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Effect of nonlinear thermal radiation on double-diffusive mixed convection boundary layer flow of viscoelastic nanofluid over a stretching sheet
Background: The present exploration deliberates the effect of nonlinear thermal radiation on double diffusive free convective boundary layer flow of a viscoelastic nanofluid over a stretching sheet. Fluid is assumed to be electrically conducting in the presence of applied magnetic field. In this model, the Brownian motion and thermophoresis are classified as the main mechanisms which are responsible for the enhancement of convection features of the nanofluid. Entire different concept of nonlinear thermal radiation is utilized in the heat transfer process. Methods: Appropriate similarity transformations reduce the nonlinear partial differential system to ordinary differential system which is then solved numerically by using the RungeKuttaFehlberg method with the help of shooting technique. Validation of the current method is proved by having compared with the preexisting results with limiting solution. Results: The effect of pertinent parameters on the velocity, temperature, solute concentration and nano particles concentration profiles are depicted graphically with some relevant discussion and tabulated result. Conclusions: It is found that the effect of nanoparticle volume fraction and nonlinear thermal radiation stabilizes the thermal boundary layer growth. Also it was found that as the Brownian motion parameter increases, the local Nusselt number decreases, while the local friction factor coefficient and local Sherwood number increase. The Author(s). 2017. -
Radiative heat transfers of Carreau fluid flow over a stretching sheet with fluid particle suspension and temperature jump
The current study is to deliberate the flow and heat transfer of a Carreau fluid over a stretching sheet with fluid particle suspension. The temperature jump is also taken into account. The standard nonlinear system is resolved numerically via Runge-Kutta based shooting scheme. Role of substantial parameters on flow fields as well as on the fiction factor and heat transportation rates are determined and conferred in depth through graphs. It's found that the velocity profile decreases and temperature profile increases, with an increasing the values of Weissenberg parameter. Further, the higher thermal slip parameter reduces the thermal boundary layer thickness. The thermal boundary layer thickness of fluid and dust particles decreases with the rise in Prandtl number. 2017 The Authors -
MHD flow and nonlinear thermal radiative heat transfer of dusty prandtl fluid over a stretching sheet
Boundary layer flows and melting heat transfer of a Prandtl fluid over a stretching surface in the presence of fluid particle suspensions has been investigated. The converted set of boundary layer equations are solved numerically by RKF-45 method. Obtained numerical results for flow and heat transfer characteristics are deliberated for various physical parameters. Furthermore, the skin friction coefficient and Nusselt number are also presented in Tabs. 2 and 3. It is found that the heat transfer rates are advanced in occurrence of nonlinear radiation compered to linear radiation. Also, it is noticed that velocity and temperature profile increases by increasing Prandtl parameter. 2020 Tech Science Press. -
IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. -
A Survey Instrument for Ranking of the Critical Success Factors for the Successful ERP Implementation at Indian SMEs
Bioinfo Business Economics, Vol-1 (1), pp. 06-12. ISSN-2249-1775 -
Accessing the role of critical success factors for successful ERP implementation at Indian SMEs: A statistical validation
Indian SMEs are also integral part of Indian economy; they also face numerous challenges in implementing technologies such as enterprise resource planning (ERP) systems, including a lack of human, technical and financial resources to support such initiatives. Like many other technological advances, ERP systems were initially implemented mostly at large organisations even in India. Their relative absence from Indian SMEs has probably been the main reason for the research focus on large Indian enterprise. A model is developed with the help of quantitative survey-based method to identify and rank the 30 CSFs and, then a framework has been proposed in terms of recommendations for managing these CSFs. It was determined whether the survey instrument was complete and clear or not with the help of pre-pilot survey of 30 questionnaires responses from the Indian ERP consultants. As a result, the initial survey instrument was extensively revised. For the final data collection, new revised survey instruments were then given via a survey to 500+ Indian ERP consultants. Copyright 2013 Inderscience Enterprises Ltd. -
Perception of online adult education in different countries
Adult education has gained immense popularity during a pandemic. Adult learners are able to meet their educational requirements through online education. Adult learners also prefer online education due to convenience and self-learning interests. Online education also poses challenges and discomfort to online learners. Statistics indicate a higher dropout rate among adult online learners due to various factors. This chapter focuses on the significant challenges adult online learners face and has identified tools, strategies, and techniques to empower and motivate them. This chapter will also help us to understand how tools and techniques, such as information and communication technology, allow us to increase the number of such learners in different countries. Information and communication technology tools are used in developed and developing countries to encourage and motivate adult learners to improve their education virtually at their convenience. 2023, IGI Global. All rights reserved. -
EFFICIENT NON-DEGRADABLE WASTE PROCESSING TECHNOLOGIES INTEGRATED WITH MANETS FOR SUSTAINABLE WASTE MANAGEMENT MODELS
In order to handle the growing amount of non-biodegradable trash, creative and sustainable solutions are becoming more and more necessary as the global waste management challenge grows. To create a complete and sustainable waste management model, this investigation suggests a revolutionary approach that combines Mobile Ad-hoc Networks (MANETs) with effective non-degradable waste processing technology. Utilising cutting-edge waste processing technology that can efficiently handle non-biodegradable materials including plastic, e-waste, and other persistent pollutants is the main goal of this. With the goal of reducing their negative effects on the environment and advancing the concepts of circular economy, these technologies include sophisticated sorting systems, chemical treatments, and recycling procedures. Furthermore, the efficiency and real-time monitoring of waste processing processes are improved by the incorporation of MANETs into the waste management paradigm. MANETs enable smooth data transmission and communication between the central control centres, waste processing units, and monitoring sensors that make up the waste management system. Because of this connectedness, waste processing activities can be dynamically optimised, facilitating prompt resource allocation and decision-making. In addition to addressing the environmental issues raised by non-biodegradable garbage, the suggested paradigm advances the creation of intelligent and networked waste management systems. Because MANETs are used, the system is scalable and adaptable, making it appropriate for a variety of urban and rural areas. The model incorporates the Ant Colony Optimisation (ACO) algorithm for resource allocation. The integration of ACO optimises resource allocation, contributing to the reduction of environmental footprints associated with waste processing. The interconnectedness facilitated by MANETs, in conjunction with ACO, enables dynamic optimisation of waste processing operations, ensuring prompt resource allocation and decision-making. This investigation envisions a sustainable waste management model that minimises pollution, promotes resource recovery, and establishes a robust framework for addressing the growing challenges of non-degradable waste on a global scale by combining cutting-edge waste processing technologies with a strong communication infrastructure. The results of the investigation have a significant impact on waste management procedures by encouraging a more ecologically friendly and sustainable way to deal with non-biodegradable garbage. 2024, Scibulcom Ltd. All rights reserved. -
Consumer perception and acceptance of minute maid pulpy orange in puducherry
International Journal of Management & Business Studies, 3 (2), pp. 119-121. ISSN-2230-2463 -
Critiquing the Regulation of Sand Mining in India: The Role of Social Workers
The soaring demand for sand driven by rapid urbanisation, population growth and increased global investment in infrastructure has intensified sand mining activities worldwide, with current extraction rates exceeding natural replenishment. The Government of India has strengthened legislation by amending existing laws and formulating new guidelines to govern sand mining operations. However, sand mining activities, both legal and illegal, have continued unabated, leading to various consequences across the country. The prevailing laws in India appear to be stringent but have failed in effective implementation at the grassroots level. Therefore, illegal and irregular sand extraction operations have continued to occur at an accelerated pace. The observations indicate that regulatory authorities are merely symbolic and ineffective in controlling and monitoring sand mining operations effectively at the community level. Further, the inefficiency of authorities has facilitated indiscriminate and illicit sand mining operations, resulting in significant social, economic and ecological repercussions. Considering these aspects, the present study advocates the use of social work methods, such as community organisation, social work research and social action, to address the issue effectively. Furthermore, it urges local authorities and policymakers to take action by setting up vigilance committees in every community, so that people themselves can monitor sand mining and protect their surroundings more effectively. The Author(s) 2026 -
Social Entrepreneurship for Digital Governance Services: An Empirical Analysis of Government and Societal Supporting Factors
Purpose: In a fast-growing social entrepreneurship field, the societal entrepreneurial intention is vital to understand to meet social needs and create sustainable rural development. This research study aims to investigate e-governance service core constructs, Hockert's (2017) societal entrepreneurial intention (SEI) and the social cognitive career theory (SCCT) model core that determines rural societal entrepreneurs intention in establishing e-governance social service centres. Design/methodology/approach: Based on a convenient and purposive sampling method, 596 survey sample data were collected through an online questionnaire from an e-governance-based social entrepreneur in Karnataka, India. The partial least square-based structural equation modelling was utilised to analyse the survey data and conceptual model. Findings: The findings indicate that empathy, appointing agencies support (APS), perceived societal support (PSS), prior experience, and government support significantly predict societal entrepreneurship self-efficacy (SES). Hence, social image and perceived process support were insignificant in predicting societal entrepreneurial self-efficacy. Furthermore, societal self-efficacy significantly influences outcome expectations and societal entrepreneurship intention to embark on e-governance social service centres. Originality: The current study was the first to explore the fully integrated model approach of Hockertss societal entrepreneurial intention theoretical model, SCCT and e-governance service supporting factors in framing rural societal entrepreneurs intention in establishing e-governance social service centres development. Key points for practitioners: The study results provide valuable insights for governments, agencies, social entrepreneurs, and social communities to establish a framework for developing and efficiently operating digital seva service centres and generating a positive social impact in rural and distant regions. The Author(s) 2025. -
Development of perceived prenatal maternal stress scale
Background: Pregnancy is a state, which is often associated with extreme joy and happiness. Women undergo a number of physiological and psychological changes during pregnancy, which are often stressful if aligned with other adverse life events, compromising their health and well-being. However, there exists no comprehensive psychological instruments for measuring this stress. Objectives: The study was conducted to develop a multidimensional scale to assess prenatal maternal stress (PNMS) comprehensively. Methods: The initial phase of the study focuses on developing items and assessing the content validity of these items. The second phase focuses on pilot-testing and field-testing the newly developed perceived PNMS scale (PPNMSS) among 356 pregnant women belonging to different parity and trimester from November 2015 to October 2016. Results: The underlying factor structure of the 28-item PPNMSS had explored using exploratory factor analysis. The final scale is retained with 15 items having considerable item loading under four major factors as follows: perceived social support, pregnancy-specific concerns, intimate partner relations, and financial concerns. Reliability of each of these dimensions was assessed using Cronbach's alpha. Convergent and divergent validity of the scale was assessed by correlating the scores with perceived stress scale and the World Health Organization (five) well-being index (1998 version). Conclusions: As a comprehensive scale, PPNMSS is efficient to measure PNMS, which facilitates an early detection of stress and depression among pregnant women and timely intervention by health care professionals. -
No right is absolute: the need for a more responsible use of social media
[No abstract available] -
Nonlinear optical studies of sodium borate glasses embedded with gold nanoparticles
Optical glasses possessing large third-order optical nonlinear susceptibility and fast response times are promising materials for the development of advanced nonlinear photonic devices. In this context, gold nanoparticle (NP)-doped borate glasses were synthesized via the melt-quench method. The nonlinear optical (NLO) properties of thus prepared glasses were investigated at different wavelengths (i.e., at 532nm using nanosecond pulses, at 750nm, 800nm, and 850nm wavelengths using femtosecond, MHz pulses). At 532nm, open aperture (OA) Z-scan signatures of gold NP-doped borate glasses demonstrated reverse saturable absorption (RSA), attributed to mixed intra-band and interband transitions, while in the 750?850nm region, the OA Z-scan data revealed the presence of saturable absorption (SA), possibly due to intra-band transitions. The NLO coefficients were evaluated at all the spectral regions and further compared with some of the recently reported glasses. The magnitudes of obtained NLO coefficients clearly demonstrate that the investigated glasses are potential materials for photonic device applications. 2018, Springer-Verlag GmbH Germany, part of Springer Nature. -
Teachers Technology Proficiency for Quality Learning and TeachingA Scoping Review
Teachers with solid technological backgrounds are better equipped to improve and transform the educational process to achieve a high-quality education. The Arksey and O'Malley framework was adopted for this scoping review, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to choose journals. The study aimed to analyze international studies to ascertain the authors study design, teachers ICT proficiency, the study's significance, and potential areas for improvement. The findings suggested that teachers ICT proficiency would increase instructional efficacy, ultimately raising educational standards. The Author(s) 2025. -
Edge and Fog Computing in Cyber-Physical Systems
The benefits of cyber-physical system advances include low latency and high bandwidth data processing in areas such as automotive, healthcare, and business automation. Traditional environments are often located in centralized and remote locations and cannot meet the demand. Edge computing and cloud computing have become fundamental concepts that will bring computing closer to the center of the data. Edge computing can reduce latency and bandwidth consumption by processing data on or near IoT devices. Fog computing adds another layer to this by distributing work and storage across multiple nodes, thus providing a scalable and flexible infrastructure. This article discusses the principles, benefits, and challenges of integrating edge and cloud computing into a CPS environment. It leverages the power of proximity-based edge computing and the centralized capabilities of cloud computing to provide scalable, instantaneous responses to CPS applications or time to optimize services. The demonstration shows a variety of things from smart cities to the use of IoT in healthcare in CPS. The article also covers some specific security and privacy issues and future directions in distributed computing, including the role of AI and 5G, which are supposed to offer additional resources in various applications. 2025 IEEE. -
Revolutionizing education with AI: ChatGPT as a personalized virtual tutor for E-learning platforms
It integrates AI into learning environments, which is transforming the conventional and online learning environment by coming up with something groundbreaking in the way of a personalized virtual tutor known as ChatGPT. The chapter looks into how ChatGPT uses the sophisticated natural language processing to present tailormade learning experiences to suit the different preferences, paces, and requirements of individual students. The instant explanations, feedback, and support on diverse subjects increase the engagement, motivation, and ultimate educational success of the students. The chapter also presents practical insights on technical integration, data security, and ethical considerations to ensure accountable use. It emphasizes the importance of combining AI with human oversight in creating balanced educational solutions. Through many examples and case studies, it demonstrates how ChatGPT is capable of connecting old learning methods with modern e- learning, thereby encouraging stakeholders to consider AI for greater personalization and transformation in education. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Impact of Demographicson Green Behavior
The need to preserve the environment, lower pollution levels, expand the amount of green space, and encourage environmentally responsible behavior has grown in recent years, all of which will contribute to a more sustainable society. This study seeks to determine the probability that demographic variables of students in higher education in Delhi NCR will influence their desire to participate in environmental education. Binary Logistics Regression has been used on the data gathered from 302 respondents and the model has been found to have been a good one as shown by Omnibus Test. It is found that 'Gender' and 'Field of Study' are the two most significant variables, which have a higher probability impact on students' willingness to join environmental education. Specifically, female students vis-vis male students and students with engineering & and science background vis-vis other students have more chance of joining environmental education courses. 2024 IEEE. -
Green Minds, Green Future: Impact of Environmental Education on Students Attitudes and Intentions
The objective of this research is to examine the effect of environmental education on green behavior mediated through environmental awareness, environmental attitude, and behavioral intentions, as mediating variables. The sample population comprised of the students of various universities of Delhi, National Capital Region (NCR), as this region of the country has the highest level of environmental pollution and therefore it is the most appropriate population for this study. One thousand questionnaires were shared among students of Delhi, NCR via Google Form out of which 689 responses were received and analyzed using structural equation modeling (SEM). The results exhibited the association between environmental education and green behavior which was significantly mediated by awareness, attitude, and behavioral intention. The findings of the study have implications for both research and practice. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Sustainable practice in fashion retail
This chapter emphasizes the urgent need for the global fashion industry to embrace sustainability due to its significant environmental impact. Highlighting issues like overconsumption, waste, and resource depletion, it critiques the "take, make, dispose" model and advocates for circular fashion, promoting reuse, repair, and recycling to extend clothing lifespans. Ethical sourcing, innovative biodegradable materials like Pinatex, and green operations in retail are explored as pivotal shifts. Local shopping models, sustainable manufacturing, and consumer demand for eco-friendly products are addressed, with tools like carbon footprint calculators and eco-labels aiding responsible consumption. Technological innovations such as AI, blockchain, and AR are presented as transformative, minimizing waste, enhancing transparency, and reducing overproduction. Challenges like high costs, fast fashion preferences, and limited recycling methods are discussed alongside solutions like strategic collaborations and R&D investments. 2025, IGI Global Scientific Publishing. All rights reserved.