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Levelling Up Organisational Learning Through Gamification: Based on Evidence from Public Sector Organisations in India
The concept of sustainability brought into focus the need for research into how to measure and achieve sustainable growth. The triple bottom line framework and the resource-based view of the firm suggest the need for organisations to look beyond profits and take into consideration the needs and effectiveness of its workforce. Research suggests that an effective workforce can be achieved through constant learning and development. Organisations have also expressed the need for training techniques that are more effective than the traditional methods. Gamification has been proposed as one such technique, and in the current study, the researchers evaluate the effectiveness of gamification in organisational training. For the purpose of the current study, 120 participants were chosen from public sector organisations in India. This is primarily because the technology-enhanced training effectiveness model (TETEM) suggests that the effectiveness of gamification would depend on the culture of the organisation, and prior research has been based in privately owned firms. The findings are in line with the theory of gamified learning and suggest that participants of the gamified module reported higher levels of learning, reaction and learner motivation. Additionally, learner motivation was found to strengthen the impact of gamification on the learning and reaction. The Author(s) 2022. -
Leveraging Big Data Analytics and Hadoop in Developing India's Healthcare Services
International Journal of Computer Applications, Vol-89 (16), pp. 44-50. ISSN-0975-8887 -
Leveraging digital yarn dyeing for colour consistency in apparel weaving
When compared to traditional processes, digital yarn dyeing provides substantial benefits in terms of color control, versatility, and environmental impact. However, technological obstacles and constraints exist. The promise of digital dyeing may be realized by carefully selecting technology, optimizing ink consumption, and adopting stringent quality control methods, resulting in improved colour constancy and a more sustainable textile sector. -
Leveraging ensemble learning for enhanced security in credit card transaction fraudulent within smart cities for cybersecurity challenges
In the age of digital transactions, credit cards have emerged as a prevalent form of payment in smart cities. However, the surge in online transactions has heightened the challenge of accurately discerning legitimate from fraudulent activities. This paper addresses this crucial concern by introducing a pioneering system for detecting fraudulent credit card transactions, particularly within highly imbalanced datasets, in the realm of cybersecurity. This paper proposes a hybrid model to effectively manage imbalanced data and enhance the detection of fraudulent transactions. This paper emphasizes the efficacy of the hybrid approach in proficiently identifying and mitigating fraudulent activities within highly imbalanced datasets, thereby contributing to the reduction of financial losses for both merchants and customers in smart cities. As cybersecurity in smart cities evolves, this paper underscores the significance of ensemble learning and cross-validation techniques in optimizing credit card transaction analysis and fortifying the security of digital payment systems. 2024, Taru Publications. All rights reserved. -
Leveraging history to invoke nationalism: from the annals of history to social engineering of present and future in Hindi cinema
Nationalism calls for ones loyalty and affiliation towards their chosen nation. Various versions of nationalism emphasise that one must prioritise said nation above themselves and their personal ethics, hence, allowing the nation to overpower the nationalists individuality. In this article, we use Critical Discourse Analysis to deconstruct the narratives of nationalism as portrayed in two popular films, viz. The Kashmir Files and Uri: The Surgical Strike, which are based on real historical eventsthe exodus of Kashmiri Hindus and the surgical strike by the Indian Army in retaliation to the Uri attack. Both films use narrative strategies to frame key historical events into certain ideological contexts, and hence they serve the populist purpose of swaying viewers opinion in favour of the dominant socio-political class. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Leveraging Machine Learning: Advanced Algorithms for Soil Data Analysis and Feature Extraction in Arid and Semi-arid Regions with Expert Systems
India is culturally diverse nation at large. There are two words of symphony one is tradition and second one is inherited agriculture. India has long historical advantage having conventional agricultural practices and the scope for it to dive into day to day life as agriculturist. Happiness shrinks as people grow into modern world current trend of agriculture faces a monument challenge and needs immediate address to survive. Now withstanding with this phrase of human life on earth its necessary to give more importance to soil rather than the existence. Soil health is more paramount in this equation, as it directly influences crop growth and yield. Traditionally, analysing a few key soil properties has been the cornerstone of soil treatment practices. However, this approach often overlooks the complex interplay between various soil characteristics. To overcome the above hurdle present research incorporates the method of multivariate data analysis with selective advanced algorithms in machine learning to find suitability to predict best fit algorithm in real time data sets in arid and semi-arid zones of kolar district in Karnataka. The purpose is to draw the attention of stake holders to leveraging the new technology to deploying them into effective assessment in building expert system to incorporate in regular use on handy devices. This penetrates the results by two extremely good classifications algorithms Decision Tree and Gradient Boosting emerged as winner with 99% accuracy. In contrast, Passive Aggressive and Linear SVC produced below average of 36% accuracy. The ensemble algorithms of SMOTE on Random Forest and Stochastic Decent Gradient produced the acceptable accuracy of 83%. This input helped dynamically to build ready to use expert systems for farmers. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. -
Lexical Richness of Adolescents Across Multimodalities: Measures, Issues and Future Directions
Lexical Richness (LR) is a scarcely researched subject in India. The objective of this paper is twofold: (i) To statistically inquire whether LR varies across three multimodalities: visual-only, audio-only, and audio-visual; and (ii) To see which of the two measures of LR (MATTR and Guiraud) is independent of text length and is best suited for short oral productions. 270 students across three types of schools were examined, out of whom 100 willingly completed all three oral tasks. The students were asked to retell the stories transacted in each modality in their own words. Randomization of sampling is done to mitigate the confounding modality bias. Additionally, the genre and parts of the storyline in each modality are similar. The students oral speech samples were recorded, transcribed and analyzed on WordCruncher and TextElixir software. The results revealed that there is statistically significant variance among the modalities. Furthermore, the Moving Average Type Token Ratio (MATTR) is seen to be independent of text length compared to Index of Guiraud. This study also throws light on the observations made during the study, pertinent issues in the field of education, and future directions for research on LR. 2023 IUP. All Rights Reserved. -
LGBTQIA+ rights, mental health systems, and curative violence in India
This commentary examines the spaceattitudeadministrative complex of mainstream mental health systems with regard to its responses to decriminalisation of nonheteronormative sexual identities. Even though the Supreme Court, in its 2018 order, instructed governments to disseminate its judgment widely, there has been no such attempt till date. None of the governmentrun mental health institutions has initiated an LGBTQIA+ rights-based awareness campaign on the judgment, considering that lack of awareness about sexualities in itself remains a critical factor for a noninclusive environment that forces queer individuals to end their lives. That the State did not come up with any awareness campaign as mandated in the landmark judgment reflects an attitude of queerphobia in the State. Drawing on the concept of biocommunicability, analysing the public interfaces of staterun mental health institutions, and the responses of mental health systems to the death by suicide of a queer student, I illustrate how mental health institutions function to further antiLGBTQIA+ sentiments of the state by churning out customerpatients out of structural violence and systemic inequalities, benefitting the mental health economy at the cost of queer citizens on whom curative violence is practised. Indian Journal of Medical Ethics 2022. -
Liberalisation and cashew industry: evidence from India (1965 to 2018)
We examine the impact of liberalisation on production, import, export and area under cultivation of cashew industry in India during 1965 to 2018 period using regression method. We divide data into two sub-periods. The liberalisation and pre-liberalisation period is from 1965 to 1991 and the post-liberalisation period covers the period from 1992 to 2018. We find that cashew production is not influenced post trade liberalisation. This study also finds trade liberalisation has a significant and positive impact on export. Further, we reveal an insignificant impact of liberalisation on import. This study show that the area under cultivation is not changed after the trade liberalisation. 2024 Inderscience Publishers. All rights reserved. -
Lie group analysis of flow and heat transfer of a nanofluid in conedisk systems with Hall current and radiative heat flux
A study of the rheological and heat transport characteristics in conedisk systems finds relevance in many applications such as viscometry, conical diffusers, and medical devices. Therefore, a three-dimensional axisymmetric flow with heat transport of a magnetized nanofluid in a conedisk system subjected to Hall current and thermal radiation effects is investigated. The simplified NavierStokes (NS) equations for the conedisk system given by Sdougos et al. [18] Journal of Fluid Mechanics, 138, 379404 are solved by using the asymptotic expansion method for the four different models, such as rotating cone with static disk (Model I), rotating disk with static cone (Model II), co-rotating cone and disk (Model III), and counter-rotating cone and disk (Model IV). The KhanaferVafaiLightstone (KVL) model along with experimental data-based properties of 37 nm Al2O3H2O nanofluid is considered. To obtain the transformations leading to self-similar equations from the NavierStokes (NS) and energy conservation equations, the Lie group technique is used. The self-similar nonlinear problem is solved numerically to examine the effects of physical parameters. There are critical values of the power exponent at which no heat transport from the disk surface occurs. Nanoparticles significantly enhance heat transport when both the cone and disk rotate in the same or opposite directions. The centrifugal force and thermal radiation improve the heat transport in conedisk systems. 2023 John Wiley & Sons Ltd. -
Light weight authentication protocol for WSN using ECC and hexagonal numbers
Wireless Sensor Network (WSN) is a spatially distributed network. It contains many numbers of distributed, self-directed, small, battery powered devices called sensor nodes or motes. In recent years the deployment of WSN in various application domains are growing in a rapid pace as with the upcoming boom of Internet of Things (IoT) and Internet of Everything (IoE). However, the effectiveness of the WSN deployment is restricted due to the constrained computation and power source. Hence, many researchers have been proposing new approaches and models to improve the efficiency of the domain specific WSN deployment procedures. Though, many research communities addressing various issues in WSN deployment, still the privacy and security of such networks are susceptible to various network attacks. Thus, it is necessary to practice different models for authentication and privacy preservation in a highly dynamic resource constrained WSN environment to realize the effectiveness and efficiency of the deployment. Hence, this paper addressing an authentication scheme that can reduce energy consumption without compromising on security and privacy. In order to provide a light weight authentication mechanism, this paper proposing an authentication mechanism for WSN deployment by combining the features of Elliptic Curve Cryptography (ECC) and Hexagonal numbers. The feature of ECC is used to reduce the key size and the effectiveness of generating hexagonal numbers is used for minimizing the energy consumption in a resource constrained WSN environment. The results of the proposed approach are evaluated with the different authentication models and the results were indicating that the proposed approach can perform better than the other approaches. 2019 Institute of Advanced Engineering and Science. -
Lightweight Model for Occlusion Removal from Face Images
In the realm of deep learning, the prevalence of models with large number of parameters poses a significant challenge for low computation device. Critical influence of model size, primarily governed by weight parameters in shaping the computational demands of the occlusion removal process. Recognizing the computational burdens associated with existing occlusion removal algorithms, characterized by their propensity for substantial computational resources and large model sizes, we advocate for a paradigm shift towards solutions conducive to low-computation environments. Existing occlusion riddance techniques typically demand substantial computational resources and storage capacity. To support real-time applications, it's imperative to deploy trained models on resource-constrained devices like handheld devices and internet of things (IoT) devices possess limited memory and computational capabilities. There arises a critical need to compress and accelerate these models for deployment on resource-constrained devices, without compromising significantly on model accuracy. Our study introduces a significant contribution in the form of a compressed model designed specifically for addressing occlusion in face images for low computation devices. We perform dynamic quantization technique by reducing the weights of the Pix2pix generator model. The trained model is then compressed, which significantly reduces its size and execution time. The proposed model, is lightweight, due to storage space requirement reduced drastically with significant improvement in the execution time. The performance of the proposed method has been compared with other state of the art methods in terms of PSNR and SSIM. Hence the proposed lightweight model is more suitable for the real time applications with less computational cost. 2024 by the author(s). -
Lightweight Spectral-Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral-spatial domain. In this article, we design an end-to-end spectral-spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial-spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. 1980-2012 IEEE. -
Lignin nanoparticles from Ayurvedic industry spent materials: Applications in Pickering emulsions for curcumin and vitamin D3 encapsulation
Lignin nanoparticles (LNP), extracted from spent materials of Dashamoola Arishta (Ayurvedic formulation), shared a molecular weight of 14.42 kDa with commercial lignin. Processed into LNPs (496.43 0.54 nm) via planetary ball milling, they demonstrated stability at pH 8.0 with a zeta potential of ?32 0.27 mV. Operating as Pickering particles, LNP encapsulated curcumin and vitamin D3 in sunflower oil, forming LnE + Cu + vD3 nanoemulsions (particle size: 347.40 0.71 nm, zeta potential: ?42.27 0.72 mV) with high encapsulation efficiencies (curcumin: 87.95 0.21%, vitamin D3: 72.66 0.11%). The LnE + Cu + vD3 emulsion exhibited stability without phase separation over 90 days at room (27 2 C) and refrigeration (4 1 C) temperatures. Remarkably, LnE + Cu + vD3 exhibited reduced toxicity, causing 29.32% and 34.99% cell death in L6 and RAW264.7 cells respectively, at the highest concentration (50 ?g/mL). This underscores the potential valorization of Ayurvedic industry spent materials for diverse industrial applications. 2024 Elsevier Ltd -
Lignite-derived nanocarbon as surface passivator and cosensitizer in dye-sensitized solar cell
Interfacial exciton recombination and narrow absorption region are two bottlenecks that limit the performance of a dye-sensitized solar cell (DSSC). The present study focuses on improving the solar cell's efficiency by utilizing a lignite-derived nanocarbon that behaves as a surface passivator and cosensitizer. Incorporating nanocarbon enhanced the spectral absorption region of the N719 dye with a bathochromic shift and played the role of a cosensitizer. In addition, the quenched photoluminescence spectra revealed that nanocarbon also aids in the swift transfer of electrons to the conduction band of TiO2 by reducing the exciton recombination and acting as a surface passivator. On measuring the fabricated DSSC under AM 1.5G irradiation with the intensity of 100 mW/cm2, the nanocarbon-based device exhibited an efficiency (?) of 9.02% with a photocurrent density of 20.45 mA/cm2, outperforming the pristine device (? = 6.21%). An enhancement of 45% in the power conversion efficiency was achieved. Thus, the results unveiled that nanocarbons derived from pollution-causing fuel synergistically aided in enhancing the performance of DSSC. 2024 Elsevier Ltd -
Lignocellulosic biomass for biochar production: A green initiative on biowaste conversion for pharmaceutical and other emerging pollutant removal
Lignocellulosic waste generation and their improper disposal has accelerated the problems associated with increased greenhouse gas emissions and associated environmental pollution. Constructive ways to manage and mitigate the pollution associated with lignocellulosic waste has propelled the research on biochar production using lignocellulose-based substrates. The sustainability of various biochar production technologies in employing lignocellulosic biomass as feedstock for biochar production not only aids in the lignocellulosic biomass valorization but also helps in carbon neutralization and carbon utilization. Functionalization of biochar through various physicochemical methods helps in improving their functional properties majorly by reducing the size of the biochar particles to nanoscale and modifying their surface properties. The usage of engineered biochar as nano adsorbents for environmental applications like dye absorption, removal of organic pollutants and endocrine disrupting compounds from wastewater has been the thrust areas of research in the past few decades. This review presents a comprehensive outlook on the up-to-date research findings related to the production and engineering of biochar from lignocellulosic biomass and their applications in environmental remediation especially with respect to wastewater treatment. Further a detailed discussion on various biochar activation methods and the future scope of biochar research is presented in this review work. 2024 Elsevier Ltd -
Line completion number of grid graph Pn Pm
The concept of super line graph was introduced in the year 1995 by Bagga, Beineke and Varma. Given a graph with at least r edges, the super line graph of index r, Lr(G), has as its vertices the sets of r-edges of G, with two adjacent if there is an edge in one set adjacent to an edge in the other set. The line completion number lc(G) of a graph G is the least positive integer r for which Lr(G) is a complete graph. In this paper, we find the line completion number of grid graph Pn Pm for various cases of n and m. 2021 Azarbaijan Shahid Madani University. -
Linear and Global Stability Analyses on the Influences of Thermal Non-Equilibrium and Non-uniform Gravity Field on DarcyBrinkmanBard Convection
Global and linear stability analyses of DarcyBrinkmanBard convection in a liquid-saturated porous medium with a non-uniform gravity field using the local thermal non-equilibrium (LTNE) model are investigated. Linear and quadratic (parabolic) gravity field profiles are considered in the analysis. The OberbeckBoussinesq approximation is assumed to be a valid and the stationary mode of onset of convection is shown to be the preferred mode due to the validity of the principle of exchange of stabilities. Critical values of wavenumber and thermal Rayleigh number are obtained numerically using the higher-order Galerkin technique. The effect of an increase in the gravity fields strength is to delay the onset of convection, and to a growth in convective cell size. Further, linear convective profile is found to postpone convection compared to the quadratic one. Global stability ensures the existence of subcritical motions in the case of a non-uniform gravity field. In contrast, subcritical motions do not exist in constant gravity in LTE and LTNE situations. A non-uniform gravity field has a significant influence on the convective instability in a liquid-saturated high-porosity medium, lesser influence in the case of a low porosity medium and least in the case of a clear fluid layer. 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Linear and non-linear analyses of double diffusive chandrasekhar convection with heat and concentration source in micropolar fluid with saturated porous media under gravity modulation
In this paper, linear and non-linear analysis of Double-Diffusive convection in the presence of magnetic field and gravity modulation with heat and concentration source in a micropolar fluid is studied by assuming the strength of heat and concentration source same. The expression for Rayleigh number and correction Rayleigh number are obtained using regular perturbation method. The effects of parameters on heat and mass transport is investigated using non-linear analysis by deriving eighth order Lorenz equation. It is found that coupling parameter and Chandrasekhar number stabilizes the system. Whereas internal Rayleigh number and Darcy number destabilizes the system. 2020 International Association of Engineers. -
Linear and non-linear analyses of double-diffusive-Chandrasekhar convection coupled with cross-diffusion in micropolar fluid over saturated porous medium
Purpose: The problem aims to find the effects of coupled cross-diffusion in micropolar fluid oversaturated porous medium, subjected to Double-Diffusive Chandrasekhar convection. Design/methodology/approach: Normal mode and perturbation technique have been employed to determine the critical Rayleigh number. Non-linear analysis is carried out by deriving the Lorenz equations using truncated Fourier series representation. Heat and Mass transport are quantified by Nusselt and Sherwood numbers, respectively. Findings: Analysis related to the effects of various parameters is plotted, and the results for the same are interpreted. It is observed from the results that the Dufour parameter and Soret parameter have an opposite influence on the system of cross-diffusion. Originality/value: The effect of the magnetic field on the onset of double-diffusive convection in a porous medium coupled with cross-diffusion in a micropolar fluid is studied for the first time. 2020, Emerald Publishing Limited.