320 20 11858 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 CMT-CNN: colposcopic multimodal temporal hybrid deep learning model to detect cervical intraepithelial neoplasia Subject The topic of the resource Attention mechanism; Cervical cancer; Deep learning; EfficientNet; Specular reflections Description An account of the resource Cervical cancer poses a significant threat to women's health in developing countries, necessitating effective early detection methods. In this study, we introduce the Colposcopic Multimodal Temporal Convolution Neural Network (CMT-CNN), a novel model designed for classifying cervical intraepithelial neoplasia by leveraging sequential colposcope images and integrating extracted features with clinical data. Our approach incorporates Mask R-CNN for precise cervix region segmentation and deploys the EfficientNet B7 architecture to extract features from saline, iodine, and acetic acid images. The fusion of clinical data at the decision level, coupled with Atrous Spatial Pyramid Pooling-based classification, yields remarkable results: an accuracy of 92.31%, precision of 90.19%, recall of 89.63%, and an F-1 score of 90.72. This achievement not only establishes the superiority of the CMT-CNN model over baselines but also paves the way for future research endeavours aiming to harness heterogeneous data types in the development of deep learning models for cervical cancer screening. The implications of this work are profound, offering a potent tool for early cervical cancer detection that combines multimodal data and clinical insights, potentially saving countless lives. 2024, Universitas Ahmad Dahlan. All rights reserved. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived International Journal of Advances in Intelligent Informatics, Vol-10, No. 2, pp. 317-332. Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan 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/10.26555/ijain.v10i2.1527" target="_blank" rel="noreferrer noopener">https://doi.org/10.26555/ijain.v10i2.1527</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201378902&doi=10.26555%2Fijain.v10i2.1527&partnerID=40&md5=a5e8814cc8b34089037f3d24f32fa92f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201378902&doi=10.26555%2fijain.v10i2.1527&partnerID=40&md5=a5e8814cc8b34089037f3d24f32fa92f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 24426571 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 Mukku L., CHRIST(Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST(Deemed to be University), Kengeri, Bangalore, 560074, 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 EGMM: removal of specular reflection with cervical region segmentation using enhanced Gaussian mixture model in cervix images Subject The topic of the resource Cervical region; Colposcopy; Enhanced Gaussian mixture model; Mexican axolotl optimization; Specular reflection Description An account of the resource Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance.Before segmenting the cervical region, specular reflection removal is an efficient one. Because, cervical cancer can be found using a visual check with acetic acid, which turns precancerous and cancerous areas whiteand these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-whiteareas and should therefore be removed. So, in this paper, specular reflection removal with segmentingthe cervix region ina colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican Axolotl Optimization (AMAO) algorithm. The performance of the proposed approach is analyzed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. 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 Mukku L.; Thomas J. 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/s11042-024-19035-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11042-024-19035-9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190708576&doi=10.1007%2Fs11042-024-19035-9&partnerID=40&md5=ecfbc67782ec0e407bb5d6de20ccc995" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190708576&doi=10.1007%2fs11042-024-19035-9&partnerID=40&md5=ecfbc67782ec0e407bb5d6de20ccc995</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 Mukku L., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India; Thomas J., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Media's influence on suicide: Building a safer online world for all Subject The topic of the resource Media; Psychiatry; Social Media; Suicide Description An account of the resource In 1999, World Health Organization (WHO) initiated a global campaign focused on suicide prevention. In collaboration with International Association for Suicide Prevention, WHO compiled recommendations and resources intended to educate various societal and groups with the potential to impact suicide prevention, and this included the media. In order to combat the alarmingly high incidence of suicides (Tandon and Nathani, 2018), it is imperative to institute guidelines outlining how the social media forums ought to disseminate altruistic, essential educational content while. This work is a step toward achieving the same by laying down guidelines that could potentially reduce the suicide rate. 2023 Elsevier B.V. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Asian Journal of Psychiatry, Vol-91 Publisher An entity responsible for making the resource available Elsevier B.V. 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/10.1016/j.ajp.2023.103868" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ajp.2023.103868</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180563467&doi=10.1016%2Fj.ajp.2023.103868&partnerID=40&md5=a1fa1109bdf227e00fdae206f344a67a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180563467&doi=10.1016%2fj.ajp.2023.103868&partnerID=40&md5=a1fa1109bdf227e00fdae206f344a67a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18762018; PubMed ID: 38141541 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 Mukku L., CHRIST (Deemed to be University), Kengeri Campus, Bangalore, 560065, India; Thomas J., CHRIST (Deemed to be University), Kengeri Campus, Bangalore, 560065, 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 TelsNet: temporal lesion network embedding in a transformer model to detect cervical cancer through colposcope images Subject The topic of the resource Cervical cancer; Colposcopy; Deep learning; Lesions; Transformer architecture Description An account of the resource Cervical cancer ranks as the fourth most prevalent malignancy among women globally. Timely identification and intervention in cases of cervical cancer hold the potential for achieving complete remission and cure. In this study, we built a deep learning model based on self-attention mechanism using transformer architecture to classify the cervix images to help in diagnosis of cervical cancer. We have used techniques like an enhanced multivariate gaussian mixture model optimized with mexican axolotl algorithm for segmenting the colposcope images prior to the Temporal Lesion Convolution Neural Network (TelsNet) classifying the images. TelsNet is a transformer-based neural network that uses temporal convolutional neural networks to identify cancerous regions in colposcope images. Our experiments show that TelsNet achieved an accuracy of 92.7%, with a sensitivity of 73.4% and a specificity of 82.1%. We compared the performance of our model with various state-of-the-art methods, and our results demonstrate that TelsNet outperformed the other methods. The findings have the potential to significantly simplify the process of detecting and accurately classifying cervical cancers at an early stage, leading to improved rates of remission and better overall outcomes for patients globally. 2023, Universitas Ahmad Dahlan. All rights reserved. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived International Journal of Advances in Intelligent Informatics, Vol-9, No. 3, pp. 502-523. Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan 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/10.26555/ijain.v9i3.1431" target="_blank" rel="noreferrer noopener">https://doi.org/10.26555/ijain.v9i3.1431</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178487120&doi=10.26555%2Fijain.v9i3.1431&partnerID=40&md5=9830a12b831c8e3d2215c2966162d27a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178487120&doi=10.26555%2fijain.v9i3.1431&partnerID=40&md5=9830a12b831c8e3d2215c2966162d27a</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 24426571 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 Mukku L., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, 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 A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition Subject The topic of the resource Deep learning; Emotion recognition; Facial image analysis; LBP-TOP; Micro-expression recognition; Micro-expressions; Optical flow Description An account of the resource Facial expression analysis to understand human emotion is the base for affective computing. Until the last decade, researchers mainly used facial macro-expressions for classification and detection problems. Micro-expressions are the tiny muscle moments in the face that occur as responses to feelings and emotions. They often reveal true emotions that a person attempts to suppress, hide, mask, or conceal. These expressions reflect a persons real emotional state. They can be used to achieve a range of goals, including public protection, criminal interrogation, clinical assessment, and diagnosis. It is still relatively new to utilize computer vision to assess facial micro-expressions in video sequences. Accurate machine analysis of facial micro-expression is now conceivable due to rapid progress in computational methodologies and video acquisition methods, as opposed to a decade ago when this had been a realm of therapists and assessment seemed to be manual. Even though the research of facial micro-expressions has become a longstanding topic in psychology, this is still a comparatively recent computational science with substantial obstacles. This paper a provides a comprehensive review of current databases and various deep learning methodologies to analyze micro-expressions. The automation of these procedures is broken down into individual steps, which are documented and debated. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-163, pp. 1-16. 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-0609-3_1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-0609-3_1</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162243130&doi=10.1007%2F978-981-99-0609-3_1&partnerID=40&md5=10d98068524374cf275e860c3cc094f6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162243130&doi=10.1007%2f978-981-99-0609-3_1&partnerID=40&md5=10d98068524374cf275e860c3cc094f6</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 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 Mukku L., CHRIST (Deemed to be University), Bangalore, 560064, India; Thomas J., CHRIST (Deemed to be University), Bangalore, 560064, 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 Attention Based Meta-Module to Integrate Cervigrams with Clinical Data for Cervical Cancer Identification Subject The topic of the resource attention; cervical cancer; Deep learning; EfficientNet; feature integration Description An account of the resource Cervical cancer remains a significant burden on public health, particularly in developing countries, where its malignancy and mortality rates are alarmingly high. Early diagnosis stands as a pivotal factor in effectively treating and potentially curing the cervical cancer. This study introduces a novel approach of meta module based on recurrent gate architecture designed to enhance the classification of cervix images efficiently. This innovative framework incorporates a meta module capable of dynamically selecting image modalities most pertinent attributes. Furthermore, it integrates clinical data with extracted image features and employs a range of EfficientNet architectures (B0-B5) for image classification. Our results indicate that the EfficientNet B5 architecture outperforms its counterparts, achieving an AUC (Area Under the Curve) score of 55.1 and an F1-Score of 75.1. Overall, this work represents a crucial step towards improving the early detection of cervical cancer, which in turn can lead to more effective treatment strategies and, ultimately, better outcomes for patients worldwide. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 286-295. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_30" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_30</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200692709&doi=10.1007%2F978-3-031-64813-7_30&partnerID=40&md5=545245aa0af99f5a209eaab737f97bd0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200692709&doi=10.1007%2f978-3-031-64813-7_30&partnerID=40&md5=545245aa0af99f5a209eaab737f97bd0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration Subject The topic of the resource cervical cancer; Deep learning; DenseNet121; feature integration; K means; ResNet50 Description An account of the resource Cervical cancer ranks as the fourth most common malignancy worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this study, we introduce an ensemble of machine learning and deep learning models, including DenseNet 121, ResNet 50, and XGBoost to classify the cervical intraepithelial neoplasia. A novel feature integration is proposed which ensembles the results of the individual models in five fold validation process. Our methodology is deployed on a dataset sourced from the International Agency for Cancer Research. The results from the proposed framework have shown to be accurate, robust and dependable. This method can be utilized for achieving automatic identification of cervical cancer in early stages so it can be treated appropriately. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 112-122. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_13</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200691505&doi=10.1007%2F978-3-031-64813-7_13&partnerID=40&md5=e8f4c4443908cd4c68c99cd1930fe79a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200691505&doi=10.1007%2f978-3-031-64813-7_13&partnerID=40&md5=e8f4c4443908cd4c68c99cd1930fe79a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Comparative Performance Analysis of Deep Learning Models in Cervical Cancer Detection Subject The topic of the resource AlexNet; cervical cancer; Deep learning; DenseNet121; feature integration; ResNet50; VGG16 Description An account of the resource Cervical cancer one of the four most common malignancies worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this paper, we deploy a range of deep learning methods, including DenseNet 121, ResNet 50, AlexNet and VGG 16 to classify the cervical intraepithelial neoplasia. Our methodology is deployed on a dataset sourced from a Cancer Research institute in India. The current experiment aims to establish the execution of the state-of-the-art pretrained frameworks in deep learning. This will be a baseline experiment for researcher who aim to develop further deep learning models for cervical cancer diagnosis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 185-194. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_20" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_20</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200687527&doi=10.1007%2F978-3-031-64813-7_20&partnerID=40&md5=a735c134e330a3e680a3e05dd9256d81" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200687527&doi=10.1007%2f978-3-031-64813-7_20&partnerID=40&md5=a735c134e330a3e680a3e05dd9256d81</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to Be University), Bangalore, India; Thomas J., CHRIST (Deemed to Be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 CeLaTis: A Large Scale Multimodal Dataset with Deep Region Network to Diagnose Cervical Cancer Subject The topic of the resource cervical cancer; colposcope image; dataset; Deep learning; segmentation Description An account of the resource Cervical cancer is a leading cause of mortality in third world countries. Although there are multiple ways of screening cervical cancer, colposcope image analysis is considered to be standard routine method of diagnosis. Due to factors like lack of skilled personnel and interobserver variability, there is a need for automated diagnostic support for cervical cancer. However, artificial intelligence solutions for medical image analysis done through deep and machine learning models require high quality, non-erroneous and sufficient amount of data. Owing to the lack of such established benchmark datasets for the colposcope images, this work aims at establishing a standard benchmark multi state colposcope image dataset that also contains clinical findings pertaining to each case. In order to establish the quality of the images, mask R-CNN method is used for segmenting the images. Subsequently, a series of IMAGENet pretrained deep learning models are deployed on the dataset to evaluate the performance. The dataset will be made available upon request for strictly research purposes. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 154-163. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-64813-7_17" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_17</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200677764&doi=10.1007%2F978-3-031-64813-7_17&partnerID=40&md5=74efcdd17038cef3cdd8aa230879dc14" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200677764&doi=10.1007%2f978-3-031-64813-7_17&partnerID=40&md5=74efcdd17038cef3cdd8aa230879dc14</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303164812-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Bangalore, India; Thomas J., CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Advanced Cervical Lesion Detection using Deep Learning Techniques Subject The topic of the resource cervical cancer; cervigram; cervix; colposcope; Segmentation Description An account of the resource Cervical cancer has been one of the common causes for mortality by cancer in women across the world. But there are currently not enough skilled colposcopists, and the training process is drawn out. This implicates that there is a significant scope for artificial intelligence based computational models for segmentation of colposcope images. This paper proposes a segmentation network to accurately segment the cervix region and acetowhite lesions in a cervigram. This research can lay a foundation for research aiming to classify the cervix malignancy using AI. The method performed with a precision of 0.73870.1541, accuracy of 0.9291, recall of 0.79120.1439, a dice score of 0.74310.1506 and specificity of 0.95890.0131. The results prove that the model is reliable and robust. 2024 IEEE. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived 2024 1st International Conference on Communications and Computer Science, InCCCS 2024 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/INCCCS60947.2024.10593544" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INCCCS60947.2024.10593544</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200566206&doi=10.1109%2FINCCCS60947.2024.10593544&partnerID=40&md5=12886896f7f7dd3a5b426199c734264f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200566206&doi=10.1109%2fINCCCS60947.2024.10593544&partnerID=40&md5=12886896f7f7dd3a5b426199c734264f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835035885-8 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 Mukku L., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Thomas J., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 A Lesion Feature Engineering Technique Based on Gaussian Mixture Model to Detect Cervical Cancer Subject The topic of the resource Cervical cancer; Deep learning; Expectation maximization; Gaussian mixture modelling; Lesion feature extraction; Segmentation Description An account of the resource Latest innovations in technology and computer science have opened up ample scope for tremendous advances in the healthcare field. Automated diagnosis of various medical problems has benefitted from advances in machine learning and deep learning models. Cancer diagnosis, prognosis prediction and classification have been the focus of an immense amount of research and development in intelligent systems. One of the major concerns of health and the reason for mortality in women is cervical cancer. It is the fourth most common cancer in women, as well as one of the top reasons of mortality in developing countries. Cervical cancer can be treated completely if it is diagnosed in its early stages. The acetowhite lesions are the critical informative features of the cervix. The current study proposes a novel feature engineering strategy called lesion feature extraction (LFE) followed by a lesion recognition algorithm (LRA) developed using a deep learning strategy embedded with a Gaussian mixture model with expectation maximum (EM) algorithm. The model performed with an accuracy of 0.943, sensitivity of 0.921 and specificity of 0.891. The proposed method will enable early, accurate diagnosis of cervical cancer. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-868, pp. 63-75. 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/10.1007/978-981-99-9037-5_6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9037-5_6</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189544119&doi=10.1007%2F978-981-99-9037-5_6&partnerID=40&md5=d88ec727023159202c272d46379d2b4f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189544119&doi=10.1007%2f978-981-99-9037-5_6&partnerID=40&md5=d88ec727023159202c272d46379d2b4f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999036-8 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 Mukku L., CHRIST (Deemed to be University) Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University) Kengeri, Bangalore, 560074, 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 Multimodal Early Fusion Strategy Based on Deep Learning Methods for Cervical Cancer Identification Subject The topic of the resource Cervical cancer; Deep learning; Early fusion Description An account of the resource It is essential to enhance the accuracy of automatic cervical cancer diagnosis by combining multiple forms of information obtained from a patients primary examination. However, existing multimodal systems are not very effective in detecting correlations between different types of data, leading to low sensitivity but high specificity. This study introduces a deep learning system for automatic diagnosis of cervical cancer by incorporating multiple sources of data. First, a convolutional neural network (CNN) to transform the image database to a vector that can be combined with non-image datasets is used. Subsequently, an investigation of jointly the nonlinear connections between all image and non-image data in a deep neural network is performed. Proposed deep learning-based method creates a unified system that takes advantage of both image and non-image data. It achieves an impressive 89.32% sensitivity at 91.6% specificity when diagnosing cervical intraepithelial neoplasia on a wide-ranging dataset. This result is far superior to any single-source system or prior multimodal approaches. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-865, pp. 109-118. 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/10.1007/978-981-99-9043-6_9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9043-6_9</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190394982&doi=10.1007%2F978-981-99-9043-6_9&partnerID=40&md5=0a7b74b039f5d9d7ea7ef150d3a00f3e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190394982&doi=10.1007%2f978-981-99-9043-6_9&partnerID=40&md5=0a7b74b039f5d9d7ea7ef150d3a00f3e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999042-9 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 Mukku L., CHRIST (Deemed to be University), Kengeri, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, 560074, 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 Specular Reflection Removal Techniques in Cervix Image: A Comprehensive Review Subject The topic of the resource Biomedical image analysis; Cervical cancer; Gaussian mixture model; Morphological top-hat transform; Specular reflection Description An account of the resource Cancer detection through medical image segmentation and classification is possible owing to the advancement in image processing techniques. Segmentation and classification tasks carried out to predict and classify diseases need to be dependable and precise. Specular reflections are the high-intensity and low-saturation areas that reflect the light from the probing devices that capture the picture of the organ surface. These areas sometimes mimic the features that are key identifying factors for cancers like acetowhite lesions. This review article examines the various methods proposed for removing specular reflections from medical images, especially those captured by colposcope. The fundamentals of specular reflection removal and its associated challenges are discussed. The paper reviews several state-of-the-art approaches for specular reflection removal. The comprehensive review can be a strong foundation for researchers looking to decide on appropriate techniques to employ in their respective research approaches. 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering, Vol-1105, pp. 479-490. 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/10.1007/978-981-99-7633-1_36" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-7633-1_36</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182518157&doi=10.1007%2F978-981-99-7633-1_36&partnerID=40&md5=77d3a10b252efd858f5e0ae6c8bf6c7f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182518157&doi=10.1007%2f978-981-99-7633-1_36&partnerID=40&md5=77d3a10b252efd858f5e0ae6c8bf6c7f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18761100; ISBN: 978-981997632-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri, Bangalore, 560074, 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 A Specular Reflection Removal Technique in Cervigrams Subject The topic of the resource cervix; HSI images; preprocessing; specular inpainting; specular reflections Description An account of the resource Cancer detection through medical image segmentation and classification is possible owing to the advancement in image processing techniques. Segmentation and classification tasks carried out to predict and classify diseases need to be dependable and precise. Specular reflections are the high-intensity and low-saturation areas that reflect the light from the probing devices that capture the picture of the organ surface. These areas sometimes mimic the features that are key identifying factors for cancers like acetowhite lesions. This review article examines the various methods proposed for removing specular reflections from medical images, especially those captured by colposcopes. The fundamentals of specular reflection removal and its associated challenges are discussed. The paper reviews several prominent approaches for removal of specular reflections proposes a novel method to remove the specular reflections. The comprehensive review can be a strong foundation for researchers looking to decide on appropriate techniques to employ in their respective research approaches. 2023 IEEE. Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications 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/InC457730.2023.10263224" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC457730.2023.10263224</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174726543&doi=10.1109%2FInC457730.2023.10263224&partnerID=40&md5=ba42fd9920e04a3c694a02dc4b77ccbf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174726543&doi=10.1109%2fInC457730.2023.10263224&partnerID=40&md5=ba42fd9920e04a3c694a02dc4b77ccbf</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033577-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Thomas J., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, 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 Letters Letter Faculty Publications-Letters Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A machine learning model to predict suicidal tendencies in students Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Mukku L.; Thomas J. Source A related resource from which the described resource is derived Asian Journal of Psychiatry, Vol-79 Publisher An entity responsible for making the resource available Elsevier B.V. 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/10.1016/j.ajp.2022.103363" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ajp.2022.103363</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144018882&doi=10.1016%2Fj.ajp.2022.103363&partnerID=40&md5=db6739754dbc82fc0e2cfdf065fedb26" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144018882&doi=10.1016%2fj.ajp.2022.103363&partnerID=40&md5=db6739754dbc82fc0e2cfdf065fedb26</a> Rights Information about rights held in and over the resource All Open Access; Bronze Open Access Relation A related resource ISSN: 18762018; PubMed ID: 36481568 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 Letter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mukku L., CHRIST (Deemed to be University), Kengeri Campus, Bengaluru, 560074, India; Thomas J., CHRIST (Deemed to be University), Kengeri Campus, Bengaluru, 560074, 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 Enhancing Mobility: A Smart Cane with Integrated Navigation System and Voice-Assisted Guidance for the Visually Impaired Subject The topic of the resource audio feedback; Blind mobility; haptic feedback; Navigation; Smart Cane; Ultrasonic sensor; vibration motor; voice control Description An account of the resource Blindness is a condition which affects many people, and for the affected people, quality of life can take a big hit. Most blind people already use walking sticks to feel the terrain in front of them as they move around and navigate using touch and sound. However, they cannot judge distances to objects until the cane actually hits the object. In some cases, the contact with the cane may damage the object. Hence, it may be better to have some early warning system so that there is less likelihood of causing damage. This paper presents the design and development of a 'Smart Cane' aimed at enhancing mobility and safety for visually impaired individuals. The cane incorporates ultrasonic sensors to detect objects in the user's surroundings. When an object is detected within a specified distance range, the cane provides haptic feedback through a bidirectional vibration motor, alerting the user to its presence. The microcontroller-based system processes data from both sensors and efficiently manages power consumption to ensure extended battery life. The device's design includes user-friendly controls and an ergonomic enclosure to offer ease of use and protection for the electronic components. Further, there is built-in navigation via online Map API. With the convenience of navigating oneself without external assistance, the 'Smart Cane' demonstrates great potential to improve the independence and confidence of visually impaired individuals in navigating their environments safely. 2024 IEEE. Creator An entity primarily responsible for making the resource Muktha D.S.; Niveditha G.; Pinto N.A.; Sinha S. Source A related resource from which the described resource is derived Proceedings - 2024 13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024, pp. 1124-1129. 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CSNT60213.2024.10546111" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CSNT60213.2024.10546111</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196767291&doi=10.1109%2FCSNT60213.2024.10546111&partnerID=40&md5=ae03094e8cb81e78fe8b11ea347c2dfc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196767291&doi=10.1109%2fCSNT60213.2024.10546111&partnerID=40&md5=ae03094e8cb81e78fe8b11ea347c2dfc</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835030546-3 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 Muktha D.S., CHRIST(Deemed to Be University), Department of Computer Science, Bangalore, India; Niveditha G., CHRIST(Deemed to Be University), Department of Computer Science, Bangalore, India; Pinto N.A., CHRIST(Deemed to Be University), Department of Computer Science, Bangalore, India; Sinha S., CHRIST(Deemed to Be University), Department of Computer Science, Bangalore, India https://archives.christuniversity.in/files/original/00c6a37774233bc5827a739eac650c9b.pdf 90e12250e53f8e544506c3754e20a9f7 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 Antecedents of psychological capital and its consequences on affective commitment and psychological wellbeing / Subject The topic of the resource Psychology Creator An entity primarily responsible for making the resource Mukti Clarence - 1750071 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 2021-01-02 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 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 Predicting the financial behavior of Indian salaried-class individuals Subject The topic of the resource behavioral finance; Bengaluru; conservatism; financial decision-making; financial selfefficacy; herding; India Description An account of the resource COVID-19 has caused not only unprecedented health crises but also economic crises among individuals across the world. White-collar (salaried-class) employees with a fixed salary face financial insecurity due to job loss, pay cuts and uncertainty in retaining a job. This study examines the financial behavior of Indian white-collar salariedclass investors to their cognitive biases. In addition, the mediating effect of financial self-efficacy on cognitive biases and financial behavior is examined. Respondents were given structured questionnaires (google forms) through emails and WhatsApp for data collection. SPSS and R-PLS are used to analyze the data. Conservatism (r = -.603, p < 0.05) and herding bias (r = -.703, p < 0.05) have a significant negative correlation with financial behavior. Financial self-efficacy has a significant positive correlation (r =.621. p < 0.050). Conservatism and herding predicted 60.5% and 62.2% of the variance, respectively. The direct and indirect paths between conservatism bias, financial self-efficacy, and financial behavior are significant. The paths between herding, financial self-efficacy and financial behavior are also significant. Ankita Mulasi, Jain Mathew, Kavitha Desai, 2022. Creator An entity primarily responsible for making the resource Mulasi A.; Mathew J.; Desai K. Source A related resource from which the described resource is derived Investment Management and Financial Innovations, Vol-20, No. 1, pp. 26-37. Publisher An entity responsible for making the resource available LLC CPC Business Perspectives 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/10.21511/imfi.20(1).2023.03" target="_blank" rel="noreferrer noopener">https://doi.org/10.21511/imfi.20(1).2023.03</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148227348&doi=10.21511%2Fimfi.20%281%29.2023.03&partnerID=40&md5=c3552dd08ae79147d12aafd938f97a63" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148227348&doi=10.21511%2fimfi.20%281%29.2023.03&partnerID=40&md5=c3552dd08ae79147d12aafd938f97a63</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 18104967 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 Mulasi A., School of Business and Management, CHRIST (Deemed to be University), India; Mathew J., School of Business and Management, CHRIST (Deemed to be University), India; Desai K., Department of Professional Studies, CHRIST (Deemed to be University), India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PHD PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Relation A related resource 61000330 Title A name given to the resource Impact of Behavioural Biases, Emotional Intelligence and Financial Literacy on Financial Behaviour Subject The topic of the resource Management Studies Description An account of the resource Behavioural finance is the integration of finance and psychology. Finance pertains to the administration of finances by an individual, while psychology involves the examination of the mind and human conduct. Behavioural finance provides a reasonable explanation for the abnormalities observed in financial markets and the irrational decisions made by investors. The foundation of behavioural finance lies in the irrational choices made by individuals, which elucidates the reasons for investors frequently encountering different biases, emotional filters, and a lack of knowledge when making financial decisions. The primary challenges stem from three critical deficiencies: the investors' inability to express their cognitive and emotional biases, insufficient financial knowledge, and an inability to regulate emotions during financial decision-making. This study investigates the influence of investors' financial literacy, emotional intelligence, and behavioural bias on their financial conduct. Studies have shown that behavioural biases negatively impact financial behaviour. Financial literacy and emotional intelligence have been recognised as critical elements that significantly impact the financial behaviour of salaried class investors. Creator An entity primarily responsible for making the resource Mulasi, Ankita Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Contributor An entity responsible for making contributions to the resource Mathew, Jain Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/574361" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/574361</a> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems Subject The topic of the resource Big data analytics; Hadoop; intelligent transport systems; machine learning; metro rail; TestDFSIO Description An account of the resource This paper deals with an intelligent data analytics platform-Jaison-Paul Data Analytics Platform (JP-DAP)-for metro rail transport systems. JP-DAP is intended to ensure smooth functioning, improved customer experience, ridership forecasting, and efficient administration of metro rail transportation systems by integrating and analysing its many data sources. It consists of a middleware which is built on the top of a Hadoop Distributed File System (HDFS) and Spark framework, along with a set of open-source software tools like Apache Hive, Pandas, Google TensorFlow and Spark ML-lib for real-time and legacy data processing. The benchmarking of JP-DAP was conducted using TestDFSIO and have found that it performs well according to industry standards. The specific use case for this project is Kochi Metro Rail Limited (KMRL). The analysis of Automated Fare Collection data from KMRL on JP-DAP framework have produced descriptive statistics visualisation of inflow and outflow analysis, travel patterns during weekdays and weekends, origin-destination matrix, etc.. Moreover JP-DAP framework is capable of producing short term passenger flow predictions using SVR machine learning algorithm with linear, radial basis function and polynomial kernels. Our experiments have shown that SVR linear kernel gives the most accurate results with the least errors in predicting the next day's passenger count using the previous five weekdays data. The station usage (one-to-all) prediction using Long Short-Term Memory (LSTM) is also integrated to this framework. The visualisation as well as analytical outcomes of JP-DAP framework have also been made available to the external world using a rich set of REST APIs and are projected on to a web-dashboard. 2000-2011 IEEE. Creator An entity primarily responsible for making the resource Mulerikkal J.; Thandassery S.; Dixon K D.M.; Rejathalal V.; Ayyappan B. Source A related resource from which the described resource is derived IEEE Transactions on Intelligent Transportation Systems, Vol-23, No. 7, pp. 9146-9156. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TITS.2021.3091542" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TITS.2021.3091542</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113196240&doi=10.1109%2FTITS.2021.3091542&partnerID=40&md5=1491387c02b153ac72ea7f197f0f88fd" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113196240&doi=10.1109%2fTITS.2021.3091542&partnerID=40&md5=1491387c02b153ac72ea7f197f0f88fd</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 15249050 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 Mulerikkal J., The Department of Computer Science, Rajagiri School of Engineering and Technology, Kochi, 682039, India; Thandassery S., The Department of Computer Science, Rajagiri School of Engineering and Technology, Kochi, 682039, India, The Department of Computer Science, Christ-Deemed to Be University, Bengaluru, 560029, India; Dixon K D.M., The Department of Computer Science, Jyothi Engineering College, Thrissur, 679531, India; Rejathalal V., The Department of Computer Science, Jyothi Engineering College, Thrissur, 679531, India; Ayyappan B., The Department of Information Technology, Rajagiri School of Engineering and Technology, Kochi, 682039, India