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                <text>Assessing Climate Change through Artificial Intelligence An Ethico-Legal Study</text>
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                <text>IPCC (The Intergovernmental Panel on climate change) [1], in the 6th Assessment Report released in 2022, reports that the net anthropogenic GHGs (greenhouse gases) continued to rise during the period 2010-19. It shows that GHG emission in the last decade is the highest in human history. According to the World Inequality Report, 2022, carbon dioxide concentration level in the atmosphere across the globe is the highest in millions of years. Consistent rise in the global emission level leading to alarming rise in atmospheric temperature has been a cause of concern for mankind. Rising atmospheric temperature leading to climate change has severely affected weather patterns; led to melting of glaciers; caused natural disaster and extinction of species, and severely impacted the ground water table. It has put the human race at a crossroads and thrown open an existential question for the world. Attempts have been made, both international and national, to reverse the impact of the rising scenario concerning climate change but have yet to be successful. The technological revolutions arising in recent times, especially in the domain of Artificial Intelligence (AI), offer hope to give a new shape to human civilization. With the aid of human intelligence, AI can perform assessment and predictive work as well which may help in mitigating the effect of adversely affecting climate change and help improve the environment. As per UNESCO (United Nations Educational, Scientific and Cultural Organisation), AI can perform assessment and prediction of climate change, which may assist in the protection of the environment. The Council identifies three priority areas relating to use of AI which includes improved understanding and predictions of climate change and geohazards [2]. This chapter aims at exploring the contribution of AI in assessing the behavioral pattern of climate change and the ethico-legal challenges involved therein.  2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.</text>
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                <text>Mishra A.; Pandey A.; Mohanty S.</text>
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                <text>Artificial Intelligence in Forecasting: Tools and Techniques, pp. 130-145.</text>
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                <text>CRC Press</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003399292-10" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003399292-10&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195927973&amp;amp;doi=10.1201%2F9781003399292-10&amp;amp;partnerID=40&amp;amp;md5=9fa9d29f725360f5968530c45efe9ee2" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195927973&amp;amp;doi=10.1201%2f9781003399292-10&amp;amp;partnerID=40&amp;amp;md5=9fa9d29f725360f5968530c45efe9ee2&lt;/a&gt;</text>
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                <text>ISBN: 978-104005150-4; 978-103250615-9</text>
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                <text>Mishra A., School of Law, Christ University, Karnataka, Bangalore, India; Pandey A., School of Law, Christ University, Karnataka, Bangalore, India; Mohanty S., School of Law, Christ University, Karnataka, Bangalore, India</text>
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                <text>Return volatility transmission among Asian stock exchanges: Evidence from a heterogeneous market outlook</text>
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            <description>The topic of the resource</description>
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                <text>: Stock exchange; Asian stock exchange; VAR; volatility Spill-over</text>
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                <text>. This pragmatic research strives to reveal the return volatility transmission throughout Asian stock exchanges, by employing variance decomposition technique of Vector autoregressive (VAR) based framework. Additionally, the current examination exerts a Granger causality approach to detect short-term cause and effect among the stock exchanges. The consequence of volatility spill-over exhibits the dominancy of Indian, Chinese and Japanese exchanges in terms of net volatility transmitter. Further, it is found that Korean, Thai, and Malaysian stock exchanges seem to be net receiver of volatility in Asia. Additionally, the outcome of current investigation reveals neutrality of Bangladeshi and Pakistani stock exchange, as the returns volatility of these stock exchange are not influenced by any other Asian stock exchanges. Furthermore, the result of Granger causality analysis signifies the existence of unidirectional causality among the Asian stock exchanges. In terms of policy implication, it is imperative for investors and policymakers to closely monitor the behaviour of the Japanese stock exchange, as it plays a significant role as a net transmitter of volatility to other stock exchanges in Asia. By keeping a vigilant eye on the Japanese stock exchange, investors can better assess and manage potential risks and opportunities in the region.  2023  IOS Press. All rights reserved.</text>
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            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="90830">
                <text>Mishra A.; Sakuja V.</text>
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            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="90831">
                <text>Risk and Decision Analysis, Vol-9, No. 45749, pp. 73-85.</text>
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                <text>IOS Press BV</text>
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              <elementText elementTextId="90833">
                <text>2023-01-01</text>
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            <description>An unambiguous reference to the resource within a given context</description>
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                <text>&lt;a href="https://doi.org/10.3233/RDA-231537" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3233/RDA-231537&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180360774&amp;amp;doi=10.3233%2FRDA-231537&amp;amp;partnerID=40&amp;amp;md5=886c7930a20b2a8d99edc8b75a91bb4a" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180360774&amp;amp;doi=10.3233%2fRDA-231537&amp;amp;partnerID=40&amp;amp;md5=886c7930a20b2a8d99edc8b75a91bb4a&lt;/a&gt;</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="90835">
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              <elementText elementTextId="90836">
                <text>ISSN: 15697371</text>
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              <elementText elementTextId="90838">
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                <text>Mishra A., Department of Economics, Birla Global University, Bhubaneswar, India; Sakuja V., Department of Economic, CHRIST (Deemed to be University), Delhi NCR, India</text>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108272">
                <text>Phytochemical analysis and antioxidant activities of Artemisia stelleriana Besser leaf extracts</text>
              </elementText>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108273">
                <text>Antioxidant activity; Artemisia stelleriana; DPPH; Total phenolic content</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108274">
                <text>The present study aims to report the proximate and mineral composition, phenolic contents, and antioxidant potential of Artemisia stelleriana leaves. The leaf extracts were prepared using various solvents like distilled water, methanol, ethanol and acetone and analyzed for their phenolic and flavo-noid contents and antioxidant activity. The methanolic extracts showed the highest total phenolic and flavonoid contents (10.09  0.24 mg GAE/g and 225.04  0.38 mg QE/g respectively). The methanolic extracts showed signifi-cantly higher 1,1-Diphenyl-2-picrylhydrazyl radical scavenging assay (DPPH-RSA), Reducing power assay and total antioxidant capacity compared to distilled water, ethanol and acetone extracts. Gas Chromatography-Mass Spectroscopy revealed that the methanolic extracts of leaves to be a good source of bioactive compounds like 2,4-di-tert-butylphenol (2,4-DTBP), neo-phytadiene, octacosane and eucalyptol.  2022 Horizon e-Publishing Group. All rights reserved.</text>
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          <element elementId="39">
            <name>Creator</name>
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              <elementText elementTextId="108275">
                <text>Mishra M.; Das A.; Sebastian J.K.</text>
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              <elementText elementTextId="108276">
                <text>Plant Science Today, Vol-9, No. 2, pp. 215-220.</text>
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              <elementText elementTextId="108277">
                <text>Horizon e-Publishing Group</text>
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                <text>2022-01-01</text>
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              <elementText elementTextId="108279">
                <text>&lt;a href="https://doi.org/10.14719/pst.1263" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.14719/pst.1263&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128613778&amp;amp;doi=10.14719%2Fpst.1263&amp;amp;partnerID=40&amp;amp;md5=0b220f433753792adc136da3c95474e5" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128613778&amp;amp;doi=10.14719%2fpst.1263&amp;amp;partnerID=40&amp;amp;md5=0b220f433753792adc136da3c95474e5&lt;/a&gt;</text>
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              <elementText elementTextId="108280">
                <text>All Open Access; Gold Open Access</text>
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            <description>A related resource</description>
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              <elementText elementTextId="108281">
                <text>ISSN: 23481900</text>
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                <text>Online</text>
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              <elementText elementTextId="108283">
                <text>English</text>
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          <element elementId="51">
            <name>Type</name>
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              <elementText elementTextId="108284">
                <text>Article</text>
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              <elementText elementTextId="108285">
                <text>Mishra M., Department of Life sciences, CHRIST (Deemed to be University), Bengaluru, 560 029, India; Das A., Department of Life sciences, CHRIST (Deemed to be University), Bengaluru, 560 029, India; Sebastian J.K., Department of Life sciences, CHRIST (Deemed to be University), Bengaluru, 560 029, India</text>
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            <description>A name given to the resource</description>
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              <elementText elementTextId="123637">
                <text>Zirconia Supported on Rice Husk Silica from Biowaste: A Novel, Efficient, and Recoverable Nanocatalyst for the Green Synthesis of Tetrahydro-1-benzopyrans</text>
              </elementText>
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          </element>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="123638">
                <text>heterogeneous reusable catalyst; multicomponent reactions (MCR); rice husk silica-supported zirconia; tetrahydro-1-benzopyrans</text>
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                <text>Abstract: Zirconia supported silica from rice husk (an agricultural waste) has been utilized as a novel and efficient heterogeneous catalyst for the synthesis of bioactive tetrahydro-1-benzopyran derivatives via multicomponent condensation of various aldehydes with dimedone and malononitrile. This protocol offers various advantages such as high yields, simple experimental work-up procedure, short reaction time, no by-products, economic availability, easy purification, and reusability of the catalyst.  2020, Pleiades Publishing, Ltd.</text>
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              <elementText elementTextId="123640">
                <text>Mishra M.; Devi K.R.S.; Pinheiro D.; Nizam A.</text>
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                <text>Mishra M., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Devi K.R.S., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Pinheiro D., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Nizam A., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India</text>
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                <text>Face recognition has been the most successful image processing application in recent times. Most work involving image analysis uses face recognition to automate attendance management systems. Face recognition is an identification process to verify and authenticate the person using their facial features. In this study, an intelligent attendance management system is built to automate the process of attendance. Here, while entering, a persons image will get captured. The model will detect the face; then the liveness model will verify whether there is any spoofing attack, then the masked detection model will check whether the person has worn the mask or not. In the end, face recognition will extract the facial features. If the persons features match the database, their attendance will be marked. In the face of the COVID-19 pandemic, wearing a face mask is mandatory for safety measures. The current face recognition system is not able to extract the features properly. The Multi-task Cascaded Convolutional Networks (MTCNN) model detects the face in the proposed method. Then a classification model based on the architecture of MobileNet V2 is used for liveness and mask detection. Then the FaceNet model is used for extracting the facial features. In this study, two different models for the recognition have been built, one for people with masks another one for people without masks.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Mishra M.; Jacob L.; Shukla S.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-462, pp. 53-68.</text>
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                <text>ISSN: 23673370; ISBN: 978-981192210-7</text>
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                <text>Mishra M., Christ University, Bangalore, India; Jacob L., Christ University, Bangalore, India; Shukla S., Christ University, Bangalore, India</text>
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                <text>Switchable surface activity of Bi2Al4O9 nano particles: A contemporary approach in heterocyclic synthesis</text>
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                <text>Azalactones; Bi&lt;sub&gt;2&lt;/sub&gt;Al&lt;sub&gt;4&lt;/sub&gt;O&lt;sub&gt;9&lt;/sub&gt; nanoparticles; Ferroelectric catalysis; Pyranopyrazoles; Tetrahydrobenzo[b]pyrans; Thermal induced polarization field</text>
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                <text>Ferroelectric catalysis is emerging as an efficient chemical transformation strategy, especially in the field of clean energy production, wastewater treatment and degradation of pollutants. The core of ferroelectric catalysis is the dynamically switchable electrical polarization on their surface. It enables them to switch their surface activity, more precisely due to binding strength with the substrate. Even though a plethora of reports are available, the introduction of ferroelectric catalytic surfaces for the generation of heterocyclic compounds is a novel aspect. Here, we introduce ferroelectric Bismuthaluminate nanoparticles as catalysts for generating derivatives of azalactone, tetrahydro-benzopyran and pyranopyrazole with improved catalytic efficiency. This can be achieved by switching the direction of polarization of the catalyst which indeed alters the surface electronic states and stimulates the reaction followed by the excellent yield. Here the switchable property is due to the thermally induced polarization of water. Graphical Abstract: [Figure not available: see fulltext.].  2023, The Author(s), under exclusive licence to Springer Nature B.V.</text>
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                <text>Mishra M.; Jomon K.J.; Chinnam S.; Devasia J.; Nizam A.; Reddy M.B.M.</text>
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              <elementText elementTextId="97826">
                <text>Journal of Nanoparticle Research, Vol-25, No. 3</text>
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                <text>Springer Science and Business Media B.V.</text>
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                <text>&lt;a href="https://doi.org/10.1007/s11051-023-05703-8" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s11051-023-05703-8&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149975308&amp;amp;doi=10.1007%2Fs11051-023-05703-8&amp;amp;partnerID=40&amp;amp;md5=4ca6f22eb5b7afb67d3cf5fc04d84ab7" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149975308&amp;amp;doi=10.1007%2fs11051-023-05703-8&amp;amp;partnerID=40&amp;amp;md5=4ca6f22eb5b7afb67d3cf5fc04d84ab7&lt;/a&gt;</text>
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                <text>ISSN: 13880764</text>
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              <elementText elementTextId="97833">
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                <text>Mishra M., Department of Chemistry, CHRIST (Deemed to Be University), Bangalore, 560029, India; Jomon K.J., Department of Chemistry, CHRIST (Deemed to Be University), Bangalore, 560029, India; Chinnam S., Department of Chemistry, M. S. Ramaiah Institute of Technology (Affiliated to Visvesvaraya Technological University, Belgaum), Bengaluru, 560054, India; Devasia J., Department of Chemistry, CHRIST (Deemed to Be University), Bangalore, 560029, India; Nizam A., Department of Chemistry, CHRIST (Deemed to Be University), Bangalore, 560029, India; Reddy M.B.M., Department of Chemistry, School of Applied Sciences, REVA University, Bengaluru, 560064, India</text>
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                <text>[18-C-6H3O+]: an in-situ generated macrocyclic complex and an efficient, novel catalyst for synthesis of pyrano[2,3-c]pyrazole derivatives</text>
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                <text>Synthesis of small aromatic heterocycles is of greater importance in the organic chemistry due to their vibrant applications in pharmaceuticals, agrochemicals and veterinary products. Pyranopyrazoles are one such class of heterocycles associated with numerous applications. Hence herein we report a multicomponent crown ether catalyzed, ultrasound irradiated methodology to make different functionalized pyranopyrazoles in a single step. This technique involves the in-situ generation of [18-C-6H3O+][OH?] complex, which in turn activates the aromatic aldehyde and aids in the facile nucleophilic addition.  2020, The Author(s).</text>
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                <text>Mishra M.; Jomon K.J.; Krishnan V.R.S.; Nizam A.</text>
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                <text>Scientific Reports, Vol-10, No. 1</text>
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                <text>Nature Research</text>
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                <text>&lt;a href="https://doi.org/10.1038/s41598-020-70665-z" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1038/s41598-020-70665-z&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090019653&amp;amp;doi=10.1038%2Fs41598-020-70665-z&amp;amp;partnerID=40&amp;amp;md5=c96d1f71c0475048191681d680e5f40b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090019653&amp;amp;doi=10.1038%2fs41598-020-70665-z&amp;amp;partnerID=40&amp;amp;md5=c96d1f71c0475048191681d680e5f40b&lt;/a&gt;</text>
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 20452322; PubMed ID: 32868818</text>
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                <text>Mishra M., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Jomon K.J., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Krishnan V.R.S., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Nizam A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India</text>
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                <text>A New Facile Ultrasound-Assisted Magnetic Nano-[CoFe2O4]-Catalyzed One-Pot Synthesis of Pyrano[2,3-c]pyrazoles</text>
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                <text>multicomponent reactions (MCR); nano-[CoFe&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;4&lt;/sub&gt;]; pyrano[2,3-c]pyrazoles; sonochemistry</text>
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                <text>Pyrano[2,3-c]pyrazole derivatives have been synthesized through a one-pot multicomponent condensation of various aldehydes, dialdehydes, and ketones with malononitrile, ethyl acetoacetate, hydrazine hydrate (or phenylhydrazine) in the presence of magnetic nano-[CoFe2O4] catalyst under ultrasonic irradiation. The catalyst can be recovered using an external magnet and used repeatedly.  2019, Pleiades Publishing, Ltd.</text>
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                <text>Russian Journal of Organic Chemistry, Vol-55, No. 12, pp. 1925-1928.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078359626&amp;amp;doi=10.1134%2FS1070428019120194&amp;amp;partnerID=40&amp;amp;md5=2aa887636ef31ce0bcb39dfb2acd38fe" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078359626&amp;amp;doi=10.1134%2fS1070428019120194&amp;amp;partnerID=40&amp;amp;md5=2aa887636ef31ce0bcb39dfb2acd38fe&lt;/a&gt;</text>
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                <text>ISSN: 10704280; CODEN: RJOCE</text>
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                <text>Mishra M., Department of Chemistry, Christ University, Bengaluru, 560029, India; Nizam A., Department of Chemistry, Christ University, Bengaluru, 560029, India; Jomon K.J., Department of Chemistry, Christ University, Bengaluru, 560029, India; Tadaparthi K., Department of Chemistry, Christ University, Bengaluru, 560029, India</text>
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                <text>A hybrid scheme of image compression employing wavelets and 2D-PCA</text>
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            <name>Subject</name>
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              <elementText elementTextId="137308">
                <text>2D-PCA; Feature matrix; Image compression; Projection vector; Wavelet structural similarity index</text>
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                <text>In this paper, we have presented a method of compressing 2D grey-scale images employing wavelets and two-dimensional principal component analysis (2D-PCA). Principal component analysis (PCA) is an already established technique for image compression which primarily aims at exploiting inter pixel redundancies present in the image, while wavelet is a tool widely used in multi-resolution image processing. In the proposed method the image is subjected to a multi-resolution decomposition using wavelet. Subsequently, 2D-PCA is applied on the set of detail images at each level of resolution. The compressed form of the image is constituted by representative pairs of principal components and projection vectors from each level of resolution along with the approximate image at the coarsest resolution. The proposed method requires relatively few number of principal components (of varied dimension) to produce improved compression ratio with acceptable peak signal to noise ratio (PSNR). The method has been implemented and tested on a set of real 2D grey-scale images and the results have been assessed on both qualitative and quantitative basis by measuring parameters like compression ratio (CR), PSNR, structural similarity index measurement (SSIM) and the overall performance is found to be satisfactory. Copyright  2017 Inderscience Enterprises Ltd.</text>
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              <elementText elementTextId="137310">
                <text>Mishra M.K.; Ghosh R.; Mukhopadhyay S.</text>
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                <text>International Journal of Computational Vision and Robotics, Vol-7, No. 5, pp. 522-537.</text>
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                <text>&lt;a href="https://doi.org/10.1504/IJCVR.2017.086275" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1504/IJCVR.2017.086275&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029212783&amp;amp;doi=10.1504%2FIJCVR.2017.086275&amp;amp;partnerID=40&amp;amp;md5=198d4ebaedc93d0f7ec4e49daa82caa3" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029212783&amp;amp;doi=10.1504%2fIJCVR.2017.086275&amp;amp;partnerID=40&amp;amp;md5=198d4ebaedc93d0f7ec4e49daa82caa3&lt;/a&gt;</text>
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              <elementText elementTextId="137315">
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                <text>ISSN: 17529131</text>
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                <text>Mishra M.K., Department of Computer Science, Christ University, Bengaluru, 560029, India; Ghosh R., Nomura Research Institute Financial Technologies, Kolkata, 700106, India; Mukhopadhyay S., Department of Computer Science and Engineering, Indian School of Mines, Dhanbad, 826004, India</text>
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          <element elementId="50">
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            <elementTextContainer>
              <elementText elementTextId="189437">
                <text>Encryption of motion vector based compressed video data</text>
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          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="189438">
                <text>Accordion matrix; CR; Motion compensation; Motion estimation; Motion vector; MSE; PSNR; Run-length coding</text>
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              <elementText elementTextId="189439">
                <text>Enormous size of video data for natural scene and objects is a burden, threat for practical applications and thus there is a strong requirement of compression and encryption of video data. The proposed encryption technique considers motion vector components of the compressed video data and conceals them for their protection. Since the motion vectors exhibit redundancies, further reduction of these redundancies are removed through run-length coding prior to the application of encryption operation. For this, the motion vectors are represented in terms of ordered pair (val, run) corresponding to the motion components along the row and column dimensions, where val represents value of the motion vector while run represents the length of repetition of val. However, an adjustment for having maximal run is made by merging the smaller run value. Eventually we encrypted the val components using knapsack algorithm before sending them to the receiver. The method has been formulated, implemented and executed on real video data. The proposed method has also been evaluated on the basis of some performance measures namely PSNR, MSE, SSIM and the results are found to be satisfactory.  Springer International Publishing Switzerland 2016.</text>
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                <text>Mishra M.K.; Mukhopadhyay S.; Biswas G.P.</text>
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                <text>Smart Innovation, Systems and Technologies, Vol-51, pp. 349-357.</text>
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              <elementText elementTextId="189442">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="189443">
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                <text>&lt;a href="https://doi.org/10.1007/978-3-319-30927-9_34" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-319-30927-9_34&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969248507&amp;amp;doi=10.1007%2F978-3-319-30927-9_34&amp;amp;partnerID=40&amp;amp;md5=2869f18c5803e884a14c4f9863ae5bfd" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969248507&amp;amp;doi=10.1007%2f978-3-319-30927-9_34&amp;amp;partnerID=40&amp;amp;md5=2869f18c5803e884a14c4f9863ae5bfd&lt;/a&gt;</text>
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              <elementText elementTextId="189445">
                <text>Restricted Access</text>
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                <text>ISSN: 21903018; ISBN: 978-331930926-2</text>
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                <text>Online</text>
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              <elementText elementTextId="189448">
                <text>English</text>
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                <text>Mishra M.K., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India; Mukhopadhyay S., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India; Biswas G.P., Department of Computer Science, Christ University, Bangalore, 560029, India, Department of CSE, Indian School of Mines, Dhanbad, 826004, Jharkhand, India</text>
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      <name>Book Chapter</name>
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                <text>Symbiotic cyanobacteria in gymnosperms</text>
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                <text>Coralloid roots; Cyanobacteria; Cycads; Nostoc; Symbiosis</text>
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                <text>Cyanobacteria are a widespread group of phototrophic bacteria that are morphologically diverse and present on almost every environment on earth. Many cyanobacteria are able to fix atmospheric nitrogen and thus are able to form symbiotic association with a wide range of eukaryotic hosts such as plants, fungi, sponges, and protists. Cyanobacteria are able to provide carbon to nonphotosynthetic hosts such as fungi, but their primary role is to supply fixed nitrogen to enable the host to flourish in nitrogen poor environments. In turn, cyanobionts get the benefits of protection from competition, predation, and environmental extremes. Of all the cyanobacterial symbiotic associations, this chapter focuses on understanding the symbiotic association between gymnosperm and cyanobacteria. Species belonging to phylum cycadophyta are associated with nitrogen-fixing cyanobacteria (Nostoc species) through small specialized roots called coralloid roots. The cyanobionts are expected to have a heterotrophic mode of carbon nutrition, due to their location in coralloid roots (complete darkness).  2023 Elsevier Inc. All rights reserved.</text>
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                <text>Mishra N., Department of Botany, St. Joseph's University, Karnataka, Bengaluru, India; Rakesh B., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India</text>
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                <text>In today's dynamic digital landscape, blockchain technology emerges as a pioneering force with the potential to redefine industries and transform the way we conduct business, share information, and establish trust. This chapter explores the foundational concepts of blockchain technology, its versatile applications, and the profound impacts it can have on various sectors. While blockchain holds immense promise, challenges like scalability, energy consumption, and regulatory frameworks must be addressed. Decentralized apps and smart contracts introduce new vulnerabilities that demand vigilant management. The integration of blockchain with wireless technology expands opportunities and streamlines processes. Wireless connectivity enhances accessibility, reach, and interaction with blockchain applications, benefiting finance, supply chain, and healthcare sectors. Real-time data sharing and reduced infrastructure reliance boost productivity. Environmental concerns, including blockchain's energy consumption and e-waste from wireless devices, need mitigation. In conclusion, the fusion of blockchain and wireless technology offers tremendous potential but demands a delicate balance between technological progress and environmental stewardship. Addressing reliability, security, scalability, and environmental impacts through innovative solutions and ethical practices is vital for a connected and sustainable future.  2024 CRC Press.</text>
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                <text>Mishra N., Department of Economics, School of Arts and Humanities, FS University, Uttar Pradesh, Shikohabad, India; Sharma V., Department of Computational Sciences, CHRIST (Deemed to be University), Delhi NCR Campus, India</text>
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                <text>We are living in a society that has been engulfed with growing technology, and the integration of it has become such an important part of our lives that it is scary to think of our daily lives without mobile phones, internet, or smart gadgets. Industry 4.0, briefly, means using new age technologies such as cloud computing, artificial intelligence, machine learning, Internet of Things, and big data in the different real-world applications of manufacturing, processing, and distribution of goods and services. Industry 4.0 involves making use of smart factories and technologies to minimize waste and to gain an absolute advantage in the development process. We already know the different use cases of these technologies and how these things help in lessening our workload, so it seems logical to apply them to broader aspects of our daily lives. Technologies mitigate our workload and improve efficiency. We have seen that these technologies are proving useful in different spheres of economics, with the help of new decision-making processes, model predictions, and even to improve healthcare. Through the scope of this chapter, we would shed light on how these different technologies are being incorporated and how these would help in stabilizing industry by its constant integration.  2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa.</text>
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                <text>Mishra N., FS University, India; Sharma V., Computer Science Department CHRIST (Deemed to be University), Delhi-NCR, India; Shankar A., University of Warwick, United Kingdom</text>
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                <text>Gated Recurrent Unit(GRU); Illegal Activity; Law Enforcement Officers (LEO)</text>
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                <text>The main reaction to the illicit extraction of natural resources in protected areas around the world is law enforcement patrols headed by rangers. On the other hand, research on patrols' efficacy in reducing criminal behavior is lacking. Similarly, tactics to enhance the effectiveness of patrol organization and monitoring have received very little attention. Sequencing is crucial for model training, feature selection, and preprocessing. Preprocessing steps include cleaning, discretizing, duplicating, and normalizing data. Feature selection makes use of genetic algorithms, which are basically search algorithms with an evolutionary bent that factor in natural selection and genetics. Training stacked GRU models necessitates meticulous feature management. Even the most cutting-edge algorithms, GRU and BiGRU, are no match for the suggested technique. An astounding 97.24% accuracy grade was disclosed by the results, showcasing exceptional growth.   2024 IEEE.</text>
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                <text>In the past two decades, corporate sustainability reporting has witnessed tremendous growth and garnered a lot of attention among scholars, and practitioners around the world. It is no longer a matter of choice for companies due to immense pressure from various stakeholders to adopt sustainability practices. This article aims to analyze key research themes in Sustainability Reporting and its disclosure from 2002 to 2022, assess their impact, track field evolution, and identify emerging areas for future study. The data have been collected from the SCOPUS database using relevant keywords and utilized VOSviewer and Biblioshiny tools for bibliometric analysis, including citation trends, authorship patterns, and keyword frequency. This study reveals a surge in scholarly literature since 2012, with prominent clusters in sustainable development, sustainability, decision-making, and stakeholder engagement. CSR emerges as the dominant keyword. This study presents a comprehensive evaluation of existing scholarly work in the field of sustainability reporting, highlights emerging trends, and suggests future research directions in corporate sustainability. It also provides practical implications for organizations, policymakers, and stakeholders, bridging the theorypractice gap and enhancing researchs practical value.  The Author(s), under exclusive licence to Springer Nature Limited 2023.</text>
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                <text>In recent times, policymakers and scholars have directed their attention toward the notion of sustainability and green finance, coinciding with the growing global emphasis on environmental protection, climate change mitigation, and sustainable development. The integration of sustainability and green finance practices has emerged as a crucial strategy to address climate change, advance sustainable development goals issues, and build a resilient global economy in the face of pressing environmental challenges. The adoption of green finance and sustainability practices is no longer limited to developed economies. Many developing and under-developed countries are also taking a proactive approach to develop and implement a roadmap and framework for incorporating sustainability. In this chapter, the authors explore the notion of green finance, its crucial role in advancing sustainability, and the substantial consequences it can bring about for diverse businesses and stakeholders.  2023, IGI Global. All rights reserved.</text>
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                <text>As a response to the threat of climate change, a growing number of businesses are voluntarily reporting carbon statistics. This article provides a comprehensive understanding of carbon disclosure, organization performance (OP), and cost of capital. This study aims to map the landscape of existing carbon disclosure and firm performance research completed over the past 10 years (2013-2022) utilizing bibliometric analysis. Sparked by the growing political, social, academic, and practical significance of controlling and reporting on climate-related concerns worldwide, this study analyzes the production and acquisition of information about significant regions and territories, institutions, publications, and channels for carbon disclosure and firm performance research using data from 878 publications retrieved from the Scopus database. To identify themes and subthemes in the research on carbon disclosure and firm performance, network analysis was utilized to reveal connections between the topics represented by keywords. Further, critical gaps have been highlighted in the literature, such as: the lack of carbon disclosure research across cross-sector settings, the lack of sectorial comparisons on the carbon disclosure practices, and the dearth of analyses of both pre-carbon disclosure and after-carbon disclosure practices and their impact on various financial and nonfinancial issues (for example, cost of capital and firm performance, sustainability, and climate change). Finally, this study makes specific recommendations for future carbon disclosure and firm performance research.  2023 Mary Ann Liebert, Inc., publishers.</text>
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                <text>The evolutions that occurred in the past decades have provoked variations in the market as well as academic and research. Given this scenario, the research explored in this article was aimed to analyze the contribution of the management of PMBOK methods for the optimization of Scientific Editorial Flow. The methodology used presented a quantitative approach, of descriptive character based on a survey, made available on social networks and Facebook groups, through the google forms platform. The sample is given by Snowball, this type of sampling enables the researcher to study specific groups and is difficult to reach. The analysis was by descriptive statistics, using the Likert scale, as well as the weighted average and fashion responses. It was identified that the Critical Success Factors of a Project that can contribute to the optimization of the editorial flow of a Scientific Periodical are efficient communication, empowerment, change management, client involvement, supplier involvement and conflict management.  2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Mishra P.; Weersma L.; Desai N.; Uppal A.; Sharma S.; Gupta S.K.; Rajsekar D.; Zadnieprovska G.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-621 LNNS, pp. 33-47.</text>
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                <text>ISSN: 23673370; ISBN: 978-303126955-4</text>
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                <text>Mishra P., Sri Balaji University, Pune, India; Weersma L., Centre Christ University, Bengaluru, Brazil; Desai N., Dr D Y Patil Institute of Management Studies, Pune, India; Uppal A., Dr D Y Patil Institute of Management Studies, Pune, India, P P Savani University, Surat, India; Sharma S., DIT University, Dehradun, India; Gupta S.K., AMET University, Chennai, India; Rajsekar D., AMET University, Chennai, India; Zadnieprovska G., V.N. Karazin, Kharkiv National University, Kharkiv, Ukraine</text>
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                <text>Exploring the Opportunities of AI Integral with DL and ML Models in Financial and Accounting Systems</text>
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          <element elementId="49">
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                <text>accounting; case studies; empirical analysis; ethical considerations; Explainable AI; financial decisionmaking; interpretability; regulatory compliance; transparency; XAI techniques</text>
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                <text>With the integration of artificial intelligence (AI), today's fast financial landscape increasingly promises the most efficient and accurate processes for decision-making in accounting practices. On the other hand, the opacity of models represents a truly difficult challenge, given that transparency and accountability are key for using AI in making financial decisions. This is a research paper that focuses on the explanation of an XAI model application as a way of improving transparency in financial decision-making within the accounting field. The paper begins by outlining how transparency is important and opens the room for trust and understanding in the process of financial decision-making. Traditional black-box AI models, although able to provide remarkable predictions, usually exhibit low interpretability; this entails that stakeholders may have a small degree of understanding regarding the rationale behind the decisions. This provides a cloudy appearance not to hamper trust and supports compliance with regulatory standards like GAAP (Generally Accepted Accounting Principles) and IFRS (International Financial Reporting Standards). The proposed work applies to the accounting domain and brings about some of the different XAI techniques that are designed under this domain. The following techniques aim at demystifying the AI algorithms for effective AI stakeholders' understanding of the model predictions and underlying decision-making processes.  2024 IEEE.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Mishra R.K., Christ University, Bengaluru, India; Srivastava S., Christ University, Bengaluru, India; Singh S., Christ University, Bengaluru, India; Upadhyay M.K., St. Xavier's College of Management &amp;amp; Technology, Patna, India</text>
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