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In today's scenario of India most of the youth is preparing for some competitive exam. If we think behind 15–20 years the number of candidates appearing for competitive exams were in thousands but as the population is increasing exponentially in India day by day the number of candidates is increasing in lacks. We can observe by daily newspapers that most of the competitive exams are facing paper leak problems. Although online examination systems are more effective and secure as compared to offline examination systems because it's not easy to open the question paper before the time starts. On the other hand there are also various consequences where the examination process can be hacked online. But the main issue with online examination process is to lack of resources to conduct parallel examination of millions of candidates, lack of techno enabled exam centers in small cities etc. Our focus is to propose a system in which offline examination can be conducted at most of the govt. and private centers in metro cities as well as small techno backward cities with reduced possibility to leak the paper before commencement of examination. [ABSTRACT FROM AUTHOR]

About one-fifth of all oral cancer cases reported globally are from India. The low-income groups in India are affected most due to the wide exposure to risk factors such as tobacco chewing and insufficient access to early diagnostic tools. Visual examination and histological study are the standard for oral cancer detection. This paper proposes the idea of using Autofluorescence-based imaging techniques to detect and classify oral cancer using AI algorithms. Various features of the images along with medical history, age, gender, and tobacco usage are considered as inputs to the proposed Mobilenet classification architecture. [ABSTRACT FROM AUTHOR]

CRM (Customer Relationship Management) Systems have long been used for strengthening relationships with customers thereby ensuring retention and enhancing business. Data stored in the CRM software can be analyzed to provide deep insights into the customer behavior thus influencing future products and services. Predictive Analytics are a branch of Business Analytics that helps in analyzing the current data, with the help of statistical tools, data mining algorithms, modelling tools, AI or machine learning, to make effective predictions for the future. This paper studies the impact of predictive analytics applied onto the CRM data of the sample Organization (name concealed owing to secrecy issues), which is among the front runners in the Instrumentation Industry in India and has been providing best quality Instruments and allied services through leading edge global technology. This paper examines the significant factors which help in winning a deal by using logistic regression in the reference Organization. Data are obtained from the Customer Relationship Management software provided by the company. The results presented in this paper confirm that the CRM data can be used to predict the probability of winning a deal. It also helps to find factors which are impacting 'Win' or 'Loss' of the opportunity/deal so that businesses can take precautionary measures to avoid potential loss of opportunity. Such analysis is helpful in the creation of new sales tactics, improvement of winning proportions and thereby enhancing sales. [ABSTRACT FROM AUTHOR]

Purpose: India is a rapidly developing economy with a rapidly expending internet infrastructure and among the largest Generation Z population. This generation is tech savvy and the access to technology and network creates a conducive environment for such usage. Internet banking for the same reasons is growing leaps and bounds. The introduction of artificial intelligence (AI) has created disruptions in the traditional banking also. This paper aims to analyze the comfort level and usage of AI-enabled banking services by Generation Z. Design/methodology/approach: The data is collected from 272 Generation Z members. The differential aspects, that is, the relationship of independent variables with dependent variables (AI-enabled internet banking), were analyzed using the structural equation modeling approach. Findings: Defining factors for AI-enabled internet banking were identified. The results of factors were consistent with previous studies. It was found that the usage of AI-enabled internet banking services is insignificant, indicating that Generation Z does not perceive any advantage in using AI-enabled internet banking services. Research limitations/implications: This paper does not incorporate age groups other than Generation Z. Further research could throw light on the difference based on age groups. Further research is required to deeply understand why Generation Z does not perceive AI-enabled internet services as very important. Practical implications: It has been observed that internet banking is important for Generation Z, but they also place greater importance on interpersonal communication. Banks need to consider this in designing their internet banking services. Originality/value: This paper addresses the gap between comfort with and usage of AI-enabled internet banking services, by Generation Z. This paper indicates that the comfort with AI-enabled internet banking services does not translate to usage. [ABSTRACT FROM AUTHOR]

Industry 4.0 is about the accelerated adoption of technologies like AI and Robotics, which are demanding new human skillsets. Organisational roles are becoming more complex, especially at the managerial levels, on account of flattening of their structures and due to the rationalisation of operational and support roles. Extensive automation and use of technologies like AI, Robotics are also perceived by top management as necessity to sustain and grow the business operations. As speed and scale of business operation increases and the environmental makes outcomes uncertain, organisations need to become highly Analysis agile and responsive. Roles will get fungible and ready-touse skills will be preferred tore-skilling existing employees. With access to new forms of data, which are critical and integral to decision making, new operating paradigms are emerging, making the work environment 'Hu-Tech' (human+technology). The co-existence of intelligent machines and human beings demands newer managerial skills besides developing newer management perspectives and methods for growing the business. Employers believe that retraining in-house resources is far too expensive and tardy in the context of business agility and responsiveness. It becomes easier and economical to contract skilled resources as and when required. This leads to the Gig culture. Skilled resources are shared across multiple organisations or used exclusively by an organisation, but for a limited period of time. The organisation disengages with the skill and prefers to enter into another engagement, based on its needs and conveniences. This paper provides empirical evidence on top management's intent to favour short-term engagements with the right skilled people. This therefore encourages the gig culture. The analysis is drawn from a sample size of 49 top executives in the Information Technology business vertical in India. [ABSTRACT FROM AUTHOR]

The coronavirus (COVID-19) has been spread all over the world making bad impact on each sector. But in this pandemic situation digital transaction increasedcompared to another sector. India is experiencing a growth trajectory in digital payments that is more prolific than many advanced less-cash economies. This paper is a discussion on Impact of Covid-19 on Digital Payment System. [ABSTRACT FROM AUTHOR]

Purpose: Non-contrast CT head scans provide rapid and accurate diagnosis of acute head injury; however, increased utilisation of CT head scans makes it difficult to prioritise acutely unwell patients and places pressure on busy emergency departments (EDs). This study validates an AI algorithm to triage patients presenting with Intracranial Haemorrhage (ICH) or Acute Infarct whilst also identifying a subset of patients as Normal, with the potential to function as a rule-out test. Methods: In total, 390 CT head scans were collected from 3 institutions in the UK, US and India. Ground-truth labels were assigned by 3 FRCR consultant radiologists. AI performance, as well as the performance of 3 independent radiologists, was measured against ground-truth labels. Results: The algorithm showed AUC values of 0.988 (0.978–0.994), 0.933 (0.901–0.961) and 0.939 (0.919–0.958) for ICH, Acute Infarct and Normal, respectively. Sensitivity/specificity for ICH and Acute Infarct were 0.988/0.925 and 0.833/0.927, respectively, compared to 0.907/0.991 and 0.618/0.977 for radiologists. AI rule-out of Normal scans achieved 0.93% negative predictive value (NPV) for the removal of 54.3% of Normal cases, compared to 86.8% NPV for radiologists. Conclusion: We show our algorithm can provide effective triage of ICH and Acute Infarct to prioritise acutely unwell patients. AI can also benefit clinical accuracy, with the algorithm identifying 91.3% of radiologist false negatives for ICH and 69.1% for Acute Infarct. Rule-out of Normal scans has huge potential for workload management in busy EDs, in this case removing 27.4% of all scans with no acute findings missed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate the impact of artificial intelligence (AI) on the human rights issue. This study has also examined issues with AI for business and its civil and criminal liability. This study has provided inputs to the policymakers and government authorities to overcome different challenges. Design/methodology/approach: This study has analysed different international and Indian laws on human rights issues and the impacts of these laws to protect the human rights of the individual, which could be under threat due to the advancement of AI technology. This study has used descriptive doctrinal legal research methods to examine and understand the insights of existing laws and regulations in India to protect human rights and how these laws could be further developed to protect human rights under the Indian jurisprudence, which is under threat due to rapid advancement of AI-related technology. Findings: The study provides a comprehensive insight on the influence of AI on human rights issues and the existing laws in India. The study also shows different policy initiatives by the Government of India to regulate AI. Research limitations/implications: The study highlights some of the key policy recommendations helpful to regulate AI. Moreover, this study provides inputs to the regulatory authorities and legal fraternity to draft a much-needed comprehensive policy to regulate AI in the context of the protection of human rights of the citizens. Originality/value: AI is constantly posing entangled challenges to human rights. There is no comprehensive study, which investigated the emergence of AI and its influence on human rights issues, especially from the Indian legal perspective. So there is a research gap. This study provides a unique insight of the emergence of AI applications and its influence on human rights issues and provides inputs to the policymaker to help them to draft an effective regulation on AI to protect the human rights of Indian citizens. Thus, this study is considered a unique study that adds value towards the overall literature. [ABSTRACT FROM AUTHOR]