100 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 Rajagopal, Manikandan; Sivasakthivel, Ramkumar; Anitha, G.; Arunachalam, Krishna Prakash; Loganathan, K.; Abbas, Mohamed; Kalathil, Shaeen; Rao, K. Srinivas Title A name given to the resource An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks 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 Scientific Reports;Volume;15;Issue;1;Article No.;27476; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1038/s41598-025-10794-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1038/s41598-025-10794-5</a> <a href="https://www.scopus.com/pages/publications/105011957938?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105011957938?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 Rajagopal M., Christ University, Karnataka, Bangalore, India; Sivasakthivel R., Christ University, Karnataka, Bangalore, India; Anitha G., Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Tamil Nadu, Chennai, India; Arunachalam K.P., Departamento de Ciencias de la Construcci, Facultad de Ciencias de la Construcci Ordenamiento Territorial, Universidad Tecnolica Metropolitana, Santiago, 8330383, Chile; Loganathan K., Department of Mathematics and Statistics, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Abbas M., Central Labs, King Khalid University, P.O. Box 960, AlQuraa, Abha, Saudi Arabia, Electrical Engineering Department, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia; Kalathil S., Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia; Rao K.S., Department of Computer Science and Engineering, MLR Institute of Technology, Telangana, Hyderabad, India Description An account of the resource Intelligent Transportation Systems (ITS) necessitate scalable, real-time, and adaptive traffic flow prediction models to enhance urban mobility and alleviate congestion. Conventional Graph Neural Network methodologies encounter difficulties in managing extensive road networks, long-range temporal relationships, and computing efficiency for real-time applications. An innovative deep learning framework named Meta Temporal Hyperbolic Quantum Graph Neural Networks that integrates hyperbolic embeddings, meta learning, quantum graph, Neural Ordinary Differential Equation (NODEs) to improve the ITS Performance. Across many cities, meta learning facilitates swift adaptation with minimum retraining whereas hyperbolic graph embeddings efficiently depict hierarchical route configurations The usage of Quantum Graph Neural Networks (QGNNs) enhances graph-based scheming, enabling real-time traffic flow to forecast for extensive networks. Also, NODEs summarize ongoing traffic progress, enhancing precision under dynamic sceneries. Datasets like Los-loop and SZ-taxi datasets are validated by experiments which highlights the impact of the proposed MTH-QGNN model, acquiringamean value RMSE of 4.5 and MAE of 3.5, ensuring minimal prediction error. MTH-QGNN model constantly sustained accuracy above 80% and R2 values exceeding 83%, representing robust predictive trustworthiness. MTH-QGNN effectively captures complex spatiotemporal traffic patterns with a variance score above threshold value. The Author(s) 2025. Subject The topic of the resource Graph neural networks (GNNs); Hyperbolic graph embeddings; Intelligent transportation systems (ITS); Meta-learning; Neural ODEs; Quantum computing; Traffic flow prediction Publisher An entity responsible for making the resource available Nature Research Relation A related resource ISSN: 20452322; 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 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 An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm Subject The topic of the resource Cloud computing; Hybrid Harris hawks optimization-cuckoo search algorithm; Load balancing; Quality of service; Service level agreement; Task scheduling Description An account of the resource Cloud computing has rapidly emerged as a burgeoning research field in recent times. However, despite this growth, a comprehensive examination of this domain reveals persistent issues in the application of cloud-based systems concerning workload distribution. The abundance of resources and virtual machines (VMs) within cloud computing underscores the importance of efficient task allocation as a critical process. Within the infrastructure as a service (IaaS) architecture, load balancing (LB) remains a pivotal but challenging task. The occurrence of overloaded or underloaded hosts/servers during cloud access is undesirable, as it leads to operational delays and system performance degradation. To address LB issues effectively, it is imperative to deploy a proficient access scheduling algorithm capable of distributing tasks across the available resources. A novel approach was introduced by combining the Harris hawks optimization and cuckoo search algorithm (HHO-CSA), with a specific focus on critical service level agreement (SLA) parameters, particularly deadlines, to uphold LB in a cloud environment. The primary objective of the hybrid HHO-CSA methodology is to provide task attributes, resource allocation, VMs prioritization, and quality of service (QoS) to clients within cloud computing applications. The outcome analysis reveals that the proposed hybrid HHO-CSA algorithm results in a resource utilization reduction of 52%, with an execution time of 529.84 ms and a makespan of 638.88 ms. These values outperform those of existing SLA-based LB algorithms. Effective task scheduling plays a pivotal role in ensuring the seamless execution of tasks within a cloud system, while LB significantly aligns with the SLAs available to users. Drawing insights from the existing literature, the suggested hybrid HHO-CSA method addresses the research gap by effectively mitigating the challenges. 2023, Accent Social and Welfare Society. All rights reserved. Creator An entity primarily responsible for making the resource Pani A.K.; Manohar M.; Thomas M.; Kumar P. Source A related resource from which the described resource is derived International Journal of Advanced Technology and Engineering Exploration, Vol-10, No. 105, pp. 1050-1062. Publisher An entity responsible for making the resource available Accent Social and Welfare Society Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.19101/IJATEE.2022.10100466" target="_blank" rel="noreferrer noopener">https://doi.org/10.19101/IJATEE.2022.10100466</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170093103&doi=10.19101%2FIJATEE.2022.10100466&partnerID=40&md5=2d5945e0d43fea281fa5081d2e64e705" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170093103&doi=10.19101%2fIJATEE.2022.10100466&partnerID=40&md5=2d5945e0d43fea281fa5081d2e64e705</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 23945443 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 Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Manohar M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Thomas M., School of Computer Science, RV University, Bengaluru, India; Kumar P., Department of Computer Science and Engineering, Motihari College of Engineering, Bihar, 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 Conference Papers 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/. Title A name given to the resource An Efficient Localized Route Recommendation Scheme using Fusion Algorithm for VANET based Applications Subject The topic of the resource co-operative vehicles; Fusion Algorithm; genetic algorithm; heuristic based approaches; Localized route recommendation Description An account of the resource The evolution of vehicles has led to the need for improved and advanced techniques to solve traffic related problems. The improvement related to cooperative vehicles has been a recent focus in dealing with such difficulties. The most popular application of co-operative vehicles is the route planning for travelers. In this paper, an innovative module namely Localized Route Recommendation with Fusion Algorithm (LR2FA) is proposed to enumerate a localized route recommendation system to communicate to co-operative vehicles. Traffic parameters such as vehicle speed and density information collected from the centralized location and used as decision factor to provide suggestions of routes using a novel Fusion Algorithm (FA). To evaluate the factors for route suggestion, FA uses a combination of genetic and heuristic-based approaches. The performance of the proposed localized route references is analyzed using simulated values of vehicle speed and density. It is seen from the results that the proposed LR2FA provides top fitting routes compared to greedy based route suggestion. 2022 IEEE. Creator An entity primarily responsible for making the resource Sankaranarayanan M.; Sajini S.; Anita E.A.M.; Janet J. Source A related resource from which the described resource is derived 2022 6th International Conference on Trends in Electronics and Informatics, ICOEI 2022 - Proceedings, pp. 672-677. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICOEI53556.2022.9777188" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICOEI53556.2022.9777188</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131960675&doi=10.1109%2FICOEI53556.2022.9777188&partnerID=40&md5=18628fe2f91011dc8bea084f7bd4e174" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131960675&doi=10.1109%2fICOEI53556.2022.9777188&partnerID=40&md5=18628fe2f91011dc8bea084f7bd4e174</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548328-5 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sankaranarayanan M., IIIT Sri City, Andhra Pradesh, Chittoor, India; Sajini S., Anna University, Chennai, India, SRM Institute of Science and Technology, Chennai, India; Anita E.A.M., School of Engineering and Technology, Christ University, Bengaluru, India; Janet J., Sri Krishna College of Engineering and Technology, Coimbatore, 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 An efficient low complexity compression based optimal homomorphic encryption for secure fiber optic communication Subject The topic of the resource Compression; Encryption; Fiber optic communication; Optical networks; Optimal key generation; Security Description An account of the resource Latest advancements in fiber optic communication have gained significant attention among researchers owing to many benefits such as high data rate, acceptable cost, bandwidth, low attenuation, etc. Fiber optic networks are found to be a commonly utilized platform to transfer data in several applications such as personal, commercial, military areas, etc. Although fiber optic networks are highly beneficial, security remains a challenging design issue. Numerous state of art works has been developed to achieve security in fiber optic communication. Among the various methods, compression then encryption is an effective way to effectively and securely transmit the data. With this motivation, this paper presents a new Low Complexity Compression Then Encryption using Optimal Homomorphic Encryption (LCCE-OHE) technique for secured fiber optic communication. The proposed LCCE-OHE technique operates on two major phases namely compression and encryption. At the first stage, low complexity compression using Neighboring Indexing Sequence (NIS) with Deflate algorithm, named Normalized Information Distance (NID) is used. Besides, in the second stage, Quasi Oppositional Sail Fish Optimizer with Homomorphic Encryption (QOSFO-HE) technique is employed. The QOSFO algorithm is derived by incorporating the quasi oppositional learning (QOBL) concept to the SFO algorithm and is applied to optimally select the encryption keys. The performance validation of the proposed model takes place on two benchmark datasets and the experimental results are examined interms of different performance measures. The experimental values highlighted the improved compression efficiency and security level of the LCCE-OHE technique over the other techniques. 2022 Elsevier GmbH Creator An entity primarily responsible for making the resource Venu D.; Mayuri A.V.R.; Neelakandan S.; Murthy G.L.N.; Arulkumar N.; Shelke N. Source A related resource from which the described resource is derived Optik, Vol-252 Publisher An entity responsible for making the resource available Elsevier GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.ijleo.2021.168545" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ijleo.2021.168545</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122210706&doi=10.1016%2Fj.ijleo.2021.168545&partnerID=40&md5=bfc4a6dde14053df54ce64a7f2692e9a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122210706&doi=10.1016%2fj.ijleo.2021.168545&partnerID=40&md5=bfc4a6dde14053df54ce64a7f2692e9a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 304026 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 Venu D., Department of ECE, KITS Warangal, India; Mayuri A.V.R., School of Computing Science and Engineering, VIT Bhopal University, India; Neelakandan S., Department of Computer Science and Engineering, R.M.K Engineering College, Chennai, India; Murthy G.L.N., Department of Electronics and Communication Engineering, Lakireddy Bali Reddy College of Engineering, Andhra Pradesh, India; Arulkumar N., Department of CS, CHRIST (Deemed to be University), Banglore, India; Shelke N., Department of CSE, Priyadarshini Indira Gandhi College of Engineering, Nagpur, 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 Conference Papers 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/. Title A name given to the resource An Efficient Machine Learning Approach: Analysis of Supervised Machine Learning Methods to Forecast the Diamond Price Subject The topic of the resource Diamonds; Estimated values; Machine learning; Regression Models and Cross validation Description An account of the resource Diamond, a found natural process compound of carbon, is one of the hardest and most immensely expensive material known to men, especially more to women. Investments in expensive gems like diamonds are in significant demand. The rate of a diamond, nevertheless, is not as easily calculated as the value of either gold or platinum since so many factors must be taken into account. Because there is such a broad range of diamond dimensions and qualities; as a result, being able to make reliable price predictions is crucial for the diamond industry. Although, making accurate predictions is challenging. In this study, we implemented multiple machine learning techniques employed to the challenge of diamond price forecasting's such as Linear Regression, Random Forest, Decision Tree Random Forest, Cat-Boost Regressor and XGB Regressor. This article's goal is to develop an accurate model for estimating diamond prices based on its characteristics such as weighting factor, cut grade, and dimensions. We compared the sum of estimated values and test values of predicted values with overestimated, underestimated and exact estimations. We applied cross-validation to calculate how much the model deviates from the actual when faced with a difference between the training set and the test set. We predicted values side by side. We performed a comparative analysis of supervised machine learning models with other models to evaluate the model accuracy and performance metrics. The Study's experimental findings show that out of all the supervised machine learning models, Random Forest performs well with R2score and Low RMSE and MAE values and CV Score. 2023 IEEE. Creator An entity primarily responsible for making the resource Basha M.S.A.; Oveis P.M.; Prabavathi C.; Lakshmi M.B.; Sucharitha M.M. Source A related resource from which the described resource is derived 2023 International Conference for Advancement in Technology, ICONAT 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICONAT57137.2023.10080618" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICONAT57137.2023.10080618</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153282231&doi=10.1109%2FICONAT57137.2023.10080618&partnerID=40&md5=1b4cedfa4958cc1932e36421c929fccb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153282231&doi=10.1109%2fICONAT57137.2023.10080618&partnerID=40&md5=1b4cedfa4958cc1932e36421c929fccb</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547517-4 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Basha M.S.A., GITAM School of Business, Gandhi Institute of Technology and Management, Deemed to Be University, Bengaluru, India; Oveis P.M., GITAM School of Business, Gandhi Institute of Technology and Management, Deemed to Be University, Bengaluru, India; Prabavathi C., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Lakshmi M.B., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Sucharitha M.M., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, 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 Conference Papers 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/. Title A name given to the resource An Efficient Machine Learning Classification model for Credit Approval Subject The topic of the resource Bank Loan; Credit Approval; Logistic Regression.; Machine Learning; Random Forest Description An account of the resource Credit authorization is a critical step for banks as well as every bank's main source of revenue is its line of credit. Thus, banks can profit from the loan interest they approve. Profitability or lost opportunity of a bank is highly dependent on loans that are whether consumers repay the debt or refuse. Loan collection is a significant factor in a bank's economic results. Forecasting the customer's ability to repay the loan in order to determine whether it should authorize or deny loan documents is a significant undertaking and a critical method in data analytics is being utilized to investigate the problem of loan default prediction: On the premise of assessment, the Logistic-Regression Classification Model, Random-Forest Classifier and Decision Tree Classification Models are compared. The mentioned classification algorithms were created as well as subsequently various evaluation metrics were obtained. By utilizing a suitable strategy, the appropriate clients for loan providing may be simply identified by assessing their probability of non-performing loans. This indicates that a bank really shouldn't simply prioritize wealthy consumers when giving loans, but it should also consider a client's other characteristics. This approach is critical in making credit judgments and forecasting default risk. 2023 IEEE. Creator An entity primarily responsible for making the resource Dr.D.M.V. R.; Lakshmanarao A.; Gupta C. Source A related resource from which the described resource is derived Proceedings of the 3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023, pp. 499-503. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICAIS56108.2023.10073706" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAIS56108.2023.10073706</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152380864&doi=10.1109%2FICAIS56108.2023.10073706&partnerID=40&md5=d0b0f428dfb39c9ba0328a42e8f89372" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152380864&doi=10.1109%2fICAIS56108.2023.10073706&partnerID=40&md5=d0b0f428dfb39c9ba0328a42e8f89372</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166546216-7 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Dr.D.M.V. R., Aditya Engineering College, Department of It, Surampalem, India; Lakshmanarao A., Aditya Engineering College, Department of It, Surampalem, India; Gupta C., Christ University, School of Commerce, Finance and Accountancy, 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 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 Anushka; George, Jossy; Nair, Akhil M.; Alapatt, Bosco Paul; Baby, Riya; Jose, Jiby Title A name given to the resource An Efficient Machine Learning Framework for Flood Forecasting 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 Networks and Systems;Volume;1278;pp.433-444 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-2703-5_29" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-2703-5_29</a> <a href="https://www.scopus.com/pages/publications/105006929995?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105006929995?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 Anushka, School of Sciences, Christ University, Bengaluru, India; George J., School of Sciences, Christ University, Bengaluru, India; Nair A.M., Luxsh Technologies Pvt Ltd, Northwood Hills, Middlesex, United Kingdom; Alapatt B.P., School of Sciences, Christ University, Bengaluru, India; Baby R., School of Sciences, Christ University, Bengaluru, India; Jose J., School of Sciences, Christ University, Bengaluru, India Description An account of the resource Floods, a significant natural disaster which has an impact on the whole world present major risks to ecosystems and humans, particularly in semi-arid areas with variable rainfall patterns. With the help of ICRISATs historical meteorological data and machine learning algorithms, this study has developed a customized flood prediction model for use. After evaluating and contrasting various models, including the proposed model Stacked Gradient Boosting with Random Forest (SGB-RAF), KNN, Decision Tree, Random Forest, and Linear Regression, it shows that SGB-RAF has the highest R2 score and lowest RMSE comparatively to other models. While other enhancements such as Ridge Regression and polynomial feature creation were studied, SGB-RAF remained effective. Overall, this study highlights how machine learning may improve flood prediction accuracy, which is important for disaster management and for improving the semi-arid regions adaptability to climatic variability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Decision tree; Flood prediction; KNN; Logistic regression; Machine learning; Random forest; Support vector regression Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981962702-8; 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 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 An efficient methodology for resolving uncertain spatial references in text documents Subject The topic of the resource Fuzzy Extraction Resolving and Clustering; Fuzzy Logic; Information Retrieval; Spatial Uncertainty Description An account of the resource In recent decades, all the documents maintained by the industries are getting transformed into soft copies in either structured documents or as an e-copies. In text document processing, there is a number of ways available to extract the raw data. As the accuracy in finding the spatial data is crucial, this domain invites various research solutions that provide high accuracy. In this article, the Fuzzy Extraction, Resolving, and Clustering (FERC) architecture is proposed which uses fuzzy logic techniques to identify and cluster uncertain textual spatial reference. When the text corpus is queried with a spatial-keyword, FERC returns a set of relevant documents sorted in view of the fuzzy pertinence score. Any two documents may be compared in light of the spatial references that exist in them and their fuzzy similarity score is presented. This enables finding the degree to which the two documents speak about a specified location. The proposed architecture provides a better result set to the user, unlike a Boolean search where the document is either rated relevant or irrelevant. Copyright 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Creator An entity primarily responsible for making the resource Raja K.; Kanagavalli V.R.; Nizar Banu P.K.; Kannan K. Source A related resource from which the described resource is derived International Journal of Service Science, Management, Engineering, and Technology, Vol-11, No. 3, pp. 1-17. Publisher An entity responsible for making the resource available IGI Global 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="https://doi.org/10.4018/IJSSMET.2020070101" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/IJSSMET.2020070101</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086916326&doi=10.4018%2FIJSSMET.2020070101&partnerID=40&md5=42c563d7eeab69fa44b464df8eed1300" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086916326&doi=10.4018%2fIJSSMET.2020070101&partnerID=40&md5=42c563d7eeab69fa44b464df8eed1300</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1947959X 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 Raja K., Dhaanish Ahmed College of Engineering, Chennai, India; Kanagavalli V.R., Sri Sai Ram Engineering College, Chennai, India; Nizar Banu P.K., Christ University (Deemed), Bangalore, India; Kannan K., Audisankara College of Engineering and Technology, Nellore, 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 Conference Papers 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/. Title A name given to the resource An Efficient Multi-Modal Classification Approach for Disaster-related Tweets Subject The topic of the resource Convolution Neural Network; Deep Learning; Disaster Tweet; Gated Recurrent Unit; Late Fusion; VGG-16 Description An account of the resource Owing to the unanticipated and thereby treacherous nature of disasters, it is essential to gather necessary information and data regarding the same on an urgent basis; this helps to get a detailed overview of the situation and helps humanitarian organizations prioritize their tasks. In this paper, "An Efficient Multi-Modal Classification Approach for Disaster-related Tweets,"the proposed framework based on Deep Learning to classify disaster-related tweets by analyzing text and image contents. The approach is based on Gated Recurrent Unit (GRU) and GloVe Embedding for text classification and VGG-16 network for image classification. Finally, a combined model is proposed using both text and image modules by the Late Fusion Technique. This portrays that the proposed multi-modal system performs significantly well in classifying disaster-related content. 2022 IEEE. Creator An entity primarily responsible for making the resource Mondal A.; Kesan A.; Rodrigues A.; George J. Source A related resource from which the described resource is derived IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICDCECE53908.2022.9792951" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDCECE53908.2022.9792951</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133428851&doi=10.1109%2FICDCECE53908.2022.9792951&partnerID=40&md5=688a26df6821cad4e8d36801c58adb26" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133428851&doi=10.1109%2fICDCECE53908.2022.9792951&partnerID=40&md5=688a26df6821cad4e8d36801c58adb26</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548316-2 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mondal A., Deemed to Be University, Department of Data Science Christ, India; Kesan A., Deemed to Be University, Department of Data Science Christ, India; Rodrigues A., Deemed to Be University, Department of Data Science Christ, India; George J., Deemed to Be University, Department of Data Science Christ, 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 An efficient nonlinear access policy based on quadratic residue for ciphertext policy attribute based encryption Subject The topic of the resource Access policy; Ciphertext policy attribute based encryption; Encryption; Non-linear secret- sharing scheme; Quadratic residue Description An account of the resource Ciphertext Policy Attribute Based Encryption (CP-ABE) is an efficient encryption scheme as data owner is making decision about the attributes that can access his data and adding that attributes to access structure while encrypting that message. Most existing CP-ABE scheme are based traditional access structure such as linear secret sharing scheme which incur large ciphertext size and linearly increases according to the number of attributes. And those schemes have more computational overhead for calculating share for each attribute and when recalculating secret in data user side. In this paper, we propose a different secret sharing scheme that can be used in access policy for CP-ABE which will reduce the size of ciphertext and there by communication overhead. Furthermore, the proposed scheme reduced computational overhead of secret sharing scheme and improved overall efficiency of the scheme. 2021 Little Lion Scientific Creator An entity primarily responsible for making the resource Ancy P.R.; Krishna A.V.N. Source A related resource from which the described resource is derived Journal of Theoretical and Applied Information Technology, Vol-99, No. 21, pp. 5050-5057. Publisher An entity responsible for making the resource available Little Lion Scientific Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119290222&partnerID=40&md5=8f7d007f43287a61c7b37bc79c774a75" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119290222&partnerID=40&md5=8f7d007f43287a61c7b37bc79c774a75</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19928645 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 Ancy P.R., CSE Dept, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Krishna A.V.N., CSE Dept, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, 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 An efficient optimization based lung cancer pre-diagnosis system with aid of feed forward back propagation neural network (FFBNN) Subject The topic of the resource Artificial bee colony (ABC) algorithm; Dimensionality reduction; Feed forward back propagation neural network (FFBNN); Risk factor and symptoms Description An account of the resource World Health Organization (WHO) reports that worldwide 7.6 million deaths are caused by cancer each year. Uncontrollable cell development in the tissues of the lung is called as lung cancer. These uncontrollable cells restrict the growth of healthy lung tissues. If not treated, this growth can spread beyond the lung in the nearby tissue called metastasis and, form tumors. In order to preserve the life of the people who are suffered by the lung cancer disease, it should be pre-diagonized. So there is a need of pre diagnosis system for lung cancer disease which should provide better results. The proposed lung cancer prediagnosis technique is the combination of FFBNN and ABC. By using the Artificial Bee Colony (ABC) algorithm, the dimensionality of the dataset is reduced in order to reduce the computation complexity. Then the risk factors and the symptoms from the dimensional reduced dataset are given to the FFBNN to accomplish the training process. In order to get higher accuracy in the prediagnosis process, the FFBNN parameters are optimized using ABC algorithm. In the testing process, more data are given to well trained FFBNN-ABC to validate whether the given testing data predict the lung disease perfectly or not. 2005-2013 JATIT & LLS.All rights reserved. Creator An entity primarily responsible for making the resource Balachandran K.; Anitha R. Source A related resource from which the described resource is derived Journal of Theoretical and Applied Information Technology, Vol-56, No. 2, pp. 263-271. Publisher An entity responsible for making the resource available Asian Research Publishing Network (ARPN) Date A point or period of time associated with an event in the lifecycle of the resource 2013-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886942617&partnerID=40&md5=0c14203eaf9e4f0952bd51864fff525d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886942617&partnerID=40&md5=0c14203eaf9e4f0952bd51864fff525d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19928645 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 Balachandran K., Department of Computer Science and Engineering, Christ University, Bengaluru, India; Anitha R., Department of Master of Computer Applications, K. S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, 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 Conference Papers 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/. Title A name given to the resource An Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion Subject The topic of the resource Fundus image enhancement; Optic nerve head; Preprocessing; Retinal vessel segmentation Description An account of the resource Retinal vessel segmentation plays a significant role for accurate diagnostics of ophthalmic diseases. In this paper, a novel preprocessing step for retinal vessel segmentation via optic nerve head exclusion is proposed. The idea relies in the fact that the exclusion of brighter optic nerve head prior to contrast enhancement process can better enhance the blood vessels for accurate segmentation. A histogram based intensity thresholding scheme is introduced in order to extract the optic nerve head which is then replaced by its surrounding background pixels. The efficacy of the proposed preprocessing step is established by segmenting the retinal vessels from the optic nerve head excluded image enhanced using CLAHE algorithm. Experimental works are carried out with fundus images from DRIVE database. It shows that 1%3% of improvement in terms of TPR measure is achieved. 2019, Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Wahid F.F.; Raju G. Source A related resource from which the described resource is derived Communications in Computer and Information Science, Vol-1046, pp. 228-239. Publisher An entity responsible for making the resource available Springer Verlag Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-13-9942-8_22" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-13-9942-8_22</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070225817&doi=10.1007%2F978-981-13-9942-8_22&partnerID=40&md5=eb318c9659a6f21fa9fa481e480fffa4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070225817&doi=10.1007%2f978-981-13-9942-8_22&partnerID=40&md5=eb318c9659a6f21fa9fa481e480fffa4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18650929; ISBN: 978-981139941-1 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Wahid F.F., Department of Information Technology, Kannur University, Kannur, 670567, Kerala, India; Raju G., Department of CSE, Faculty of Engineering, Christ (Deemed to be University), Bengaluru, 560764, Karnataka, 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 An efficient privacy-preserving model based on OMFTSA for query optimization in crowdsourcing Subject The topic of the resource crowdsourcing; moth flame-based tunicate swarm algorithm; query; select and join queries Description An account of the resource Crowdsourcing is now one of the most important and transformative paradigms, with great success in a variety of application tasks. Crowdsourcing obtains knowledge and information to solve cognitive or intelligence-intensive tasks from an evolving group of participants via the Internet. Unfortunately, providing a hard privacy guarantee and query optimization is incompatible when a higher task acceptance rate needs to be accomplished and this case is common in most existing crowdsourcing solutions. The state of art systems suffered from different complexities such as lack of crowdsourcing optimization techniques, increased cost, latency, security, and scalability issues. In this paper, we have proposed a crowdsourcing model to optimize the cost and latency, issues that occur while query optimization using the Moth Flame and Tunicate Swarm Algorithm (MF-TSA). The TSA algorithm is added to the MF algorithm to enhance its exploitation capability and yield fast convergence. The data privacy concerns of the worker and the requestor are addressed using homomorphic encryption that simultaneously enhances the efficiency of the crowdsourcing framework. The main aim of this work is to optimize the cost and latency for query plan selection along with security. Initially, the homomorphic encryption model is used to encrypt the data. In query design, two kinds of crowd-controlled administrators, that is, Crowd Powered Selection (CSelect) and Crowd Powered Join (CJoin) are connected for assessing query. The proposed framework utilizes MF-TSA to optimize the selection and join queries with low cost and latency. Finally, the experimental results demonstrate better query optimization performance than other existing algorithms such as sequential, parallel, and CrowdOp. 2021 John Wiley & Sons Ltd. Creator An entity primarily responsible for making the resource Renukadevi M.; Anita E.A.M.; Mohana Geetha D. Source A related resource from which the described resource is derived Concurrency and Computation: Practice and Experience, Vol-33, No. 24 Publisher An entity responsible for making the resource available John Wiley and Sons Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1002/cpe.6447" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/cpe.6447</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109413408&doi=10.1002%2Fcpe.6447&partnerID=40&md5=287f53542d164da307755f889245bb4b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109413408&doi=10.1002%2fcpe.6447&partnerID=40&md5=287f53542d164da307755f889245bb4b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 15320626; CODEN: CCPEB 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 Renukadevi M., Department of CSE, S.A. Engineering College, Chennai, India; Anita E.A.M., Department of CSE, School of Engineering and Technology, CHRIST University, Bengaluru, India; Mohana Geetha D., Department of Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, 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 Conference Papers 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/. Title A name given to the resource An Efficient Quantum Transfer Learning for Cancer Prediction Using Tumour Markers: New Era of Computer in Medical Subject The topic of the resource accuracy; antigen; biomarkers; diagnosis; ovarian cancer; prediction; prognosis; Quantum learning; transfer learning; tumour Description An account of the resource Ovarian cancer prediction models or algorithms estimate a person's risk of getting the disease based on different variables, such as their medical history, genetics, and biomarkers. Early identification and intervention will enhance patient successive diagnosis outcomes. Tumour markers are chemicals frequently detected in higher concentrations than usual in cancer patient's blood, urine, or tissues. They could be certain chemicals or proteins linked to the presence of tumours or cancer kinds. Tumour markers are employed for diagnosis, prognosis, and treatment response monitoring. Applying information or models from one quantum job to enhance the performance of another requires quantum transfer learning. Transferring knowledge from one domain to another seeks to increase learning effectiveness in novel quantum contexts. The main goal of efficient Quantum Transfer Learning (QTL) is to minimize the resources (computer power, data, or time) necessary to transfer between tasks successfully. In this research work, QTL is used to predict Ovarian Cancer (OC) with the assistance of biomarkers. The Quantum Transfer Learning- Ovarian Cancer (QTL-OC) achieves 93.78% accuracy and outperforms the existing techniques. 2023 IEEE. Creator An entity primarily responsible for making the resource Narendran M.; Andi H.K.; Sharma D.K.; Amarendra K.; Uma S.; Poonia R.C. Source A related resource from which the described resource is derived 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023, pp. 432-437. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCSAI59793.2023.10421549" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCSAI59793.2023.10421549</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186679596&doi=10.1109%2FICCSAI59793.2023.10421549&partnerID=40&md5=b01a0309ee6aed345006b0543ea25a9a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186679596&doi=10.1109%2fICCSAI59793.2023.10421549&partnerID=40&md5=b01a0309ee6aed345006b0543ea25a9a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036996-0 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Narendran M., Kcg College of Technology, Department of Information Technology, Tamil Nadu, Chennai, India; Andi H.K., Asia Metropolitan University, Centre for Postgraduate Studies, Malaysia; Sharma D.K., Jaypee University of Engineering and Technology, Department of Mathematics, Madhya Pradesh, Guna, 473226, India; Amarendra K., Koneru Lakshmaiah Education Foundation, Department of Computer Science and Engineering, Andhra Pradesh, Vaddeswaram, 522502, India; Uma S., Dhanalakshmi Srinivasan College of Engineering and Technology, Department of Computer Science and Engineering, Tamil Nadu, Mamallapuram, India; Poonia R.C., Christ (Deemed to Be University), Department of Computer Science, Delhi-NCR, Uttar Pradesh, Ghaziabad, 201003, 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 An efficient reconfigurable band tuning filter design for channelizer in transponder satellite system Subject The topic of the resource Channelizer; Cosine modulation; Exponential modulation; FIR filters; Interpolated FIR (IFIR) Description An account of the resource For improved performance in a variety of applications, the transponder in satellite systems must be very flexible. The channelizer-dependent transponder system significantly boosts the operation of a satellite system. When channelizing wideband input signals, a digital filter bank is typically used to extract several small sub-bands. In this research, a reconfigurable band tuning (RBT) design for the channelizer in the satellite transponder system is designed and implemented. Cosine modulation, exponential modulation and IFIR filter are the techniques behind the RBT design. The RBT design facilitates the generation of many channels enabling channelization with non-uniform narrow transition width. A number of examples are presented to illustrate how well the RBT design performs. Findings indicate that there are fewer filter coefficients in the RBT design than there are in the current approaches Effective implementation of a properly designed RBT design lowers power consumption and simplifies the hardware. 2024 The Franklin Institute Creator An entity primarily responsible for making the resource Varghese R.C.; Amir A.; Inbanila K. Source A related resource from which the described resource is derived Journal of the Franklin Institute, Vol-362, No. 2 Publisher An entity responsible for making the resource available Elsevier Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.jfranklin.2024.107474" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jfranklin.2024.107474</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213205183&doi=10.1016%2Fj.jfranklin.2024.107474&partnerID=40&md5=463e7aa6bdd3ee54ce75dce6d851ac75" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213205183&doi=10.1016%2fj.jfranklin.2024.107474&partnerID=40&md5=463e7aa6bdd3ee54ce75dce6d851ac75</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 160032; CODEN: JFINA 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 Varghese R.C., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Amir A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Inbanila K., CHRIST (Deemed to be University), Karnataka, Bangalore, 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 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 Varghese, Rinu C.; Amir, A.; Inbanila, K. Title A name given to the resource An efficient reconfigurable band tuning filter design for channelizer in transponder satellite system 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 the Franklin Institute;Volume;362;Issue;2;Article No.;107474; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.jfranklin.2024.107474" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jfranklin.2024.107474</a> <a href="https://www.scopus.com/pages/publications/85213205183?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85213205183?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 Varghese R.C., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Amir A., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Inbanila K., CHRIST (Deemed to be University), Karnataka, Bangalore, India Description An account of the resource For improved performance in a variety of applications, the transponder in satellite systems must be very flexible. The channelizer-dependent transponder system significantly boosts the operation of a satellite system. When channelizing wideband input signals, a digital filter bank is typically used to extract several small sub-bands. In this research, a reconfigurable band tuning (RBT) design for the channelizer in the satellite transponder system is designed and implemented. Cosine modulation, exponential modulation and IFIR filter are the techniques behind the RBT design. The RBT design facilitates the generation of many channels enabling channelization with non-uniform narrow transition width. A number of examples are presented to illustrate how well the RBT design performs. Findings indicate that there are fewer filter coefficients in the RBT design than there are in the current approaches Effective implementation of a properly designed RBT design lowers power consumption and simplifies the hardware. 2024 The Franklin Institute Subject The topic of the resource Channelizer; Cosine modulation; Exponential modulation; FIR filters; Interpolated FIR (IFIR) Publisher An entity responsible for making the resource available Elsevier Ltd Relation A related resource ISSN: 160032; CODEN: JFINA 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 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 An Efficient Routing Strategy for Energy Management in Wireless Sensor Network Using Hybrid Routing Protocols Subject The topic of the resource Grid-based data dissemination; HKHSM; Packet delivery and throughput ratio; Routing protocol; Wireless communication channel Description An account of the resource In these days, Wireless Sensor Networks (WSN) shows a huge impact on all appliances but one of the huge challenges in WSN is management of energy because the nodes in the network run with battery power. As the replacement of energy drained nodes is difficult, and frequent failure of links may occur and it incurs huge data loss. To avoid this issue the we proposed a Hybrid Krill Herd and Spider Monkey with Grid-Based Data Dissemination (HKHSM-GBDD) protocol with the Shortest Energy Resourceful Routing (SERR) mechanism to develop an efficient and better wireless communication channel. The presented HKHSM framework is utilized to classify malicious and energy drained nodes in earlier stage and to detect the link failure. Furthermore, the SERR mechanism is processed to recover the link and route maintenance. This novel proposed protocol has improved packet delivery ratio and energy consumption. It also enhances energy state of sensor nodes by mounting its lifetime and rerouting. Finally, the competence of the proposed mechanism is compared with existing works and it shows significant improvement over existing algorithms for the considered parameters. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. Creator An entity primarily responsible for making the resource Kocherla R.; Vatambeti R. Source A related resource from which the described resource is derived Wireless Personal Communications, Vol-124, No. 1, pp. 49-73. Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11277-021-09318-x" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11277-021-09318-x</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118424376&doi=10.1007%2Fs11277-021-09318-x&partnerID=40&md5=ab6356085ada10fa5c3fdf59021b5d13" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118424376&doi=10.1007%2fs11277-021-09318-x&partnerID=40&md5=ab6356085ada10fa5c3fdf59021b5d13</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9296212; CODEN: WPCOF 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 Kocherla R., Research Scholar, Computer Science and Engineering, Presidency University, Bengaluru, India; Vatambeti R., Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, 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 An efficient scheme for water leakage detection using support vector machines (SVM)-Zig Subject The topic of the resource Machine Learning; Random Forest; Support Vector Machines; Water Leakage Detection Description An account of the resource Water is one of the most essential and valuable resources for all living beings, yet in the present day, there is a scarcity of it. Half of the water loss in large cities and industries is due to leaks and illegal lines. 10%-20% of water loss can be reduced by detecting leaks but without the presence of advanced monitoring systems, this problem is typically worsened. Monitoring the consumption and leak detection for such large areas is a challenging task. To overcome this issue a small prototype is prepared called Zig. Zig is designed for both household and industrial purposes. Its main aim is to monitor the flow and consumption of water at different levels of a building like a first-floor and so on which may represent some industrial and household situation. This work focuses on pressure/flow monitoring method to reduce the operational cost and also to detect leakage. One of the machine learning algorithms, Support Vector Machines (SVM) has been applied to detect the leakage and it is compared with Random Forest algorithm to show that proposed scheme is detecting water leakage better. BEIESP. Creator An entity primarily responsible for making the resource Kothari A.; Balamurugan M. Source A related resource from which the described resource is derived International Journal of Recent Technology and Engineering, Vol-7, No. 6, pp. 39-46. Publisher An entity responsible for making the resource available Blue Eyes Intelligence Engineering and Sciences Publication Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067851164&partnerID=40&md5=1e7ad9b39bf1c3f95a102206445b1917" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067851164&partnerID=40&md5=1e7ad9b39bf1c3f95a102206445b1917</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22773878 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 Kothari A., Department of CSE, Christ (Deemed to be University), Bengaluru, Karnataka, India; Balamurugan M., Department of CSE, Christ (Deemed to be University), Bengaluru, Karnataka, 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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 Efficient Security-Enabled Routing Protocol for Data Transmission in VANET Using Blockchain Ripple Protocol Consensus Algorithm Subject The topic of the resource ANN; Blockchain; GA; IoT; IoV; RPCA; RSU; VANET Description An account of the resource The security quality in Vehicular Ad-hoc NETworks (VANET) has improved as a result of recent developments in Intelligent Transportation Systems (ITS). However, within the current VANET system, providing a cheap computational cost with a high serving capability is a significant necessity. When a vehicle user goes between one Roadside Unit (RSU) to another RSU region in the current scenario, the current RSU periodically needs re-authentication of the vehicle user. This increases the computational complexity of the system. The gathering and broadcast of existing traffic event information by automobiles are critical in Vehicular Ad-hoc Networks (VANET). Traditional VANETs, on the other hand, have several security concerns. This work develops a blockchain-based authentication protocol to address the aforementioned difficulty. To address critical message propagation issues in the VANET, we invent a novel type of blockchain. We develop a local blockchain for exchanging real-world event messages among cars within a countrys borders, which is a novel sort of blockchain ideal for the VANET. We describe a public blockchain RPCA that records the trustworthiness of nodes and messages in such a distributed ledger suitable for secure message distribution. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. Creator An entity primarily responsible for making the resource Lamani M.R.; Benadit P.J.; Vaithinathan K.; Parthiban L. Source A related resource from which the described resource is derived EAI/Springer Innovations in Communication and Computing, Vol-Part F1496, pp. 253-264. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH 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/10.1007/978-3-031-35751-0_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-35751-0_18</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174850567&doi=10.1007%2F978-3-031-35751-0_18&partnerID=40&md5=ea58943d2df932868f15d9fcc10e1cde" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174850567&doi=10.1007%2f978-3-031-35751-0_18&partnerID=40&md5=ea58943d2df932868f15d9fcc10e1cde</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 25228595 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 Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lamani M.R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bangalore, India; Benadit P.J., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bangalore, India; Vaithinathan K., Department of Computer Engineering, Karaikal Polytechnic College, Puducherry, Karaikal, India; Parthiban L., Department of Computer Science, Pondicherry University, Tamil Nadu, Pondicherry, 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 An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation Subject The topic of the resource Analogue sorting; capacitor voltage balancing; modular multilevel converters (MMCs); space vector pulsewidth modulation (SVPWM) Description An account of the resource Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE. Creator An entity primarily responsible for making the resource Muthavarapu A.K.; Biswas J.; Barai M. Source A related resource from which the described resource is derived IEEE Transactions on Power Electronics, Vol-37, No. 8, pp. 9254-9265. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TPEL.2022.3160665" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TPEL.2022.3160665</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126708135&doi=10.1109%2FTPEL.2022.3160665&partnerID=40&md5=78bd2b363c7cbfe0d01827bcc9f6e2ce" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126708135&doi=10.1109%2fTPEL.2022.3160665&partnerID=40&md5=78bd2b363c7cbfe0d01827bcc9f6e2ce</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 8858993; CODEN: ITPEE 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 Muthavarapu A.K., Aditya Engineering College (A), Electrical and Electronics Engineering Department, Surampalem, 533437, India; Biswas J., Christ University, Department of Computer Science, Bengaluru, 560029, India; Barai M., National Institute of Technology, Department of Electrical Engineering, Kozhikode, Calicut, 673601, India