5 (2), (2013), pp 377-386.
XXVI. K. V. Babitha, J. J. Sunil, Soft Set Relations and Functions, Comput. Math. Appl., 60 (7), (2010), pp 1840-1849.

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Abstract:

India Meteorological Department has started issuing district-level weather forecasts for up to 5 days on an operational basis from 1st June 2008. The weather parameters related to agro, namely rainfall, maximum and minimum temperature, wind speed, and direction, relative humidity, and cloudiness were chosen for outputs from the model. The rainfall forecast is generated based on multi-model ensemble techniques ( MME ) and ECMWF forecasts ( presently IMDGFS) are used for forecasting other parameters. These forecast generated for the districts of West Bengal by the model is further moderated by State Agro Met. Centre, Kolkata, and forwarded to six Agro Met. Field Units ( created by six agro-climatic zones in West Bengal ) and seven District Agro Met. Unit ( DAMU ) for preparation of weather-based District as well as Block level Agromet advisory bulletin which benefits the farmers in their crop production. Thus forecast verification of the model as well as moderated value for the monsoon season of 2019 and 2020 has been done to make a comparative study of the model performance concerning Kolkata and its suburbs based on Probability of Detection, False alarm, Heidke Skill score, Missing rate, Critical Success Index, True Skill Score, Hanssen, and Kuipers Index, etc. The monsoon rainfall of 2019 and 2020 was chosen to study the performance of the model concerning the pre-covid non-lockdown and covid lockdown period so that the effect of pollutants on the performance of the model can be analyzed. The verification results show that the model forecast, as well as a moderated forecast of this region, has to be more refined by taking inputs of other parameters and index that has been computed by different recent research works on this region because this region is under the influence of tropical climate. Moreover, the comparative study between monsoon 2019 and monsoon 2020 reveals that there have been changes in the performance of the model.

Keywords:

Pre Covid period,Covid period,Probability of Detection,False alarm,Heidke Skill score,Missing rate,Critical Success Index,True Skill Score,Hanssen and Kuipers Index,

Refference:

I. Chattopadhyay , N., Roy Bhowmik , S.K. , Singh ,K.K., Ghosh ,K., and Malathi , K., 2016 , “ Verification of district level weather forecast “ , Mausam , 67, 4 , 829-840.

II. Krishnamurti , T. N ., Kishtawal , C.M., Larow , T., Bachiochi ,D., Zhang, Z., Willford,E.C., Gadgil,S. and Surendran , S.,1999, “Improved weather and seasonal climate forecasts from multimodel super ensemble “ , Science , 285 , 1548-1550.

III. Rajeevan , M .,Bhate,J.,Kale,J.D. and Lal,B.,2005, “ development of high resolution gridded rainfall data for Indian Region “,IMD Met. Monograph No. Climatology 22/2007.

IV. Rathore , L.S., Roy Bhowmik , S.K. and Chattopadhyay , N., 2011 , “Integrated Agro Advisory Services of India”, Challenges and opportunities of Agro-meteorology , 195-205 ( Spinger publication )

V. Roy Bhowmik , S.K. and Das, A.K., 2007 , “Rainfall Analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates : Evaluation of monsoon rainfall features “. Journal of Earth System Science , 116 . 3 , 187-198.

VI. Roy Bhowmik , S.K. and Durai, V.R., 2012 , “Development of multi-model satellite ensemble based district level medium range rainfall forecast system for Indian region “, Journal of Earth System Science , 121 . 2 , 273 – 285.

VII. WMO Technical Circular No.- WMO /TO No. 1023 Guidelines on Performance Assessment of Public Weather Services.

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