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Magnetohydrodynamic flow of williamson nanofluid due to an exponentially stretching surface in the presence of thermal radiation and chemical reaction
A steady MHD boundary layer flow of Williamson nanofluid over an exponential stretching surface through a porous medium is considered. The effects of Brownian motion and thermophoresis have examined in the energy transport equation. The influences of solar radiation and chemical reaction are taken into the account. The governing boundary layer equations with the boundary conditions are transformed into nonlinear ordinary differential equations with the help of selected exponential type of similarity variables. They are then solved numerically using well-known Shooting technique along with Runge-Kutta-Fehlberg method. The numerical results are presented through graphs and a table to discuss the characteristics of different flow fields versus pertinent parameters. Comparisons with previously published work have been conducted and the results are found to be in good agreement. It is found that temperature field is enhanced for the larger Brownian motion, thermophoresis parameter and radiation parameter effects. 2017 by American Scientific Publishers. All rights reserved. -
Magnetohydrodynamic squeezing two-phase flow of particulate suspension in a rotating channel with transpiration cooling
This article addresses the time-dependent two-phase magnetohydrodynamic squeezing flow of dusty liquid. The fluid flow is considered in a rotating channel. The flow is constructed by squeezing of an upper plate and stretching of the lower plate and relevant equations are obtained. Numerical results are computed by utilizing shooting method along with the RKFehlberg scheme. The obtained solutions are validated by comparison with the existing analytical solutions. The effects of pertinent parameters on velocities of both phases are comprehensively discussed through graphical results. The numerical values of shear stress of both phases at lower and upper walls are also tabulated. Furthermore, the slope of the linear regression line through data points is determined in order to quantify the increase/decrease. Numerical simulations disclosed that the normal and transverse velocities are decreased due to stronger Coriolis force. It is also established that the velocities of the fluid phase are higher than that of the dust phase IMechE 2018. -
Magnetohydrodynamic three-dimensional flow of nanofluids with slip and thermal radiation over a nonlinear stretching sheet: a numerical study
A numerical simulation for mixed convective three-dimensional slip flow of water-based nanofluids with temperature jump boundary condition is presented. The flow is caused by nonlinear stretching surface. Conservation of energy equation involves the radiation heat flux term. Applied transverse magnetic effect of variable kind is also incorporated. Suitable nonlinear similarity transformations are used to reduce the governing equations into a set of self-similar equations. The subsequent equations are solved numerically by using shooting method. The solutions for the velocity and temperature distributions are computed for several values of flow pertinent parameters. Further, the numerical values for skin-friction coefficients and Nusselt number in respect of different nanoparticles are tabulated. A comparison between our numerical and already existing results has also been made. It is found that the velocity and thermal slip boundary condition showed a significant effect on momentum and thermal boundary layer thickness at the wall. The presence of nanoparticles stabilizes the thermal boundary layer growth. 2016, The Natural Computing Applications Forum. -
Mahe's Memorialisation of French Colonialism
[No abstract available] -
Mainstream tradition and exclusive traditions : Study of Kongu Folk Epic Annanmar Kathai /
International Journal of Social Science and Humanities Research, Vol.3, Issue 3, pp.294-298, ISSN No: 2348-3164 (Online) 2348-3156 (Print) -
Mainstreaming Northeast Tribal Women in India through Financial Education: A Systematic Review
Financial education is required to enhance financial literacy for socio-economic development. This paper aims to understand the financial literacy level among the Scheduled Tribes of India, specifically the Mao-Naga Tribe women of Northeast India. The current paper is based on secondary data and adheres to the steps and process of a systematic review. Prominent authors, times, tribes, countries, journals, and keywords have been identified for the comprehensive analysis. Since the goal of this paper is to review the existing literature regarding financial literacy among tribals, the findings indicate that financial education intervention, socio-cultural practices, social affinity, and early life financial experience affect individuals financial literacy. It has also been observed that a productive pathway to achieve financial literacy and inclusion lies in integrating financial education programs within the socio-cultural practices of tribal women. Thus, financial literacy can enhance the financial well-being that is necessary for socio-economic development among Mao-Naga Tribal women. This paper can help governments, central bank regulators, and researchers know the essential elements of financial literacy and identify the pertinent areas for further empowerment among sub-groups of the population, especially among tribal women of Northeast India. 2022 Journal of International Womens Studies. -
Mainstreaming Reproductive Mental Health of Women: The Unmet Need of the Hour
Background: While the existing research is limited, over recent years, there has been growing awareness to understand the mental health of women during menstruation, menopause, and postpartum. Methodology: A woman's distinct reproductive life stages adversely affect her psychological well-being, aggravated by other underlying social, economic, and cultural factors. Drawing upon the analysis of governing laws and womens reproductive health literature. Results: The existing reproductive health law, educational, and workplace frameworks in India are inadequate for supporting the reproductive mental health of women. Conclusion: It is of critical importance to adopt a holistic approach and call for mainstreaming the reproductive mental health of women through urgent legal and healthcare reforms. The Author(s). -
Making a Difference: Social Responsibilities of Infosys
International Journal of Management, IT and Engineering Vol. 2, Issue 10, pp 336-350, ISSN No. 2249-0558 -
Making of socially sensitive students
Educational institutions have a major role in realising equal representation in the society, writes John J Kennedy. -
Making students future-ready
By all means, let the child bloom. But do not forget to water the roots, writes John J Kennedy -
Making the body public: Implications of the new standards of body-image
[No abstract available] -
Making youth politically aware
Educations sole purpose has become acquiring a degree, preferably with todays much-hyped employability skills, and landing cushy jobs with fat salaries -
Malayalam kavi Kumaranasan ka yug bodh /
International Journal of Hindi Research, Vol.4, Issue 4, pp.56-58, ISSN No: 2455-2232. -
Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks
In wireless, every device can moves anywhere without any infrastructure also the information can be maintained constantly for routing the traffic. The open issues of wireless Adhoc network the attacks which are chosen the forwarding attack that is dropped by malicious node to corrupt the network performance then the information integrity exposure. Aim of the problem that existing methods in Adhoc network for malicious node detection which cannot assure the traceability of the node as well as the fairness of node detection. In this paper, the proposed heterogeneous cluster based secure routing scheme provides trust based secure network for detection of attacks such as wormhole and black hole caused by malicious nodes presence in wireless Adhoc network. The simulation result shows that the proposed model is detect the malicious nodes effectively in wireless Adhoc networks. The malicious node detection efficiency can be achieved 96% also energy consumption also 10% better than existing method. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
Malicious Traffic Classification in WSN using Deep Learning Approaches
Classifying malicious traffic in Wireless Sensor Networks (WSNs) is crucial for maintaining the network's security and dependability. Traditional security techniques are challenging to deploy in WSNs because they comprise tiny, resourceconstrained components with limited processing and energy capabilities. On the other hand, machine learning-based techniques, such as Deep Learning (DL) models like LSTMs, may be used to detect and categorize fraudulent traffic accurately. The classification of malicious traffic in WSNs is crucial because of security. To protect the network's integrity, data, and performance and ensure the system functions properly and securely for its intended use, hostile traffic categorization in WSNs is essential. Classifying malicious communication in a WSN using a Long Short-Term Memory (LSTM) is efficient. WSNs are susceptible to several security risks, such as malicious nodes or traffic that can impair network performance or endanger data integrity. In sequential data processing, LSTM is a Recurrent Neural Network (RNN) appropriate for identifying patterns in network traffic data. 2023 IEEE. -
Malicious URL Detection Using Machine Learning Techniques
Cyber security is a very important requirement for users. With the rise in Internet usage in recent years, cyber security has become a serious concern for computer systems. When a user accesses a malicious Web site, it initiates a malicious behavior that has been pre-programmed. As a result, there are numerous methods for locating potentially hazardous URLs on the Internet. Traditionally, detection was based heavily on the usage of blacklists. Blacklists, on the other hand, are not exhaustive and cannot detect newly created harmful URLs. Recently, machine learning methods have received a lot of importance as a way to improve the majority of malicious URL detectors. The main goal of this research is to compile a list of significant features that can be utilized to detect and classify the majority of malicious URLs. To increase the effectiveness of classifiers for detecting malicious URLs, this study recommends utilizing host-based and lexical aspects of the URLs. Malicious and benign URLs were classified using machine learning classifiers such as AdaBoost and Random Forest algorithms. The experiment shows that Random Forest performs really well when checked using voting classifier on AdaBoost and Random Forest Algorithms. The Random Forest achieves about 99% accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
MALL-Based Writing Instruction: Assessing the Effectiveness of Digital Platforms Among ESL Learners
Nowadays, mobile-assisted language learning (MALL) has emerged as a globally adopted approach that builds on the earlier development of computer-assisted language learning (CALL) by utilizing the accessibility and flexibility of mobile devices to promote independent and self-directed learning. It enables learners to extend lan guage practice beyond classroom boundaries and provides authentic opportunities to engage with English as a Second Language (ESL). This study investigates the potential of digital platforms, specifically WordPress and Hem ingwayEditor, in enhancing the writing skills of non-native English learners within a MALL framework. WordPress offers a collaborative digital space where learners can publish, share, and receive feedback on their writing, while Hemingway Editor provides real-time analytical feedback to improve readability, grammar, and stylistic accuracy. The research adopted a quantitative design with both control and experimental groups to examine the effective ness of these platforms. Participants included ESL learners who engaged in structured writing tasks, with their progress assessed through pre- and post-tests. The findings of the study reveal that learners using WordPress and Hemingway Editor demonstrated notable improvements in writing performance when compared to the control group. The integration of these tools not only improved grammatical accuracy and stylistic clarity but also encour aged active participation, reflection, and learner autonomy. The results emphasize the pedagogical value of incor porating MALL strategies into language instruction, particularly for developing essential writing skills among ESL learners. In conclusion, this research affirms that mobile technologies, when strategically integrated into teaching, significantly enhance learning outcomes and offer sustainable pathways for improving ESL writing proficiency. 2025, Digital Technologies Research and Applications. All rights reserved. -
Malpractice Detection in Examination Hall using Deep Learning
Various institutions administer tests at designated examination locations, chosen third-party and approved centers, and have established standards for installing CCTV cameras and conducting frisking under the supervision of designated personnel. Some institutions are using online proctoring, which enables students to take exams from any location. In all of the aforementioned scenarios, human monitoring is conducted, and maintaining a high level of vigilance may be challenging due to administrative oversight or intentional allowance of malpractice for personal gain. The malpractice detection may be attributed to acts like as plagiarism, unauthorized sharing of papers, and non-verbal communication. The study is conducted by capturing the dataset in the classroom of Christ University. The proposed approach is based on the YOLO framework. The movies are processed in real time to identify hand rotation, paper extraction, and classify the motion. The accuracy for the Head_right class is significantly higher than that of the Head_left class. The system is implemented using the programming language Python and has the potential for future expansion to provide real-time monitoring. 2024 IEEE. -
Mamaearth: from a mothers dilemma to a multi-crore brand
Learning outcomes: The case study has several objectives: to gauge the evaluation of the direct-to-consumer industry in the economy of India, to analyse the competition of the brands, to ascertain the evolution of smaller direct-to-consumer (DTC) brands on the purchasing capacity of consumers, to analyse challenges in branding in Tier 2 and 3 cities and to evaluate the strategic branding decisions of Mamaearth. Case overview/synopsis: During her pregnancy, Ghazal Alagh and her husband Varun Alagh, the co-founders of Mamaearth, were looking for some good and natural products for their babys skincare. However, she could not find products that were 100% safe. Hence, as a concerned mother, she started using a few hands-on home remedies for her baby, which were 100% organic, and then the idea clicked to her to start a baby care brand named Mamaearth, which later also included personal care products. The company started as a DTC/internet-first brand in 2016, which only used to sell products online without any intermediaries when it was still trying to make its way in the market and was aware of the stiff competition by giants such as Hindustan Unilever and Proctor & Gamble, who were ruling the market for decades. When the COVID-19 pandemic hit, the market saw a shift in consumer buying patterns. There was greater use of e-commerce touch points for shopping, as various digital platforms such as the official site of products, social media and mobile platforms were used by consumers during the pandemic, leading to digitalization in buying and digitalization of consumer shopping journey. These technology platforms were expected to play a substantial role in reaching and creating consumer awareness, transaction and retention post-COVID according to reports by Deloitte 2020. Moreover, such a shift in behaviour amidst the COVID-19 pandemic shot up sales of this DTC brand and made itself the big shot it is today, where they were looking to get into an initial public offering in just seven years of its launch. They re-evaluated their strategy, which helped them become the biggest brand in no time. Complexity academic level: This case study is suitable for Doctor of Philosophy students. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. 2023, Emerald Publishing Limited. -
Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks
The exponential development of e-commerce in recent decades has enhanced convenience for individuals. Compared to the conventional business environment, e-commerce is characterized by increased dynamism and complexity, resulting in several obstacles. Data mining assists individuals in effectively addressing these difficulties. Traditional data mining cannot efficiently use big data in the power provider industry. It heavily relies on time-consuming and labor-intensive feature engineering, and the resulting model could be more easily scalable. Convolutional Neural Networks (CNN) can efficiently use vast amounts of data and autonomously extract valuable elements from the original input, resulting in increased effectiveness. This article utilizes a CNN to extract valuable insights from e-commerce information to forecast commodities sales accurately and proposes a CNN-based Sales Forecasting Model (CNN-SFM). The findings indicate that using data mining and CNN yields a high level of precision in forecasting forthcoming people buying capacity data. The correlation variable between actual usage information and projected usage information was 0.98, and the highest mean error was just 1.78%. Data mining can effectively extract hidden relevant information and forecast future consumption habits for e-commerce systems. CNN demonstrates proficiency in accurately predicting forthcoming consumption power and trends. The Research Publication.