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                <text>N, Tanuja T.; L, Kavitha; Rehman, Khalil Ur; Varma, S.V.K.; Shatanawi, Wasfi; Kumar, G.V.; Asghar, Zeeshan</text>
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                <text>Parametric analysis for thermally magnetized hybrid ternary (TMHT) nanofluid flow on thin film with temperature stratification</text>
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                <text>International Journal of Thermofluids;Volume;26;Issue;;Article No.;101089;</text>
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                <text>N T.T., Department of Mathematics, School of Applied Sciences, REVA University, Karnataka, Bengaluru, India, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, India; L K., Department of Mathematics, School of Applied Sciences, REVA University, Karnataka, Bengaluru, India; Rehman K.U., Department of Mathematics and Sciences, College of Humanities and Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia; Varma S.V.K., Department of Mathematics, School of Applied Sciences, REVA University, Karnataka, Bengaluru, India; Shatanawi W., Department of Mathematics and Sciences, College of Humanities and Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia, Department of Mathematics, Faculty of Science, The Hashemite University, P.O. Box 330127, Zarqa, 13133, Jordan; Kumar G.V., Department of Mathematics, CSSR &amp;amp; SRRM Degree &amp;amp; PG College, A.P., Kamalapuram, 516289, India; Asghar Z., Department of Mathematics and Sciences, College of Humanities and Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia</text>
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                <text>The thermophysical examination of flow field claims various applications in both scientific and industrial domains and hence it remains important to inspect especially when both the heat and mass transfer are taken simultaneously. Owning such motivation, the present study offers a response surface optimization for thermal flow field of hybrid ternary water-based aluminium, silicon and Zinc nanofluid over a stretched surface manifested with both temperature stratification and concentration stratification effects. The governing equations are formulated for mathematical model and those PDE's are reduced to ODE's by using appropriate similarity transformations. Those obtained resultant equations are solved numerically by using Runge Kutta Fehlberg fourth fifth-order (RKF 45) technique. The supremacy of essential aspects on the flow field, heat and mass transfer rates were analyzed using graphical representation. Additionally, Response surface Methodology is performed to derived the heat transfer rate as a response function for the input factors for different parameters. From the graph it is noticed that temperature profile drops as the thermal stratification parameter increases. The temperature admits the direct relation with an increase in the solid volume fraction of ternary nanofluids. From RSM it is noticed that adjusted R-squared and R-squared are obtained as 100 % accuracy of the mathematical model.  2025 The Author(s)</text>
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                <text>Heat transfer; Magnetic field; Stretched surface; Temperature stratification; Ternary nanofluid</text>
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                <text>ISSN: 26662027;</text>
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>INVERSE DOMINATION  NUMBER OF GRAPHS</text>
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                <text>N.  LEVI CHELLSON</text>
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                <text>Entropy generation analysis of magneto-nanoliquids embedded with aluminium and titanium alloy nanoparticles in microchannel with partial slips and convective conditions</text>
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                <text>Alloy nanoparticles; Convective condition; Joule heating; Microchannel; Nanofluid; Slip flow</text>
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                <text>Purpose: Outstanding features such as superior electrical conductivity and thermal conductivity of alloy nanoparticles with working fluids make them ideal materials to be used as coolants in microelectromechanical systems (MEMSs). This paper aims to investigate the effects of different alloy nanoparticles such as AA7075 and Ti6Al4V on microchannel flow of magneto-nanoliquids with partial slip and convective boundary conditions. Flow features are explored with the effects of magnetism and nanoparticle shape. Heat transport of fluid includes radiative heat, internal heat source/sink, viscous and Joule heating phenomena. Design/methodology/approach: Suitable dimensionless variables are used to reduce dimensional governing equations into dimensionless ordinary differential equations. The relevant dimensionless ordinary differential systems are computed numerically by using RungeKuttaFehlberg-based shooting approach. Pertinent results of velocity, temperature, entropy number and Bejan number for assorted values of physical parameters are comprehensively discussed. Also, a closed-form solution is obtained for momentum equation for a particular case. Analytical results agree perfectly with numerical results. Findings: It is established that the entropy production can be improved with radiative heat, Joule heating, convective heating and viscous dissipation aspects. The entropy production is higher in the case of Ti6Al4V-H2O nanofluid than AA7075-H2O. Further, the inequality Ns(?)Sphere &amp;gt; Ns(?)Hexahedran &amp;gt; Ns(?)Tetrahydran &amp;gt; Ns(?)Column &amp;gt; Ns(?)Lamina holds true. Originality/value: Effects of aluminium and titanium alloy nanoparticles in microchannel flows by using viscous dissipation and Joule heating are investigated for the first time. Flow features are explored with the effects of magnetism and nanoparticle shape. The results for different alloy nanoparticles such as AA7075 and Ti6Al4V have been compared.  2019, Emerald Publishing Limited.</text>
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                <text>N.S S.; Gireesha B.J.; Mahanthesh B.; B.C P.; Chamkha A.J.</text>
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              <elementText elementTextId="128338">
                <text>International Journal of Numerical Methods for Heat and Fluid Flow, Vol-29, No. 10, pp. 3638-3658.</text>
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                <text>Emerald Publishing</text>
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                <text>&lt;a href="https://doi.org/10.1108/HFF-06-2018-0301" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1108/HFF-06-2018-0301&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059590596&amp;amp;doi=10.1108%2FHFF-06-2018-0301&amp;amp;partnerID=40&amp;amp;md5=26dbfa1d1b6858ce47f4da30ad10fcf9" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059590596&amp;amp;doi=10.1108%2fHFF-06-2018-0301&amp;amp;partnerID=40&amp;amp;md5=26dbfa1d1b6858ce47f4da30ad10fcf9&lt;/a&gt;</text>
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              <elementText elementTextId="128342">
                <text>Restricted Access</text>
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                <text>ISSN: 9615539; CODEN: INMFE</text>
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                <text>English</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>N.S S., Department of Mathematics, Kuvempu University, Shankaraghatta, Karnataka, India; Gireesha B.J., Department of Mathematics, Kuvempu University, Shankaraghatta, Karnataka, India; Mahanthesh B., Department of Mathematics, Kuvempu University, Shankaraghatta, Karnataka, India, Department of Mathematics, Christ University, Bangalore, India; B.C P., Department of Mathematics, Government First Grade College, Koppa, India; Chamkha A.J., Department of Mechanical Engineering, Prince Mohammad Bin Fahd University, Al-Khobar, Saudi Arabia</text>
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                <text>&lt;em&gt;&lt;strong&gt;Structural investigation of higher order members of bismuth system superconductors /&lt;/strong&gt;&lt;/em&gt;</text>
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                <text>Physics</text>
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                <text>International Journal Of Chemtech Research, Vol.6, Issue 3, pp.635-637, ISSN No: 0974-4290.</text>
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                <text>N.V Ashokan, George Thomas C and K Srinivasan</text>
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                <text>&lt;a href="https://sphinxsai.com/2014/vol6pt3/6/(1733-1735)ICMCT14.pdf" target="_blank" title="Structural investigation of higher order members of bismuth system superconductors" rel="noreferrer noopener"&gt;https://sphinxsai.com/2014/vol6pt3/6/(1733-1735)ICMCT14.pdf&lt;/a&gt;</text>
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                <text>International Journal Of Chemtech Research</text>
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                <text>Sub-type discernment of attention deficit hyperactive disorder in children using a cluster partitioning algorithm</text>
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            <name>Subject</name>
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                <text>ADHD; Clustering; K-Means algorithm; MRI spectroscopy; Unsupervised learning</text>
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              <elementText elementTextId="137979">
                <text>Background/Objectives: Attention deficit hyperactive disorder is one major neuropsychiatric disorder particularly found in children. This medical disorder is difficult to identify and quantify, even if done, it is very subjective as it is the discretion of the psychiatrists or parents. Methods/Statistical analysis: The most exigent task after identifying ADHD children is to find their exact deficiency of what is the category, is it a hyperactive disorder, an impulsive disorder or an attention deficit disorder. Each category insists a diverse form of treatment and training. With the MRI image data the Tr values are estimated and given for clustering, a k-means algorithm was deployed for clustering. Findings: With different distance measures k-means was able to cluster precisely the three categories from the data. The result obtained would be a very substantial data for the medical physicists and an inevitable philanthropic contribution for the children society combating against this disorder. Applications/Improvements: The method adopted is novel and concise approach to identify the type of ADHD prevalent children. The method can be further perfected and completely automated to identify the category of ADHD in children.</text>
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              <elementText elementTextId="137980">
                <text>Nachamai M.</text>
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              <elementText elementTextId="137981">
                <text>Indian Journal of Science and Technology, Vol-9, No. 8</text>
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              <elementText elementTextId="137982">
                <text>Indian Society for Education and Environment</text>
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                <text>2016-01-01</text>
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                <text>&lt;a href="https://doi.org/10.17485/ijst/2016/v9i8/87909" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.17485/ijst/2016/v9i8/87909&lt;/a&gt;
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            <elementTextContainer>
              <elementText elementTextId="137985">
                <text>All Open Access; Gold Open Access; Green Open Access</text>
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            </elementTextContainer>
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              <elementText elementTextId="137986">
                <text>ISSN: 9746846</text>
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              <elementText elementTextId="137988">
                <text>English</text>
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                <text>Nachamai M., Department of Computer Science, Christ University, Bengaluru, Karnataka, 560029, India</text>
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      <name>Conference Paper</name>
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            <elementTextContainer>
              <elementText elementTextId="190021">
                <text>Cataloging of happy facial affect using a radial basis function neural network</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="190022">
                <text>Emotion recognition; Image processing; Radial basis function network</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="190023">
                <text>The paper entitled "Cataloging of Happy facial Affect using a Radial Basis Function Neural Network" has developed an affect recognition system for identifying happy affect from faces using a RBF neural network. The methodology adapted by this research is a four step process: image preprocessing, marking of region of interest, feature extraction and a classification network. The emotion recognition system has been a momentous field in human-computer interaction. Though it is considerably a challenging field to make a system intelligent that is able to identify and understand human emotions for various vital purposes, e.g. security, society, entertainment but many research work has been done and going on, in order to produce an accurate and effective emotion recognition system. Emotion recognition system can be classified into facial emotion recognition and speech emotion recognition. This work is on facial emotion recognition that identifies one of the seven basic emotions i.e. happy affect. This is carried out by extracting unique facial expression feature; calculating euclidean distance, and building the feature vector. For classification radial basis function neural network is used. The deployment was done in Matlab. The happy affect recognition system gave satisfactory results.  2013 Springer.</text>
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          <element elementId="39">
            <name>Creator</name>
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              <elementText elementTextId="190024">
                <text>Nachamai M.; Dutta P.</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="190025">
                <text>Lecture Notes in Electrical Engineering, Vol-221 LNEE, No. VOL. 1, pp. 597-608.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>&lt;a href="https://doi.org/10.1007/978-81-322-0997-3_53" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-81-322-0997-3_53&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885230862&amp;amp;doi=10.1007%2F978-81-322-0997-3_53&amp;amp;partnerID=40&amp;amp;md5=c8ce63069fac9749d76d7691f35efecf" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885230862&amp;amp;doi=10.1007%2f978-81-322-0997-3_53&amp;amp;partnerID=40&amp;amp;md5=c8ce63069fac9749d76d7691f35efecf&lt;/a&gt;</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="190028">
                <text>Restricted Access</text>
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                <text>ISSN: 18761119; ISBN: 978-813220996-6</text>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>Online</text>
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                <text>English</text>
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                <text>Nachamai M., Department of Computer Science, Christ University, Bangalore, India; Dutta P., Department of Computer Science, Christ University, Bangalore, India</text>
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      <name>Article</name>
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          <element elementId="50">
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            <description>A name given to the resource</description>
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              <elementText elementTextId="79250">
                <text>Synthesis, characterization and application of rare earth (Lu3+) doped zinc ferrites in carbon monoxide gas sensing and supercapacitors</text>
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          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="79251">
                <text>Carbon monoxide; Ferrites; Sensing; Supercapacitors</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="79252">
                <text>The novel rare earth (Lu) doped zinc ferrite nanoparticles, synthesized via a solution combustion approach, exhibit exceptional sensitivity to carbon monoxide (C.O.), a capability studied for the first time. The successful detection of C.O. by these nanoparticles underscores their potential as efficient gas sensors. Structural and morphological characterization confirmed the creation of single-phase zinc ferrite nanoparticles, utilizing various standard and advanced modern probes. To assess the gas sensing capabilities, the nanoparticles were exposed to carbon monoxide gas, revealing an outstanding gas response of 80 % at 300 C, with a response against 20,000 parts per million by volume (PPMv) of carbon monoxide. These results indicate the promising applicability of Lu-doped zinc ferrite nanoparticles in C.O. gas sensing applications. Furthermore, the supercapacitance performance of the synthesized nanoparticles was investigated. Electrodes fabricated from Lu-doped zinc ferrite nanoparticles (Lu 0, 0.3, 0.5, and 0.7) were examined in a 3 M K.O.H. electrolyte using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (E.I.S.). The electrochemical properties of all nanoparticles exhibited good Faradaic behaviour, with the Lu 0.7 electrode achieving a high specific capacitance of 280 F/g at a current density of 0.25 A/g. This highlights the prominent electrochemical stability and potential applications of Lu-doped zinc ferrite nanoparticles in energy storage devices. Overall, the comprehensive investigation of the gas sensing and super capacitance performance of Lu-doped zinc ferrite nanoparticles demonstrates their versatility and potential for various technological applications, including gas sensing and energy storage. These findings pave the way for further research and development in utilizing rare earth-doped ferrite nanoparticles for advanced functional materials.  2024 Elsevier Ltd and Techna Group S.r.l.</text>
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              <elementText elementTextId="79253">
                <text>Nadaf S.; Chethan B.; Swathi K.M.; Laxmeshwar S.S.; Angadi V J.; Manjunatha K.; Vandana M.; Chattham N.; Hegde G.; Sharma K.; Sathish T.; Gupta M.; Ubaidullah M.; Pattar V.; Basavegowda N.; Wu S.Y.; Manjunatha S.O.; Bajorek A.</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="79254">
                <text>Ceramics International, Vol-50, No. 13, pp. 23208-23221.</text>
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              <elementText elementTextId="79255">
                <text>Elsevier Ltd</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="79256">
                <text>2024-01-01</text>
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              <elementText elementTextId="79257">
                <text>&lt;a href="https://doi.org/10.1016/j.ceramint.2024.04.045" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.ceramint.2024.04.045&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191003998&amp;amp;doi=10.1016%2Fj.ceramint.2024.04.045&amp;amp;partnerID=40&amp;amp;md5=8712b78775a6fc912ac51b1bff83faa0" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191003998&amp;amp;doi=10.1016%2fj.ceramint.2024.04.045&amp;amp;partnerID=40&amp;amp;md5=8712b78775a6fc912ac51b1bff83faa0&lt;/a&gt;</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="79258">
                <text>Restricted Access</text>
              </elementText>
            </elementTextContainer>
          </element>
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                <text>ISSN: 2728842; CODEN: CINND</text>
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                <text>Online</text>
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              <elementText elementTextId="79261">
                <text>English</text>
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                <text>Nadaf S., Department of P. G. Studies in Chemistry, P. C. Jabin Science College, Hubballi, 31, India; Chethan B., Deparment of Physics, Indian Institute of Science, Bengaluru, 12, India; Swathi K.M., Department of P. G. Studies in Chemistry, P. C. Jabin Science College, Hubballi, 31, India; Laxmeshwar S.S., Department of P. G. Studies in Chemistry, P. C. Jabin Science College, Hubballi, 31, India; Angadi V J., Department of Physics, P. C. Jabin Science College, Hubballi, 31, India; Manjunatha K., Department of Physics, National Dong Hwa University, Hualien, 97401, Taiwan; Vandana M., Department of Physics, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand; Chattham N., Department of Physics, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand; Hegde G., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Bangalore, 560029, India; Sharma K., Centre for Research Impact and Outcomes, Chitkara University, Punjab, Rajpura, India; Sathish T., Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Tamil Nadu, Chennai, India; Gupta M., Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, 174103, India; Ubaidullah M., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Pattar V., Education Technology Unit, JNCASR, Bengalore, India; Basavegowda N., Department of Biotechnology, Yeungnam University, Gyeongbuk, Gyeongsan, 38541, South Korea; Wu S.Y., Department of Physics, National Dong Hwa University, Hualien, 97401, Taiwan; Manjunatha S.O., Department of Physics, B.M.S. College of Engineering, Bangalore, 560 019, India; Bajorek A., A. Che?kowski Institute of Physics, University of Silesia in Katowice, 75 Pu?ku Piechoty 1, Chorz, 41-500, Poland</text>
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              <elementText elementTextId="289032">
                <text>Nadampalli, Babitha; Jain, Sunitha Abhay</text>
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                <text>From Mass Campaigns to Phygital Governance: Health Literacy, Policy Advertising, and Reform Pathways in India</text>
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              <elementText elementTextId="289034">
                <text>01-01-2026</text>
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            <elementTextContainer>
              <elementText elementTextId="289035">
                <text>Phygital Insights on National Health Reform: Economics, Marketing, and Leadership;pp.233-263</text>
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                <text>Nadampalli B., Christ University, India; Jain S.A., Christ University, India</text>
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                <text>Over seven decades, Indias health literacy journey has progressed from traditional mass campaigns to integrated phygital governance, blending physical outreach with digital communication. This paper examines the evolution of health communication, policy advertising, and reform through the lens of Indias Five- Year Plans (19512017). It traces the shift from school- based civic education and rural health campaigns to technologically enabled, participatory Information, Education, and Communication (IEC) strategies. While health literacy has remained a core national priority, persistent gaps in equity, access, and behavioral outcomes endure. The study underscores the need for phygital inclusion, participatory communication, and data- driven governance to strengthen public health systems and ensure equitable, sustainable health literacy for all citizens in the digital age.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Nadampalli, Babitha; Jain, Sunitha Abhay</text>
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                <text>From Public Awareness to Phygital Action: Health Literacy, Economics, and Leadership in Indias Healthcare Reform</text>
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                <text>Phygital Insights on National Health Reform: Economics, Marketing, and Leadership;pp.325-357</text>
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                <text>Nadampalli B., Christ University, India; Jain S.A., Christ University, India</text>
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                <text>Over seven decades, Indias health reform has transitioned from traditional awareness programs to participatory phygital (physical + digital) models. This paper traces the evolution of health literacy governance through successive Five- Year Plans (19512017), analyzing how economic priorities, marketing strategies, and leadership paradigms shaped reform outcomes. It highlights the shift from rural welfare and communicable disease control to challenges of lifestyle disorders, digital health equity, and nutrition security. Persistent gaps in efficiency, communication, and leadership integration across the phygital ecosystem are identified. The study concludes with recommendations to embed health literacy, digital inclusion, and collaborative leadership within Indias public health framework, advancing equitable, action- oriented, and sustainable healthcare reform.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Nadeem Pasha, K.; Antar, Dina; Shakir, Alakbarova Tamara; Sharan, Mudita; Farheen, Syeda Fatima; Mallick, Mohamed</text>
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                <text>The Impact of AI Tools on Enhancing EFL Learners' Engagement in Higher Education Using HubSVM Models</text>
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                <text>2025 Global Conference in Emerging Technology, GINOTECH 2025;</text>
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                <text>Nadeem Pasha K., Hkbk College of Engineering, Department of Mechanical Engineering, Karnataka, India; Antar D., American University of Ras Al Khaimah, School of Arts &amp;amp; Sciences, Department of Humanities and Social Sciences, United Arab Emirates; Shakir A.T., Alakbarova Tamara Shakir Azerbaijan Technological University, Department Automation and Information Technologies, Azerbaijan; Sharan M., Christ (Deemed to be University), School of Sciences, Department of Computer Science and Engineering, Delhi, India; Farheen S.F., Vardhaman College of Engineering, Department of English, Telangana, Hyderabad, India; Mallick M., Vel Tech Rangarajan Dr Sagunthala R&amp;amp;d Institute of Science and Technology, Department of Cse, Tamil Nadu, Chennai, India</text>
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                <text>BL has become prevalent in higher education as a means of delivering information, managing activities, and executing lessons, thanks in large part to the proliferation of COVID-19 and other technological developments in education. By combining online and offline learning, BL encourages students to be more engaged and flexible than in a typical classroom setting. Engaged learners are crucial for psychometric analysis; they are like energy in action, full of life, focus, and determination. By encouraging mental and physical exertion towards studying, it significantly improves EFL students' involvement in higher education. Using MinMax for feature scaling and the HubSVM, which, similar to the L1-norm SVM, allows automatic feature selection, this study analyses and improves engagement. By highlighting highly connected features, HubSVM improves the selection process and makes computing the complete solution path easier. The results show that when dealing with highly correlated variables, HubSVM performs better than L1-norm SVM. The suggested classifier outperforms the competition with an accuracy of 95.65%. The results show that the concept works well to make BL settings more engaging for students. This research helps make higher education more engaging for EFL learners by incorporating modern machine learning techniques, which means they will have a better, more effective learning experience.   2025 IEEE.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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