374 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 An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect Subject The topic of the resource COVID-19; SEIR model; SEIRV; social distancing; vaccination Description An account of the resource Currently, the spread of COVID-19 is running at a constant pace. The current situation is not so alarming, but every pandemic has a history of three waves. Two waves have been seen, and now expecting the third wave. Compartmental models are one of the methods that predict the severity of a pandemic. An enhanced SEIR model is expected to predict the new cases of COVID-19. The proposed model has an additional compartment of vaccination. This proposed model is the SEIRV model that predicts the severity of COVID-19 when the population is vaccinated. The proposed model is simulated with three conditions. The first condition is when social distancing is not incorporated, while the second condition is when social distancing is included. The third one condition is when social distancing is combined when the population is vaccinated. The result shows an epidemic growth rate of about 0.06 per day, and the number of infected people doubles every 10.7 days. Still, with imparting social distancing, the proposed model obtained the value of R0 is 1.3. Vaccination of infants and kids will be considered as future work. 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Creator An entity primarily responsible for making the resource Poonia R.C.; Saudagar A.K.J.; Altameem A.; Alkhathami M.; Khan M.B.; Hasanat M.H.A. Source A related resource from which the described resource is derived Life, Vol-12, No. 5 Publisher An entity responsible for making the resource available MDPI 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/10.3390/life12050647" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/life12050647</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129768302&doi=10.3390%2Flife12050647&partnerID=40&md5=0e5d3f6c2b8f1048b799b593c3581662" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129768302&doi=10.3390%2flife12050647&partnerID=40&md5=0e5d3f6c2b8f1048b799b593c3581662</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20751729 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 Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Saudagar A.K.J., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Altameem A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Alkhathami M., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Khan M.B., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Hasanat M.H.A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia 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 Book Faculty Publications- Book 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 Deep Learning for Sustainable Agriculture Description An account of the resource The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. 2022 Elsevier Inc. All rights reserved. Creator An entity primarily responsible for making the resource Poonia R.C.; Singh V.; Nayak S.R. Source A related resource from which the described resource is derived Deep Learning for Sustainable Agriculture, pp. 1-390. Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/C2020-0-02363-7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/C2020-0-02363-7</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134781217&doi=10.1016%2FC2020-0-02363-7&partnerID=40&md5=107ce545aa63742328cc0d4f507de9c0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134781217&doi=10.1016%2fC2020-0-02363-7&partnerID=40&md5=107ce545aa63742328cc0d4f507de9c0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-032390362-2; 978-032385214-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Poonia R.C., Department of Computer Science CHRIST, Deemed to be University, Bangalore, India; Singh V., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India; Nayak S.R., Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, 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 Book Faculty Publications- Book 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 Deep Learning for Sustainable Agriculture Description An account of the resource The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. 2022 Elsevier Inc. All rights reserved. Creator An entity primarily responsible for making the resource Poonia R.C.; Singh V.; Nayak S.R. Source A related resource from which the described resource is derived Deep Learning for Sustainable Agriculture, pp. 1-390. Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-323-85214-2.09992-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-323-85214-2.09992-4</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129889018&doi=10.1016%2FB978-0-323-85214-2.09992-4&partnerID=40&md5=7b3ee2e7d4d888b7fb7db1e48b6c5bff" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129889018&doi=10.1016%2fB978-0-323-85214-2.09992-4&partnerID=40&md5=7b3ee2e7d4d888b7fb7db1e48b6c5bff</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-032385214-2; 978-032390362-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Singh V., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India; Nayak S.R., Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Noida, 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 Real-Time Cyber-Physical Risk Management Leveraging Advanced Security Technologies Subject The topic of the resource Accuracy; IoT security; Machine learning; Performance metrics; Precision Description An account of the resource Conducting an in-depth study on algorithms addressing the interaction problem in the fields of machine learning and IoT security involves a meticulous evaluation of performance measures to ensure global reliability. The study examines key metrics such as accuracy, precision, recall, and F1 scores across ten scenarios. The highly competitive algorithms showcase accuracy rates ranging from 95.5 to 98.2%, demonstrating their ability to perform accurately in various situations. Precision and recall measurements yield similar information about the model's capabilities. The achieved balance between accuracy and recovery, as determined by the F1 tests ranging from 95.2 to 98.0%, emphasizes the practical importance of data transfer in the proposed method. Numerical evaluation, in addition to an analysis of overall performance metrics, provides a comprehensive understanding of the algorithm's performance and identifies potential areas for improvement. This research leads to advancements in the theoretical vision of machine learning for IoT protection. It offers real-world insights into the practical use of robust models in dynamically changing situations. As the Internet of Things environment continues to evolve, the study's results serve as crucial guides, laying the foundation for developing strong and effective security systems in the realm of interaction between virtual and material reality. The Author(s) 2024. Creator An entity primarily responsible for making the resource Poonia R.C.; Upreti K.; Alapatt B.P.; Jafri S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1011 LNNS, pp. 339-350. 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/10.1007/978-981-97-4581-4_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-4581-4_25</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202602687&doi=10.1007%2F978-981-97-4581-4_25&partnerID=40&md5=8a02527ce7f77d3a15d8c905270c80e8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202602687&doi=10.1007%2f978-981-97-4581-4_25&partnerID=40&md5=8a02527ce7f77d3a15d8c905270c80e8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981974580-7 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 Poonia R.C., Department of Computer Science, Christ University, Delhi NCR, Ghaziabad, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR, Ghaziabad, India; Alapatt B.P., Department of Computer Science, Christ University, Delhi NCR, Ghaziabad, India; Jafri S., Administrative Science Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia 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 Improved Image Up-Scaling Technique using Optimize Filter and Iterative Gradient Method Subject The topic of the resource corner averaging; high resolution; low resolution; optimized filter component Description An account of the resource In numerous realtime applications, image upscaling often relies on several polynomial techniques to reduce computational complexity. However, in high-resolution (HR) images, such polynomial interpolation can lead to blurring artifacts due to edge degradation. Similarly, various edge-directed and learning-based systems can cause similar blurring effects in high-frequency images. To mitigate these issues, directional filtering is employed post corner averaging interpolation, involving two passes to complete the corner average process. The initial step in low-resolution (LR) picture interpolation involves corner pixel refinement after averaging interpolation. A directional filter is then applied to preserve the edges of the interpolated image. This process yields two distinct outputs: the base image and the detail image. Furthermore, an additional cuckoo-optimized filter is implemented on the base image, focusing on texture features and boundary edges to recover neighboring boundary edges. Additionally, a Laplacian filter is utilized to enhance intra-region information within the detailed image. To minimize reconstruction errors, an iterative gradient approach combines the optimally filtered image with the sharpened detail image, generating an enhanced HR image. Empirical data supports the effectiveness of the proposed algorithm, indicating superior performance compared to state-of-the-art methods in terms of both visual appeal and measured parameters. The proposed method's superiority is demonstrated experimentally across multiple image datasets, with higher PSNR, SSIM, and FSIM values indicating better image degradation reduction, improved edge preservation, and superior restoration capabilities, particularly when upscaling High-Frequency regions of images. 2023 IEEE. Creator An entity primarily responsible for making the resource Poonia R.C.; Upreti K.; Hundekari S.; Dadhich P.; Malik K.; Kapoor A. Source A related resource from which the described resource is derived 3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICMNWC60182.2023.10435962" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICMNWC60182.2023.10435962</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186988852&doi=10.1109%2FICMNWC60182.2023.10435962&partnerID=40&md5=bebebd4667b28e267602519592b878c3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186988852&doi=10.1109%2fICMNWC60182.2023.10435962&partnerID=40&md5=bebebd4667b28e267602519592b878c3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835031702-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Poonia R.C., CHRIST(Deemed to Be University), Dept. of Computer Science, Ghaziabad, Delhi NCR, India; Upreti K., CHRIST(Deemed to Be University), Dept. of Computer Science, Ghaziabad, Delhi NCR, India; Hundekari S., MIT ADT University Rajbaug Loni Kalbhor, Pune, India; Dadhich P., School of Computer Application, Manav Rachna International Institute of Research and Studies, India; Malik K., School of Law, CHRIST(Deemed to Be University), Ghaziabad, Delhi NCR, India; Kapoor A., Maharaja Surajmal Institute of Technology, Dept. of Computer Science, Delhi, 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 FOREWORD Description An account of the resource [No abstract available] Creator An entity primarily responsible for making the resource Poonia R.C.; Upreti K.; Jafri S.; Bhardwaj R.; Kushwah V.S.; Vats P.; Gangwar D.; Dayal M.; Divakaran P. Source A related resource from which the described resource is derived Journal of Discrete Mathematical Sciences and Cryptography, Vol-27, No. 7, pp. iii-. Publisher An entity responsible for making the resource available Taru Publications 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/10.47974/JDMSC-27-7-Foreword" target="_blank" rel="noreferrer noopener">https://doi.org/10.47974/JDMSC-27-7-Foreword</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210418577&doi=10.47974%2FJDMSC-27-7-Foreword&partnerID=40&md5=98943109f2c37a55554cd7bb6054060e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210418577&doi=10.47974%2fJDMSC-27-7-Foreword&partnerID=40&md5=98943109f2c37a55554cd7bb6054060e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9720529 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 Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Uttar Pradesh, Delhi NCR, 201003, India; Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, 201003, India; Jafri S., Department of Administrative Sciences, Imam Abdulrahman Bin Faisal University, Dammam, 34212, Saudi Arabia; Bhardwaj R., Chitkara Business School, Chitkara University, Punjab, Rajpura, 140401, India; Kushwah V.S., School of Computer Science & Engineering, VIT Bhopal University, Madhya Pradesh, Bhopal, 466114, India; Vats P., Department of Computer Science and Engineering, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Gangwar D., Department of Management, Babu Banarasi Das Institute of Technology and Management, Dr. A.P.J Abdul Kalam Technical University, Uttar Pradesh, 226028, India; Dayal M., Department of Information Technology, Bharati Vidyapeeths College of Engineering, New Delhi, 110063, India; Divakaran P., Department of Management, Himalayan University, Arunachal Pradesh, Itanagar Papumpare, 791111, 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 Biomedical Mammography Image Classification Using Patches-Based Feature Engineering with Deep Learning and Ensemble Classifier Subject The topic of the resource Biomedical images; Breast mass classification technique; CNN; Deep learning; Mammography Description An account of the resource In order to reduce the expense of radiologists, deep learning algorithms have recently been used in the mammograms screening field. Deep learning-based methods, like a Convolutional Neural Network (CNN), are now being used to categorize breast lumps. When it involves classifying mammogram imagery, CNN-based systems clearly outperform machine learning-based systems, but they do have certain disadvantages as well. Additional challenges include a dearth of knowledge on feature engineering and the impossibility of feature analysis for the existing patches of pictures, which are challenging to distinguish in low-contrast mammograms. Inaccurate patch assessments, higher calculation costs, inaccurate patch examinations, and non-recovered patched intensity variation are all results of mammogram image patches. This led to evidence that a CNN-based technique for identifying breast masses had poor classification accuracy. Deep Learning-Based Featured Reconstruction is a novel breast mass classification technique that boosts precision on low-contrast pictures (DFN). This system uses random forest boosting techniques together with CNN architectures like VGG 16 and Resnet 50 to characterize breast masses. Using two publicly accessible datasets of mammographic images, the suggested DFN approach is also contrasted with modern classification methods. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Poonia R.C.; Upreti K.; Jafri S.; Parashar J.; Vats P.; Singh J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1046 LNNS, pp. 275-285. 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_29" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-64813-7_29</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200652501&doi=10.1007%2F978-3-031-64813-7_29&partnerID=40&md5=0ca86de482edf8996bc11e8bb67acd80" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200652501&doi=10.1007%2f978-3-031-64813-7_29&partnerID=40&md5=0ca86de482edf8996bc11e8bb67acd80</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 Poonia R.C., Department of Computer Science, CHRIST (Deemed to Be University), Delhi NCR, Ghaziabad, India; Upreti K., Department of Computer Science, CHRIST (Deemed to Be University), Delhi NCR, Ghaziabad, India; Jafri S., Administrative Science Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; Parashar J., Department of Computer Science and Engineering, Dr. Akhilesh Das Gupta Institute of Technology and Management, Delhi, India; Vats P., Department of Computer Science and Engineering, SCSE, Manipal University Jaipur, Rajasthan, Jaipur, India; Singh J., School of Computer Science Engineering and Technology, Bennett University, Greater Noida, 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 Finding Real-Time Crime Detections during Video Surveillance by Live CCTV Streaming Using the Deep Learning Models Subject The topic of the resource Classification; Deep Learning; live CCTV; Real-Time crime detection (RCV); Video Surveillance Description An account of the resource Nowadays, securing people in public places is an emerging social issue in the research of real-Time crime detection (RCD) by video surveillance, in which initial automatic recognition of suspicious objects is considered a prime problem in RCD. Dynamic live CCTV monitoring and finding real-Time crime activities by detecting suspicious objects is required to prevent unusual activities in public places. Continuous live CCTV video surveillance of objects and classification of suspicious activities are essential for real-Time crime detection. Deep training models have greatly succeeded in image and video classifications. Thus, this paper focuses on the use of trustworthy deep learning models to intelligently classify suspicious objects to detect real-Time crimes during live video surveillance by CCTV. In the experimental study, various convolutional neural network (CNN) models are trained using real-Time crime and non-crime videos. Three performance parameters, accuracy, loss, and computational time, are estimated for three variants of CNN models for the real-Time crime classifications. Three categories of videos, i.e., crime video (CV), non-crime video (NCV), and weapon-crime video (WCV), are used in the training of three deep models, CNN, 3D CNN, and Convolutional Long short-Term memory (ConvLSTM). The ConvLSTM scored higher accuracy, lower loss values, and runtime efficiency than CNN and 3D CNN when detecting real-Time crimes. 2024 ACM. Creator An entity primarily responsible for making the resource Poonia R.C.; Upreti K.; Prabu P.; Rajendra Prasad K. Source A related resource from which the described resource is derived ACM International Conference Proceeding Series, pp. 272-277. Publisher An entity responsible for making the resource available Association for Computing Machinery 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/10.1145/3669754.3669794" target="_blank" rel="noreferrer noopener">https://doi.org/10.1145/3669754.3669794</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203828349&doi=10.1145%2F3669754.3669794&partnerID=40&md5=e038488dd6b27ac09fd3edc356e967f4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203828349&doi=10.1145%2f3669754.3669794&partnerID=40&md5=e038488dd6b27ac09fd3edc356e967f4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-840071705-5 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 Poonia R.C., Department of Computer Science, Christ University, Delhi NCR, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR, India; Prabu P., Department of Computer Science, Christ University, Delhi NCR, India; Rajendra Prasad K., Department of Computer Science and Engineering, Institute of Aeronautical Engineering, Telangana, Hyderabad, India https://archives.christuniversity.in/files/original/95eb351ac750e396228651871c966ba1.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 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 Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents 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 Lightning Cards! / Subject The topic of the resource Computer Science Description An account of the resource Patent Number: 202141060863, Applicant: Bundela Disha Hitenbhai. The present system or invention, Lightning Cards, is an online multiplayer card game that utilises computer vision and machine learning techniques in order to deliver a fast-paced reactions card game unheard of not only online, but also as a physical card game. The present system is enabled by way of ML tools to recognise the hand keypoint landmarks and other algorithms for recognising the actual hand gesture. Creator An entity primarily responsible for making the resource Poonia, Ramesh Chandra. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1vDvJBwBPrki5-h1kwnOUSfqqwcSuiNu_/view" target="_blank" title="Lightning Cards!" rel="noreferrer noopener">https://drive.google.com/file/d/1vDvJBwBPrki5-h1kwnOUSfqqwcSuiNu_/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-13 Language A language of the resource English Type The nature or genre of the resource Patent https://archives.christuniversity.in/files/original/1cc244c220ebc2266098f21c8299ec09.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 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 Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents 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 Atendo: The portable attendence recorder / Subject The topic of the resource Computer Science Description An account of the resource Patent Number: 202241019881, Applicant: Kevin Benny. Attendance is the fact of being present or absent at a place or an event. One of the most basic things to understand and analyse the response of an event is by recording the attendance of the event. By tracking the sessions attended by the attendees and how long the attendees stay in the event, it is possible to derive a clear picture of how engaged the event was. Attendance monitoring is very important for examining the success or failure of an event. Tracking session attendance is an easy and accurate way to gather attendee feedback and translate this information into useful data. Creator An entity primarily responsible for making the resource Poonia, Ramesh Chandra. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/1WHuJBOU29HmWqeaKQX8dDqty3o1R0zyD/view" target="_blank" title="Atendo: The portable attendence recorder /" rel="noreferrer noopener">https://drive.google.com/file/d/1WHuJBOU29HmWqeaKQX8dDqty3o1R0zyD/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-18 Language A language of the resource English Type The nature or genre of the resource Patent https://archives.christuniversity.in/files/original/ad840393d73069d63541c76c32d56049.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 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 Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents 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 Vimana / Subject The topic of the resource Communication Description An account of the resource Patent Number: 202241030155, Applicant: Ramesh Chandra Poonia. Drone navigation works by building a map of its surroundings while tracking its position within the map. This allows the drone to demonstrate positional accuracy (the global average URE (User error rate) across all satellites) of < 0.643 m (2.1 ft.) 95% of the lime using the Global Positioning System (GPS). The problem with this technology is twofold. It deploys only L band communication in practice. Creator An entity primarily responsible for making the resource Poonia, Ramesh Chandra. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/17J1tTJKPAkE5tM425Sm7TBDFkRu1XNOX/view" target="_blank" title="Vimana /" rel="noreferrer noopener">https://drive.google.com/file/d/17J1tTJKPAkE5tM425Sm7TBDFkRu1XNOX/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-19 Language A language of the resource English Type The nature or genre of the resource Patent https://archives.christuniversity.in/files/original/73f375705e40042161a309724fae7533.jpg 0b6dfeeadbd8dbf97f5aef738454f6b9 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 Patents Subject The topic of the resource Patent Description An account of the resource Patent Patent Patents 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 3D painting for fracture treatment / Subject The topic of the resource Bio-Medical Engineering Description An account of the resource Patent Number: 202241048127, Applicant: Ramesh Chandra Poonia. The effect of technological advancements has made an impact on the way medical applications are used in the treatment of fracture. The possibility of medical application and technology has immensely grown, and 3D printing and its applications in medical sciences are much explored and found to be acceptable and applicable financially and technically during recent years. While 3D technology is used in diagnosis, 3D printing technology is useful for making treatment and rehabilitation tools. Creator An entity primarily responsible for making the resource Poonia, Ramesh Chandra. Source A related resource from which the described resource is derived <a href="https://drive.google.com/file/d/16piPXfHv88qR9BcLxRHmNCEA0FwZue3Q/view" target="_blank" title="3D painting for fracture treatment /" rel="noreferrer noopener">https://drive.google.com/file/d/16piPXfHv88qR9BcLxRHmNCEA0FwZue3Q/view</a> Publisher An entity responsible for making the resource available Intellectual Property India Date A point or period of time associated with an event in the lifecycle of the resource 2022-05-22 Language A language of the resource English Type The nature or genre of the resource Patent 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 Performance Evaluation of Predicting IoT Malicious Nodes Using Machine Learning Classification Algorithms Subject The topic of the resource Classification Algorithms; Internet of Things (IoT); Machine Learning; Malicious Nodes; Network Security Description An account of the resource The prediction of malicious nodes in Internet of Things (IoT) networks is crucial for enhancing network security. Malicious nodes can significantly impact network performance across various scenarios. Machine learning (ML) classification algorithms provide binary outcomes ("yes" or "no") to accurately identify these nodes. This study implements various classifier algorithms to address the problem of malicious node classification, using the SensorNetGuard dataset. The dataset, comprising 10,000 records with 21 features, was preprocessed and used to train multiple ML models, including Logistic Regression, Decision Tree, Naive Bayes, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Performance evaluation of these models followed the ML workflow, utilizing Python libraries such as scikit-learn, Seaborn, Matplotlib, and Pandas. The results indicated that the Naive Bayes classifier outperformed others with an accuracy of 98.1%. This paper demonstrates the effectiveness of ML classifiers in detecting malicious nodes in IoT networks, providing a robust predictive model for real-time application. The SensorNetGuard dataset is available on the IEEE data port and Kaggle platform. 2024, Prof.Dr. ?skender AKKURT. All rights reserved. Creator An entity primarily responsible for making the resource Poorana S.S.; Wilfred B.N.R.; Rajesh K.R.; Karthik S. Source A related resource from which the described resource is derived International Journal of Computational and Experimental Science and Engineering, Vol-10, No. 3, pp. 341-349. Publisher An entity responsible for making the resource available Prof.Dr. ?skender AKKURT 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/10.22399/ijcesen.395" target="_blank" rel="noreferrer noopener">https://doi.org/10.22399/ijcesen.395</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201698353&doi=10.22399%2Fijcesen.395&partnerID=40&md5=5c1a7dfb66ae39d12ab225d6adf38ab9" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201698353&doi=10.22399%2fijcesen.395&partnerID=40&md5=5c1a7dfb66ae39d12ab225d6adf38ab9</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21499144 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 Poorana S.S., Dr. N.G.P. Arts and Science College, Department of Computer Applications, Tamil Nadu, Coimbatore, 641048, India; Wilfred B.N.R., University of Tech. and Applied Sciences, College of Computing and Information Sciences, Ibri, Oman; Rajesh K.R., Christ University, Department of Computer Science, Karnataka, 560029, India; Karthik S., Kristu Jayanti College, Department of Computer Science (PG), Karnataka, 560077, 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 Additively Composite Model Objective Function for Routing Protocol for Low-Power and Lossy Network Protocol Subject The topic of the resource bottleneck routing; IoT; load balancing; metrics; objective function; RPL Description An account of the resource The Internet of Things (IoT) networks always operate within the context of diverse and constrained characteristics of the devices. Low-Power and Lossy Networks (LLNs) constitute a network architecture commonly utilized in IoT application deployments, facilitating networking and the establishment of paths for data transmission. The Routing Protocol for Low-Power and Lossy Networks (RPL) demonstrates promising capabilities for LLN network operations, supporting IPv4 and IPv6-enabled services. The RPL protocol constructs a Destination Oriented Directed Acyclic Graph (DODAG) logical routing topology based on defined Objective Function (OF) metrics. Routing operations within the DODAG utilize these metrics and constraints to select parent nodes and calculate optimal routes between two nodes. Standardized OFs have traditionally focused on either parent node selection or routing objectives within the DODAG, often treating load balancing and bottleneck optimization separately. However, their combined impact on RPL's effectiveness has been overlooked. This paper introduces an Adaptively Composite Objective Function (AC-OF) approach that considers the combined objectives of DODAG load balancing and optimized routing operations. Through simulation evidence, the paper presents improved network parameters. The AC-OF implementation brings out significant results in the form of a balanced DODAG topology and it has good impacts on data transmission, control overhead messages, parent switching, delay, energy consumption, and node lifetime. 2024 Totem Publisher, Inc. All rights reserved. Creator An entity primarily responsible for making the resource Poorana Senthilkumar S.; Wilfred Blessing N.R.; Subramani B.; Rajesh Kanna R. Source A related resource from which the described resource is derived International Journal of Performability Engineering, Vol-20, No. 5, pp. 300-311. Publisher An entity responsible for making the resource available Totem Publisher 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/10.23940/ijpe.24.05.p5.300311" target="_blank" rel="noreferrer noopener">https://doi.org/10.23940/ijpe.24.05.p5.300311</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207487433&doi=10.23940%2Fijpe.24.05.p5.300311&partnerID=40&md5=38e25d24db663efffff51e2b7756dd53" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207487433&doi=10.23940%2fijpe.24.05.p5.300311&partnerID=40&md5=38e25d24db663efffff51e2b7756dd53</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9731318 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 Poorana Senthilkumar S., Department of Computer Applications, Dr. N.G.P. Arts and Science College, Tamil Nadu, India; Wilfred Blessing N.R., College of Computing and Information Sciences, University of Technology and Applied Sciences, Ibri, Oman; Subramani B., Department of Computer Science, SNMV College of Arts and Science, Tamil Nadu, India; Rajesh Kanna R., Department of Computer Science, Christ University, Karnataka, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 comprehensive investigation of the effect of mineral additives to bituminous concrete Subject The topic of the resource Bituminous concrete; Indirect tensile strength; Mineral additives; Tensile strength ratio Description An account of the resource Research efforts to employ sustainable materials for road construction have been on the rise in recent years. In particular, the use of polymers as additives in asphalt mix has been actively explored by several researchers. Bituminous pavementsnormally constructed in India, have increasing number of premature failures, due to increase in traffic density and noteworthy variations in road temperatures. The modified binders have proven to improve numerous properties of bituminous surfaces such as temperature susceptibility, fatigue life, creep, resistance to permanent deformation and rutting. The present study has focussed on the experimental investigations conducted to evaluate the influence of mineral additives, such as wollostonite and Rice Husk Ash (RHA) on Indirect Tensile Strength (ITS) and Tensile Strength Ratio (TSR) of bituminous concrete (BC)maintaining uniformity of aggregate properties.The results establish that the bituminous concrete blends modified using rice husk ash at 20% and wollostonite at 8%, with hydrated lime are most suitable for practical applications. 2021 Elsevier Ltd. All rights reserved. Creator An entity primarily responsible for making the resource Poorna Prajna S.; Anjum M.I.; Lakshmi P.S.; Gayathri G.; Beulah M.; Sudhir M.R. Source A related resource from which the described resource is derived Materials Today: Proceedings, Vol-46, pp. 714-721. Publisher An entity responsible for making the resource available Elsevier Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.matpr.2020.12.090" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.matpr.2020.12.090</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112573754&doi=10.1016%2Fj.matpr.2020.12.090&partnerID=40&md5=fbbff06c49a7b052e0907c8636309310" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112573754&doi=10.1016%2fj.matpr.2020.12.090&partnerID=40&md5=fbbff06c49a7b052e0907c8636309310</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22147853 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 Poorna Prajna S., Civil Engineering Department, PESCE, Karnataka, Mandya, 571 401, India; Anjum M.I., Civil Engineering Department, GCE, Karnataka, Ramanagaram, 562159, India; Lakshmi P.S., Civil Engineering Department, PESCE, Karnataka, Mandya, 571 401, India; Gayathri G., Civil Engineering Department, ACSCE, Karnataka, Bengaluru, 560074, India; Beulah M., Civil Engineering Department, Christ University, Karnataka, Bengaluru, 560029, India; Sudhir M.R., Civil Engineering Department, Christ University, Karnataka, Bengaluru, 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 Solid-state fermentation of pigment producing endophytic fungus Fusarium solani from Madiwala lake and its toxicity studies Subject The topic of the resource Antimicrobial; Antioxidant; Cytotoxicity; Endophytic fungus; Fusarium solani; Green synthesis; Natural colors; Pigment; Silver nanoparticles; Synthetic colors Description An account of the resource Several consumer products look enticing due to colors and there has been a demand for colors for various applications ever since human civilization started. Although in the primitive days, humans had used natural colors, the wake of the industrial revolution saw the excessive use of diverse types of synthetic colors. Although it looked very fancy initially, slowly scientists discovered the dangers of large-scale use of these colorants. The current demand is for natural colors, and hence, there is a scope for sources of natural colors from biosources. The present study involved the isolation of an endophytic fungus, Fusarium solani producing a red pigment from the polluted waters of Madiwala lake in Bangalore. The fungal extract showed good antimicrobial and moderate antioxidant properties. Cytotoxicity assays using brine shrimps proved negligible toxicity which is a positive trait for natural colorants for safer applications in industries. Media optimization and solid state fermentation were carried out to improve the yield of the fungal pigment and also to formulate a cheaper media for fungal multiplication and pigment production. Green synthesis of silver nanoparticles was also carried out with the fungal extract and the nanoparticles were characterized. Thus, the present study provides an option for the extraction of environment friendly natural colorant from the fungus F. solani for potential industrial applications. 2024 Bhoomika Prakash Poornamath, et al. Creator An entity primarily responsible for making the resource Poornamath B.P.; Sarojini S.; Jayaram S.; Biswas S.; Kaloor A.; Umesh M. Source A related resource from which the described resource is derived Journal of Applied Biology and Biotechnology, Vol-12, No. 2, pp. 264-272. Publisher An entity responsible for making the resource available Open Science Publishers LLP 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/10.7324/JABB.2024.143030" target="_blank" rel="noreferrer noopener">https://doi.org/10.7324/JABB.2024.143030</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185946290&doi=10.7324%2FJABB.2024.143030&partnerID=40&md5=029a8e30a9f08c328888c27ad7d53d04" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185946290&doi=10.7324%2fJABB.2024.143030&partnerID=40&md5=029a8e30a9f08c328888c27ad7d53d04</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 2347212X | LS; 2023-2024; Vol-2; 0645-0646 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 Poornamath B.P., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Sarojini S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Jayaram S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Biswas S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Kaloor A., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Umesh M., Department of Life 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 Template based speech enhancement of disordered speech Subject The topic of the resource correlation coefficient; differently abled; Directly Radiated EL Noise (DREL); disordered speech; Electrolarynx (EL); F0 contour; Fundamental frequency - Pitch; K-measns algorithm; laryngectomy K-NN algrorithm; Larynx disorder; spectral subtraction; speech enhancement; speech intelligibility; speech naturalness; speech processing; Template matching algorithm Description An account of the resource In this paper, we have taken Electro-Larynx (EL) speech and have improved the speech quality, electro-larynx speech was improved in terms of naturalness and intelligibility by introducing variations in the F0-contour and template matching with correlation coefficient. Initially, we introduced two different speech signals, the first speech signal introduced was healthy speech signal and the second speech signal introduced was disordered speech signal. Here, the second speech signal, the disordered speech is taken as the EL speech. The fundamental frequency or pitch was extracted first from the two inputed speech signals, then the contour of each fundamental frequency was extracted from the two input speech signals. Using these extracted features of fundamental frequency the gender classification by K-means algorithm was instigated. The same process was implemented with F0 contour features which was extracted using K-NN algorithm. EL speech contains directly radiated electrolarynx noise (DREL). The noise was filtered out using spectral subtraction algorithm. Once DREL noise is removed from EL speech, the quality of the speech was greatly improved. Then EL enhanced speech signal is compared and mapped with healthy speech signal using template matching algorithm with the help of correlation coefficient, this improves the overall quality, that is the naturalness and intelligibity of the introduced disordered speech signal. This technique helps solve the major problem of speech faced by differently abled persons with larynx disorder. 2016 IEEE. Creator An entity primarily responsible for making the resource Poornima K.A.; Inbanila K. Source A related resource from which the described resource is derived Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016 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 2016-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCPCT.2016.7530254" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCPCT.2016.7530254</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992124420&doi=10.1109%2FICCPCT.2016.7530254&partnerID=40&md5=771c8c03a7a4c853d9120b9470f254e5" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992124420&doi=10.1109%2fICCPCT.2016.7530254&partnerID=40&md5=771c8c03a7a4c853d9120b9470f254e5</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-150901277-0 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 Poornima K.A., Department of ECE, Christ University, Faculty of Engineering, Bangalore, India; Inbanila K., Department of ECE, Christ University, Faculty of 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 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 Modelling Networks withAttached Storage Using Perfect Italian Domination Subject The topic of the resource Corona product of graphs; Domination number; Join of graphs; Perfect Italian domination Description An account of the resource Network-attached storage (NAS) is how data is stored and shared among hosts through a configured network. This is cheaper yet the best solution for sharing and using any huge unstructured data in an organization. Optimal distribution of NAS in a network of servers can be done using the concept of Perfect Italian Domination (PID). PID is a vertex labelling where the vertices of a graph G are labelled by 0, 1, 2 such that a vertex with label 0 should have a neighbourhood where the summation of the labels is exactly 2. The minimum possible sum of the labels obtained for graph G is its PID number. A network in an organization can have any structure. It can be highly interconnected, like a graph obtained from the Join of two graphs or the Corona product of two graphs. Hence, this paper discusses the PID of different graphs generated by the Join and the Corona products. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Poovathingal A.; Kureethara J.V. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-832, pp. 23-33. 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/10.1007/978-981-99-8129-8_3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-8129-8_3</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187799578&doi=10.1007%2F978-981-99-8129-8_3&partnerID=40&md5=a74e40d3c899b9b63020e8a102a48516" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187799578&doi=10.1007%2f978-981-99-8129-8_3&partnerID=40&md5=a74e40d3c899b9b63020e8a102a48516</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981998128-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Poovathingal A., Department of Mathematics, Christ University, Bangalore, India; Kureethara J.V., Department of Mathematics, Christ 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 On Some Graphs Whose Domination Number Is thePerfect Italian Domination Number Subject The topic of the resource Domination number; Independent set; Join operator; perfect italian domination Description An account of the resource Perfect Italian Domination (PID) is a vertex labelling of a graph G by numbers from the set such that a vertex in G labelled 0 has a neighbourhood where the summation of the labels of the vertices in it is precisely 2. The summation of labels on the vertices of the graph which satisfy the PID labelling is known as its PID number, and is the minimum possible PID number of a graph G. We find some characterization of graphs for which . We also find a lower bound for |V(G)|, which satisfies the same. Further, we discuss the graphs that satisfies or . A realisation problem is used to prove that PID cannot be bounded by a scalar multiple of the Domination number. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Poovathingal A.; Kureethara J.V. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-869 LNNS, pp. 191-200. 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/10.1007/978-981-99-9040-5_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9040-5_13</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190359075&doi=10.1007%2F978-981-99-9040-5_13&partnerID=40&md5=f982d7f6b7c83bb2e9bcd23f9d800b8b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190359075&doi=10.1007%2f978-981-99-9040-5_13&partnerID=40&md5=f982d7f6b7c83bb2e9bcd23f9d800b8b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999039-9 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 Poovathingal A., Department of Mathematics, Christ University, Bangalore, India; Kureethara J.V., Department of Mathematics, Christ 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 Some characterizations of Gallai graphs Description An account of the resource Gallai graph of a graph G is a graph whose vertices are the edges of G and the adjacency of the vertices depends on whether they are part of a triangle or not in G. We find some forbidden subgraph characterization of graphs for which Gallai graph is either a trivially perfect graph or a 3-sun-free graph or an interval graph. 2020 Author(s). Creator An entity primarily responsible for making the resource Poovathingal A.; Kureethara J.V. Source A related resource from which the described resource is derived AIP Conference Proceedings, Vol-2236 Publisher An entity responsible for making the resource available American Institute of Physics Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1063/5.0006807" target="_blank" rel="noreferrer noopener">https://doi.org/10.1063/5.0006807</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085696718&doi=10.1063%2F5.0006807&partnerID=40&md5=5d3db75b48a9812a2a193b5d47bb4359" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085696718&doi=10.1063%2f5.0006807&partnerID=40&md5=5d3db75b48a9812a2a193b5d47bb4359</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 0094243X; ISBN: 978-073541995-7 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 Poovathingal A., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, India; Kureethara J.V., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, India