778 20 16481 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Pandey, Adesh Kumar; Kushwah, Virendra Singh; Kshirsagar, Pravin R.; Sharma, Kamal Kant; Singh, Jagendra; Parashar, Jyoti; Jain, Rituraj Title A name given to the resource Predictive modeling of mechanical behavior in waste ceramic concrete using machine learning techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Journal of Basic and Applied Sciences;Volume;14;Issue;1;pp.124-135 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.14419/ywwvvd04" target="_blank" rel="noreferrer noopener">https://doi.org/10.14419/ywwvvd04</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105005015895?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105005015895?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Pandey A.K., Department of Information Technology, KIET Group of Institutions, Ghaziabad, India; Kushwah V.S., School of Computing Science &amp; Engineering, VIT Bhopal University, Highway, Kothrikalan, Madhya Pradesh, Sehore, India; Kshirsagar P.R., Department of Electronics &amp; Telecommunication Engineering, J D College of Engineering &amp;; Management, Maharashtra, Nagpur, India; Sharma K.K., Department of Information Technology, KIET Group of Institutions, Ghaziabad, India; Singh J., School of Computer Science Engineering &amp; Technology, Bennett University, Greater Noida, India; Parashar J., Bharati Vidyapeeths Institute of Computer Applications and Management, New Delhi, India; Jain R., Department of Information Technology, Marwadi University, Gujarat, Rajkot, India Description An account of the resource This study identifies the critical demand for a certain approach that aims to predict and ascertain the mechanical behavior of concrete admixed with waste ceramic, a method to overcome and mitigate the related environmental challenges as it pertains to the construction field. Concrete modification with ceramic wastes has received significant attention due to its potential improvement in sustainability. The developed predictive models on waste ceramic concrete (WCC) involved the use of advanced machine learning techniques such as Artificial Neural Network (ANN) and Light Gradient Boosting Machine (LightGBM). Experimental datasets were formulated based on 5% and 20% variability of ceramic waste percentages as input variables for training and testing data for validation of the proposed model. In each case, iterative training improved model performance, with the ANN showing moderate predictability (R = 0.70 and 0.67) and LightGBM demonstrating stronger accuracy. Predictive values ranged between 1.02 MPa and 0.12 MPa for compressive and splitting tensile strengths and had R values of 0.70 and 0.67 for the ANN model, respectively. The established findings will lead to a dependable framework for assessing and improving the performance of ceramic waste-modified concrete. In this regard, these findings have reinforced the potential of machine learning in developing sustainable construction practices. This paper is of value to engineers and decision-makers within the construction industry, providing an informed choice towards environmental sustainability and better risk management. Kamal Upreti et al. Subject The topic of the resource Artificial Neural Network; Construction Industry; Environmental Sustainability; LightGBM; Machine Learning; Waste Ceramic Concrete Publisher An entity responsible for making the resource available Science Publishing Corporation Inc. Relation A related resource ISSN: 22275053; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Poonia, Ramesh Chandra; Verma, Rajesh; Malik, Khushboo; Kureethara, Joseph Varghese Title A name given to the resource A Comprehensive Study Using Convolutional Neural Networks as a Method for Multi-class Skin Cancer Image Classification Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering;Volume;1269;pp.1-11 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-9515-4_1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-9515-4_1</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003894975?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003894975?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., CHRIST University, Delhi NCR, Ghaziabad, India; Poonia R.C., CHRIST University, Delhi NCR, Ghaziabad, India; Verma R., CHRIST University, Delhi NCR, Ghaziabad, India; Malik K., CHRIST University, Delhi NCR, Ghaziabad, India; Kureethara J.V., CHRIST University, Bangalore, India Description An account of the resource Skin disorders occur more frequently than other kinds of diseases. Skin diseases can be attributed to a number of aspects, like fungi, bacteria, viruses, allergies, and so on. The rapid advancement of healthcare centered around lasers and photonics has rendered it feasible to diagnose skin disorders in a more accurate and timely manner. However, the cost of such a diagnostic remains extremely limited and prohibitively expensive. As a result, the use of image processing methods is beneficial in the initial phases of designing a computerized dermatology screening system. The retrieval of characteristics is an extremely important step in classifying skin disorders. The use of computer vision may play a crucial role in the diagnosis of a variety of skin conditions using a variety of approaches. The strategy we have proposed is straightforward and quick and requires no expensive technology besides a computer and a camera. When applied to the inputs of a colored picture, the method is successful. After that, resize a portion of the image to retrieve attributes with a pretrained convolutional neural network. The attribute was then classified using the multi-class XGBoost program. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Convolutional neural network (CNN); Deep learning; International skin identification collaborations (ISIC) and image processing; Recurrent repetition convolutional (RRN); Skin cancer; Ultraviolet (UV) Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 18761100; ISBN: 978-981979514-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Radhakrishnan, G.V.; Ga-B?aszczykowska, Agnieszka; Date, Saroj; Gautam, Mamta; Jain, Rituraj Title A name given to the resource Integrated biogasification and carbon capture pathways: a system-level review of technologies, storage options, and deployment challenges Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Environment Systems and Decisions;Volume;46;Issue;2;Article No.;15; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s10669-026-10078-x" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10669-026-10078-x</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105033752967?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105033752967?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Department of Computer Science, Christ University, NCR, New Delhi, India; Radhakrishnan G.V., Kalinga School of Management, Kalinga Institute of Industrial Technology, Maharashtra, Bhubaneswar, India; Ga-B?aszczykowska A., Department of Law, War Studies University, Warsaw, Poland; Date S., Department of Artificial Intelligence and Data Science, CSMSS Chh. Shahu college of Engineering, Maharashtra, Aurangabad, India; Gautam M., Department of Applied Sciences and Humanities, ABES Engineering College, Uttar Pradesh, Ghaziabad, India; Jain R., Department of Information Technology, Marwadi University, Gujarat, Rajkot, India Description An account of the resource Carbon-negative energy systems that integrate bioenergy production with permanent carbon dioxide (CO2) sequestration are increasingly recognized as essential for achieving global net-zero and beyond-zero climate targets. While extensive research exists on individual components such as biogasification, carbon capture technologies, and geological storage, a coherent system-level synthesis linking these pathways remains fragmented. This review addresses this gap by providing an integrated assessment of biogasification-based carbon capture and storage (CCS) systems, with particular emphasis on techno-economic performance, capture efficiency, subsurface storage options, and deployment challenges. Following the PRISMA 2020 guidelines, 112 studies were systematically selected from an initial pool of 780 publications and analyzed to compare advanced gasification routes, emerging capture technologies, and storage strategies. The results indicate that hybrid gasificationsolid oxide fuel cell systems can achieve efficiencies of up to 55%, while cryogenic carbon capture consistently delivers CO? purities above 95% with reduced energy penalties. Supercritical water gasification and hydrothermal pathways demonstrate strong potential for wet biomass conversion, achieving hydrogen yields exceeding 1150 mmol/L and carbon efficiencies above 80%. Despite these technical advances, large-scale deployment remains constrained by high costs (USD 8001350 per tonne CO2), infrastructure limitations, and policy uncertainty. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. Subject The topic of the resource Biogasification; Carbon capture; Climate change; Subsurface CO₂ storage; Techno-economic feasibility; Thermodynamic efficiency Publisher An entity responsible for making the resource available Springer Relation A related resource ISSN: 21945403; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Radhakrishnan, G.V.; Shankar, Uma; Tiwari, Akhilesh; Gupta, Komal; Rajendran, Vijayalaxmi Title A name given to the resource Enhancing Diagnostic Precision in Lung Cancer Detection Using Smote-Based Balancing Techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/APSIT63993.2025.11086231" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/APSIT63993.2025.11086231</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013070827?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013070827?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Christ University, Department of Computer Science, Ghaziabad, India; Radhakrishnan G.V., Kalinga School of Management, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Shankar U., Faculty of Management and Social Sciences, Qaiwan International University, Kurdistan, Sulaymaniyah, Iraq; Tiwari A., Christ University, Department of Business and Management, Ghaziabad, India; Gupta K., Accenture, Banglore, India; Rajendran V., School of Business and Management, Christ University, Ghaziabad, India Description An account of the resource Worldwide, Lung cancer is the primary cause of death from cancer, and chances of surviving are considerably raised by early detection. While traditional diagnostic approaches heavily rely on imaging and specialized infrastructure, they often fail to serve low-resource or early screening environments. In this work, based on deep learning, lightweight framework for detecting lung cancer from structured survey data is presented. The research tackles the prevalent the problem of class disparity using the Synthetic Minority Over-sampling Technique (SMOTE), enhancing the sensitivity of predictive models. A comparative evaluation was conducted across six models Logistic Regression, SVM, KNN, Naive Bayes, Random Forest, and XGBoost. Among these, Random Forest and XGBoost achieved 95% accuracy, 0.98 recall, and ROC-AUC scores of 0.9943 and 0.9835 respectively. The proposed hybrid ensemble model (Random Forest + XGBoost) outperformed all with 96% accuracy, 0.95 precision, 0.98 recall, and a ROC-AUC score of 0.9961. These findings demonstrate that the hybrid strategy is effective in providing high diagnostic precision using clinical survey data that is not imaging. 2025 IEEE. Subject The topic of the resource Hybrid Ensemble; Lung Cancer Detection; Machine Learning; Medical AI; Non-Imaging Prediction Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152989-5; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Shankar, Uma; Upreti, Shitiz; Radhakrishnan, G.V.; Hundekari, Sheela; Date, Saroj Title A name given to the resource AQUAPHISH: Leveraging Metaheuristics and Automated Machine Learning for Precision Phishing Detection Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Applied Science and Technology Trends;Volume;6;Issue;1;pp.87-102 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.38094/jastt61238" target="_blank" rel="noreferrer noopener">https://doi.org/10.38094/jastt61238</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105012279379?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105012279379?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Department Computer Applications, Christ University, Delhi NCR, Ghaziabad, India; Shankar U., Faculty of Management and Social Sciences, Qaiwan International University, Kurdistan Region, Sulaimanyah, Iraq; Upreti S., Lloyd Business School, Uttar Pradesh, Greater Noida, India; Radhakrishnan G.V., Department of Economics and Finance, KIIT School of Management (KSOM), KIIT University, Bhubaneswar, India; Hundekari S., Chinchwad University, School of Computer Applications, Pune, India; Date S., Department of Artificial Intelligence and Data Science, CSMSS Chh. Shahu College of Engineering, Chh. Sambhajinagar, Maharashtra, India Description An account of the resource Phishing is an ongoing and dynamic threat in the field of cybersecurity, targeting user trust to capture sensitive data through fraudulent websites. Conventional detection systems tend to use binary classification and static features, which make them less flexible to new attack paradigms. This paper seeks to design a solid and comprehensible phishing detection system that alleviates the drawbacks of binary labeling by proposing a regression-based risk scoring model. The aim is to improve accuracy, feature interpretability, and deployment in real-time settings. The new method combines Whale Optimization Algorithm (WOA) for feature selection and H2O AutoML for model creation and assessment. A filtered dataset of 10,000 phishing and normal websites is operated upon using 48 features, which are then reduced to 36 using WOA. The last models are optimized with H2O AutoML, encompassing ensemble learners, and tested on various regression metrics. Interpretability is achieved with SHAP analysis. The best model had an R of 0.9534, RMSE of 0.1079, and MSE of 0.0116, better than traditional classification-based phishing detectors. The system, with only 36 features, had training time decreased by 23.6% and inference latency reduced by ~18%, without any sacrifice in detection accuracy (98.3%). Regression-based scoring also supported adaptive threat ranking in real time. By posing phishing detection as a regression problem and integrating metaheuristic feature selection with AutoML, this work introduces a scalable and explainable framework ready for real-world deployment. The low-latency yet high-accuracy model is best suited for integration into browser-level phishing filters and cloud-based threat intelligence platforms. 2025, Interdisciplinary Publishing Academia. All rights reserved. Subject The topic of the resource cybersecurity; optimization algorithm; Phishing attack; random forest algorithm; regression analysis; whale optimization algorithm Publisher An entity responsible for making the resource available Interdisciplinary Publishing Academia Relation A related resource ISSN: 27080757; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Singh, Anju; Singh, Divakar; Shoran, Preety; Shankar, Uma; Yadav, Meenakshi; Jain, Rituraj Title A name given to the resource Enhanced Pneumonia Detection from Chest X-rays Using Machine Learning and Deep Neural Architectures Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived ARO-The Scientific Journal of Koya University;Volume;13;Issue;1;Article No.;12174;pp.215-226 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.14500/aro.12174" target="_blank" rel="noreferrer noopener">https://doi.org/10.14500/aro.12174</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105011745503?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105011745503?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India; Singh A., Department of Computer Science and Engineering, Lakshmi Narain College of Technology, Kalchuri Nagar, Raisen Road, Madhya Pradesh, Bhopal, India; Singh D., Department of Computer Science and Engineering, university Institute of Technology, Barkatullah University, Madhya Pradesh, Bhopal, India; Shoran P., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India; Shankar U., Department of Management, Faculty of Management and Social Sciences, Qaiwan International University, Kurdistan, Sulaimanyah, Iraq; Yadav M., Department of Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India; Jain R., Department of Information Technology, Marwadi University, Gujarat, Rajkot, India Description An account of the resource Pneumonia is a major worldwide health concern, particularly for vulnerable groups such as babies and the elderly. Despite advances in medical imaging, diagnosing pneumonia using a chest X-ray remains difficult, due to the subtle presentation of symptoms and the variety in picture interpretation. This study utilizes modern machine learning can improve the accuracy and speed of diagnosing pneumonia using chest X-ray images. Utilizing a comprehensive dataset from the Kaggle online repository, consisting of over 5,000 annotated images, we evaluate the efficacy of various machine learning models including deep convolutional neural networks (CNN) and ensemble learning techniques. Our findings indicate that models like the Fuzzy opponent histogram filter combined with Logistic model trees (LMT) achieved the highest accuracy at 96.97%, while the deep learning-based Lenet (CNN) with LMT closely followed at 95.85%. The study aims to improve diagnostic precision, reduce interpretation discrepancies, and facilitate faster clinical decision-making by identifying the most effective machine learning approaches for real-world applications in healthcare settings. 2025 Kamal Upreti, Anju Singh, Divakar Singh, Preety Shoran, Uma Shankar, Meenakshi Yadav and Rituraj Jain. Subject The topic of the resource Artificial intelligence; Chest X-rays; Fuzzy opponent histogram filter; Machine learning; Pneumonia Publisher An entity responsible for making the resource available Koya University Relation A related resource ISSN: 24109355; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Upreti, Kamal; Yadav, Amit; Rai, Ashish Kumar; Atasever, Mesut; Sharma, Suman; Radhakrishnan, G.V. Title A name given to the resource IT Strategies for Effective Marketing in Globally Diverse Corporate Environments Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 World Skills Conference on Universal Data Analytics and Sciences, WorldSUAS 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/WorldSUAS66815.2025.11199065" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/WorldSUAS66815.2025.11199065</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105022270076?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105022270076?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Upreti K., CHRIST University, Dept. of Computer Sciecne, India; Yadav A., Chandiwala Institute of Professional Studies, Dept. of Management Banarsidas, Delhi, India; Rai A.K., Ramchandra Chandravansi University, Faculty of Commerce &amp; Management, Jharkhand, India; Atasever M., T.C. Usak University, Faculty of Applied Sciences, Department of Logistics Management, Turkey; Sharma S., Chandigarh Group of Colleges Jhanjeri, Department of Multimedia and Journalism, Punjab, Mohali, India; Radhakrishnan G.V., Kalinga Institute of Technology, Kalinga School of Management, Bhubaneswar, India Description An account of the resource Today, organizations discern multicultural teams, dynamic consumer tastes and shrinking landscapes of competition bordering on the internet-centric global economy. This paper investigates the role of IT strategies in improving the strategic marketing within different corporate environments. An examination of IT's role in addressing marketing and management complexity in different cultural context is made. Theoretical models are reviewed and responsible global marketing practices are promoted through digital transformation to reshapes the business operations. We also illustrate IT based solutions for dealing with cross cultural communication barriers, resistance to change as well as team dynamics. In this case study and trend analysis with trends, we show how own best practices of market segments, digitalization as well as cross cultural management work together with IT to encourage agility, customer focus, and continuous learning in the organization. 2025 IEEE. Subject The topic of the resource Cross-Cultural Management; Cultural Adaptability; Diverse Work Environments; Global Business Strategy; Inclusive Marketing; Information Technology(IT); Market Segmentation; Strategic Marketing Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153925-2; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Uprety, Deepak Chandra; Upreti, Kamal; Kshirsagar, Pravin R.; Tak, Tan Kuan; Upreti, Shitiz; Radhakrishnan, Ganesh V.; Kumar, Ajay Title A name given to the resource Decentralized Data Integrity: Integrating MySQL with Blockchain for Resilient Healthcare Systems Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Mobile Multimedia;Volume;21;Issue;2;pp.275-306 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.13052/jmm1550-4646.2124" target="_blank" rel="noreferrer noopener">https://doi.org/10.13052/jmm1550-4646.2124</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014256518?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014256518?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Uprety D.C., Dept. of Computer Science and Engineering, Noida Institute of Engineering and Technology, Greater Noida, India; Upreti K., Dept. of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India; Kshirsagar P.R., Dept. of Electronics &amp; Telecommunication, J D College of Engineering &amp; Management, Maharashtra, Nagpur, India; Tak T.K., Engineering Cluster, Singapore Institute of Technology, Singapore; Upreti S., School of Computer Science &amp; Engineering (SCSE), IILM University, (UP), Greater Noida, India; Radhakrishnan G.V., Dept. of Economics and Finance, KIIT School of Management (KSOM), KIIT University, Bhubaneswar, India; Kumar A., Inderprastha Engineering College, Ghaziabad, India Description An account of the resource A transformational solution to the problems created by healthcare data management is presented by the integration of MySQL and blockchain technology, centered around security, scalability, and efficiency. This paper presents MBHA MySQL-Blockchain Healthcare Architecture combining thestructured data storage, querying capabilities of MySQL with the decentralized, tamper-proof framework of blockchain. The system shows impressive performance metrics with an average API response time of 1.54 seconds for user registration and 841 milliseconds for login. The database queries and data retrieval or insertion took less than 1 millisecond, and JWT tokens were generated for authentication in less than 50 milliseconds. Conclusion Results indicate an efficient real-time system to accomplish tasks with integrity in terms of data but also with safety in operations. This architectural model, discussed above, is issues regarding data security and access with a need to provide care-collaboration needs. Scalability would then be optimized while keeping down computational overhead; in fact, work toward readiness for adoption is mainly towards being more regulatory compliant. 2025 River Publishers Subject The topic of the resource blockchain; data integration; data secrity; healthcare information systems; MySQL Publisher An entity responsible for making the resource available River Publishers Relation A related resource ISSN: 15504646; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Urs C, Yogeshraj; Prasanna, H S; Unnam, Anil Title A name given to the resource A physics-informed neural network framework for consolidation parameter prediction using controlled clay-sand mixtures Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Results in Engineering;Volume;29;Issue;;Article No.;109255; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.rineng.2026.109255" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.rineng.2026.109255</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105029067932?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105029067932?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Urs C Y., Department of Civil Engineering, The National Institute of Engineering, Mysuru, Visvesvaraya Technological University, Karnataka, Belgaum, India, Department of Civil Engineering, SOET, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Prasanna H.S., Department of Civil Engineering, The National Institute of Engineering, Mysuru, Visvesvaraya Technological University, Karnataka, Belgaum, India; Unnam A., Department of Civil Engineering, The National Institute of Engineering, Mysuru, Visvesvaraya Technological University, Karnataka, Belgaum, India Description An account of the resource This paper introduces a novel Physics-Informed Neural Network (PINN) model for predicting the coefficient of consolidation (Cv) in high plasticity clays. The model was trained from experimental data obtained from controlled clay-sand mixtures. The input parameters include clay content, Atterberg limits, initial void ratio, compaction energy, applied pressure and consolidation characteristics like compression index (Cc) and volumetric compressibility (mv). Additional parameters like plasticity index, porosity, activity-clay interaction and compaction efficiency were derived from feature engineering. The proposed PINN model combines data-driven loss and physics-based loss into a total loss function. The physics loss includes three constraints derived from modified Kozeny-Carman equations, activity-based mineralogical relations, and compression-volume consistency. Hyperparameter optimization identified the optimal configuration: 800 epochs, learning rate 0.001, architecture [128, 64, 32], and physics loss weights distributed as 0.7, 0.25, and 0.05. Five-fold cross-validation demonstrated robust performance (R2 = 0.9903 0.0026), significantly outperforming baseline neural networks (R2 = 0.9682 0.0126, p = 0.0116) with 73.9% reduction in Root Mean Square Error (RMSE = 6.37 10-11 m/s) and 5.71% improvement in Mean Absolute Percentage Error (MAPE = 4.48%). External validation showed the PINN (R = 0.9968) substantially outperformed empirical correlations (best R2 = 0.1636) and conventional machine learning models (best R2 = 0.9878). SHapley Additive exPlanations (SHAP) interpretability analysis validated physically meaningful decision-making, with plastic limit and activity emerging as primary drivers. This framework provides a transferable, physics-consistent solution applicable across diverse clay types for foundation design and site characterization. Copyright 2026. Published by Elsevier B.V. Subject The topic of the resource Activity-clay interaction; Coefficient of consolidation; Explainable AI; Geotechnical engineering; High plasticity clays; Machine learning; Physics-informed neural networks Publisher An entity responsible for making the resource available Elsevier B.V. Relation A related resource ISSN: 25901230; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Effect of glass and coir fiber on geotechnical properties of clayey soil Subject The topic of the resource CBR; Coir fiber; Glass fiber; UCS Description An account of the resource The use of fibers for the improvement of weak subgrade soils is beneficial as it not only acts as reinforcement but also, increases drainage, provides better workability, inexpensive and required in exiguous quantity. Available studies on clay soil reinforced are limited to a particular type of fiber, any comparative study on two or more types of fibers on same soil, provides a useful information on understanding suitability of specific type of fiber. This study deals with experimental characterization of clay soil reinforced with glass and coir fibers. California Bearing Ratio (CBR) and Unconfined Compressive Strength (UCS) tests were performed on these fiber reinforced clay samples with different percentage of glass and coir fibers. The results of these unreinforced and reinforced soils are compared. 2019 SERSC. Creator An entity primarily responsible for making the resource Urs Y.C.; Nanjunda K.N.; Thejas H.K. Source A related resource from which the described resource is derived International Journal of Advanced Science and Technology, Vol-29, No. 3, pp. 5212-5218. Publisher An entity responsible for making the resource available Science and Engineering Research Support Society Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082753506&amp;partnerID=40&amp;md5=3950b41a61d9050a377936f4025ee11e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082753506&amp;partnerID=40&amp;md5=3950b41a61d9050a377936f4025ee11e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 20054238 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Urs Y.C., CHRIST (Deemed to be University), India; Nanjunda K.N., Reva University, India; Thejas H.K., CHRIST (Deemed to be University), India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Wall jet nanofluid flow with thermal energy and radiation in the presence of power-law Subject The topic of the resource Nanofluid; power-law; radiation; suction/injection; wall jet Description An account of the resource The effectiveness of jet flow in the energy transfer process has made it very useful in industrial applications. These flows also have higher heat transfer coefficients than traditional cooling through convection. The appliances inclusive of the jet make effective use of fluid and enhance the heat transfer rate. The contemporary article investigates the jet flow of power-law nanofluid past a moving wall. The nanofluid is formed by suspending Cu and Al2O3 nanoparticles in water. Furthermore, the jet flow is analyzed in the presence of radiation, which is further assumed to be linear, and the application of Rosseland approximation is considered to be valid. Considering these aspects, the model is designed using partial differential equations (PDE), which are then converted to a system of non-linear ordinary differential equations (ODE) by implementing certain similarity transformations. Thus, the obtained system is solved using numerical methods, and the results are discussed with the help of graphs. The significant conclusions of the analysis were that the increase in the radiation parameter contributed to the increase in the temperature of the nanofluid. The increase in the Prandtl number reported a decrease in the amount of heat absorbed by the nanofluid. 2023 Taylor &amp; Francis Group, LLC. Creator An entity primarily responsible for making the resource Usafzai W.K.; Saeed A.M.; Aly E.H.; Puneeth V.; Pop I. Source A related resource from which the described resource is derived Numerical Heat Transfer; Part A: Applications, Vol-85, No. 14, pp. 2367-2379. Publisher An entity responsible for making the resource available Taylor and Francis Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/10407782.2023.2222456" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/10407782.2023.2222456</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162630575&amp;doi=10.1080%2F10407782.2023.2222456&amp;partnerID=40&amp;md5=32b09379e83ef604c0e5b6bc180ae83a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162630575&amp;doi=10.1080%2f10407782.2023.2222456&amp;partnerID=40&amp;md5=32b09379e83ef604c0e5b6bc180ae83a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 10407782; CODEN: NHAAE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Usafzai W.K., School of Mathematics and Physics, Nanjing Institute of Technology, Jianging, Nanjing, China; Saeed A.M., Department of Mathematics, College of Science, Qassim University, Burayadah, Saudi Arabia; Aly E.H., Department of Mathematics, Faculty of Education, Ain Shams University, Roxy, Cairo, Egypt; Puneeth V., Department of Computational Sciences, School of Sciences, CHRIST University, Delhi NCR, Ghaziabad, India; Pop I., Department of Mathematics, Babe?-Bolyai University, Cluj-Napoca, Romania Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A study on Challenges of Indian Hospitality Industry and Remedies For Sustainability in the Ever Changing Market Scenario. Subject The topic of the resource Department of Hotel Management Description An account of the resource VOLUME NO. 3 (2013), ISSUE NO. 11 (NOVEMBER) ISSN: 231-1009 Creator An entity primarily responsible for making the resource Usha Dinakaran Source A related resource from which the described resource is derived <a href="https://ijrcm.org.in/article_info.php?article_id=3991" target="_blank" title="Click Here" rel="noreferrer noopener">https://ijrcm.org.in/article_info.php?article_id=3991</a> Publisher An entity responsible for making the resource available International Journal of Research in Computer Application & Management Date A point or period of time associated with an event in the lifecycle of the resource 2013 Language A language of the resource English Type The nature or genre of the resource Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Culinary influence on Bengaluru as a tourism destination / Subject The topic of the resource Hotel Management Description An account of the resource International Journal of Recent Technology And Engineering, Vol.8, Issue 4, pp.766-774, ISSN No: 2277-3878. Creator An entity primarily responsible for making the resource Usha Dinakaran and Sushil Dwarkanath Source A related resource from which the described resource is derived <a href="https://www.ijrte.org/portfolio-item/D7368118419/">https://www.ijrte.org/portfolio-item/D7368118419/</a> Publisher An entity responsible for making the resource available IJRTE Date A point or period of time associated with an event in the lifecycle of the resource 2019-12-31 Language A language of the resource English Type The nature or genre of the resource Journal Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PHD PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Relation A related resource 61000114 Title A name given to the resource A Study on the impact of foreign investment in infrastructure sector in india Subject The topic of the resource Commerce Description An account of the resource The growth of an economy is determined by the amount of investment made or the capital created in the economy. Capital creation happens when the economy has excess of income over expenditure, in other words, savings. newlineForeign Investment is a good source of fund for developing economies whose savings is low. Hence, opening up the economy for inflow of foreign funds has almost become inevitable in the present situation of liberalization, privatization and globalization. Therefore, all developing economies, including India, are creating opportunities for foreign investments. Infrastructure plays a pivotal role in development of a country. However infrastructure projects require huge investment and the projects take a long time for the projects to be completed. This necessitates investment inflows to originate from the Government, PPP, FDI, etc. Foreign investment through foreign direct investment and Foreign Institutional Investment has newlinebecome a popular source of investment, particularly for financing the projects newlineof infrastructure sector. Foreign funds flow into the firms through investment in the equity of the firms Infrastructure plays a pivotal role in development of a country. newlineHowever infrastructure projects require huge investment and the projects take a long time for the projects to be completed. This necessitates investment inflows to originate from the Government, PPP, FDI, etc. Foreign investment through foreign direct investment and Foreign Institutional Investment has newlinebecome a popular source of investment, particularly for financing the projects newlineof infrastructure sector. Foreign funds flow into the firms through investment in the equiy of the firms Regression analysis is used to ascertain the functional relationship among FDI, Growth, Trade enness, Economic Stability and Energy position. The result of the regression analysis proves that there exists a functional relationship between FDI equity inflows and growth and trade openness. Creator An entity primarily responsible for making the resource Usha, S. Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Contributor An entity responsible for making contributions to the resource L, Ganesh Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/340510" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/340510</a> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Uthaman, Ujwal; Dsilva, Alan Chris; Johny, Danny; Parag Jose, C.; Venkataswamy, R.; Wang, Yong Title A name given to the resource Digital Twinning of an Electric Two-Wheeler for Real-Time Battery State Estimation and Augmented Reality Visualization Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 IEEE International Conference on Vehicular Technology and Transportation System, ICVTTS 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICVTTS67119.2025.11296457" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICVTTS67119.2025.11296457</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032070394?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032070394?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Uthaman U., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Dsilva A.C., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Johny D., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Parag Jose C., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Venkataswamy R., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Wang Y., Binghamton University, New York, United States Description An account of the resource This paper describes the design and structure of a digital twin system for an electric two-wheeler. It enables real-time battery state estimation and augmented reality visualization. Using digital twin technology, the system improves battery monitoring, rider experience, and operational efficiency through real-time simulation and optimization. The structure includes a physical sensing layer, an ESP32-based processing unit, cloud-based data management using ThingSpeak, and an AR front-end. It tackles key challenges in estimating the state of LiFePO4 batteries, such as voltage plateau behavior, temperature sensitivity, and accuracy of algorithms. The system also considers the limits of microcontroller-based sensing and data interfacing, ensuring reliable performance in real-time. 2025 IEEE. Subject The topic of the resource Augmented Reality; battery management system; Digital twin; electric two-wheeler; ESP32; Internet of Things; LiFePO4 battery; Model Viewer; range estimation; State of Charge; State of Health; ThingSpeak Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156522-0; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Utkarsh, Utkarsh; Kanwar, Palak Title A name given to the resource Alexithymia and Internet Addiction: Mediating Role of Social Connectedness, Impulsivity, and Moderation by Depression Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Europe's Journal of Psychology;Volume;21;Issue;2;pp.125-137 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.5964/ejop.15353" target="_blank" rel="noreferrer noopener">https://doi.org/10.5964/ejop.15353</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007576002?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007576002?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Utkarsh U., Department of Psychology, Christ University, Karnataka, Bangalore, India; Kanwar P., Department of Psychology, Christ University, Karnataka, Bangalore, India Description An account of the resource Internet addiction is a mounting concern in current times. Recent studies indicate a link between alexithymia and Internet addiction, but the underlying mechanisms of this association require more investigation. The present study explores the relationship between alexithymia and Internet addiction, with the mediating effect of Impulsivity and social connectedness, and the moderating effect of depression. A convenience sample of 362 participants between the ages of 18 and 25 years participated in this study and completed the Youngs Internet Addiction Test, Toronto-Alexithymia Scale, The Social Connectedness Scale, Barratt Impulsiveness Scale 15, and The Centre for Epidemiological Studies Depression Scale Revised. The results indicate that the direct effect of alexithymia on Internet addiction is partially mediated through impulsivity and social connectedness. Further, the moderating effect of depression is found to be non-significant. The results revealed two possible pathways through which alexithymia influences Internet addiction. Future research and interventions on Internet addiction can use these findings to mitigate the adverse outcomes of Internet addiction. 2025, PsychOpen. All rights reserved. Subject The topic of the resource alexithymia; depression; impulsivity; internet addiction; social connectedness Publisher An entity responsible for making the resource available PsychOpen Relation A related resource ISSN: 18410413; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Uwah, Salome Enoshi; Iwendi, Celestine; Sharma, Vandana; Ojo, Olayinka Anthony; Okewumi, Peter Olufeyi; Nwigwe, Simon Title A name given to the resource Deep Learning-Based Health Risk Prediction in Contact Sports Using Wearable Sensor Data Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 12th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRITO66076.2025.11241161" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO66076.2025.11241161</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105029803555?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105029803555?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Uwah S.E., University of Greater Manchester, Centre of Intelligence of Things, Bolton, United Kingdom; Iwendi C., University of Greater Manchester, Centre of Intelligence of Things, Bolton, United Kingdom; Sharma V., Christ University, Dept. of Computer Science, Bengaluru, India; Ojo O.A., University of Greater Manchester, Centre of Intelligence of Things, Bolton, United Kingdom; Okewumi P.O., University of Greater Manchester, Centre of Intelligence of Things, Bolton, United Kingdom; Nwigwe S., University of Greater Manchester, Centre of Intelligence of Things, Bolton, United Kingdom Description An account of the resource This study presents a deep learning-based approach to predicting physiological health risks in athletes engaged in contact sports using wearable sensor data. Motivated by the need to detect early warning signs of collapse or severe fatigue, this study employs a Long Short-Term Memory (LSTM) neural network to analyse multivariate time-series data. Key physiological signals, including heart rate, body temperature, and motion, were extracted from the PAMAP2 dataset to train and validate the model. The LSTM demonstrated strong predictive performance, achieving an accuracy of 98.3% in identifying potentially dangerous physiological states. In addition to its high classification accuracy, the model effectively captured temporal dependencies in the data, underscoring its suitability for health risk prediction in dynamic, high-intensity sports environments. This study highlights the potential of wearable data and LSTMbased analysis in supporting proactive athlete health management and injury prevention. 2025 IEEE. Subject The topic of the resource Athlete Health; Collapse risk Prediction; Contact Sports; LSTM-long short-term memory; Monitoring; PAMAP2; Wearable sensors Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155421-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library https://archives.christuniversity.in/files/original/27cb911f312f57fc74cc7dfde9fcade8.pdf 9e3f49f4ef622faa272ad606c18ff792 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource MPHIL Mphil Mphil Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Expert System for Diabetes Diagnosis Creator An entity primarily responsible for making the resource V Smitha Date A point or period of time associated with an event in the lifecycle of the resource 2010 Source A related resource from which the described resource is derived Computer Science Description An account of the resource Expert system is a computer system that emulates the decision making ability of a human expert. That is it acts in all respects like a human expert. It uses human knowledge to solve problems that would require human intelligence. The expert system represents expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Diabetes is a knotty disease and very common in the modern world. Diabetes is a serious disease that affects almost every organ in the body like heart, eyes, kidney, skin, nerves, blood vassals, foot etc. If left the disease unchecked it will make serious complications including death. Though the disease can not possible to cure completely, it can be well managed or control and can lead a very healthy life. Early diabetes diagnosis plays a crucial role in diabetic control, and can prevent further medical complications. This paper presents the design and development of medical expert system for Diabetes disease and it support diagnosis, give information about complications and act as diabetes trainer. It used rule based approach to collect data and forward chaining inference technique. This system provides a user interactive, menu driven environment. Symptoms and risk factors associated with diabetes are taken as the basis of this study. In case of diagnosis the system will ask a bunch of questions about the symptoms and risk factors to the expert system user and user should give yes or no answer. According to the answer the system will make judgment about the possibility of illness, how much severe it is like slight chance, moderate chance, high chance, very high chance, diabetic or not. If the user wants to know the details of diabetes complications he can select the complication option from the menu. It can also used in teaching practice. The system is drawn up with CLIPS expert system building tool version 6.3 and in Windows/Dos environment. https://archives.christuniversity.in/files/original/f470e9c74853a0caef3cef1b184db03e.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Unstructured data extraction system using multi head attention and a novel language model / Subject The topic of the resource A system 100 for Offline handwritten text recognition (HTR) of a scanned handwritten text input image Description An account of the resource Patent Number: 202141056398, Applicant: K. P. Kavitha. A system 100 for Offline handwritten text recognition (HTR) of a scanned handwritten text input image leveraging Modern Deep Recurrent Neural Network (RNN). System 100 comprises (RNN) is proposed with the help of the present's embodiments disclosure (RNN). A cursive eliminated handwritten text image is mapped to a multi-head attention-based sequence-to-sequence learning applying the beam search technique and employing an RNN-based variable-length encoder-decoder architecture. Creator An entity primarily responsible for making the resource V B, Kirubanand. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1XgfZYa8TLnvoNTuhS87WtObtmF9TeNlZ/view" target="_blank" title="Unstructured data extraction system using multi head attention and a novel language model /" rel="noreferrer noopener">https://drive.google.com/file/d/1XgfZYa8TLnvoNTuhS87WtObtmF9TeNlZ/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2021-05-09 Language A language of the resource English Type The nature or genre of the resource Patent https://archives.christuniversity.in/files/original/d29a9ba5d643019021611bb5abeecf96.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Secure image retrieval and classification framework for IOT based healthcares systems using deep neural networks / Subject The topic of the resource Computer Science Description An account of the resource Patent Number: 202241035066, Applicant: Dr.S.Balamurugan. Deep Learning has shown promising results in the domain of Medical Image Analysis and Image Processing. Proposed is a secure image retrieval and classification framework for IoT based healthcare systems using Deep Neural Networks. The problem of solving the error introduced by adversarial noise is considered. Back Propagation Algorithm is employed for Segmentation (localization) as well as error prediction and detection. Creator An entity primarily responsible for making the resource V B, Kirubanand. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1VB0jQZjiG19a9G9BqvnIBsCff2HwDMfi/view" target="_blank" title="Secure image retrieval and classification framework for IOT based healthcares systems using deep neural networks /" rel="noreferrer noopener">https://drive.google.com/file/d/1VB0jQZjiG19a9G9BqvnIBsCff2HwDMfi/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-22 Language A language of the resource English Type The nature or genre of the resource Patent