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Coronavirus outbreaks during the last couple of years created a huge health disaster for human lives. Diagnosis of COVID-19 infections is, thus, very important for the medical practitioners. For a quick detection, analysis of the COVID-19 chest X-ray images is inevitable. Therefore, there is a strong need for the development of a multiclass segmentation method for the purpose. Earlier techniques used for multiclass segmentation of images are mostly based on entropy measurements. Nonetheless, entropy methods are not efficient when the gray-level distribution of the image is nonuniform. To address this problem, a novel adaptive class weight adjustment-based multiclass segmentation error minimization technique for COVID-19 chest X-ray image analysis is investigated. Theoretical investigations on the first-hand objective functions are presented. The results on both the biclass and multiclass segmentation of medical images are enlightened. The key to our success is the adjustment of the pixel counts of different classes adaptively to reduce the error of segmentation. The COVID-19 chest X-ray images are taken from the Kaggle Radiography database for the experiments. The proposed method is compared with the state-of-the-art methods based on Tsallis, Kapur's, Masi, and Renyi entropy. The well-known segmentation metrics are used for an empirical analysis. Our method achieved a performance increase of around 8.03% in the case of PSNR values, 3.01% for FSIM, and 4.16% for SSIM. The proposed technique would be useful for extracting dots from micro-array images of DNA sequences and multiclass segmentation of the biomedical images such as MRI, CT, and PET.
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The vaccination drive for the COVID-19 pandemic was initiated globally more than a year ago, with booster shots being the new addition currently. There are some setbacks regarding the acceptance of the vaccine that the government needs to tackle to achieve a fully vaccinated ecosystem. Vaccine hesitancy is not a new concept and has been witnessed by people for decades. In simple terms, vaccine hesitancy refers to a situation where people are reluctant to get vaccinated despite its availability. This is due to technological retrogression, superstitions, doubt towards the government and misinformation. This paper is a systematic literature review to analyse the behavioural economics theories shown by people towards vaccines in the SARS-CoV-2 pandemic. We aim to connect psychological and economic factors that lead to this hesitancy through behavioural economics. Availability bias, omission bias, confirmation bias, incentives, anticipated regret, illusory correlation, recency effect, tailoring and framing are the biases that influence decision-making under the behavioural economics framework. This paper is an attempt to analyse these principles and explain potential barriers to vaccine acceptance and intervention strategies for medical professionals and the state. © 2022 SAGE Publications India Pvt. Ltd.
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PurposeThe present study aims to understand the relationship between psychological contract breach (PCB) and outcome variables with mediation role of job stress, psychological empowerment and moderating role of learned helplessness.Design/methodology/approachDescriptive cross-sectional research design was deployed. Data were collected from the Indian public sector bank employees, especially from those who are regularly going to the banks even during the lockdown situation. A total of 239 respondents were contacted via online and offline method.FindingsThe authors reported that bank employees feel the breach of psychological contract which induced job stress. Further, job stress negatively impacts their psychological empowerment and psychological empowered employees exhibit increased innovative behavior and well-being. The authors also found that job stress and psychological empowerment mediated the relationship between PCB and outcome variables, and learned helplessness moderates this relationship. The current study captures the psychological response of employees during the pandemic era.Originality/valueThe study also highlights that during the pandemic, when majority of the employers have given work from home, the public sector employees were regularly going to the banks with fragile mindset. The banks' managers and HR managers can also understand that how the fulfillment of expectations is important not only for employee well-being but also for the health of the organization.
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The Technology of Image Processing has been incredibly used in many era of application like Medical Diagnosis using Image Segmentation, Face Recognition, HandWriting Analysis using Pattern Recognition. It has created its' own identity and has been fascinating all over the Research studies. Our paper is based on Image Processing called as "MULTI-LEVEL IMAGE THRESOLDING METHODS FOR COVID X-RAY IMAGE SEGMENTATION ". The mirror of the whole paper is summarized in this part. The people life has been affected due to the ongoing commotion due to COVID-19.The Researcher's left no stone unturned to deal out with Corona virus. Many methods had been applied like RT-PCR, CT Scan, Image Segmentation, uses of Meta-heuristic Algorithm: PSO, Cuckoo search, MRFO, MRFO Algorithm, MRFO-OBL, etc. © 2022 IEEE.
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Purpose: The study aims to explore and validate the revised psychological contract scale in this new normal era. Design/methodology/approach: To serve the purpose, four studies were conducted. Study 1 was conducted for item generation through the extant literature review and phenomenological study. Study 2 highlighted the expert review. Study 3 explained the confirmatory factor analysis. At the end of study 3, the new psychological contract content had 14 items along with 15 traditional psychological contract content items. The nomological study validated the scale with the help of antecedent, i.e. supervisor's support, and outcomes, i.e. well-being and innovative behavior. Findings: The revised psychological contract was bifurcated into two categories: new and traditional. Further, the revised psychological contract scale was having two dimensions: content and breach/fulfillment. The new content was the outcome of changes in perceived obligations due to pandemic. The nomological study found that supervisor support had a positive impact on the content of the psychological contract and fulfillment/breach of the psychological contract. Further, it was found that the new content of psychological contract was impacting more on well-being and innovative behavior than the traditional psychological contract. Research limitations/implications: In the new normal era, the working style and patterns have changed. Thus, it was important to capture changes in perceived obligations and employees' perception regarding to which extent their organizations were able to meet these altered perceived obligations. The study has direct implications for the practitioners as the revised psychological contract scale enlisted the perceived obligations of the employee and the extent to which these obligations were fulfilled by the employer. The study is also helpful in developing new normal HR policies and practices in the organization. Originality/value: The study is original as it creates a new scale to measure the content of psychological contract and fulfillment/breach of psychological contract during new normal. © 2022, Emerald Publishing Limited.
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Purpose: This study identifies antecedents and consequences of destination brand engagement (DBE) that have redefined the tourists' behavior during the COVID-19 outbreak. Specifically, it assesses the impact of social media interaction and destination authenticity on DBE and DBE's effect on tourists' willingness to pay (WTP). Further, it examines the mediating role of affective attitude and the moderating role of perceived risk between the associations of DBE and WTP. Design/methodology/approach: Survey data were collected from 436 respondents through a structured questionnaire from selected tourism destinations in India. Structural equation modeling (CB-SEM) is employed to empirically examine the formulated hypotheses. Besides, hierarchical second-order confirmatory factor analysis is also deployed to analyze certain constructs as higher-order factors. Findings: Social media interaction and destination authenticity elevate DBE, and DBE enhances affective attitude and WTP. Affective attitude mediates the relationship between DBE and WTP. Hence, the association between tourists' engagement and spending behavior becomes crucial under elevated affective attitude conditions. Finally, perceived risk during the pandemic dampens the association between DBE and WTP. Practical implications: The findings may provide newer insights to the tourism companies, marketers and policymakers to create targeted strategies to minimize the risk perception and improve engagement levels of the tourists, which can yield economic returns in the long run. Originality/value: Based on the cues from protection motivation theory (PMT), this study develops a DBE framework and identifies the factors affecting its sustenance in the pandemic hit tourism sector. Further, suggesting implications to ensure safety measures in the tourism industry that may assist in establishing economic resilience. © 2022, Emerald Publishing Limited.
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COVID-19 pandemic affected many people world-wide. It has become a global issue. The major priority of the scientific community is to control this pandemic. The infection can spread through various ways, mainly by touching a contaminated or infected surface or person-to-person contact (droplets from the oral and nasal passage from an infected person). Increase in the rate of infection can by caused by inadequate hygiene practices and cleanliness. The virus is active up to few hours on various surfaces and time may vary according to the nature of the surface. The virus can continue to spread rapidly by contact surfaces and air. Prevention of further viral spread can be attained by effective disinfection of surface and air. It is suggested that sanitizers (0.1% sodium hypochlorite) can effectively arrest COVID-19 virus within a minute. This paper describes a strong IoT-based disinfectant tunnel which is used to disinfect external surface of objects, clothes, or even human skin to provide protection against COVID-19 in social or public places such as malls, schools, hospitals, airports, and offices. Primarily focusing on the significance, structural design, and functioning of the tunnel. To make the tunnel cost-effective and sustainable, solar panels and steel rods have been used. The disinfectant tunnel is highly efficient as it offers no contact disinfection or sanitization. This sensitization tunnel must detect human to sanitize, this paper illustrates a novel approach of using sensors for human detection, and since this project is based on IoT as backbone, so security model must be there to guard against malicious user. This paper also illustrates end-to-end security model. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.