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Ethical living and work self efficacy beliefs of academicians of higher education in ASIA: A key determinant of one's belief in one's ability to achieve the desired result in a precise state of affairs
Ethical academicians are perfectly virtuous. They always strive for greater virtue and follow strictly the moral stands of their profession. The ethical living and self-efficacy are important to them because of being fair and honest in their academics. Determinants of ethics include knowledge, values, attitude and intention. The domain-specific framework developed by Verbeke et al. (2004) has been considered as fundamental for identifying the dimensionality of work Self-efficacy and ethical challenges of academicians. A comprehensive literature review is undertaken regarding the concept of work Self-efficacy to assess workers' confidence and their ethical living in the workplace. This article examines theoretically and analytically the antecedent processes and information cues involved in the formation of work self-efficacy. Theoretical and numerical analysis of the key determinants of work self-efficacy increases the understanding of moral values, truthful fair and honest. Factors which decisively affect ethical living were identified from literature collected from the academicians who are working in the Five Regions of Asia-Central Asia (Tajikistan, Uzbekistan, Kazakhstan, Turkmenistan, Kyrgyzstan) East Asia (China, Mongolia, North Korea, South Korea, Japan, Hong Kong, Taiwan, Macau) South Asia (Sri Lanka, Bangladesh, India, Afghanistan, Pakistan, Bhutan, Nepal, the Maldives) through Google classroom. Methods of Statistical Analysis of self-efficacy data are descriptive statistics, Pearson Correlation Coefficient and Kolmogorov-Smirvnos normality test and KruskalWallis one-way analysis of variance and Principal Component Analysis. Positive, mastery experiences give academicians a sense of accomplishment when they have faced a challenge ethically. Positive Zeal during Academic interaction, vicarious experiences that occur when academician see others succeed and feel an increased sense of their own ability to succeed. Sincere & deeper self, mingling with students, Social persuasion increase a teachers sense of confidence and ability to succeed. A proper plan of action has drawn special attention, and inferences pertaining to future research are discussed at the end of the critique. 2019, Sciedu Press. All rights reserved. -
Ethical Integrity and Performance in Isolation: An Intrinsic Motivation Mediated Focus
This research investigates the mediating influence of intrinsic motivation on employee isolation and job performance of work-from-anywhere Information Technology professionals in India. Intrinsic motivation and ethical integrity are fundamentally intertwined, each enhancing and reinforcing the other. The lenses of the self-determination theory underpin the study. The research questions covered in the study are: (a) Does employee isolation affect job performance? (b) Does intrinsic motivation during employee isolation affect job performance? (c) Does intrinsic motivation mediate the connection between employee isolation and job performance? The SEM based approach survey was conducted to collect data from 410 IT employees who work from anywhere for a minimum of one or more days per week. The findings indicate that (a) employee isolation has a negative influence on job performance, (b) intrinsic motivation significantly influences job performance during employee isolation, and (c) intrinsic motivation mediates indirect-only (full mediation) the link between employee isolation and job performance. The employers need to build upon intrinsic motivation tools for work-from-anywhere Information Technology professionals, which ensures employees relatedness by giving rewards, a sense of purpose towards assignments, autonomy through intrinsic motivation and ethical integrity, and developing IT expertise, which significantly increases performance among employees in work isolation situations. Through the lens of self-determination theory, the research contributes to the work-from-anywhere literature by exploring the relations between employee isolation, job performance, and the mediating influence of intrinsic motivation on IT professionals in India in the current scenario. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Ethical imperatives and frameworks for responsible AI adoption in digital entrepreneurship
This study explores ethical dimensions in AI adoption for digital entrepreneurship. Thematic analysis highlights transparency, fairness, and accountability. Findings recommend comprehensive ethical guidelines, inclusive decision-making, and robust accountability mechanisms. Practical implications extend to digital ventures, policymakers, and educators. Future research may delve into industry-specific nuances, cross-cultural analyses, and the longitudinal impact of ethical frameworks, contributing significantly to responsible AI adoption discourse in digital entrepreneurship. 2024, IGI Global. All rights reserved. -
Ethical dimensions of GIS data privacy: Examining the intersection of ethics and privacy
The proliferation of mapping technologies has spurred significant attention to the ethical conduct surrounding geographic information systems (GIS). Various studies have explored these ethical considerations. Academic map and geography libraries are increasingly responsible for managing geospatial datasets, emphasizing the need for maintaining ethical standards in data archiving, cataloging, and distribution. Moral concerns about geospatial technologies encompass data accuracy, copyright, and quality assurance. Users of geospatial data must discern between ground-truth data and voluntary contributions, particularly with the rise of social media and participatory GIS. This chapter discusses the concerns concerning GIS data and the important data privacy issues while using GIS data. 2024, IGI Global. All rights reserved. -
Ethical Decision-Making in HRM: Insights From India Ethos
This research is especially relevant given the dynamic nature of Human Resource Management (HRM) and its objectives to offer a systematic view of ethical decision-making, focusing on the Indian system. The research relies on the combination of investigations from ethics, HRM, cultural studies, and organizational behavior to reach a maximum understanding of the research subject. The findings of the study are based on a multilayered exploration of ethical decision-making in HRM. It explores the current challenges of human resources (HR) professionals who must consider both business and ethical aspects while promoting their organizations. Also, this study focuses on ideological and cultural aspects to describe the Indian ethical phenomenon. The anticipated results of the proposed research will have practical implications for HR practitioners and leaders. The study will further assist in understanding how HR professionals and leaders can encourage ethical decision-making. Based on the unique indigenous qualities of the Indian continent, the research will also help in the establishment of more culturally suitable HRM ethical practices. It will add value internationally due to the coordination brought by different cultures. This research contributes to existing HRM research on ethical decision-making complexities since it stresses the need for a culture-sensitive approach to these complexities. The utilization of Indias indigenous ethics makes the researchs point of view unique, making it beneficial for both practitioners and scholars. The novelty of this study is uncovering the cultural crossroads of the Indian ethos and HRM ethics as a part of the greater debate on organizational decision-making. 2025 Anitha K., Indrajit Ghosal and Mohammad Irfan. -
Ethical considerations in nanomedicine research involving women
This chapter elaborates social impact and perspectives of advanced technologies as well as critically discuss the ethical issues of womens participation in nano-medicine research. It starts by addressing the issue that women have been under sampled in clinical research but it is moral to take their samples farther into research most notably with certain special health conditions and unique reactions to drug treatments that are likely to be unique to women. One of the most emphasized concepts is informed consent, for the purpose of precisions and clarity in explaining its purpose and usefulness, as well as the probable consequences in the form of some narrowly speculative treatments with particular relevance to certain probabilities remaining beyond the range of perception on the female body after some or other nano-scale procedures. The chapter also talks about the ethical implications in the present strategies to increase the efficacy and safety for women only therapies like nanomedicine; the author urges for stringent preclinical and clinical guidelines which should have examined the following gender variations. It also examines the regulation with guidance and suggests contingency structures that are employed in the management of the ethical use of nanomedicine in women health care. Therefore this chapter tries to develop ethics together with science, incorporate these met ethical considerations into methods and guidelines in research, to contribute to enhancement of beneficial impact of the nanomedicine for womens rights and well-being. 2026 Elsevier Inc. All rights reserved.. -
Ethical considerations in multimodal data collection and analysis
Nowadays, research and industry rely more on collecting and analyzing multimodal data that integrates a host of formats like text, images, audio, and video. Such integration increases the decision-making capabilities and builds insightful information, but equally raises serious ethical issues to be followed up with caution. In multifarious and interrelated datasets, questions about ownership of the data, informed consent, and privacy become much more complex. This has further worsened by the advent of social media and big data analytics, exposing participants to possible harms. This paper discusses the ethical issues arising in such scenarios and calls for strong mechanisms that ensure responsible and just conduct in multimodal research. 2026 Elsevier Inc. All rights reserved. -
ETHICAL CONFLICTS AMONG THE LEADING MEDICAL AND HEALTHCARE LEADERS
Today, the whole world is fighting the COVID-19 pandemic. In these circumstances, medical professionals are being viewed as the frontline warriors who are risking their lives for the sake of helping, caring, and curing these patients. However, in these difficult times, there are few medical professionals and health care providers who are taking advantage of this situation and taking advantage of distressed and distraught patients at will. A conflict between professional and personal ethical values makes them depressed and puzzled. It is tough for them to maintain a good image of their profession and business. The objectives of this study are to review the ethical conflict amid the ongoing Covid pandemic and post-Covid pandemic (vaccination period) in the context of medical professionals and health care providers. The paper is designed based on a literature review. Almost fifty-two research papers, articles, survey reports, and newspapers were studied in the context of ethics in business/profession. After reviewing moral distress is ongoing and post-pandemic period, the researchers have tried to present the medical professionals and health care providers' critical situation to give priority to their professional ethics or personal interest. School of Engineering, Taylor's University -
Ethical and Societal Implications of Artificial Intelligence in Space Mining
The advent of Artificial Intelligence (AI) in space mining marks a pivotal shift in the exploration and utilization of extraterrestrial resources. This paper presents a thematic analysis of the ethical, societal, technological, economic, and environmental implications of integrating AI in space mining operations. Through topic modeling of relevant literature, five key themes were identified: AI integration and ethical considerations, economic efficiency and equity, technological innovations and advancements, international collaboration and governance, and environmental sustainability and planetary protection. These themes highlight the potential of AI to revolutionize space mining, enhancing efficiency and enabling the extraction of valuable resources beyond Earth. However, they also underscore the need for robust ethical frameworks, equitable economic models, international cooperation, and sustainable practices to address the multifaceted challenges posed by this frontier. The paper concludes with recommendations for future research and policy-making, emphasizing the importance of inclusive, collaborative approaches to ensure the responsible and beneficial advancement of space mining. 2024 IEEE. -
Ethical and Privacy Considerations in GAN-Based Security
Generative Adversarial Networks (GANs) have caused a great transformation in a number of fields, including anomaly detection, healthcare, data encryption, deep learning (DL), machine learning (ML), and entertainment. They are also employed in various security applications. This chapter explores mainly the privacy and ethical concerns associated with the use of GANs. Although GANs have enormous possibilities for security applications such as biometrics, intrusion detection, and data augmentation, implementing them requires careful consideration regarding privacy and ethical issues. GANs ability to produce remarkably lifelike deepfakes poses a risk since it might promote social engineering attacks. Moreover, these discrepancies may be increased by biased security programs that arise from biases in training data. Even with all of the potential benefits, ethical and privacy concerns must be prioritized for the safe and reliable application of GANs in security. This chapter also lays the foundation of GAN-based applications in Cybersecurity. 2026 selection and editorial matter, E. Chandra Blessie, Pethuru Raj, and B. Sundaravadivazhagan; individual chapters, the contributors. -
Ethical and Legal Dimensions of Drones and Robots in Smart Business: Navigating the Autonomous Innovations in Logistics
Use of drones and robots are slowly but surely making their way into people's personal and professional lives. International companies are spending millions of dollars on drone research and development for logistics. Companies like Google, Amazon, DHL, and Walmart are actively experimenting on autonomous systems and robotics. Drones and robots are used in the business strategies of these organizations to ensure last-mile delivery, which involves transporting packages straight from a depot to the ultimate customer, maintaining inventory, loading and unloading of trucks, order processing, and the like. But the usage of these advancements poses some critical ethical and legal issues. Authorities must pay attention to these challenges and difficulties in order to ensure their meaningful usage. This chapter, in this perspective, overviews the most significant legal and ethical concerns pertaining to the use of autonomous vehicles in smart businesses and logistics and provides recommendations for their effective utilization in future. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Ethical AI in Humanitarian Contexts: Challenges, Transparency, and Safety
This chapter elaborates on how emerging technologies for artificial intelligence (AI) can help create social change and solve worldwide problems. The chapter brings to light the issue of ethical matters and responsible AI practices that should be considered to avoid technology usage by the vulnerable population to harden already present inequalities. This chapter also examines the role of AI in ensuring that quality education is accessible to all, in addressing poverty through innovative approaches, and in the amplification quest of human rights advocacy by marginalized groups. This chapter presents a complete picture of the impact of AI on humanitarianism, exemplifying the devices of new horizons and emphasizing the necessity of responsible and inclusive applications. This chapter provides findings and advice for researchers, practitioners, policymakers, and all interested parties who are involved in using the new technologies to make their world fairer and well-sustained. The chapter aims to comprehend the AI-humanitarianism nexus and simultaneously proclaim safety measures and transparency for the sake of social upheaval. 2025 selection and editorial matter, Adeyemi Abel Ajibesin and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Ethical AI in Humanitarian Contexts: Challenges, Transparency, and Safety
This chapter elaborates on how emerging technologies for artificial intelligence (AI) can help create social change and solve worldwide problems. The chapter brings to light the issue of ethical matters and responsible AI practices that should be considered to avoid technology usage by the vulnerable population to harden already present inequalities. This chapter also examines the role of AI in ensuring that quality education is accessible to all, in addressing poverty through innovative approaches, and in the amplification quest of human rights advocacy by marginalized groups. This chapter presents a complete picture of the impact of AI on humanitarianism, exemplifying the devices of new horizons and emphasizing the necessity of responsible and inclusive applications. This chapter provides findings and advice for researchers, practitioners, policymakers, and all interested parties who are involved in using the new technologies to make their world fairer and well-sustained. The chapter aims to comprehend the AI-humanitarianism nexus and simultaneously proclaim safety measures and transparency for the sake of social upheaval. 2025 selection and editorial matter, Adeyemi Abel Ajibesin and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Ethical AI in HR: Navigating the Data-driven Frontier
The integration of artificial intelligence (AI) in human resources (HRs) presents significant opportunities while raising ethical dilemmas for an organisation. This chapter examines challenges in AI-enhanced HR concerning bias mitigation, data protection, transparency and governance through literature review, and real-life examples. Through a mixture of academic research and industry use cases including Amazon's AI hiring tool, HireVue video interview analysis, IBM Watson Career Coach and Unilever recruitment powered through AI study analyses AI impact on HR functions and approaches to address ethical concerns. This research offers an advanced methodological framework for ethical implementation of AI in HR which is based upon eight foundational components including interdisciplinary collaboration, bias minimisation, transparency and explainability, ethics-based privacy policies governance, continuous monitoring improving engagement with stakeholders, and adaptive trust-enhancing policy. The model weights a set of quantitative suggestion, new metrics such as Team Integration Score (TIS) for assessing cross-functional relationship success. Synthesis of multiple academic sources and case studies mentioned the chapter plan on responsible AI implementation in HR through stakeholder engagement, transparency practices, and review mechanisms. This approach balances technological advancement and ethical considerations within AI-driven HR processes. The significance of this chapter is to bring together academic sources and experts from the industry to provide a complete guide of integrating global best practices for implementing ethical AI. The proposed framework serves as a valuable tool for HR AI practitioners and researchers offering a structured approach to the ethical AI deployment while remaining adaptable to emerging challenges and opportunities in this rapidly growing area. 2026 by A.R. Deepti, B. Manimekala, Farzeen Basith, Vivek K. and Vijayanandh Rajamanickam. All rights reserved. -
Estimation of Vehicle Distance Based on Feature Points Using Monocular Vision
In this digital era safety and security have the highest precedence, the advanced driver assistance system is the latest trend and where many challenges are open for researchers. Vehicle to vehicle distance estimation is one of the most important challenges to provide the security and safety alerts for the driver. In order to achieve this, image of the front vehicle is captured using the single camera under monocular vision to estimate the vehicle distance. Then three key steps are designed to estimate the vehicle distance: extracting and locating the key features of the vehicle, characteristic triangle is drawn between those features to calculate pixel area and develop the measuring formula to calculate the distance. For efficient feature extraction and localizing of the feature position, conventional AdaBoost algorithm is utilized to find the strong features for scalable samples. Distance measurement formulation is used to derive the correlation between the pixel area and distance by considering the different parameters from the prototype of pinhole camera, camera standardization and plotting of area. Formula is developed to estimate the optimum moving distance between vehicles to vehicle. After the experimental analysis, the accuracy rate is improved and time complexity satisfies the precision. 2019 IEEE. -
Estimation of the size and structure of the broad line region using Bayesian approach
Understanding the geometry and kinematics of the broad line region (BLR) of active galactic nuclei (AGN) is important to estimate black hole masses in AGN and study the accretion process. The technique of reverberation mapping (RM) has provided estimates of BLR size for more than 100 AGN now; however, the structure of the BLR has been studied for only a handful number of objects. Towards this, we investigated the geometry of the BLR for a large sample of 57 AGN using archival RM data. We performed systematic modelling of the continuum and emission line light curves using a Markov chain Monte Carlo method based on Bayesian statistics implemented in PBMAP (Parallel Bayesian code for reverberation-MAPping data) code to constrain BLR geometrical parameters and recover velocity integrated transfer function. We found that the recovered transfer functions have various shapes such as single-peaked, double-peaked, and top-hat suggesting that AGN have very different BLR geometries. Our model lags are in general consistent with that estimated using the conventional cross-correlation methods. The BLR sizes obtained from our modelling approach is related to the luminosity with a slope of 0.583 0.026 and 0.471 0.084 based on H ? and H ? lines, respectively. We found a non-linear response of emission line fluxes to the ionizing optical continuum for 93 per cent objects. The estimated virial factors for the AGN studied in this work range from 0.79 to 4.94 having a mean at 1.78 1.77 consistent with the values found in the literature. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Estimation of the black hole spin in LMC X-1 using AstroSat
LMC X-1, a persistent, rapidly rotating, extra-galactic, black hole X-ray binary (BHXB) discovered in 1969, has always been observed in its high soft state. Unlike many other BHXBs, the black hole mass, source distance, and binary orbital inclination are well established. In this work, we report the results of simultaneous broad-band spectral studies of LMC X-1 carried out using the data from Soft X-ray Telescope and Large Area X-ray Proportional Counter aboard AstroSat as observed on 2016 November 26 and 2017 August 28. The combined spectrum was modelled with a multicolour blackbody emission (diskbb), a Gaussian along with a Comptonization component (simpl) in the energy range 0.7-30.0 keV. The spectral analysis revealed that the source was in its high soft state (? = 2.67+0.24-0.24 and ? = 2.12+0.19-0.20) with a hot disc (kTin = 0.86+0.01-0.01 and kTin = 0.87+0.02-0.02). Thermal disc emission was fitted with a relativistic model (kerrbb) and spin of the black hole was estimated to be 0.93+0.01-0.01 and 0.93+0.04-0.03 (statistical errors) for the two Epochs through X-ray continuum-fitting, which agrees with the previous results. 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
Estimation of System Reliability Based on Inverted Exponentiated Pareto Distribution Under a Progressively First-Failure Censored Scheme With Application
This article explores and derives the estimation of the multicomponent stressstrength (MSS) reliability parameter, assuming that the samples are coming from the inverted exponentiated Pareto distribution using a progressively first-failure censored scheme. To estimate the MSS reliability, both classical and Bayesian approaches are adopted. In the classical approach, the maximum likelihood and the asymptotic confidence interval estimation methods are used. The Bayes estimates with their corresponding highest posterior density credible interval estimates are obtained under the Bayesian approach, under the linear exponential loss function under both the noninformative and gamma informative priors. In addition, to compute the Bayes estimates, Markov chain Monte Carlo methods are used. To compare the efficacy of the different estimation strategies adopted in this paper, a Monte Carlo simulation study is carried out. To demonstrate the applicability of the proposed methodology, two real-life scenarios resulting/arising from two different carbon fiber data sets arere-analyzed. 2025 The Author(s). Quality and Reliability Engineering International published by John Wiley & Sons Ltd. -
Estimation of stellar parameters and mass accretion rate of classical TTauri stars from LAMOST DR6
Classical T Tauri stars (TTS) are low-mass pre-main sequence stars with an active circumstellar environment. In this work, we present the identification and study of 260 classical TTS using LAMOST Data Release 6, among which 104 stars are newly identified. We distinguish classical TTS from giants and main-sequence dwarfs based on the log g values, and the presence of H ? emission line and infrared excess that arises from the circumstellar accretion disk. We estimated the mass and age of 210 stars using the Gaia colormagnitude diagram. The age is from 0.1 to 20 Myr, where 90% of the stars have age <10 Myr and the mass ranges between 0.11 and 1.9 M? . From the measured H ? equivalent widths, we homogeneously estimated the mass accretion rates for 172 stars, with most values ranging from 10 - 7 to 10 - 10M? yr - 1 . The mass accretion rates are found to follow a power law distribution with the mass of the star, having a relation of the form M?acc?M?1.430.26 , in agreement with previous studies. 2023, Indian Academy of Sciences. -
Estimation of state of charge considering impact of vibrations on traction battery pack
Interest towards electric vehicle adoption is on the rise due to the lower running and maintenance cost it offers, along with zero tailpipe emissions. Range anxiety is one of the only concern that affects the adoption of electric vehicles. The state of charge of the traction battery pack has to be accurately determined and provided to the user to avoid range anxiety. Minute battery parameters has to be considered to improve the accuracy of the state of charge determination. In order to overcome the problem of range anxiety, an innovative strategy that takes into account how vibrations affect the performance of EV batteries is developed in this research. By doing this, the state of charge estimation precision is improved and thereby raises the drivers faith in electric vehicles. The impacts and vibrations felt on the traction battery pack during driving would lead to heat generation. The heat generated is found to be highest when the vibrations resonate at the natural frequencies of the traction battery pack. The natural frequency of the battery pack is considered when the battery is kept in the battery chamber of the two-wheeler electric vehicle. The vibrations at natural frequency produces heat which is accounted for when the state of charge is determined. To obtain accurate state of charge estimation, a Kalman filter-based approach is used. The Kalman filter-based estimation uses the conventional methods which are the open circuit voltage method and the Coulomb counting method to improve the estimation process along with the consideration of the heat component due to vibrations and impact. The vibration analysis is performed using MATLAB, while the state of charge determination is implemented in hardware and the Kalman estimation done using Python. The system is modelled on an electric two-wheeler platform and the testing is done to compare the state of charge accuracy of the open circuit voltage method, the Coulomb counting method and the Kalman filter-based estimation approach. The inclusion of the vibrational heat analysis for State of Charge estimation in the hardware testing of the electric two-wheeler provides an accurate state of charge value. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.