A Comprehensive Review: Nanomembranes and Nanosorbents for Water Treatment
Dr. Mishu Singh, Dr. Akhilesh Kumar- September 2022 Page No.: 01-06
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Abstract
Water despite being an indispensable part of human life is facing a major problem of being contaminated worldwide. There are several contaminants present in sewage and industrial effluents being discharged into water bodies making them unfit for drinking. This review explains the various claims of nanomaterial in removing contaminants from polluted water. Due to the unique properties of being nano-scale sized, high reactivity, and nanomaterial have been the major subject of research and development for the last decade. Studies have shown that nanomaterials are highly effective and successfully applied in removing contaminants from wastewater. Due to their exceptional properties of having a larger surface area, and being able to act at very low concentrations, nanomaterials have enormous possibilities to treat wastewater containing metallic & non-metallic substances, different organic and inorganic impurities, etc. Still, there are many challenges and issues with wastewater treatment. This paper discusses the various nanomaterials and the treatment methods using nanomaterials which are flexible, cost-effective, and efficient for the commercialization also.
Page(s): 01-06 Date of Publication: 25 September 2022
Authors
Dr. Mishu Singh
Department of Chemistry, Pt. D. D. U. Govt. Girls P. G. College, Lucknow, India
Dr. Akhilesh Kumar
Department of Chemistry, Pt. D. D. U. Govt. Girls P. G. College, Lucknow, India
References
[1] Ahmad, A.; Mohd-Setapar, S.H.; Chuong, C.S.; Khatoon, A.; Wani, W.A.; Kumar, R.; Rafatullah, M. Recent advances in new generation dye removal technologies: Novel search for approaches to reprocess wastewater. RSC Adv. 2015, 5, 30801–30818.
[2] Zhang, Y.; Wu, B.; Xu, H.; Liu, H.; Wang, M.; He, Y.; Pan, B. Nanomaterials-Enabled water and wastewater treatment. Nano Impact 2016, 3, 22–39.
[3] Gitis, V.; Hankins, N.Water treatment chemicals: Trends and challenges. J. Water Process Eng. 2018, 25, 34–38.
[4] Hodges, B.C.; Cates, E.L.; Kim, J. Challenges and prospects of advanced oxidation water treatment processes using catalytic nanomaterial. Nat. Nanotechnol. 2018, 13, 642–650.
[5] Umar, K.; Haque, M.M.; Mir, N.A.; Muneer, M. Titanium dioxide-Mediated photocatalyzed mineralization of Two Selected organic pollutants in aqueous suspensions. J. Adv. Oxid. Technol. 2013, 16, 252–260.
[6] Umar, K.; Ibrahim, M.N.M.; Ahmad, A.; Rafatullah, M. Synthesis of Mn-doped TiO2 by the novel route and photocatalytic mineralization/intermediate studies of organic pollutants. Res. Chem. Intermediate. 2019, 45, 2927–2945.
[7] Baruah, S.; Khan, M.N.; Dutta, J. Perspectives and applications of nanotechnology in water treatment. Environ. Chem. Lett. 2016, 14, 1–14.
[8] Wu, Y.; Pang, H.; Liu, Y.; Wang, X.; Yu, S.; Fu, D.; Chen, J.; Wang, X. Environmental remediation of heavy metal ions by novel-Nanomaterials: A review. Environ. Pollut. 2019, 246, 608–620.
[9] Daer, S.; Kharraz, J.; Giwa, A.; Hasan, S.W. Recent applications of nanomaterials in water desalination: A critical review and future opportunities. Desalination 2015, 367, 37–48.
[10] Yaqoob, A.A.; Ibrahim, M.N.M. A Review Article of Nanoparticles; Synthetic Approaches and Wastewater Treatment Methods. Int. Res. J. Eng. Technol. 2019, 6, 1–7.
[11] Tang, W.W.; Zeng, G.M.; Gong, J.L. Impact of humic/fulvic acid on the removal of heavy metals from aqueous solutions using nanomaterials: A review. Sci. Total Environ. 2014, 468, 1014–1027.
[12] C. Buzea, I. I. Pacheco, and K. Robbie, “Nanomaterials and nanoparticles: sources and toxicity,” Biointerphases, vol. 2, no. 4, pp. MR17–MR71, 2007.
[13] Parmon, “Nanomaterials in catalysis,” Materials Research Innovations, vol. 12, no. 2, pp. 60–61, 2008.
[14] X.-J. Liang, A. Kumar, D. Shi, and D. Cui, “Nanostructures for medicine and pharmaceuticals,” Journal of Nanomaterials, vol. 2012, Article ID 921897, 2 pages, 2012.
[15] A. Kusior, J. Klich-Kafel, A. Trenczek-Zajac, K. Swierczek, M. Radecka, and K. Zakrzewska, “TiO2–SnO2 nanomaterials for gas sensing and photocatalysis,” Journal of the European Ceramic Society, vol. 33, no. 12, pp. 2285–2290, 2013.
[16] B. Bujoli, H. Roussière, G. Montavon, et al., “Novel phosphate–phosphonate hybrid nanomaterials applied to biology,” Progress in Solid State Chemistry, vol. 34, no. 2–4, pp. 257–266, 2006.
[17] M. M. Khin, A. S. Nair, V. J. Babu, R. Murugan, and S. Ramakrishna, “A review on nanomaterials for environmental remediation,” Energy & Environmental Science, vol. 5, no. 8, pp. 8075–8109, 2012.
[18] W.-W. Tang, G.-M. Zeng, J.-L. Gong et al., “Impact of humic/fulvic acid on the removal of heavy metals from aqueous solutions using nanomaterials: a review,” Science of the Total Environment, vol. 468-469, pp. 1014–1027, 2014.
[19] J. Yan, L. Han, W. Gao, S. Xue, and M. Chen, “Biochar supported nanoscale zerovalent iron composite used as persulfate activator for removing trichloroethylene,” Bioresource Technology, vol. 175, pp. 269–274, 2015.
[20] F. Liu, J. H. Yang, J. Zuo, et al., “Graphene-supported nanoscale zero-valent iron: removal of phosphorus from aqueous solution and mechanistic study,” Journal of Environmental Sciences, vol. 26, no. 8, pp. 1751–1762, 2014]
[21] R. S. Kalhapure, S. J. Sonawane, D. R. Sikwal, et al., “Solid lipid nanoparticles of clotrimazole silver complex: an efficient nano antibacterial against Staphylococcus aureus and MRSA,” Colloids and Surfaces B: Biointerfaces, vol. 136, pp. 651–658, 2015.
[22] Mir, N.A.; Haque, M.M.; Khan, A.; Umar, K.; Muneer, M.; Vijayalakshmi, S. Semiconductor mediated photocatalyzed reaction of two selected organic compounds in aqueous suspensions of Titanium dioxide.J. Adv. Oxid. Technol. 2012, 15, 380–391.
[23] Umar, K.Water Contamination by Organic-Pollutants: TiO2 Photocatalysis. In Modern Age Environmental Problem and Remediation; Oves, M., Khan, M.Z., Ismail, I.M.I., Eds.; Springer Nature: Basel, Switzerland, 2018; pp. 95–109.
[24] Kalhapure, R.S.; Sonawane, S.J.; Sikwal, D.R. Solid lipid nanoparticles of clotrimazole silver complex: An e_cient nano antibacterial against Staphylococcus aureus and MRSA. Colloid Surf. B 2015, 136, 651–658.
[25] Fang, X.; Li, J.; Li, X.; Pan, S.; Zhang, X.; Sun, X.; Han, J.S.W.; Wang, L. Internal pore decoration with polydopamine nanoparticle on polymeric ultrafiltration membrane for enhanced heavy metal removal. Chem. Eng. 2017, 314, 38–49.
[26] Sekoai, P.T.; Ouma, C.N.M.; Du Preez, S.P.; Modisha, P.; Engelbrecht, N.; Bessarabov, D.G.; Ghimire, A.Application of nanoparticles in biofuels: An overview. Fuel 2019, 237, 380–397.
[27] Sekoai, P.T.; Ouma, C.N.M.; Du Preez, S.P.; Modisha, P.; Engelbrecht, N.; Bessarabov, D.G.; Ghimire, A. Application of nanoparticles in biofuels: An overview. Fuel 2019, 237, 380–397.
[28] Jhaveri, J.H.; Murthy, Z.V.P. A comprehensive review on anti-Fouling nanocomposite membranes for pressure-driven membrane separation processes. Desalination 2016, 379, 137–154.
[29] Hogen-Esch, T.; Pirbazari, M.; Ravindran, V.; Yurdacan, H.M.; Kim,W. High-Performance Membranes for Water Reclamation Using Polymeric and Nanomaterials. U.S. Patent No. 20160038885A, 29 October 2019.
[30] Waduge, P.; Larkin, J.; Upmanyu, M.; Kar, S.; Wanunu, M. Programmed Synthesis of Freestanding Graphene Nanomembrane Arrays. Nano Microphone 2015, 11, 597–603.
[31] Bassyouni, M.; Abdel-Aziz, M.H.; Zoromba, M.S.; Abdel Hamid, S.M.S.; Drioli, E. A review of polymeric nanocomposite membranes for water purification. J. Ind. Eng. Chem. 2019, 73, 19–46.
[32] Zahid, M.; Rashid, A.; Akram, S.; Rehan, Z.A.; Razzaq, W. A Comprehensive Review on Polymeric Nano-Composite Membranes for Water Treatment. J. Membr. Sci. Technol. 2018, 8, 179–190.
[33] Saleh, A.; Parthasarathy, P.; Irfan, M. Advanced functional polymer nanocomposites and their use in water ultra-purification. Trends Environ Anal. 2019, 24, 67–78.
[34] Kochkodan, V.; Hilal, N. A comprehensive review on surface-modified polymer membranes for biofouling mitigation. Desalination 2015, 356, 187–207.
[35] Ronen, A.; Duan, W.; Wheeldon, I.; Walker, S.; Jassby, D. Microbial Attachment Inhibition through Low-Voltage Electrochemical Reactions on Electrically Conducting Membranes. Environ. Sci. Technol. 2015, 49, 12741–12750.
[36] Hirata, K.; Watanabe, H.; Kubo, W. Nanomembranes as a substrate for ultra-thin lightweight devices. Thin Solid Film. 2019, 676, 8–11.
[37] Yin, J.; Yang, Y.; Hu, Z.; Deng, B. Attachment of silver nanoparticles (AgNPs) onto thin-Film composite (TFC) membranes through covalent bonding to reduce membrane biofouling. J. Membr. Sci. 2013, 441, 73–82.
[38] Zhang, M.; Field, R.W.; Zhang, K. Biogenic silver nanocomposite polyethersulfone UF membranes with antifouling properties. J. Membr. Sci. 2014, 471, 274–284.
[39] Hirata, K.; Watanabe, H.; Kubo, W. Nanomembranes as a substrate for ultra-thin lightweight devices. Thin Solid Film. 2019, 676, 8–11.
[40] Gopalakrishnan, I.; Samuel, S.R.; Sridharan, K. nanomaterials-Based adsorbents for water and wastewater treatment. Emerg. Nanotechnol. Environ. Sustain. 2018, 6, 89–98
[41] Liu, S.; Wang, Y.; Zhou, Z.; Hana, W.; Li, J.; Shen, J.; Wang, I. Improved degradation of the aqueous flutriafol using a nanostructure microporous PbO2 as a reactive electrochemical membrane. Electrochim. Acta 2017, 253, 357–367.
[42] Shetti, N.P.; Bukkitgar, S.D.; Reddy, K.R.; Aminabhavi, T.M. Nanostructured titanium oxide hybrids-Based electrochemical biosensors for healthcare applications. Colloids Surf. B Biointerfaces 2019, 178, 385–394.
[43] Kunduru, R.K.; Kovsky, M.N.; Rajendra, S.F.; Pawar, P.; Basu, A.; Domb, A.J. Nanotechnology for water purification: Applications of nanotechnology methods in wastewater treatment. Water Purif. 2017, 10, 33–74.
[44] Ibrahim, R.K.; Hayyan, M.; Al-Saadi, M.A.; Hayyan, A.; Ibrahim, S. Environmental application of nanotechnology; air, soil, and water. Environ. Sci. Pollut. R 2016, 23, 13754–13788.
[45] Mekaru, H.; Lu, J.; Tamanoi, F. Development of mesoporous silica-Based nanoparticles with controlled release capability for cancer therapy. Adv. Drug Deliv. Rev. 2015, 95, 40–49.
[46] 45 Jawed, A.; Saxena, V.; Pandey, L.M. Engineered nanomaterials and their surface functionalization for the removal of heavy metals: A review. J. Wat. Process. Eng. 2020, 33, 101009.
[47] Abdullah, N.; Yusof, N.; Lau, W.J.; Jaafar, J.; Ismail, A.F. Review Recent trends of heavy metal removal from water/wastewater by membrane technologies. J. Ind. Eng. Chem. 2019, 76, 17–38.
[48] Bhat, A.H.; Rehman, W.U.; Khan, I.U.; Ahmad, S.; Ayoub, M.; Usmani, M.A. Nanocomposite membrane for environmental remediation. In Polymer-BasedNanocompositesforEnergyandEnvironmentalApplications; Jawaid, M., Khan, M.M., Eds.; Woodhead Publishing: Cambridge, UK, 2018; pp. 407–440.
[49] Muntha,S.T.;Kausar,A.;Siddiq,M.Advancesinpolymericnanofiltrationmembrane: Areview. Polym.-Plast Technol. Eng. 2017, 56, 841–856.
[50] Rashidi, H.R.; Sulaiman, N.M.N.; Hashim, N.A.; Hassan, C.R.C.; Ramli, M.R. Synthetic reactive dye wastewater treatment by using nano-Membrane filtration. Desalin. Water Treat. 2015, 55, 86–95.
[51] Feng, C.; Khulbe, K.C.; Matsuura, T. Recent progress in the preparation, characterization, and applications of nanofibers and nanofiber membranes via electrospinning/interfacial polymerization. J. Appl. Polym. Sci. 2010, 115, 756–776.
[52] Esfahani, M.R.; Aktij, S.A.; Dabaghian, Z.; Firouzjaei, M.D.; Rahimpour, A.; Eke, J.; Escobar, I.C.; Abolhassani, M.; Greenlee, L.F.; Esfahani, A.R.; et al. Nanocomposite membranes for water separation and purification: Fabrication, modification, and applications. Sep. Purif. Technol. 2019, 213, 465–499.
[53] Tang, C.;Wang, Z.; Petrini´c, I.; Fane, A.G.; Hélix-Nielsen, C. Biomimetic aquaporin membranes coming of age. Desalination 2015, 368, 89–105.
[54] Cornwell, D.J.; Smith, D.K. Expanding the scope of gels–Combining polymers with low-MOLECULAR-Weight gelators to yield modified self-Assembling smart materials with high-Tech applications. Mater. Horiz. 2015, 2, 279–293.
[55] Asatekin, A.; Menniti, A.; Kang, S.; Elimelech, M.; Morgenroth, E.; Mayes, A.M. Antifouling nanofiltration membranes for membrane bioreactors from self-assembling graft copolymers. J. Membr. Sci. 2006, 285, 81–89.
[56] Bello ˇ n, T.; Polezhaev, P.; Vobecká, L.; Slouka, Z. Fouling of a heterogeneous anion-Exchange membrane and single anion-Exchange resin particle by ssdna manifests di_erently. J. Membr. Sci. 2019, 572, 619–631.
[57] Naeem, F.; Naeem, S.; Zhao, Z.; Shu, G.Q.; Zhang, J.; Mei, Y.; Huang, G.S. Atomic layer deposition synthesized ZnO nanomembranes: A facile route towards stable supercapacitor electrode for high capacitance. J. Power Source 2020, 451, 227740.
[58] Asatekin, A.; Menniti, A.; Kang, S.; Elimelech, M.; Morgenroth, E.; Mayes, A.M. Antifouling nanofiltration membranes for membrane bioreactors from self-assembling graft copolymers. J.Membr. Sci. 2006,285,81–89.
[59] Tang, C.; Wang, Z.; Petrinic´, I.; Fane, A.G.; Hélix-Nielsen, C. Biomimetic aquaporin membranes coming of age. Desalination 2015, 368, 89–105.
[60] Asatekin, A.; Menniti, A.; Kang, S.; Elimelech, M.; Morgenroth, E.; Mayes, A.M. Antifouling nanofiltration membranes for membrane bioreactors from self-assembling graft copolymers. J.Membr. Sci. 2006,285,81–89.
[61] Esfahani, M.R.; Aktij, S.A.; Dabaghian, Z.; Firouzjaei, M.D.; Rahimpour, A.; Eke, J.; Escobar, I.C.; Abolhassani, M.; Greenlee, L.F.; Esfahani, A.R.; et al. Nanocomposite membranes for water separation and purification: Fabrication, modification, and applications. Sep. Purif. Technol. 2019, 213, 465–499.
[62] Cornwell,D.J.;Smith,D.K.Expandingthescopeofgels–Combiningpolymerswithlow-MOLECULAR-Weight gelators to yield modified self-Assembling smart materials with high-Tech applications. Mater. Horiz. 2015, 2, 279–293.
[63] Feng,C.;Khulbe,K.C.;Matsuura,T.Recentprogressinthepreparation, characterization, and applications of nanofibers and nanofiber membranes via electrospinning/interfacial polymerization. J. Appl. Polym. Sci. 2010, 115, 756–776.
[64] Taurozzi, J.S.; Arul, H.; Bosak, V.Z.; Burban, A.F.; Voice, T.C.; Bruening, M.L.; Tarabara, V.V. Effect of filler incorporation route on the properties of polysulfone–silver nanocomposite membranes of different porosities. Journal of Membrane Science 2008, 325, 58-68, https://doi.org/10.1016/j.memsci.2008.07.010.
[65] Pan, B.; Xing, B. Adsorption Mechanisms of Organic Chemicals on Carbon Nanotubes. Environmental Science & Technology 2008, 42, 9005-9013,
[66] Montemagno, C.; Schmidt, J.; Tozzi, S. Biomimetic Membranes. U.S. Patent No. 20040049230, 11 March 2004.
[67] Salim, W.; Ho, W.S.W. Recent developments on nanostructured polymer-Based membranes. Curr. Opin. Chem. Eng. 2015, 8, 76–82.
[68] Yu, L.; Ruan, S.; Xu, X.; Zou, R.; Hu, J. Review One-Dimensional nanomaterial-Assembled macroscopic membranes for water treatment. Nano Today 2017, 17, 79–95.
[69] Fuwad, A.; Ryu, H.; Malmstadt, N.; Kim, S.M.; Jeon, T.J. Biomimetic membranes as potential tools for water purification: Preceding and future avenues. Desalination 2019, 458, 97–115.
[70] Shen, Y.X.; Saboe, P.O.; Sines, I.T.; Erbakan, M.; Kumar, M. Biomimetic membranes: A review. J. Membr. Sci. 2014, 454, 359–381.
[71] Peng, F.; Xu, T.; Wu, F.; Ma, C.X.; Liu, Y.; Li, J.; Zhao, B.; Mao, C. Novel biomimetic enzyme for sensitive detection of superoxide anions. Talanta 2017, 174, 82–91.
[72] Giwa, A.; Hasan, S.W.; Yousaf, A.; Chakraborty, S.; Johnson, D.J.; Hilal, N. Biomimetic membranes: A critical review of recent progress. Desalination 2017, 420, 403–424.
[73] Diallo, M.S.WaterTreatmentbyDendrimer EnhancedFiltration.U.S.PatentNo.2009/0223896,10 September 2009.
[74] Khan, F.S.A., Mubarak, N.M., Khalid, M. et al. Magnetic nanoadsorbents’ potential route for heavy metals removal—a review. Environ Sci Pollut Res 27, 24342–24356 (2020).
[75] Sahebi, S.; Sheikhi, M.; Ramavandi, B. A new biomimetic aquaporin thin film composite membrane for forwarding osmosis: Characterization and performance assessment. Desalin. Water Treat. 2019, 148, 42–50.
[76] Manikam, M.K.; Halim, A.A.; Hanafiah, M.M.; Krishnamoorthy, R.R. Removal of ammonia nitrogen, nitrate, phosphorus, and COD from sewage wastewater using palm oil boiler ash composite adsorbent. Desal. Water Treat. 2019, 149, 23–30. 161.
[77] Charee,S.W.;Aravinthan,V.;Erdei,L.;Raj,W.S.Useofmacadamianutshellresiduesasmagneticnanosorbents. Int. Biodeter. Biodegr. 2017, 124, 276–287.
[78] Lee, X.J.; Foo, L.P.Y.; Tan, K.W.; Hassell, D.G.; Lee, L.Y.Evaluation of carbon-Based nano sorbents synthesized by ethylene decomposition on stainless steel substrates as potential sequestrating materials for nickel ions in aqueous solution. J. Environ. Sci. 2012, 24, 1559–1568.
[79] Kyzas, G.Z.; Matis, K.A. Review Nanoadsorbents for pollutants removal: A review. J. Mol. Liq. 2015, 203, 159–168.
[80] Wang X. Cai W. Lin Y. et al.: ‘Mass production of micro/nanostructured porous ZnO plates and their strong structurally enhanced and selective adsorption performance for environmental remediation, J. Mater. Chem., 2010, 20, (39), pp. 8582 –8590
[81] Zhou Y.T. Nie H.L. White C.B. et al.: ‘Removal of Cu2+ from aqueous solution by chitosan-coated magnetic nanoparticles modified with α-ketoglutaric acid’, J. Colloid Interf. Sci., 2009, 330, (1), pp. 29 –37
[82] Adav,V.B.;Gadi,R.;Kalra,S.Claybasednanocompositesforremovalofheavymetalsfromwater: A review. J. Environ. Manag. 2019, 232, 803–817. [PubMed]
[83] Vunain, E.; Mishra, A.K.; Mamba, B.B. Dendrimers, mesoporous silicas and chitosan-Based nanosorbents for the removal of heavy-Metal ions: A review. Int. J.Biolog. Macromol. 2016, 86, 570–586. [PubMed]
[84] Khajeh, M.; Laurent, S.; Dastafkan, K. Nanoadsorbents: Classification, preparation, and applications (with emphasis on aqueous media). Chem. Rev. 2013, 113, 7728–7768. [PubMed].
[85] Rabia Nazir, Introduction to Environmental Nanotechnology, Research Anthology on Emerging Techniques in Environmental Remediation, 10.4018/978-1-6684-3714-8, (44-70), (2022).Crossref
[86] Shamik Chowdhury, Sharadwata Pan, Graphene‐Based Macromolecular Assemblies for Scavenging Heavy Metals, ChemistryOpen, 10.1002/open.202000182, 9, 10, (1065-1073), (2020).
[87] Yadav, V.B.; Gadi, R.; Kalra, S. Clay-based nanocomposites for removal of heavy metals from water: A review. J. Environ. Manag. 2019, 232, 803–817. [PubMed]
[88] Wang, Y.; Zhang, Y.; Hou, C.; Liu, M. Mussel-Inspired synthesis of magnetic polydopamine–Chitosan nanoparticles as bio sorbent for dyes and metals removal. J. Taiwan Inst. Chem. E 2016, 61, 292–298.
[89] Rodovalho, F.L.; Capistrano, G.; Gomes, J.A.; Sodre, F.F.; Chaker, J.A.; Campos, A.F.C.; Bakuzis, A.F.; Sousa, A.H. Elaboration of magneto-Thermally recyclable nanosorbents for remote removal of toluene in contaminated water using magnetic hyperthermia. Chem. Eng. J. 2016, 15, 725–732.
[90] Sun, X.; Liu, Z.; Zhang, G.; Qiu, G.; Zhong, N.; Wu, L.; Cai, D.; Wu, Z. Reducing the pollution risk of pesticide using nanonetworks induced by irradiation and hydrothermal treatment. J. Environ. Sci. Health C 2015, 50, 901–907. [PubMed]
[91] Lee, X.J.; Foo, L.P.Y.; Tan, K.W.; Hassell, D.G.; Lee, L.Y. Evaluation of carbon-Based nanosorbents synthesized by ethylene decomposition on stainless steel substrates as potential sequestrating materials for nickel ions in aqueous solution. J. Environ. Sci. 2012, 24, 1559–1568.
[92] Kyzas, G.Z.; Matis, K.A. Review Nanoadsorbents for pollutants removal: A review. J. Mol. Liq. 2015, 203, 159–168. Water 2020, 12, 495 28 of 30
[93] Krsti´c, V.; Pesovski, T.U.B. A review on adsorbents for treatment of water and wastewaters containing copper ions. Chem. Eng. Sci. 2018, 192, 273–287.
[94] Unuabonah, E.I.; Taubert, A. Review article Clay-Polymer nanocomposites (CPNs): Adsorbents of the future for water treatment. Appl. Clay Sci. 2014, 99, 83–92.
[95] Moo, J.G.S.; Pumera, M. Chemical energy powered nano/micro/macromotors and the environment. Chem.–A Eur. J. 2015, 21, 58–72.
[96] Tahir, M.B.; Kiran, H.; Iqbal, T. The detoxification of heavy metals from the aqueous environment using the nano-photocatalysis approach: A review. Environ. Sci. Pollut. Res. 2019, 26, 10515–10528.
[97] Berekaa, M.M. Nanotechnology in wastewater treatment; the influence of nanomaterials on microbial systems. Int. J. Curr. Microbiol. App. Sci 2016, 5, 713–726.
[98] Malik, A.; Hameed, S.; Siddiqui, M.J.; Haque, M.M.; Umar, K.; Khan, A.; Muneer, M. Electrical and optical properties of nickel-and molybdenum-doped titanium dioxide nanoparticle: Improved performance in dye-sensitized solar cells. J. Mater. Eng. Perform. 2014, 23, 3184–3192.
[99] Guya, N.; Cakar, S.; Ozacar, M. Comparison of palladium/zinc oxide photocatalysts prepared by different palladium doping methods for congo red degradation. J. Colloid Interface Sci. 2016, 466, 128–137
[100] Sadegh, H.; Ali, G.A.M.; Gupta, V.K.; Makhlouf, A.S.H.; Nadagouda, M.N.; Sillanpaa, M.; Megiel, E. The role of nanomaterials as effective adsorbents and their applications in wastewater treatment. J. Nanostructure Chem. 2017, 7, 1–14.
[101] Raliya, S.R.; Avery, C.; Chakrabarti, S.; Biswas, P. Photocatalytic degradation of methyl orange dye by pristine TiO2, ZnO, and graphene oxide nanostructures and their composites under visible light irradiation. Appl. Nano Sci. 2017, 7, 253–259.
[102] Mir, N.A.; Khan, A.; Umar, K.; Muneer, M. Photocatalytic Study of a Xanthene Dye Derivative, Phloxine B in Aqueous Suspension of TiO2: Adsorption Isotherm and Decolourization Kinetics. Energy Environ. Focus 2013, 2, 208–216.
[103] Dar, A.A.; Umar, K.; Mir, N.A.; Haque, M.M.; Muneer, M.; Boxall, C. Photocatalysed degradation of an herbicide derivative, Dinoterb, in aqueous suspension. Res. Chem. Intermediate. 2011, 37, 567–578.
[104] Schlosser, D. Biotechnologies for Water Treatment. In Advanced Nano-Bio Technologies for Water and Soil Treatment; Springer, Cham: Berlin/Heidelberg, Germany, 2020; pp. 335–343. 213
[105] Lu, F.; Astruc, D. Nanocatalysts and other nanomaterials for water remediation from organic pollutants. Coord. Chem. Rev. 2020, 408, 213180
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Dr. Mishu Singh, Dr. Akhilesh Kumar “A Comprehensive Review: Nanomembranes and Nanosorbents for Water Treatment” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.01-06 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/01-06.pdf
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Implicit Seven Step Simpson’s Hybrid Block Second-derivative Method with One Off-Step Point for Solving Second Order Ordinary Differential Equations
Umaru, A. H., Donald, J. Z., and Skwame, Y.- September 2022 Page No.: 07-11
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This paper is concerned with the construction of continuous Seven-Step implicit hybrid block Simpson’s Second derivative method for solving initial value problems of second order ordinary differential equations were derived through interpolation and collocation method using maple software. Power series approximation method was used to generate the unknown parameters in the corrector. These Continuous formulations were evaluated at some desired points to give the discrete schemes which constitute the hybrid block method. The constructed block method is consistent, zero-stable and A(α)-Stable. Numerical results obtained using the new block method show that it superior on some system of initial value problems. The study revealed that our new method performed better.
Page(s): 07-11 Date of Publication: 03 October 2022
Authors
Umaru, A. H.
Department Of Mathematics, Adamawa State University Mubi Nigeria
Donald, J. Z.
Department Of Mathematics, Adamawa State University Mubi Nigeria
Skwame, Y.
Department Of Mathematics, Adamawa State University Mubi Nigeria
References
[1] Butcher, J. C., 1993. “General linear methods for the parallel solution of ordinary differential equations” Appl Anal., vol. 2, pp.97-111.
[2] Chollom, J. P. Ndam, J. N. and Kumleng, G. M. (2007): On some properties of the block linear multistep methods. Science World Journal 2(3).
[3] Donald, J.Z., Yusuf, S., Pius T. and Paul, I. D. (2009): Construction of two step Simpson’s multistep method as parallel integration for the solution of ODEs, Bagale J. Pure Appl. Sci. 7: 1 – 12
[4] Dahlquist, G. G. (1956). Convergence and stability in the numerical integration of ordinary differential equations Math. Scand. 4:33-50
[5] Henrici, P. (1962); Discrete variable methods in ordinary differential equations John Willey and sons, New York.
[6] Ibijola, E. A., Skwame, Y., and Kumeleng, G., (2011) “Formation of hybrid block of higher sizes, through the continuous multi-step collocation” American journal of Science and Industrial Research. 52, pp. 161-173.
[7] Jain, M. K., Iyangar, R. S. K., and Jain, R. K., (2014). Numerical methods for Scientific and Engineering computation. 6th ed. New Delhi: New Age International Publishers.
[8] Lambert, J.D. (1973). Computational Methods in ODEs. New York: John Wiley.
[9] Milne, W. E. (1953). Numerical Solution of Differential Equations. New York, Willey.
[10] Onumanyi, P., Awoyemi, D. 0., Jator, S. N., & Sirisena, U. W., (1994). New Linear Multistep Methods with Continuous Coefficients for First Order IVPs. Journal of Nigerian Mathematical Society, 13: 37-51
[11] Sirisena, U. W. (1997); A reformation of continuous General Linear Multistep Method by Matrix Inversion for first order Initial Value Problem. Spectrum Journal, 150 – 168
[12] Skwame, Y. (2018). Formation of multiple off-grid points for the treatment of system of stiff ordinary differential equations. Academic Journal of Applied Mathematical SciencesVol.4 Issue. 1, pp; 1-7.
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Umaru, A. H., Donald, J. Z., and Skwame, Y. “Implicit Seven Step Simpson’s Hybrid Block Second-derivative Method with One Off-Step Point for Solving Second Order Ordinary Differential Equations” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.07-11 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/07-11.pdf
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Assessment of the Relationship Between the AST&D Beneficiaries and the Perceived Benefits and Challenges.
Shedrack Enyeribe Nwannunu- September 2022 Page No.: 12-19
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The study looked at the relationship between TETFUND AST&D beneficiaries’ satisfaction with the benefit and the obstacles associated with the funding for academic staff training and development. The study’s population was drawn from Abdu Gusau Polytechnic in the Northwest, Nigeria. Twenty of the thirty structured questionnaires were returned as valid and were used in the study. The descriptive statistics were obtained by SPSS 2023, and the hypothesis was tested using Spearman’s correlation coefficients. Statistics reveal a totally positive and statistically significant association between the satisfaction of AST&D recipients and the benefits and difficulties. Second, the interaction between AST&D benefits and challenges was strongly positive and statistically significant, indicating that the challenges had no effect on the benefits. The study recommends that TETFUND should entice local funding to attract applicants. Balancing the disparity between local and international AST&D funds will attract more local trainees and will also increase Nigeria’s assets denominated in foreign currency (foreign reserves) that are held by the Central Bank of Nigeria (CBN).
Page(s): 12-19 Date of Publication: 03 October 2022
DOI : 10.51584/IJRIAS.2022.7901Authors
Shedrack Enyeribe Nwannunu
Department of Accountancy
Abdu Gusau Polytechnic, Talata Mafara, Zamfara, Nigeria
References
[1] Abdulmujib, J. (2021). Tetfund intervention and manpower training and development in northern Nigeria : Evidence from Selected Tertiary Institutions. Bakolori Journal of General Studies, 12(1), 3423–3439.
[2] Adesanwo, J. F. E. O. (2021). Impact of Tertiary Education Trust Fund ( Tetfund ) Interventions On Industrial Peace In Olabisi Onabanjo. Journal of Varna University of Economics, 65(1), 12–135.
[3] Ahlström, G., Ros, H., & Persson, E. I. (2022). Quality of Life among Next of Kin of Frail Older People in Nursing Homes : An Interview Study after an Educational Intervention concerning Palliative Care. International Journal of Environmental Research and Public Health Article, 2022(9), 2–17.
[4] Anaehobi, E. S. ;, & Agim, E. C. (2019). TETFund intervention and development of university libraries in South-. Library and Information Perspectives and Research, 1(50), 50–58.
[5] Anderibom, A. S. ;Enoch B. (2017). Science Education Department Adamawa State Polytechnic Yola. International Journal of Education and Research, 5(5), 41–60.
[6] Chinwe, Nancy;UDU, G. O. C. (2019). Quality And Relevance Of Tertiary Education Trust Fund Intervention Researches In Tertiary Institutions In South East Nigeria (2010-2015). International Journal of Development and Management Review (INJODEMAR), 14(1), 85–95.
[7] Conn, K. M. (2017). Identifying Effective Education Interventions in Sub-Saharan Africa : A Meta-Analysis of Impact Evaluations. Review of Educational Research, XX(X), 1–36. https://doi.org/10.3102/0034654317712025
[8] Danaher, P. J., & Haddrell, V. (1996). A comparison of question scales used for measuring customer satisfaction. International Journal of Service Industry Management, 7(4), 4–26. https://doi.org/10.1108/09564239610129922
[9] Evans, D. K., & Yuan, F. (2022). What We Learn about Girls’ Education from Interventions That Do Not Focus on Girls. World Bank Economic Review, 36(1), 244–267.
[10] Hair Jr., J. F., Gabriel, M. L. D. da S., & Patel, V. K. (2014). Modelagem de Equações Estruturais Baseada em Covariância (CB-SEM) com o AMOS: Orientações sobre a sua aplicação como uma Ferramenta de Pesquisa de Marketing. Revista Brasileira de Marketing, 13(2), 44–55. https://doi.org/10.5585/remark.v13i2.2718
[11] Ibrahim, B. (2021). Impact of TETFund Intervention on Quality and Relevance of Research Development in Tertiary Institutions in North Central Nigeria. Journal of Science Technology and Education, 9(1), 117–125.
[12] Isiaka, A., Nasiru, O. I., & Olushola, I. A. (2020). Tertiary education trust fund intervention on academic staff capacity building in Lagos State University, Nigeria. Journal of Education and Learning, 14(2), 155–161. https://doi.org/10.11591/edulearn.v14i2.14544
[13] Kılıç, M., Uyar, A., Kuzey, C., & Karaman, A. S. (2021). Does institutional theory explain integrated reporting adoption of Fortune 500 companies? Journal of Applied Accounting Research, 22(1), 114–137. https://doi.org/10.1108/JAAR-04-2020-0068
[14] Koskela-Huotari, K., Vink, J., & Edvardsson, B. (2020). The institutional turn in service research: taking stock and moving ahead. Journal of Services Marketing, 34(3), 373–387. https://doi.org/10.1108/JSM-02-2019-0101
[15] Li, J., Zhou, Y., Yao, J., & Liu, X. (2021). An empirical investigation of trust in AI in a Chinese petrochemical enterprise based on institutional theory. Scientific Reports, 11(1), 1–12. https://doi.org/10.1038/s41598-021-92904-7
[16] Mbawuni, J. (2018). Perceived Benefits and Challenges of IFRS Adoption in Ghana: Views of Members of Institute of Chartered Accountants, Ghana (ICAG). International Journal of Financial Research, 9(1), 99–114. https://doi.org/10.5430/ijfr.v9n1p99
[17] Nawaz, R., Sun, Q., Shardlow, M., Kontonatsios, G., Aljohani, N. R., Visvizi, A., & Hassan, S. (2022). applied sciences Leveraging AI and Machine Learning for National Student Survey : Actionable Insights from Textual Feedback to Enhance Quality of Teaching and Learning in UK’s Higher Education.
[18] Ng, E. D., Yan, J., Chua, X., & Shorey, S. (2020). The Effectiveness of Educational Interventions on Traditional Bullying and Cyberbullying Among Adolescents : A Systematic Review and Meta-Analysis. https://doi.org/10.1177/1524838020933867
[19] Nkwede, J. O., & Idolor, J. (2014). Tertiary Education Trust Fund Interventions and Sustainable Development in Nigerian Universities : Evidence from … Journal of Sustainable Development, 7(4), 191–205. https://doi.org/10.5539/jsd.v7n4p191
[20] NNAEMEKA, J. & YAHAYA J. A, S. (2021). Influence of TETFund Intervention on Staff and Infrastructural Development for Improving Quality Tertiary Education in Abia State, Nigeria. International Journal of Management Studies and Social Science Research Influence, 3(5), 1–10.
[21] Oko, F. (2019). The Effects of Manpower Development Efforts of the Tertiary Education Trust Fund on Productivity and Performance of Academic Staff Members of Colleges of Education in Nigeria. American Journal of Creative Education, 5(1), 149–160. https://doi.org/10.20448/815.23.149.160
[22] OLATUNJI, A. A. W. (2020). Assessment of Tertiary Education Trust Fund Intervention (Tetfund) in Kwara State Polytechnic Ilorin, Nigeria. International Journal of Politics and Good Governance, XI(11), 1–13.
[23] Onwuchekwa, Grace, U. (2016). Influence of tertiary education trust fund (get fund) on educational research in Nigerian universities. International Journal of Academia, Volume, 2(1), 1–12.
[24] Onyeneke, C. (2020). TETFund intervention in the provision of library resources in academic libraries in Nigeria. IFLA Journal, XX(X), 2–11. https://doi.org/10.1177/0340035220958019
[25] RAJI, R. A. (2019). Impact of Tetfund’s Foreign Postgraduate Training on Human Capital Development And Local Adaptation of Transferred Knowledge. Ilaro Journal of Environmental Research & Development, 3(1), 227–239.
[26] Robertson, J., Dowling, M., Washington, M., Leopkey, B., Lee Ellis, D., & Smith, L. (2021). Institutional Theory in Sport: A Scoping Review. Journal of Sport Management, 1–14. https://doi.org/10.1123/jsm.2021-0179
[27] Udoka, Dikeocha, L. (2021). Management of business teacher education in colleges of education in the southeast zone. Journal of Business Education 8(3), 24–35.
[28] Willmott, H. (1995). Managing the Academics: Commodification and Control in the Development of University Education in the UK. Human Relations, 48(9), 993–1027. https://doi.org/10.1177/001872679504800902
[29] Zhang, W., Henderson, C., Magnusdottir, E., Chen, W., Ma, N., Ma, H., & Thornicroft, G. (2022). Effect of a contact-based education intervention on reducing stigma among community health and care staff in Beijing, China : A pilot randomized controlled study. Asian Journal of Psychiatry, 73(November 2021).
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Shedrack Enyeribe Nwannunu “Assessment of the Relationship Between the AST&D Beneficiaries and the Perceived Benefits and Challenges.” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.12-19 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7901
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Finite Element Analysis of Pressure Vessels Subjected to Uniform Internal Pressure Using Ansys Software
Feysal Mohamed Shirwa- September 2022 Page No.: 20-26
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This paper discusses the stresses developed in the pressure vessels having various thicknesses. Pressure vessels are intended to hold gases or liquids at a pressure substantially different from atmospheric pressure. Equations of static equilibrium along with free body diagrams will be used to determine the normal stress σ1 in the hoop direction and σ2 in the longitudinal direction also the von misses’ stresses. Also we will discuss the deformations and displacements to the pressure vessel using commercial finite element software called ANSYS for modelling and analyzing of the vessels. And the main results we found is that there is stress and deformation variation in the vessel according to thickness
Page(s): 20-26 Date of Publication: 09 October 2022
DOI : 10.51584/IJRIAS.2022.7902Authors
Feysal Mohamed Shirwa
Masters in Structural Engineering, BSc in Civil Engineering
Senior Lecturer at Department of Civil Engineering of Zamzam University of Science and Technology
Somali International University, University of Somalia, Mogadishu, Banadir, Somalia
References
[1] Assistant, M. kumar. (20173). Stress Analysis of Pressure Vessels. IJARIIE, 3(3), 2570–2573. https://doi.org/10.1115/pvp2012-78138
[2] Pendbhaje, R. A., Gaikwad, M., Deshmukh, N., & Patil, R. (2014). Design and Analysis of Pressure Vessel. International Journal of Innovative Research in Technology & Science, 2(3), 28–34. Retrieved from http://ijirts.org/volume2issue3/IJIRTSV2I3036.pdf
[3] Kharagpur, I. I. T. (201AD). Thick cylinders- Stresses due to internal and external pressures. www.iitkgp.ac.in, 1–14. tge.readthedocs.io (accessed at 2:00 pm, 18 May 2019)
[4] Kharagpur, I. I. T. (201AD). Thick cylinders- Stresses due to internal and external pressures. www.iitkgp.ac.in, 1–14.
[5] Univeristy of Washington. (2011). Thick Walled Cylinders. N.N, 1–5.
[6] Roylance, D. (1989). Pressure vessels and piping papers published in 1988 Contents of volume 31. International Journal of Pressure Vessels and Piping, 36(1), i–xi. https://doi.org/10.1016/0308-0161(89)90061-6
[7] Livingston, E. (2000). Livingston , E., Scavuzzo, R. J. “Pressure Vessels.” Design.
[8] Wadkar, V. V, Malgave, S. S., Patil, D. D., Bhore, H. S., & Gavade, P. P. (2015). Design and Analysis of Pressure Vessel Using Ansys. Journal of Mechanical Engineering and Technology,3(32),1–13.Retrieved from http://www.iaeme.com/IJMET.asp%0Ahttp://www.iaeme.com/JMET/issue.asp?JType=JMET&VType=3&IType=2
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Feysal Mohamed Shirwa “Finite Element Analysis of Pressure Vessels Subjected to Uniform Internal Pressure Using Ansys Software” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.20-26 September 2022
DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7902
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Bluetooth And Arduino Uno-Based Voice-Controlled Home Automation System
Modupe E. Sanyaolu, Victoria O. Amolegbe, Alexander A. Willoughby- September 2022 Page No.: 27-30
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People nowadays seek strategies to improve their lifestyles by utilizing the most up-to-date technologies. Also, the physically challenged find it difficult to do minor tasks alone in the home. Home automation systems are getting more attention coinciding with developments in the Internet of Things. In line with assistive technology, this project demonstrates the implementation of a low-cost home automation system by designing and building a microcontroller-based system for controlling and monitoring home devices with the use of a voice remote control system that allows data to be transferred through wireless media. The technology is simple to use and is built on an Android-based smartphone with an easy interface. Demonstrations reveal that the system makes it easier for the system’s intended users (the elderly and the disabled) to operate lighting, heating, cooling, and security systems in their homes.
Page(s): 27-30 Date of Publication: 09 October 2022
DOI : 10.51584/IJRIAS.2022.7903Authors
Modupe E. Sanyaolu
Department of Physical Sciences, Faculty of Natural Sciences, Redeemer’s University, PMB 230, Ede, Osun State, Nigeria
Victoria O. Amolegbe
Department of Physical Sciences, Faculty of Natural Sciences, Redeemer’s University, PMB 230, Ede, Osun State, Nigeria
Alexander A. Willoughby
Department of Physical Sciences, Faculty of Natural Sciences, Redeemer’s University, PMB 230, Ede, Osun State, Nigeria
References
[1] Malik, N. & Bodwade, Y. (2017). Literature review on home automation system. international Journal of Advanced Research in Computer and Communication Engineering (ijarcce).
[2] Smitha.M, T., Ayesha Rumana, & Sutha P. (2015) , “Hand gesture based home automation for visually challenged, International journal of innovations in engineering research and technology
[3] Latha A.P., Agarwal, Rishabh Rajgarhia, Shashank Sinha, & Nafiya Monis (2015). Home automation using Android application and Predictive Behaviour Implementation”, International Journal of Engineering and Techniques
[4] Asadullah, M., & Raza, A. (2016). An overview of home automation systems. 2nd International Conference on Robotics and Artificial Intelligence (ICRAI).
[5] Abhishek Neb thesis (2014). Design of home automation using voice control.
[6] Murali Krishna, B., Narasimha Nayak, Ravi Kishore Reddy, B., Rakesh,P. Manoj Kumar, & Sandhya N. (2015) “Bluetooth based Wireless home automation system using FPGA” Journal of Theoretical and Applied Information Technology
[7] Anusha, S., Madhavi, M., & Hemalatha, R. (2015) home automation using ATmega 328 microcontroller and android application.
[8] Ganesan, M. T. M. S., Jothi, M. R., Sangavi, R. S., & Umayal, L. (2019). Home Automation using Arduino and Smart Phone. International Journal of Engineering Research & Technology
[9] Manda, V. L. K. B., Kushal, V., & Ramasubramanian, N. (2018). An Elegant Home Automation System Using GSM and ARM-Based Architecture, institute of electrical and electronics engineers (in IEEE Potentials).
[10] Rezuan, A., Azman, B. and Darul, P. (2013) design of a home automation using Arduino with wireless control.
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Modupe E. Sanyaolu, Victoria O. Amolegbe, Alexander A. Willoughby “Bluetooth And Arduino Uno-Based Voice-Controlled Home Automation System” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.27-30 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7903
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Monitoring and Evaluation of Air Quality: A Case Study of Mogadishu, Somalia
Abdulshakur Abdullahi Diiso, Mohamed M. Garas, Abdisalam Abdullahi Adan, Nur Rashid Ahmed- September 2022 Page No.: 31-36
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The long lasting civil war in Somalia and the limited functionality of the Mogadishu based government for over the last 20 years have had negative implications on both the environment and public health majorly through air pollution. The absence of strong laws or legislations concerning access and use of different natural resources has severe consequences on the entire Somalia population as a whole. This study was aimed at assessing the level of air quality in Mogadishu, Somalia. The focus of the assessment was to carefully document the prevailing environmental health situation or air quality in the selected districts of Mogadishu mostly concerning the areas of sanitation and hygiene, industrial pollution and energy as well as air quality as a whole. A descriptive observational study was undertaken in the seven selected Mogadishu of districts to assess the level of air quality and the overall environmental health situation in the area. A sample of 10 commercial areas was used for each district, and both PM2.5 and PM 10 devices were installed, and each areawas checked three times (7:00Am.) (12:00PM) and (3:00PM) values were entered in Excel 2019. The level of pollution in all areas of the study are very healthy state. Except the Hodan district in which there is moderate to high level of pollution followed by Yaqshid and Heliwa. However; in Somalia the air pollution is not a national issues as compared the Neighboring countries. Although our study season may have impact on overall study results due to the winter season we suggest that need for further study in the different seasons to expose the hidden factors that minimize the level of pollution.
Page(s): 31-36 Date of Publication: 17 October 2022
Authors
Abdulshakur Abdullahi Diiso
Research Fellow, Department of Engineering, Faculty of Civil Engineering, Jamhuriye University of Science and Technology, Somalia
Mohamed M. Garas
Research Fellow, Department of Engineering, Faculty of Civil Engineering, Jamhuriye University of Science and Technology, Somalia
Abdisalam Abdullahi Adan
Research Fellow, Department of Engineering, Faculty of Civil Engineering, Jamhuriye University of Science and Technology, Somalia
Nur Rashid Ahmed
Research Fellow, Department of Engineering, Faculty of Civil Engineering, Jamhuriye University of Science and Technology, Somalia
References
[1] Ando, M., Katagiri, K., Tamura, K., Yamamoto, S., Matsumoto, M., Li, Y. F., … & Liang, C. K. (1996). Indoor and outdoor air pollution in Tokyo and Beijing supercities. Atmospheric Environment, 30(5), 695-702.
[2] Arya, S. P. (1999). Air pollution meteorology and dispersion (Vol. 6). New York: Oxford University Press.
[3] Brunekreef, B., & Holgate, S. T. (2002). Air pollution and health. The lancet, 360(9341), 1233-1242.
[4] Brimblecombe, P. (2012). The Big Smoke (Routledge Revivals): A History of Air Pollution in London since Medieval Times. Routledge.
[5] Gatari, M. J. (2019). First WHO Global Conference on Air Pollution and Health: A Brief Report. Clean Air Journal, 29(1), 7-7.
[6] Evans, G. W., & Jacobs, S. V. (1981). Air pollution and human behavior. Journal of Social Issues, 37(1), 95-125.
[7] Effects, H. (n.d.). Health & Environmental Effects of Air Pollution.
[8] Friedrich, M. J. (2017). UNICEF reports on the impact of air pollution on children. Jama, 317(3), 246-246.
[9] Huang, Y. C. T. (2014). Outdoor air pollution a global perspective. Journal of Occupational and Environmental Medicine, 56(10), S3–S7. https://doi.org/10.1097/JOM.0000000000000240
[10] Jeong, S. J. (2013). The impact of air pollution on human health in Suwon City. Asian journal of atmospheric environment, 7(4), 227-233.
[11] Kampa, M., & Castanas, E. (2008). Human health effects of air pollution. Environmental pollution, 151(2), 362-367.
[12] Kamra, A. K., Deshpande, C. G., & Gopalakrishnan, V. (1997). Effect of relative humidity on the electrical conductivity of marine air. Quarterly Journal of the Royal Meteorological Society, 123(541), 1295–1305. https://doi.org/10.1256/smsqj.54107
[13] Larssen, s & Adams, Martin & Barrett, KJ & Bolscher, Maarten & de Leeuw, Frank & Pulles, Tinus. (2004). Air Pollution in Europe 1990-2000.
[14] Petkova, E. P., Jack, D. W., Volavka-Close, N. H., & Kinney, P. L. (2013). Particulate matter pollution in African cities. Air Quality, Atmosphere & Health, 6(3), 603-614.
[15] Song, C., Wu, L., Xie, Y., He, J., Chen, X., Wang, T., … & Dai, Q. (2017). Air pollution in China: status and spatiotemporal variations. Environmental pollution, 227, 334-347.
[16] Viebahn, P. (2002). An environmental management model for universities: From environmental guidelines to staff involvement. Journal of Cleaner Production, 10(1), 3–12. https://doi.org/10.1016/S0959-6526(01)00017-8
[17] World Health Organization (WHO. (2000). Air quality guidelines for Europe.
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Abdulshakur Abdullahi Diiso, Mohamed M. Garas, Abdisalam Abdullahi Adan, Nur Rashid Ahmed “Monitoring and Evaluation of Air Quality: A Case Study of Mogadishu, Somalia” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.31-36 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/31-36.pdf
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A Deep Learning Based Classification Model for the Detection of Brain Tumor using MRI
Md. Abid Hasan Nayeem, Mehedi Hasan Shakil, Sadia Afrin, Sadah Anjum Shanto, Shadia Jahan Mumu, Md. Mahmudul Hasan Shanto- September 2022 Page No.: 37-42
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The diagnosis of a brain tumor requires high accuracy, as even small errors in judgment can lead to critical problems. For this reason, brain tumor segmentation is an important challenge for medical purposes. The wrong classification can lead to worse consequences. Therefore, these must be properly divided into many classes or levels, and this is where multiclass classification comes into play. The latest development of image classification technology has made great progress, and the most popular and better method is considered to be the best in this area is CNN, so this paper uses CNN for the brain tumor classification problem. The proposed model successfully classifies brain images into two distinct categories, namely the absence of tumors indicating that a given brain MRI is free of tumors or the Brain contains Tumor. This model produces an accuracy based on the results of a study that was conducted on a group of volunteers.
Page(s): 37-42 Date of Publication: 17 October 2022
DOI : 10.51584/IJRIAS.2022.7904Authors
Md. Abid Hasan Nayeem
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
Mehedi Hasan Shakil
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
Sadia Afrin
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
Sadah Anjum Shanto
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
Shadia Jahan Mumu
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
Md. Mahmudul Hasan Shanto
Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
References
[1] Wahid, R. R., Anggraeni, F. T., & Nugroho, B. (2021). Brain Tumor Classification with Hybrid Algorithm Convolutional Neural Network-Extreme Learning Machine. IJCONSIST JOURNALS, 3(1), 29-33.
[2] Jin, K. H., McCann, M. T., Froustey, E., & Unser, M. (2017). Deep convolutional neural network for inverse problems in imaging. IEEE Transactions on Image Processing, 26(9), 4509-4522.
[3] Machhale, K., Nandpuru, H. B., Kapur, V., & Kosta, L. (2015, May). MRI brain cancer classification using a hybrid classifier (SVM-KNN). In 2015 International Conference on Industrial Instrumentation and Control (ICIC) (pp. 60-65). IEEE.
[4] Pathak, K., Pavthawala, M., Patel, N., Malek, D., Shah, V., & Vaidya, B. (2019, June). Classification of brain tumor using convolutional neural network. In 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 128-132). IEEE.
[5] Khan, H. A., Jue, W., Mushtaq, M., & Mushtaq, M. U. (2020). Brain tumor classification in MRI image using convolutional neural network. Math. Biosci. Eng, 17(5), 6203-6216.
[6] Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., … & Van Leemput, K. (2014). The multimodal brain tumor image segmentation benchmark (BRATS). IEEE transactions on medical imaging, 34(10), 1993-2024.
[7] Mohsen, H., El-Dahshan, E. S. A., El-Horbaty, E. S. M., & Salem, A. B. M. (2018). Classification using deep learning neural networks for brain tumors. Future Computing and Informatics Journal, 3(1), 68-71.
[8] Sobhaninia, Z., Rezaei, S., Noroozi, A., Ahmadi, M., Zarrabi, H., Karimi, N., … & Samavi, S. (2018). Brain tumor segmentation using deep learning by type-specific sorting of images. arXiv preprint arXiv:1809.07786.
[9] Sultan, H. H., Salem, N. M., & Al-Atabany, W. (2019). Multi-classification of brain tumor images using deep neural network. IEEE access, 7, 69215-69225.
[10] Irmak, E. (2021). Multi-classification of brain tumor MRI images using a deep convolutional neural network with a fully optimized framework. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 45(3), 1015-1036.
[11] Hemanth, D. J., Vijila, C. K. S., Selvakumar, A. I., & Anitha, J. (2014). Performance improved iteration-free artificial neural networks for abnormal magnetic resonance brain image classification. Neurocomputing, 130, 98-107.
[12] Pan, Y., Huang, W., Lin, Z., Zhu, W., Zhou, J., Wong, J., & Ding, Z. (2015, August). Brain tumor grading is based on neural networks and convolutional neural networks. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 699-702). IEEE.
[13] Hossain, T., Shishir, F. S., Ashraf, M., Al Nasim, M. A., & Shah, F. M. (2019, May). Brain tumor detection using convolutional neural network. In 2019 1st international conference on advances in science, engineering, and robotics technology (ICASERT) (pp. 1-6). IEEE.
[14] Saleh, A., Sukaik, R., & Abu-Naser, S. S. (2020, August). Brain tumor classification using deep learning. In 2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech) (pp. 131-136). IEEE.
[15] Paul, J. S., Plassard, A. J., Landman, B. A., & Fabbri, D. (2017, March). Deep learning for brain tumor classification. In Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging (Vol. 10137, pp. 253-268). SPIE.
[16] Deepak, S., & Ameer, P. M. (2019). Brain tumor classification using deep CNN features via transfer learning. Computers in biology and medicine, 111, 103345.
[17] Brain tumor detection | Data Science and Machine Learning | Kaggle
[18] Lukas, L., Devos, A., Suykens, J. A., Vanhamme, L., Howe, F. A., Majós, C., … & Van Huffel, S. (2004). Brain tumor classification is based on long echo proton MRS signals. Artificial intelligence in medicine, 31(1), 73-89.
[19] Hemanth, D. J., Vijila, C. K. S., Selvakumar, A. I., & Anitha, J. (2014). Performance improved iteration-free artificial neural networks for abnormal magnetic resonance brain image classification. Neurocomputing, 130, 98-107.
[20] Ari, A., & Hanbay, D. (2018). Deep learning based brain tumor classification and detection system. Turkish Journal of Electrical Engineering and Computer Sciences, 26(5), 2275-2286.
[21] Ghosal, P., Nandanwar, L., Kanchan, S., Bhadra, A., Chakraborty, J., & Nandi, D. (2019, February). Brain tumor classification using ResNet-101 based squeeze and excitation deep neural network. In 2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP) (pp. 1-6). IEEE.
[22] Ayadi, W., Elhamzi, W., Charfi, I., & Atri, M. (2021). Deep CNN for brain tumor classification. Neural Processing Letters, 53(1), 671-700.
[23] Choudhury, C. L., Mahanty, C., Kumar, R., & Mishra, B. K. (2020, March). Brain tumor detection and classification using convolutional neural network and deep neural network. In 2020 international conference on computer science, engineering and applications (ICCSEA) (pp. 1-4). IEEE.
[24] Abiwinanda, N., Hanif, M., Hesaputra, S. T., Handayani, A., & Mengko, T. R. (2019). Brain tumor classification using convolutional neural network. In World congress on medical physics and biomedical engineering 2018 (pp. 183-189). Springer, Singapore
[25] Kibriya, H., Masood, M., Nawaz, M., Rafique, R., & Rehman, S. (2021, July). Multiclass Brain Tumor Classification Using Convolutional Neural Network and Support Vector Machine. In 2021 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) (pp. 1-4). IEEE.
[26] Agarwal, A. K., Sharma, N., & Jain, M. K. (2021). Brain tumor classification using CNN. Advances and Applications in Mathematical Sciences.
[27] Zhang, Wenlu, Rongjian Li, Houtao Deng, Li Wang, Weili Lin, Shuiwang Ji, and Dinggang Shen. “Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.” NeuroImage 108 (2015): 214-224
[28] Dai, Jifeng, Kaiming He, Yi Li, Shaoqing Ren, and Jian Sun. “Instance-sensitive fully convolutional networks.” In European Conference on Computer Vision, pp. 534-549. Springer, Cham, 2016.
[29] Pereira, Sérgio, Adriano Pinto, Victor Alves, and Carlos A. Silva. “Brain tumor segmentation using convolutional neural networks in MRI images.” IEEE transactions on medical imaging 35, no. 5 (2016): 1240-1251.
[30] Febrianto, D. C., Soesanti, I., & Nugroho, H. A. (2020, March). Convolutional neural network for brain tumor detection. In IOP Conference Series: Materials Science and Engineering (Vol. 771, No. 1, p. 012031). IOP Publishing.
[31] Afshar, P., Mohammadi, A., & Plataniotis, K. N. (2018, October). Brain tumor type classification via capsule networks. In 2018 25th IEEE international conference on image processing (ICIP) (pp. 3129-3133). IEEE.
[32] Farzana Arefin Nazira, Sadah Anjum Shanto, Kamruddin Nur, and M. F. Mridha. 2022. Hemifacial Microsomia Detection Using Convolutional Neural Networks. In Proceedings of the 2nd International Conference on Computing Advancements (ICCA ’22). Association for Computing Machinery, New York, NY, USA, 384–391. https://doi.org/10.1145/3542954.3543009
[33] F. A. Nazira, S. R. Das, S. A. Shanto and M. F. Mridha, “Depression Detection Using Convolutional Neural Networks,” 2021 IEEE International Conference on Signal Processing, Information, Communication & Systems (SPICSCON), 2021, pp. 9-13, doi: 10.1109/SPICSCON54707.2021.9885517.
[34] Alqazzaz, S., Sun, X., Yang, X., & Nokes, L. (2019). Automated brain tumor segmentation on multi-modal MR image using SegNet. Computational Visual Media, 5(2), 209
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Md. Abid Hasan Nayeem, Mehedi Hasan Shakil, Sadia Afrin, Sadah Anjum Shanto, Shadia Jahan Mumu, Md. Mahmudul Hasan Shanto “A Deep Learning Based Classification Model for the Detection of Brain Tumor using MRI” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.37-42 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7904
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Susceptibility and Characterization of Vibrio cholerae Obtained from Aqua-based Samples in Selected Local Government Areas, Zamfara State, Nigeria
Christopher E. Ezeamagu, Cajethan O. Ezeamagu, Mande Garuba and Toyosi F. Osisami- September 2022 Page No.: 43-46
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Vibrio cholerae is causative agent of cholera and its impact has been associated with significant morbidity and mortality in health care institution and community settings globally. Studies have shown that two serotypes are associated with cholera outbreak globally, but an atypical strains with reduced resistance to antibiotics have been implicated in Nigeria. Hence, this study was designed to identify and determine the antibiogram of Vibrio cholerae obtained from water samples in Zamfara State with a view to help in antibiotic surveillance system. Thirty-eight (38) water samples comprising of well water, streams and rivers were randomly selected from nine Local Government Areas in Zamfara State; (Tsafe (3), Zurmi (2), Maradun (1), Talata Mafara (2), Gusau (3), Bungudu (13), Birnin Magaji/Kiyaw (1) and Shinkafi (12). Vibrio cholerae were isolated using TCBS agar by standard microbiological method. The sensitivity of the isolates was determined by disc diffusion method while the isolated was confirmed by polymerase chain reaction (PCR) using cholera toxin gene (ctxA) specific primers. A total of 15 isolates; well (1), rivers (11), streams (3), were obtained from 38 samples collected. The resistance profile of isolates showed that all isolates (100%) were resistant to ceftriaxone, cefixime, and ceftazidime. Also, 8%, 46% and 81% of the isolates were resistance to gentamicin, nitrofurantoin and amoxicillin/clavulanate respectively, but all the isolates were susceptible to ofloxacin with 88% susceptible to both gentamicin and ciprofloxacin. Likewise, 54% of isolates were susceptible to nitrofurantoin while 19% were susceptible to amoxicillin/clavulanate. The results obtained revealed presence of Vibrio cholerae in an environmental reservoir especially in river sources with high profile antibiotic resistance which could pose serious health risk to the community. Hence, antibiotic surveillance system in this region is advised.
Page(s): 43-46 Date of Publication: 17 October 2022
Authors
Christopher E. Ezeamagu
Chemistry Department, Federal College of Education, Technical Gusau, Zamfara State, Nigeria
Cajethan O. Ezeamagu
Department of Microbiology, Babcock University, Nigeria.
Mande Garuba
Chemistry Department, Federal College of Education, Technical Gusau, Zamfara State, Nigeria
Toyosi F. Osisami
Department of Microbiology, Babcock University, Nigeria.
References
[1] Abakpa, G. O., Umoh, V. J., & Ameh, J. B. (2013). Occurrence of Vibrio cholerae in some households engaged in livestock farming in some parts of Zaria, Nigeria. Advances in Microbiology Vol.3 No.1(2013), Article ID:29408,4 pages DOI:10.4236/aim.2013.31020
[2] Ali M, Nelson AR, Lopez AL, Sack D. (2015). PLoS Negl Trop Dis 9(6): e0003832. doi:10.1371/journal.pntd.0003832.
[3] Are, J. 2021 August 04 Cholera kills ’30 people’ in Zamfara. The Cable https://www.thecable.ng/cholera-kills-30-people-inzamfara#.YrnzxUNeKeA.link (accessed online on 24 August, 2022).
[4] Ceccarelli, D., Chen, A., Hasan, N. A., Rashed, S. M., Huq, A., & Colwell, R. R. (2015). Non-O1/non-O139 Vibrio cholerae carrying multiple virulence factors and V. cholerae O1 in the Chesapeake Bay, Maryland. Applied and Environmental Microbiology, 81(6), 1909-1918.
[5] Ceccarelli, D., Amaro, C., Romalde, J., L., Suffredini, E. & Vezzulli, L. (2019). “Vibrio species,” in Food Microbiology: Fundamentals and Frontiers, 5th Edn, eds P. M. Doyle, F. Diez−Gonzalez, and C. Hill (Washington, DC: ASM press), 347–388.
[6] Chijioke, A. N., Samuel, T. K., & Chibuzor, M. N. (2014). Incidence and antibiotic susceptibility pattern of Vibrio species isolated from sea foods sold in Port-Harcourt, Nigeria. African Journal of Bacteriology Research, 6(2), 13-16. doi: 10.1111/1462-2920.15040
[7] Elimian, K. O., Musah, A., Mezue, S., Oyebanji, O., Yennan, S., Jinadu, A., … & Ihekweazu, C. (2019). Descriptive epidemiology of cholera outbreak in Nigeria, January–November, 2018: implications for the global roadmap strategy. BMC Public Health, 19(1), 1-11.
[8] Frans, I., Michiels, C., W., Bossier, P., Willems, K., A., Lievens, B., & Rediers, H. (2011). Vibrio anguillarum as a fish pathogen: Virulence factors, diagnosis and prevention. Journal of Fish Diseases, 34, 643–661. Retrieved from http://dx.doi.org/10.1111/j.13652761.2011.01279.x 10.1111/jfd.2011.34.issue-9
[9] Igbinosa, E. O. (2010). Surveillance of invasive Vibrio species in discharged aqueous effluents of wastewater treatment plants in the Eastern Cape province of South Africa (p. 109, PhD thesis). University of Fort Hare Alice, South Africa.
[10] NCDC 2018. Cholera outbreak in Nigeria. https://reliefweb.int/sites/reliefweb.int/files/resources/An%20update%20of%20Cholera%20outbreak%20in%20Nigeria_210618_25.pdf (Accessed online 16 August, 2018).
[11] Mandal, J., Dinoop, K., P. & Parija, S., C. (2012). Increasing antimicrobial resistance of Vibrio cholerae OI biotype E1 tor strains isolated in a tertiary care centre in India. Journal of Health Population and Nutrition, 30:12 6.
[12] Marin, Michel A., Thompson, Cristiane C., Freitas, Fernanda S., Fonseca, Erica L., Aboderin, A. Oladipo., Zailani, Sambo B., Quartey, Naa Kwarley E., Okeke, Iruka N., Vicente, Ana Carolina P. Cholera Outbreaks in Nigeria Are Associated with Multidrug Resistant Atypical El Tor and Non-O1/NonO139 Vibrio cholera PLOS Neglected Tropical Diseases, 2013;7 (2) e2049.
[13] Mengel M.A., Delrieu I., Heyerdahl L., Gessner B.D. (2014) Cholera Outbreaks in Africa. In: Nair G., Takeda Y. (eds) Cholera Outbreaks. Current Topics in Microbiology and Immunology, vol 379. Springer, Berlin, Heidelberg.
[14] Morita, D., Takahashi, E., Morita, M., Ohnishi, M., Mizuno, T., Miyoshi, S., I., Dutta, D., Ramamurthy, T., Chowdhury, G., Mukhopadhyay, A., K. & Okamoto, K. (2020). Genomic characterization of antibiotic resistance‐encoding genes in clinical isolates of Vibrio cholerae non‐O1/non‐O139 strains from Kolkata, India: generation of novel types of genomic islands containing plural antibiotic resistance genes. Microbiology and Immunology, 64(6), pp.435-444.
[15] Olago D, Marshall M, Wandiga SO, Opondo M, Yanda PZ, Kanalawe R, Githeko AK, Downs T, Opere A, Kavumvuli R, Kirumira E, Ogallo L, Mugambi P, Apindi E, Githui F, Kathuri J, Olaka L, Sigalla R, Nanyunja R, Baguma T, Achola P (2007) Climatic, socio-economic, and health factors affecting human vulnerability to cholera in the Lake Victoria basin, East Africa. Ambio 36(4):350–358
[16] Oramadike, C., & Ogunbanwo, S., T. (2015). Prevalence and antimicrobial susceptibility of Vibrio parahaemolyticus isolated from seafoods in Lagos Lagoon Nigeria. Cogent Food & Agriculture, 1(1), 1041349.
[17] Ramamurthy, T., Nandy, R.K., Mukhopadhyay, A.K., Dutta, S., Mutreja, A., Okamoto, K., Miyoshi, S.I., Nair, G.B. and Ghosh, A., (2020). Virulence regulation and innate host response in the pathogenicity of Vibrio cholerae. Frontiers in cellular and infection microbiology, 10, p.572096.
[18] Uppal, B., Mehra, B., Panda, P. S., & Kumar, S. K. (2017). Changing epidemiology and antimicrobial resistance pattern of Vibrio cholerae isolates at a tertiary care health laboratory in North India (2011–2015). water supply, 4, 6.
[19] Vezzulli, L., Baker-Austin, C., Kirschner, A., Pruzzo, C., & Martinez-Urtaza, J. (2020). Global emergence of environmental non-O1/O139 Vibrio cholerae infections linked with climate change: a neglected research field? Environmental Microbiology. 22, 4342–4355.
[20] WHO 2018. Cholera: http://www.who.int/news-room/fact-sheets/detail/cholera (visited online 16 August, 2018).
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Christopher E. Ezeamagu, Cajethan O. Ezeamagu, Mande Garuba and Toyosi F. Osisami “Susceptibility and Characterization of Vibrio cholerae Obtained from Aqua-based Samples in Selected Local Government Areas, Zamfara State, Nigeria” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.43-46 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/43-46.pdf
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A Similarity Solutions Approach to Forced Convection via a Porous Medium Attached to Flat Plate
Augustine Akuoko Kwarteng, Jose Corona, John Kizito- September 2022 Page No.: 47-58
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In the present study, a porous medium adjoining a heated flat plate was modelled by a similarity approach to determine the effect of porosity on the heat transfer phenomena. The momentum and energy equations for porous media transport were transformed using an appropriately determined similarity parameter. The solutions to the momentum equations proved to depend only on the porosity and not the material used. The energy equation however was additionally dependent on the combinations of fluid type and metal matrix used and was solved for four combinations; water/aluminum, air/aluminum, air/copper and SAE 20W-50/stainless. The results show that replacing the clear fluid control volume with a porous matrix altered both the velocity profiles and temperature distribution profiles at all Reynolds numbers. As the porosity of the medium decreased, it resulted in an increase in interfacial area as well as thermal diffusion in the direction normal to the plate, both of which was seen to enhance the heat transfer coefficients. Decreasing porosity also resulted in an increase in thermal storage as well a reduction in volume flow rate going through the medium, which on the other hand tend to inhibit convection. Thus, changing the porosity triggered effects on the heat transfer coefficient. This opposing trend favored convection at porosity greater than 0.5 for low Prandtl number fluids. The clear fluid condition has the lowest heat transfer coefficient and the values increased steeply as porosity changed from 0.99 through 0.7. The heat convection curve reached its maximum turning point at a porosity of 0.5 and then reversed in trend. The dimensionless heat transfer coefficient was found to fit the equation hLL/ReL0.5kfPrf=aebPrmc ( a= 0.51966;b=0.54683;c=-0.665349) . Using Stanton number representation, the relation is StReL>1/2=1/3 aebPrmc , which portrays in relative terms how the convection enhancement and the opposing thermal storage effects vary with porosity. This study concluded that implementing a porous structure in a medium is feasible for enhancing heat transfer performance.
Page(s): 47-58 Date of Publication: 25 September 2022
DOI : 10.51584/IJRIAS.2022.7905Authors
Augustine Akuoko Kwarteng
Department of Mechanical Engineering, University of Mines and Technology, P.O. Box 237, Tarkwa, Ghana
Department of Mechanical Engineering, North Carolina A&T State University, 1601 East Market St, Greensboro, NC 27411, U.S.A
Jose Corona
Department of Mechanical Engineering, North Carolina A&T State University, 1601 East Market St, Greensboro, NC 27411, U.S.A
John Kizito
Department of Mechanical Engineering, North Carolina A&T State University, 1601 East Market St, Greensboro, NC 27411, U.S.A
References
Alazmi, B. and K. Vafai, Analysis of Variants Within the Porous Media Transport Models. Journal of Heat Transfer, 1999. 122(2): p. 303-326.
[2] Yen, S.C.P., Y.L.; San, K.C., Design of a Porous Bluff-Body Disc on Improving the Gas-Mixing Efficiency. Proceedings of the World Congress on Engineering, 2017. II(WCE 2017): p. 1003-1007.
[3] Anirudh, K. and S. Dhinakaran, Effects of Prandtl number on the forced convection heat transfer from a porous square cylinder. International Journal of Heat and Mass Transfer, 2018. 126: p. 1358-1375.
[4] Abbas, M.N., Modeling Of Porosity Equation For Water Flow Through Packed Bed Of Monosize Spherical Packing. Journal Of Engineering And Development, 2011. 15(4): p. 205-226.
[5] Goldstein, R.J., et al., Heat transfer—A review of 2005 literature. International Journal of Heat and Mass Transfer, 2010. 53(21): p. 4397-4447.
[6] Goldstein, R.J., et al., Heat transfer—A review of 2004 literature. International Journal of Heat and Mass Transfer, 2010. 53(21): p. 4343-4396.
[7] Mahjoob, S. and K. Vafai, A synthesis of fluid and thermal transport models for metal foam heat exchangers. International Journal of Heat and Mass Transfer, 2008. 51(15): p. 3701-3711.
[8] Dukhan, N., et al., One-dimensional heat transfer analysis in open-cell 10-ppi metal foam. International Journal of Heat and Mass Transfer, 2005. 48(25): p. 5112-5120.
[9] Giani, L., G. Groppi, and E. Tronconi, Heat Transfer Characterization of Metallic Foams. Industrial & Engineering Chemistry Research, 2005. 44(24): p. 9078-9085.
[10] Yang, X.H., et al., A simplistic analytical unit cell based model for the effective thermal conductivity of high porosity open-cell metal foams. Journal of Physics D: Applied Physics, 2013. 46(25): p. 255302.
[11] Jeng, T.-M., L.-K. Liu, and Y.-H. Hung, A Novel Semi-empirical Model for Evaluating Thermal Performance of Porous Metallic Foam Heat Sinks. Journal of Electronic Packaging, 2004. 127(3): p. 223-234.
[12] Karimi, N., Y. Mahmoudi, and K. Mazaheri, Temperature fields in a channel partially filled with a porous material under local thermal non-equilibrium condition – An exact solution. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2014. 228(15): p. 2778-2789.
[13] Vafai, K. and R. Thiyagaraja, Analysis of flow and heat transfer at the interface region of a porous medium. International Journal of Heat and Mass Transfer, 1987. 30(7): p. 1391-1405.
[14] Nakayama, A.P., I, Momentum and heat transfer over a continuous moving surface in a non-Darcian fluid. Wärme – und Stoffübertragung, 1993. 28(4): p. 177-184.
[15] Das, M.K., P.P. Mukherjee, and K. Muralidhar, Equations Governing Flow and Transport in Porous Media, in Modeling Transport Phenomena in Porous Media with Applications, M.K. Das, P.P. Mukherjee, and K. Muralidhar, Editors. 2018, Springer International Publishing: Cham. p. 15-63.
[16] Huang, H. and J.A. Ayoub, Applicability of the Forchheimer Equation for Non-Darcy Flow in Porous Media, in SPE Annual Technical Conference and Exhibition. 2006, Society of Petroleum Engineers: San Antonio, Texas, USA. p. 14.
[17] White, F.M., Viscous Fluid Flow. 2006, India: McGraw Hill. 629.
[18] Toolbox, E. Air – Prandtl Number 2018 [cited 2019 5/11/2019]; Available from: https://www.engineeringtoolbox.com/air-prandtl-number-viscosity-heat-capacity-thermal-conductivity-d_2009.html.
[19] Thermophysical Properties: Engine Oil. 2011 11/13/2011 [cited 2019 5/22/2019]; Available from: https://www.thermalfluidscentral.org/encyclopedia/index.php/Thermophysical_Properties:_Engine_Oil,_Unused.
[20] Kwarteng, A. A., 2019. A Similarity Solutions Approach to Forced Convection Heat Transfer Enhancement by Using Porous Media. PhD Thesis, Greensboro: North Carolina Agricultural and Technical State University, 124.
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Augustine Akuoko Kwarteng, Jose Corona, John Kizito “A Similarity Solutions Approach to Forced Convection via a Porous Medium Attached to Flat Plate” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.47-58 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7905
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Photocatalytic Degradation of Phenol in Wastewater: A Mini Review
Lawal, A.I., Muhammad, Z., Obunadike, C.V., Yakubu, Y.Y., Ogunsanmi, A.O., Abdulrazak, O.O., Ayodele, C.O. and Komolafe, F.E.- September 2022 Page No.: 59-64
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A major public health concern in many developing countries, including Nigeria, is the quality of their water supply. Everything a live entity does depends on water, a fundamental component of the biosphere. To ensure that water is safe for industrial and home use, it must be treated before consumption. However, phenolic compounds are found in our water bodies due to the polluted wastewater from industrial, agricultural, and home activities. Nature also has a role in their occurrence. These substances are poisonous and can cause long-term harm to both humans and animals. This paper reviewed research on the photodegradation of phenol utilizing nanoparticles in water treatment. This provides additional information and facts on cost-effective methods of treating wastewater and mineralizing phenol into valuable chemicals.
Page(s): 59-64 Date of Publication: 20 October 2022
DOI : 10.51584/IJRIAS.2022.7906Authors
Lawal, A.I.
Kaduna State University, Nigeria
Muhammad, Z.
Kaduna State University, Nigeria
Obunadike, C.V.
Osun State University, Nigeria
Yakubu, Y.Y.
Kwame Nkrumah University of Science and Technology, Kumasi- Ghana
Ogunsanmi, A.O.
Kwara State University, Nigeria
Abdulrazak, O.O.
Osun State University, Nigeria
Ayodele, C.O.
Federal University of Agriculture, Abeokuta, Nigeria
Komolafe, F.E.
Federal University of Technology, Akure, Nigeria
References
[1] Crittenden, J. C., Lıu, J., Hand, D. W. and Perram, D. L.: 1997, ‘Photocatalytic oxidation of chlorinated hydrocarbons in water’, Wat. Res. 31, 429–438.
[2] Matthews, R. W.: 1991, ‘Photo oxidative degradation of coloured organics in water using supported catalysts TiO2 on sand’, Wat. Res. 25, 1169–1176.
[3] D’Oliveira,J.-C., Al-Sayyed, G. and Pichat, P.: 1990, ‘Photodegradation of 2- and 3-chlorophenol in TiO2 aqueous suspension’, Environ.Sci. Technol. 24, 990–996.
[4] Winterbottom, J. M., Khan, Z., Boyes, A. P. and Raymahasay, S.: 1997, ‘Photocatalyzed oxidation of phenol in water using a concurrent down flow contactor reactor’, Environ. Progress 16, 125–131.
[5] Lakshmi, S., Renganathan, R. and Fujita, S.: 1995, ‘Study on TiO2-mediated photocatalytic degradation of methylene blue’, J. Photochem. Photobiol. 88, 163–167.
[6] Agency for Toxic Substances and Disease Registry (ATSDR). 2008. ToxicologicalProfile for Phenol. Atlanta, GA: U.S. Department of Health and Human Services, PublicHealth Service.
[7] Agency for Toxic Substances and Disease Registry (ATSDR). Toxicological Profile for Phenol (Update). Public Health Service, U.S. Department of Health and Human Services, Atlanta, GA. 1998.
[8] R. Saravanan, Francisco Gracia and A. Stephen Basic Principles, Mechanism, and Challenges of Photocatalysis.
[9] Rajeshwar K, Osugi ME, Chanmanee W, Chenthamarakshan CR, Zanoni M, Kajitvichyanukul P, Krishnan-Ayer R (2008) Heterogeneous photocatalytic treatment of organic dyes in air and aqueous media. J Photochem Photobiol C 9(4):171–192
[10] Rehman S, Ullah R, Butt AM, Gohar ND (2009) Strategies of making TiO2 and ZnO visible light active. J Hazard Mater 170(2–3):560–569
[11] Fujishima A, Rao TN, Tryk DA (2000) Titanium dioxide photocatalysis. J Photochem Photobiol C1(1):1–21
[12] Fujishima A, Honda K (1972) Electrochemical photolysis of water at a semiconductor electrode. Nature 238(5358):37–38
[13] Khan MM, Adil SF, Al-Mayouf A (2015b) Metal oxides as photocatalysts. J Saudi Chem Soc 19(5):462–464
[14] Konstantinou IK, Albanis TA (2004) TiO2-assisted photocatalytic degradation of azo dyes in aqueous solution: kinetic and mechanistic investigations. Appl Catal B 49(1):1–14
[15] Nakata K, Fujishima A (2012) TiO2 photocatalysis: design and applications. J Photochem Photobiol C 13(3):169–189
[16] Hagen J (2006) Industrial catalysis: a practical approach/Jens Hagen, 2nd edn. Wiley, Weinheim
[17] F. F. Runge, Ann. Phys. Chem., 31, 65 (1834); F. F. Runge, Ann. Phys. Chem., 32, 308 (1834); C. F. v. Reichenbach, Ann. Phys. Chem., 32, 497 (1834).
[18] Central pollution control board. (ministry of environment, forests & climate change). parivesh bhawan, east arjun nagar, delhi – 110032, website: www.cpcb.nic.in. August, 2016. Compiled by Dr. Yogita Kharayat, Scientist ‘B’; Sh. V. K. Verma, SSA; Sh. Bhupander Kumar, Scientist `C’ and Dr. C. S. Sharma, Scientist `E’.
[19] Fleeger, J.W., K.R. Carman and R.M. Nisbet, 2003. Indirect effect of contaminants in aquatic ecosystem. Science Total Environments, 3170: 207-233.
[20] Kumar, A., Kumar, S., and Kumar, S. (2005). Biodegradation kinetics of phenol and catechol using Pseudomonas putida MTCC 1194. Biochem. Eng. J. 22, 151–159.
[21] Edalat Manesh, M., Mehrvar, M., and Dhib, R. (2008). Optimization of phenol degradation in a combined photochemical–biological wastewater treatment system. Chem. Eng. Res. Des. 86, 1243–1252.
[22] Nuhoglu, A., and Yalcin, B. (2005). Modelling of phenol removal in a batch reactor. Process Biochem. 40, 1233–1239.
[23] Yan, J., Jianping, W., Jing, B., Daoquan, W., and Zongding, H. (2006). Phenol biodegradation by the yeast Candida tropicalis in the presence of m-cresol. Biochem. Eng. J. 29, 227–234.
[24] Al Zarooni, M., and Elshorbagy, W. (2006). Characterization and assessment of Al Ruwais refinery wastewater. J. Hazard. Mater. A136, 398–405.
[25] Liu, Y. J., Zhang, A. N., and Wang, X. C. (2009). Biodegradation of phenol by using free and immobilized cells of Acinetobacter sp. XA05 and Sphingomonas sp. FG03. Biochem. Eng. J. 44, 187–192.
[26] El-Naas, M., Al-Zuhair, S., and Makhlouf, S. (2010). Batch degradation of phenol in a spouted bed bioreactor system. J. Ind. Eng. Chem. 16, 267–272.
[27] Shourian, M., Noghabi, K. A., Zahiri, H. S., Bagheri, T., Karballaei, G., Mollaei, M., Rad, I., Ahadi, S., Raheb, J., and Abbasi, H. (2009). Efficient phenol degradation by a newly characterized Pseudomonas sp. SA01 isolated from pharmaceutical wastewaters. Desalination; 246, 577–594.
[28] Agarry, S. E., Durojaiye, A. O., and Solomon, B. O. (2008). Microbial degradation of phenols: A review. Int. J. Environ. Pollut. 32, 12–28.
[29] Nair, C. I., Jayachandran, K., and Shashidhar, S. (2008). Biodegradation of phenol. Afr. J. Biotechnol. 7, 4951–4958. https://education.Jlab.org/itselemental/ele028.html.
[30] https://www.fhwa.dot.gov/pavcmcnt/rccmicro.html,“Microsilica-Utilization of Recycled Materials in Illinois Highway construction”
[31] Yilleng, M. T. (2014). Photocatalysis activity of metal
[32] Santos, A., Yustos, P., Durban, B., Garcia-Ochoa, F., 2001. Oxidation of phenol in aqueous solution with copper catalysts. Catal. Today 66, 511-517.
[33] Kulkarni, U.S., Dixit, S.G., 1991. Destruction of phenol from wastewater by oxidation with sulfite-oxygen. Ind. Eng. Chem. Res. 30, 1916-1920.
[34] Brezová, V., Blazžková, A., Borošová, E., Čeppan, M., Fiala, R., 1995. The influence of dissolved metal ions on the photocatalytic degradation of phenol in aqueous TiO2 suspensions. J. Mol. Catal. A-Chem. 98, 109-116.
[35] T. Teka, A. Reda, Int. J. Technol. Enhance. Emerg. Eng. Res. 2, 2347 (2014)
[36] H. Eskandarloo, A. Badiei, C. Haug, Mater. Sci. Semicond. Process. 27, 240 (2014)
[37] I. Prabha, S. Lathasree, Mater. Sci. Semicond. Process. 26, 603 (2014)
[38] P. Navarro, J. Sarasa, D. Sierra, S. Esteban, I.L. Obelleiro, Water Sci. Technol. 51, 113 (2005)
[39] M.N. Chong, B. Jin, C.W.K. Chow, C. Saint, Water Res. 44, 2997 (2010)
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Lawal, A.I., Muhammad, Z., Obunadike, C.V., Yakubu, Y.Y., Ogunsanmi, A.O., Abdulrazak, O.O., Ayodele, C.O. and Komolafe, F.E. “Photocatalytic Degradation of Phenol in Wastewater: A Mini Review” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.59-64 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7906
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Capital Structure and Firm Performance: Evidence From 2021 Best-Performed Stocks in Nigeria
Shedrack Enyeribe Nwannunu- September 2022 Page No.: 65-75
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The researcher used an eight-firm sample drawn randomly from a population of ten to study the relationship between capital structure and stock performance of the companies that traded the best-performing stocks on the Nigerian stock exchange in 2021. The study used a four-year panel data collection (2018–2021). For hypothesis testing, the study used EXCEL-generated research statistics and the least-squares dummy variables (LSDV) regression in SPSS. The findings show a statistically significant positive correlation between corporate capital structure and stock performance (ROA and R.O.E.). The study recommended employing larger samples of the best-performing equities over two or more years.
Page(s): 65-75 Date of Publication: 25 October 2022
DOI : 10.51584/IJRIAS.2022.7907Authors
Shedrack Enyeribe Nwannunu
Department of Accountancy, Abdu Gusau Polytechnic, Nigeria
References
[1] Aamir, E., Khan, A., & Abubakar Tariq, M. (2022). The Influence of Teleconnections on the Precipitation in Baluchistan. Atmosphere, 13(7), 1001. https://doi.org/10.3390/atmos13071001
[2] Abdullah, H., & Tursoy, T. (2021). Munich Personal RePEc Archive Capital structure and firm performance : a panel causality test Abdullah, Harlem and Troy, Turgut. MPRA Paper No. 105871. She posted 08 Feb 2021 11:09 UTC, February 1–9.
[3] Abughniem, M. S., Al Aishat, M. A. H., Hamdan, A., & Weshah, S. R. (2020). Capital structure, firm growth and firm performance: Evidence from Jordan. International Journal of Innovation, Creativity and Change, 10(12), 655–667.
[4] Akinyomi, O. J., & Olagunju, A. (2013). Determinants of Capital Structure in Nigeria. 3(4), 999–1005.
[5] Akoglu, H. (2018). Turkish Journal of Emergency Medicine User’s s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(August), pp. 91–93.
[6] Alita, D., Putra, A. D., & Darwis, D. (2021). Analysis of classic assumption test and multiple linear regression coefficient tests for employee structural office recommendation. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15(3), 295. https://doi.org/10.22146/ijccs.65586
[7] Al-Quraan, A., Al-Masri, H., Al-Mahmodi, M., & Radaideh, A. (2022). Power curve modelling of wind turbines- A comparison study. I.E.T. Renewable Power Generation, 16(2), 362–374. https://doi.org/10.1049/rpg2.12329
[8] Alrabba, H. M., Ahmad, M. A., & Hamadneh, M. (2019). Evidence from Jordanian publicly traded companies International Journal of Scientific and Technology Research,8(10), 364-375,
[9] Altahtamouni, F., Alfayhani, A., Qazaq, A., Alkhalifah, A., Masfer, H., Almutawa, R., & Alyousef, S. (2022). Sustainable Growth Rate and ROE Analysis: An Applied Study on Saudi Banks Using the PRAT Model. Economies, 10(3). https://doi.org/10.3390/economies10030070
[10] Appiah, G. K., & Xiao, L. lan (2020). Examining Cal Bank, Ecobank GH Ltd, Ghana Commercial Bank (G.C.B. ), and Standard Chartered Bank (S.C.B.) as listed financial institutions in Ghana, focusing on risk and return. Open Science Journal 5(1), pp. 1-17.https://doi.org/10.23954/osj.v5i1.2167
[11] Benyadi, F. C., Hajanirina, A., & Reyes, M. A. (2022). The Jakarta Stock Exchange dividend policy listed manufacturing companies and the underlying factors. JAAF (Journal of Applied Accounting and Finance), 6(1), 61. https://doi.org/10.33021/jaaf.v6i1.3615
[12] Bingilar Paymaster F. and Angbari Ebi O. (2021). Performance of Firms’ Capital Structures Based on Evidence from the Consumer Goods Sectors An Evidential Study of Capital Structure and Firm Performance. Journal of Humanities and Social Science, 26(8), 39–43 (IOSR-JHSS). https://doi.org/10.9790/0837-2608063843
[13] Brahma, S., Nwafor, C., & Boateng, A. (2021). Board gender diversity and firm performance: the British proof. 26(4), 5704-5719, International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2089
[14] Cai, J., & Kwan, M. P. (2022). Detecting spatial flow outliers in the presence of spatial autocorrelation. Computers, Environment and Urban Systems, 96(2), 1–14. https://doi.org/10.1016/j.compenvurbsys.2022.101833
[15] Cañibano, A., & Avgoustaki, A. (2022). To telework or not to telework: Does the macro context matter? A signalling theory analysis of employee interpretations of telework in times of turbulence. Human Resource Management Journal, April 1–17. https://doi.org/10.1111/1748-8583.12457
[16] Dehuan, J., & Jin, Z. (2008). Firm Performance and Stock Returns: An Empirical Study of the Top Performing Stocks Listed on Shanghai Stock Exchange. Academy of Accounting and Financial Studies Journal, 12(1), 79.
[17] Dhan Raj Chalise, N. R. A. (2022). The Impact of Capital Structure and Firm Size on Financial Performance of Commercial Banks in Nepal.pdf. Journal of Planning Education and Research, 4(1), 102–111.
[18] Doorasamyticle, M. (2021). Capital structure, firm value and managerial ownership : Evidence from East African countries. 18(1), 2021–2028. https://doi.org/10.21511/imfi.18(1).2021.28
[19] Durrah, O., Aziz, A., Rahman, A., Jamil, S. A., & Ghafeer, N. A. (2016). Exploring the Relationship between Liquidity Ratios and Indicators of Financial Performance : An Analytical Study on Food Industrial Companies Listed in Amman Bursa. 6(2), 435–441.
[20] Ebi, B. P. F. and A. (2021). Capital Structure and Firms Performance : An Evidential Analysis of Consumer Goods Sectors Capital Structure and Firms Performance : An Evidential. Journal of Humanities And Social Science, 26(8), 38–43. https://doi.org/10.9790/0837-2608063843
[21] Fatmasari, S., ;Ghozali, I., Fuad, F., Almasyhari, A. K., & Nurcahyono, N. (2021). Factors Affecting the Stock Price: The Role of Firm Performance. Journal of Asian Finance, Economics and Business, 8(2), 165–173. https://doi.org/10.13106/jafeb.2021.vol8.no2.0165
[22] Guest, D. E., Oliveira, T., Sanders, K., & Rodrigues, R. (2020). A conceptual analysis and empirical exploration. February 2019. https://doi.org/10.1111/1748-8583.12326
[23] Hung, D. Van, Nhung, L. T., & Hung, N. T. (2021). The Impact of Capital Structure on Firm Value in Vietnam. Advances and Applications in Statistics, 8(5), 287–292. https://doi.org/10.17654/as069020115
[24] Husnadi, T. C., Marianti, T., & Ramadhan, T. (2022). Determination of shareholders’ welfare with financing quality as a moderating variable. APTISI Transactions on Management (A.T.M.), 6(2), 191–208. https://doi.org/10.33050/atm.v6i2.1799
[25] Ibrahim, U. A. (2020). Effect of Financial Leverage on Firm Value: Evidence From Selected Firms Quoted on the Nigerian Stock Exchange. European Journal of Business and Management, 124–135. https://doi.org/10.7176/ejbm/12-3-16
[26] Islam, Z., & Iqbal, M. M. (2022). New Evidence from Pakistan on the Association Between Capital Structure and Firm Performance, 9(2), 81–92. https://doi.org/10.13106/jafeb.2022.vol9.no2.0081
[27] Jasim, S. H. (2017). Using The Multiple Regression Model for the Relationship Between Effective Variables In Diabetes. Journal of the College of Basic Education, 23(99/), pp. 35–42.
[28] Javed, T., Younas, W., & Imran, M. (2014). Impact of Capital Structure on Firm Performance: Evidence from Pakistani Firms. International Journal of Academic Research in Economics and Management Sciences, 3(5). https://doi.org/10.6007/ijarems/v3-i5/1141
[29] Jee, K. F., Ngui, J. E. J., Poh, P. P. J., Chan, W. L., & Wong, Y. S. (2021). Capital Structure and Firm Performance: Evidence from Malaysian Public Listed Plantation Companies. UNIMAS Review of Accounting and Finance, 5(1), 123–142. https://doi.org/10.33736/uraf.3536.2021
[30] Khadijah, N., Azhari, M., Mahmud, R., Naquia, S., & Shaharuddin, H. (2022). Capital Structure of Malaysian Companies: Are They Different During the COVID-19 Pandemic ?*. Journal of Asian Finance, Economics and Business, 9(4), 239–250. https://doi.org/10.13106/jafeb.2022.vol9.no4.0239
[31] Kim, H. (2013). Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restorative Dentistry & Endodontics, 38(1), 52. https://doi.org/10.5395/rde.2013.38.1.52
[32] Larsson, J. P., & Thulin, P. (2019). Independent by necessity? The life satisfaction of necessity and opportunity entrepreneurs in 70 countries. Small Business Economics, 53(4), 921–934. https://doi.org/10.1007/s11187-018-0110-9
[33] Lee, C., Wu, W., & Yang, C. (2019). Employees’ Perceptions of Training and Sustainability of Human Resources. 1–11.
[34] Lee, S. W. (2022). Regression analysis for continuous independent variables in medical research: statistical standard and guideline of Life Cycle Committee. Life Cycle, pp. 2, 1–8. https://doi.org/10.54724/lc.2022.e3
[35] Li, K., Niskanen, J., & Niskanen, M. (2019). Capital structure and firm performance in European S.M.E.s: Does credit risk make a difference? Managerial Finance, 45(5), 582–601. https://doi.org/10.1108/MF-01-2017-0018
[36] Li, L., Yang, L., Zhao, M., Liao, M., & Cao, Y. (2022). Exploring the success determinants of crowdfunding for cultural and creative projects: An empirical study based on signal theory. Technology in Society, 70(August), pp. 1–5. https://doi.org/10.1016/j.techsoc.2022.102036
[37] Lone, M. A. (2022). Rainfall-runoff modelling using MIKE 11 N.A.M. of the Jhelum river in Kashmir Valley, India. 2(551), 365–372.
[38] Maizan, S., Manaf, A., Husna, N., & Ahmad, A. (2021). Determinants of Profitability on Listed Telecommunications Service Providers Companies : Evidence in Bursa Malaysia. 9(1), 22–28.
[39] Mentzer, J. T. (2008). Rigour versus relevance: Why would we choose only one? Journal of Supply Chain Management, 44(2), 72–77. https://doi.org/10.1111/j.1745-493X.2008.00058.x
[40] Moratis, L. (2018). Signalling responsibility? Applying signalling theory to the ISO 26000 standard for social responsibility. Sustainability (Switzerland), 10(11), 1–20. https://doi.org/10.3390/su10114172
[41] Musa;, A. B. B. . M. . B.-A. (2021). IMPACT OF NON-FINANCIAL FIRMS CAPITAL STRUCTURE ON FIRM-VALUE PERFORMANCE IN DEVELOPING AFRICA STRUCTURE ON FIRM-VALUE. International Journal of Management, 12(1), 1483–1491. https://doi.org/10.34218/IJM.12.1.2021.130
[42] Mushafiq, M., Sindhu, M. I., & Sohail, M. K. (2021). Financial performance under the influence of credit risk in non-financial firms: evidence from Pakistan. Journal of Economic and Administrative Sciences, pp. 1–9. https://doi.org/10.1108/jeas-02-2021-0018
[43] Muslim, A. H. and M. (2022). View of Several Factors Affecting Firm Value Manufacturing In Indonesia.pdf. Jurnal Akuntansi, XXVI(01), 127–143.
[44] Nugroho, M. (2021). Corporate governance and firm performance. Accounting, 7(1), 13–22. https://doi.org/10.5267/j.ac.2020.10.019
[45] Nyagadza, B., Kadembo, E. M., & Makasi, A. (2021). When corporate brands tell stories: A signalling theory perspective. Cogent Psychology, 8(1), 1–134. https://doi.org/10.1080/23311908.2021.1897063
[46] Pandey, I. M. (2002). CAPITAL STRUCTURE AND MARKET POWER INTERACTION: EVIDENCE FROM MALAYSIA. The Capital Market Review, 10(23–40), 1–26.
[47] Petter, S., Delone, W., & McLean, E. R. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29(4), 7–62. https://doi.org/10.2753/MIS0742-1222290401
[48] Pucheta-Martínez, M. C., Bel-Oms, I., & Rodrigues, L. L. (2020). Does stakeholder engagement encourage environmental reporting? The mediating role of firm performance. Business Strategy and the Environment, 29(8), 3025–3037. https://doi.org/10.1002/bse.2555
[49] Putro, D. C., & Risman, A. (2021). the Effect of Capital Structure and Liquidity on Firm Value Mediated By Profitability. The Europeans: Journal on Global Socio-Economic Dynamics, 24(2(27)), 26–34. https://doi.org/10.35678/2539-5645.2(27).2021.26-34
[50] Roberta , O Gough, Gülnur M, S, S. (2013). How Does a Firm’s Capital Structure Affect Stock Performance ? Roberta Adami. Frontiers in Finance and Economics, 12(1), 1–31.
[51] Rutkowska-Ziarko, A. (2022). Market and Accounting Measures of Risk: The Case of the Frankfurt Stock Exchange. Risks, 10(1). https://doi.org/10.3390/risks10010014
[52] Sachin, N., & Rajesh, R. (2022). An empirical study of supply chain sustainability with financial performances of Indian firms. Environment, Development and Sustainability, 24(5), 6577–6601. https://doi.org/10.1007/s10668-021-01717-1
[53] Schjoedt, L., & Sangboon, K. (2015). Control Variables: Problematic Issues and Best Practices. The Palgrave Handbook of Research Design in Business and Management, 239–261. https://doi.org/10.1007/978-1-137-48495-6_15
[54] Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation Coefficients: Appropriate Use and Interpretation. XXX(Xxx), 1–6. https://doi.org/10.1213/ANE.0000000000002864
[55] Senthilnathan, S. (2019). The usefulness of Correlation Analysis. SSRN Electronic Journal, July. https://doi.org/10.2139/ssrn.3416918
[56] Sheng, Y., & Li, Z. (2022). Detecting the Influencing Factors of Maize Production in China during 2009-2019. 648(Icfied), 2428–2432.
[57] Singh, A., & Vishwakarma, G. K. (2019). Improved predictive estimation for mean using the Searls technique under ranked set sampling. Communications in Statistics – Theory and Methods, 50(9), 2015–2038. https://doi.org/10.1080/03610926.2019.1657456
[58] Sodanin, K., Niwitpong, S., & Niwitpong, S. (2022). Estimating Simultaneous Confidence Intervals for Multiple Contrasts of Means of Normal Distribution with Known Coefficients of Variation. 6(4), 705–716.
[59] Suhaily, Manaf, A., Athirah, N. H., Kamshor, A., & Salleh, W. A. (2021). Determinants of Profitability on Listed Telecommunications Service Providers Companies: Evidence in Bursa Malaysia. Journal of Research in Business and Management, 9(1), pp. 2347-3002.
[60] Sukesti, F., Ghozali, I., Fuad, F., Almasyhari, A. K., & Nurcahyono, N. (2021). Factors Affecting the Stock Price: The Role of Firm Performance. Journal of Asian Finance, Economics and Business, 8(2), 165–173. https://doi.org/10.13106/jafeb.2021.vol8.no2.0165
[61] Thomas, E, P. (1994). Sacred Cows and Workhorses: The sale of Accounts and Chattel Paper under the U.C.C. and the Effects of Violating a Fundamental Draft Principle. 26(2), 397–520.
[62] Tiep, T., & Ikram, M. (2022). Do sustainability innovation and firm competitiveness help improve firm performance ? Evidence from the S.M.E. sector in Vietnam. 29, 588–599.
[63] Toader, D. A., Vintila, G., & Gherghina, S. C. (2022). Firm- and Country-Level Drivers of Capital Structure: Quantitative Evidence from Central and Eastern European Listed Companies. 2022. https://doi.org/10.5171/2022.572694
[64] Ullah, A., Pinglu, C., Ullah, S., Zaman, M., & Hashmi, S. H. (2020). The nexus between capital structure, firm-specific factors, macroeconomic factors and financial performance in the textile sector of Pakistan. Heliyon, 6(8), e04741. https://doi.org/10.1016/j.heliyon.2020.e04741
[65] Vo, Q. T. (2019). Export performance and stock return: A case of fishery firms listing in Vietnam Stock markets. Journal of Asian Finance, Economics and Business, 6(4), 37–43. https://doi.org/10.13106/jafeb.2019.vol6.no4.37
[66] Wikandari, Y. D. (2022). THE INFLUENCE OF LEARNING STYLES ON STUDENTS READING ACHIEVEMENT AT SMP QURAN AN NAWAWY MOJOKERTO IN THE ACADEMIC YEAR OF 2020 / 2021. 5(01), 45–51.
[67] Xu, J., Haris, M., & Irfan, M. (2022). The Impact of Intellectual Capital on Bank Profitability during COVID-19: A Comparison with China and Pakistan. Hindawi Complexity, 2022(March 2020), pp. 1–10. https://doi.org/10.1155/2022/2112519
[68] Zhang, G., Pan, Y., & Zhang, L. (2022). Automation in Construction Deep learning for detecting building façade elements from images considering prior knowledge. Automation in Construction, 133(October 2021), 104016. https://doi.org/10.1016/j.autcon.2021.104016
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Shedrack Enyeribe Nwannunu “Capital Structure and Firm Performance: Evidence From 2021 Best-Performed Stocks in Nigeria” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.65-75 September 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7907
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Computer Simulation of Airflow Distribution in a Heat Pump Dryer
Kavindi M. A. R., Amaratunga K.S.P., Ekanayake E.M.A.C- September 2022 Page No.: 76-82
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Computer simulation is an effective technique for better understanding the physical phenomena of drying. Understanding and predicting the drying behavior before applying the material would increase the dryer efficiency by properly designing existing heat pump dryer systems. This study was done to simulate the airflow in a heat pump dryer chamber using Computational Fluid Dynamics (CFD). COMSOL Multiphysics software v5.4 has been used for simulation. Air velocity, temperature, and relative humidity distribution profile were achieved by solving the Naiver stoke fluid equation, Heat transfer equation, and Transport of diluted species equation (Fick’s law). The simulated data for nine different locations were verified using experimental results. The relative error and mean relative deviation for temperature profile were less than ±1.8% and 7.8%. It was recorded less than ±2.8% and 10.6% values for the relative error and mean relative deviation for relative humidity profiles. Therefore, this would be a suitable prediction method to understand the airflow pattern and conditions inside a chamber
Page(s): 76-82 Date of Publication: 25 October 2022
Authors
Kavindi M. A. R.
Department of Agricultural Engineering, Faculty of Agriculture, University of Peradeniya, Sri Lanka.
Amaratunga K.S.P.
Department of Agricultural Engineering, Faculty of Agriculture, University of Peradeniya, Sri Lanka.
Ekanayake E.M.A.C
Postgraduate Institute of Agriculture, University of Peradeniya, Sri Lanka.
References
[1] Dimitriadis, A. N., & Akritidis, C. B. (2004). A model to simulate chopped alfalfa drying in a fixed deep bed. Drying Technol., 22(3), 479-490. https://doi.org/10.1081/DRT-120029994
[2] ElGamal, R. A., Kishk, S. S., & ElMasry, G. M. (2017). Validation of CFD models for the deep bed drying of rice using thermal imaging. Biosyst. Eng., 161, 135-144. https://doi.org/10.1016/j.biosystemseng.2017.06.018
[3] ElGamal, R., Ronsse, F., & Pieters, J. (2013). Modeling deep-bed grain drying using Comsol Multiphysics. Proc. COMSOL Conf.
[4] Ficarella, A., Perago, A., Starace, G., & Laforgia, D. (2003). Thermo-fluid-dynamic investigation of a dryer, using numerical and experimental approach. Journal of food engineering, 59(4), 413-420.https://doi.org/10.1016/S0260-8774(02)00500-9
[5] Getahun, E., Vanierschot, M., Gabbiye, N., Delele, M. A., Workneh, S., & Gebrehiwot, M. (2019). Computational fluid dynamic modeling and simulation of red chili solar cabinet dryer. Proc. 4th Int. Conf. on Advancements of Science and Technology. https://doi.org/10.1007/978-3-030-43690-2_45.
[6] Ghiaus, A. G., & Gavriliuc, R. (2007). Simulation of air flow and dehydration process in tray drying systems. UPB Sci. Bull. (69), 41-50.
[7] Goh, L. J., Othman, M. Y., Mat, S., Ruslan, H., & Sopian, K. (2011). Review of heat pump systems for drying application. Renewable and Sustainable Energy Reviews, 15(9), 4788-4796. https://doi.org/10.1016/j.rser.2011.07.072.
[8] Harchegani, M. T., Moheb, A., Sadeghi, M., Tohidi, M., & Naghavi, Z. (2012). Experimental study of operating parameters affecting deep-bed drying kinetics of rough rice and comparing with a non-equalibrium mathematical model: Agric. Eng. Int.: CIGR J., 14(4), 195-202.
[9] Horikiri, K., Yao, Y., & Yao, J. (2011). Numerical simulation of convective airflow in an empty room. International Journal of Energy and Environment, 5(1), 574-581.
[10] Jamaleddine, T. J., and Ray, M. B (2010). Application of computational fluid dynamics for simulation of drying processes: A review. Drying technology,28(2),120-14. https://doi.org/10.1080/07373930903517458
[11] Janjai, S., Srisittipokakun, N., & Bala, B. K. (2008). Experimental and modelling performances of a roof-integrated solar drying system for drying herbs and spices. Energy, 33(1), 91-103.https://doi.org/10.1016/j.energy.2007.08.009
[12] Kalbasi, M. (2003). Heat and moisture transfer model for onion drying. Drying Technol., 21(8), 1575-1584. https://doi.org/10.1081/DRT-120024492
[13] Kavindi, M. R., Amaratunga, K. S. P., Ekanayake, E. M. C., Fernando, A. J., & Abesinghe, A. M. S. K. (2021). CFD Simulation of Airflow Distribution in a Heat Pump Assisted Deep-Bed Paddy Dryer. In Applied Engineering in Agriculture, 38(1): 1-8, doi: 10.13031/aea.14483.
[14] Kumar, A., Pramanik, S., & Mishra, M. (2016). COMSOL Multiphysics modeling in darcian and non-darcian porous media. In Proceedings of the 2016 COMSOL Conference, Bangalore, India (pp. 20-21).
[15] Liu, H., Yousaf, K., Chen, K., Fan, R., Liu, J., & Soomro, S. A. (2018). Design and thermal analysis of an air source heat pump dryer for food drying. Sustainability, 10(9), 3216. https://doi.org/10.3390/su10093216
[16] Mabrouk, S. B., Khiari, B., & Sassi, M. (2006). Modelling of heat and mass transfer in a tunnel dryer. Applied thermal engineering, 26(17-18), 2110-2118. https://doi.org/10.1016/j.applthermaleng.2006.04.007
[17] Madhiyanon, T., Soponronnarit, S., & Tia, W. (2001). Industrial scale prototype of continuous spouted bed paddy dryer. Drying Technol., 19(1), 207-216. https://doi.org/10.1081/DRT100001362
[18] Misha, S., Mat, S., Rosli, M. A., Ruslan, M. H., Sopian, K., & Salleh, E. (2015) Simulation of air flow distribution in a tray dryer by CFD. Proc. 10th Int. Conf. on Energy & Environment. Recent Advances in Renewable Energy Sources, (pp. 126-135)
[19] Noh, A., Mat, S.., & Ruslan, M. H. (2020). CFD Simulation of Temperature and Air Flow Distribution Inside Industrial Scale Solar Dryer. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 45(1), 156–164. Retrieved from https://akademiabaru.com/submit/index.php/arfmts/article/view/2192
[20] Park, K. J., Vohnikova, Z., & Brod, F. P. R. (2002). Evaluation of drying parameters and desorption isotherms of garden mint leaves (Mentha crispa L.). J. Food Eng., 51(3), 193-199. https://doi.org/10.1016/S0260-8774(01)00055-3
[21] Patel, K. K., & Kar, A. (2012). Heat pump assisted drying of agricultural produce: An overview. J. Food Sci. Technol., 49(2), 142-160. https://doi.org/10.1007/s13197-011-0334-z
[22] Ranjbaran, M., Emadi, B., & Zare, D. (2014). CFD Simulation of deep-bed paddy drying process and performance. Drying Technol., 32(8), 919-934. https://doi.org/10.1080/07373937.2013.875561
[23] Sitompul, J. P., Istadi, & Widiasa, I. N. (2001). Modeling and simulation of deep-bed grain dryers. Drying Technol., 19(2), 269-280. https://doi.org/10.1081/DRT-10010290
[24] Salehi, F. (2021). Recent applications of heat pump dryer for drying of fruit crops: A review. Int. J. Fruit Sci., 21(1), 546-555.https://doi.org/10.1080/15538362.2021.1911746
[25] Woo, M. W., Daud, W. R. W., Mujumdar, A. S., Wu, Z., Meor Talib, M. Z., & Tasirin, S. M. (2008). CFD evaluation of droplet drying models in a spray dryer fitted with a rotary atomizer. Drying Technology, 26(10), 1180-1198.https://doi.org/10.1080/07373930802306953
[26] Zare, D., Minaei, S., Mohamad Zadeh, M., & Khoshtaghaza, M. H. (2006). Computer simulation of rough rice drying in a batch dryer. Energy Conversion Manag., 47(18), 3241-3254. https://doi.org/10.1016/j.enconman.2006.02.021
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Kavindi M. A. R., Amaratunga K.S.P., Ekanayake E.M.A.C “Computer Simulation of Airflow Distribution in a Heat Pump Dryer” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.76-82 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/76-82.pdf
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Application of Geophysical and Geotechnical Methods for Mapping and Characterization of Sand and Gravel Deposits in Njaba Area of Imo River Basin, Nigeria.
Emeka Nwadisia, Leonard I. Nwosu and Bright O. Nwosu- September 2022 Page No.: 83-91
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Excavation of sand and gravel occurs along Njaba River bank for Civil engineering purposes which occasionally results to landslides that lead to casualties. Hence, Geoelectrical and Geotechnical techniques were adopted for mapping and characterizing the sand and gravel deposits and at the same time assess the slopes stability. Ten vertical electrical soundings (VES) were carried out at different locations, using OHMEGA-500 resistivity meter. The field data were interpreted using Advanced Geosciences Incorporation (AGI) ID resistivity inversion software and Schlumberger Automatic analysis version. The model results revealed that the sand and gravel layers have high resistivity values ranging from 1359Ωm to 7353Ωm. The geologic information, the borehole data and VES model were integrated to map the sand and gravel bed. The thickness of the beds ranges from 15.70m to 67.60m. Four samples collected at different locations were tested and analyzed in laboratory to determine basic geotechnical parameters. Average values obtained were: moisture content (10.7%), bulk density (2.10g/cm3) maximum Dry density (1.73g/cm2), California Bearing Ratio (24%). The particle size distribution obtained revealed that the coarse sand, medium sand, fine sand are 3.7%, 34.52%, 61.26% respectively, implying that they are of good grade and in conformity with civil engineering requirements. The slopes instability in the study area is as a result of the low shear strength.
Page(s): 83-91 Date of Publication: 25 October 2022
Authors
Emeka Nwadisia
Department of Physics University of Port Harcourt, Nigeria.
Leonard I. Nwosu
Department of Physics University of Port Harcourt, Nigeria.
Bright O. Nwosu
Department of Geology University of Port Harcourt, Nigeria.
References
[1] AASTHTO, (2008), standard specification for classification of soils and soil-Aggregate mixture for high way construction purposes, AASHTO.
[2] Oghonyon, R., Adeniran, A. and Opaimi, L (2015); Geotechnical attributes of Niger Delta Soils,Warrienvirons, Nigeria. International Journal of Science Inventions Today, l4(2): 213-225.
[3] Adejumo, S. A., Oyerinde, A. O., Aleem, M. O. (2015); Integrated Geophysical and Geotechnical Subsoil Evaluation for Pre-foundation study of Proposed Site of Vocational Skill and Entrepreneurship Center at The Polytechnic, Ibadan, Sw, Nigeria. International Journal of Scientific & Engineering Research, 6(6), June-2015 910 ISSN 2229-5518.
[4] Nwosu, L.I. Emujakporue, G.O. and Nwosu, B.O. (2017). Integration of Geoelectrical and Geotechnical Data for Evaluation of the Structural Disposition of the foundation Beds within the University of Port Harcourt, Nigeria. International Journal of Science and Research Methodology. 5(4): 95-110.
[5] Aghamelu, O. P. and Okogbue C. O, (2011); Geotechnical Assessment of Road Failures in the Abakaliki Area, Southeastern Nigeria. Engineering International Journal of Civil & Environmental Engineering IJCEE-IJENS 11(02):12, 111502-8383 IJCEE-IJENS.
[6] Mbonu, P.D.C., Ebeniro, J.O, Ofoegbu, C.O. and Ekine, A.S. (1990).Geoelectric Sounding for the Determination of Aquifer Characteristics in Parts of the Umuahia Area of Nigeria. Geophysics. 56(2): 284-291.
[7] Onyeaguocha, A.C. (1980). Petrography and Depositional Environment of Benin Formation. Journal of Mining Geology. 17(2): 147-151
[8] Short, K. C. and Stauble, A. J. (1967). Outline of Geology of the Niger Delta.American Association of Geologists, 51 (5) 761 – 779.
[9] Reyment, R.A (1965). Aspects of the Geology of Nigeria, University of Ibadan Press, 133
[10] Nwosu. L.I. Nwankwo, C.N. and Ekine, A.S. (2013); Geoelectric Investigation of the Hydraulic Properties of the Acquiferous zones for Evaluation of Groundwater Potentials in the complex Geological Area of Imo State, Nigeria. Asian Journal of Earth Sciences. 6(1): 1-15.
[11] Ibeneme S. I., Okereke, C.N., Iroegbu C. and Etiefe, E.0. (2014). Vertical Electrical Sounding for Aquifer Characterisation around the Lower Orashi River Sub-Basin Southeastern Nigeria. Communications in Applied Sciences, 2(3): 36-51
[12] Nwachukwu, M.A., Huan, Feng and Duke Ophori (2010). Groundwater Flow Model and Particle Track Analysis for Selecting Water Quality Monitoring Well Sites and Soil Sample Profile. Journal of spatial hydrology 10(1), 1- 14
[13] Barley, M.J, (1976); Degradation and other parameters related to the use of the shale in compacted embankments Joint Highway Research Project No.23, Purdue University and Indiana State Highway Commission. 209.
[14] Okagbue, C. O. and Ochulor, O. H (2007);Thepotential of cement-stabilized coal-reject as a Construction material. Bulletin of Engineering Geology and Environment. 66:143-151.
[15] Bareither, C.A., Benson, C.H. and Edil, T.B. (2008). Reproducibility of direct shear tests conducted on granular backfill materials. Geotechnical Testing Journal 31(1): 1–11, http://dx.doi.org/10.1520/GTJ100878.
[16] IWADA (2006). Imo Water Development Agency Documentary on Groundwater Resources Potential of Imo State Nigeria’ (Unpublished). 20-39
[17] Nwosu, L.I, Nwachukwu, M.A, Emujakporue, G.O, Ibekwe, K.E. and Nwosu, B.O. (2019). investigating the relationship between water table and topographic variations within Owerri metropolis. International Journal of Research and Innovation in Applied Science. 4(12), 2454-6194
[18] USCS. (n.d) Wikipedia. Retrieved, January, 2018, from https:/en.m.wikipedia.org/wiki/unified_soil_classification_system.
[19] O’Flahetty, C. A. (1988). Highway Engineering (2nd Ed.). Edward Almond Publishers, London UK, 51: 762-779
[20] Federal Ministry of Works and Housing, Nigeria (1994). General specification for Road and Bridges. Federal Highway Department, 2: 145-284
[21] Bowles, J.E. (1996); Foundation Analysis and Design, 5th ed. Singapore, McGraw-Hill. British Standard. 1997, Soils for Civil Engineering Purposes – 1377 Part 2: Classification Tests.
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Emeka Nwadisia, Leonard I. Nwosu and Bright O. Nwosu “Application of Geophysical and Geotechnical Methods for Mapping and Characterization of Sand and Gravel Deposits in Njaba Area of Imo River Basin, Nigeria.” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.83-91 September 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/83-91.pdf
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Estimating The Accuracy of Classifiers in Analyzing Multiple Diseases
AJAYI Olusola Olajide- October 2022 Page No.: 92-96
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Medical data are regarded as been sensitive not only in terms of the need to keep it private but also and majorly in terms of the need to get it right and accurate. Patients’ medical data are diagnose and analyze with optimal accuracy to avoid error of prescription. Multiple diseases are one that can easily get complicated where the analysis of symptoms are not right. Machine learning is a known field of inquiry found very suitable in the medical area for analysis of medical diagnosis. The need for the right classification algorithm to deploy for a particular medical experimentation/prediction becomes very germane especially in the case of multiple diseases. No doubt, many researches have been done in this regard but not specifically tailored towards multiple diseases. The study which utilizes medical data from third party, www.kaggle.com, applied selected common three classification algorithms on the dataset. The result of the experimentation carried out using WEKA Explorer, shows Artificial Neural Network (ANN) outperforms Decision Tree and Naïve Bayes in terms of level of accuracy.
Page(s): 92-96 Date of Publication: 25 October 2022
Authors
AJAYI Olusola Olajide
Department of Computer Science, Faculty of Science, Adekunle Ajasin University, Akungba-Akoko, Ondo, Nigeria
References
[1] Ajinkya, K., Harshal S., Nuzhat F. S. (2016). A Review on Prediction of Multiple Diseases and Performance Analysis using Data Mining and Visualization Techniques, International Journal of Computer Applications, Volume 155, page 0975 – 8887.
[2] Durga K. and Gaikwad S. K. (2018), Survey on data mining techniques for disease prediction, International Research Journal of Engineering and Technology, Volume 5.
[3] Hitesh H. P, Glory H. S, (2013), Experimental and Comparative Analysis of Machine Learning Classifiers, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3.
[4] Mohammed Khalilia1, Sounak Chakraborty, Mihail Popescu (2012), Predicting disease risks from highly imbalanced data using random forest,
[5] Paola G., and Roberto T. (2018), Data Mining: Accuracy and Error Measures for Classification and Prediction.
[6] Runzhi Li, Wei Liu, Yusong Lin, Hongling Zhao, Chaoyang Zhang (2017), An Ensemble Multilabel Classification for Disease Risk Prediction, Journal of Healthcare Engineering.
[7] Sudhir M. G, Ankit D, Pritesh P, (2017), A Study of Some Data Mining Classification Techniques, International Research Journal of Engineering and Technology, Volume 01.
[8] Selvaraj A, Mithra M. K, Keerthana S, Deepika M, (2018), Prediction Support System for Multiple Disease Prediction Using Naive Bayes Classifier, International Journal of Engineering and Techniques, Volume 4.
[9] Shratik J. Mishra, Albar M. Vasi, Vinay S. Menon, Prof. K. Jayamalini, (2018), General Disease Prediction System, International Research Journal of Engineering and Technology, Volume 5.
[10] Vincent L, Hocine C, (2011), Accuracy Measures for the Comparison of Classifiers.
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AJAYI Olusola Olajide “Estimating The Accuracy of Classifiers in Analyzing Multiple Diseases ” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-9, pp.92-96 October 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-9/92-96.pdf
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