630 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 Sarah, Preethi; Chellaswamy, Karthigai Prakasam Title A name given to the resource Entrepreneurial challenges of transgender entrepreneurs in India 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 Business and Globalisation;Volume;39;Issue;2;pp.266-278 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1504/IJBG.2025.143914" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJBG.2025.143914</a> <a href="https://www.scopus.com/pages/publications/85215668396?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85215668396?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 Sarah P., Department of Commerce, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India; Chellaswamy K.P., Department of Commerce, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India Description An account of the resource Social exclusion has impeded transgender individuals to enter mainstream society and curbing them to start a business venture. Sporadic transgender individuals have paved their way to start the business venture. This study aims to explore the entrepreneurial challenges faced by transgender entrepreneurs. Twenty transgender entrepreneurs who have relinquished begging and commercial sex work were interviewed. The grounded theory analysis has revealed six significant categories: financial resources, competitors, human resources, marketing issues, natural calamities, and transphobia. The participants expressed that transphobia, and financial resources were highly challenging to start a business venture. These findings extend our understanding of their challenges beyond the current knowledge of cisgender entrepreneurs. Finally, the limitation of the study is enunciated. Copyright 2025 Inderscience Enterprises Ltd. Subject The topic of the resource challenges; entrepreneurship; India; transgender; transgender entrepreneurs Publisher An entity responsible for making the resource available Inderscience Publishers Relation A related resource ISSN: 17533627; 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 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 Introduction, scope and significance of fermentation technology Subject The topic of the resource Fermentation; Fermenter design; Solid state fermentation; Submerged fermentation; World market Description An account of the resource Fermentation technology is a field which involves the use of microorganisms and enzymes for production of compounds that have applications in the energy, material, pharmaceutical, chemical and food industries. Though fermentation processes have been used for generations as a requirement for sustainable production of materials and energy, today it has become more demanding for continuous creations and advancement of novel fermentation processes. Efforts are directed both towards the advancement of cell factories and enzymes, as well as the designing of new processes, concepts, and technologies. The global market of microbial fermentation technology was valued at approximately USD 1,573.15 million in 2017 and which is expected to generate revenue of around USD 2,244.20 million by end of 2023. However, regular supply of materials, such as nutrients, microorganisms, the complex nature of production process, and high manufacturing cost hinder the market growth. 2019 Scrivener Publishing LLC. All rights reserved. Creator An entity primarily responsible for making the resource Saran S.; Malaviya A.; Chaubey A. Source A related resource from which the described resource is derived High Value Fermentation Products, Volume 1: Human Health, pp. 1-25. Publisher An entity responsible for making the resource available Scrivener Publishing LLC 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-s2.0-85133146128&partnerID=40&md5=736c1a90cec2e328f76e9cdf6a828e45" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133146128&partnerID=40&md5=736c1a90cec2e328f76e9cdf6a828e45</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-111946005-3; 978-111946001-5 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 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 Saran S., Fermentation Technology Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu Tawi, India; Malaviya A., Department of Life Sciences, CHRIST (Deemed To Be University), Hosur Road, Bengaluru, India; Chaubey A., Fermentation Technology Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu Tawi, 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 Modeling Consumer Price Index: A Machine Learning Approach Subject The topic of the resource artificial neural network; consumer price index; machine learning; mean absolute percentage error; particle swarm optimization Description An account of the resource The change in price of a group of goods and services is reflected in terms of consumer price index (CPI), making it one of the most important economic indicators. This is also the mostly used measure of inflation. Forecasted CPI values help the Government to take corrective measures to control the economic conditions of the country. This paper implements and examines two machine learning models such as artificial neural network (ANN) and ANN model optimized with particle swarm optimization (PSO) known as ANN-PSO to assess the accuracy in predictability of CPI. The data set for four groups such as food and beverages, housing, clothing, and footwear used for the calculation of all India CPI has been taken from the official website of the Government of India. The mean absolute percentage error (MAPE) has been used as the validator for model accuracy. The MAPE calculated for all experiments are less than 10% which indicates that the ANN-PSO models used are highly accurate for prediction of CPI of India. 2022 Wiley-VCH GmbH Creator An entity primarily responsible for making the resource Sarangi P.K.; Sahoo A.K.; Sinha S. Source A related resource from which the described resource is derived Macromolecular Symposia, Vol-401, No. 1 Publisher An entity responsible for making the resource available John Wiley and Sons 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/10.1002/masy.202100349" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/masy.202100349</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125152652&doi=10.1002%2Fmasy.202100349&partnerID=40&md5=5f4d28551421c3b064c3388be2441d61" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125152652&doi=10.1002%2fmasy.202100349&partnerID=40&md5=5f4d28551421c3b064c3388be2441d61</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 10221360; CODEN: MSYME 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 Sarangi P.K., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, 140401, India; Sahoo A.K., Graphic Era Hill University, Dehradun, 248002, India; Sinha S., Christ (Deemed to be University), Delhi, 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 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 Machine Learning Approach for the Prediction of Consumer Food Price Index Subject The topic of the resource ANN; CFPI; forecasting; MAPE Description An account of the resource The price of food and food related items are dynamic. A measure change in the price affects the buying behaviour of the consumer and monetary policies by the Government. The Consumer Food Price Index (CFPI) reflects the variations in food prices during a certain period. In India, the CFPI is released monthly by the Central Statistical Organization. It also reflects the inflation and helps the Government to take corrective measures in time. In this paper we have applied the machine learning approach in forecasting the consumer food price index in India. In specific, this work has focused on the applicability of Artificial Neural Network (ANN) models with back propagation learning in predicting the future values of CFPI. The monthly data for rural, urban and combined from the period 2013 to 2021 have been used to train and validate the models. The Mean Absolute Percentage Error (MAPE) values have been used to validate the accuracy of the models. The experimental results show that a simple ANN model with back propagation algorithm is highly capable in forecasting the future values of CFPI. 2021 IEEE. Creator An entity primarily responsible for making the resource Sarangi P.K.; Sinha D.; Sinha S.; Mittal N. Source A related resource from which the described resource is derived 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021 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 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRITO51393.2021.9596527" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO51393.2021.9596527</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125916788&doi=10.1109%2FICRITO51393.2021.9596527&partnerID=40&md5=e134879a1b111bb09c0783bdfba33866" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125916788&doi=10.1109%2fICRITO51393.2021.9596527&partnerID=40&md5=e134879a1b111bb09c0783bdfba33866</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166541703-7 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 Sarangi P.K., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Sinha D., CHRIST (Deemed to be University), India; Sinha S., CHRIST (Deemed to be University), India; Mittal N., Amity University, Noida, Uttar Pradesh, India https://archives.christuniversity.in/files/original/ca23e476c518c621749adcaf2cc8e7b5.pdf 1765c27e5edcb0f0c32e72155bb0cacc 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 Thesis PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Isolation of fungal endophytes from hulimavu lake flora and characterization and optimization of fungal enzymes / Subject The topic of the resource Life Sciences_Biotechnology Creator An entity primarily responsible for making the resource Saranya Jayaram - 2071607 Publisher An entity responsible for making the resource available CHRIST (Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-07-11 Language A language of the resource English Type The nature or genre of the resource PhD 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 Image Analysis of MRI-based Brain Tumor Classification and Segmentation using BSA and RELM Networks Subject The topic of the resource Brain Tumor Segmentation; Central Nervous System (CNS); FuzzyClustering Method (FCM) Description An account of the resource Brain tumor segmentation plays a crucial role in medical image analysis. Brain tumor patients considerably benefit from early discovery due to the increased likelihood of a successful outcome from therapy. Due to the sheer volume of MRI images generated in everyday clinical practice, manually isolating brain tumors for cancer diagnosis is a challenging task. Automatic segmentation of images of brain tumors is essential. This system aimed to synthesize previous methods for BSA-RELM-based brain tumor segmentation. The proposed methodology rests on four fundamental pillars: preprocessing, segmentation, feature extraction, and model training. Filtering, scaling, boosting contrast, and sharpening are all examples of preprocessing techniques. When doing segmentation, a clustering technique based on Fuzzy Clustering Means (FCM) is used to breakdown the overall dataset into numerous subsets. The proposed approach used the region of filling for feature extraction. After that, a BSA-RELM is used to train the models with the input features. The proposed technique outperforms BSA and RELM, two of the most common alternatives. There was a 98.61 percent success rate with the recommended method. 2023 IEEE. Creator An entity primarily responsible for making the resource Saranya R.; Pushpakumar R.; Srinivasan P.; Aparna N.; Karthika K.; Chauhan A. Source A related resource from which the described resource is derived 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, pp. 523-528. 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/ICACRS58579.2023.10405052" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACRS58579.2023.10405052</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185368770&doi=10.1109%2FICACRS58579.2023.10405052&partnerID=40&md5=1f8bae7e8b2b6b666733355609e142ae" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185368770&doi=10.1109%2fICACRS58579.2023.10405052&partnerID=40&md5=1f8bae7e8b2b6b666733355609e142ae</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034023-5 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 Saranya R., Department of Computer science with Data Analytics, PSG College of Arts and Science, Coimbatore, India; Pushpakumar R., Department of Information Technology, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Tamil Nadu, Chennai, India; Srinivasan P., Department of ECE, Sona College of Technology, Tamilnadu, Salem, India; Aparna N., Department of Biomedical Engineering, Dhaanish Ahmed Institute of Technology, Tamil Nadu, Veerappanur, India; Karthika K., Civil Engineering, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, India; Chauhan A., Department of Life Sciences, School of Sciences, CHRIST (Deemed to be university), Karnataka, 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 Analysis of Manufacturing Machine Failures and Optimization Using Replacement Year Prediction Subject The topic of the resource Failure rate; Machine learning; Manufacturing failures; Operations research; Random forest classifier; Replacement years; Statistical analysis Description An account of the resource The manufacturing industry is highly susceptible to equipment failures, leading to costly downtime, production delays, and increased maintenance expenses. Effective maintenance planning and resource allocation depend on the early detection of possible faults and the precise forecasting of replacement years. The fundamental technique for assuring operational resilience, limiting disruptions, and improving preventative maintenance processes is manufacturing failure analysis. It entails the methodical analysis of failures and spans several sectors, including the automobile, aerospace, electronics, and heavy machinery. In this research, an integrated methodology for predicting replacement years in the manufacturing industry using operations research approaches and the Python-based machine learning algorithm Random Forest Classifier (RFC) is proposed. The program first calculates the total failure rate after importing manufacturing data from a dataset. The failure rate for each manufacturing line is then determined, and the lines with a high failure rate are identified. The program uses machine learning to improve the analysis by teaching a Random Forest classifier to anticipate failures. The model's performance is assessed by measuring the accuracy of a test set. To determine machine replacement years, it also incorporates replacement theory assumptions. Based on the company's founding year and the current year, it determines the replacement year considering the machine's lifespan. This program's advantages include recognizing production lines with high failure rates, employing machine learning to forecast problems, and offering suggestions on when to replace machines. Manufacturers may enhance their processes, lower failure rates, and increase overall efficiency by utilizing statistical analysis, machine learning, andoptimizationstrategies. As technology advances, the field of failure analysis will continue to evolve, enabling firms to achieve improvements. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Saranya R.; Sneha M.; Sridevi R. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-922 LNNS, pp. 311-324. 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/10.1007/978-981-97-0975-5_28" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-0975-5_28</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197277440&doi=10.1007%2F978-981-97-0975-5_28&partnerID=40&md5=fa4c27e07b7cd3cc1ca110e6e0238922" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197277440&doi=10.1007%2f978-981-97-0975-5_28&partnerID=40&md5=fa4c27e07b7cd3cc1ca110e6e0238922</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981970974-8 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 Saranya R., PSG College of Arts and Science, Coimbatore, India; Sneha M., PSG College of Arts and Science, Coimbatore, India; Sridevi R., Christ Deemed to be UniversityCentral Campus, Bangalore, 560029, 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 Design of automatic follicle detection and ovarian classification system for ultrasound ovarian images Subject The topic of the resource Accuracy; Active contour; Biomedical instrumentation; Detection of PCOS; Follicle; Modified Otsu; Sensing systems; Ultrasound image Description An account of the resource Polycystic Ovary Syndrome (PCOS) is a common reproductive and metabolic disorder characterized by an increased number of ovarian follicles. Accurate diagnosis of PCOS requires detailed ultrasound imaging to assess follicles size, number, and position. However, noise often needs to be improved on these images, complicating manual detection for radiologists and leading to potential misidentification. This paper introduces an automated diagnostic system for integration with ultrasound imaging equipment to enhance follicle identification accuracy. The system consists of two main stages: preprocessing and follicle segmentation. Preprocessing employs an adaptive Frost filter to reduce noise, while follicle segmentation utilizes a region-based active contour combined with a modified Otsu method. Unlike the conventional Otsu method, where the threshold value is selected manually, the modified Otsu method automatically selects initial threshold values using an iterative approach. After segmentation, features are extracted from the segmented results. An SVM classifier then categorizes the ovarian image as normal, cystic, or polycystic. Experimental results demonstrate that the proposed methods Follicle Identification Rate is 96.3% and the False Acceptance Rate is 2%, which significantly improves classification accuracy, highlighting its potential advantages for clinical application. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Creator An entity primarily responsible for making the resource Saranya R.; Sridevi R. Source A related resource from which the described resource is derived Multimedia Tools and Applications 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11042-024-20370-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11042-024-20370-0</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212391699&doi=10.1007%2Fs11042-024-20370-0&partnerID=40&md5=0003457aec33606840def110694640fd" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212391699&doi=10.1007%2fs11042-024-20370-0&partnerID=40&md5=0003457aec33606840def110694640fd</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 13807501; CODEN: MTAPF 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 Saranya R., Department of Computer Science with Data Analytics, PSG College of Arts & Science, Tamil Nadu, Coimbatore, India; Sridevi R., Department of Computer Science, CHRIST 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 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 Untold and Painful Stories of Survival: The Life of Adolescent Girls of the Paniya Tribes of Kerala, India Subject The topic of the resource Adolescent girls; Kerala; Paniya tribe; Sexual abuse; Untold stories Description An account of the resource Tribal adolescent girls are vulnerable to neglect, abuse and exploitation across the world. Literature on the status of adolescents belonging to the Paniya tribe is scanty. However, limited information about the Paniya tribe of Kerala indicates that they are neglected and deprived from basic facilities. According to the Census Report of India (2011), 49.5% of the Paniya tribe members are literate. The lives of adolescents in the Paniya community are distinct from those of other sections of society, and they are yet to be addressed by the government or the media. The objective of this chapter is to discuss the issues and concerns of Paniya adolescent girls of Kerala. A Paniya girl from Vattachira (Calicut) treks around 2 km during her menstruation to fetch fresh and clean water. They use pieces of clothes to manage menstruation since they do not have access to pads or tampons. Drying their garments during the rainy season is difficult, which leaves them susceptible to rashes and infections. They are provided with residential educational facilities by the government, but they are unable to adjust to the lifestyles of other members of the society and are frequently bullied and discriminated, leading to school dropouts. Sexual exploitation by strangers and community members is widespread among Paniya girls, and unmarried mothers under the age of 18 are also prevalent among this community. The chapter highlights upon some of the challenges of the Paniya Tribal adolescent girls of Kerala and offers some suggestions for improving the quality of life of this marginalized group, which will assist the policymakers and government for taking need-based measures. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. Creator An entity primarily responsible for making the resource Saranya T.S.; Deb S.; Paul D.; Deb S. Source A related resource from which the described resource is derived Child Safety, Welfare and Well-being: Issues and Challenges, Second Edition, pp. 185-194. Publisher An entity responsible for making the resource available Springer Nature 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/10.1007/978-981-16-9820-0_11" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-16-9820-0_11</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161141833&doi=10.1007%2F978-981-16-9820-0_11&partnerID=40&md5=0df408f24e565f8b293db7db982c832d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161141833&doi=10.1007%2f978-981-16-9820-0_11&partnerID=40&md5=0df408f24e565f8b293db7db982c832d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-981169820-0; 978-981169819-4 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 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 Saranya T.S., Department of Psychology Sree Narayana College, Vadakara, India; Deb S., CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Paul D., RGNIYD, Tamil Nadu, Sriperumbudur, India; Deb S., Rajiv Gandhi National Institute of Youth Development (RGNIYD), Tamil Nadu, Sriperumbudur, India, School of Public Health and Social Work, QUT, Australia 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 Saranya, R.; Rajagopal, Manikandan; Ramprasath, J.; ThamaraiSelvi, K.; Leelavathy, S. Title A name given to the resource An Efficient Fuzzy Logic-Integrated Hybrid Deep Learning Framework for Medical Diagnosis 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 Fuzzy Information and Engineering;Volume;18;Issue;1;pp.1-18 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.26599/FIE.2025.9270072" target="_blank" rel="noreferrer noopener">https://doi.org/10.26599/FIE.2025.9270072</a> <a href="https://www.scopus.com/pages/publications/105038223936?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038223936?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 Saranya R., Dr. SNS Rajalakshmi College of Arts and Science, Department of Computer Science with Cyber Security, Coimbatore, 600049, India; Rajagopal M., School of Business and Management, Christ University, Bangalore, 600871, India; Ramprasath J., Dr. Mahalingam College of Engineering and Technology, Department of Information Technology, Pollachi, 642003, India; ThamaraiSelvi K., New Horizon College of Engineering, Department of Information Science and Engineering, Bangalore, 600671, India; Leelavathy S., Panimalar Engineering College, Department of AI&DS, Chennai, 600123, India Description An account of the resource Medical diagnosis involves analyzing symptoms, test results, and patient histories, but uncertainty from vague symptoms and incomplete records complicates the process. Fuzzy logic-based systems address this issue but often depend on manual rule creation, which is time-consuming. This research proposes a hybrid approach integrating fuzzy logic with deep learning techniques (FL-DLT) for intelligent diagnosis. The framework combines adaptive neuro-fuzzy inference system (ANFIS) for handling uncertainty with convolutional neural networks (CNNs) for extracting features from medical images like X-rays and MRIs. ANFIS models relationships between symptoms, results, and diagnoses, while CNNs analyze medical images. Experimental results show high accuracy and reliability, even with noisy or incomplete data. The proposed approach can improve diagnostic accuracy and efficiency, supporting clinicians in decision-making. Key contributions include the development of the FL-DLT framework and its evaluation using a large dataset of patient records and medical images. Additionally, the research offers insights into the application of fuzzy logic and deep learning in medical diagnosis, highlighting their potential to enhance diagnostic outcomes and efficiency in clinical practice. 2009 Tsinghua University Press. Subject The topic of the resource adaptive neuro-fuzzy inference system (ANFIS); decision support systems; deep learning; fuzzy logic; intelligent healthcare systems; medical diagnosis Publisher An entity responsible for making the resource available Tsinghua University Press Relation A related resource ISSN: 16168658; 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 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 Saranya, R.; Sandhika, G. Title A name given to the resource Leveraging Machine Learning for Epidermal Ailment Detection 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 Lecture Notes in Networks and Systems;Volume;1497 LNNS;pp.275-288 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-9184-5_22" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-9184-5_22</a> <a href="https://www.scopus.com/pages/publications/105028358148?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028358148?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 Saranya R., Department of Computer Science with Data Analytics, PSG College of Arts and Science, Coimbatore, India; Sandhika G., Department of Statistics and Data Science, Christ University, Bangalore, India Description An account of the resource Skin disorders are common across the globe, often proving to be difficult to diagnose because of coexisting signs and symptoms. In this paper, we study the feasibility of using machine learning (ML) techniques for automatic skin disease detection. We look at the emerging patterns in fundamental studies within the scope of focus that deals with image processing for feature extraction and employing classification methods for disease detection. We focus on feature extraction and the classification of images. One of the major strengths is the ML-based approach with better access and usability and higher chances of them being detected at an early stage. In addition, we consider some of the drawbacks and problems of these methods, including biased data and lack of sufficient professional oversight. We also consider other aspects, whereby one of them is further analysis of the requirement in the case of the absence of the adequate data, standard models, and unambiguous explanations of the inner processes. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Deep learning; Diagnosis; Image processing; Machine learning; Skin ailment detection Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981969183-8; 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 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 Saranya, R.; Sridevi, R. Title A name given to the resource Design of automatic follicle detection and ovarian classification system for ultrasound ovarian images 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 Multimedia Tools and Applications;Volume;84;Issue;27;pp.32643-32669 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11042-024-20370-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11042-024-20370-0</a> <a href="https://www.scopus.com/pages/publications/85212391699?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85212391699?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 Saranya R., Assistant Professor, Department of Computer Science with Data Analytics, PSG College of Arts & Science, Tamil Nadu, Coimbatore, India; Sridevi R., Associate Professor, Department of Computer Science, CHRIST University, Karnataka, Bangalore, India Description An account of the resource Polycystic Ovary Syndrome (PCOS) is a common reproductive and metabolic disorder characterized by an increased number of ovarian follicles. Accurate diagnosis of PCOS requires detailed ultrasound imaging to assess follicles size, number, and position. However, noise often needs to be improved on these images, complicating manual detection for radiologists and leading to potential misidentification. This paper introduces an automated diagnostic system for integration with ultrasound imaging equipment to enhance follicle identification accuracy. The system consists of two main stages: preprocessing and follicle segmentation. Preprocessing employs an adaptive Frost filter to reduce noise, while follicle segmentation utilizes a region-based active contour combined with a modified Otsu method. Unlike the conventional Otsu method, where the threshold value is selected manually, the modified Otsu method automatically selects initial threshold values using an iterative approach. After segmentation, features are extracted from the segmented results. An SVM classifier then categorizes the ovarian image as normal, cystic, or polycystic. Experimental results demonstrate that the proposed methods Follicle Identification Rate is 96.3% and the False Acceptance Rate is 2%, which significantly improves classification accuracy, highlighting its potential advantages for clinical application. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Subject The topic of the resource Accuracy; Active contour; Biomedical instrumentation; Detection of PCOS; Follicle; Modified Otsu; Sensing systems; Ultrasound image Publisher An entity responsible for making the resource available Springer Relation A related resource ISSN: 13807501; CODEN: MTAPF 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 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/. Creator An entity primarily responsible for making the resource Saranya, S.; Antony, Nittymol; George, Ginu; Sasikala, K.; Thomas, Mary Rani Title A name given to the resource Beyond Surveys: A Study on Metrics and Tools in Employee Engagement Analytics 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 Studies in Systems, Decision and Control;Volume;613;pp.493-503 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-99470-8_51" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-99470-8_51</a> <a href="https://www.scopus.com/pages/publications/105039320780?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105039320780?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 Saranya S., Department of Professional Accounting and Finance, Kristu Jayanti College (Autonomous), Bengaluru, India; Antony N., Department of Professional Accounting and Finance, Kristu Jayanti College (Autonomous), Bengaluru, India; George G., Westford University College, Sharjah, United Arab Emirates; Sasikala K., Department of Commerce, Kongu Arts and Science College(Autonomous), Erode, India; Thomas M.R., Department of Commerce, CHRIST (Deemed to be University), Bengaluru, India Description An account of the resource In the evolving landscape of employee engagement assessment, this current research explores the shift from conventional survey methods to a dynamic paradigm employing advanced metrics and tools. The study delves into the significance of employee engagement for organizational success and individual well-being, emphasizing the limitations inherent in traditional survey approaches. The current research uses a mixed-methods approach, including a literature review and case studies. The research unveils the transformative potential of advanced analytics, shedding light on recent trends where organizations integrate artificial intelligence, sentiment analysis, and continuous feedback mechanisms to gain a more nuanced understanding of workforce dynamics. The findings highlight the importance for organizations to move beyond static surveys, adapting strategies to the real-time, multifaceted nature of employee engagement for fostering a positive and thriving work environment. This study serves as a practical guide for HR professionals, organizational leaders, and researchers navigating the complexities of modern workplaces, offering insights that bridge theory and implementation in the realm of employee engagement analytics. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. Subject The topic of the resource Analytics; Employee engagement; Metrics; Tools Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 21984182; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Saranya, T.S.; Gimcule; Gupta, Sandeep Kumar; Saibalaji, Sudha; Yucel, Sebnem; Naila, P.; Yucel, Recep; Philip, Smitha Title A name given to the resource Traditional beliefs and practices associated with relieving psychological problems of pregnant women of the Zeliang tribe 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 Discover Mental Health;Volume;6;Issue;1;Article No.;92; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s44192-026-00442-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s44192-026-00442-3</a> <a href="https://www.scopus.com/pages/publications/105040399664?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105040399664?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 Saranya T.S., Amity Institute of Behavioural Health and Allied Sciences, Amity University, Bengaluru, India; Gimcule, Bengaluru, India; Gupta S.K., Mohan Babu University, Tirupati, India; Saibalaji S., SRMIST, Kattanlulathur, Chennai, India; Yucel S., Selcuk University, Konya, Turkey; Naila P., Bengaluru, India; Yucel R., Kirikkale University, Kirikkale, Turkey; Philip S., School of Psychological Sciences, Christ University, Bengaluru, India Description An account of the resource In Indigenous and resource-limited communities, emotional distress during pregnancy is often understood and managed through culturally grounded belief systems rather than biomedical frameworks. This qualitative study explores how pregnant women of the Zeliang tribe in Benreu village, Nagaland, perceive, interpret, and cope with emotional distress using traditional beliefs and practices. Guided by community psychology, cultural safety frameworks, and Lazarus and Folkmans Transactional Model of Stress and Coping, semi-structured interviews were conducted with ten pregnant women and two traditional healers. Data were analyzed using reflexive thematic analysis. Three interconnected themes were generated. First, emotional vulnerability and cultural conceptions of pregnancy revealed that fear, sadness, and emotional instability were interpreted through spiritual and ancestral meanings rather than psychiatric categories. Second, healing practices as emotional regulation tools illustrated how ritual chanting, fumigation, protective threads, and herbal remedies functioned as embodied coping mechanisms supported by intergenerational kin networks. Third, traditional healers roles in psychosocial support highlighted their function as trusted interpreters of distress who provide narrative explanation, reassurance, and culturally congruent guidance. Participants also described a complementary care pathway in which biomedical services were used for physical monitoring while emotional and spiritual concerns were addressed through traditional systems. The findings indicate that traditional healing within the Zeliang community operates as a culturally embedded model of perinatal emotional care integrating spiritual, relational, and symbolic dimensions of well-being. The study underscores the importance of culturally safe maternal mental health approaches that respect Indigenous explanatory systems and encourage collaboration between biomedical providers and community-based healing structures. The Author(s) 2026. Subject The topic of the resource Cultural safety; Emotional well-being; India; Indigenous healing; Perinatal mental health; Pregnancy; Traditional medicine; Zeliang tribe Publisher An entity responsible for making the resource available Springer Nature Relation A related resource ISSN: 27314383; 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 Saranya, T.S.; Yucel, Sebnem; Balaji, Sudha Sai; Naila, P.; Sarkar, Kritica; Mathew, Natasha Suzan; Laishram, Linda; Gupta, Sandeep Kumar; Jha, Mithali; Yucel, Recep Title A name given to the resource Neurocognitive modeling of emotional states using EEG and hidden markov models: A multidisciplinary approach 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 Multidisciplinary Science Journal;Volume;8;Issue;5;Article No.;e2026296; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.31893/multiscience.2026296" target="_blank" rel="noreferrer noopener">https://doi.org/10.31893/multiscience.2026296</a> <a href="https://www.scopus.com/pages/publications/105020760638?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105020760638?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 Saranya T.S., Amity University, Bengaluru, India; Yucel S., Selcuk University, Konya, Turkey; Balaji S.S., SRMIST Chennai, India; Naila P., Bengaluru, India; Sarkar K., Bengaluru, India; Mathew N.S., Bengaluru, India; Laishram L., Bengaluru, India; Gupta S.K., Mohan Babu University, Tirupati, India; Jha M., Christ University, Bengaluru, India; Yucel R., Kirikkale University, Kirikkale, Turkey Description An account of the resource This interdisciplinary research cuts computational modeling and cognitive neuroscience approaches with the intention of studying dynamic emotional involvement with multimedia stimuli via HMM analysis of EEG data. In particular, the paper deals with advertisements that target excitement and love-type emotions, setting forth new paradigms for understanding the building and modulation of emotional experience across time in the human brain. EEG parameters such as amplitude, arousal, and frontal activation were studied as markers of neural reactions to emotionally arousing content. The neural markers are tracked over time to record the changes in emotional engagement. The HMMs use identifies hidden neural states and their probabilistic transitions, making the temporal description of neural dynamics during emotional processing rich and nuanced. The analytical approach provides identifiable neural patterns for excitement and love stimuli distinguished in terms of arousal, spectral amplitude, and hemispheric asymmetry in frontal activation. Due to these distinctions, we ascertain that the brain processes different affective tones distinctly, shedding light on the intricacies of emotion perception and its immediate brain counterpart. Using the results, a predictive HMM model is presented to model emotional changes when individuals are subjected to effective multimedia stimuli. The model serves as a bridge to further real-time developments in human-computer interaction, adaptive e-learning, immersive media conception, and affective UX (user experience) optimization. In other words, this enables the system to detect shifts in the user's emotions automatically and adapt content accordingly, representing truly affect-sensitive technologies. Amalgamating computational modeling with neurophysiological measurement, this study contributes to the birth of emotion-aware technology that can be dynamically responsive to the users' current affective state, thus harnessing engagement, personalization, and user satisfaction as opportunities. It builds on the interdisciplinary discourse between cognitive neuroscience, affective computing, and computational psychology to serve as a methodological guideline for future investigations into emotional dynamics and brain-computer interfaces (BCIs), as well as neuroadaptive technology. It makes a case for the relevance of temporal modeling in decoding emotional cognition and therefore advocates the continued employment of machine-learning approaches in brain activity and human affective behaviour studies. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Subject The topic of the resource adaptive learning; affective computing; arousal; excitement; frontal activation; love-themed advertisements Publisher An entity responsible for making the resource available Malque Publishing Relation A related resource ISSN: 26751240; 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 Saranya, T.S.; Yucel, Sebnem; Balaji, Sudha Sai; Naila, P.; Sarkar, Kritica; Mathew, Natasha Suzan; Laishram, Linda; Gupta, Sandeep Kumar; Jha, Mithali; Yucel, Recep Title A name given to the resource Cultural resonance in the brain: EEG-Based insights into emotional engagement with festive imagery 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 Multidisciplinary Science Journal;Volume;8;Issue;5;Article No.;e2026305; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.31893/multiscience.2026305" target="_blank" rel="noreferrer noopener">https://doi.org/10.31893/multiscience.2026305</a> <a href="https://www.scopus.com/pages/publications/105020466419?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105020466419?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 Saranya T.S., Amity University Bengaluru, India; Yucel S., Selcuk University, Konya, Turkey; Balaji S.S., SRMIST Chennai, India; Naila P., Bengaluru, India; Sarkar K., Bengaluru, India; Mathew N.S., Bengaluru, India; Laishram L., Bengaluru, India; Gupta S.K., Mohan Babu University, Tirupati, India; Jha M., Christ University, Bengaluru, India; Yucel R., Kirikkale University, Kirikkale, Turkey Description An account of the resource Festive imagery is fundamental in constructing cultural identity, affective resonance, and collective memory. The neural engagement patterns in Kolkata individuals, upon viewing familiar and unfamiliar festive images, have been studied by using electroencephalography (EEG) as an on-line, non-invasive indicator of neural activity. In particular, the study compares participants' neural reactions to images of the Onam festival of Keralaa culturally unfamiliar festivalto those of Durga Puja celebrations outside Kolkata, which, although culturally familiar, are not immediately geographically specific. The EEG parameters that were assessed were cognitive load, emotional arousal, neural stimulation, and frontal lobe activation linked to attention and affective processing. Results show that novel but colorful festive images like Onam had greater and longer-lasting cognitive and emotional activation than familiar Durga Puja images. Such increased activation was associated with augmented beta and gamma wave activity, reflecting high arousal and attention, as well as marked frontal lobe activation. The findings indicate that novelty, visual symbolism, and the richness of cultural representations have a central role to play in the modulation of cognitive processing and emotional resonance, even among culturally homogenous populations. The research adds to the growing body of literature in neuroaesthetics and cultural neuroscience by demonstrating how culturally unfamiliar but symbolically dense images can elicit profound cognitive and affective responses. These findings have implications for intercultural communication, visual media design, and festival tourism promotion, where strategic deployment of culturally diverse imagery can increase audience engagement and emotional resonance. Copyright (c) 2026 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Subject The topic of the resource adaptive learning; affective computing; arousal; excitement; frontal activation; love-themed advertisements Publisher An entity responsible for making the resource available Malque Publishing Relation A related resource ISSN: 26751240; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Optimal procurement policy for growing items under permissible delay in payment Subject The topic of the resource delay in payment; deteriorating items; growing items; inventory management; mortality Description An account of the resource In the last decade, growing item industries have shown an increasing trend in production and it is expected that such industries will maintain this increasing pace in the future. Existing challenges of these industries, like mortality in the production phase and deterioration in the consumption phase, make procurement decisions more complex. In this article, we established an inventory model with mortality, deterioration, and price-dependent demand. To increase the sales volume and profit, a delay in payment policy is considered. A numerical example is presented to explain the solution procedure. The concavity of the profit function is discussed analytically for decision variables. It has been observed through sensitivity analysis that selling price is the most sensitive among decision variables and parameters. 2024 Inderscience Enterprises Ltd. Creator An entity primarily responsible for making the resource Saraswat A.K.; Sharma A. Source A related resource from which the described resource is derived International Journal of Services and Operations Management, Vol-47, No. 3, pp. 354-365. Publisher An entity responsible for making the resource available Inderscience Publishers 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/10.1504/IJSOM.2024.137318" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJSOM.2024.137318</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187993567&doi=10.1504%2FIJSOM.2024.137318&partnerID=40&md5=abbe177f8f3ca2f6f3add917bd54f839" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187993567&doi=10.1504%2fIJSOM.2024.137318&partnerID=40&md5=abbe177f8f3ca2f6f3add917bd54f839</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17442370 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 Saraswat A.K., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi- NCR, Ghaziabad, 201003, India; Sharma A., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi- NCR, 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 Inventory model for the growing items with price dependent demand, mortality and deterioration Subject The topic of the resource deterioration; growing items; inventory model; mortality; price dependent demand Description An account of the resource Growing items like livestock, chicks, etc. gain weight in the growing phase but some of them are lost due to mortality. In the selling phase, some inventory is lost due to deterioration. Such aspects make procurement decisions quite difficult for these items. In the light of such aspects, we developed an inventory model for the growing items with price dependent demand, mortality and deterioration. Shortages are partially backlogged. Our aim is to optimise the total cost by determining the optimal ordered quantity and total cycle length. Convexity of the cost function with respect to the decision variables has been discussed analytically. Solution procedure along with numerical example at different percentage of backlogged quantity is provided to show the applicability and validity of our model. Sensitivity analysis shows that total cycle length is the most sensitive among all the decision variables and parameters. Copyright 2023 Inderscience Enterprises Ltd. Creator An entity primarily responsible for making the resource Saraswat A.K.; Sharma A. Source A related resource from which the described resource is derived International Journal of Operational Research, Vol-47, No. 4, pp. 534-546. Publisher An entity responsible for making the resource available Inderscience Publishers 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/10.1504/IJOR.2023.132818" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJOR.2023.132818</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170233660&doi=10.1504%2FIJOR.2023.132818&partnerID=40&md5=132ca87499915b5d483d210173b8cb81" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170233660&doi=10.1504%2fIJOR.2023.132818&partnerID=40&md5=132ca87499915b5d483d210173b8cb81</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17457645 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 Saraswat A.K., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi-NCR, Ghaziabad, 201003, India; Sharma A., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi-NCR, 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 Editorials Editorial Faculty Publications- Editorial 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 Preface Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Saraswat M.; Balachandran K.; Bansal J.C.; Sharma H.; Kim J.H. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. v-vi. 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 2022-01-01 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-s2.0-85133667351&partnerID=40&md5=bbe3dc25361a7a035098421fbd425cb1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133667351&partnerID=40&md5=bbe3dc25361a7a035098421fbd425cb1</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 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 Editorial Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Saraswat M., Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India; Balachandran K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Bansal J.C., South Asian University, New Delhi, India; Sharma H., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India; Kim J.H., Korea University, Seoul, South Korea 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 Editorials Editorial Faculty Publications- Editorial 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 Preface Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Saraswat M.; Sharma H.; Balachandran K.; Kim J.H.; Bansal J.C. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-111, pp. v-vi. 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 2022-01-01 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-s2.0-85133513346&partnerID=40&md5=4199a52b0a150e8ce99793cc426fe290" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133513346&partnerID=40&md5=4199a52b0a150e8ce99793cc426fe290</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 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 Editorial Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Saraswat M., Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology, Noida, India; Sharma H., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India; Balachandran K., Department of Computer Science and Engineering, CHRIST (Deemed to be University, Bengaluru, India; Kim J.H., Korea University, Seoul, South Korea; Bansal J.C., South Asian University, New Delhi, India