Browse Items (14428 total)
Sort by:
-
Factors influencing user perception on mobile social networking apps /
Sumedha Journal Of Management, Vol.4, Issue 2, pp.429-448, ISSN No: 2277-6753. -
Factors influencing user perception on mobile social networking apps /
Sumedha Journal of Management, Vol.4, Issue 2, pp.429-448, ISSN No: 2277-6753. -
Impact of smartphone news apps on print media - A twin TAM framework /
IOSR Journal Of Business And Management, Vol.17, Issue 4, pp.449-457, ISSN No: 2278-487X (Online) 2319-7668 (Print). -
Effect of inoculum density and different media on the growth of hairy roots and production of withanolide-A from withaniasomnifera /
Mapana Journal of Sciences, Vol. 16(4),pp.13-22. ISSN 0975-3303. -
Heuristic and biases related to finanical investment and the role of behavioral finance in investment decisions - A study /
Zenith International Journal Of Business Economics And Management Research, Vol.5, Issue 12, pp. -
Exploring the impact of creative movement on experential learning in Indian primary school education
This research paper explores the potential of creative dance as an innovative pedagogy for experiential learning in Indian primary school children. The study investigates the impact of incorporating creative dance into the curriculum on various aspects of child development, including cognitive skills, social-emotional growth, and physical well-being. Through a mixed-methods approach, including quantitative assessments and qualitative observations, the research examines the effectiveness of creative dance in enhancing learning outcomes and overall educational experiences. The findings suggest that creative dance can serve as a powerful tool for experiential learning, fostering creativity, critical thinking, and holistic development among Indian primary school children. The Author(s) 2025. -
Parametric analysis for thermally magnetized hybrid ternary (TMHT) nanofluid flow on thin film with temperature stratification
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) -
Entropy generation analysis of magneto-nanoliquids embedded with aluminium and titanium alloy nanoparticles in microchannel with partial slips and convective conditions
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 > Ns(?)Hexahedran > Ns(?)Tetrahydran > Ns(?)Column > 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. -
Structural investigation of higher order members of bismuth system superconductors /
International Journal Of Chemtech Research, Vol.6, Issue 3, pp.635-637, ISSN No: 0974-4290. -
Smart Home Activity Recognition for Ambient Assisted Living (AAL)
With the increasing age of an individual, the chances of being prone to chronic diseases like diabetes or non-curable diseases like Alzheimer's Syndrome or Parkinson's Syndrome increases. Due to the health issues, elderly must be accompanied by caretakers to monitor their well-being at all times. With growing responsibilities and work pressure, the family members may find it challenging to find a trustworthy caretaker. In such scenarios, an assisted living environment acts as a boon. A normal home embedded with different sensors to monitor an individual's well-being is called as Ambient Assisted Living(AAL). This living environment detects anomalous behaviour and recognizes human activities. In this research paper, a smart home activity recognition model is proposed and implemented using four machine learning algorithms using six different publicly available datasets. It has been observed that Random Forest machine learning algorithm shows the best accuracy on most of the dataset. The Electrochemical Society -
Alkali-activated concrete paver blocks made with recycled asphalt pavement (RAP) aggregates /
Case Studies In Construction Materials, Vol.12, pp.2214-5095, ISSN No: 2214-5095. -
A precise method for gender cataloguing using a minimum distance classifier /
The International Journal of Engineering and Science, Vol-3 (2), pp. 1-4. ISSN (p)-2319-1805 ISSN (e)-2319-1813 -
An incisive framework for attention deficit hyperactivity disorder discernment /
Current Trends in Technology and Science, Vol-3 (2), pp. 65-68. ISSN-2279-0535 -
Alphabet recognition of American sign language:A hand gesture recognition approach using sift algorithm /
International Journal of Artificial Intelligence & Applications Vol.4, No.1, pp.105-115 ISSN No. 0975-900X (O) 0976-2191 (P) -
Sub-type discernment of attention deficit hyperactive disorder in children using a cluster partitioning algorithm
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. -
Cataloging of happy facial affect using a radial basis function neural network
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. -
Synthesis, characterization and application of rare earth (Lu3+) doped zinc ferrites in carbon monoxide gas sensing and supercapacitors
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. -
From Mass Campaigns to Phygital Governance: Health Literacy, Policy Advertising, and Reform Pathways in India
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. -
From Public Awareness to Phygital Action: Health Literacy, Economics, and Leadership in Indias Healthcare Reform
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. -
The Impact of AI Tools on Enhancing EFL Learners' Engagement in Higher Education Using HubSVM Models
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.