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Human Resource Management in Digital India
The business entities of today are aware of the vital role played by technological interventions in value creation. HR technological interventions are no exceptions either. These interventions are aligned to business goals and help businesses achieve their bottom lines. Nevertheless, some business owners are apprehensive about the way forward while adopting technology. This chapter focuses on the various technologies that aid HR functions, its implementation framework keeping in perspective the key apprehensions, considerations and competency requirements. The chapter highlights few Indian organizations that have adopted it. The findings show that emphasis is laid on business value creation for stakeholders due to HR technology adoption. 2023 by World Scientific Publishing Co. Pte. Ltd. All right reserved. -
Responsible Service of Alcohol: An Evaluation of Policies and Practices of Five Star Hotels in Karnataka
Networking and socializing has been a human practice since ancient times and alcohol has been the social lubricant ??yesterday, today and also tomorrow. While we cannot trace its origin to a particular culture or civilization, its role and impact has been recorded in ancient texts and literature across cultures. A person can get drunk for a few rupees or spend a few lakhs for the same. It is consumed across social classes- by a daily wage worker to a business tycoon. The only thing differentiating the two being the price he has paid for the drink and the glass he is having it from. Even though the price and glass differs the effect it has on a person is more or less the same. This research and study is based on the belief that alcohol in itself is not the major cause of all the issues and troubles it is blamed for, but it is the nature and manner in which it is treated, consumed and served. This study is based on the latter aspect, ????the service of alcohol???. As mentioned in the previous paragraph, alcohol is a social lubricant and bars and restaurants have always been a popular place for socializing. The people who deal with the sale and service of alcoholic beverages along with the management and owners have a moral responsibility to ensure that alcohol is both served and consumed responsibly. This practice of Responsible Beverage Service or Responsible Service of Alcohol might look simple and easy on paper but to practice it, is a different story! It involves the support and approval of all the stakeholders. The owner and management on their part have to compromise on the earnings from the extra sale alcohol. The server has the additional responsibility of checking that his customers are not getting intoxicated and that he is following all the rules and regulations associated with alcohol service and above all the consumers too have to support and accept responsible service practices by the establishment. This study has looked into the practice of Responsible Beverage Service followed in the bars and restaurants in five star hotels, in the state of Karnataka. The initial study involved a review on early research and study on Responsible Beverage Service, Its impact on controlling alcohol abuse and intoxication, Responsible Beverage Service practices and various other dimensions and issues associated with Responsible Service of Alcohol. VII This research has focused on both the consumer as well as the server???s perspective on Responsible Beverage Service. The primary data for the study was collected from both consumers and hotels through a structured questionnaire, followed by data analysis using the appropriate tool. The findings give an insight and understanding into the acceptance of responsible beverage service in the state. What works and what needs to be improved? The practices which has the most impact in controlling alcohol abuse and answers to other questions associated with the study. -
Hyperspectral Image Classification Using Denoised Stacked Auto Encoder-Based Restricted Boltzmann Machine Classifier
This paper proposes a novel solution using an improved Stacked Auto Encoder (SAE) to deal with the problem of parametric instability associated with the classification of hyperspectral images from an extensive training set. The improved SAE reduces classification errors and discrepancies present within the individual classes. The data augmentation process resolves such constraints, where several images are produced during training by adding noises with various noise levels over an input HSI image. Further, this helps in increasing the difference between multiple classes of a training set. The improved SAE classifies HSI images using the principle of Denoising via Restricted Boltzmann Machine (RBM). This model ambiguously operates on selected bands through various band selection models. Such pre-processing, i.e., band selection, enables the classifier to eliminate noise from these bands to produce higher accuracy results. The simulation is conducted in PyTorch to validate the proposed deep DSAE-RBM under different noisy environments with various noise levels. The simulation results show that the proposed deep DSAE-RBM achieves a maximal classification rate of 92.62% without noise and 77.47% in the presence of noise. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Determining the Impact of Adapted Yoga Training on Physical Functioning in Students with Mild Intellectual Disability
Background. Individuals with mild intellectual disability (ID) often encounter challenges in physical functioning, impacting their overall well-being and quality of life. Traditional exercise programs may not always be accessible or effective for this population due to various barriers. Adapted yoga programs have emerged as a promising alternative, offering tailored interventions to address the unique needs of individuals with ID. Objectives. The study aimed to close this gap by examining the effect of a structured, modified yoga programme on factors related to physical functioning. Materials and methods. A total of 40 students with mild ID, aged between 11 and 15 years, were selected from Special Schools in Coimbatore, Tamil Nadu. A quasi-experimental design was used in this study. The participants were divided into an experimental group undergoing an 8-week adapted yoga program and a control group maintaining regular activities. Physical function parameters were assessed using standardized tests measuring cardiorespiratory endurance, muscular strength and endurance, flexibility, body composition, and balance. The adapted yoga program, conducted by qualified instructors, comprised 8 weeks of sessions, 5 days a week, each lasting 45 to 60 minutes. Statistical analyses confirmed the normal distribution of data and employed paired sample t-tests to assess pre-and post-test differences, with SPSS version 20.0 used for analysis, setting the significance level at 0.05. Results. After undergoing 8 weeks of adapted yoga training, the results showed a significant improvement in the upper body strength (p < 0.04), lower body strength (p < 0.001), core strength (p < 0.002), flexibility (p < 0.00), and static balance (p < 0.00). However, there was no significant difference in body fat and cardiorespiratory endurance between adapted yoga training. Conclusions. This study highlights the potential of adapted yoga programs as an intervention for improving physical functioning in students with mild ID. These findings indicate that the imlementation of adapted yoga can be a valuable and accessible intervention for enhancing physical functioning in this population. Yuvaraj, D., Dibakar, D., Prem, K. G., Aravindh, M., Ramesh, A. J., & Alphi, G. S., 2024. -
Influence of Autonomous Sensory Meridian Response on Relaxation States: An Experimental Study
Multiple studies have stated that autonomous sensory meridian response (ASMR) induces relaxation. ASMR is defined as a static tingling-like sensation across the scalp and back of the head, experienced by some people in response to specific audio and visual triggers like tapping, whispering, and slow hand movements. This study explores the relaxation states and the stress states on which ASMR videos have the highest impact. Data from 60 college students with a mean age of 22 years and a standard deviation of 1.12 were collected for this study, among which 30 were assigned to an experimental group and 30 were assigned to a control group single blindly. The relaxation states and stress states were measured using Smith Relaxation Scale Inventory (SRSI) for the pretest and Smith Relaxation Posttest Inventory (SRPI) for the posttest. The experimental group watched an ASMR video, and the control group watched a neutral video between the pretest and posttest. SPSS version 16 was used for data analysis. The result suggested a significant increase in sleepiness after watching the ASMR video (significant difference). 2021 International Society for Neurofeedback and Research. All rights reserved. -
Computational investigation into the solvent effect, electron distribution, reactivity profile, pharmacokinetic properties and anti-cancer action of Hemimycalin C
This work consists of DFT studies and biological evaluation of the marine alkaloid Hemimycalin C. The DFT calculations include energy minimisation, reactivity analysis of the frontier molecular orbitals, electronic transition studies (UV spectra generation), molecular electrostatic potential colour map analysis (MEP), and natural bond orbitals (NBO) studies. Non-linear optical (NLO) properties estimation is also performed to obtain the first-order hyperpolarizability, mean polarizability and dipole moment of Hemimycalin C. The solvent methanol emerges as the most interesting among the polar solvents employed in this study, as it impacts the properties of Hemimycalin C to a significant extent. Multiwfn software is used for topological analyses, which include the calculation of Reduced Density Gradient (RDG), Localised Orbital Locator (LOL) maps), and Electron Localisation Function (ELF). The computed ADMET profile indicates that the molecule is a potent lead (drug candidate) as the medicinal chemistry parameters are mostly within the optimal range. The Ramachandran plots are also computed to show the stability and quality of the target proteins, by computation of the permitted psi and phi angles. The complexes of the ligand are docked using AutoDock Tools against blood cancer receptors to obtain good binding affinity values. 2025 Elsevier B.V. -
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X-Tract: Framework for Flexible Extraction of Features in Chest Radiographs for Disease Diagnosis Using Machine Learning
Various types of medical images are used as diagnostic tools for identifying pathologies in human bodies, and in this research, chest X-ray images are used as diagnostic tools. Several pre-built models are created by the participants of ImageNet competitions for non-medical images, and these models are also being used in medical image classification; for example, Khan et al. (Comput Methods Prog Biomed 196:105581, 2020) developed a model called Coronet and Narayan Das et al. (IRBM 1:16, 2020) proposed a deep transfer learning-based model. Instead of using the pre-built models, a different approach was taken to address this problem. A framework was created to extract the frequency and spatial domain-based features, along with the raw statistics of the images. The model proposed in this article using the SVM algorithm has reached accuracy levels ranging from 91% to 97% and sensitivity of 92% to 96% on various samples of test data of over 400 images. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Heat transfer optimisation through viscous ternary nanofluid flow over a stretching/shrinking thin needle
The current investigation interprets the flow and the thermal characteristics of the ternary nanofluid composed of MoS 2, ZnO, and SiO 2 spherical nanoparticles and water. The resulting nanofluid is (Formula presented.) where (Formula presented.) act as the base fluid which help in the flow and the nanoparticles contribute to enhancing the heat conductivity. The flow is assumed to occur across a thin needle whose surface is maintained at a higher temperature than the surroundings. The mathematical model is framed by incorporating radiation introduced by Rosseland in terms of partial differential equations (PDE). This system of equations governs the flow and thermal properties of fluid which are converted to a system of ordinary differential equations (ODE). The major outcomes of the study indicated that the increase in the amount of molybdenum disulfide enhanced the heat conducted by the nanofluid whereas it reduced the flow speed. The positive values of the heat source/sink parameter caused the heat conduction of the nanofluid to go high. 2023 The Author(s). Published with license by Taylor & Francis Group, LLC. -
Thermal optimisation through the stratified bioconvective jetflow of nanofluid
Bioconvection is a fascinating phenomenon observed in various biological systems, where the motion of motile microorganisms generates fluid flow patterns. This article explores the occurrence and characteristics of bioconvection within the context of a jet flow. The study of bioconvection in jet flow involves the interaction between motile microorganisms and the fluid dynamics of the surrounding medium. Microorganisms such as bacteria and algae are known to exhibit directed swimming behavior, which can lead to the formation of dynamic flow structures. Investigating the mechanisms underlying bioconvection in jet flow requires a multidisciplinary approach encompassing fluid dynamics, microbial ecology, and mathematical modeling. Experimental techniques, such as microscopy and particle image velocimetry, along with computational simulations, are employed to analyze the complex interactions between microorganisms and the fluid flow. In this regard, a supportive mathematical model is designed using partial differential equations (PDEs) which are later transformed into ordinary differential equations using similarity transformations. The resulting system of equations is solved using the RKF-45 method and the outcomes are recorded in tables and graphs. The consideration of thermophoresis has shown a significant impact on the heat and mass transfer of the jet flow and both these profiles are observed to increase with thermophoresis. Meanwhile, the Schmidt number decrease their respective mass profiles. Furthermore, the porosity is found to create a drag force which tends to oppose the fluid flow. 2023 Taylor & Francis Group, LLC. -
Perception to Control: End-to-End Autonomous Driving Systems
End-to-end autonomous driving systems have garnered a lot of attention in recent years, and researchers have been exploring different ways to make them work. In this paper, we provide an overview of the field with a focus on the two main types of systems: those that use only RGB images and those that use a combination of multiple modalities. We review the literature in each area, highlighting the strengths and limitations of each approach. We also discuss the challenges of integrating these systems into a complete end-to-end autonomous driving pipeline, including issues related to perception, decision-making, and control. Lastly, we identify areas where more research is needed to make autonomous driving systems work better and be safer. Overall, this paper provides a comprehensive look at the current state-of-the-art in end-to-end autonomous driving, with a focus on the technical challenges and opportunities for future research. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Text Summarization Techniques for Kannada Language
Text Summarization is summarizing the original text document into a shorter description. This short version should retain the meaning and information content of the original text document. A concise summary can help humans quickly understand a large original document better in a short time. Summarization can be used in many text documents, such as reviews of books, movies, newspaper articles, content, and huge documents. Text summarization is broadly classified into extractive Text Summarization (ETS) and Abstractive Text Summarization (ATS). Even though more research works are carried out using extractive methods, meaningful summaries can be attained using abstractive summary techniques, which are more complex. In Indian languages, very few works are carried out in abstract summarization, and there is a high need for research in this area. The paper aims to generate extractive and abstractive summaries of the text by using deep learning and extractive summaries and comparisons between them in the Kannada language. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Parametric Study on Compaction Characteristics of Clay Sand Mixtures
The behaviour of fine-grained soils can be attributed to their mineral composition and the amount of fines present in them. The present study aims to determine the effect of mineral composition and quantity of fines on the Atterberg limits and compaction characteristics and to determine the correlation between them. Two types of fine-grained artificial soil mixtures were prepared in the laboratory representing kaolinitic and montmorillonitic mineral compositions.The amount of fines was varied at 10% intervals, from 50 to 100%. The Atterberg limits like liquid limit, plastic limit, shrinkage limit, and compaction characteristics like maximum dry density (MDD) and optimum moisture content (OMC) for two compaction energy levels, i.e. standard proctor (SP) and modified proctor (MP) tests, were determined. The correlations were developed between percentage fines and Atterberg limits and similarly between percentage fines, Atterberg limits, and compaction characteristics for artificial mix proportions. The developed correlations were used to predict the properties of natural soil samples, and the predicted and actual values are compared. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Investigating Key Contributors to Hospital Appointment No-Shows Using Explainable AI
The healthcare sector has suffered from wastage of resources and poor service delivery due to the significant impact of appointment no-shows. To address this issue, this paper uses explainable artificial intelligence (XAI) to identify major predictors of no-show behaviours among patients. Six machine learning models were developed and evaluated on this task using Area Under the Precision-Recall Curve (AUC-PR) and F1-score as metrics. Our experiment demonstrates that Support Vector Classifier and Multilayer Perceptron perform the best, with both scoring the same AUC-PR of 0.56, but different F1-scores of 0.91 and 0.92, respectively. We analysed the interpretability of the models using Local Interpretable Model-agnostic Explanation (LIME) and SHapley Additive exPlanations (SHAP). The outcome of the analyses demonstrates that predictors such as the patients' history of missed appointments, the waiting time from scheduling time to the appointments, patients' age, and existing medical conditions such as diabetes and hypertension are essential flags for no-show behaviours. Following the insights gained from the analyses, this paper recommends interventions for addressing the issue of medical appointment no-shows. 2024 IEEE. -
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Machine Learning based Plant Disease Identification by using Hybrid Nae Bayes with Decision Tree Algorithm
Artificial intelligence or machine learning as a domain started as a distinct domain marketplace for enthusiasts. Over an extended period of time, this has evolved into an industry with boundless potential. This is the focal point of a plethora of technologies like real-time analytics, deep learning in computer science. It's inherent to various customer needs such as fault detection, home automation, health monitoring devices as well as appliances, and multiple RPM devices Artificial intelligence which has been tested and trained to recognize and determine a plethora of flaws and inaccuracies. This could be intriguing procedures in day-to-day applications. An unimaginable number of prediction models, packages, libraries as well as sensors are utilized to sieve through flaws with the aid of mobile app development and other multispectral sensors. These trendy devices have become ever present and a part of our extensive routine. The demand for dependable and efficient algorithms is satisfied while implementing these devices. The objective primarily dictates emphasis on the prediction of plant diseases in the agricultural arena in reality by providing aid in the field of agriculture, and industry. In this case, the device incorporates a database which stores and keeps track of previously detected flaws or defects. In addition, the history of detected plant infections is maintained in an online repository. This can help with the forecast of the defects within the gadgets that are to be enhanced. Furthermore, the suggested approach of this text inculcates the invigilation of every leaf in the plant via machine learning model. Hence, this approach of implementation limits interaction of humans with the interface and it detects disease ridden plants efficiently with accuracy. The plant disease identification problem is to solve the proposed hybrid Nae Bayes with Decision Tree algorithm. The proposed model provides higher accuracy level compare to the regular model. 2023 IEEE. -
Photocatalytic seawater splitting for hydrogen fuel production: impact of seawater components and accelerating reagents on the overall performance
The future fuel, hydrogen, is a clean, sustainable energy source with a substantial density of energy per unit volume/weight. Breakthroughs in hydrogen production, storage, and transportation are essential to meet the sustainable global energy demands. Solar-to-hydrogen conversion through water-splitting reactions (via photo/electro/photoelectro-processes) is a promising strategy for producing green hydrogen fuel. Specifically, the photocatalytic hydrogen generation reaction, mimicking artificial photosynthesis, is a simple and cost-effective method adopted for solar-hydrogen production. Various semiconductor photocatalysts and hybrid photocatalytic systems have been developed to address the sluggish kinetics and selectivity of pristine water/seawater splitting reactions. Recently, seawater has been used as feedstock for large-scale hydrogen production to advance the field and alleviate the scarcity of freshwater sources. This review article, therefore, aims to highlight the importance of seawater splitting reactions using different photocatalytic systems. A brief introduction to the fundamentals, historical progress, and mechanism of the seawater splitting reaction is presented. The impact of seawater components and accelerating reagents on the intrinsic performance of water splitting catalysts is discussed in detail, followed by an elaborate discussion of natural water and artificial seawater splitting with emphasis on onerous photocatalyst designs. Finally, the current challenges and opportunities of saltwater electrolysis for sustainable hydrogen fuel generation and applications are discussed. 2023 The Royal Society of Chemistry. -
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Expanding the Notion of Personal Well-Being During COVID-19 Campus Closure in India: Results from a Mixed-Methods Study with Members of Higher Education
The COVID-19 pandemic has challenged lives globally in unprecedented ways. While numerous studies have discussed the impact of this pandemic on human lives, this descriptive study examined how this pandemic affected personal well-being (PW) for members of Indian higher education in the early phase of the pandemic in 2020 when there were no vaccines and remedies available. Research participants (n = 551) were faculty members, graduate students, and non-teaching staff in Indian higher education. At the time of data collection, when all campuses were closed, all participants were functioning in their roles in the academic communities via virtual platforms. This descriptive study, based on a mixed-methods research design with concurrent triangulation strategies, collected data from all regions of India. Resulting data identified and discussed the impact of the pandemic on six domains of PW in the life of participants: (a) self-care; (b) professional growth; (c) quality of interrelationship within the family; (d) relationships with significant others outside of the family; (e) process of experiencing/facing and addressing challenges; and, (f) relationship with spirituality/transcendental dimensions. The relevance of the last domain may be unique to Indian participants socio-cultural context and ethos. The findings and discussion explain how PW is a composite of all these six domains, and the pandemic expanded the notion of PW for the members of Indian higher education. Further, the findings also provided a general orientation on how educational leadership teams and institutions can enhance at least three specific dimensions of their community members and thus increase the likelihood of improving the quality of their professional and personal life. The findings may also have relevance for academic communities worldwide and inform clinicians working with members of academic communities, educational institutions, and policymakers. Penerbit Universiti Sains Malaysia, 2024. -
Implementing strategic responses in the COVID-19 market crisis: a study of small and medium enterprises (SMEs) in India
Purpose: The COVID-19 pandemic presents unprecedented challenges for small and medium enterprises (SMEs) in emerging economies. This paper aims to examine how India's SMEs implement their strategic responses in this crisis. Design/methodology/approach: The study uses dynamic capability theory to explore the strategic responses of SMEs. Strategy implementation theory helps to explain how they implement innovative practices for outcomes. A research model defines the COVID-19 challenges, strategic responses and performance outcomes. The study reports the findings of an initial pilot study of 75 firms and follow-up case study results in the context of COVID-19. Findings: Firms choose their approaches according to their perceived market risks. Case studies illustrate that firms display diverse attitudes depending on their strategic direction, leadership vision and organizational culture. They achieve different outcomes by implementing specific styles of risk management practices (e.g. risk-averting, risk-taking and risk-thriving). Research limitations/implications: Although the study context is Indian SMEs, the findings suggest meaningful lessons for other emerging economies in similar crisis events. The propositions may be extended to future research in broad contexts. Practical implications: Even in the extraordinary COVID-19 market crisis, SMEs with limited resources display their strategic potential by recognizing their unique capabilities, translating them into effective actions and achieving desirable outcomes. Social implications: In the COVID-19 pandemic, top leaders' mental attitude, strategic perspective and routine practices are contagious. Positive leadership motivates both internal and external stakeholders with an enormous level of collaboration. Originality/value: This rare study of Indian SMEs provides a theoretical framework for designing a pilot survey and conducting a case study of multiple firms. Based on these findings, testable propositions are articulated for future research in diverse organizational and national contexts. 2021, Emerald Publishing Limited.