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 Saini, Madan Lal; Satish, Aravapalli Rama; Rao, Telu Venkata Madhusudhana; Mandala, Jyothi; Das, Smritilekha; Rajan, Cristin Title A name given to the resource A novel multigrade classification in FL using brain MRI images based on FHAT_EfficientNet 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 Ad Hoc and Ubiquitous Computing;Volume;49;Issue;4;pp.251-269 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1504/IJAHUC.2025.147753" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJAHUC.2025.147753</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105012360811?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105012360811?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 Saini M.L., Department of Computer Science and Engineering, Chandigarh University, Gharuan, Punjab, Mohali, 140055, India; Satish A.R., School of Computer Science and Engineering, VIT-AP University, Andhra Pradesh, India; Rao T.V.M., Department of AI&amp;DS, Vignans Institute of Information Technology, Visakhapatnam, 530049, India; Mandala J., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India; Das S., Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India; Rajan C., Department of Computer Science and Engineering, GMR Institute of Technology, Andhra Pradesh, Rajam, 532127, India Description An account of the resource This paper establishes the fractional harmony artificial tree (FHAT)_EfficientNet for multi-grade classification in federated learning (FL). Here, the established FHAT is attained by the integration of the fractional calculus (FC) and harmony search-based feedback artificial tree (HSFAT) algorithm, and the HSFAT is developed by the combination of harmony search (HS) and feedback artificial tree (FAT). Initially, the input MRI image is taken from a particular dataset and subjected to pre-processing. Thereafter, tumour segmentation is accomplished based on fuzzy local information c-means (FLICM). Later, image augmentation and feature extraction are performed. Finally, the multi-grade classification is carried out using EfficientNet fine-tuned based on the proposed FHAT. Moreover, the established FHAT_EfficientNet attained better accuracy, specificity, sensitivity, mean squared error (MSE), root mean square error (RMSE), and loss function of 0.917, 0.936, 0.966, 0.058, 0.241, and 0.083. Copyright 2025 Inderscience Enterprises Ltd. Subject The topic of the resource EfficientNet; federated learning; FHAT; FLICM; fractional calculus; fractional harmony artificial tree; fuzzy local information c-means Publisher An entity responsible for making the resource available Inderscience Publishers Relation A related resource ISSN: 17438225; 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