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                <text>Toward precision agriculture in Cyber-Physical Agricultural System</text>
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                <text>Agriculture 4.0 or Agri 4.0; cyber-physical agricultural system; cyber-physical system; industry 4.0; precision agriculture</text>
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                <text>Agriculture 4.0 or Agri 4.0 is a newly developed system that consists of various digital technologies adapted from Industry 4.0 based on smart automation. Agriculture 4.0 is a subset of Industry 4.0 aimed at sustainable precision agriculture (PA) and increasing agricultural efficiency using digital technologies and the Internet of Things. The cyber-physical system (CPS) is the seamless integration of digital and physical domains and when CPS is applied in agriculture, it is termed cyber-physical agricultural system (CPAS). The application of CPS in carrying out PA with sustainable management of resources is termed Agri 4.0. Research papers are reviewed to understand the bigger picture behind various details of digital technologies and CPS with a focus on agriculture 4.0 and to determine its applications, challenges, and developments in the field. It is apparent that most of the small and marginal farms in remote areas are not able to use this technology due to a lack of knowledge and resources. It is the need of the hour to support these farmers by making favorable policies and appropriating budgets such that it will lead to more profitable and sustained PA and in the process contribute to the social and economic upliftment of farmers of India.  2024 Elsevier Inc. All rights reserved.</text>
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                <text>Gokul Krishnan K.B.; Mehta V.; Rai V.; Hirendra Rai R.; Sharma V.; Mishra N.</text>
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                <text>Agri 4.0 and the Future of Cyber-Physical Agricultural Systems, pp. 157-174.</text>
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                <text>&lt;a href="https://doi.org/10.1016/B978-0-443-13185-1.00009-5" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/B978-0-443-13185-1.00009-5&lt;/a&gt;
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                <text>Gokul Krishnan K.B., Department of Agricultural Statistics, College of Agriculture, Acharya Narendra Deva University of Agriculture and Technology, Uttar Pradesh, Ayodhya, India; Mehta V., Department of Agricultural Statistics, College of Agriculture, Acharya Narendra Deva University of Agriculture and Technology, Uttar Pradesh, Ayodhya, India; Rai V., Manipal Institute of Technology, Karnataka, Manipal, India; Hirendra Rai R., School of Physiotherapy, Delhi Pharmaceutical Sciences and Research University, Delhi, India; Sharma V., Department of Computational Sciences, Christ University, Delhi NCR Campus, India; Mishra N., Department of Economics, FS University, Uttar Pradesh, Shikohabad, India</text>
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                <text>Jain, Kurunandan; Krishnan, Prabhakar; Pachiyannan, Prabu; Jaganathan, Logeshwaran; Khan, Muhammad Attique; Li, Yang</text>
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                <text>Toward Smart 5G and 6G: Standardization of AI-Native Network Architectures and Semantic Communication Protocols</text>
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                <text>IEEE Communications Standards Magazine;</text>
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                <text>Jain K., Amrita Vishwa Vidyapeetham, Center for Cyber Security Systems and Networks, Amritapuri-Campus, Kerala, 690525, India; Krishnan P., Amrita Vishwa Vidyapeetham, Center for Cyber Security Systems and Networks, Amritapuri-Campus, Kerala, 690525, India; Pachiyannan P., College of Computer and Information Sciences, Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Jaganathan L., Christ University, Department of Computer Science, Karnataka, Bengaluru, 560029, India; Khan M.A., Prince Mohammad bin Fahd University, Center of AI, Al Khobar, Dhahran, 34754, Saudi Arabia; Li Y., Shihezi University, College of Mechanical and Electrical Engineering, Shihezi, 832003, China</text>
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                <text>Semantic communication and AI-native design are widely recognized as defining features of 6G, yet existing surveys often treat them conceptually or in isolation. This article provides a standards-oriented perspective that integrates these paradigms and evaluates their implications for architectural design and standardization. We make three concrete contributions: 1) we propose enriched KPI frameworks, security and privacy taxonomies, and interoperability prescriptions that extend beyond current 3GPP, ITU-T, and O-RAN activities; 2) we analyze implementation trade-offs such as computational overhead of semantic encoding and the scalability of federated learning in ultra-dense deployments; and 3) we demonstrate the potential of semantic communication through a UAV case study, highlighting measurable improvements in bandwidth, latency, and coordination efficiency. These contributions distinguish our work from prior surveys by moving beyond high-level vision toward feasibility analysis and concrete standardization pathways, thereby offering actionable insights for the evolution of semantic-aware 6G systems.  2017 IEEE.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISSN: 24712825;</text>
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                <text>Toward sustainability 4.0: A comprehensive analysis of sustainability in corporate environment</text>
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                <text>Circular economy; Corporate sustainable responsibility; Green Building Information Management; Green Internet of Things; Greenhouse gas emissions; Net-zero energy buildings</text>
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                <text>Sustainability is one of the key requirements for any business, and continuously changing business requirements and the environment are the main drivers of sustainable business practices. However, there exist gaps in recognizing and aligning these sustainable practices with everyday operational activities. This study's aim is to explore the current awareness level in business leaders and stakeholders about corporate responsibility toward sustainability and reflects on the obstacles encountered by them in diverse built environments, laying the groundwork for addressing these hurdles and contributing toward the overall sustainable development. The study has two major findings: the analysis revealed that there is a paradigm shift in the understanding of sustainability; in contrast to earlier publications, newer publications focus on technological advancements such as the use of "Green Building Information Management" and "Green Internet of Things" illustrating the real-time implications of sustainable practices. Further analysis found a knowledge gap that exists among business leaders in understanding the concept of sustainable development. This, in essence, poses a burden for corporate leaders to keep up with ongoing technological developments. The study concludes that to achieve sustainable growth, leadership in the corporate environment needs a 360-degree view of sustainability, allowing them to assign equal value to the environment, social, and economic pillars of sustainability to address the current issues leveraging from the state-of-the-art technological innovations. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved.</text>
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                <text>Wankhar V.; Fukey L.; Sinha M.</text>
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                <text>Green Technological Innovation for Sustainable Smart Societies: Post Pandemic Era, pp. 67-87.</text>
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                <text>2021-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-3-030-73295-0_4" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-030-73295-0_4&lt;/a&gt;
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                <text>Wankhar V., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Fukey L., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Sinha M., School of Business and Management CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Abstract: Coffee is one of the most significant beverages consumed worldwide, dating to times immemorial. It plays a pivotal role in several economies owing to its second position in the list of trading commodity, after petroleum. The growing demand for coffee has resulted in a great amount of coffee production and processing and subsequent release of large volumes of wastewater. This wastewater is characterized to have very high chemical oxygen demand and biological oxygen demand with potential to cause environmental pollution thus requiring smart strategies to effectively reduce their load of the wastewater before releasing them into the habitable ambiance. The existing research on coffee wastewater treatment should be critically analyzed for their sustainability and economic viability for them to be commercially used in developing countries for effluent mitigation. This literature review aims to suggest an effective way to treat the wastewater by combining various methods, coupling it with value addition like energy generation. The goal of this review is to provide a direction for future research to integrated treatment with valorization along with a focus on emerging technologies. Graphic abstract: [Figure not available: see fulltext.].  2020, Springer-Verlag GmbH Germany, part of Springer Nature.</text>
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                <text>Sengupta B.; Priyadarshinee R.; Roy A.; Banerjee A.; Malaviya A.; Singha S.; Mandal T.; Kumar A.</text>
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                <text>Clean Technologies and Environmental Policy, Vol-22, No. 5, pp. 995-1014.</text>
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                <text>&lt;a href="https://doi.org/10.1007/s10098-020-01841-y" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s10098-020-01841-y&lt;/a&gt;
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                <text>ISSN: 1618954X</text>
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                <text>Sengupta B., The Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 8th St., Troy, 12180, NY, United States; Priyadarshinee R., Department of Biotechnology, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Roy A., Department of Chemical Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Banerjee A., Department of Chemical Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Malaviya A., Applied and Industrial Biotechnology Laboratory, Department of Life Sciences, CHRIST (Deemed to be University), Hosur Main Road, Bhavani Nagar, S. G. Palya, Bengaluru, 560029, Karnataka, India; Singha S., Department of Chemical Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Mandal T., Department of Chemical Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Kumar A., Department of Chemical Engineering, National Institute of Technology Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India</text>
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                <text>Towards a culturally-informed counselling and psychotherapy</text>
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                <text>Indigenizing health psychological practices in the background of cultural diversity in India needs to address the tremendous resources of healing practices embedded in the Indian traditions. Looking for cultural imprints in mental health has received attention among academicians and researchers in the last two decades significantly. Teaching, training and practice of counseling and psychotherapy has also greatly been benefitted and progressed eventually. Several academic and research initiatives have been taken to build a culturally informed counseling and psychotherapy in India. There is need to internalize cultural differences and incorporating them consciously in the training and practice of therapy. A cultural sensitive approach in counseling and psychotherapy is mindful of the observance of a community-oriented perspective.  Springer (India) Pvt. Ltd., part of Springer Nature 2018.</text>
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                <text>Thomas T.M.; Gopal B.; Sasidharan T.</text>
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                <text>Psychosocial Interventions for Health and Well-Being, pp. 241-252.</text>
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                <text>ISBN: 978-813223782-2; 978-813223780-8</text>
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                <text>Thomas T.M., Department of Psychology, University of Kerala, Thiruvananthapuram, Kerala, India; Gopal B., Department of Psychology, CHRIST (Deemed to be University), Bangalore, India; Sasidharan T., Department of Psychology, University of Calicut, Malappuram, Kerala, India</text>
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                <text>Towards a Framework for Supply Chain Financing for Order-Level Risk Prediction: An Innovative Stacked A-GRU Based Technique</text>
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                <text>Order financing is changing the game in the banking and financial supply chain industry. It's great for SMEs and opens up new revenue streams for logistics and finance companies. But in order to find the weak spots offered by banks and other financial institutions, companies need to undertake thorough risk assessments right now. Careful timing is crucial for training the model, extracting features, and preprocessing. Outlier identification and missing value handling are the first steps in preprocessing, which also includes normalization and standardization to improve data integrity and reduce unit discrepancies. Principal component analysis makes use of multivariate statistics to aid in feature extraction, guaranteeing effective data representation. Careful consideration of every detail is required during the training of a Stacked-A-GRU model, which follows attribute selection. Impressively outperforming state-of-the-art algorithms SAFE and GRU, the suggested solution achieves a remarkable correctness rating of 97.34%, indicating notable progress in predicting accuracy.   2024 IEEE.</text>
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                <text>Amarnath Reddy B.; Vinesh Kumar G.; Dhiliphan Kumar M.; Veena S.; Chauhan A.; Anwer Basha H.</text>
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                <text>1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Amarnath Reddy B., Vignana Jyothi Institute of Management, Department of Finance, Telangana, Hyderabad, India; Vinesh Kumar G., Vardhaman College of Engineering, Department of Management Studies, Telangana, Hyderabad, India; Dhiliphan Kumar M., Deemed University, Business Administration, Kalasalingam Academy of Research and Education, Virudhunagar, India; Veena S., Deemed University, Business Administration, Kalasalingam Academy of Research and Education, Virudhunagar, India; Chauhan A., School of sciences, CHRIST (Deemed to be university), Department of life sciences, Karnataka, Bengaluru, India; Anwer Basha H., Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Sciences, Department of Computer Science, Chennai, India</text>
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                <text>Towards a Human-Like AGI Architecture: GeneralIntelligence Framework (GIF)</text>
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                <text>Journal of Computer Science;Volume;21;Issue;7;pp.1637-1650</text>
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                <text>Puliyanmakkal J.K., Department of Computer Science, Christ (Deemed to be University), Bangalore, India; Rohini V., Department of Computer Science, Christ (Deemed to be University), Bangalore, India</text>
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                <text>Artificial Intelligence (AI) has achieved significant breakthroughsbut remains limited by its specialization and inability to generalize acrossdomains, unlike human cognition. Current models such as Large LanguageModels (LLMs) and Multimodal Large Language Models (MLLMs) excel atspecific tasks but struggle with real-time adaptability and cross-domaingeneralization. This paper introduces the General Intelligence Framework(GIF), an approach designed to bridge this gap by mimicking human-likecognitive processes. By integrating Deep Learning (DL), Spiking NeuralNetworks (SNNs), and neuromorphic hardware, the framework fosters Real-Time Learning (RTL) and adaptability. The proposed framework holdspotential for industries like robotics, healthcare, education, astronomy,defense, autonomous systems, etc., where flexible, adaptive AI is critical.We hypothesize that the framework will enable AI systems to handleunforeseen inputs and tasks without requiring extensive retraining,representing a step toward achieving Artificial General Intelligence (AGI).  2025 Jiran Kurian Puliyanmakkal and Rohini V. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.</text>
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                <text>Kunnumpurath B., Christ University, Department of Media Studies, Bengaluru, India; Menon V.A., Kristu Jayanti College (Autonomous), Department of Media Studies, Bengaluru, India; Ashique Ali K.A., Central University of Tamil Nadu, Department of Commerce, Thiruvarur, India; Paul A., Christ University, Department of Media Studies, Bengaluru, India</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., 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>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., 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>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>The chaotic space caused by information explosion in present times has made the process and purpose of reading to be always questioned. Technological advancement has made reading appear as a mere mockery at the very outset. But the world still prioritizes knowledge that is acquired through observation, valuation and interpretation. At the time of Big Data, there still persists a sense of agency to define a given information as episteme. The present essay emphasizes on looking at reading as a modern phenomenon by presupposing the epistemological presence at the centre of any rational pursuit. Based on the Kantian precepts on enlightenment, the paper attempts to understand this presence of knowledge by delving into the major disciplines of modern philosophy that help in observing, valuing and interpreting the act of reading in present times. More than laying terms for defining the text within the modern space, the study essentializes reading in a virtually driven algorithmic world.  AesthetixMS 2021</text>
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                <text>Arun D.M., Department of English, Pondicherry University, Puducherry, India, Department of English and Cultural Studies, BGR Campus, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Towards an Improved Model for Stability Score Prediction: Harnessing Machine Learning in National Stability Forecasting</text>
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                <text>and security; Economy politics; Fragile State of Index; Machine Learning</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>Maheshwari A.; Malhotra A.; Singh Hada B.; Ranka M.; Amzad Basha M.S.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Maheshwari A., Christ (Deemed to Be University), School of Commerce, Finance and Accountancy, Ghaziabad, India; Malhotra A., Christ (Deemed to Be University), School of Commerce, Finance and Accountancy, Ghaziabad, India; Singh Hada B., Christ (Deemed to Be University), School of Commerce, Finance and Accountancy, Delhi-NCR, India; Ranka M., Dayananda Sagar College of Arts, Science and Commerce, Bengaluru, India; Amzad Basha M.S., Gitam (Deemed to Be University), Gitam School of Business, Bengaluru, India</text>
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                <text>Towards Automated and Optimized Security Orchestration in Cloud SLA</text>
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                <text>Cloud Computing; Orchestration; Security; Service Level Agreement</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.; Kumar Bharti A.; Pandey H.; Kumar Yadav R.; Sharma D.; Shanker N.R.</text>
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                <text>International Journal on Recent and Innovation Trends in Computing and Communication, Vol-11, No. 3, pp. 215-222.</text>
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                <text>&lt;a href="https://doi.org/10.17762/ijritcc.v11i3.6339" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.17762/ijritcc.v11i3.6339&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 23218169</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>Towards Computation Offloading Approaches in IoT-Fog-Cloud Environment: Survey on Concepts, Architectures, Tools and Methodologies</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.; Jose D.V.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 37-52.</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., 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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                <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>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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