Journal Vol – 19 No – 2, February 2024

Abstract:

In today's world, communication is essential for various aspects of life. From military operations and medical systems to community networks, communication plays a crucial role in ensuring the smooth functioning of these applications. With the advancement of technology, communication has become more efficient and has significantly reduced the barriers of distance, bringing people and nations closer together. One of the key components of modern communication systems is microstrip devices. These devices are used in a wide range of applications, including filters, diplexers, and triplexers. Filters are used to selectively allow certain frequencies to pass through while blocking others, making them essential for signal processing and interference reduction in communication systems. Diplexers and triplexers are used to combine or separate multiple signals, allowing for more efficient use of the available frequency spectrum. This article aims to provide an overview of the state-of-the-art microstrip devices used in communication systems. It will review previous studies and advancements in the field, providing insights into the latest developments and technologies. By understanding the current state of research and development in microstrip devices, engineers and researchers can gain valuable knowledge to improve the performance and efficiency of communication systems. Furthermore, the article will explore the potential applications of microstrip devices in various communication systems, such as satellite communications, wireless networks, and radar systems. Understanding the capabilities and limitations of these devices will be crucial for optimizing their performance in different scenarios. Overall, this article will serve as a comprehensive resource for anyone interested in the role of microstrip devices in communication systems. Delving into the scope of filters, diplexers, and triplexers, will provide valuable insights into the advancements and potential future developments in this important area of technology.

Keywords:

Microstrip,Bandpass Filter,Diplexer,Triplexer,

Refference:

I. A. Al-ghoul and T. F. Skaik, “Design of UMTS/LTE Diplexer and DCS/UMTS/LTE Triplexer for Mobile Communication Systems,” Islamic University of Gaza, 2013.
II. A. B. Yousif, “Design of Microstrip Diplexer Filters for Wireless Applications,” University of Technology, 2020.
III. A. E. Ammar, N. M. Mahmoud, M. A. Attia, and A. H. Hussein, “Efficient diplexer with high selectivity and low insertion loss based on SOLR and DGS for WiMAX,” Prog. Electromagn. Res. C, vol. 116, pp. 171–180, 2021, doi: 10.2528/PIERC21090104.
IV. A. El-Tokhy, R. Wu, and Y. Wang, “Microstrip triplexer using a common triple-mode resonator,” Microw. Opt. Technol. Lett., vol. 60, no. 7, pp. 1815–1820, 2018, doi: 10.1002/mop.31244.
V. A. Kumar and D. K. Upadhyay, “A compact planar diplexer based on via-free CRLH TL for WiMAX and WLAN applications,” Int. J. Microw. Wirel. Technol., vol. 11, no. 2, pp. 130–138, 2019, doi: 10.1017/S1759078718001496.
VI. A. Rezaei and L. Noori, “Miniaturized microstrip diplexer with high performance using a novel structure for wireless L-band applications,” Wirel. Networks, vol. 26, no. 3, pp. 1795–1802, 2020, doi: 10.1007/s11276-018-1870-5.
VII. A. Rezaei and L. Noori, “Novel low-loss microstrip triplexer using coupled lines and step impedance cells for 4G and WiMAX applications,” Turkish J. Electr. Eng. Comput. Sci., vol. 26, no. 4, pp. 1871–1880, 2018, doi: 10.3906/elk-1708-48.
VIII. A. Rezaei, S. I. Yahya, L. Nouri, and M. H. Jamaluddin, “Design of a low-loss microstrip diplexer with a compact size based on coupled meandrous open-loop resonators,” Analog Integr. Circuits Signal Process., vol. 102, no. 3, pp. 579–584, 2020, doi: 10.1007/s10470-020-01625-w.
IX. A. Rezaei, S. I. Yahya, S. Moradi, and M. H. Jamaluddin, “A compact microstrip triplexer with a novel structure using patch and spiral cells for wireless communication applications,” Prog. Electromagn. Res. Lett., vol. 86, pp. 73–81, 2019, doi: 10.2528/pierl19060104.
X. C. Jayanth, P. Peter, and B. Santhosh, “Optical Triplexer and Diplexer Filter Using Two-Dimensional Photonic Crystal,” Journal of Optics (2023): 1-8.‏

XI. C. Sangdao, “Simulation of Triplexer Design for Improving Insertion Loss and Isolation,” in 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020, 2020, pp. 603–606, doi: 10.1109/ECTI-CON49241.2020.9158285.
XII. C. W. Tang and M. G. Chen, “Packaged microstrip triplexer with star-junction topology,” Electronics Letters, vol. 48, no. 12, pp. 699-701, 2012.
XIII. D. A. Letavin, “Microstrip diplexer implemented on high-pass and low-pass filters,” in International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM, 2018, vol. 2018-July, pp. 199–202, doi: 10.1109/EDM.2018.8435001.
XIV. D. K. Choudhary and R. K. Chaudhary, “Compact Lowpass and Dual-Band Bandpass Filter with Controllable Transmission Zero/Center Frequencies/Passband Bandwidth,” IEEE Trans. Circuits Syst. II Express Briefs, vol. 67, no. 6, pp. 1044–1048, 2020, doi: 10.1109/TCSII.2019.2931446.
XV. D. Sen, E. Dillibabu, and M. Ramesh, “Design of compact inline triplexer for multi band receiver,” 2018, doi: 10.1109/IMaRC.2018.8877199.
XVI. F. Fouladi and A. Rezaei, “A six-channel microstrip diplexer for multi-service wireless communication systems,” Eng. Rev., vol. 41, no. 3, 2021, doi: 10.30765/ER.1556.
XVII. H. A. Hussein, Y. S. Mezaal, and B. M. Alameri, “Miniaturized microstrip diplexer based on fr4 substrate for wireless communications,” Elektron. ir Elektrotechnika, vol. 27, no. 5, pp. 34–40, 2021, doi: 10.5755/j02.eie.28942.
XVIII. H. Tizyi, F. Riouch, A. Tribak, A. Najid, and A. Mediavilla, “Microstrip diplexer design based on two square open loop bandpass filters for RFID applications,” Int. J. Microw. Wirel. Technol., vol. 10, no. 4, pp. 412–421, 2018, doi: 10.1017/S1759078718000314.
XIX. H. X. Xu, G. M. Wang, C. X. Zhang, and J. G. Liang, “Novel design of compact microstrip diplexer based on fractal-shaped composite right/left handed transmission line,” Journal of Infrared and Millimeter Waves, vol. 30, no. 5, pp. 390-396, 2011.
XX. H.-X. Xu, G.-M. Wang, and H.-P. An, “Hilbert fractal curves form compact diplexer,” Microw. & RF, vol. 49, no. 8, pp. 92-95, 2010.
XXI. J. H. Song, K. S. Lee, and Y. Oh, “Triple wavelength demultiplexers for low-cost optical triplexer transceivers,” Journal of Lightwave Technology, vol. 25, no. 1, pp. 350-358, 2007.
XXII. J. Konpang and N. Wattikornsirikul, “An analysis of high selectivity and harmonic suppression based on stepped-impedance resonator structure for dual-mode diplexer,” Prog. Electromagn. Res. C, vol. 112, pp. 45–54, 2021, doi: 10.2528/PIERC21032102.
XXIII. J. Liu et al., “New design of a compact 6-pole reconfigurable narrowband triplexer based on common net-type resonator,” 2018, doi: 10.1109/ASEMD.2018.8558973.
XXIV. J. Liu, T. Su, H. Lv, L. Lin, and B. Wu, “Six-channel diplexer using stub-loaded stepped impedance resonators,” Appl. Comput. Electromagn. Soc. J., vol. 37, no. 10, pp. 1582–1587, 2019, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074453270&partnerID=40&md5=1cfa615441d068f8c9ed93e35a37884d.
XXV. J. S. G. Hong and M. J. Lancaster, “Microstrip filters for RF/microwave applications,” John Wiley & Sons, 2004.‏
XXVI. J. Xu, et al., “Diplexer-integrated spdt switches with multiple operating modes using common fractal stub-loaded resonator,” IEEE Transactions on Microwave Theory and Techniques, vol. 69, no. 2, pp. 1464-1473, 2020, doi: 10.1109/TMTT.2019.2892732.
XXVII. J. Xu, F. Liu, Z. Y. Feng, and Y. F. Guo, “Diplexer-Integrated SPDT Switches with Multiple Operating Modes Using Common Fractal Stub-Loaded Resonator,” IEEE Trans. Microw. Theory Tech., vol. 69, no. 2, pp. 1464–1473, 2021, doi: 10.1109/TMTT.2020.3039603.
XXVIII. J. Xu, Z. Y. Chen, and H. Wan, “Lowpass-bandpass triplexer integrated switch design using common lumped-element triple-resonance resonator technique,” IEEE Trans. Ind. Electron., vol. 67, no. 1, pp. 471–479, 2020, doi: 10.1109/TIE.2019.2898579.
XXIX. J. Zhou, J. L. Li, C. G. Sun, H. Li, and S. S. Gao, “A novel microstrip diplexer based on coupled line,” Electromagnetics, vol. 38, no. 2, pp. 87–95, 2018, doi: 10.1080/02726343.2018.1436668.
XXX. J.-G. Liang, W.-L. Chen, and G.-M. Wang, “Harmonics suppression microstrip diplexer for 3G wireless communication system using fractal‐shaped geometry,” Microwave and Optical Technology Letters, vol. 49, no. 12, pp. 2973-2975, 2007.
XXXI. K. Al-Majdi and Y. S. Mezaal, “Microstrip diplexer for recent wireless communities,” Period. Eng. Nat. Sci., vol. 10, no. 1, pp. 387–396, 2022, doi: 10.21533/pen.v10i1.2664.

XXXII. K. D. Xu, M. Li, Y. Liu, Y. Yang, and Q. H. Liu, “Design of Triplexer Using E-Stub-Loaded Composite Right-/Left-Handed Resonators and Quasi-Lumped Impedance Matching Network,” IEEE Access, vol. 6, pp. 18814–18821, 2018, doi: 10.1109/ACCESS.2018.2819641.
XXXIII. M. A. Sazali, N. A. Shairi, and Z. Zakaria, “Hybrid microstrip diplexer design for multi-band WiMAX application in 2.3 and 3.5 GHz bands,” Int. J. Electr. Comput. Eng., vol. 8, no. 1, pp. 576–584, 2018, doi: 10.11591/ijece.v8i1.pp576-584.
XXXIV. M. Hayati, A. R. Zarghami, S. Zarghami, and S. Alirezaee, “Designing a miniaturized microstrip lowpass-bandpass diplexer with wide stopband by examining the effects between filters,” AEU – Int. J. Electron. Commun., vol. 139, p. 153912, 2021, doi: https://doi.org/10.1016/j.aeue.2021.153912.
XXXV. M. Q. Dinh and M. Thuy Le, “Triplexer-Based Multiband Rectenna for RF Energy Harvesting from 3G/4G and Wi-Fi,” IEEE Microw. Wirel. Components Lett., vol. 31, no. 9, pp. 1094–1097, 2021, doi: 10.1109/LMWC.2021.3095074.
XXXVI. P. H. Deng, S. W. Lei, W. Lo, and M. W. Li, “Novel Diplexer and Triplexer Designs Avoiding Additional Matching Circuits Outside Filters,” IEEE Access, vol. 8, pp. 14714–14723, 2020, doi: 10.1109/ACCESS.2020.2966262.
XXXVII. S. Ben Haddi, A. Zugari, and A. Zakriti, “Low Losses and Compact Size Microstrip Diplexer Based on Open-Loop Resonators with New Zigzag Junction for 5G Sub-6-GHz and Wi-Fi Communications,” Prog. Electromagn. Res. Lett., vol. 102, pp. 109–117, 2022, doi: 10.2528/PIERL21120305.
XXXVIII. S. H. Esmaeli and S. H. Sedighy, “A compact size, high isolation and low insertion loss microstrip diplexer,” J. Circuits, Syst. Comput., vol. 27, no. 13, 2018, doi: 10.1142/S0218126618502110.
XXXIX. T. H. Le, X. W. Zhu, C. Ge, and T. V. Duong, “A Novel Diplexer Integrated with a Shielding Case Using High Q -Factor Hybrid Resonator Bandpass Filters,” IEEE Microw. Wirel. Components Lett., vol. 28, no. 3, pp. 215–217, 2018, doi: 10.1109/LMWC.2018.2804174.
XL. T. Upadhyaya, J. Pabari, V. Sheel, A. Desai, R. Patel, and S. Jitarwal, “Compact and high isolation microstrip diplexer for future radio science planetary applications,” AEU – Int. J. Electron. Commun., vol. 127, 2020, doi: 10.1016/j.aeue.2020.153497.

XLI. X. Bi, Q. Ma, C. Ning, and Q. Xu, “A Compact Switchable Filtering Diplexer Based on Reused L-Shaped Resonator,” IEEE Trans. Circuits Syst. II Express Briefs, vol. 65, no. 12, pp. 1934–1938, 2018, doi: 10.1109/TCSII.2018.2810066.
XLII. X. Guan, M. Xu, B. Ren, W. Liu, X. Zhang, and B. Zhao, “High Isolated and Wide Stopband Switchable Diplexer with Inserted Lowpass Filter,” 2020. 10.1109/CSRSWTC50769.2020.9372460.
XLIII. X. Guan, W. Liu, B. Ren, H. Liu, and P. Wen, “A Novel Design Method for High Isolated Microstrip Diplexers without Extra Matching Circuit,” IEEE Access, vol. 7, pp. 119681–119688, 2019, doi: 10.1109/ACCESS.2019.2936553.
XLIV. Y. Chu, K. Ma, and Y. Wang, “A novel triplexer based on SISL platform,” IEEE Trans. Microw. Theory Tech., vol. 67, no. 3, pp. 997–1004, 2019, doi: 10.1109/TMTT.2019.2892732.
XLV. Y. F. Tsao, T. J. Huang, H. T. Hsu, and C. W. Wu, “Planar Diplexer Design Using Hairpin Resonators Loaded with External Capacitors for Improvement of Isolation and Stopband Rejection Levels,” in 2019 49th European Microwave Conference, EuMC 2019, 2019, pp. 368–371, doi: 10.23919/EuMC.2019.8910892.
XLVI. Y. S. Mezaal and H. T. Eyyuboglu, “A new narrow band dual-mode microstrip slotted patch bandpass filter design based on fractal geometry,” in 2012 7th International Conference on Computing and Convergence Technology (ICCCT), IEEE, 2012, pp. 1180–1184.
XLVII. Y. S. Mezaal, H. H. Saleh, and H. Al-saedi, “New compact microstrip filters based on quasi fractal resonator,” Adv. Electromagn., vol. 7, no. 4, pp. 93–102, 2018.
XLVIII. Y. S. Mezaal, S. A. Hashim, A. H. Al-fatlawi, and H. A. Hussein, “New microstrip diplexer for recent wireless applications,” Int. J. Eng. Technol., vol. 7, no. 3.4 Special Issue 4, pp. 96–99, 2018, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082370717&partnerID=40&md5=29671327ca11331ef98fa39d8d95a883.
XLIX. Y. Shi, J. Chen, and H. Xu, “Silicon-based on-chip diplexing/triplexing technologies and devices,” Science China Information Sciences, vol. 61, pp. 1-15, 2018.
L. Zhang, L., Liu, D., Jiang, H., & Dai, D. First demonstration of an on-chip quadplexer for passive optical network systems. Photonics Research, vol.9, no.5, pp.757-763, 2021.

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Abstract:

Nowadays Polymeric materials reinforced with synthetic fibers play an incredible role in almost all spheres of day-to-day life due to their elevated stiffness, outstanding strength-to-weight ratio, and electrical, thermal, and wear properties. The accumulation of micro-fillers or particulates in polymeric components reinforced with fibers made from synthetic materials may enhance their properties compared to fiber-reinforced composites. Solid particle erosion of engineering components made up of polymer composites is a major industrial problem, and it is significantly affected by the components' mechanical characteristics and their working environment. Therefore, it's essential to research the polymer composites' solid particle erosion properties. One area that has attracted less research attention is the impact of particle fillers and E-glass fiber reinforcing on erosion wear characteristics. Because of its significance to science and industry, research in this area is especially needed about particle fillers. Furthermore, to properly design a machine or structural component and use materials that will increase wear resistance, one must have a thorough grasp of how every system variable affects wear rate. In this research article, to estimate the erosion damage induced by solid particle impact on composites without conducting the experiment on an air jet erosion test rig, a theoretical model is proposed. The successful implementation of this theoretical model can reduce the experimentation cost with good quantitative accuracy.

Keywords:

Erosion,Erosion Modeling,Air-jet erosion test rig,Operating Parameters,Theoretical Model,

Refference:

I. Aglan H.A and Chenock T.A Jr., (1993). Erosion damage features of polyimide Thermoset composites, SAMPE Quartery, 41-47.
II. Bitter J. G. A, (1963). A study of erosion phenomena part 1, Wear, 6(1), pp.5-21.
III. Bitter J. G. A, (1963). A study of erosion phenomena part II, Wear, 6(3), pp.169-190.
IV. Bourgoyne A.T, (1989). Experimental study of erosion in diverter systems due to sand production, SPE/IADC Drilling Conference, 28 February-3 March 1989, New Orleans, Louisiana, SPE/IADC 18716, pp. 807-816.
V. Budinski K.G, (1998). Surface Engg. For Wear Resistance, N.J, USA.
VI. Chase D. P, Rybicki E. F and Shadley J. R, (1992). A model for the effect of velocity on erosion of N80 steel tubing due to the normal impingement of solid particles, Journal of Energy Resources Technology, 114(1), pp.54-64.
VII. Chen Q and Li D. Y, (2003). Computer simulation of solid particle erosion, Wear, 254(3-4), pp.203-210.
VIII. Elalem K, Li D.Y, Anderson M. J and Chiovelli S, (2001). Modelling of abrasive wear of homogenous and heterogeneous materials, hydraulic failure analysis: fluids, components and system effects, ASTM, STP, 1339, Totten G. E, Wills D. K and Feldmann D, Eds., American Society for Testing and Materials, West Conshohocken, PA.
IX. Finnie I., (1958). The mechanism of erosion of ductile metals, in: Proceedings of 3rd US national congress of applied mechanics, American Society of Mechanical Engineers, 527-532.
X. Gachon Y, Vannes A. B and Farges G, (1998). Study of sand particle erosion of magnetron sputtered multilayer coatings, in: Proceedings of the International Conference on Erosive and Abrasive Wear (ICEAW); 9th International Conference on Erosion by Liquid and Solid Impact (ELSI IX), Cambridge, UK.
XI. Gomes-Ferreira C, Ciampini D and Papini M, (2004). The effect of inter-particle collisions in erosive streams on the distribution of energy flux incident to a flat surface, Tribology International, 37(10), pp. 791- 807.
XII. Gorham D. A, Kharaz A. H, (2000). The measurement of particle rebound characteristics, Powder Technology, 112(3), pp.193-202.
XIII. Gumbsch P and Cannon R. M, (2000). Atomic aspects of brittle fracture, MRS Bulletin, 25, pp.15-20.
XIV. Halling, (1975). Principles of Tribology, The McMillan Press Ltd, NY, USA.
XV. Hutchings I. M, Winter R. E and Field J. E, (1976). Solid particle erosion of metals: the removal of surface material by spherical projectiles, Proceedings of the Royal Society of London A, 348, pp. 379-392.
XVI. Jordan K. G, (1998). Erosion in multiphase production of oil and gas, CORROSION 98, March 22 – 27, San DiegoCa.
XVII. Karaz A. H and Gorham D. A, (2000). A study of the restitution coefficient in elastic-plastic impact, Philosophical Magazine Letters, 80(8), pp. 549-559.
XVIII. Kleis I and Hussainova I, (1999). Investigation of particle-wall impact process, Wear, 233-235, pp.168-173.
XIX. Laitone J.A., (1979). Erosion prediction near a stagnation point resulting from aerodynamically entrained solid particles, Journal of Aircraft, 16(12), pp.809-814.
XX. Lancaster J. K., Friction and wear, (1972) in A. D. Jenkins (ed.), Polymer Science: A Materials Science Handbook, 2, North-Holland, London, pp.959-1046.
XXI. Li D.Y, Elalem K, Anderson M. J and Chiovelli S, (1999). A micro scale dynamical model for wear simulation, Wear, 225-229 (1), pp.380-386.
XXII. Mc Laury B. S, (1993). A model to predict solid particle erosion in oil field geometries. MS thesis, The University of Tulsa.
XXIII. Mishra P K, (1997). Nonconventional Machining, Narosa Publishing House, New Delhi.
XXIV. Molinari J. F and Ortiz M, (2002). A study of solid-particle erosion of metallic targets, International Journal of Impact Engineering, 27(4), pp. 347-358.
XXV. Mohapatra, Sangita & Mantry, Sisir & Singh, s & Satapathy, Alok. (2014). Solid particle erosion behaviour of glass-epoxy composites filled with TiC derived from limonite. International Journal of Plastics Technology. 18.75-87. 10.1007/s12588-014-9066-z.
XXVI. Nesic S, (1991). Computation of localized erosion-corrosion in disturbed two-phase flow, PhD thesis, University of Saskatchewan, Saskatoon, Canada.
XXVII. Päivi Kivikytö-Reponen, (2006). Correlation of Material Characteristics and Wear of Powder Metallurgical Metal Matrix Composites, Doctoral Theses in Materials and Earth Sciences, Helsinki University of Technology, Laboratory of Materials Science, Espoo,1-2.
XXVIII. Patnaik A, Satapathy A, Mahapatra S. S and Dash R. R, (2008). A Taguchi Approach for Investigation of Erosion of Glass Fibre-Polyester Composites, Journal of Reinforced Plastics and Composites, 27(8), pp. 871-888.
XXIX. Patnaik A, Satapathy A, Mahapatra S. S and Dash R. R, (2008). Parametric Optimization of Erosion Wear of Polyester-GF-Alumina Hybrid Composites using Taguchi Method, Journal of Reinforced Plastics and Composites, 27(10), pp. 1039-1058.
XXX. Patnaik A, Satapathy A, Mahapatra S. S and Dash R. R, (2008). Implementation of Taguchi Design for Erosion of Fibre Reinforced Polyester Composite Systems with SiC Filler, Journal of Reinforced Plastics and Composites, 27(10), pp. 1093-1111.
XXXI. Patnaik A, Satapathy A, Mahapatra S. S and Dash R. R, (2008). A Modelling Approach for Prediction of Erosion Behaviour of Glass Fibre-Polyester Composites, Journal of Polymer Research, 15(2), pp. 147-160.
XXXII. Patnaik A, Satapathy A, Mahapatra S. S and Dash R. R, (2009). Tribo- Performance of Polyester Hybrid Composites: Damage Assessment and Parameter Optimization using Taguchi Design, Materials and Design, 30(1), pp. 57-6.
XXXIII. Papini M, Ciampini D, Krajac T and Spelt J. K, (2003). Computer modeling of interference effects in erosion testing: effect of plume shape, Wear, 255(1-6), pp.85-97.
XXXIV. Pool K.V, Dharan C.K.H, and Finnie I, (1986). Erosion wear of composite materials, wear, vol. 107, 1-12.
XXXV. Rao P.V, (1995). Characterization of optical and surface parameters during particle impact damage, ASME/Fluids engineering publications, 23:87-96.
XXXVI. Rabinowicz E, (1979). The wear equation for erosion of metals by abrasive particles, Department of ME, MIT.
XXXVII. Robinowicz E, (1965). Friction and wear of materials, Willey, NY, USA.
XXXVIII. Ratner S. N, Farberoua I. I, Radyukeuich O. V and Lure E. G, (1967). Correlation between wear resistance of plastics and other mechanical properties, in: D.I. James (Ed.), Abrasion of Rubber, MacLaren, London, pp.145-154.
XXXIX. Sandhyarani Biswas and Alok Satapathy, 2009, “Tribo-performance analysis of red mud filled glass-epoxy composites using Taguchi experimental design”, Materials and Design, 30 (8), 2841-2853.
XL. Sandhyarani Biswas and Alok Satapathy, “Use of copper slag in glass-epoxy composites for improved wear resistance” Waste Management and Research, 28 (7), 2010, pp. 615-625.
XLI. Sandhyarani Biswas and Alok Satapathy, “Erosion Wear Analysis of SiC Filled Glass-Epoxy Composites using Taguchi Technique”, International Polymer Processing, 1, 2010, pp. 23-33.
XLII. Sandhyarani Biswas and Alok Satapathy, “A Study on Tribological Behaviour of Alumina Filled Glass-Epoxy Composites using Taguchi Experimental Design” Tribology Transactions, 53, 2010, pp. 520-532.
XLIII. Salama M. M and Venkatesh E. S, (1983). Evaluation of erosion velocity limitations of offshore gas wells, 15th Annual OTC. Houston, TX: May 2-5, OTC no.4485.
XLIV. Sundararajan G and Shewmon P. G, (1987). The oblique impact of a hard ball against ductile, semi-infinite, target materials-experiment and analysis, International Journal of Impact Engineering, 6(1), pp.3-22.
XLV. Shimizu K, Noguchi T and Seitoh H, (1998). FEM analysis of the dependency on impact angle during erosive wear, in: Proceedings of the International Conference on Erosive and Abrasive Wear (ICEAW); 9th International Conference on Erosion by Liquid and Solid Impact (ELSI IX), Cambridge, UK.
XLVI. Sundararajan G, (1991). The depth of the plastic deformation beneath eroded surfaces: the influence of impact angle and velocity, particle shape and material properties, Wear, 149(1-2), pp.129-153.
XLVII. Sundararajan G, Roy M and Venkataraman B, (1990). Erosion Efficiency- A New parameter to characterize the Dominant Erosion Micro-mechanism, Wear, 140(2), pp. 369-381.
XLVIII. Shirazi S. A and McLaury B. S, (2000). Erosion modeling of elbows in multiphase flow, In: Proceedings of 2000 ASME fluids engineering summer meeting, June 11-15, Boston, MA: Paper no. FEDSM2000- 11251.
XLIX. Stolarski T.A, (1990). Tribology in Machine Design, Heiman Newnes, UK.
L. Svedeman S. J and Arnold K. E, (1994). Criteria for sizing Multiphase flow lines for erosive/corrosive services, SPE Production & Facilities, 9(1), pp.74-80.
LI. Tennyson, R.C, (1991). LDEF Mission update: composites in space, Advance materials & processes, 5:33-36.
LII. Thomas H. Kosel, (1992). ASM Handbook: Friction, Lubrication, and Wear Technology, ASM International Handbook Committee. 18,371-372.
LIII. Tirupataiah Y, Venkataraman B and Sundararajan G, (1990). The nature of the elastic rebound of a hard ball impacting on ductile, metallic target materials, Materials Science and Engineering: A, 124(2), pp.133-140.
LIV. Tomassone M. S, Sokoloff J. B and Widom A., (1997). Dominance of phonon friction for a xenon film on a silver (111) surface, Physical Review Letters, 79(24), pp.4798-4801.
LV. Velten K, Reinicke R and Friedrich K, (2000). Wear volume prediction with artificial neural networks, Tribology International, 33(10), pp. 731- 736.
LVI. Wu C, Li L and Thornton C, (2003). Rebound behaviour of spheres for plastic impacts, International Journal of Impact Engineering, 28, pp. 929-946.
LVII. Zhang Z, Friedrich K and Velten K, (2002). Prediction on tribological properties of short fibre composites is using artificial neural networks, Wear, 252(7-8), 668-675.
LVIII. Zhang Z and Friedrich K, (2003). Artificial neural network applied to polymer composites: a review, Composites Science and Technology, 63(14), pp. 2029-2044.
LIX. Zhong W and Tománek D, (1990). First-principles theory of atomic- scale friction, Physical Review Letters, 64 (25), pp.3054-3057.

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Abstract:

In order to improve the welfare of newborns, this study investigates the use of sound-recognition-based artificial intelligence (AI) approaches to the interpretation and monitoring of infant screams. Crying has long been a problem because it is the primary means of communication between infants and caregivers. The limitations of conventional interpretation techniques are discussed. These limitations include the subjective nature of interpretation and the inability to detect subtle variations in crying patterns. The goal of the research is to categorize crying patterns based on the cries of male and female infants and identify noises that are a sign of distress. The study utilized the Mel Frequency Cepstral Coefficients (MFCC) method to extract features from internet-sourced MP3 and WAV audio data. The technique successfully captured the unique qualities of each crying sound using various machine-learning models, including Random Forest and XGBoost. These models outperformed others with accuracy rates of 94.5% and 94.2%, respectively. These findings show how well these algorithms perform in correctly categorizing various newborn cries. The findings of this study establish the platform for possible Internet of Things (IoT) and healthcare framework implementations targeted at supporting parents in caring for their newborns by offering an insightful understanding of the distinctive vocalizations connected with weeping.

Keywords:

infant cry interpretation,machine learning,artificial intelligence,infant monitoring,real-time systems,privacy concerns,XGBoost,

Refference:

I. A. Bashiri and R. Hosseinkhani, : ‘Infant crying classification by using genetic algorithm and artificial neural network.’ Acta Medica Iranica, 531-539 (2020).
II. A. Chittora and H. A. Patil, : ‘Data collection of infant cries for research and analysis.’ Journal of Voice, 31(2), 252-e15 (2017).
III. A. Rosales-Pérez, C. A. Reyes-García, J. A. Gonzalez, O. F. Reyes-Galaviz, H. J. Escalante, and S. Orlandi, : ‘Classifying infant cry patterns by the Genetic Selection of a Fuzzy Model.’ Biomedical Signal Processing and Control, 17, 38-46 (2015).
IV. A. McStay and G. Rosner, : ‘Emotional artificial intelligence in children’s toys and devices: Ethics, governance and practical remedies.’ Big Data & Society, 8(1), 2053951721994877 (2021).
V. A. Virani, L. Duffett-Leger, and N. Letourneau, : ‘Parenting apps review: in search of good quality apps.’ Mhealth, 5 (2019).
VI. A. Kachhi, S. Chaturvedi, H. A. Patil, and D. K. Singh, : ‘Data Augmentation for Infant Cry Classification.’ In 2022 13th International Symposium on Chinese Spoken Language Processing (ISCSLP), 433-437. IEEE (2022, December).
VII. A. Sharma, A. Thakur, M. Garg, and S. Sharma, : ‘Early intervention saved the life of mother and baby: Management of a parturient with snake bite with neurotoxicity.’ Indian Journal of Anaesthesia, 65(Suppl 3), S139 (2021).
VIII. A. K. Olsavsky, J. Stoddard, A. Erhart, R. Tribble, and P. Kim, : ‘Reported maternal childhood maltreatment experiences, amygdala activation and functional connectivity to infant cry.’ Social cognitive and affective neuroscience, 16(4), 418-427 (2021).
IX. A. Pothula, M. A. R. Mondol, S. Narasimhan, S. M. Islam, and D. Park, : ‘SEDRo: A Simulated Environment for Developmental Robotics.’ In 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 1-2. IEEE (2020, October).
X. A. Chakraborty, B. Singh, A. Sau, D. Sanyal, B. Sarkar, S. Basu, & J. S. Banerjee: Intelligent vehicle accident detection and smart rescue system. In Applications of Machine Intelligence in Engineering (pp. 565-576). CRC Press (2022).
XI. A. Chakraborty, J. S. Banerjee, R. Bhadra, A. Dutta, S. Ganguly, D. Das, S. Kundu, M. Mahmud, & G. Saha: A framework of intelligent mental health monitoring in smart cities and societies. IETE Journal of Research, 1-14 (2023).
XII. C. Pan, W. Zhao, S. Deng, W. Wei, Y. Zhang, and Y. Xu, : ‘The Methods of Realizing Baby Crying Recognition and Intelligent Monitoring Based on DNN-GMM-HMM.’ In 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 352-356. IEEE (2018, May).
XIII. C. Ji, T. B. Mudiyanselage, Y. Gao, and Y. Pan, : ‘A review of infant cry analysis and classification.’ EURASIP Journal on Audio, Speech, and Music Processing, 2021(1), 1–17 (2021).
XIV. C. Pan, J. S. Banerjee, D. De, P. Sarigiannidis, A. Chakraborty, and S. Bhattacharyya, : ‘ChatGPT: A OpenAI Platform for Society 5.0.’ In Doctoral Symposium on Human Centered Computing, 384-397. Singapore: Springer Nature Singapore (2023, February).
XV. D. M. Romeo, M. Ricci, M. Picilli, B. Foti, G. Cordaro, and E. Mercuri, : ‘Early neurological assessment and long-term neuromotor outcomes in late preterm infants: a critical review.’ Medicina, 56(9), 475 (2020).
XVI. F. S. Matikolaie, & C. Tadj: Machine learning-based cry diagnostic system for identifying septic newborns. Journal of Voice (2022).
XVII. F. Fahmi, W. Shalannanda, I. Zakia, and E. Sutanto, : ‘Design of an IoT-based smart incubator that listens to the baby.’ In IOP Conference Series: Materials Science and Engineering, Vol. 1003, No. 1, 012153. IOP Publishing (2020, December).
XVIII. F. S. Matikolaie, Y. Kheddache, and C. Tadj, : ‘Automated newborn cry diagnostic system using machine learning approach.’ Biomedical Signal Processing and Control, 73, 103434 (2022).
XIX. G. Esposito, J. Nakazawa, P. Venuti, and M. H. Bornstein, : ‘Componential deconstruction of infant distress vocalizations via tree-based models: A study of cry in autism spectrum disorder and typical development.’ Research in Developmental Disabilities, 34(9), 2717-2724 (2013).
XX. G. Zamzmi, R. Kasturi, D. Goldgof, R. Zhi, T. Ashmeade, and Y. Sun, : ‘A review of automated pain assessment in infants: features, classification tasks, and databases.’ IEEE reviews in biomedical engineering, 11, 77–96 (2017).
XXI. H. Kumari and M. Paliwal, : ‘Concept of Trisutra Ayurveda: A Review.’ International journal of research in ayurveda and pharmacy, 8, 13-16 (2017).
XXII. H. Xuan, Z. Zhang, S. Chen, J. Yang, and Y. Yan, : ‘Cross-modal attention network for temporal inconsistent audio-visual event localization.’ In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34, No. 01, 279-286 (2020, April).
XXIII. H. I. Salehin, Q. R. A. Joy, F. T. Z. Aparna, A. T. Ridwan, and R. Khan, : ‘Development of an IoT based smart baby monitoring system with face recognition.’ In 2021 IEEE World AI IoT Congress (AIIoT), 0292-0296.
XXIV. https://www.soundsnap.com/
XXV. H. Norholt, : ‘Revisiting the roots of attachment: A review of the biological and psychological effects of maternal skin-to-skin contact and carrying of full-term infants.’ Infant Behavior and Development, 60, 101441 (2020).
XXVI. I. M. Lyså, : ‘Managing Risk and Balancing Minds Transforming the Next Generation through ‘Frustration Education’.’ In Childhood Cultures in Transformation 30 Years of the UN Convention on the Rights of the Child in Action towards Sustainability. Brill (2021).
XXVII. J. M. Leventhal, G. A. Edwards, and R. G. Barr, : ‘Abusive Head Trauma and Infant Crying—A Flawed Analysis.’ JAMA pediatrics, 175(11), 1181-1181 (2021).
XXVIII. J. S. Banerjee, A. Chakraborty, M. Mahmud, U. Kar, M. Lahby, G. Saha: Explainable Artificial Intelligence (XAI) Based Analysis of Stress Among Tech Workers Amidst COVID-19 Pandemic. In: Advanced AI and Internet of Health Things for Combating Pandemics. Springer (2023).
XXIX. J. K. Mandal, S. Misra, J. S. Banerjee, S. Nayak (eds.): Applications of machine intelligence in engineering. In: Proceedings of 2nd Global Conference on Artificial Intelligence and Applications (GCAIA, 2021), 8–10 September 2021, Jaipur, India. CRC Press (2022).
XXX. J. S. Banerjee, M. Mahmud, D. Brown: Heart rate variability-based mental stress detection: an explainable machine learning approach. SN Comput. Sci. 4(2), 176 (2023).
XXXI. J. S. Banerjee, S. Bhattacharyya, A. J. Obaid, & W. C. Yeh, (Eds.): Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management. CRC Press, (2022).
XXXII. J. Chattopadhyay, S. Kundu, A. Chakraborty, & J. S. Banerjee: Facial expression recognition for human computer interaction. New Trends in Computational Vision and Bio-inspired Computing: Selected works presented at the ICCVBIC 2018, Coimbatore, India, 1181-1192, (2020).
XXXIII. K. Wermke and W. Mende, : ‘Musical elements in human infants’ cries: in the beginning is the melody.’ Musicae Scientiae, 13(2_suppl), 151-175 (2009).
XXXIV. K. Wakunuma, G. Ogoh, D. O. Eke, and S. Akintoye, : ‘Responsible AI, SDGs, and AI Governance in Africa.’ In 2022 IST-Africa Conference (IST-Africa), 1-13. IEEE (2022, May).
XXXV. K. G. Srinivasa, B. J. Sowmya, A. Shikhar, R. Utkarsha, and A. Singh, : ‘Data analytics assisted internet of things towards building intelligent healthcare monitoring systems: IoT for healthcare.’ Journal of Organizational and End User Computing (JOEUC), 30(4), 83–103 (2018).
XXXVI. K. Das, & J. S. Banerjee: Green IoT for intelligent cyber-physical systems in industry 4.0: A review of enabling technologies, and solutions. In Applications of machine intelligence in engineering, 463-478, CRC Press (2022).
XXXVII. K. Das, & J. S. Banerjee: Cognitive Radio-Enabled Internet of Things (CR-IoT): An Integrated Approach towards Smarter World. In Applications of Machine intelligence in Engineering (pp. 541-555). CRC Press (2022).
XXXVIII. L. Liu, W. Li, X. Wu, and B. X. Zhou, : ‘Infant cry language analysis and recognition: an experimental approach.’ IEEE/CAA Journal of Automatica Sinica, 6(3), 778–788 (2019).
XXXIX. L. Provenzi, J. Lindstedt, K. De Coen, L. Gasparini, D. Peruzzo, S. Grumi, and S. Ahlqvist-Björkroth, : ‘The paternal brain in action: a review of human fathers’ fMRI brain responses to child-related stimuli.’ Brain Sciences, 11(6), 816 (2021).
XL. M. K. Kim and D. J. Kim, : ‘Effects of oral stimulation intervention in newborn babies with Cri du Chat syndrome: Single-Subject Research Design.’ Occupational Therapy International, 2018.
XLI. M. Lahby, V. Pilloni, J. S. Banerjee, M. Mahmud (eds): Advanced AI and Internet of Health Things for Combating Pandemics. Springer (2023).
XLII. Q. Gao, L. Tong, L. Tang, W. Zhong, and H. Zhu, : ‘Parental knowledge on infant crying and abusive head trauma and relevant shaking behaviors in China.’ Child Abuse & Neglect, 115, 105025 (2021).
XLIII. R. Majumder, M. Dasgupta, A. Biswas, & J. S. Banerjee: IoT-Based Smart City for the Post COVID-19 World: A Child-Centric Implementation Emphasis on Social Distancing. In Applications of Machine intelligence in Engineering (pp. 599-612). CRC Press (2022).
XLIV. R. L. Babbitt, T. A. Hoch, D. A. Coe, M. F. Cataldo, K. J. Kelly, C. Stackhouse, and J. A. Perman, : ‘Behavioral assessment and treatment of pediatric feeding disorders.’ Journal of Developmental & Behavioral Pediatrics, 15(4), 278-291 (1994).
XLV. R. Gupta, M. H. Choudhury, M. Mahmud, & J. S. Banerjee: Patent Analysis on Artificial Intelligence in Food Industry: Worldwide Present Scenario. In Doctoral Symposium on Human Centered Computing (pp. 347-361). Singapore: Springer Nature Singapore (2023).
XLVI. S. Kim, J. Chen, T. Cheng, A. Gindulyte, J. He, S. He, and E. E. Bolton, : ‘PubChem in 2021: new data content and improved web interfaces.’ Nucleic acids research, 49(D1), D1388-D1395 (2021).
XLVII. S. Lahmiri, C. Tadj, and C. Gargour, : ‘Nonlinear statistical analysis of normal and pathological infant cry signals in cepstrum domain by multifractal wavelet leaders.’ Entropy, 24(8), 1166 (2022).
XLVIII. S. P. Dewi, A. L. Prasasti, and B. Irawan, : ‘The study of baby crying analysis using MFCC and LFCC in different classification methods.’ In 2019 IEEE International Conference on Signals and Systems (ICSigSys), 18-23. IEEE (2019, July).
XLIX. S. P. Dewi, A. L. Prasasti, and B. Irawan, : ‘Analysis of LFCC feature extraction in baby crying classification using KNN.’ In 2019 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS), 86-91. IEEE (2019, November).
L. S. Biswas, L. K. Sharma, R. Ranjan, S. Saha, A. Chakraborty, & J. S. Banerjee: Smart farming and water saving-based intelligent irrigation system implementation using the internet of things. In Recent Trends in Computational Intelligence Enabled Research (pp. 339-354). Academic Press (2021).
LI. S. Bhattacharyya, J. S. Banerjee, S. Gorbachev, K. Muhammad, & M. Koeppen (eds.): Computer Intelligence Against Pandemics. De Gruyter (2023).
LII. S. Bhattacharyya, J. S. Banerjee, & D. De (eds.): Confluence of Artificial Intelligence and Robotic Process Automation. Springer (2023).
LIII. S. Bhattacharyya, J. S. Banerjee, M. Köppen (eds.): Human-Centric Smart Computing: Proceedings of ICHCSC 2022, vol. 316. Springer Nature (2022).
LIV. S. Bhattacharyya, J. S. Banerjee, M. Köppen (eds.): Human-Centric Smart Computing: Proceedings of ICHCSC 2023, Springer Nature, (2024) (Press)
LV. S. Bhattacharyya, J. S. Banerjee, D. De, M. Mahmud (eds): Intelligent Human Centered Computing. Human 2023. Springer Tracts in Human-Centered Computing. Springer, Singapore (2023).
LVI. S. Guhathakurata, S. Saha, S. Kundu, A. Chakraborty, J. S. Banerjee: South Asian countries are less fatal concerning COVID-19: a fact-finding procedure integrating machine learning & multiple criteria decision-making (MCDM) technique. J. Inst. Eng. (India): Series B, 1–15 (2021).
LVII. S. Guhathakurata, S. Kundu, A. Chakraborty, J. S. Banerjee: A novel approach to predict COVID-19 using support vector machine. In: Data Science for COVID-19, pp. 351–364. Academic Press (2021).
LVIII. S. Guhathakurata, S. Saha, S. Kundu, A. Chakraborty, J. S. Banerjee: A new approach to predict COVID-19 using artificial neural networks. In: Cyber-Physical Systems, pp. 139–160. Academic Press (2022).
LIX. T. Ozseven, : ‘Infant cry classification by using different deep neural network models and hand-crafted features.’ Biomedical Signal Processing and Control, 83, 104648 (2023).
LX. T. Khan, : ‘An intelligent baby monitor with automatic sleeping posture detection and notification.’ AI, 2(2), 290-306 (2021).
LXI. T. Hussain, K. Muhammad, S. Khan, A. Ullah, M. Y. Lee, and S. W. Baik, : ‘Intelligent baby behavior monitoring using embedded vision in IoT for smart healthcare centers.’ Journal of Artificial Intelligence and Systems, 1(1), 110-124 (2019).
LXII. X. Zhang, Y. Zou, and Y. Liu, : ‘AICDS: An infant crying detection system based on lightweight convolutional neural network.’ In Artificial Intelligence and Mobile Services–AIMS 2018, 7, 185-196. Springer International Publishing (2018).
LXIII. Y. C. Liang, I. Wijaya, M. T. Yang, J. R. Cuevas Juarez, and H. T. Chang, : ‘Deep learning for infant cry recognition.’ International Journal of Environmental Research and Public Health, 19(10), 6311 (2022).
LXIV. Z. Khalilzad, Y. Kheddache, and C. Tadj,: ‘An entropy-based architecture for detection of sepsis in newborn cry diagnostic systems.’ Entropy, 24(9), 1194 (2022).

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Abstract:

This article provides an overview of cloud computing and fog computing, as well as a discussion of the potential applications of these technologies in Iraq. The ability of cloud computing to provide scalable and adaptable computer resources on demand has led to a significant uptick in interest in this computing model all around the world. However, fog computing improves cloud computing by moving computation to devices that are positioned on the edge of a network. This research investigates the up-to-date applications of cloud computing and fog computing in Iraq, as well as the challenges that have been faced and the potential applications of these technologies in the future, particularly in the areas of agriculture, transportation, and healthcare. The use of questionnaires in research will be the topic of discussion in this study. This is made up of two different parts that work separately. In the first part of our survey, we ask respondents questions about their level of expertise with direct and indirect cloud on object and fog computing. The remaining aspects of the investigation are dissected in Part 2 of the study. These inquiries are in accordance with concerns regarding the complexity of the implementation process, the size and culture of an organization, practicability, compliance with legislation, compatibility with current systems, and support from the government. The final open-ended inquiry of the survey will assist us in compiling a wide variety of opinions on the types of cloud-on-object and fog computing services that are required by the Iraqi government.

Keywords:

Cloud of Thing,Fog Computing,Governmental support,Administrative Informatics Sustainability,

Refference:

I. D. G. Bonett, T. A. Wright, “Cronbach’s alpha reliability: Interval estimation, hypothesis testing, and sample size planning,” Journal of Organizational Behavior 36, no. 1, pp. 3-15, 2015.
II. F. Abayaje, S. A. Hashem, H. S. Obaid, Y. S. Mezaal, & S. K. Khaleel, “A miniaturization of the UWB monopole antenna for wireless baseband transmission,” Periodicals of Engineering and Natural Sciences, vol. 8, no. 1, pp. 256–262, 2020.
III. F. F. S. Al-Bajjari, “A model for adopting cloud computing in government sector: Case study in Iraq” (Master’s thesis, Çankaya Üniversitesi).
IV. F. Franceschini, M. Galetto, M. Varetto, “Qualitative ordinal scales: the concept of ordinal range,” Quality Engineering 16, no. 4, pp. 515-524, 2004.
V. H. F. Atlam, R. J. Walters, & G. B. Wills, “Fog computing and the internet of things: A review,” Big Data and Cognitive Computing, vol. 2, no. 2, pp.10, 2018.
VI. J. K. Ali, Y. S. Miz’el, “A new miniature Peano fractal-based bandpass filter design with 2nd harmonic suppression,” In 2009 3rd IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2009.
VII. M. Amini, A. Bakri, “Cloud computing adoption by SMEs in Malaysia: A multi-perspective framework based on DOI theory and TOE framework,” Journal of Information Technology & Information Systems Research (JITISR), vol. 9, no. 2, pp. 121-135, 2015.
VIII. M. S. Shareef, Y. S. Mezaal, N. H. Sultan, S. K. Khaleel, A. A. Al-Hillal, H. M. Saleh, … & K. Al-Majdi, “Cloud of Things and fog computing in Iraq: Potential applications and sustainability,” Heritage and Sustainable Development, vol. 5, no. 2, pp. 339-350, 2023.
IX. T. Abd, Y. S. Mezaal, M. S. Shareef, S. K. Khaleel, H. H. Madhi, & S. F. Abdulkareem, “Iraqi e-government and cloud computing development based on unified citizen identification,” Periodicals of Engineering and Natural Sciences, vol. 7, no. 4, pp. 1776-1793, 2019.
X. V. K. Quy, N. V. Hau, D. V. Anh, L. A. Ngoc, “Smart healthcare IoT applications based on fog computing: architecture, applications and challenges,” Complex & Intelligent Systems, vol. 8, no. 5, pp. 3805-3815, 2022.
XI. V. Kumar, A. A. Laghari, S. Karim, M. Shakir, A. A. Brohi, “Comparison of fog computing & cloud computing,” Int. J. Math. Sci. Comput 1, pp. 31-41, 2019.
XII. Y. S. Mezaal, H. H. Saleh, H. Al-saedi, “New compact microstrip filters based on quasi fractal resonator,” Adv. Electromagn., vol. 7, no. 4, pp. 93–102, 2018.
XIII. Y. S. Mezaal, H. T. Eyyuboglu, “A new narrow band dual-mode microstrip slotted patch bandpass filter design based on fractal geometry,” In 2012 7th International Conference on Computing and Convergence Technology (ICCCT), IEEE, pp. 1180–1184, 2012.
XIV. Y. S. Mezaal, S. F. Abdulkareem, “New microstrip antenna based on quasi-fractal geometry for recent wireless systems,” In 2018 26th Signal Processing and Communications Applications Conference (SIU), 2018.

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Abstract:

This work provides a theoretical framework to investigate the shear wave propagation properties within an Electrostrictive cylindrical layered structure. The structure is made up of a concentric, Functionally Assessed Electrostrictive Material (FAEM) cylindrical layer of limited width and an inadequately bonded Electrostrictive material cylinder. The FAEM layer has a constant functional gradient in the radial direction, and flaws at the interface are taken seriously, mirroring actual circumstances involving structural and electrical degradation. The fundamental electromechanical connected Bessel's equations are used to simplify field differential equations by mathematical modifications. Relationships for shear wave propagation under electrically short and open circumstances are established analytically. The acquired findings are verified against predefined standards and a particular issue instance. The impact of variables on the phase velocity of shear waves, including functional range and imperfection parameters, is shown through numerical simulations and graphical displays. The research also establishes boundaries for electrically short and open circumstances, taking into account the shear defect that exists between the inner and outer cylindrical layers.

Keywords:

Shear Wave Propagation,Cylinder,Electrostrictive Materials,Functional Assessment,

Refference:

I. Chaudhary, S., Sahu, S.A., Singhal, A. and Nirwal, S., 2019. Interfacial imperfection study in a pres-stressed rotating multiferroic cylindrical tube with wave vibration analytical approach. Materials Research Express, 6(10), p.105704.

II. Della Schiava, N., Thetpraphi, K., Le, M.Q., Lermusiaux, P., Millon, A., Capsal, J.F. and Cottinet, P.J., 2018. Enhanced figures of merit for a high-performing actuator in electrostrictive materials. Polymers, 10(3), p.263.

III. Di Stefano, S., Miller, L., Grillo, A. and Penta, R., 2020. Effective balance equations for electrostrictive composites. Zeitschrift für angewandte Mathematik und Physik, 71, pp.1-36.

IV. Liang, C., Yaw, Z. and Lim, C.W., 2023. Thermal strain energy induced wave propagation for imperfect FGM sandwich cylindrical shells. Composite Structures, 303, p.116295.

V. Luo, H., Tao, M., Wu, C. and Cao, W., 2023. Dynamic response of an elliptic cylinder inclusion with imperfect interfaces subjected to plane SH wave. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 9(1), p.24.

VI. Manduca, A., Bayly, P.V., Ehman, R.L., Kolipaka, A., Royston, T.J., Sack, I., Sinkus, R. and Van Beers, B.E., 2021. MR elastography: Principles, guidelines, and terminology. Magnetic resonance in medicine, 85(5), pp.2377-2390.
VII. Marino, A., Genchi, G.G., Sinibaldi, E. and Ciofani, G., 2017. Piezoelectric effects of materials on bio-interfaces. ACS Applied Materials & interfaces, 9(21), pp.17663-17680.

VIII. Ming, T., Hao, L., Rui, Z. and Gongliang, X., 2023. Dynamic response of an elliptic cylinder inclusion with imperfect interfaces subjected to plane SH wave (No. EGU23-7726). Copernicus Meetings.

IX. Pankaj, K.K., Sahu, S.A. and Kumari, S., 2020. Surface wave transference in a piezoelectric cylinder coated with reinforced material. Applied Mathematics and Mechanics, 41, pp.123-138.

X. Reijmers, J.J., Kaminski, M.L. and Stapersma, D., 2022. Analytical formulations and comparison of collapse models for risk analysis of axisymmetrically imperfect ring-stiffened cylinders under hydrostatic pressure. Marine Structures, 83, p.103161.

XI. Ryu, J. and Jeong, W.K., 2017. Current status of musculoskeletal application of shear wave elastography. Ultrasonography, 36(3), p.185.

XII. Singhal, A., Baroi, J., Sultana, M. and Baby, R., 2022. Analysis of SH-waves propagating in multiferroic structure with interfacial imperfection. Mechanics Of Advanced Composite Structures, 9(1), pp.1-10.

XIII. Trujillo, D.P., Gurung, A., Yu, J., Nayak, S.K., Alpay, S.P. and Janolin, P.E., 2022. Data-driven methods for discovery of next-generation electrostrictive materials. npj Computational Materials, 8(1), p.251.

XIV. Uchino, K., 2017. The development of piezoelectric materials and the new perspective. In Advanced Piezoelectric Materials (pp. 1-92). Woodhead Publishing.

XV. Wijeyewickrema, A.C. and Leungvichcharoen, S., 2022. Effect of imperfect contact on the cloaking of a circular elastic cylinder from antiplane elastic waves. Mechanics Research Communications, 124, p.103964.

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Abstract:

Considering the basic role of numbers in Mathematics, Science, and Technology the author developed a new structure of numbers named as ‘Theory of Dynamics of Numbers.’ According to the Theory of Dynamics of Numbers, the author defined 0 (zero) is the starting point of any number and also defined 0 (zero) as a neutral number. The numbers can move in infinite directions from the starting point 0 (zero) and back to 0 (zero). The author has defined the three types of numbers: 1) Neutral Numbers, 2) Count Up Numbers, and 3) Count Down Numbers. These three types of numbers cover the entire numbers in the number system where there is no necessity for the concept of imaginary numbers. Introducing this new concept the author solved the quadratic equation in one unknown (say x) in the form ax² + bx + c = 0, even if the numerical value of the discriminant b² – 4ac < 0 in real numbers without using the concept of imaginary numbers. Already the author solved the quadratic equation x² + 1 = 0 and proved that  √ -1 = -1  by using the Theory of Dynamics of Numbers. The Theory of Dynamics of Numbers is a more powerful tool than that of the real and imaginary number system to explain the truth of nature.

Keywords:

Cartesian Coordinate System,Imaginary Numbers,Quadratic Equation,Rectangular Bhattacharyya’s Coordinate System,Theory of Numbers,Theory of Dynamics of Numbers.,

Refference:

I. Amelia Ethan. Exploring the Use of Number Theory in Modern Cryptography: Advancements and Applications. Department of Journalism, University of Harvard. July 2023. pp 1-6.
II. A. Harripersaud, (2021). The quadratic equation concept. American Journal of Mathematicsand Statistics, (11)3, 2021, 67-71.
III. B. B. Dutta, (1929). : “The Bhakshali Mathematics”. Calcutta, West Bengal: Bulletin of the Calcutta Mathematical Society.
IV. B. B. Datta, & A. N. Singh, (1938). : “History of Hindu Mathematics, A source book”. Mumbai, Maharashtra: Asia Publishing House.
V. H. Lee Price, Frank R. Bernhart, : “Pythagorean Triples and a New Pythagorean Theorem”. arXiv:math/0701554 [math.HO]. 10.48550/arXiv.math/0701554
VI. Lucena, F. J. H., Díaz, I. A., Rodríguez, J. M. R., and Marín, J. A. M., Influencia del aula invertida en el rendimiento académico. Una revisión sistemática. Campus Virtuales, 8(1), p. 9-18, 2019.
VII. L. Nurul , H., D., (2017). : “Five New Ways to Prove a Pythagorean Theorem”. International Journal of Advanced Engineering Research and Science. Volume 4, issue 7, pp.132-137. 10.22161/ijaers.4.7.21
VIII. Makbule Gözde DİDİŞ KABAR. : A Thematic Review of Quadratic Equation Studies in The Field of Mathematics Education. Participatory Educational Research (PER)Vol.10(4), pp. 29-48, July 2023. 10.17275/per.23.58.10.4
IX. Manjeet Singh. Transformation of number system. International Journal of Advance Research, Ideas and Innovations in Technology. Volume 6, Issue 2 , 2020. pp 402-406. 10.13140/RG.2.2.33484.77442
X. M. Janani et al, : “Multivariate Crypto System Based on a Quadratic Equation to Eliminate in Outliers using Homomorphic Encryption Scheme”. Homomorphic Encryption for Financial Cryptography. pp 277–302. 01 August 2023. Springer
XI. M. Sandoval-Hernandez et al, : “The Quadratic Equation and its Numerical Roots”. International Journal of Engineering Research & Technology (IJERT). Vol. 10 Issue 06, June-2021 pp. 301-305. 10.17577/IJERTV10IS060100
XII. M. Sandoval-Hernandez, H. Vazquez-Leal, U. Filobello-Nino , Elisa De-Leo-Baquero, Alexis C. Bielma-Perez, J.C. Vichi-Mendoza , O. Alvarez-Gasca, A.D. Contreras-Hernandez, N. Bagatella-Flores , B.E. Palma-Grayeb, J. Sanchez-Orea, L. Cuellar-Hernandez. : The Quadratic Equation and its Numerical Roots’. IJERT. Volume 10, Issue 06 (June 2021), 301-305. 10.17577/IJERTV10IS060100
XIII. Peter Chew, : ‘Peter Chew Method for Quadratic Equation’ (2019). 2019 the 8th International Conference on Engineering Mathematics and Physics, Journal of Physics: Conference Series1411 (2019) 012003, IOP Publishing, 10.1088/1742-6596/1411/1/012003
XIV. Pieronkiewicz, B., & Tanton, J. (2019). Different ways of solving quadraticequations. Annales Universitatis Paedagogicae Cracoviensis Studia ad DidacticamMathematicae Pertinentia, 11, 103-125
XV. Prabir Chandra Bhattacharyya, : “AN INTRODUCTION TO RECTANGULAR BHATTACHARYYA’S CO-ORDINATES: A NEW CONCEPT”. J. Mech. Cont. & Math. Sci., Vol.-16, No.-11, November (2021). pp 76-86. 10.26782/jmcms.2021.11.00008
XVI. Prabir Chandra Bhattacharyya, : “AN INTRODUCTION TO THEORY OF DYNAMICS OF NUMBERS: A NEW CONCEPT”. J. Mech. Cont. & Math. Sci., Vol.-17, No.-1, January (2022). pp 37-53. 10.26782/jmcms.2022.01.00003
XVII. Prabir Chandra Bhattacharyya, : ‘A NOVEL CONCEPT IN THEORY OF QUADRATIC EQUATION’. J. Mech. Cont. & Math. Sci., Vol.-17, No.-3, March (2022) pp 41-63. 10.26782/jmcms.2022.03.00006
XVIII. Prabir Chandra Bhattacharyya. : “A NOVEL METHOD TO FIND THE EQUATION OF CIRCLES”. J. Mech. Cont. & Math. Sci., Vol.-17, No.- 6, June (2022). pp 31-56. 10.26782/jmcms.2022.06.00004
XIX. Prabir Chandra Bhattacharyya, : “AN OPENING OF A NEW HORIZON IN THE THEORY OF QUADRATIC EQUATION: PURE AND PSEUDO QUADRATIC EQUATION – A NEW CONCEPT”. J. Mech. Cont. & Math. Sci., Vol.-17, No.-11, November (2022). pp 1-25. 10.26782/jmcms.2022.11.00001
XX. Prabir Chandra Bhattacharyya, : “A NOVEL CONCEPT FOR FINDING THE FUNDAMENTAL RELATIONS BETWEEN STREAM
FUNCTION AND VELOCITY POTENTIAL IN REAL NUMBERS IN TWO-DIMENSIONAL FLUID MOTIONS”. J. Mech. Cont. & Math. Sci., Vol.-18, No.-02, February (2023) pp 1-19. 10.26782/jmcms.2023.02.00001
XXI. Prabir Chandra Bhattacharyya, : “A NEW CONCEPT OF THE EXTENDED FORM OF PYTHAGORAS THEOREM”. J. Mech. Cont. & Math. Sci., Vol.-18, No.-04, April (2023) pp 46-56. 10.26782/jmcms.2023.04.00004.
XXII. Prabir Chandra Bhattacharyya, A NEW CONCEPT TO PROVE, √− 1 = −𝟏 IN BOTH GEOMETRIC AND ALGEBRAIC METHODS WITHOUT USING THE CONCEPT OF IMAGINARY NUMBERS. J. Mech. Cont. & Math. Sci., Vol.-18, No.-9, September (2023) pp 20-43
XXIII. Sánchez, J. A. M. Investigaciones en clase de matemáticas con Geo Gebra, jornades d’Educació Matemàtica de la Comunittat Valenciana: Innovació i tecnologia en educació matemàtica. Instituto de Ciencias de la Educación, 2019.
XXIV. Sandoval-Hernandez, M. A., Alvarez-Gasca, O., Contreras-Hernandez, A. D., Pretelin-Canela, J. E., Palma-Grayeb, B. E., Jimenez-Fernandez, V. M., and Vazquez-Leal, H. Exploring the classic perturbation method for obtaining single and multiple solutions of nonlinear algebraic problems with application to microelectronic circuits. International Journal of Engineering Research & Technology, 8(9), p. 636-645, 2019.
XXV. Sandoval-Hernandez, M. A., Vazquez-Leal, H., Filobello-Nino, U., and Hernandez-Martinez, L., New handy and accurate approximation for the Gaussian integrals with applications to science and engineering. Open Mathematics, 17(1), p. 1774-1793, 2019.
XXVI. S. Mahmud, (2019). : “Calculating the area of the Trapezium by Using the Length of the Non Parallel Sides: A New Formula for Calculating the area of Trapezium”. International Journal of Scientific and Innovative Mathematical Research. volume 7, issue 4, pp. 25-27. 10.20431/2347- 3142.0704004
XXVII. T. A. Sarasvati Amma, : “Geometry in Ancient and Medieval India”. Pp. – 17. Motilal Banarasidass Publishers Pvt. Ltd. Delhi.
XXVIII. T. A. Sarasvati Amma, : “Geometry in Ancient and Medieval India”. pp. – 219. Motilal Banarasidass Publishers Pvt. Ltd. Delhi.
XXIX. Vazquez-Leal, H., Sandoval-Hernandez, M. A., Garcia-Gervacio, J. L. , Herrera-May, A. L. and Filobello-Nino, U. A., PSEM Aproximations for Both Branches of Lambert W with Applications. Discrete Dynamics in Nature ans Society, Hindawi, 2019, 15 pages, 2019.
XXX. William Robert. An Overview of Number System. RRJSMS| Volume 8 | Issue 4 |April, 2022. 10.4172/ J Stats Math Sci.8.4.002.

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