165 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 Srinivasiah, Raghavendra; Jankatti, Santosh Kumar; Lamani, Manjunath Ramanna; Jinachandra, Niranjana Shravanabelagola Title A name given to the resource Change detection and classification of satellite images using convolutional neural network 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 IAES International Journal of Artificial Intelligence;Volume;15;Issue;1;pp.329-337 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijai.v15.i1.pp329-337" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijai.v15.i1.pp329-337</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105031521090?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031521090?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 Srinivasiah R., Machine Learning and Data Science, School of Engineering and Technology, CHRIST University, Bangalore, India; Jankatti S.K., Department of Computer Science and Technology, School of Engineering, Dayananda Sagar University, Bangalore, India; Lamani M.R., Department of Computer Science and Engineering, Moodlakatte Institute of Technology, Kundapura, India; Jinachandra N.S., Department of Mechanical Engineering, School of Engineering and Technology, CHRIST University, Bangalore, India Description An account of the resource Satellite and airborne imagery, collectively known as earth observation imagery, are images of the earth collected from spaceborne or airborne platforms such as satellites and aircraft. Over the last 100 years, with the fast development of aviation, space exploration, and imaging technologies, the coming together of these technologies has been inevitable. Earth observation imagery has many applications in regional planning, geology, reconnaissance, fishing, meteorology, oceanography, agriculture, biodiversity conservation, forestry, landscape, intelligence, cartography, education, and warfare. With the rise in the number of these airborne and spaceborne imaging platforms being deployed by government and private entities alike, the capability to sift through and analyze vast amounts of data generated by these platforms is the need of the hour. With the exponential improvement in the computational capabilities of computers over the last half a century, analysts are exceedingly moving towards the practice of artificial intelligence, machine learning (ML), and computer vision solutions to automate a large part of the processes employed in analyzing earth observation imagery. This work recommends a workflow to perceive and classify changes in earth observation imagery of a given area by utilizing the vast flexibility that convolutional neural networks (CNN) provide. This is an open access article under the CC BY-SA license. https://creativecommons.org/licenses/by-sa/4.0/. Subject The topic of the resource Artificial intelligence; Computer vision; Convolutional neural network; Machine learning; Satellite image Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20894872; 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 Lingaraju, Anoop Ganadalu; Shankaregowda, Asha Mangala; Sathiyamurthy, Babu Kumar; Channegowda, Santhrupth Budanoor; Jalapur, Shruti; Chennakeshava, Chaitra Palahalli Title A name given to the resource Optimizing citrus disease detection: a transferable convolutional neural network model enhanced with the fruitfly optimization algorithm 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 IAES International Journal of Artificial Intelligence;Volume;14;Issue;4;pp.3201-3213 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijai.v14.i4.pp3201-3213" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijai.v14.i4.pp3201-3213</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014374362?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014374362?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 Lingaraju A.G., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India; Shankaregowda A.M., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India; Sathiyamurthy B.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India; Channegowda S.B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India; Jalapur S., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India; Chennakeshava C.P., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, India Description An account of the resource Fungal, bacterial, and viral diseases significantly threaten citrus production and quality worldwide, prompting producers to explore technological solutions to mitigate the financial impact of these diseases. Image analysis techniques have emerged as powerful tools for detecting citrus diseases by differentiating between healthy and diseased specimens through the extraction of discriminative features from input images. This paper introduces a valuable dataset comprising 953 color images of orange leaves from the species Citrus sinensis (L.) Osbeck, which serves to train, evaluate, and compare various algorithms aimed at identifying abnormalities in citrus fruits. The development of automated detection systems is crucial for reducing economic losses in citrus production, with this research focusing on twelve specific diseases and nutrient deficiencies. We propose a novel approach to citrus plant disease detection utilizing a hyper-parameter tuned transferrable convolutional neural network (TCNN) model, referred to as the enhanced fruitfly optimization algorithm (EFOA)-TCNN model. This model optimizes the parameters of TCNN using the EFOA and enhances architectural design by incorporating three convolutional layers alongside an energy layer instead of a traditional pooling layer. Experimental results demonstrate that the proposed EFOA-TCNN model outperforms existing state-of-the-art methods, achieving a sensitivity of 0.975 and an accuracy of 0.995. 2025, Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Bacteria; Citrus fruit disease detection; Enhanced fruitfly optimization algorithm; Image analysis; Transferrable convolutional neural network Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20894872; 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 Govinda, Sangeetha; Vincent, Agnes Nalini; Babu, Merwa Ramesh Title A name given to the resource Novel artificial intelligence-based ensemble learning for optimized software quality 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 IAES International Journal of Artificial Intelligence;Volume;14;Issue;3;pp.1820-1828 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijai.v14.i3.pp1820-1828" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijai.v14.i3.pp1820-1828</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008100220?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008100220?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 Govinda S., Department of Computer Science, Christ University, Bangalore, India; Vincent A.N., Faculty of Information Technology, AMITY Institute of Higher Education, Quatre Bornes, Mauritius; Babu M.R., Department of Computer Science, Bharathiar University, Coimbatore, India Description An account of the resource Artificial intelligence (AI) contributes towards improving software engineering quality; however, existing AI models are witnessed to deploy learning-based approaches without addressing various complexities associated with datasets. A literature review showcases an unequilbrium between addressing the accuracy and computational burden. Therefore, the proposed manuscript presents a novel AI-based ensemble learning model that is capable of performing an effective prediction of software quality. The presented scheme adopts correlation-based and multicollinearity-based attributes to select essential feature selection. At the same time, the scheme also introduces a hybrid learning approach integrated with a bio-inspired algorithm for constructing the ensemble learning scheme. The quantified outcome of the proposed study showcases 65% minimized defect density, 94% minimized mean time to failure, 62% minimized processing time of the algorithm, and 43% enhanced predictive accuracy. 2025, Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Accuracy; Artificial intelligence; Defect density; Software engineering; Software quality Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20894872; 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 Govinda, Sangeetha; Prasanthi, B.G.; Vincent, Agnes Nalini Title A name given to the resource Novel preemptive intelligent artificial intelligence-model for detecting inconsistency during software testing 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 IAES International Journal of Artificial Intelligence;Volume;14;Issue;3;pp.1781-1789 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijai.v14.i3.pp1781-1789" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijai.v14.i3.pp1781-1789</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008110548?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008110548?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 Govinda S., Department of Computer Science, Christ University, Bangalore Central Campus, Bangaluru, India; Prasanthi B.G., Department of Computer Science and Applications, St. Josephs University, Bangaluru, India; Vincent A.N., Faculty of Information Technology, AMITY Institute of Higher Education, Quatre Bornes, Mauritius Description An account of the resource The contribution of artificial intelligence (AI)-based modelling is highly significant in automating the software testing process; thereby enhancing the cost, resources, and productivity while performing testing. Review of existing AI-models towards software testing showcases yet an open-scope for further improvement as yet the conventional AI-model suffers from various challenges especially in perspective of test case generation. Therefore, the proposed scheme presents a novel preemptive intelligent computational framework that harnesses a unique ensembled AI-model for generating and executing highly precise and optimized test-cases resulting in an outcome of adversary or inconsistencies associated with test cases. The ensembled AI-model uses both unsupervised and supervised learning approaches on publicly available outlier dataset. The benchmarked outcome exhibits supervised learning-based AI-model to offer 21% of reduced error and 1.6% of reduced processing time in contrast to unsupervised scheme while performing software testing. 2025, Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Artificial intelligence; Automation; Error; Inconsistency; Software testing Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20894872; 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 Maju, Sonam Vayaliparambil; Siryapushpam, Gnana Prakasi Oliver Title A name given to the resource ApDeC: A rule generator for Alzheimer's disease prediction 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 IAES International Journal of Artificial Intelligence;Volume;14;Issue;3;pp.1772-1780 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijai.v14.i3.pp1772-1780" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijai.v14.i3.pp1772-1780</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008092478?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008092478?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 Maju S.V., Department of Computer Science and Engineering, Christ University, Bangalore, India, School of Computer Science and Engineering, RV University, Bangalore, India; Siryapushpam G.P.O., Department of Computer Science and Engineering, Christ University, Bangalore, India Description An account of the resource Artificial intelligence (AI) paved the way and helping hand for the medical practitioners in various aspects and early disease prediction is one among many. Interdisciplinary research studies on the early prediction of diseases are often analyzed based on the accuracy of the prediction model. But how early these diseases can be predicted will not be answered in many of the research studies unless they have a time series data. This work proposes a machine learning model, ApDeC which solves the above-mentioned problem by generating association rules for the early disease prediction of Alzheimer patients. The ApDeC model calculates the probability of occurrence of eleven Alzheimer disease prediction risk factors and identifies the combination of diseases that can lead to Alzheimer disease. The association rules will be generated by considering the observed combination of risk factors. The research introduces an innovative approach that helps in the early prediction of Alzheimer disease from the risk factors/symptoms. The results show the strong correlation of diabetes and blood pressure with Alzheimer disease. 2025, Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Alzheimers disease; Apriori algorithm; Artificial intelligence; Association rules; Machine learning Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20894872; 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 Ahmad, Akram; Singh, Vaishali; Upreti, Kamal Title A name given to the resource AI-driven emotion recognition systems for sustainable mental health care: an engineering perspective 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 Advances in Applied Sciences;Volume;14;Issue;4;pp.1111-1117 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijaas.v14.i4.pp1111-1117" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijaas.v14.i4.pp1111-1117</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105026990261?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105026990261?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 Ahmad A., Maharishi University of Information Technology, Lucknow, India; Singh V., Maharishi University of Information Technology, Lucknow, India; Upreti K., CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India Description An account of the resource Emotion recognition systems are transforming human-computer interaction (HCI) applications by enabling AI-driven, adaptive, and responsive mental health interventions. This study explores AI-based emotion recognition technologies using facial expressions, voice analysis, text-based sentiment processing, and physiological signals to develop scalable, real-time mental health support systems. Utilizing datasets such as FER2013, JAFFE, and CK+, our research examines deep learning models, including EfficientNet-XGBoost, which achieved over 90% accuracy across key evaluation metrics. Unlike traditional mental health interventions, AI-driven systems provide cost-effective, accessible, and sustainable solutions through telemedicine, wearable biosensors, and virtual counselors. The study also highlights critical challenges such as algorithmic bias, ethical AI compliance, and the energy consumption of deep learning models. By integrating machine learning, cloud-based deployment, and edge computing, this research contributes to the development of sustainable, ethical, and user-centric AI solutions for mental health care. Future directions include AI model optimization for energy-efficient deployments and the creation of diverse, inclusive datasets to improve performance across global populations. 2025, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Environmental awareness; Human-computer interaction; Machine learning; Mental illness; Predictive modeling; Sustainable engineering Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 22528814; 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 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 Pasha, Fairoz; Natarajan, Jayapandian Title A name given to the resource Multi objective energy aware integrated cloud scheduling with a consensus-based security 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 Bulletin of Electrical Engineering and Informatics;Volume;15;Issue;2;pp.1313-1323 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/eei.v15i2.9885" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/eei.v15i2.9885</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105036280214?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105036280214?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 Pasha F., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Kengeri Campus, Bangalore, India, Department of Computer Science Engineering, School of Technology, Maulana Azad National Urdu University Polytechnic, Bangalore, India; Natarajan J., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Kengeri Campus, Bangalore, India Description An account of the resource This research presents a multi-objective, energy-aware workflow scheduling framework for heterogeneous cloudedge environments that addresses both efficiency and data integrity challenges. Conventional encryption-based security mechanisms, although effective in protecting data during task offloading, often introduce significant computational and communication overhead, leading to degraded system performance. To overcome this limitation, this work proposes the consensus security-integrity and quality-aware workflow scheduler (CSIQA-WS), which integrates energy-aware scheduling with a lightweight, consensus-driven security mechanism. The model incorporates automatic service management and an attack prevention module to detect and mitigate malicious behavior during inter-node data transmission while maintaining quality of service (QoS) constraints. A dynamic coordination between edge and cloud resources enables efficient workload distribution and robust resource utilization. Experimental evaluation using scientific workflow benchmarks demonstrates that CSIQA-WS significantly reduces processing time and energy consumption compared to existing approaches. The proposed model achieves up to 92.29% reduction in processing time and consistently improves overall QoS while preserving data integrity in dynamic execution environments. These results indicate that CSIQA-WS provides an effective and scalable solution for secure and energy-efficient workflow scheduling in modern cloudedge systems. 2026 Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Cloud computing; Consensus-based security; Dynamic scheduling; Multi-objective; Workflow Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20893191; 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 Umamaheswari; Kannan; Rozario, Juliet; Manimekala Title A name given to the resource Exploration of digital image tampering detection using CNN with modified particle swarm optimization in deep learning 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 Bulletin of Electrical Engineering and Informatics;Volume;14;Issue;3;pp.1981-1989 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/eei.v14i3.9400" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/eei.v14i3.9400</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105005260385?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105005260385?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 Umamaheswari, Department of Computer Science, Christ University, Bangalore, India; Kannan, Department of Computer Science, Christ University, Bangalore, India; Rozario J., Department of Computer Science, Christ University, Bangalore, India; Manimekala, Department of Computer Science, Christ University, Bangalore, India Description An account of the resource The field of image processing is crucial for many different applications, including forensic evidence, insurance claims, medical imaging, bio-informatics, artifact collection and more. In many sectors nowadays, digital photographs are regarded as a trustworthy source of information. The manipulation of such photographs leads to a variety of issues. The study presents a method using convolutional neural networks (CNN) combined with modified particle swarm optimization (MPSO) to improve the accuracy of tampering detection. This advancement contributes to improved reliability in fields requiring image authenticity verification, such as forensics and media. The design includes the collection of a dataset comprising both original and tampered images for training and testing the model. A dataset, such as the Media Integration and Communication Center (MICC) dataset, is utilized, which includes various images that have been altered through different tampering techniques. This dataset serves as the foundation for training the CNN and evaluating its performance The findings indicate that the proposed MPSO_CNN method outperforms traditional techniques in terms of precision, accuracy, recall, and F-measure, demonstrating its effectiveness in identifying tampered images. The results highlight the significance of using advanced deep learning techniques for reliable image authenticity verification. 2025, Institute of Advanced Engineering and Science. All rights reserved. Subject The topic of the resource Convolutional neural networks; Deep learning; Ensemble learning; Image tampering; Particle swarm optimization Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Relation A related resource ISSN: 20893191; 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 Mathew, Jemy Jose; Thomas, Kennedy Andrew Title A name given to the resource Ethnographic research on primary education of tribals: a scoping review 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 Journal of Education and Learning;Volume;20;Issue;2;pp.1032-1042 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v20i2.23687" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v20i2.23687</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034323963?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034323963?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 Mathew J.J., Department of Education, CHRIST (Deemed to be University), Bengaluru, India; Thomas K.A., Department of Education, CHRIST (Deemed to be University), Bengaluru, India Description An account of the resource Ethnographic research offers comprehensive learning outcomes by examining the socio-emotional, economic and cultural components crucial for comprehending marginalized groups experiences. This study aims to examine the methodologies used in studies and the gaps in the literature on the primary education of tribal communities, highlighting the limitations of the current research approaches. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) of Arksey and OMalleys six-step framework, the scoping review has considered 19 studies of 406 research articles published from 2015 to 2024 across the databases Scopus, JSTOR, and ERIC. The review highlights that most of these studies used descriptive survey design, mixed-method research design, and ethnographic research design. While the first two document barriers, the ethnographic studies provide richer cultural in-depth also. However, gaps in the literature include a lack of interventions for specific tribes, such as the Mannan community in Kerala, India, and the integration of indigenous knowledge, which is only possible through cultural inclusiveness. The findings suggest that future research should prioritize interdisciplinary collaboration and teacher training in multilingual education (MLE) through ethnographic methods for developing culturally sensitive interventions. These recommendations aim to contribute to developing more culturally inclusive educational practices and policies in the primary education curricula. 2026, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Cultural inclusiveness; Ethnography; Indigenous people; Multilingual education; Primary education Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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; Hybrid 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 Prakasha, G.S.; Grundmeyer, Trent; Arulnesan, Sivaselwam; Thirumalesha, S.; Gururaja, C.S. Title A name given to the resource K-12 schools campus, food service, and transportation directors COVID-19 and current 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 Journal of Education and Learning;Volume;20;Issue;2;pp.1043-1055 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v20i2.23359" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v20i2.23359</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034357334?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034357334?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 Prakasha G.S., School of Education, Christ University, Bengaluru, India; Grundmeyer T., School of Education, Buena Vista University, Storm Lake, United States; Arulnesan S., School of Education, Christ University, Bengaluru, India; Thirumalesha S., Department of Education, Mount Carmel College, Bengaluru, India; Gururaja C.S., Department of Education, Central University of Kashmir, Srinagar, India Description An account of the resource This study examines the COVID-19 experiences of K-12 school campus directors, especially in terms of building and grounds, transportation, and food services from the Midwestern United States. The COVID-19 pandemic has changed to online education mode and implemented safety protocols to ensure equitable access to K-12 education. School directors play a crucial role in United Statess school administration. The researchers used a mixed method research design and purposive sampling. The sample included 9 school-grounds directors, 34 food service directors, and 31 transportation directors. A 5-point Likert-type questionnaire was prepared by the researchers to collect the relevant data for the study. The data were analyzed using descriptive statistics and thematic analysis. While revealing their experiences, various school directors mentioned that key challenges are reliable sources of information for them to work, inequities in resource allocation, finance allocation, and lack of professional training. The survey highlighted the need for several resources, including federal and state funding, teacher professional development programs, and community partnerships that support K-12 education. School directors addressed challenges regarding transportation, buildings, grounds, and food services during COVID-19. The study revealed the need for systemic policy changes and communication resources to create resilient and adaptive learning environments for K-12 education. Eventually, the study recommended that policymakers and educational leaders bring changes to K-12 infrastructure to withstand crises like COVID-19. 2026, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Barriers and resources; K-12 education; Midwestern United States; School directors; School superintendents Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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; Hybrid 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 Chakyarkandiyil, Nisha; Prakasha, G.S. Title A name given to the resource Impact of online cooperative learning strategies on self-directed learning among pre-service teachers 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 Education and Learning;Volume;19;Issue;4;pp.1914-1921 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v19i4.23496" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v19i4.23496</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013503054?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013503054?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 Chakyarkandiyil N., School of Education, Christ University, Bangalore, India; Prakasha G.S., School of Education, Christ University, Bangalore, India Description An account of the resource Self-directed learning (SDL) often drives learners to engage with what they want to learn. Thus, investigating teaching-learning strategies that drive SDL gains importance in this technology-driven era. The present study investigates the impact of online cooperative learning (OCL) strategies on SDL skills among pre-service teachers (PST). The study engaged 130 PSTs using a quasi-experimental non-equivalent control group design with a pretest and posttest. The study divided PST into a control group and an experimental group. The experimental group underwent OCL strategy, and the control group had a traditional online lecture method. The researchers measured the SDL of PST using the SDL scale. The paired sample t-test results indicated a significant enhancement in SDL skills among the experimental group compared to the control group. The findings underscore the importance of integrating cooperative learning (CL) strategies in online instruction to foster SDL ability among learners. Further studies may create user-friendly features in video-conferencing platforms that provide more opportunities to engage students with CL pedagogies. 2025, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Blended learning; Collaborative learning; Life-long learning; Online learning; Pre-service teachers; Self-directed learning Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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 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 Prakasha, G.S.; Grundmeyer, Trent; Arulnesan, Sivaselvam; Bahubali, G.P.; Sangtam, Yolila Title A name given to the resource Teachers professional development on student achievement: perceptions of district superintendents of schools in USA 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 Education and Learning;Volume;19;Issue;4;pp.1795-1804 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v19i4.23295" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v19i4.23295</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013489710?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013489710?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 Prakasha G.S., School of Education, Christ University, Bangalore, 560029, India; Grundmeyer T., School of Education, Educational Leadership, Buena Vista University, Storm Lake, United States; Arulnesan S., Department of Education, The Open University of Sri Lanka, Colombo, Sri Lanka; Bahubali G.P., Faculty of Education, University College of Education, Bangalore University, Bangalore, India; Sangtam Y., Department of Teacher Education, Nagaland University, Zunheboto, India Description An account of the resource The perceptions of school superintendents on planning and designing of school teachers professional development programmes (PDP) place a crucial role in inservice teacher development. The present study aimed to examine the school superintendents perceptions towards professional development of teachers based on students academic achievement. The study employed quantitative descriptive research design which included descriptive and inferential statistics to interpret the superintendents perceptions on teachers professional development plan. The researchers utilized quntitiatve surveys to gather data from 128 public school superintendents and captured their perceptions on Teachers PDPs. Findings reported that superintendents perceived PDPs must integrate knowledge on student achievemet, skills needed, and worthwhile-content mastery. Study further revealed that, students academic achievement details can provide accurate components to be included in teachers PDP. Future researchers may explore the evidence-based planning of PDPs to motivate the teachers active participation in professional growth activities. 2025, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource District superintendent; Education officer; Inservice teacher training; Professional development; Student achievement Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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; Hybrid 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 Sahani, Chatterjee; Prakasha, G.S. Title A name given to the resource Museum visit as an academic engagement activity: teachers perspective 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 Education and Learning;Volume;19;Issue;3;pp.1583-1589 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v19i3.22686" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v19i3.22686</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105006987761?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105006987761?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 Sahani C., School of Education, Christ University, Bangalore, India; Prakasha G.S., School of Education, Christ University, Bangalore, India Description An account of the resource The educational value of museums are immense as they are the storehouse of artifacts depicting history, culture, and science. Teachers must tap this resource to provide students the experiential learning. Bangalore is one of the metropolitan cities of India, hosting variety of museums where artifacts related to various school subjects such as history, geography, science, art, culture, technology, and music are found. Therefore, the present study aims to find out the teachers' perspective on museum visits as an academic engagement activity and a resource for experiential learning. The study employed a descriptive survey design to understand school teachers' perspectives on museum visits in Bangalore. A convenient sampling method yielded 200 complete responses from school teachers. The study revealed that despite knowing about the field trip to museum as a source of learning, teachers revealed several constraints in organization and implementation of such visits. Having understood teachers perspective, study suggests future research may delve into students' learning engagement on a field trip. 2025, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Bangalore city; Descriptive survey; Fieldtrip; Museum visit; Teachers perspective Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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; Hybrid 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 Suja, V.J.; Mathai, Sebastian; Prakasha, G.S. Title A name given to the resource Vocational training for women empowerment: Saint Kuriakose Elias Chavaras vision 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 Education and Learning;Volume;19;Issue;3;pp.1317-1329 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/edulearn.v19i3.22092" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/edulearn.v19i3.22092</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007035382?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007035382?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 Suja V.J., Department of International Studies, Political Science and History, Christ University, Bangalore, India; Mathai S., Department of International Studies, Political Science and History, Christ University, Bangalore, India; Prakasha G.S., School of Education, Christ University, Bangalore, India Description An account of the resource The present study attempted to describe the initiatives of Saint (St.) Kuriakose Elias Chavara on vocational training and womens empowerment. The study narrated the present condition of one of his vocational training initiatives known as rosary-making, which is in vogue at Koonammavu Village in Kerala state, India. The study employed a multi-method research design approach to carry out the present study. It included historical, qualitative, and quantitative methods in sequence. In the historical method, the study employed document analysis of primary and secondary sources. As a part of the qualitative method, the study conducted a semi-structured interview with 10 rosary-making entrepreneurs in Koonammavu. As a part of the quantitative method, the study administered a questionnaire to 100 families who are actively involved in the rosary-making business. Document analysis revealed that St. Chavaras initiative on rosary-making vocational training for nuns was a contribution to womens empowerment. Narrative thematic analysis revealed 5 main themes and 10 subthemes in Chavaras contribution. Quantitative data revealed that rosary-making emerged as a livelihood, business, and source of income for many families. The study recommends future researchers focus on all the initiatives of St. Chavara in the realm of vocational training and womens empowerment. 2025, Intelektual Pustaka Media Utama. All rights reserved. Subject The topic of the resource Koonammavu; Rosary making; Saint Chavara; Vocational training; Women empowerment Publisher An entity responsible for making the resource available Intelektual Pustaka Media Utama Relation A related resource ISSN: 20899823; 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; Hybrid 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 Ali, K. M. D. Riyaz; Memala, W. Abitha; Amutha, W. Margaret Title A name given to the resource Hybrid Renewable Source Powered Dual Input Single Output Converter With High Voltage Gain for Rural Healthcare Facilities 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 Electrical and Computer Engineering;Volume;2025;Issue;1;Article No.;8855158; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1155/jece/8855158" target="_blank" rel="noreferrer noopener">https://doi.org/10.1155/jece/8855158</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021859625?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021859625?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 Ali K.M.D.R., Department of Electrical and Electronics Engineering, Sathyabama Institute of Science and Technology (Deemed to be University), Tamil Nadu, Chennai, India; Memala W.A., Department of Electrical and Electronics Engineering, Sathyabama Institute of Science and Technology (Deemed to be University), Tamil Nadu, Chennai, India; Amutha W.M., Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Deemed to be University, Ramapuram Campus, Ramapuram, Tamil Nadu, India Description An account of the resource Rural dwellers need a well-equipped healthcare service for a decent life. Most of the rural areas located in southern parts of India away from the grid connection thereby lack in electricity. Unreliable electric power leads to the limited access or inaccessibility of most essential medical equipment in the clinic. The deficiency has also reduced rural healthcare centers ethics criteria. This research work finds all the available resources in the rural healthcare clinic and proposes hybrid solar PV source and supercapacitor-based approaches to make sure of reliable energy access and uninterrupted power supply. Any healthcare facilities include an emergency room, waiting hall, nursing room, consulting room, delivery room, male and female room, and a testing lab. It may take a daily average energy consumption of 16 kWh with 3 kW peak demand. In the input side, solar PV system with an H-type clamped capacitorbased boost converter is proposed for the reduction of input current ripples and power switch conduction losses. At the load side, a capacitor with a switch (switched capacitor) is considered to reduce voltage stress of the components present in the topology and to attain high gain. This research work adopts interleaved structure-based capacitors for current ripple reduction, and the series structure is considered to attain high gain. The proposed novel converter takes the input voltage of 40 V and produces the output voltage of 280 V. The DC link output is then connected with the voltage source inverter (VSI) to get a desired output. The proposed novel converter is employed to run a 3? induction motor for the AC load with the rating of 400 V, 15 A AC power. MATLAB R2015a software is preferred for the simulation analysis. Copyright 2025 K. M. D. Riyaz Ali et al. Journal of Electrical and Computer Engineering published by John Wiley &amp; Sons Ltd. Subject The topic of the resource clamped capacitor converter; energy management; hybrid solar PV-supercapacitor; interleaved switched capacitor two-way converter; MATLAB/Simulink; rural health care center; voltage source inverter Publisher An entity responsible for making the resource available John Wiley and Sons Ltd Relation A related resource ISSN: 20900147; 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 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 Perumal, Vivek Karthick; Jayabalan, Ramesh; Paul, Eldho; Selvaraj, Dhanasekaran Title A name given to the resource VLSI Implementation of High-Speed and Area-Efficient Multiplierless Address Generation Architecture for Deinterleaver in WiMAX Applications 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 Electrical and Computer Engineering;Volume;2025;Issue;1;Article No.;2638291; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1155/jece/2638291" target="_blank" rel="noreferrer noopener">https://doi.org/10.1155/jece/2638291</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019803776?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019803776?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 Perumal V.K., Department of Electronics and Communication Engineering, Sona College of Technology, Salem, India; Jayabalan R., Department of Electronics and Communication Engineering, PSG College of Technology, Coimbatore, India; Paul E., Department of Electronics and Communication Engineering, School of Engineering and Technology, Christ University, Bangalore, India; Selvaraj D., Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, India Description An account of the resource This paper presents a VLSI implementation of a high-speed, area-efficient, multiplierless address generation architecture for the WiMAX deinterleaver, conforming to the IEEE 802.16e standard. The primary motivation of this work is to reduce hardware complexity and delay by eliminating multipliers, which are traditionally used in address generation. The proposed architecture is designed for FPGA and ASIC platforms, emphasizing simplicity, reduced latency, and efficient hardware utilization. The design supports standard modulation schemesQPSK, 16-QAM, and 64-QAMwith their respective code rates. Two key performance evaluations were conducted: Score 1, which refers to FPGA implementation on the Xilinx XC3S400, demonstrated a 13% increase in speed, and Score 2, based on ASIC analysis using 45-nm CMOS technology, and achieved improvements of 17% in power delay product (PDP) and 22% in area delay product (ADP) over existing architectures. These results confirm the architectures effectiveness for high-speed, low-power applications in modern communication systems. Copyright 2025 Vivek Karthick Perumal et al. Journal of Electrical and Computer Engineering published by John Wiley &amp; Sons Ltd. Subject The topic of the resource address generator; deinterleaver; FPGA; VLSI; WiMAX Publisher An entity responsible for making the resource available John Wiley and Sons Ltd Relation A related resource ISSN: 20900147; 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 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 Praghash, K.; Peter, Geno; Ananth, Christo; Supriya, M.; Stonier, Albert Alexander; Lawrence, Thomas Samraj Title A name given to the resource Optimizing Resource Allocation in Smart Healthcare Edge Networks Using Federated Swarm Intelligence and Artificial Neural Networks 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 International Journal of Distributed Sensor Networks;Volume;2026;Issue;1;Article No.;8463941; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1155/dsn/8463941" target="_blank" rel="noreferrer noopener">https://doi.org/10.1155/dsn/8463941</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105039690553?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105039690553?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 Praghash K., Department of Electronics and Communications Engineering, Christ University, Bengaluru, India; Peter G., Centre for Research of Innovation and Sustainable Development (CRISD), School of Engineering and Technology, University of Technology Sarawak, Sibu, Malaysia; Ananth C., Faculty of Artificial Intelligence and Digital Technologies, Samarkand State University, Samarkand, Uzbekistan; Supriya M., Department of Computer Science Engineering, Stella Mary?s College of Engineering, Nagercoil, India; Stonier A.A., School of Electrical Engineering, Vellore Institute of Technology, Vellore, India; Lawrence T.S., Department of Information Technology, School of Engineering and Technology, Dambi Dollo University, Dambi Dollo, Ethiopia Description An account of the resource Smart healthcare edge networks should be able to serve two purposes at once: to train federated machine learning models across a range of devices without violating patient privacy and to schedule other activities with latency constraints, like real-time patient events. Such methods as FFL-ANN attempt this by using fixed fuzzy rules, which do not work in the situation where the conditions of the network change in an unforeseen manner. In this paper, the framework FSI-ANN is introduced to combine particle swarm optimization to quality-aware model aggregation with ant colony optimization to adaptive real-time task scheduling and ANN-based predictions into a single framework. We experimented with FSI-ANN on 200 edge devices. It achieved 0.825 precision compared with 0.82 with FedAvg and 0.80 with FFL-ANN and reduced inference latency by 18%, 0.370.45 s. Throughput was maintained at 33 tasks/sec as compared with 27 of FedAvg. At burst load, the miss rate of the critical deadline was decreased by 90.2 percent and the energy consumed was decreased by 14.8% per round. The results suggest that adaptive learning using swarm is superior to the fixed rule-based approaches and simple averaging in the distribution of resources at the sustainable healthcare advantage. Copyright 2026 K. Praghash et al. International Journal of Distributed Sensor Networks published by John Wiley &amp; Sons Ltd. Subject The topic of the resource edge computing; federated learning; resource allocation; smart healthcare; sustainable healthcare; swarm intelligence Publisher An entity responsible for making the resource available John Wiley and Sons Ltd Relation A related resource ISSN: 15501329; 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 Farale, Harish; Sreevidhya, K.B.; Manuel, Manju; Kanchi, Suvardhan Title A name given to the resource Multivariate optimization of electrochemical sensing parameters for bisphenol a detection using an AgNPs/g-C3N4/IL@GCE via box-behnken design 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 Journal of the Electrochemical Society;Volume;173;Issue;4;Article No.;47504; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1149/1945-7111/ae42f5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1149/1945-7111/ae42f5</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105033901792?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105033901792?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 Farale H., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560029, India; Sreevidhya K.B., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560029, India; Manuel M., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560029, India; Kanchi S., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560029, India Description An account of the resource We developed an electrochemical sensor for detecting BPA using AgNPs/g-C3N4/IL@GCE. Graphitic carbon nitride was synthesized by the calcination of melamine at 550 C. In contrast AgNPs were synthesized via a green tea extract method, and the nanocomposite was dropcast onto the GCE surface along with 1-butyl-3-methylimidazolium methyl sulfate (BMIM-MeSO4) ionic liquid as a binder. Morphology was characterized, and response surface methodology (RSM) using Box-Behnken Design (BBD) was used as a concurrent strategy to optimize pH, scan rate, and deposition time. Independent validation experiments conducted at multiple interior points within the design space showed good agreement between predicted and experimental responses, with prediction errors of 6.29%-10.11% for oxidation peak current and 1.63%-5.24% for oxidation potential. Applying the optimized conditions, the sensor linearized BPA detection over the concentration range of 1-10 ?M, with a limit of detection of 0.66 ?M, and a limit of quantification of 2.20 ?M. The sensor showed excellent recovery (99.16%-102.26%) of BPA present in real water samples. The improved electrocatalytic activity of the sensor interfaces was due to the synergistic effects of AgNPs and g-C3N4. The novelty of this research was the use of an RSM-BBD approach to systematically optimize a green synthesized AgNPs/g-C3N4 nanocomposite electrode, enabling predictive modelling to show reasonable electrochemical sensitivity towards BPA detection. 2026 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited. All rights. Publisher An entity responsible for making the resource available Institute of Physics Relation A related resource ISSN: 134651; CODEN: JESOA 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 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 Harilal, Calvin Carl; Uwaya, Gloria Ebube; Kanchi, Suvardhan; Bisetty, Krishna Title A name given to the resource Engineered MOF-199 Modified Electrodes for Enhanced Electrochemical Immunosensing of Lactoferrin via Signal Amplification 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 Electrochemical Society;Volume;172;Issue;12;Article No.;126503; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1149/1945-7111/ae2bac" target="_blank" rel="noreferrer noopener">https://doi.org/10.1149/1945-7111/ae2bac</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105033935861?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105033935861?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 Harilal C.C., Department of Chemistry, Faculty of Applied Sciences, Durban University of Technology, Durban, 4000, South Africa; Uwaya G.E., Department of Chemistry, Faculty of Applied Sciences, Durban University of Technology, Durban, 4000, South Africa; Kanchi S., Department of Chemistry, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560 029, India; Bisetty K., Department of Chemistry, Faculty of Applied Sciences, Durban University of Technology, Durban, 4000, South Africa Description An account of the resource The detection of lactoferrin (LF), an essential immunological and nutritional biomarker, demands highly sensitive analytical platforms for low-level detection. In this study, a label-free electrochemical immunosensing platform was constructed by immobilizing anti-lactoferrin antibodies (Anti-LF-Ab) on a multiwalled carbon nanotube and a metalorganic framework (MWCNT/MOF-199) nanocomposite-modified glassy carbon electrode (GCE). The synergy between MWCNTs and MOF-199 provided abundant active sites for antibody immobilization and enhanced electron transfer, yielding an eightfold current increase compared to bare GCE. Electrochemical analyses confirmed efficient charge transfer and stable antibody binding. Under optimized conditions, the immunosensor exhibited exceptional analytical performance with a low detection limit of 5.24 ng ml?1 and a quantification limit of 17.46 ng ml?1 across a wide detection range of 050 ng ml?1. The platform demonstrated strong analytical reliability, including excellent repeatability (RSD &lt; 5%), reproducibility and operational stability over multiple measurement cycles for LF detection in food diagnostics. In addition, Monte Carlo simulations confirmed the stability of the layer-by-layer assembly, supporting the robustness of the engineered sensing interface. 2025 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited. Subject The topic of the resource electrochemical immunosensor; lactoferrin; metal-organic frameworks Publisher An entity responsible for making the resource available Institute of Physics Relation A related resource ISSN: 134651; CODEN: JESOA 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; Hybrid 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 Gandhi, Mansi; Amreen, Kharunnisa; Varghese, Anitha Title A name given to the resource Phyto-Electrochemical Mapping of Indian Cappers: Redox Mediator Application on Mesoporous Carbon Based Electrodes 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 Electrochemical Society;Volume;172;Issue;12;Article No.;127503; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1149/1945-7111/ae2a75" target="_blank" rel="noreferrer noopener">https://doi.org/10.1149/1945-7111/ae2a75</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105030134155?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105030134155?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 Gandhi M., Department of Chemistry, Christ University, Bengaluru, 560029, India; Amreen K., St. Anns College for women-Mehdipatnam, Telangana, Hyderabad, 500028, India; Varghese A., Department of Chemistry, Christ University, Bengaluru, 560029, India Description An account of the resource Indian Cappers (IC), often known for its wide range of applications as a medicinal plant, is an essential spice with phenolic phytochemical attributes. These are plausibly electrochemically redox active in nature. The redox moiety of phytochemicals can be exploited as a green route electron-transfer mediator, rather than conventional chemical redox mediators. Herein, mesoporous carbon-assisted electrochemical redox mapping of a phytochemical using IC plant is reported. A well-defined redox peak for IC-redox with E0 = 0.2 V is observed with a surface excess (?) value of 44.8 109 mol cm?2. Physico-chemical characterization is carried out to provide a detailed analysis of IC redox-based constituents. Furthermore, the fabricated IC sensor is used for the electrocatalytic oxidation of Ascorbic acid (AA) as a model system for preparing electrochemical sensors. The prepared sensor gave a notable oxidation peak for AA at E?= 220 mV with a sensitivity value of 0.0385 ?A/?M in the range of 0?1000 ?M. This work is a preliminary experiment for on-site testing of ascorbic acid in blood serum samples as a point of care testing. Additionally, the Cappers showed appreciable antibacterial activity against both Gram-positive and Gram-negative strains, producing clear inhibition zones even without the use of antibiotics. 2025 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved. Publisher An entity responsible for making the resource available Institute of Physics Relation A related resource ISSN: 134651; CODEN: JESOA 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