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Dynamics of public debt sustainability in major Indian states
This study empirically tests whether the public debt is sustainable or not at 22 major Indian states during 200607 to 201516. It employs the Bohn model for panel data, five alternative specifications and p-spline technique to analyze the issue at aggregate and disaggregate levels. While the results indicate that the debt is sustainable at the aggregate level, it is sustainable only in about 11 states. The results suggest that the fiscal reaction function is linear and the central grant-in aid is an important and a significant undermining factor of sustainability. If the grant-in-aid is excluded from the primary balance, there remain significant positive responses at the aggregate level. However, at the disaggregate level it is significant in only 11 states. Further, the most sustainable states fail to meet the no-Ponzi condition and so the policy intervention is required to improve the debt situation of the states where debt is unsustainable. 2019, 2019 Informa UK Limited, trading as Taylor & Francis Group. -
Dynamics of Sustainable Economic Growth in Emerging Middle Power Economies: Does Institutional Quality Matter?
The present study investigates the relevance of Institutional structures quality as a determinant of the GDP of the Emerging Middle Power Economies (MIKTA) which constitute predominantly middle-income countries, namely Mexico, South Korea, Indonesia, Turkey, and Australia over the timeframe of 19852016. In addition to institutional variables such as Government Stability, Bureaucratic Quality and Socioeconomic Conditions, the study uses productive factors (per worker capital, human capital) and a macroeconomic indicator (inflation) to show the GDP of the above-mentioned countries. The impact that institutional variables taken have on Efficient Environmental resources, Sustainability and their management has shown to have an impact on the rate of growth of the middle-income economies. To estimate a long-run relation, the study employs the Autoregressive Distributed Lag model, also known as the ARDL model, bringing in controls for cointegration, nonstationary, heterogeneity and cross-sectional dependency and accounts for a mixed order of integration of variables. The model indicates that capital per worker, socio-economic conditions, bureaucratic quality, human capital and inflation have a long-run effect on the GDP of a country. The paper concludes with a positive impact of institutional variables during both, the short-run and the long-run, for the de-pendent variable. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Dynamics of Sutterby fluid flow due to a spinning stretching disk with non-Fourier/Fick heat and mass flux models
The magnetohydrodynamic Sutterby fluid flow instigated by a spinning stretchable disk is modeled in this study. The Stefan blowing and heat and mass flux aspects are incorporated in the thermal phenomenon. The conventional models for heat and mass flux, i.e., Fourier and Fick models, are modified using the Cattaneo-Christov (CC) model for the more accurate modeling of the process. The boundary layer equations that govern this problem are solved using the apt similarity variables. The subsequent system of equations is tackled by the Runge-Kutta-Fehlberg (RKF) scheme. The graphical visualizations of the results are discussed with the physical significance. The rates of mass and heat transmission are evaluated for the augmentation in the pertinent parameters. The Stefan blowing leads to more species diffusion which in turn increases the concentration field of the fluid. The external magnetism is observed to decrease the velocity field. Also, more thermal relaxation leads to a lower thermal field which is due to the increased time required to transfer the heat among fluid particles. The heat transport is enhanced by the stretching of the rotating disk. 2021, Shanghai University. -
Dynamics of the Dadras-Momeni System in the Frame of the Caputo-Fabrizio Fractional Derivative
Investigation of chaos in dynamical systems is one of the most fascinating issues that has received a lot of attention across a variety of scientific domains. One such dynamical system which generates two, three, and four-scroll chaotic attractors with a single parameter change, is the novel Dadras-Momeni system. In this study, we have analyzed the Dadras-Momeni system in the frame of the Caputo-Fabrizio fractional derivative. Theoretical aspects such as boundedness, existence, and uniqueness of solutions are presented. A detailed analysis is presented regarding the stability of points of equilibrium. To regulate chaos in this fractional-order system with unpredictable dynamics, a sliding mode controller is developed and the global stability of the system with control law is established. Later, we introduced uncertainties and external disturbances to the controlled system, and the condition of global stability is derived. To perform numerical simulation we have identified certain values of the parameters where the system exhibits chaotic behavior. Then the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations. 2023 Taylor & Francis Group, LLC. -
E-Commerce data analytics using web scraping
Some companies, like Twitter and others, provide an application programming interface (API) to fetch the information. If the API is not available, we will have to search other websites to get the data in a structured format. The primary way to get data from a web page is through web scraping. The basic idea of web scraping is to pull data from a website and convert it into a format that can be used for analysis. In this paper, we will discuss the simple explanation of how we can use Beautiful Soup to scratch data into Python and later save the extracted data in an Excel spreadsheet and do the spreadsheet analysis later. We will pull data from the Flipkart website to know the cell phone name, cell phone price, cell phone rating, and cell phone specification. 2023 Scrivener Publishing LLC. -
E-Commerce in Indian Retail Industry: Its Proliferation and Performance
The growth of the e-commerce industry in India has seen a multitude of growth since the growth of netizens in India has reached its peak post the demonetization in Indian economy. Research in e-commerce acts as a catalyst for studies in the field of digital innovation. The developments made by India in the field of e-commerce are notable by the world. India has made extensive use of the advancement in the field of technology. Recent years have seen a transformation in the way Indian shops and exchanges grew from cash mode payments to digital mode of service delivery and payments. This research is focused on studying the parameters that have acted as impetus in the expansion of e-commerce in the Indian retail sector. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
E-Development and Sustainable Management Education for Effective Leadership and Sustainable Society
Electronic development is the process of systematic evolution for mankind and society at large that ensures the overall progress of the electronic mode of learning, education, healthcare, society, and corporate governance. The main objective of the chapter was to address the impacts of e-development and sustainable management education for effective leadership that leads to constructing a sustainable society. The required data were collected both from primary and secondary sources. Primary data were collected from 120 respondents. The secondary data sources included official websites. The study is empirical and various statistical tools like mean, standard deviation, and t-test were executed for data analysis. The results of the research study were indicated the high degree and low degree of contribution from e-development and sustainable management education are not significant between effective leadership and sustainable society. E-development can be effective for creating a sustainable society with the goal setting of improving effective leadership skills. Copyright 2022, IGI Global. -
E-governance diffusion in the telecenters of Karnataka - a gender analysis /
International Journal of Business Information Systems, Vol.24, Issue 4, pp.452-468, ISSN: 1746-0980 (Print), 1746-0980 (Online). -
E-governance diffusion in the telecenters of Karnataka-a gender analysis
E-governance is the interaction between a government and its citizens to deliver services in an efficient manner by means of information technology and telecommunication. The current study takes into account three aspects namely-economical, governance and services that impact the e-governance diffusion in the telecenters set up at the hobli level of Karnataka state. A framework is created with these aspects and validated through the present study. The study explores whether gender differentials exist in the e-governance diffusion process. The research adds up to the literature in establishing that gender differentials disappear when the e-governance is in the stage of maturity. One-way ANOVA is used to identify the gender differentials in e-governance diffusion through the NadaKacheri centres of Karnataka. The study proposes policy changes by the government to render better services and governance to the citizens. 2017 Inderscience Enterprises Ltd. -
E-governance service quality and effective e-governance: A qualitative evaluation of telecentres of Karnataka /
Asian Journal of Research in Social Sciences and Humanities, Vol. 7, Issue 3, pp. 1272-1288, ISSN: 2249-7315. -
E-leadership, psychological contract and real-time performance management: Remotely working professionals
Using the model of E- Leadership in Virtual teams (Avolio et al.), this paper examines impact of Psychological Contract, mediated by E-leadership, on Real-time Performance Management of Remotely working professionals. Following a quantitative research method, data was collected from 57 remotely working professional across the world. Significant positive relationships were found among Leadership Effectiveness of E-leaders, Relational Psychological Contract and Efficiency of RPM. The results confirm the interaction of the given variables in Avolio's Model of E-leadership, highlighting technological aspects of human interactions and ways to optimise them. The results underline several important managerial implications for effective leadership, fulfilling psychological contract and effective performance management, of a type of workforce that is only virtually available. 2019 SCMS Group of Educational Institutions. All rights reserved. -
E-learning During COVID-19Challenges and Opportunities of the Education Institutions
As part of the COVID-19 lockdown, educational institutions were closed and adopted e-learning to keep the learning process going. Due to the COVID-19 pandemic, e-learning has become a required component of all educational institutions such as schools, colleges, and universities worldwide. This pandemic has thrown the offline teaching process into chaos. This chapter discusses the concept and role of e-learning during the pandemic and various challenges and opportunities of e-learning encountered by educational institutions. Three broad challenges identified in e-learning are inaccessibility, self-inefficacy, and technical incompetency. E-learning opportunities are no geographic barriers, flexibility, creativity, and critical learning incorporation increased utilization of online resources and reinforced distance learning. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
E-service quality-impact on customer satisfaction
The paper aims to determine the impact of e-service quality on customer satisfaction. The study utilised data from 252 customers of private and public banks in India through questionnaires. It was found that the e-service quality has significant impact on customer satisfaction in public sector banks as well as private sector banks. 2019 SERSC. -
E-shopping orientation, trust and impulse buying in the online context a study based on female members of Generation Z in India
A large number of studies have attempted to understand consumer behaviour in the online context. One construct that has been of particular interest to marketers, retailers and researchers, is impulse buying behaviour. The number of studies attempting to understand the drivers of impulsive purchases has been on a rise. The current pandemic also saw a rise in impulsive purchases and the interest in the construct was renewed. The current study is based on the S-O-R model and evaluates the relationship between e-shopping orientation, trust and impulse buying behaviour. The findings are based on data collected from female members of Generation Z and suggest that frequent visits to e-retail stores and increased patronage can increase the level of trust in the retail partner and influence the number of impulsive purchases. The findings are particularly significant for retailers looking to drive sales through impulsive purchases. In addition, the findings provide empirical support for the application of the S-O-R model to online retail context. Copyright 2024 Inderscience Enterprises Ltd. -
Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest Based FinTech Application for Hyper-automation
Hyper automation is the group of approaches and software companies utilised to automate manual procedures. Financial Technology (FinTech) was processed as a distinctive classification that highly inspects the financial technology sector from a broader group of functions for enterprises with utilise of Information Technology (IT) application. Financial crisis prediction (FCP) is the most essential FinTech technique, defining institutions financial status. This study proposes an Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest (ESAOA-ODCF) based FinTech Application for Hyperautomation. The ESAOA-ODCF technique has achieved exceptional performance with maximum accu y of 98.61%, and F score of 98.59%. Extensive experimental research revealed that the ESAOA-ODCF model beat more modern, cutting-edge approaches in terms of overall performance. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Ear Recognition Using Pretrained Convolutional Neural Networks
Ear biometrics, which involves the identification of a person from an ear image, is challenging under unconstrained image capturing scenarios. Studies in Ear biometrics reported that the Convolutional Neural Network is a better alternative to classical machine learning with handcrafted features. Two major concerns in CNN are the requirement of enormous computing resources and large datasets for training. The pretrained network concept helps to use CNN with smaller datasets and is less demanding on hardware. In this paper, three pre-trained CNN models, AlexNet, VGG16, and ResNet50 are used for ear recognition. The fully connected classification layers of the nets are trained with AWE, an unconstrained ear dataset. Alternatively, the CNN layers output (the CNN features) are extracted, and an SVM classification model is built. To improve the classification accuracy, the training dataset size is increased through data augmentation. Data augmentation improved the classification accuracy drastically. The results show that ResNet50, with the fully connected classification layer, results in higher accuracy. 2021, Springer Nature Switzerland AG. -
Ear Recognition Using Rank Level Fusion of Classifiers Outputs
An individuals authentication plays a vital role in our daily life. In the last decade, biometric-based authentication has become more prevalent than traditional approaches like passwords and pins. Ear recognition has gained attention in the biometric community in recent years. Researchers defined several features for the identification of a person from ear image. The features play a vital role in the success of classification models. This paper considers an ensemble of features for designing a new classification model. The features are assessed in isolation as well as through feature-level fusion. Subsequently, a rank-level fusion for classification is introduced. The experiments are conducted on both constrained and unconstrained ear datasets. The results are promising and open up new possibilities in machine learning-based ear recognition 2023, International journal of online and biomedical engineering.All Rights Reserved. -
Ear Recognition Using ResNet50
Deep learning techniques have become increasingly common in biometrics over the last decade. However, due to a lack of large ear datasets, deep learning models in ear biometrics are limited. To address this drawback, researchers use transfer learning based on various pre-trained models. Conventional machine learning algorithms using traditional feature extraction techniques produce low recognition results for the unconstrained ear dataset AWE. In this paper, an ear recognition model based on the ResNet-50 pretrained architecture outperforms traditional methods in terms of recognition accuracy in AWE dataset. A new feature level fusion of ResNet50 and GLBP feature is also experimented to improve the recognition accuracy compared to traditional features. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Earlier Stage Identification of Bone Cancer with Regularized ELM
A major focus of current research in the field of image processing is the application of such methods to the field of medical imaging. While dealing with biological issues like fractures, canoers, ulcers, etc., image processing facilitated pinpointing the precise cause and tailoring a remedy. In the field of tumor identification, medical imaging has set a new standard by overcoming a number of challenges. Medical imaging is the practice of generating images of the human body for diagnostic or exploratory purposes. Because of its high image quality, MRI is the method of choice for detecting tumors. This research study proposes the integration of RLM to detect tumors and presents an automatic bone cancer detection system to assist oncologists in making early diagnosis of bone malignancies, which in turn allows patients to receive treatment as soon as possible. This research work also proposes to detect bone tumors by using a combination of the RELM based M3 filtering, Canny Edge segmentation, and the Enhanced Harris corner approach. When compared to other models like CNN, ELM, and RNN, the suggested technique achieves an accuracy of around 97.55%. 2023 IEEE. -
Earliness of SME internationalizationand performance: Analyzing the role of CEO attributes
Purpose: The purpose of this paper is to understand the mediating effects of Chief Executive officer (CEO) attributes on the earliness of internationalization and performance in context of Indian small and medium enterprises (SMEs). Design/methodology/approach: The proposed framework is tested through analysis of a sample of 102 internationalized SMEs of the engineering industry in the Bangalore city region of India. Findings: Results highlight that CEOs age and educational background moderates between early internationalization and performance in the Indian SME context. Practical implications: Overall results facilitate in leveraging the decision-makers capabilities to successfully formulate and strategize their international marketing efforts to achieve higher performance. Originality/value: The study enriches the importance of CEO attributes in influencing the early internationalization and degree of internationalization in the context of an emerging economy where studies are limited. 2019, Emerald Publishing Limited.