The legal and ethical issues that confront society due to Artificial Intelligence (AI) include privacy and surveillance, bias or discrimination, and potentially the philosophical challenge is the ...role of human judgment. Concerns about newer digital technologies becoming a new source of inaccuracy and data breaches have arisen as a result of its use. Mistakes in the procedure or protocol in the field of healthcare can have devastating consequences for the patient who is the victim of the error. Because patients come into contact with physicians at moments in their lives when they are most vulnerable, it is crucial to remember this. Currently, there are no well-defined regulations in place to address the legal and ethical issues that may arise due to the use of artificial intelligence in healthcare settings. This review attempts to address these pertinent issues highlighting the need for algorithmic transparency, privacy, and protection of all the beneficiaries involved and cybersecurity of associated vulnerabilities.
Though the Corporate Governance concept has gained paramount interest due to the spate of corporate scandals, there is a void in the literature in terms of a summary overview of corporate governance ...in the Indian context. The present study aims to provide a state-of-the-art summary of corporate governance in India. To do so, the study employs a bibliometric analysis with a systematic literature review approach with extensive use of Bibliometric R Packages and VOSViewer software. To this end, the study reviews a total of 344 articles published in the Scopus database between 2004 and 2022. Akin to this, the review performs performance analysis, science mapping, and network analysis. The findings show an increasing trend in publications since 2004 till date with an annual growth rate of 23.99%. The network analysis results delineate earnings management, gender diversity, ownership structure, board structure, board size, corporate governance, ownership, and firm performance as major research themes in this field. This study is the primary attempt to show the growth and evolution of CG research in India. Thus, the review contributes to the existing literature on CG at the country level and provides scope for further research. Also, the study findings help policymakers, academicians, and regulators to strengthen corporate governance practices in the country.
Data science is an interdisciplinary field that extracts knowledge and insights from many structural and unstructured data, using scientific methods, data mining techniques, machine-learning ...algorithms, and big data. The healthcare industry generates large datasets of useful information on patient demography, treatment plans, results of medical examinations, insurance, etc. The data collected from the Internet of Things (IoT) devices attract the attention of data scientists. Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results. The process of data cleansing, data mining, data preparation, and data analysis used in healthcare applications is reviewed and discussed in the article. The article provides an insight into the status and prospects of big data analytics in healthcare, highlights the advantages, describes the frameworks and techniques used, briefs about the challenges faced currently, and discusses viable solutions. Data science and big data analytics can provide practical insights and aid in the decision-making of strategic decisions concerning the health system. It helps build a comprehensive view of patients, consumers, and clinicians. Data-driven decision-making opens up new possibilities to boost healthcare quality.
Recent advances in artificial intelligence (AI) have certainly had a significant impact on the healthcare industry. In urology, AI has been widely adopted to deal with numerous disorders, ...irrespective of their severity, extending from conditions such as benign prostate hyperplasia to critical illnesses such as urothelial and prostate cancer. In this article, we aim to discuss how algorithms and techniques of artificial intelligence are equipped in the field of urology to detect, treat, and estimate the outcomes of urological diseases. Furthermore, we explain the advantages that come from using AI over any existing traditional methods.
As India has set its ambitious target of reaching renewable energy by 2050, it has shown overwhelming interest in Environmental, Social, and Governance (ESG) focused financial products. However, ...studies on the Indian green bond market are sparse, besides its divergent role in terms of green bond issuance from an emerging market’s perspective. This study aims to fill this gap by employing a systematic review of the literature, emphasizing green bond market growth, the limiting factors, and its future development. This review examined papers published between 2010 and 2022. The review demonstrates that the lack of proper framework, high transaction costs, non-labeling of bonds, higher greenwashing, issuers’ poor creditworthiness, less government involvement, unattractive sovereign rate, unavailability of financial benefits, and lack of awareness have suppressed the rapid expansion of this market. The study based on its findings suggests effective policy measures with the expectation of the active involvement of multiple stakeholders.
Though the green bond markets are growing expeditiously, the summary overview of this market literature is sparse. This study addresses the gap by employing a bibliometric analysis through a ...systematic review of the literature approach and provides a state-of-the-art overview of the current trends, status, and future development of the green bond markets. To do so, the study reviewed 265 articles retrieved from the Scopus database spanning from 2011 to 2022. Akin to this, the study unpacks the publication trend, most influencing articles, prolific authors, top contributing journals, countries, as well as affiliations in green bond research. The review shows that the publication trend has surged exponentially with an annual growth rate of 55.12%. The study also reveals major themes such as sustainable development, sustainability, green bonds, sustainable finance, green finance, and sustainable investment. The findings of the study suggest curating future research with the main emphasis on multiple types of green bonds, the impact of various green projects, the attention of various market participants, and the incorporation of advanced technology for the development of the green bond market. The study will help policymakers, regulators, and academicians to promote sustainability.
The COVID-19 pandemic has put a strain on the entire global healthcare infrastructure. The pandemic has necessitated the re-invention, re-organization, and transformation of the healthcare system. ...The resurgence of new COVID-19 virus variants in several countries and the infection of a larger group of communities necessitate a rapid strategic shift. Governments, non-profit, and other healthcare organizations have all proposed various digital solutions. It's not clear whether these digital solutions are adaptable, functional, effective, or reliable. With the disease becoming more and more prevalent, many countries are looking for assistance and implementation of digital technologies to combat COVID-19. Digital health technologies for COVID-19 pandemic management, surveillance, contact tracing, diagnosis, treatment, and prevention will be discussed in this paper to ensure that healthcare is delivered effectively. Artificial Intelligence (AI), big data, telemedicine, robotic solutions, Internet of Things (IoT), digital platforms for communication (DC), computer vision, computer audition (CA), digital data management solutions (blockchain), digital imaging are premiering to assist healthcare workers (HCW's) with solutions that include case base surveillance, information dissemination, disinfection, and remote consultations, along with many other such interventions.
Purpose
The purpose of this paper is to present a conceptual model that explains how necessity and opportunity start-up motivation affects firm performance among women entrepreneurs (WEs) through the ...mediating influences of motivation to learn (MtL) and women entrepreneurial competencies (WEC).
Design/methodology/approach
Necessity (NEC) and Opportunity (OPP) motivation is used as the guiding theory to acknowledge the contraries of women entrepreneurial motivation. Female Entrepreneurial Competency (FEC) framework is used as a basis for WEC. Embedded in this reasoning, MtL and FECs are integrated into the conceptual model to understand the connection between start-up motivation and business performance among WEs in a developing economy.
Findings
To date, there is a limited understanding of how learning motivation and competencies together explain the business performance of WEs through the lens of their differences in start-up motivation. In this respect, this conceptual model advances scholarly insights by conceptualizing the relationship between NEC and OPP motivation, and business performance through the mediating influences of MtL and WECs.
Research limitations/implications
The proposed conceptual model does not consider any aspects other than entrepreneurial motivation, learning motivation and competencies related to business performance such as access to finance, sociocultural aspects and personality traits.
Practical implications
The proposed conceptual model can contribute to academics by adding to the body of knowledge on women entrepreneurship. It can also aid policymakers in understanding the critical link between differentials in start-up motivation and firm performance through the mediating influences of learning motivation and competencies, thus potentially providing a basis for formulating focused skilling strategies for WEs.
Originality/value
This paper proposes a unique conceptual framework that incorporates theories of learning motivation and FECs to examine the critical link between start-up motivation and business performance among WE.
Electric vehicles (EVs) are one of the near-term practical solutions in-vehicle technology, which can reduce emissions leading to the greenhouse effect and dependence on fossil fuels that are ...correlated with conventional vehiclesconventional vehicles (CVs). Several interferences are yet to be overcome for widespread adoption of EVs, despite many benefits provided to the consumers. The tendencies of customers to resist new technology is one of the major barriers in EV adoption. Hence, the policy-related decisions that showing grim concerns of EV have a greater level of success. This research aims to identify potential environmental and socio-technical barriers to purchase of EVs and it determines if governmental policies and awareness of individuals affect the customer decisions purchasing an EV. This research tries to convey valuable insights into perceptions and preferences of technology enthusiasts, individuals who are greatly connected to latest technology developments, and those who are well equipped to sort out the numerous differences between CVs and EVs. These results can provide direction to EV engineer's decision in including customer preference into EV engineering design. It can also help policymakers in developing transportation and energy policies. A survey-based study was conducted with a sample of 1230 people from urban cities of emerging Asian markets, i.e. India and Srilanka. The data collected were analyzed, which found perception of economic benefits, functional characteristics of EVs, awareness, knowledge, and familiarity of EVs as significant parameters, which directly have an impact on the purchase behavior of fully EVs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Medical imaging is a complex process that capitulates images created by X-rays, ultrasound imaging, angiography, etc. During the imaging process, it also captures image noise during image ...acquisition, some of which are extremely corrosive, creating a disturbance that results in image degradation. The proposed work addresses the challenge to eliminate the corrosive Gaussian additive white noise from computed tomography (CT) images while preserving the fine details. The proposed approach is synthesized by amalgamating the concept of method noise with a deep learning-based framework of a convolutional neural network (CNN). The corrupted images are obtained by explicit addition of Gaussian additive white noise at multiple noise variance levels (σ = 10, 15, 20, 25). The denoised images obtained are then evaluated according to their visual quality and quantitative metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These metrics for denoised CT images are then compared with their respective values for the reference CT image. The average PSNR value of the proposed method is 25.82, the average SSIM value is 0.85, and the average computational time is 2.8760. To better understand the proposed approach’s effectiveness, an intensity profile of denoised and original medical images is plotted and compared. To further test the performance of the proposed methodology, the results obtained are also compared with that of other non-traditional methods. The critical analysis of the results shows the commendable efficiency of the proposed methodology in denoising the medical CT images corrupted by Gaussian noise. This approach can be utilized in multiple pragmatic areas of application in the field of medical image processing.
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