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Environmental Concern in TPB Model for Sustainable IT Adoption
Rapid advancement in technology and continuous environmental degradation has attracted the attention of practitioners toward sustainable solutions. This study aims to investigate educated millennial beliefs and behavior toward sustainable IT practices. The Theory of Planned Behavior (TPB) model deployed in the study was extended through perceived environmental responsibility. A survey was conducted to examine the sustainable IT adoption behavior of millennial in the National Capital Region, Delhi India. Variance based partial least square structure equation modeling was employed to evaluate the hypothesized model. Findings of the study confirm environmental concern (ER) a precursor for attitude (ATT), perceived behavioral control (PBC), and subjective norm (SN). Further, there is a significant positive influence of ATT, PBC, and SN on the adoption intention of sustainable IT practices, followed by the effect of adoption intention on actual adoption behavior. Study disseminates valuable insights to policymakers and marketers to formulate strategies and policies to attain sustainability through sustainable IT practices. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Characteristic Mode Analysis of Metallic Automobile Logo Geometry
This paper presents a characteristic mode analysis of a few popular automobile logo geometries. It is performed to get an insight into the physical behavior of those geometries which can be employed as a radiating element, such as an antenna. Such an analysis helps design multi-band and multi-mode antennas suitable for 5G sub-6 GHz bands. The resonant behavior, bandwidth capability, and modal current distribution analysis are presented for various modes of different automobile logo geometries, demonstrating that Audi, Suzuki, and Volkswagen logos show multi-band performance. Moreover, due to having symmetric modes, the BMW logo was found to be suitable for designing a circularly polarized antenna. 2023 IEEE. -
Characteristic Mode Analysis of Closed Metal Geometric Ring Shapes
In this study, the characteristic mode theory is used to better explain the physical behavior of a few simple closedshaped geometries. The bandwidth coverage, resonant behavior, and modal current distributions for several ringshaped geometries are shown and discussed. It has been demonstrated that the triangular, rectangular, and square ring geometries can result in multi-band performance, whereas the hexagonal, circular, square, and triangular rings are promising candidates for circularly polarized antenna designs. 2024 IEEE. -
Sustainable Computing: A Determinant of Industry 4.0 for Sustainable Information Society
Rapid advancement in technology and continuous environmental degradation have attracted the attention of practitioners toward sustainable solutions. This study intends to promote Industry 4.0 information society research by comprehending sustainable ICT adoption in businesses to promote sustainable information society (SIS). Further, it extends the theory of planned behavior model and deploys a quantitative research approach. The findings from PLS-SEM confirm the perceived environmental responsibility (PER), a precursor for attitude (ATT), perceived behavioural control (PBC), and subjective norm (SN). Further, there is a significant positive influence of ATT, PBC, and SN on the adoption intention of sustainable ICT practices followed by the effect of adoption intention on sustainable information society (SIS). This study bridges the literature gap through a novel attitude behavior gap model and provides a possible understanding of how businesses might contribute to the creation of sustainable development and information society. 2022 Nishant Kumar et al. -
Solution of a dengue fever model via fractional natural decomposition and modified predictor-corrector methods
In this paper, we solved a model of a well-known infectious disease called dengue fever via fractional natural decomposition and modified Predictor-Corrector (PC) methods. A study of the dengue epidemic in the Cape Verde Islands off the coast of West Africa in 2009 has been resumed here for a better understanding of the results. The results are obtained using Liouville-Caputo and new generalized Caputo-type fractional derivatives. The numerical simulations are presented for various orders of given derivatives. Existence and uniqueness analysis of the given problem are also performed in the new generalized Caputo sense. The explored results are verified using figures. The main target of this paper is to explore the different dynamics of the given dengue fever model via two types of fractional numerical algorithms. 2024 World Scientific Publishing Company. -
Advancing Image Security Through Deep Learning and Cryptography in Healthcare and Industry
Securing electronic health records (EHRs) in the Internet of Medical Things (IoMT) ecosystem is a key concern in healthcare due to the sector's differed environment. As the evolution of technology continues, ensuring the confidentiality, integrity, and accessibility of EHRs becomes more and more challenging. To enhance the confidentiality of healthcare picture data, this study explores the combined use of deep learning and cryptography methods. Through the utilization of weight analysis for improving encryption strength and the combination of chaotic systems to generate undetectable encryption patterns, it explores how deep neural networks can be modified for use in encryption. It also provides a survey of the present scenario of deep learning-based image detection of anomalies methods in working environments, such as network typologies, supervision levels, and assessment norms. Techniques in cryptography provide an effective means to protect confidential medical picture data while it's being transmitted and stored. Deep learning, on the other hand, has the ability to entirely change cryptography by providing robust encryption, resolution augmentation, and detection capabilities for medical image security. The paper outlines future research approaches to overcome these problems and tackles the opportunities and obstacles in medical image cryptography and industrial picture anomaly detection. Through this work, picture privacy in the healthcare and industrial sectors is advanced, opening the door to enhanced privacy, integrity, and availability of vital image data by overcoming the gap between deep learning and cryptography. 2024 IEEE. -
Play and Play Spaces for Global Health, Happiness, and Well-Being
Play has a significant role in an individuals learning and holistic development. Play and recreation are a need and right. Research on play indicates that the significance of play is neglected among the current generation. Play spaces are shrinking, and physical play is becoming extinct in most communities. This current scenario may or have led to poor physical and mental health outcomes. The proposed book chapter aims to present play and play spaces in physical and mental health. The literature of play theories in child development shows the role of play in socioemotional, physical, and cognitive development. The current paper brings together literature on play across the lifespan, highlighting how play and recreation impacts children, youth, adults, and older adults physical and mental health. The change in lifestyle patterns has contributed to the neglect of play and recreation. The paper throws light on the need for the attention of professionals and policymakers for interventions and advocacy at both local and global levels in promoting play and preserving natural play spaces. The Editor(s) (if applicable) and The Author(s), under exclusive license to Taylor and Francis Pte Ltd. 2022. -
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. -
Mixed convection 3D radiating flow and mass transfer of eyring-powell nanofluid with convective boundary condition
Three-dimensional mixed convection flow, heat and mass transfer of Eyring-powell fluid over a convectively heated stretched sheet is inspected in this paper. The encouragement of Brownian motion, thermophoresis, convective condition and thermal radiations are accounted. Appropriate transformations are used to reduce the principal PDE's into set of coupled highly nonlinear ODE's which are then solved numerically using RKF fourth-fifth order method. The consequence of several parameters on flow, heat and mass transfer characteristics are deliberated with the help of graphs and tables. It is observed that the temperature and concentration profiles diminish for higher values mixed convection parameter. Further, the temperature and its related boundary layer thickness is increases with increasing the Biot number and thermal radiation effects. 2018 Trans Tech Publications, Switzerland. -
Machine Learning Observation on the Prediction of Diabetes Mellitus Disease
Diabetes disease has become as one of the common syndromes in many of the age groups. Diabetes can result in high blood sugar levels, a heart attack, or heart disease. This is one of the fastest developing illnesses, and it requires regular care. After seeing the doctor and being diagnosed, the patient is typically compelled to obtain their reports. Because this procedure is time-consuming and costly, we have the option of using ML approaches to solve this problem. Our research aims to foster a framework prepared to do all the more precisely foreseeing a patient's diabetes risk level. To develop models, classification methods such as Logistic Regression, K-Nearest Neighbor, Support Vector Machine, and Random Forest Classifier are employed. The results indicate that the techniques are quite accurate. The result showed that the prediction with the Logistic Regression model acquired the highest accuracy. 2023 IEEE. -
Metaverse marketing: a review and future research agenda
Purpose: The metaverse represents a rapidly evolving digital environment that blurs the lines between physical and virtual reality, and it offers unique opportunities and challenges for businesses and marketers. The purpose of this study is to provide a comprehensive review of metaverse marketing research. The present study reviews the literature on metaverse to identify theories, contexts, gaps and methodologies using TCCM framework (Theories, Contexts, Characteristics and Methodology) to set a future research agenda. Design/methodology/approach: A review was conducted of 179 English papers related to metaverse marketing from 2010 to 2023 from the Scopus and Web of Science core collection after applying relevant filters using the TCCM framework. Findings: The findings suggest that the studies have inadequately distinguished metaverse as something that only builds interactive experiences that combine the virtual environment and the real world, whereas the theoretical domain of metaverse is dominated by studies in various domains. The applicability of metaverse marketing research is pertinent in various domains of the management field. The study explores various facets of metaverse marketing to capture its dynamic nature. Research limitations/implications: By presenting a comprehensive review, themes and knowledge gaps of the research on metaverse marketing, this study will enhance research output and provide valuable tools for future research on metaverse. Practical implications: By analyzing metaverse in marketing, the companies will be able to use this concept effectively to formulate innovative marketing strategies and personalized consumer experiences and understand consumer behavior. Furthermore, research into metaverse marketing will be helpful in offering predictions about future trends in consumer behavior, technology adoption and virtual world development. Originality/value: This study provides a thorough analysis of the current state of research on metaverse in marketing and provides a road map for further research in this area. 2024, Emerald Publishing Limited. -
Exploring the role of Python in self-supervised contrastive learning for generating medical imaging reports
This chapter investigates Python's involvement in self-supervised contrastive learning (SSCL) for medical imagery with report generation. The research highlights the relevance of SSCL as a method for creating medical imaging reports and the benefits of implementing it using Python. The literature review gives a complete overview of SSCL approaches in medical imaging and shows the advantages of SSCL implementation using Python libraries such as PyTorch, TensorFlow, and Keras. The study's methodology describes the research topics, survey design, methods of data gathering, and analytic procedures. The study named SSCL-GMIR findings indicate that several practitioners utilize SSCL in medical imaging using Python modules. This study highlights Python's significance in implementing SSCL for creating medical imaging report documents, offering researchers and practitioners a more efficient and effective method for producing accurate and informative reports and diagnoses. 2023, IGI Global. All rights reserved. -
Utilization of Iron Ore Tailings for the Production of Fly Ash - GGBS-Based Geopolymer Bricks
In India, million tons of manufacturing ravages such as ground-granulated blast furnace slag (GGBS), fly ash and mine tailings, are endangering. These ravages turn out to be injurious as they are landfilled close to the production sites and somewhere else. Since these manufacturing ravages include silica, alumina, calcium, etc., it is probable to formulate these as unprocessed resources to produce building substance which diminishes the carbon trace. In this circumstance, this analysis observes on utilizing iron ore tailings and slag sand as a substitution for clay or natural sand for the construction of steady geopolymer obstruct. Furthermore, in this analysis, geopolymer is utilized as a binder rather than cement. Expansion of geopolymer binder-oriented bricks with fly ash and GGBS has been implemented in this study. The analysis consists of automatic possessions of the geopolymer bricks. Sodium silicate (Na2SiO3) and sodium hydroxide (NaOH) resolution have been employed as alkaline activators. The proportion of alkaline liquid to aluminosilicate solid quotient and fraction of binder encompass foremost control on the force of brick. The bricks were casted and cured at ambient warmth. The compressive strength was tested at 7, 14 and 28 days. 2017 World Scientific Publishing Company. -
Impact of sentimental factors on stock portfolio returns an empirical analysis
This study aims to introduce an integrated model for understanding the influence of various sentimental factors in conjunction with macroeconomic factors on portfolio returns across ten industry sectors within the US market. These sentimental factors are categorized into market-wide, consumer, and individual stock market factors to assess their impact on industry portfolio returns. Employing the Autoregressive Distributed Lag (ARDL) model, the study evaluates the effects of macroeconomic and sentimental factors on stock market portfolio returns. The findings reveal a negative relationship between short-term interest rates and portfolio returns in specific industry sectors like manufacturing, telecom, and wholesale/retail. The study finds a positive relationship between the Hi-tech sector's risk spread and portfolio returns. Market sentimental factors positively influence portfolio returns of durable, non-durable, utility, and other sectors. Individual sentimental factors negatively impact portfolio returns in hi-tech, utility, durable, energy, and other sectors. The stock market-related individual, sentimental factor of the number of IPOs has a positive impact on portfolio returns in the energy sector and a negative impact on portfolio returns in other sectors. Consumer sentimental factors are significant positive determinants for portfolio returns in durable, energy, telecom, health, and other sectors. Discounts on closed-end funds may provide vital fundamental information regarding lower future earnings for stocks in the durable and energy sectors. The study provides valuable insights for investors to optimize their portfolio strategies in response to macroeconomic and sentimental factors within specific industry sectors. 2024 The Authors -
Modeling Environmentally Conscious Purchase Behavior: Examining the Role of Ethical Obligation and Green Self-Identity
Due to environmental degradation, using environment-friendly products has become necessary to reduce carbon emissions. However, the consumption of such products is still below expectations because these products are usually costlier than their traditional counterparts. The current study aims to investigate consumer behavior towards environment-friendly products using Ajzens theory of planned behavior as a theoretical model. The study seeks to examine the role of the key determinates of environmentally conscious purchase behavior, such as ethical obligation and green self-identity. A total of 386 responses were collected from consumers living in a few major cities of northern India using purposive sampling. The data were analyzed using structural equation modeling in Amos 22.0. The results demonstrated that attitudes towards environment-friendly products perceived behavioral control and green self-identity as the major determinants of green purchase intentions. In addition, attitude was reported to mediate the effect of ethical obligation on green purchase intentions and green self-identity was found to moderate the effect of attitude on green purchase intentions. Additionally, green self-identity was also reported to moderate the relationship between ethical obligation and attitude. The study adds value to the existing literature by signifying the role of green self-identity and ethical obligation in stimulating consumers green purchase intentions. The findings of the study are also meaningful for marketers and policymakers. 2023 by the authors. -
Transient analysis of the reinforced concrete framed structure with steel fibres when subjected to blast loads
In the recent past in major cities all over the world, public structures are vulnerable to blast loads caused by explosions either accidentally or intentionally. The purposeful causes are not on solidified military targets however on significant regular civilian structures, similar to business, monetary and urban focuses. The study of fortified solid Ground + 3 Storied structure exposed to impact burdens have picked up significance, as routinely the strengthened solid structures are not intended for shoot stacks the same number of the stacking codes due not command for the equivalent and because of the way that measuring the greatness of the impact burden is hard to appraise. In any case, the structures are defenceless to harm from the blast. To secure the life of individuals and to limit the harm to the structure, it has turned out to be basic to consider the impact of impact stacks too notwithstanding the customary burdens, considered according to the overarching codes, during the investigation and plan of every single open structure. The charge weights of the explosive used on the structure are 8kg, 16 kg and 24kg. The equivalent blast pressure subjected on the structure is determined, to study its corresponding effects for stand-off distances of 3000 mm and 6000mm using surface blast load. The behavior of the structure is studied by varying the parameters and verified which of these parameters can be critical to the performance of the structure. The response of the ground floor + 3 upper storied reinforced concrete skeletal structure is studied for understanding the variation of the displacements, strains and stresses for the parameters considered. The 3D modeling of structure and structural components were produced by utilizing of PTC CREO 3.0. Discretization (meshing) of structural also its components were used in HYPERMESH. Static analysis and blast load analysis was carried out using ANSYS. A reinforced concrete structure can be designed and constructed to passively control the effects of the blast loads on the structure by including steel fibers to the concrete to improve its performance by reducing the deflections and the strain rates based on the standoff distance and the charge weight used in the explosion. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
How Does Perceived Risk and Trust Affect Mobile Banking Adoption? Empirical Evidence from India
The emergence of high-speed internet (5G) services and the demonetization of the Indian currency by the Government of India in the year 2016 served as catalysts for the growth of banking services, such as internet/mobile banking. The main objective of the study was to investigate the role of perceived financial cost, perceived risk, and trust in the adoption of mobile banking services by users. The study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to explain the adoption of mobile banking services by young Indian customers. The data from 253 users of age between 1830 years were collected through a survey questionnaire and were analyzed using structural equation modeling with Amos 22.0. The results revealed that performance expectancy, effort expectancy, social influence, and perceived financial cost exhibited a significant positive influence on behavioral intentions. However, the facilitating conditions were found to exert no effect on actual use. In addition, the results demonstrate that both perceived risk and perceived trust moderate the relationship between behavioral intention and the actual use of mobile banking. The results of the study provide some novel insights into how perceived risk and perceived trust shape the interplay between behavioral intention and the actual use of mobile banking services. The inferences drawn from the study may enhance the understanding of the transformation of behavioral intention into the adoption and actual use of mobile banking services. 2023 by the authors. -
Analysis of the photo-thermal excitation in a semiconducting medium under the purview of DPL theory involving non-local effect
Non-local theory comprises a unique characteristics by analyzing the effects of all points of the body on a single point of the material. The present study enlightens the propagation of photo-thermal waves in a semiconductor by adopting the two phase lag theory of thermoelasticity in the frame of non-local effect. Normal mode analysis has been employed to obtain the exact expressions of the field quantities such as temperature, components of the displacement, carrier density, and components of the stress. Each field quantity is found to be influenced by the non-local parameter as well as phase lags. Quantitative results are determined in the time-domain by adopting a suitable technique of Laplace transform inversion which exhibit the influence of the non-locality effect on the distributions of field variables. Significant differences have been attributable to the studied fields due to the non-locality effect. Also, computational results are compared with the corresponding results obtained by using single phase lag theory proposed by Lord and Shulman (LS model)LS model single phase lag model (LS model). 2022, Springer Nature B.V. -
Characterization of thermal damage of skin tissue subjected to moving heat source in the purview of dual phase lag theory with memory-dependent derivative
This investigation is devoted to exhibit the thermal damage of skin tissue exposed to a moving heat source. Modelling of the problem is performed by adopting dual phase lag theory of bio heat transfer in context of memory dependent derivative. Laplace transform technique has been adopted to represent the analytical solutions of temperature and thermal damage of skin tissue. Thermal damages to the tissues are calculated by the extent of the denatured protein employing with the Arrhenius equation. In order to predict the significance of memory dependent derivative approach, computational results of temperature and thermal damage are evaluated in the frame of different kernel functions as well as time-delay. For the purpose of exhibiting the attractiveness of the present model, obtained results are compared with the results corresponding to the absence of memory dependent derivative. Also, the impact of the velocity of moving heat source has been precisely investigated on temperature variation and thermal damage of skin tissue using quantitative results. Authors believe that this study will be helpful to study the thermal treatment of several diseases such as hyperthermia. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Employee Attrition, Job Involvement, and Work Life Balance Prediction Using Machine Learning Classifier Models
Employee performance is an integral part organizational success, for which Talent management is highly required, and the motivating factors of employee depend on employee performance. Certain variables have been observed as outliers, but none of those variables were operated or predicted. This paper aims at creating predictive models for the employee attrition by using classifier models for attrition rate, Job Involvement, and Work Life Balance. Job Involvement is specifically linked to the employee intentions to turn around that is minimal turnover rate. So, getting justifiable solution, this paper states the novel and accurate classification models. The Ridge Classifier model is the first one it has been used to classify IBM employee attrition, and it gave an accuracy of 92.7%. Random Forest had the highest accuracy for predicting Job Involvement, with accuracy rate of 62.3%. Similarly, Logistic Regression has been the model selected to predict Work Life Balance, and it has a 64.8% accuracy rate, making it an acceptable classification model. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.