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                <text>Towards a Smarter Connected Society by Enhancing Internet Service Providers' QoS metrics using Data Envelopment Analysis</text>
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                <text>This paper analyses wireline broadband Quality of Service (QoS) metrics of India's small and medium Internet Service Providers (ISPs). Key Performance Indicators (KPIs) used in this analysis are - Fault repair (&amp;gt;90% in 1 working day and &amp;gt;=99% in 3 working days), Response time to customer for voice-to-voice operator assistance (in 60 sec. &amp;gt;60% and in 90 sec. &amp;gt;90%), Broadband connection speed from ISP to node (Download speed) and Service availability/uptime. Benchmarks are arrived at, using the Slack Based Measure (SBM) in Data Envelopment Analysis (DEA). Twenty Decision Making Units (DMUs - ISPs) were used in the analysis with eight of them needing to improve their QoS on some of the mentioned parameters. Relative benchmark providers for all providers needing improvement with their weightage are found and optimal targets by each QoS metric is mathematically arrived at.  The Electrochemical Society</text>
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                <text>Gracia S.; Soundarabai P.B.; Raj P.</text>
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                <text>ECS Transactions, Vol-107, No. 1, pp. 225-239.</text>
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                <text>Institute of Physics</text>
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                <text>ISSN: 19386737; ISBN: 978-160768539-5</text>
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                <text>Gracia S., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Soundarabai P.B., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Raj P., Reliance Jio Platforms Ltd., Karnataka, Bangalore, India</text>
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                <text>TOWARDS A SUSTAINABLE FUTURE: Need for Posthuman Ethics in the Anthropocene Era</text>
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                <text>Philosophical Post-humanism; Post- Anthropocentrism; Post-Dualism; Post-human Ethics; Post-humanism</text>
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                <text>Ethics, which constitutes principles that guide human conduct, deserves particular attention in this era of the Anthropocene, when human actions greatly influence ecology. Renaissance humans have hegemonised humanistic ethics of living and interacting with the world since the Enlightenment. While exalting human exceptionalism, humanism has relegated all other forms of existence to a subservient taxonomy, categorising them as raw material for human empowerment. The self-exalted autonomous subject, homo sapiens, faces the threat of extinction in the wake of unprecedented and violent ecological reactions. The exponential growth of the agency of intelligent machines also calls to question the autonomous human agency propagated by humanism. A paradigm shift is the moments need; this paper suggests posthuman ethics as an alternative. The new worldview, post-humanism, places the homo sapiens in relation to the rest of the universe. Philosophical post-humanism, proposed by Francesca Ferrando, foregrounds posthuman ethics that are post-humanistic, post-anthropocentric, and post-dualistic. They form a roadmap towards a sustainable future.  2023 Journal of Dharma: Dharmaram Journal of Religions and Philosophies.</text>
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                <text>Wilson K.D.; Edwin Jeevaraj A.</text>
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                <text>Journal of Dharma, Vol-48, No. 2, pp. 211-230.</text>
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                <text>ISSN: 2537222</text>
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                <text>Wilson K.D., Department of English and Cultural Studies, School of Arts and Humanities, Christ (Deemed to be University), Bangalore, India; Edwin Jeevaraj A., Department of English and Cultural Studies, School of Arts and Humanities, Christ (Deemed to be University), Bangalore, India</text>
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                <text>Towards a theory of well-being in digital sports viewing behavior</text>
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                <text>Digital sports well-being; Digitalization; Focus groups; Perceived autonomy; Qualitative research; Sports audience viewing behavior; Technology and service; Transformative; Uncertainty reduction; Virtual connectedness; Vividness; Well-being</text>
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                <text>Purpose: Social television (Social TV) viewing of live sports events is an emerging trend. The realm of transformative service research (TSR) envisions that every service consumption experience must lead to consumer well-being. Currently, a full appreciation of the well-being factors obtained through Social TV viewing is lacking. This study aims to gain a holistic understanding of the concept of digital sports well-being obtained through live Social TV viewing of sports events. Design/methodology/approach: Focus group interviews were used to collect data from the 40 regular sports viewers, and the qualitative data obtained is analyzed thematically using NVivo 12. A post hoc verification of the identified themes is done to narrow down the most critical themes. Findings: The exploration helped understand the concept of digital sports well-being (DSW) obtained through live Social TV sports spectating and identified five critical themes that constitute its formation. The themes that emerged were virtual connectedness, vividness, uncertainty reduction, online disinhibition and perceived autonomy. This study defines the concept and develops a conceptual model for DSW. Research limitations/implications: This study adds to the body of knowledge in TSR, transformative sport service research, digital customer engagement, value co-creation in digital platforms, self-determination theory and flow theory. The qualitative study is exploratory, with participants views based on a single match in one particular sport, and as such, its findings are restrained by the small sample size and the specific sport. To extend this studys implications, empirical research involving a larger and more diversified sample involving multiple sports Social TV viewing experiences would help better understand the DSW concept. Practical implications: The research provides insights to Social TV live streamers of sporting events and digital media marketers about the DSW construct and identifies the valued DSW dimensions that could provide a competitive advantage. Originality/value: To the best of the authors knowledge, the exploration is the first attempt to describe the concept of DSW and identify associated themes.  2021, Emerald Publishing Limited.</text>
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                <text>Rejikumar G.; Jose A.; Mathew S.; Chacko D.P.; Asokan-Ajitha A.</text>
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                <text>Journal of Services Marketing, Vol-36, No. 2, pp. 245-263.</text>
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                <text>Emerald Group Holdings Ltd.</text>
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                <text>Rejikumar G., Department of Management, Amrita Vishwa Vidyapeetham  Kochi Campus, Kochi, India; Jose A., Department of Professional Studies, Christ University, Bangalore, India; Mathew S., School of Business and Management, Christ University, Bangalore, India; Chacko D.P., Toyota Motor Corporation Australia, Melbourne, Australia; Asokan-Ajitha A., Indian Institute of Management Amritsar, Amritsar, India</text>
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                <text>In our increasingly interconnected world, national stability holds immense significance, impacting global economics, politics, and security. This study leverages machine learning to forecast stability scores, essential for understanding the intricate dynamics of country stability. By evaluating various regression models, our research aims to identify the most effective methods for predicting these scores, thus deepening our insight into the determinants of national stability. The field of machine learning has seen remarkable progress, with regression models ranging from conventional Linear Regression (LR) to more complex algorithms like Support Vector Regression (SVR), Random Forest (RF), and Gradient Boosting (GB). Each model has distinct strengths and weaknesses, necessitating a comparative analysis to determine the most suitable model for specific predictive tasks. Our methodology involves a comparative examination of models such as LR, Polynomial Regression (PR), Lasso, Ridge, Elastic Net (ENR), Decision Tree (DT), RF, GB, K-Nearest Neighbors (KNN), and SVR. Performance metrics like Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and R-squared (R2) assess each model's predictive accuracy using a diverse dataset of country stability indicators. This study's comprehensive model comparison adds novelty to predictive analytics literature. Our findings reveal significant variations in the performance of different regression models, with certain models exhibiting exceptional predictive accuracy, as indicated by high R2 values and low error metrics. Notably, models such as LR, SVR, and Elastic Net demonstrate outstanding performance, suggesting their suitability for stability score prediction.   2024 IEEE.</text>
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                <text>In cloud computing, providers pool their resources and make them available to customers. Next-generation computer scientists are flocking to the cutting-edge field of cloud computing for their research and exploration of uncharted territory. There are still several barriers that cloud service providers must overcome in order to provide cloud services in accordance with service level agreements. Each cloud service provider aspires to achieve maximum performance as per Service Level Agreements (SLAs), and this is especially true when it comes to the delivery of services. A cloud service level agreement (SLA) guarantees that cloud service providers will satisfy the needs of large businesses and offer their clients with a specified list of services. The authors offer a web service level agreementinspired approach for cloud service agreements. We adopt patterns and antipatterns to symbolize the best and worst practices of OCCI (Open Cloud Computing Interface Standard), REST (Representational State Transfer), and TOSCA (Topology and Orchestration Specification for Cloud Applications) with DevOps solutions, all of which API developers should bear in mind when designing APIs. When using this method, everything pertaining to the cloud service, from creation to deployment to measurement to evaluation to management to termination, may be handled mechanically. When distributing resources to cloud apps, our system takes into account the likelihood of SLA breaches and responds by providing more resources if necessary. We say that for optimal performance, our suggested solution should be used in a private cloud computing setting. As more and more people rely on cloud computing for their day-to-day workloads, there has been a corresponding rise in the need for efficient orchestration and management strategies that foster interoperability.  2023 International Journal on Recent and Innovation Trends in Computing and Communication. All rights reserved.</text>
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                <text>Singh S., Research Scholar, Computer Science and Engineering, Maharishi University of Information and Technology, U.P., Lucknow, India; Kumar Bharti A., School of Computer Application, Babu Banarasi Das University, Lucknow, U.P., Lucknow, India; Pandey H., Computer Science and Engineering, Lucknow University, U.P., Lucknow, India; Kumar Yadav R.; Sharma D., School of Business Management, Christ University, U.P., Ghaziabad, India; Shanker N.R., Computer Science and Engineering, Aalim Muhamed Salegh College of Engineering, Tamil Naidu, Chennai, India</text>
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                <text>Computational offloading; Internet of Things (IoT); IoT-Fog-Cloud architecture; Offloading algorithms</text>
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                <text>The Internet of Things (IoT) provides communication and processing power to different entities connected to it, thereby redefining the way objects interact with one another. IoT has evolved as a promising platform within short duration of time due to its less complexity and wide applicability. IoT applications generally rely on cloud for extended storage, processing and analytics. Cloud computing increased the acceptance of IoT applications due to enhanced storage and processing. However, the integration does not offer support for latency-sensitive IoT applications. The latency-sensitive IoT applications had greatly benefited with the introduction of fog/edge layer to the existing IoT-Cloud architecture. The fog layer lies close to the edge of the network making the response time better and reducing the delay considerably. The three-tier architecture is still in its earlier phase and needs to be researched further. This paper addresses the offloading issues in IoT-Fog-Cloud architecture which helps to evenly distribute the incoming workload to available fog nodes. Offloading algorithms have to be carefully chosen to improve the performance of application. The different algorithms available in literature, the methodologies and simulation environments used for the implementation, the benefits of each approach and future research trends for offloading are surveyed in this paper. The survey shows that the offloading algorithms are an active research area where more explorations have to be done.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Thomas P., CHRIST (Deemed to be University), Bangalore, India; Jose D.V., CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Towards connected government services: A cloud software engineering framework</text>
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                <text>Cloud computing technologies are being used highly successfully in large-scale businesses. Therefore, it is useful for governments to adopt cloud-driven multi-channel, and multiple devices to offer their services such as e-tax, e-vote, e-health, etc. Since these applications require open, flexible, interoperable, collaborative, and integrated architecture, service-oriented architecture approach can be usefully adopted to achieve flexibility and multi-platform and multi-channel integration. However, its adoption needs to be systematic, secure, and privacy-driven. In this context, micro services architecture (MSA), a direct offshoot of SOA, is also a highly attractive mechanism for building and deploying enterprise-scale applications. This chapter proposes a systematic framework for cloud e-government services based on the cloud software engineering approach and suggests a cloud adoption model for e-government, leveraging the benefits of MSA patterns. The proposed model is based on a set of evaluated application characteristics that, in turn, support emerging IT-based technologies.  2021 by IGI Global. All rights reserved.</text>
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                <text>Ramachandran M.; Chelliah P.R.; Soundarabai P.B.</text>
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                <text>Web 2.0 and Cloud Technologies for Implementing Connected Government, pp. 113-135.</text>
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                <text>&lt;a href="https://doi.org/10.4018/978-1-7998-4570-6.ch006" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/978-1-7998-4570-6.ch006&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137312389&amp;amp;doi=10.4018%2F978-1-7998-4570-6.ch006&amp;amp;partnerID=40&amp;amp;md5=c56d4dc47e5d15b0cf3e781fe5e707b1" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137312389&amp;amp;doi=10.4018%2f978-1-7998-4570-6.ch006&amp;amp;partnerID=40&amp;amp;md5=c56d4dc47e5d15b0cf3e781fe5e707b1&lt;/a&gt;</text>
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                <text>Ramachandran M., Leeds Beckett University, Leeds, United Kingdom; Chelliah P.R., Reliance Jio Platforms Ltd, Bangalore, India; Soundarabai P.B., Christ University (Deemed), Bangalore, India</text>
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                <text>Towards developing an automated technique for glaucomatous image classification and diagnosis (AT-GICD) using neural networks</text>
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          <element elementId="49">
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              <elementText elementTextId="93767">
                <text>ANN; Feature extraction; Fundus image; Glaucomatous image classification; Histogram gradients; Wavelet energy</text>
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                <text>Glaucoma is the eye defect that has become the second leading cause of blindness worldwide and also stated as incurable, may cause complete vision loss. The earlier diagnosis of glaucoma in Human Eye is a great confrontation and very important in present scenario, for providing efficient and appropriate treatments to the persons. Though there is much advancement in Ocular Imaging that affords methods for earlier detection, the appropriate results can be obtained by integrating the data from structural and functional evaluations. With that note, this paper involves in developing automated technique for glaucomatous image classification and diagnosis (AT-GICD). The model considers both the textural and energy features for effectively diagnosing the defect. Image Segmentation is processed for obtaining the exact area of optic nerve head; histogram gradient based conversion is employed for enhancing the fundus image features. Further, Wavelet Energy features are extracted and applied to the artificial neural networks (ANN) for classifying the NORMAL and GLAUCOMA images. The Accuracy rate based comparison with other existing models is carried out for evidencing the effectiveness of the proposed model in glaucomatous image classification.  2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.</text>
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                <text>Karthikeyan M.P.; Mary Anita E.A.; Mohana Geetha D.</text>
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                <text>International Journal of Information Technology (Singapore), Vol-15, No. 7, pp. 3727-3739.</text>
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                <text>ISSN: 25112104</text>
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                <text>Karthikeyan M.P., Department of CSE, R.M.K Engineering College, Chennai, India; Mary Anita E.A., Department of CSE, CHRIST (Deemed to be University), Bengaluru, India; Mohana Geetha D., Department of ECE, Sri Krishna College of Engineering and Technology, Kuniyamuthur, India</text>
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                <text>Towards reading song in performance as aural narrative : Reading a sense of spatiality in select albums of mark knopfler using henri lefebver's notions of space  </text>
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                <text>One of the chief objectives of this study is to explore and offer a strategy to read song in performance as Aural Narratives. This was necessary because verbal texts can be read in multiple ways. Perhaps the chief claim of a text s possibility to be literary lies in its inherent potential to be discursive. Therefore sound texts require a way of understanding sound as an element of storytelling. Shifts in Humanities necessitate an expanding notion of textuality. One of the chief concerns and burdens of the writer of literature is the evocation of a sense of spatiality which can be perceived as an outcome of spatial practice. Spatial practice in turn is defined by social codes and practices. Spaces can be read therefore through the life experiences of the inhabitants of a space as spatial practices are dependent on particular spaces. This study explores the use of Sound in creating a sense of Spatiality. Singer, songwriter and guitarist, Mark Knopfler creates songs that are arranged around a central character s lived experience. Thus the perception and conception of a sense of space that is thus evoked can be negotiated using Henri Lefebvre s triadic notions of newlinespatiality as a reading strategy. </text>
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                <text>Selvamony, Nirmal</text>
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                <text>Sustainability in business is expected considering the growth in the long run. Sustainable development goals are important for our sustainability on this planet. In case of a business, it is essential to ensure sustainable processes and sustainability of the existing customers. Sustainable customers can in turn contribute to improving the process by providing constructive suggestions to the business. This paper is an attempt to review sentiment analysis techniques to improve the customer experience of a business.  2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad.</text>
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                <text>Goswami M.; Sharma A.</text>
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                <text>Towards Sustainable Living through Sentiment Analysis during Covid19</text>
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                <text>good health and wellbeing; impact of covid 19; impact of social media; sentiment analysis; sustainable development goals; twitter</text>
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                <text>Artificial intelligence is the process of the machine to perform with the simulation of human intelligence. Computing within the field of emotions paves the recognitions to sentiment analysis. Sentiment analysis is the method of capturing the emotions behind a text whether or not it's positive, negative or neutral. Sentiment Analysis (SA) or Opinion Mining (OA) is the process to provide computational treatment to unstructured data to categorize and identify the sentiments or emotions expressed in a piece of text. It combines Natural Language Processing Techniques and Machine Learning Techniques. This technology is additionally referred to as opinion mining or feeling computing. Sentiment Analysis uses the ideas of machine learning alongside an AI based process called NLP to extract and analyse the data, emotions, information from the text. This work explores the impact of social media during covid 19 and possible link between sustainable living and health care with the usage of sentiments. This paper address the sustainable development goal 3 (good health and wellbeing) of SDG 2030 and a possible way towards sustainable living through sentiment analysis.  The Electrochemical Society</text>
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                <text>Goswami M.; Abraham A.</text>
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                <text>ECS Transactions, Vol-107, No. 1, pp. 18569-18582.</text>
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                <text>ISSN: 19386737; ISBN: 978-160768539-5</text>
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                <text>Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint</text>
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                <text>DYNARDL; Ecological footprint; Mineral production; Pakistan</text>
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                <text>The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns.  2024 Elsevier Ltd</text>
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                <text>Villanthenkodath M.A.; Pal S.</text>
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                <text>Journal of Environmental Management, Vol-364</text>
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                <text>A new trend in feature abstraction is Big Data Analysis combined with computational techniques. This includes gathering knowledge from reputable data sources, analyzing information quickly, and forecasting the future. Big data entails vast amounts of data that are challenging to analyze using typical database and software approaches. When using big data applications, a technological hurdle arises when transporting data across several locations, which is quite expensive and necessitates a huge primary memory for storing data for processing. Big data refers to the transaction and interaction of datasets whose size and complexity transcend the usual technical capabilities of acquiring, organizing, and processing data in a cloud environment. This article provides an in depth study of various applications of big data. It also provides a detailed view on various problems and challenges in Big Data.   2021 IEEE.</text>
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                <text>Proceedings of the 5th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2021, pp. 1361-1365.</text>
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                <text>ISBN: 978-166543524-6</text>
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                <text>Rajendran R., CHRIST (Deemed to Be) University, Department of Professional Studies, India; Paruchuri H., Anthem, Inc., United States; Ayub Ahmed A.A., School of Accounting, Jiujiang University, China; Ganapathy A., Adobe Systems, California, United States; Vadlamudi S., Xandr, ATT Services Inc., United States; Naved M., Jagannath University, Department of Business Analytics, Delhi-NCR, India</text>
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                <text>Towards Visibility: Subaltern Counterpublics in Paul Chirakkarodes Pulayathara</text>
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                <text>caste; conversions; Dalit Christianity; public sphere; subaltern counterpublics</text>
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                <text>Christianity has always been celebrated as a catalyst towards modernity for the Dalits of Kerala. Though missionary accounts and ethnographic studies confirm the progress of the community, there was rampant casteism and separatism too. This is succinctly revealed in Dalit Christian texts. Pulayathara by Paul Chirakkarode stands as a testimony to the Dalit Christian dilemma and traces the history of the Kuttanadan Pulaya community in the pre- and post-conversion scenarios. Conversions could not change the existing public sphere of Kerala, where upper castes were the dominant party. They (Dalits) continued to be marginalized and subordinated and lacked a class consciousness. The article highlights the limitations in the public sphere that emerged in Kerala as part of the missionary endeavours in accommodating the converted Dalits. The article attempts to trace the emergence of subaltern counterpublics among the Dalit Christians to oppose the continued oppression and casteism by situating Pulayathara at the centre of the analysis.  2022 Indian Institute of Management, Ahmedabad.</text>
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                <text>Romeo C.; Nayar A.</text>
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                <text>Contemporary Voice of Dalit</text>
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                <text>&lt;a href="https://doi.org/10.1177/2455328X221117639" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/2455328X221117639&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138298273&amp;amp;doi=10.1177%2F2455328X221117639&amp;amp;partnerID=40&amp;amp;md5=ed283215204eff5bb7190ead13a564cc" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138298273&amp;amp;doi=10.1177%2f2455328X221117639&amp;amp;partnerID=40&amp;amp;md5=ed283215204eff5bb7190ead13a564cc&lt;/a&gt;</text>
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              <elementText elementTextId="111367">
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                <text>ISSN: 2455328X</text>
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                <text>Romeo C., Department of English and Cultural Studies, Christ (Deemed to be) University, Karnataka, Bangalore, India; Nayar A., Department of English and Cultural Studies, Christ (Deemed to be) University, Karnataka, Bangalore, India</text>
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                <text>Toxic Effects of Nanoparticles on Fish Embryos</text>
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              <elementText elementTextId="197249">
                <text>Metal oxide; Metal toxicity; Nanoparticles; Nanotoxicity; Pollution</text>
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                <text>Nanoparticles are used widely in the in-drug delivery, diagnostics, cosmetics, paints, electronics, fabrics, solar cells, medicines etc. Their wide application is due to their special properties which include minute size, high reaction rate, increased surface area and quantum effect. Despite their multiple applications, nanoparticles have harmful effects too due to their improper disposal causing their entry into the aquatic environment greatly threatening the ecological security as well as our health. Zebra fishes (Danio rerio) are used more commonly for the evaluation of toxicity and are considered a promising animal model. Studies on Salmon and Labeo rohita have also been used for toxicity evaluation. Nanoparticles affect the embryo more easily than the adult since the embryo are more sensitive. Hence it becomes important for us to study the effect of the nanoparticles on the embryo of the fishes. These nanoparticles have the ability to cross the chorion layer and affect the developing embryo. Since the fishes are a part of the food chain, when these organisms get affected they will eventually harm the humans too. This review focuses on the effect of metal nanoparticles (NPs) like gold(Au), silver(Ag), copper(Cu), platinum and metal oxides nanoparticles like titanium dioxide, aluminium oxide, copper oxide, nickel oxide zinc oxide on the embryonic development of fish embryos. When compared to the other nanoparticles (NPs) like silver, copper and platinum, it has been observed that the gold nanoparticles (Au NPs) showed no toxicity to embryos of zebrafish though few studies contradict this. Aluminium nanoparticles showed no toxicity and role of reactive oxygen species (ROS) in enhancing the toxicity of nanoparticles have also been discussed.  2021 World Research Association. All rights reserved.</text>
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                <text>Gopalraaj J.; Manikantan P.; Arun M.; Balamuralikrishnan B.; Anand A.V.</text>
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                <text>Research Journal of Biotechnology, Vol-16, No. 12, pp. 140-149.</text>
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                <text>World Research Association</text>
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                <text>&lt;a href="https://doi.org/10.25303/1612rjbt140149" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.25303/1612rjbt140149&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123557688&amp;amp;doi=10.25303%2F1612rjbt140149&amp;amp;partnerID=40&amp;amp;md5=152600f5aadf4f2a7b8ba79bb5b09369" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123557688&amp;amp;doi=10.25303%2f1612rjbt140149&amp;amp;partnerID=40&amp;amp;md5=152600f5aadf4f2a7b8ba79bb5b09369&lt;/a&gt;</text>
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                <text>ISSN: 9736263</text>
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                <text>Gopalraaj J., Department of Life Sciences, CHRIST (Deemed to be) University, Karnataka, Bangalore, 560029, India; Manikantan P., Department of Life Sciences, CHRIST (Deemed to be) University, Karnataka, Bangalore, 560029, India; Arun M., Department of Life Sciences, CHRIST (Deemed to be) University, Karnataka, Bangalore, 560029, India; Balamuralikrishnan B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Anand A.V., Department of Human Molecular Genetics, Bharathiar University, Tamilnadu, Coimbatore, 641046, India</text>
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                <text>Sreehari K.S., Department of Physics and Electronics, Christ University, India; Namratha W.N., Department of Physics and Electronics, Christ University, India; Joseph N., Department of Physics and Electronics, Christ University, India; Balachandran M., Department of Physics and Electronics, Christ University, India</text>
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                <text>The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of content being posted by the users of the sites every second. The traditional algorithms that depend on users reporting toxic content for it to be deleted and necessary actions to be taken against the users posting the content would take a long time, within which it would have gained media attention and would have lead to huge fights over the content. Thus, it becomes important for the content to be evaluated for toxicity at the time it is posted in order to stop it from being posted. Therefore, we have designed and trained a deep learning model that can be read through the textual content given through it and determine if it is toxic or not.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.</text>
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