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                <text>Systematic Contemplate Paradigm on Diabetes Mellitus using different Machine Learning Predictive Techniques</text>
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                <text>data set; Diabetes Mellitus; Machine Learning; Supervised; support vector machine; Unsupervised</text>
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                <text>As the foodies love fast food, from micro to combined families across the world the ratio of family members 1:4 is affected with silent killer named as diabetes. A very high blood glucose levels, metabolism, improper carbohydrate, damaged hormone insulin alleviating a human body disability leading to the silent killer of the body parts is the diabetes. An estimated 425 million of people around the globe suffering with diabetes up to 108 million to 1.7 trillion will be affected with diabetes. Therefore millennium, the universe ubiquity suffering with diabetes has next to quadrupled, growing from 9 percent and above among the people. As the eating habits of people in this trendy 21st century is dramatically devastating to the risk of overweight or obese. The silent killer diabetes consequences include kidney failure, Diabetic retinopathy, Heart attack, Stiffness of body muscles, Nerves stroke and lower limb amputation leads to type I and type II diabetes. As the researchers across the globe are using the machine learning algorithms as the reliable problem solver, The complications still continue. The purpose of this percu is to help with the apt selection of features garnishing with machine learning paradigm techniques in selecting the accurate attributes for each person to be properly diagnosed. In this archetype survey paper, we have done a systematic review chronologically a decade research which will help the researchers to explore and get the contemplate on various tangible and intangible data sets they can adopt in diagnosing the mellitus diabetes.  Grenze Scientific Society, 2023.</text>
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                <text>Padmaja K.; Mukhopadhyay D.</text>
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                <text>14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023, Vol-2023-June, pp. 1768-1775.</text>
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                <text>Padmaja K., CHRIST (Deemed to be University), Department of CSE, Bangalore, India; Mukhopadhyay D., CHRIST (Deemed to be University), Department of CSE, Bangalore, India</text>
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                <text>Coal is the plentiful and widely and universally used fuel. However, its structural characteristic makes a perception that it is only worthwhile for generating energy via combustion. Herein we report a simple method to synthesize nanometre-sized graphene sheets with amorphous carbon addends on the edges from sub-bituminous coal. The X-ray analysis reveals the presence of crystalline carbon in the amorphous background. The average number of carbon atoms and aromatic layers was estimated as ?21 and 8. The interlayer spacing d 002 for the aromatic lamellae of samples leached using HF and acetic acid, are found to be 0.352 and 0.376 nm, respectively. The oxidation of coal structure resulted in nanometre sized graphene having lateral size of 4.19 nm and stacking height of 2.3 nm. The Raman spectrum analysis confirmed the formation of finite sized, less defective graphene nanolayers with leaching. The crystalline carbon within the coal matrix displaced with chemical leaching, resulting nano-meter sized graphene sheets. The results also established that with HF leaching, carbon in coal becomes more stacked and ordered compared to organic acid leached coal.  2014 Pleiades Publishing, Ltd.</text>
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                <text>Manoj B.; Kunjomana A.G.</text>
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                <text>Russian Journal of Applied Chemistry, Vol-87, No. 11, pp. 1726-1733.</text>
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                <text>Maik Nauka-Interperiodica Publishing</text>
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                <text>&lt;a href="https://doi.org/10.1134/S1070427214110251" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1134/S1070427214110251&lt;/a&gt;
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                <text>Manoj B., Department of Physics, Christ University, Bangalore Karnataka, India; Kunjomana A.G., Department of Physics, Christ University, Bangalore Karnataka, India</text>
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                <text>Systematic literature review and future research directions for service robots in hospitality and tourism industries; [????????????????????????]</text>
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                <text>hospitality; scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR); Service robots; touchless experience; tourism sector</text>
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                <text>Service robots create a touchless experience for travellers; therefore, this research aims to conduct a systematic literature review (SLR) of service robots in the tourism and hospitality sector. This study used the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) approach for reviewing the articles. One hundred eighteen articles are selected for the final review. A thematic analysis divided the articles into three themes and nine sub-themes. For establishing the future research directions Theory, Methodology, and Context (TMC) framework was used and forty-one future research questions are proposed. The study provides various research implications concerning theory and practical perspective. Different management theories are linked with future research questions. Few review papers discussed the service robot in the context of the tourism sector, but none of these studies used the SPAR-4-SLR and TMC framework. This study comprehensively reviews the articles and provides potential future research directions.  2023 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Mukherjee S.; Baral M.M.; Nagariya R.; Venkataiah C.; Rao U.V.A.; Rao K.S.</text>
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                <text>Service Industries Journal, Vol-43, No. 15-16, pp. 1083-1116.</text>
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                <text>&lt;a href="https://doi.org/10.1080/02642069.2023.2243592" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/02642069.2023.2243592&lt;/a&gt;
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                <text>All Open Access; Bronze Open Access</text>
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                <text>ISSN: 2642069</text>
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                <text>Mukherjee S., GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam, India; Baral M.M., GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam, India; Nagariya R., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Venkataiah C., Indira Gandhi National Open University, New Delhi, India; Rao U.V.A., GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam, India; Rao K.S., GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam, India</text>
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                <text>Systematic Literature Review on Industry Revolution 4.0 to Enhance Supply Chain Operation Performance</text>
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                <text>Industry 4.0 is a notion in which industries automate systems and processes, innovate digitally, and share information. It aims to obtain a smart factory in an attempt to lessen required time in responding to consumer demand or unexpected circumstances and to enhance organizational productivity. The integration of Industry 4.0 and supply chain management (SCM) ensures immense development opportunities for manufacturing firms. This article provides a systematic literature review and formulation of the existing research on Industry 4.0 in SCM, resulting in some intriguing analyses that will be useful to academics and industry, particularly top managers. The content of the article is classified into three categories: exploratory vs. confirmatory, qualitative vs. quantitative, and management level vs. technology level. The findings will benefit managers in understanding the significance of Industry 4.0 and its relationship with SCM. The formation of clusters and their affiliations has resulted in the emergence of new areas requiring managerial attention. The article concludes by examining the possibilities of the present and future research.  2022 ACM.</text>
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                <text>Industry 4.0 is digitized revolution for manufacturers or companies where in new technologies are imbibed into their production system for their day-to-day operations or activities. So that their overall economic needs and efficiency can be improved. In manufacturing industry maintenance of the equipment is the key concern. When the equipment requires maintenance, it has to be done at the earliest, failing which companies will have to face consequences in terms of loss of customers, time and money. Solution is provided to this problem in terms of a technique called predictive maintenance. The content of the article focuses on different predictive maintenance strategies, which help manufacturers to forecast if equipment/component will fail so that its maintenance and repair can be scheduled exactly before the component fails. The results will be useful for manufacturers to understand the importance of industry 4.0 for predictive maintenance.  2023 IEEE.</text>
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                <text>Proceedings of the 3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023, pp. 194-199.</text>
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                <text>Sowmya P., Nmam Institute of Technology-Affiliated to NITTE(Deemed to Be University), Department of Robotics and Artificial Intelligence, Karnataka, Nitte, India; Ravichandran S.K., Christ University, School of Engineering and Technology, Department of Computer Science, Karnataka, Bangalore, India; Rakshitha, Nmam Institute of Technology-Affiliated to NITTE(Deemed to Be University), Department of Artificial Intelligence and Machine Learning, Karnataka, Nitte, India</text>
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                <text>Purpose: The objective of this paper is to synthesize a systematic review and showcase the findings of how interparental conflict affects the adult offsprings relationship satisfaction. Approach: The paper follows a systematic review approach adhering to PRISMA Guidelines. Findings: Three major themes were identified by the researcher that explained the consequences of interparental conflict on adult offspring. The themes are-Offspring Factors, Offspring factors feature the significant components and factors of offspring that highlight the differences in impact of interparental conflict on ones own romantic relationship; Consequences of Interparental Conflict on Offspring, which highlights the various corollaries on offspring of divorce; and Parent Factors help understand the different parental elements that affect relationship satisfaction of adult offspring. Limitations: 4 full text articles could not be accessed by the author, and hence were not accounted for in the study. Practical Implications: The study helps practitioners comprehend the extensive effects of interparental conflict for usage in therapeutic setups. It also highlights research gaps in existing literature such as lack of studies focusing on men, LGBTQ+ population, children from polygamous families and multicultural cohorts. Value/Originality: Despite the numerous studies published on the topic interparental conflict and its effects on adult offspring, no review has been done to the authors knowledge, thereby limiting the accessibility of precise information. The research aims to bridge this gap, and make comprehensive findings easily accessible.  2022 RESTORATIVE JUSTICE FOR ALL.</text>
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                <text>Paul T.; Chukkali S.</text>
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                <text>Youth Voice Journal, Vol-12</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170700584&amp;amp;partnerID=40&amp;amp;md5=5dc9b4d2b37d60f4dabe75326ec850a2" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170700584&amp;amp;partnerID=40&amp;amp;md5=5dc9b4d2b37d60f4dabe75326ec850a2&lt;/a&gt;</text>
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                <text>Paul T., Nandgram Road, Marium Nagar, Sewa Nagar, Uttar Pradesh, Ghaziabad, 201003, India; Chukkali S., CHRIST (Deemed to be University), NCR, Delhi, India</text>
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                <text>Systematic Review on Decentralised Artificial Intelligence and Its Applications</text>
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            <name>Subject</name>
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                <text>Artificial Intelligence; Blockchain; Data Privacy; Decentralised; Federated Learning; Machine Learning</text>
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                <text>Initially, Artificial Intelligence (AI) models were centralized. This resulted in various challenges. To overcome this challenge, the decentralized or distributed frameworks were developed. Recent advancements in blockchain technology and cryptography have accelerated the decentralization process. Decentralized Artificial Intelligence (DAI) is gaining a significant research attention in recent times. This study reviews various DAI techniques such as Decentralized machine learning frameworks, Federated Learning and Distributed AI marketplaces. In particular, this study focuses on reviewing the recent developments in DAI by analyzing its potential advantages and challenges.   2023 IEEE.</text>
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                <text>International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2023 - Proceedings, pp. 241-246.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Vincent M., Christ University, Department of Cse, Bangalore, India; George A.E., Christ University, Department of Cse, Bangalore, India; Christa T.S., Christ University, Department of Cse, Bangalore, India; Jayapandian N., Christ University, Department of Cse, Bangalore, India</text>
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                <text>Systematic Review on Humanizing Machine Intelligence and Artificial Intelligence</text>
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                <text>Artificial Intelligence; Cognitive Intelligence; Humanizing; Machine Learning; Social Interactions;</text>
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                <text>In this era, Machine Learning is transforming human lives in a very different way. The need to give machines the power to make decisions or giving the moral compass is a big dilemma when humanity is more divided than it has ever been. There are two main ways in which law and AI interact. AI may be subject to legal restrictions and be employed in courtroom procedures. The world around us is being significantly and swiftly changed by AI in all of its manifestations. Public law includes important facets such as nondiscrimination law and labor law. In a manner similar to this when artificial intelligence (AI) is applied to tangible technology like robots. In certain cases, artificial intelligence (AI) might be hardly noticeable to customers but evident to those who built and are using it. The behavior research offers suggestions for how to build enduring and beneficial interactions between intelligent robots and people. The human improvement is main obstacles in the development and implementation of artificial intelligence. Best practices in this area are not governed by any one strategy that is generally acknowledged. Machine learning is about to revolutionize society as it is know it. It is crucial to give intelligent computers a moral compass now more than ever before because of how divided mankind is. Although machine learning has limitless potential, inappropriate usage might have detrimental long-term implications. It will think about how, for instance, earlier cultures built trust and improved social interactions via creative answers to many of the ethical issues that machine learning is posing now.   2023 IEEE.</text>
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                <text>Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems, ICEARS 2023, pp. 1092-1097.</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/ICEARS56392.2023.10084967" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICEARS56392.2023.10084967&lt;/a&gt;
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                <text>ISBN: 979-835034664-0</text>
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                <text>Abraham J., Deemed to Be University, Christ, Department of CSE, Bangalore, India; Cherian G.J., Deemed to Be University, Christ, Department of Mechanical Engineering, Bangalore, India; Jayapandian N., Deemed to Be University, Christ, Department of CSE, Bangalore, India</text>
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          <element elementId="50">
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                <text>Tadpole domination number of graphs</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>Domination; tadpole domination number; tadpole graph</text>
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                <text>The graph obtained by joining cycle Cm to a path Pn with a bridge is called Tadpole graph denoted by Tm,n. A subset D of V (G) is said to be a tadpole dominating set of G if D is a dominating set and the set of vertices of D spans a tadpole graph Tm,n where m ? 3, n ? 1. In this paper, we find the tadpole domination number of cartesian product of certain graphs, namely, paths, cycles and complete graphs. Also the tadpole domination number for the Mycielskian of cycles and paths is obtained.   2023 World Scientific Publishing Company.</text>
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              <elementText elementTextId="92359">
                <text>Prebhath V.S.; Sangeetha V.</text>
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                <text>Discrete Mathematics, Algorithms and Applications, Vol-15, No. 8</text>
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              <elementText elementTextId="92361">
                <text>World Scientific</text>
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                <text>&lt;a href="https://doi.org/10.1142/S1793830922501737" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1142/S1793830922501737&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144773425&amp;amp;doi=10.1142%2FS1793830922501737&amp;amp;partnerID=40&amp;amp;md5=7e90ba8cab12f260bd55606241d3534c" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144773425&amp;amp;doi=10.1142%2fS1793830922501737&amp;amp;partnerID=40&amp;amp;md5=7e90ba8cab12f260bd55606241d3534c&lt;/a&gt;</text>
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                <text>ISSN: 17938309</text>
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                <text>Prebhath V.S., Department of Mathematics, CHRIST (Deemed to Be University), Karnataka, Bengaluru, India; Sangeetha V., Department of Mathematics, CHRIST (Deemed to Be University), Karnataka, Bengaluru, India</text>
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                <text>Tag indicator: a new predictive tool for stock trading</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="158652">
                <text>Mean square error (MSE); Predictive stock market tool; Stochastic gradient descent method; TAG indicator</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="158653">
                <text>In this paper, TAGan indicator for stock market prediction in which volume-based means for measuring potential trading and investing decision-making is introduced. This task has been in correlation of the changes in the volume with the changes in the actual trade volume. Using this, a concise trading strategy is formulated. Hoping to outperform the market and analyze the results by back testing across intraday, price data for the last 1 year, 2019, is performed. It was discovered that about 48.9% of the time, the volume-based trading strategy outperformed and the returns from market are also healthy enough to support the claim. Statistical methods like linear regression, mean square error in prediction and stochastic gradient descent are applied. Furthermore, while the scope of the study was limited to a few stocks in Nifty in order to mitigate selection bias, nonetheless, we hypothesize that numerous other assets that similarly possess a predictable correlation to volumes based on daily high and low are likely to exist.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.</text>
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              <elementText elementTextId="158654">
                <text>Tom T.; Cheruparambil G.; Puthussery A.</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="158655">
                <text>Lecture Notes in Networks and Systems, Vol-132, pp. 261-266.</text>
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                <text>Springer</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-15-5309-7_28" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-15-5309-7_28&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090368269&amp;amp;doi=10.1007%2F978-981-15-5309-7_28&amp;amp;partnerID=40&amp;amp;md5=8fe7f0cb0fe029a4f23a93fa9d0aa950" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090368269&amp;amp;doi=10.1007%2f978-981-15-5309-7_28&amp;amp;partnerID=40&amp;amp;md5=8fe7f0cb0fe029a4f23a93fa9d0aa950&lt;/a&gt;</text>
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              <elementText elementTextId="158659">
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                <text>ISSN: 23673370</text>
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                <text>Tom T., CHRIST (Deemed to be University), Bengaluru, India; Cheruparambil G., CHRIST (Deemed to be University), Bengaluru, India; Puthussery A., CHRIST (Deemed to be University), Bengaluru, India</text>
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              <elementText elementTextId="133752">
                <text>Taguchi-based ANN predictions to analyze the tensile strength of adhesive-bonded single lap joints</text>
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          <element elementId="49">
            <name>Subject</name>
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              <elementText elementTextId="133753">
                <text>Adhesive bonding; Artificial neural network approach; Single lap joint; Taguchi method; Tensile strength</text>
              </elementText>
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                <text>The adhesive bonding method is commonly used in various industries to join different materials because of its benefits, which include a high strength-to-weight ratio, low cost, and high efficiency properties. Automotive, aerospace, marine, and construction industries are increasingly using adhesively bonded joints because the hand layup techniques involve simpler fabrication methodologies, maintenance procedures, and controllable stress distribution parameters in the overlap region, which ultimately lead to easier production of automobile, aircraft, and ship components. The objective of the present work is primarily to assess the overlap length in conjunction with the adhesive strength of glass-epoxy adherends bonded with epoxy resin. In this article, the experiments are performed on single lap-bonded joints. The parameters considered for the current work involve the length of overlap, which is maintained at 15, 25, and 35 mm, and adhesive bonding thickness that is maintained at 0.2, 0.3, and 0.5 mm, respectively. The strength of the adhesively bonded lap joint is determined using a Universal Testing Machine (Lloyd Instruments Ltd., West Sussex, United Kingdom) with a 1-20 kN capacity. The investigational outcome reveals that, as the overlap length of the adhesively bonded single lap joint increases, a substantial increase in the joint strength is observed; additionally, it is noted that, with the increase in adhesive thickness, the joint strength decreases. It was observed that the artificial neural network-predicted values from the analysis were extremely close to the experimental values, and the difference between the experimental and predicted values was very small. Copyright  2018 by ASTM International.</text>
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                <text>Ravichandran G., Department of Mechanical Engineering, Faculty of Engineering, Christ (Deemed to Be University), Mysore Rd., Bengaluru, Karnataka, 560074, India; Rathnakar G., Department of Mechanical Engineering, ATME College of Engineering, Bannur Rd., Mysore, Karnataka, 570028, India; Ratan P., Department of Mechanical Engineering, Faculty of Engineering, Christ (Deemed to Be University), Mysore Rd., Bengaluru, Karnataka, 560074, India; Joshy J., Department of Mechanical Engineering, Faculty of Engineering, Christ (Deemed to Be University), Mysore Rd., Bengaluru, Karnataka, 560074, India; Vishal S., Department of Mechanical Engineering, Faculty of Engineering, Christ (Deemed to Be University), Mysore Rd., Bengaluru, Karnataka, 560074, India</text>
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                <text>Tailor-Made Polyelectrolyte Multilayers for the Removal of Obidoxime from Water in Microfiltration Process</text>
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                <text>bilayer; electrostatic interaction; layer-by-layer; nylon 66 membranes; poly(diallyldimethylammonium chloride); Poly(sodium 4-styrenesulfonate) solution; ultrafiltration</text>
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                <text>Abstract: The aim of this study was to develop and review the properties including removal efficacy of novel polyelectrolyte based multilayers against a pharmaceutical, obidoxime (OBD) from water. After examining a wide range of bilayer pairs based on different polyelectrolytes, the layer-by-layer (LbL) modification of polyamide microfiltration membrane with a uniform coating of poly(diallyldimethylammoniumchloride) (PDAC) and poly(sodium styrene sulfonate) (PSS) multilayers was found to be effective in its removal. The characterization of the bilayer pair was done with analytical instruments like UV-vis spectroscopy, ATR-FTIR, spectroscopic ellipsometry, TGA, SEM and AFM. The characterization of bilayer pairs demonstrated the stability and integrity of bilayer pair. The removal efficiency of bilayer buildup was analyzed by adjusting different assembly conditions and other filtration parameters. The maximum removal rate by the bilayer was 99.26% for 7 bilayer with average permeate flux of 6.19 m3/m2 day. These bilayers exhibit stable rejection properties under various applied conditions including change in pH, presence of anions, and macromolecules etc. suggesting its potential rejection application. The major factors that facilitate the rejection are found to be hydrophilic interaction and steric factor. The present study validated the application of polyelectrolyte modified microfiltration membranes as a potentially feasible and promising method for the removal of obidoxime residues from water matrix.  2020, Pleiades Publishing, Ltd.</text>
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                <text>P. Nikhil Chandra; Mothi Krishna Mohan</text>
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                <text>Membranes and Membrane Technologies, Vol-2, No. 2, pp. 132-147.</text>
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                <text>ISSN: 25177516</text>
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                <text>P. Nikhil Chandra, P.G. and Research Department of Chemistry, Sree Narayana College, Kollam, 691001, Kerala, India, Advanced Centre of Environmental Studies and Sustainable Development (ACESSD), Mahatma Gandhi University, Kottayam, 686560, Kerala, India; Mothi Krishna Mohan, Kerala Department of Sciences and Humanities, Christ University Faculty of Engineering, Bangalore, 560074, Karnataka, India</text>
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                <text>Tailoring a Multifunctional PEDOT/Co3O4-CeO2 Composite for Sustainable Energy Applications</text>
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                <text>energy applications; her analysis; pedot composites; pedot/co&lt;sub&gt;3&lt;/sub&gt;o&lt;sub&gt;4&lt;/sub&gt;-ceo&lt;sub&gt;2&lt;/sub&gt;; supercapattery</text>
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                <text>Energy sources play a crucial role in the development of the society. The gargantuan depletion of fossil fuels creates new glitches in the routine activities of human beings. Electrocatalysts can efficiently produce and store energy and, therefore, have the potential to alleviate this situation. A multifunctional electrocatalyst, Poly (3,4-ethylenedioxythiophene)/cobalt oxide-cerium oxide(PEDOT/Co3O4-CeO2), is synthesized by incorporating mixed metal oxide to 3,4-ethylenedioxythiophene (EDOT) using the in situ chemical oxidative polymerization method and is employed for both energy production and storage applications. The successful synthesis of the catalyst is confirmed through various characterization techniques. The composite shows a specific capacity of 617.8Cg?1 and a specific capacitance value of 1298.1Fg?1. The hydrogen evolution reaction (HER) analysis shows that the composite requires a low overpotential of 163.1mV at a current density of 10mAcm?2. Synthesized electrocatalysts can effectively handle the energy related issues prevailing in the society.  2024 Wiley-VCH GmbH.</text>
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                <text>Varghese A.; Devi K R S.</text>
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                <text>Advanced Sustainable Systems, Vol-8, No. 7</text>
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                <text>&lt;a href="https://doi.org/10.1002/adsu.202300575" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/adsu.202300575&lt;/a&gt;
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                <text>ISSN: 23667486</text>
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                <text>Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Devi K R S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India</text>
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                <text>Tailoring of low grade coal to fluorescent nanocarbon structures and their potential as a glucose sensor</text>
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                <text>Lignite is an abundantly utilized feedstock for the facile synthesis of fluorescent carbon dots and carbon nanomaterials. Its value is appreciated as an energy source for combustion for long time. Herein we report a novel top-down strategy to synthesis lignite based fluorescent nano carbon structures by combined acidic oxidation and chemical reflux. The nanocarbon crystallites in lignite are converted to oxygenated nano carbon dots and graphene sheets. They exhibited stable fluorescence property in the visible region depending on their size, functionalities and defects which were highly stable in all the pH conditions. These nanocarbon structures are an effective probe for fluorescent sensing of label-free and selective detection of glucose ions with detection limit as low as 0.125 mM, promising real-world sensor applications. These findings establish a scalable method for the production of fluorescent carbon based glucose sensor from lignite.  2018, The Author(s).</text>
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                <text>Scientific Reports, Vol-8, No. 1</text>
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>The research aims to examine the awareness of Artificial Intelligence among the HR managers and Talent Acquisition managers in the process of Talent Acquisition, Investigating the factors influencing the adoption and usage of Assisted Intelligence, and evaluating the impact of Artificial Intelligence on Talent Management. Multi-Stage sampling method was adopted to collect the responses from the 384 customers across the HR and TA managers working across the IT companies situated in Bangalore, Mysore, Pune, and Chennai &amp;amp; Hyderabad. SAS was applied to perform the Simple Percentage Analysis, Correlation Analysis, Multiple Linear Regression Analysis to validate the hypothesis. The demographic &amp;amp; construct variables considered were Adoption, Actual usage, Perceived usefulness, Perceived Ease of Use, &amp;amp; Talent Management. Awareness of the Artificial Intelligence technology and its adoption in managing Talent Acquisition has the positive and high correlation and followed by its actual usage. Candidate experience is the most influencing variable from the first factor, Competency and Easy to use is the most influencing variable from the second factor, Effectiveness in the adoption and actual usage of Artificial Intelligence in Talent Acquisition. Talent Management is the highest predictor of using the technology and its adoption is the most influencing predictor in the effective implementation of the technology among the Information Technology Companies.   The Authors, published by EDP Sciences.</text>
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                <text>Khan M.A., Department of Business Administration, Barani Institute of Sciences, Pakistan; Di Virgilio F., Department of Economics, University of Molise, Italy; Baber R., School of Business and Management, Christ University, Bengaluru, Karnataka, India</text>
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                <text>Employee retention is a huge challenge for many companies because of the difficulty of getting the right talent at the right place for the right job with the required potential to cope with the new changing environment. A Gartner survey revealed that 91% of HR leaders expect employee turnover in the immediate future. Even more so if employees have more job offers while joining a company, and if they find discrepancies from their expectations, they are ready to leave the job. In this scenario, it is the need for organizations to identify the beststrategies to retain talented employees. This chapter explains the concepts of talent retention, its relevance, practices, factors, and analytics contributing in retaining employees. This chapter will be helpful for organizations to devise new strategies for retaining the employees. This will also be useful for academicians and students to apply analytics in retaining employees.  2023, IGI Global. All rights reserved.</text>
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                <text>commitment and Involvement; Job Involvement; Retention</text>
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                <text>Even if there is presently much need for improvement, the information technology (IT) sector plays a key role in the nation's financial development. With enormous growth potential, India's IT sector is up against fierce competition. Numerous participants are competing with one another for resources and jobs inside the company. The direction of events and the manageability of the IT industry depend on capable employees and their responsibilities and participation. Additionally, there is a grouping of the representatives who possess the capacity. Between duty and association and ability maintenance, work fulfilment plays a crucial guiding role. The goal of the current study is to comprehend the effects of talent retention, job satisfaction, and organizational commitment in the IT industry. In this research, we looked at the variables factor analysis. In Bangalore, we chose to survey workers in the IT industry. To understand the results of Talent Retention, Job Involvement, and Commitment for IT Sector Employees, we collected the data using a questionnaire (Likert-scale), which we then analyzed using spss26.   2023 Author(s).</text>
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                <text>&lt;a href="https://doi.org/10.1063/5.0164526" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0164526&lt;/a&gt;
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                <text>Basha M.D.S.A., GITAM School of Business, Gandhi Institute of Technology and Management, GITAM University, Karnataka, Bengaluru, India; Sucharitha M.M., School of Commerce, Finance and Accountancy, CHRIST University, Karnataka, Bengaluru, India; Lakshmi M.B., School of Commerce, Finance and Accountancy, CHRIST University, Karnataka, Bengaluru, India; Kumar J.P.S., GITAM School of Business, Gandhi Institute of Technology and Management, GITAM University, Karnataka, Bengaluru, India</text>
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