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Analysis and dynamics of the Ivancevic option pricing model with a novel fractional calculus approach
The aim of the current study is to capture the complex behavior of the Ivancevic option pricing (IOP) model using the (Formula presented.) -homotopy analysis transform method ((Formula presented.) -HATM) with novel fractional operator. The generalization of the Black-Scholes model with the nonlinear Schringer equation plays a pivotal role in financial mathematics in studying the option-pricing wave function associated with two parameters. Based on adaptive market potential and volatility constant with distinct initial situations, we hired three distinct cases to exemplify the ability of (Formula presented.) -HATM. The considered method is elegant unification of the (Formula presented.) -homotopy analysis and Laplace transform algorithms. The derivative of fractional order is projected with the Atangana-Baleanu (AB) operator. The fixed-point theorem is used to present the existence and uniqueness of the attained result for the considered model, and we hire five distinct initial conditions. The hired scheme is highly methodical and exact to analyze the insights of the complex system with integer and fractional order exemplifying associated areas of science, which can be observed using plots and table. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Determinants of adoption of digital payment services among small fixed retail stores in Bangalore, India
India is well on its way to becoming a trillion-dollar digital economy and the government is actively working towards it. Digital payment is taking up and gaining momentum in India. Digital payments have penetrated in all parts of life in India. But it is reported that digital payments are less penetrated among small vendors across the country. This study intends to identify and analyse the factors that determine the adoption of digital payment technologies among small fixed retail stores in tier 1 cities such as Bangalore. The study is based on primary data which is collected through well-structured questionnaires from small fixed retail merchants. The collected data are analysed to determine the factors affecting the adoption of digital payment services among small fixed retail merchants using appropriate statistical tools. The study has found that habit, pervasiveness, and operating costs are the factors that significantly affect the adoption of digital payment services among small fixed retail merchants. Copyright 2022 Inderscience Enterprises Ltd. -
Job satisfaction while working from home during the COVID-19 pandemic: do subjective work autonomy, work-family conflict, and anxiety related to the pandemic matter?
The imposed lockdown, due to the COVID-19 outbreak, resulted in the rise to a new normal of working from home. This study explores how the lockdown and the sudden shift in the working style affected the job satisfaction of employees in India. We examined the relationship of job satisfaction with work autonomy, and determined whether work-family conflict, and anxiety due to COVID-19 are negatively related to job satisfaction amongst employees working from home in India. Through a correlational research design, a total of 211 participants took part in the study, and only 200 of the data, representing a 95% response rate, were eligible for further analysis. The data were analyzed using Structural Equation Modeling, and the results showed that work-family conflict and anxiety related to COVID-19 have a negative correlation with job satisfaction, while work autonomy had a positive correlation with job satisfaction. Perceived work autonomy, work-family conflict, and anxiety related to the COVID-19 pandemic significantly predicted job satisfaction and accounted for an overall 37.8% of the variance in job satisfaction. The findings of the current study provide valuable insight into the consequences of a pandemic or similar uncontrollable event, and augmented the literature on organizational behavior where most employees are compelled to work remotely, either full-time or part-time. The theoretical and empirical implications of how work-family conflict and anxiety related to the COVID-19 pandemic negatively impact the job satisfaction of employees in India were discussed. Evaluation of the structural relationship (SEM) reveals that the overall exogenous constructs significantly predicted job satisfaction of employees working from home in India during the COVID-19 pandemic. 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Optimization of Abrasive Wear Parameters of Halloysite Nanotubes Reinforced Silk/Basalt Hybrid Epoxy Composites using Taguchi Approach
The demand for environmentally friendly and sustainable materials for nonstructural and structural applications grows by the day. Polymeric composites reinforced with fillers and fibres are considered to have increased strength and desirable wear resistance. Abrasive wear of industrial and agricultural based components are currently one of the most serious issue. Therefore, the current research reports on the influence of Halloysite-Nanotubes (HNTs) loading on the three body abrasive behavior of bi-directional silk fibre (SF) and basalt fibre (BF) reinforced epoxy (Ep) composites. Rubber wheel with dry sand abrasion testing in accordance with ASTM G65-16e1 was performed with four control parameters such as filler content, load, abrading distance and silica sand size. The tests were planned as per orthogonal array of Taguchi (L27). Significant impact of control factors were identified using ANOVA (Analysis of variance). The results demonstrated that adding HNTs to SF-BF/Ep nanocomposites significantly improved the wear resistance and the combination of A2, B1, C3 and D1 control factors yields the lower specific wear rate (SWR). Findings exhibit that the load and abrading distance were the most significant parameters affecting the abrasive wear of SF-BF/Ep nanocomposites followed by filler content and silica sand size. Microstructural features were observed via scanning-electron-microscopy (SEM). 2022 Published by Faculty of Engineering. -
Brand Love for Sports Apparels Among Indians: A Triangular Theory of Love Perspective
This study aims to evaluate the concept of brand love among the Indians in sports apparel industry. Drawing on Sternbergs (1986) triangular theory of love, we propose a three-dimensional brand love model. We further discuss the interrelationship between these variables and provide a theoretical model for explaining the concept using sports apparels. Then, this theoretical model is tested using empirical research undertaken among 327 respondents. These exploratory results indicated that the concept of brand love in India is similar to that of interpersonal love, contradicting the earlier finding in the field of brand love. These contradicting findings were attributed to the cultural differences between Eastern and Western cultures, especially in the field of extended self (Markus & Kitayama, 1991). These findings create the possibility for future research into brand love via the triangular theory of love to understand how the changes in the perceptions of self influence the brand love. 2022 Management Development Institute. -
ENVIRONMENTAL JURISPRUDENCE IN INDIA: A JOURNEY TOWARDS ATTAINING ECO-CENTRIC IDEALS
Environmental Law has had a long, arduous journey in India, but has been able to keep up with the many changes that have taken place, around the globe, and has helped shape India's environmental legal regime. By tracing the growth of environmental law, through different ages, and by highlighting some of those factors, which have contributed immensely to its growth, the idea is to identify certain false grounds and figure out ways to make environmental law more effective. By looking at it through a sociocultural lens, the aim is to examine as to whether culture, tradition and rituals can be imbibed into law or given a legal recognition, and thereby giving more power to law. The development of Earth Jurisprudence principles and the way in which it is sought to be imbibed in India and the challenges that it faces too are discussed. 2022 Universitat Rovira i Virgili. All right reserved. -
Behavioural drivers of access-based consumption among millennial and generation Z in India
The world of consumerism is very dynamic, and technology driven changes in the field of consumerism are unavoidable especially among new generation customers millennial and generation Z. The customers, especially in urban areas, gradually move from ownership-based consumption to access-based consumption. The purpose of this study is to explore the behavioural drivers of new generation customers towards access-based consumption. The study is descriptive in nature and employed a survey method for data collection. The drivers identified are tested through a quantitative study and the primary data are collected using online questionnaires. The study has also analysed the impact of behavioural drivers on current usage of access-based consumption as well as on willingness to use access-based consumption in the future. The study has found that sustainability is the only driver that significantly motivates access-based consumption in Indian urban areas. Copyright 2022 Inderscience Enterprises Ltd. -
Role of Need for Achievement on Decision making and Life Orientation of Young Adults
Purpose-To assess the role of need for achievement on decision making and life orientation of young adults. Design/methodology/approach-The data was collected from the participants using a questionnaire. The sample size is 100 young adults. The sampling technique used is convenience sampling, and the research design is a cross-sectional survey. It was hypothesised that individuals high in achievement motivation will also be high in life orientation level and there will be a positive correlation between achievement motivation and decision making. Findings The results of the study indicate that an individual high in achievement motivation will also be high in life orientation level and a positive correlation is found between achievement motivation and decision making. The other findings are that optimising decision-making styles is positively correlated with achievement motivation and a significant difference in achievement motivation between males and females is found, indicating a higher need for achievement in females as compared to males. Social Implications-The findings of the study are considerable with respect to the personal, professional, and educational development of young adults. As the research suggests, there is a positive relationship between decision-making styles, achievement motivation, and orientation towards life. Therefore, various decision-making styles can be introduced in the behavioural sciences subject domain. Higher achievement needs in females indicate their potential in various professional realms, and such platforms, if provided, can increase women's participation in the workforce, resulting in economic, social, and personal development for women as well as society. Originality/ Value The youth of a country are its greatest assets, and for an aspirational country, there is a need for a highly motivated task force. The research topic focuses on how motivated behaviour occupies a central position in personality and its relationship with decision-making style and orientation towards life. This study focuses on the need of the hour, which is harnessing our youth and exploring more about the achievement-oriented behaviour and optimistic outlook of young adults, which is the demographic dividend of the country. 2022 RESTORATIVE JUSTICE FOR ALL. -
Automated Risk Management Based Software Security Vulnerabilities Management
An automated risk assessment approach is explored in this work. The focus is to optimize the conventional threat modeling approach to explore software system vulnerabilities. Data produced in the software development processes are better leveraged using Machine Learning approaches. A large amount of industry knowledge around security vulnerabilities can be leveraged to enhance current threat modeling approaches. Work done here is in the ecosystem of software development processes that use Agile methodology. Insurance business domain data are explored as a target for this study. The focus is to enhance the traditional threat modeling approach with a better quantitative approach and reduce the biases introduced by the people who are part of software development processes. This effort will help bridge multiple data sources prevalent across the software development ecosystem. Bringing these various data sources together will assist in understanding patterns associated with security aspects of the software systems. This perspective further helps to understand and devise better controls. Approaches explored so far have considered individual areas of software development and their influence on improving security. There is a need to build an integrated approach for a total security solution for the software systems. A wide variety of machine learning approaches and ensemble approaches will be explored. The insurance business domain is considered for the research here. CWE (Common Weaknesses Enumeration) mapping from industry knowledge are leveraged to validate the security needs from the industry perspective. This combination of industry and company data will help get a holistic picture of the software system's security. Combining the industry and company data helps lay down the path for an integrated security management system in software development. The risk management framework with the quantitative threat modeling process is the work's uniqueness. This work contributes toward making the software systems secure and robust with time. 2013 IEEE. -
A Sampling-Based Stack Framework for Imbalanced Learning in Churn Prediction
Churn prediction is gaining popularity in the research community as a powerful paradigm that supports data-driven operational decisions. Datasets related to churn prediction are often skewed with imbalanced class distribution. Data-level solutions, like over-sampling and under-sampling, have been commonly used by researchers to address this problem. There are limited number of case studies that attempt to evolve these data-level solutions by integrating them with computationally advanced frameworks, like ensembles. Ensembles primarily employ algorithmic diversity using a fixed set of training instances to achieve superior performance. This study aims to introduce algorithmic diversity in ensembles by modifying the fixed set of training instances using diverse sampling strategies to increase predictive performance in imbalanced learning. Data is acquired from the world's largest open hotel commerce platform company. A four-part series of experiments is conducted to analyze the effectiveness of sampling techniques and ensemble solutions on model performance. A new sampling-based stack framework called 'Stacking of Samplers for Imbalanced Learning' is proposed. The framework combines the prediction capabilities of sampling solutions to stimulate the information gain of the meta features in ensemble. It is observed that the proposed framework leads to improvement in model performance with AUC of 86.4% and top-decile lift of 4.7 for customers of the hotel technology provider. Additionally, results show that the framework records a higher information gain for meta features used in a stack, compared to commonly used stack frameworks. 2013 IEEE. -
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. -
A privatised approach in enhanced spam filtering techniques using TSAS over cloud networks
Major problem over cloud networks is the effect of malicious code that protrudes its own activity without intend of network user in resource sharing. One such activity is the spam-filtering techniques which assumes the data with training and testing sets and also rely on fundamental classification through distribution. A privatised spam filtering approach is a classic problem which automatically recognises user context and incoming mail information relevance. To filter mail contents learning based methods, probabilistic based method trying to improve their accuracy but they cannot attain an improvement in identifying suspicious contents and also in segregating legitimate mail entries. Here a novel representation of structured abstraction scheme (SAS) used to generate abstraction in e-mail process using HTML tag content in e-mail and its algorithm for filtering such process of spam filtering is depicted. In this SAS methodology near duplicate matching process with HTML tag ordering will be processed and newly assigned position ordering were deliberated. The experimental setup shows that there will be a great improvement while filtering spam in accuracy of e-mail content while sharing in cloud networks. Copyright 2022 Inderscience Enterprises Ltd. -
Multi-layer Stacking-based Emotion Recognition using Data Fusion Strategy
Electroencephalography (EEG), or brain waves, is a commonly utilized bio signal in emotion detection because it has been discovered that the data recorded from the brain seems to have a connection between motions and physiological effects. This paper is based on the feature selection strategy by using the data fusion technique from the same source of EEG Brainwave Dataset for Classification. The multi-layer Stacking Classifier with two different layers of machine learning techniques was introduced in this approach to concurrently learn the feature and distinguish the emotion of pure EEG signals states in positive, neutral and negative states. First layer of stacking includes the support vector classifier and Random Forest, and the second layer of stacking includes multilayer perceptron and Nu-support vector classifiers. Features are selected based on a Linear Regression based correlation coefficient (LR-CC) score with a different range like n1, n2,n3,n4 a, for d1 used n1 and n2 dataset,for d2 dataset, combined dataset of n3 and n4 are used and developed a new dataset d3 which is the combination of d1 and d2 by using the feature selection strategy which results in 997 features out of 2548 features of the EEG Brainwave dataset with a classification accuracy of emotion recognition 98.75%, which is comparable to many state-of-the-art techniques. It has been established some scientific groundwork for using data fusion strategy in emotion recognition. 2022. International Journal of Advanced Computer Science and Applications. All Rights Reserved. -
Aquila Optimizer Based Optimal Allocation of Soft Open Points for Multi-Objective Operation in Electric Vehicles Integrated Active Distribution Networks
The appropriate position and sizing of soft open points (SOPs) for reducing the detrimental impact of electric vehicle (EV) load penetration and renewable energy (RE) variation on active distribution networks (ADNs) are provided in this study. Soft open points (SOPs) have been used to create a multi-objective framework that considers loss minimization and voltage profile enhancement. The non-linear multi-variable complicated SOP allocation problem is solved for the first time using a modern meta-heuristic Aquila optimizer (AO). The modified IEEE 33-bus benchmark and IEEE 69-bus ADNs are used in the simulations. Before SOPs, the average real power loss in IEEE 33-bus AND was 370.329 kW, but after SOPs, it was reduced to 259.356 kW (i.e., 29.96 percent reduction). Similarly, effective SOPs integration in the IEEE 69-bus resulted in a loss reduction of 81.07 percent. AO's computational efficiency is also compared to that of multiobjective particle swarm optimization (MOPSO), particle swarm optimization (PSO), and cuckoo search algorithm (CSA). The AO has produced better results in terms of lower losses, improved voltage profile despite variations in EV load penetration, and RE and load volatility in ADNs, according to the results 2022. International Journal of Intelligent Engineering and Systems.All Rights Reserved -
Secured personal health records using pattern-based verification and two-way polynomial protocol in cloud infrastructure
This present research proposes the digitalised healthcare system that enables patients to generate, aggregate and store in the form of personal health records (PHRs). This requires more attention on cost effectiveness and less response time on public cloud platform. The existing cloud platforms have failed to implement the systemic approach for immediate verification and correction models on increasing PHR datasets. The storage and computation are two prime factors. Moreover, cloud systems need more attention on security and privacy breaches. In this proposed model the publisher-observer pattern-based healthcare systems allow the patients to verify and correct the PHRs before any type of computations. The cloud system acts as a backend framework that offers openness and easy accessibility. The experimental segment ensures the computational cost and response time for multiple polynomial PHR variations. The details evaluation also ensures the security and privacy preservation on sensitive healthcare datasets. Copyright 2022 Inderscience Enterprises Ltd. -
Facile synthesis of novel SrO 0.5:MnO 0.5 bimetallic oxide nanostructure as a high-performance electrode material for supercapacitors
Perovskite bimetallic oxides as electrode material blends can be an appropriate method to enhance the supercapacitor properties. In the present research, SrO 0.5:MnO 0.5 nanostructures (NS) were synthesized by a facile co-precipitation method and calcinated at 750800C. Crystal structure of SrO 0.5:MnO 0.5 NS were characterized by X-ray diffraction, surface chemical composition and chemical bond analysis, and dispersion of SrO into MnO was confirmed by X-ray photoelectron spectral studies. Structural morphology was analyzed from scanning electron microscopy. Optical properties of SrO 0.5:MnO 0.5 NS were studied using UV-Visible spectrophotometer and SrO 0.5 and MnO 0.5 NS showed ?75nm grain, ? 64nm grain boundary distance, with two maxima at 261nm and 345nm as intensity of absorption patterns, respectively. The synthesized SrO 0.5:MnO 0.5 NS exhibited high specific capacitance of 392.8F/g at a current density of 0.1A/g. Electrochemical impedance spectroscopy results indicated low resistance and very low time constant of 0.2s ?73% of the capacitance was retained after 1000 galvanostatic charge-discharge (GCD) cycles. These findings indicate that SrO 0.5:MnO 0.5 bimetallic oxide material could be a promising electrode material for electrochemical energy storage systems. The Author(s) 2022. -
Psychometric Properties of the Interpersonal Emotion Regulation Questionnaire Among Couples in India
The aim of the present study was to translate the Interpersonal Emotion Regulation Questionnaire (IERQ) into the Tamil language and examine its psychometric properties in the Indian cultural context. Data were collected from a dyadic sample of 340 married heterosexual couples (N = 680) currently residing in India. The mean age of husbands was 39.57 (SD = 6.10; 26 ? range ? 58), and the wives was 35.33 (SD = 5.72; 23 ? range ? 54). Descriptive results indicated that husbands and wives reported similar levels of interpersonal emotion regulation. Confirmatory factor analysis showed a 20-item model with four factorsenhancing positive affect, perspective-taking, soothing and social modeling, similar to the original version, fits the data well. Furthermore, the multiple-group analysis indicated robust measurement invariance across gender (husbands vs. wives), family type ( joint vs. nuclear) and marriage type (arranged vs. love), indicating that the Tamil version of the IERQ operates similarly across these groups. Besides, the Tamil version of the IERQ showed good convergent and discriminant validity with measures of dyadic coping and relationship satisfaction. Implications for research and couples therapy in the Indian cultural context are discussed. 2022, PsychOpen. All rights reserved. -
Theoretical Study of Convective Heat Transfer in Ternary Nanofluid Flowing past a Stretching Sheet
A new theoretical tri-hybrid nanofluid model for enhancing the heat transfer is presented in this article. This model explains the method to obtain a better heat conductor than the hybrid nanofluid. The tri-hybrid nanofluid is formed by suspending three types of nanoparticles with different physical and chemical bonds into a base fluid. In this study, the nanoparticles TiO2, Al2O3 and SiO2 are suspended into water thus forming the combination TiO2-SiO2-Al2O3-H2O. This combination helps in decomposing harmful substances, environmental purification and other appliances that requires cooling. The properties of tri-hybrid nanofluid such as Density, Viscosity, Thermal Conductivity, Electrical Conductivity and Specific Heat capacitance are defined mathematically in this article. The system of equations that governs the flow and temperature of the fluid are converted to ordinary differential equations and are solved using RKF-45 method. The results are discussed through graphs and it is observed that the tri-hybrid nanofluid has a better thermal conductivity than the hybrid nanofluid. 2022. Shahid Chamran University of Ahvaz, Ahvaz, Iran. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0 license) (http://creativecommons.org/licenses/by-nc/4.0/). -
A Neuro Fuzzy with Improved GA for Collaborative Spectrum Sensing in CRN
Cognitive Radio Networks (CRN) have recently emerged as an important solution for addressing spectrum constraint and meeting the stringent criteria of future wireless communication. Collaborative spectrum sensing is incorporated in CRNs for proper channel selection since spectrum sensing is a critical capability of CRNs. According to this viewpoint, this study introduces a new Adaptive Neuro Fuzzy logic with Improved Genetic Algorithm based Channel Selection (ANFIGA-CS) technique for collaborative spectrum sensing in CRN. The suggested methods purpose is to find the best transmission channel. To reduce spectrum sensing error, the suggested ANFIGA-CS model employs a clustering technique. The Adaptive Neuro Fuzzy Logic (ANFL) technique is then used to calculate the channel weight value and the channel with the highest weight is selected for transmission. To compute the channel weight, the proposed ANFIGA-CS model uses three fuzzy input parameters: Primary User (PU) utilization, Cognitive Radio (CR) count and channel capacity. To improve the channel selection process in CRN, the rules in the ANFL scheme are optimized using an updated genetic algorithm to increase overall efficiency. The suggested ANFIGA-CS model is simulated using the NS2 simulator and the results are investigated in terms of average interference ratio, spectrum opportunity utilization, average throughput, Packet Delivery Ratio (PDR) and End to End (ETE) delay in a network with a variable number of CRs. 2022, Tech Science Press. All rights reserved. -
Stock Market Efficiency and COVID-19 with Multiple Structural Breaks: Evidence from India
The objective of the study is to investigate the influence of the coronavirus pandemic (endogenous crisis) on the stock market efficiency of India during the multiple break periods. The empirical analysis is performed using conditional heteroscedasticity and a small sample robust wild bootstrap automatic variance ratio test and automatic portmanteau test on a daily stock return data of two benchmark indices, that is, NIFTY and SENSEX. The empirical results demonstrate that the stock return of two indices deviates from market efficiency during some periods of the analysis, notably during the nationwide lockdown and peak periods of coronavirus cases in India. These findings indicate that changing stock market behaviour becomes more speculative and earns abnormal profits. To the best of the authors knowledge, this study provides the first evidence of investigating the variations in the stock market efficiency of India in response to this endogenous crisis. 2022 International Management Institute, New Delhi.