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                <text>Broad-band mHz QPOs and spectral study of LMC X-4 with AstroSat</text>
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                <text>accretion, accretion discs; pulsars: general; stars: neutron; X-rays: binaries; X-rays: individual: LMC X-4</text>
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                <text>We report the results of broad-band timing and spectral analysis of data from an AstroSat observation of the high-mass X-ray binary LMC X-4. The Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) instruments onboard the AstroSat observed the source in 2016 August. A complete X-ray eclipse was detected with the LAXPC. The 340 keV power density spectrum showed the presence of coherent pulsations along with a ?26 mHz quasi-periodic oscillation feature. The spectral properties of LMC X-4 were derived from a joint analysis of the SXT and LAXPC spectral data. The 0.525 keV persistent spectrum comprised of an absorbed high-energy cut-off power law with photon index of ? ? 0.8 and cut-off at ?16 keV, a soft thermal component with kTBB ? 0.14 keV, and Gaussian components corresponding to Fe K?, Ne IX, and Ne X emission lines. Assuming a source distance of 50 kpc, we determined 0.525 keV luminosity to be ?2 1038 erg s?1  2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.</text>
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                <text>Monthly Notices of the Royal Astronomical Society, Vol-519, No. 2, pp. 1764-1770.</text>
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                <text>Sharma R., Raman Research Institute, C.V. Raman Avenue, Sadashivanagar, Karnataka, Bengaluru, 560080, India; Jain C., Hansraj College, University of Delhi, Delhi, 110007, India; Rikame K., Raman Research Institute, C.V. Raman Avenue, Sadashivanagar, Karnataka, Bengaluru, 560080, India, Department of Physics and Electronics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Paul B., Raman Research Institute, C.V. Raman Avenue, Sadashivanagar, Karnataka, Bengaluru, 560080, India</text>
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                <text>Beyond the Stats: How Investment Decisions Are Influenced by Non-Accounting Data</text>
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                <text>accounting information; decision-making factors; financial markets; financial reports; investment analysis; Investment decision-making; market information; non-accounting information; shareholders</text>
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                <text>Making investment decisions is a complex process that is influenced by data from non-accounting and accounting sources. In order to better understand the importance of financial reports in comparison to non-accounting data [1], this article examines this complexity. The study is guided by three main objectives: determining the relative importance of financial reports against non-accounting sources; determining the effect of non-accounting information on investment decisions [2]; and investigating the role of demographic factors on this effect. The study finds that, when making investment decisions, shareholders more frequently turn to non-accounting sources through thorough analysis and statistical testing. Notably, credit rating agencies, stock indices, and brokers all have a big say in how decisions are made, highlighting their significance. This work improves our knowledge of how accounting and non-accounting data interact to influence investment decision-making. It emphasizes how crucial it is to take into account a variety of information sources in order to make wise financial decisions [3]. When navigating the ever-changing market landscape of today, investors, financial analysts, and politicians can benefit greatly from these ideas.   2024 IEEE.</text>
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                <text>Sharma R.; Prajkta Yawalkar D.; Sanghvi M.; Bikash Acharjee P.; Ashfaq A.; Dixit A.</text>
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                <text>TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/TQCEBT59414.2024.10545146" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/TQCEBT59414.2024.10545146&lt;/a&gt;
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                <text>Sharma R., Christ University, Bengaluru, India; Prajkta Yawalkar D., Christ University, Bengaluru, India; Sanghvi M., Christ University, Bengaluru, India; Bikash Acharjee P., Christ University, Bengaluru, India; Ashfaq A., Christ University, Bengaluru, India; Dixit A., Christ University, Bengaluru, India</text>
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                <text>Digital Platforms and Techniques for Marketing in the Era of Information Technology</text>
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                <text>Digital marketing; Digital platforms; Digital tools</text>
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                <text>Digital marketing is the promotion of a product or service through at least one form of electronic media. This form of marketing is distinct from traditional marketing, but it uses some of the ideologies of traditional marketing. This research article examines the various technologies and platforms used in digital marketing that allow any organization or business to do this form of marketing and study what works for them and what does not. The article also explores the recent advancements in digital marketing due to the increase in users and the vast amount of data collected from these users. The two main advancements analyzed and discussed in this paper are machine learning (ML) and artificial intelligence (AI) tools.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Sharma R.; Siby A.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-400, pp. 669-677.</text>
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                <text>ISSN: 23673370; ISBN: 978-981190094-5</text>
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                <text>Sharma R., CHRIST (Deemed to Be University), Bengaluru, India; Siby A., CHRIST (Deemed to Be University), Bengaluru, India</text>
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                <text>A Study of Factors Affecting the Adoption of Digital Currencies</text>
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                <text>Economical; Social and Digital Currencies; Technological</text>
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                <text>Digital currency has taken into the world slowly but steadily, rising in the leads of trades and commercialization, which can create a huge impact on the economic wellbeing. Digital currencies can be further classified into Cryptocurrencies, Virtual currencies and Central bank digital currencies. In this research we study thefactors of adopting digital currencies. Primary data has been collected using structured questionnaire. A total of 140 responses are used for the purpose of analysis. We have used correlation and heatmap foranalysing the impact of the identified factors such as Technological, Economical and Social.   2024 IEEE.</text>
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                <text>Sharma R.K., Christ University, Bengaluru, India; Roy B., Christ University, Bengaluru, India; Shukla A., Christ University, Bengaluru, India; Acharjee P.B., Christ University, Bengaluru, India; Dixit A., Christ University, Bengaluru, India; Bhattacharjee J., Christ University, Bengaluru, India</text>
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                <text>HTLML: Hybrid AI Based Model for Detection of Alzheimers Disease</text>
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                <text>Alzheimers disease; convolutional neural network; deep learning; DenseNet121; DenseNet201; gaussian NB; SVM; XGBoost</text>
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                <text>Alzheimers disease (AD) is a degenerative condition of the brain that affects the memory and reasoning abilities of patients. Memory is steadily wiped out by this condition, which gradually affects the brains ability to think, recall, and form intentions. In order to properly identify this disease, a variety of manual imaging modalities including CT, MRI, PET, etc. are being used. These methods, however, are time-consuming and troublesome in the context of early diagnostics. This is why deep learning models have been devised that are less time-intensive, require less high-tech hardware or human interaction, continue to improve in performance, and are useful for the prediction of AD, which can also be verified by experimental results obtained by doctors in medical institutions or health care facilities. In this paper, we propose a hybrid-based AI-based model that includes the combination of both transfer learning (TL) and permutation-based machine learning (ML) voting classifier in terms of two basic phases. In the first phase of implementation, it comprises two TL-based models: namely, DenseNet-121 and Densenet-201 for features extraction, whereas in the second phase of implementation, it carries out three different ML classifiers like SVM, Nae base and XGBoost for classification purposes. The final classifier outcomes are evaluated by means of permutations of the voting mechanism. The proposed model achieved accuracy of 91.75%, specificity of 96.5%, and an F1-score of 90.25. The dataset used for training was obtained from Kaggle and contains 6200 photos, including 896 images classified as mildly demented, 64 images classified as moderately demented, 3200 images classified as non-demented, and 1966 images classified as extremely mildly demented. The results show that the suggested model outperforms current state-of-the-art models. These models could be used to generate therapeutically viable methods for detecting AD in MRI images based on these results for clinical prospective.  2022 by the authors.</text>
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                <text>Sharma S.; Gupta S.; Gupta D.; Altameem A.; Saudagar A.K.J.; Poonia R.C.; Nayak S.R.</text>
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                <text>Diagnostics, Vol-12, No. 8</text>
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 20754418</text>
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                <text>Sharma S., Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, 140401, India; Gupta S., Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, 140401, India; Gupta D., Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, 140401, India; Altameem A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, 11533, Saudi Arabia; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Nayak S.R., Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida, 201301, India</text>
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                <text>Federated Learning and Blockchain: A Cross-Domain Convergence</text>
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                <text>blockchain; consensus protocols; Federated learning; machine learning; smart contracts</text>
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                <text>Gaining significant attention within decentralized contexts, Federated Learning (FL) has been positioned as a highly desirable method for machine learning. By enabling multiple entities to train a shared model cooperatively, data privacy and security are preserved by Federated Learning. Harnessing inherent transparency and accountability of blockchain technology to trace and authenticate updates effectively in federated learning has transpired as an up-and-coming avenue to tackle data challenges related to confidentiality, protection, and reliability. This study examines the viability of federated learning and blockchain integration across multiple dimensions. The technological components of this integration., including incentive systems, consensus mechanisms, data validation, and smart contracts, are delved into. In the study, a novel proposed model for federated learning integrated with blockchain is designed and implemented. It is observed that the mean cypher size is 100 bytes for varying values of gradients. The average throughput recorded is 1.7 bytes per second, while the mean accuracy is 87.1% for 50 epochs.   2023 IEEE.</text>
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                <text>Sharma S.; Pandey A.; Sharma V.; Mishra S.; Alkhayyat A.</text>
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                <text>Proceedings - International Conference on Technological Advancements in Computational Sciences, ICTACS 2023, pp. 1121-1127.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICTACS59847.2023.10390227" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICTACS59847.2023.10390227&lt;/a&gt;
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                <text>ISBN: 979-835034233-8</text>
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                <text>Sharma S., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Pandey A., Oriental Institute of Science and Technology, Madhya Pradesh, Bhopal, India; Sharma V., Christ (Deemed to Be University), Delhi NCR, India; Mishra S., Christ (Deemed to Be University), Delhi NCR, India, Kalinga Institute of Industrial Technology, Deemed to Be University, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq</text>
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                <text>Assessment of Enablers for Adoption of Blockchain Technology in the Indian Hospitality Industry</text>
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                <text>Purpose  The chapter attempts to analyse various enablers for implementing blockchain technology in the Indian hospitality sector and examine the appropriate set of facilitators through the causal interactions among the enablers. Design/methodology/approach  To analyse the enablers for the adoption of blockchain, the tool used is the decision-making trial and evaluation laboratory (DEMATEL), which captures the judgements provided by the experts in the field for the cause-and-effect enablers and the interaction effect among these enablers. Findings  The literature suggests fifteen enablers classified into cause-and-effect enabler groups and interactions (i.e., enabling and enabled) among each blockchain adoption practice. The study reveals a reduction in cost and transparency as the most significant cause enablers and the effect variables as trust and database security. Research limitations/implications  The results generate various enablers that can be focused upon for bringing out various significant interventions in the field. The study, however, provides an understanding of the enablers for this specific industry in the Indian context. Practical implications  The results may be useful for devising policies and managerial implications related to adopting blockchain technology in the hospitality sector. Originality/value  Very few researchers have integrated the role of grey DEMATEL techniques in the hospitality industry.  2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors.</text>
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                <text>Sharma S.; Raghavendra Rao R.</text>
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                <text>Technology and Luxury Hospitality: Ai, Blockchain and the Metaverse, pp. 116-134.</text>
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                <text>Sharma S., Department of Computer Science, CHRIST (Deemed to Be University), Hosur Road, Bangalore, Karnataka, 560029, India; Sebastian S., Department of Computer Science, CHRIST (Deemed to Be University), Hosur Road, Bangalore, Karnataka, 560029, India</text>
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                <text>Role of Triguna Personality Towards Emotional Expression in Relation to Emotional Regulation</text>
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                <text>Daughters; Emotional expression; Emotional regulations; Mothers; Socio-cultural perspective; Triguna personality</text>
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                <text>With the changing times, people are more aware of their emotions regarding how to express and regulate them. The present generation is more active and expressive than the previous generation as they understand the significance of emotions in ones life. The body of literature claims that a person with better emotional understanding and expression is expected to have meaningful emotional regulation irrespective of the generation they represent. Traditional Indian Philosophy defines three essential characteristics, Sattva (purity, harmony), Rajas (activity, passion), and Tamas (resistance, darkness), that influence human behavior and experience. The degree to which one of the gunas predominates in an individual, to that extent, we characterize that person with that guna. The complicated interactions between Trigunas personality, emotional expression, and emotional regulation are examined. Considering the available facts, the present research focuses on exploring the association between emotional expression and emotion regulation strategies and the effect of the triguna personality in it, across two generations within the family. To accomplish this, a cross-sectional research design will be used to explore the generational difference, followed by a correlational research design to study the associations among variables for participants within each group. Participants would include the parents (mothers, 45 to 50 years) and their children (siblings, 18 to 24 years). The data was collected from 30 families.  2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors.</text>
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                <text>Health Psychology in Integrative Health Care, pp. 160-167.</text>
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                <text>Sharma S., Department of Psychology, Christ University, NCR, Delhi, India; Singh S., Department of Psychology, Christ University, NCR, Delhi, India; Ahirwar S., Department of Psychology, Christ University, NCR, Delhi, India; Panwar N., Department of Psychology, Christ University, NCR, Delhi, India</text>
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                <text>Social, Medical, and Educational Applications of IoT to Assist Visually Impaired People</text>
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            <name>Subject</name>
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              <elementText elementTextId="158236">
                <text>Arduino; IoT; Machine learning; Sensor applications; Sensors; Smart devices; Wearable sensors</text>
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                <text>General daily tasks have always been a problem for visually impaired people. Identification of daily objects becomes a hectic task. Traditional methods such as a walking stick and a guide dog have been helpful to the visually impaired for basic navigation. Such, methods have a lot of limitations and often fail under varied situations. Technologies such as Computer Vision and Pattern Recognition (CVPR), Image Processing (IP) Internet of Things (IoT), etc. have made a major contribution to overcoming the limitations. IoT brings a lot of technical and automated solutions to assist the visually impaired people. Data science and analytics are a major part of the process. Data accumulated via various sensors can be processed and used to identify obstacles and enhance basic navigation using haptic and voice feedback. Raw data goes through a series of analysis and refinement. This is then processed into a form which is understandable to the system and can be directly interpreted to perform various components of an application. These applications involve education, navigation, entertainment, security, consumer, etc. These applications are across various verticals of technologies differing in terms of hardware, software, and protocols. Various economically feasible and accurate solutions are now available. While, optimization remains an issue. These devices have generally been very helpful to ease the lives of visually impaired people. The main aim of this article is to provide essential details related to real-world applications of IoT in the field of education, healthcare, entertainment, security, navigation, and solutions to address the daily challenges faced by visually impaired people. The structure of the article includes introduction to IoT, applications of IoT in modern era is dealt in detail in Sect.10.1. Followed by hardware device and communication technologies in Sect.10.2. Section10.3 deals with state of art which focus majorly on research contributions related to applications of IoT and smart devices benefiting the lives of visually impaired. Section10.4 incorporates the future scope and concludes with a summary in Sect.10.5. The article covers more than 30 research contributions in the pastten years which includes journal papers, conference papers and patents which provide a detailed and clear view on the research being carried out in the field of IoT to help the visually impaired.  2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <elementText elementTextId="158238">
                <text>Sharma S.; Umme Salma M.</text>
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                <text>Studies in Big Data, Vol-73, pp. 195-214.</text>
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              <elementText elementTextId="158240">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-15-4112-4_10" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-15-4112-4_10&lt;/a&gt;
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            <description>Information about rights held in and over the resource</description>
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                <text>ISSN: 21976503</text>
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                <text>Sharma S., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Umme Salma M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India</text>
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                <text>Impact of the COVID-19 outbreak on the currency exchanges of selected countries</text>
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            <description>The topic of the resource</description>
            <elementTextContainer>
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                <text>COVID-19; Currency Exchange; Forex Market; Investor; Liquidity; Pandemic Crisis; Spot Rate; Trend Analysis</text>
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            <description>An account of the resource</description>
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                <text>The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies-USD/JPY, AUD/USD, and USD/CHF-and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers. Copyright  2022, IGI Global.</text>
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                <text>Sharma S.; Yadav M.P.; Jha B.</text>
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                <text>International Journal of Sociotechnology and Knowledge Development, Vol-14, No. 2, pp. 73-91.</text>
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                <text>ISSN: 19416253</text>
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                <text>Sharma S., Fortune Institute of International Business, Delhi, India; Yadav M.P., ACCF, Amity University, Noida, India; Jha B., Christ University, Ghaziabad, India</text>
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                <text>Bromelain enhances digestibility of Spirulina-based fish feed</text>
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                <text>Arthrospira platensis; In vitro digestibility; Microalgae; Oreochromis mossambicus; Papain; Trypsin</text>
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                <text>Microalgae like Spirulina (Arthrospira platensis) are protein rich and can be alternative protein sources to fishmeal and soybean meal in fish feed formulation. The present study aims to improve the protein bioavailability of Spirulina by cost-effective protein extraction followed by protease supplementation in fish feed, using in vitro studies. Different extraction procedures such as microwave-assisted, high pressure, and temperature-mediated extraction, boiling and an isoelectric precipitation were employed to study the protein yield from Spirulina powder, and this was compared with the conventional soybean meal and fishmeal conditioning during feed manufacture. Bromelain is a potent protease that has not been widely used as a feed additive with Spirulina. To study the comparative efficiency of bromelain and other proteases like papain and trypsin on Spirulina and conventional feed substrates, a protease assay was performed at different temperatures and enzyme concentrations. The digestibility of these substrates was also studied in vitro, using gut extracts from the fingerlings of Mozambique tilapia (Oreochromis mossambicus). Unlike an in vivo feeding trial, a novel method was used to study the effect of protease supplementation on the inherent digestibility of the gut with an in vitro method. Bromelain showed the highest activity on all the substrates at both the temperatures. Bromelain supplementation improved the in vitro digestibility of the Spirulina that were subjected to protein extraction, more than the un-extracted one. The results of the present in vitro study suggest that Spirulina could serve as an alternative protein source, and bromelain-based supplementation could improve the digestibility of Spirulina-based fish diets.  2021, Springer Nature B.V.</text>
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                <text>This book introduces recent wireless technologies and their impact on recent trends, applications, and opportunities. It explores the latest 6G, IoT, and Blockchain techniques with AI and evolutionary applications, showing how digital integration can be used to serve society. It explores the most important aspects of modern technologies, providing insights into the newest 6G technology and practices; covering the roles, responsibilities, and impact of IoT, 6G, and Blockchain practices to sustain the world economy. This book highlights the roles, responsibilities, and impact of IoT, 6G, and Blockchain and its practices. By describing the implementation strategies for Blockchain, IoT, and 6G, this book focuses on technologies related to the advancement in wireless ad-hoc networks and the current sustainability practices used in IoT. It offers popular use cases and case studies related to 6G, IoT, and Blockchain to provide a better understanding and covers the global approach towards the convergence of 6G, IoT, and Blockchain along with recent applications and future potential. The book is a reference for those working with 6G, IoT, AI, and its related application areas. Students at both the UG and PG levels in various departments such as manufacturing, electronics, telecommunications, computer science, other engineering fields, and information technology will be interested in this book. It is ideally designed for use by technology development, academicians, data scientists, industry professionals, researchers, and students.  2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Gianluigi Ferrari, and Prerna Ajmani.</text>
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                <text>Sharma V., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India; Kapse M., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University), NCR, Delhi, India; Mahajan V., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India</text>
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                <text>Robotic dining delight unravelling the key factors driving customer satisfaction in service robot restaurants using PLS-SEM and ML</text>
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                <text>machine learning; PLS-SEM; repeat experience; robotics; service restaurants; trust</text>
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                <text>In the past few years there has been a remarkable surge in demand for robot service restaurants. However, as both the technology and the concept of such restaurants are relatively new, there is a limited understanding of how consumers would react to this new change in the service industry. This study focuses on the key factors influencing customer satisfaction and their intention to repeat the experience by using two staged hybrid PLS-SEM and Machine Learning approaches. The finding confirms that perceived enjoyment, speed, and novelty influence customer satisfaction, whereas perceived usefulness has no influence. Additionally, the study uncovers that customer satisfaction and trust positively mediate the relationship and establish the link with repeat experience. The machine learning models (Artificial Neural Network, Support Vector Machines, Random Forest, K-Nearest Neighbors, Elastic Net) predict the intention to repeat the experience of the service robot with an overall model fit of around 57%. We also discussed several new and useful theoretical and practical implications for enhancing the customer experience during the visit to the restaurants.  2023 The Author(s). Published by Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Kapse M., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University), Delhi-NCR, India; Mahajan Y., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India</text>
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                <text>This article investigates the possibilities of integrating edge computing and IoT in supply chain management, as well as the adoption of disruptive technologies such as blockchain integration, digital twins, robotics, and autonomous systems. Operational efficiency can be considerably enhanced by establishing a linked and intelligent supply chain ecosystem. The benefits of this technology include increased openness, efficiency, and resilience in supply chain processes. Among the benefits include real-time product tracking, environmental sustainability, enhanced production, and cost savings. The use of blockchain technology in a three-tiered Supply Chain Network (SCN) shows promise in terms of boosting supply chain transparency and security. The SCOR model is also discussed as a comprehensive framework for optimising supply chain processes. However, concerns such as data privacy, security, and employment displacement must be solved before firms can fully reap the benefits of new technologies. Overall, embracing these innovations has the potential to revolutionise supply chain management and create trust among stakeholders.   2023 IEEE.</text>
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                <text>2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2023, pp. 1055-1062.</text>
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