506 20 16481 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Potato Leaf Disease Identification using Hybrid Deep Learning Model Subject The topic of the resource CNN; leaf disease; LSTM; OCNN-LSTM; Potato Description An account of the resource The potato is one of the most significant crops in the world. However, it is prone to several leaf diseases that can result in significant productivity losses, leading to economic challenges. Early and precise disease identification is essential for sensitive crops like potatoes. Deep learning approaches have demonstrated excellent potential in image-based disease classification tasks in recent years. This paper presents a hybrid strategy for classifying potato leaf image diseases by integrating Optimised Convolutional Neural Network (OCNN) and Long Short-Term Memory (LSTM) networks. The Adaptive Shark Smell Optimisation (ASSO) technique is used to optimize the weights of CNN models. The CNN component is initially used to extract pertinent characteristics from Potato leaves, capturing significant visual patterns related to various diseases. These extracted features are then fed into the LSTM model, which utilizes its sequential learning capability to model the temporal dependencies among the extracted features. The model performance is analyzed based on Accuracy, Precision, Recall, and F1-score criteria. Experimental results showed that the hybrid OCNN-LSTM model outperforms the individual CNN, LSTM, and MobileNet models. The proposed model results are compared with existing state-of-the-art work, and it was found that the OCNN-LSTM model performed better and received 99.02% accuracy. 2023 IEEE. Creator An entity primarily responsible for making the resource Patil M.A.; Manohar M. Source A related resource from which the described resource is derived 2023 International Conference on Network, Multimedia and Information Technology, NMITCON 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/NMITCON58196.2023.10276091" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/NMITCON58196.2023.10276091</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175401706&amp;doi=10.1109%2FNMITCON58196.2023.10276091&amp;partnerID=40&amp;md5=d88357d877dadc48b14463f596e08d74" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175401706&amp;doi=10.1109%2fNMITCON58196.2023.10276091&amp;partnerID=40&amp;md5=d88357d877dadc48b14463f596e08d74</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835030082-6 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 Patil M.A., School O F Engineering and Technology, Dept, of Computer Science and Engineering Christ (Deemed to Be University), Bengaluru, India; Manohar M., School O F Engineering and Technology, Dept, of Computer Science and Engineering Christ (Deemed to Be University), 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 A Comprehensive Review onCrop Disease Prediction Based onMachine Learning andDeep Learning Techniques Subject The topic of the resource Classification; Crop disease; DL; Leaf image; ML; Segmentation Description An account of the resource Leaf diseases cause direct crop losses in agriculture, and farmers cannot detect the disease early. If the diseases are not detected early and correctly, the farmer must undergo huge losses. It may lead to the wrong pesticide or over pesticide, directly affect crop productivity and economy, and indirectly affect human health. Sensitive crops have various leaf diseases, and early prediction of these diseases remains challenging. This paper reviews several machine learning (ML) and deep learning (DL) methods used for different crop disease segmentation and classification. In the last few years, computer vision and DL techniques have made tremendous progress in object detection and image classification. The study summaries the available research on different diseases on various crops based on machine learning (ML) and deep learning (DL) techniques. It also discusses the data sets used for research and the accuracy and performance of existing methods. It does mean that the methods and available data sets presented in this paper are not projected to replace published solutions for crop disease identification, perhaps to enhance them by finding the possible gaps. Seventy-five articles are analysed and reviewed to find essential issues that involve additional study for future research in this domain to promote continuous progress for data sets, methods, and techniques. It mainly focuses on image segmentation and classification techniques used to solve agricultural problems. Finally, this paper provides future research scope and challenges, limitations, and research gaps. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Patil M.A.; Manohar M. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-608, pp. 481-503. 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/10.1007/978-981-19-9225-4_36" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9225-4_36</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150988733&amp;doi=10.1007%2F978-981-19-9225-4_36&amp;partnerID=40&amp;md5=961c4f261e23cca3921325b7f5ad35ac" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150988733&amp;doi=10.1007%2f978-981-19-9225-4_36&amp;partnerID=40&amp;md5=961c4f261e23cca3921325b7f5ad35ac</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981199224-7 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 Patil M.A., Department of Computer Science and Engineering, School of Engineering and Technology, Christ (Deemed to be University), Karnataka, Bangalore, 560074, India, Department of Information Technology, Vasavi College of Engineering, Telangana, Hyderabad, 500032, India; Manohar M., Department of Computer Science and Engineering, School of Engineering and Technology, Christ (Deemed to be University), Karnataka, 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 Hybrid Deep Learning-Based Potato andTomato Leaf Disease Classification Subject The topic of the resource Crop disease; Hybrid model; MobileNet; OCNN-OLSTM; ResNet50 Description An account of the resource Predicting potato and tomato leaf disease is vital to global food security and economic stability. Potatoes and tomatoes are among the most important staple crops, providing essential nutrition to millions worldwide. However, many tomato and potato leaf diseases can seriously reduce food productivity and yields. We are proposing a hybrid deep learning model that combines optimized CNN (OCNN) and optimized LSTM (OLSTM). The weight values of LSTM and CNN models are optimized using the modified raindrop optimization (MRDO) algorithm and the modified shark smell optimization (MSSO) algorithm, respectively. The OCNN model is used to extract potato leaf image features and then fed into the OLSTM model, which handles data sequences and captures temporal dependencies from the extracted features. Precision, recall, F1-score, and accuracy metrics are used to analyze the output of the proposed OCNN-OLSTM model. The experimental performance is compared without optimizing the CNN-LSTM model, individual CNN and LSTM models, and existing MobileNet and ResNet50 models. The presented model results are compared with existing available work. We have received an accuracy of 99.25% potato and 99.31% for tomato. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Patil M.A.; Manohar M.; Laxuman C.; Parane K.; Dodamani B.M.; Sunkad G. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-891, pp. 157-174. 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/10.1007/978-981-99-9524-0_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-9524-0_13</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187647518&amp;doi=10.1007%2F978-981-99-9524-0_13&amp;partnerID=40&amp;md5=b36ccd6a30bf9b01413f71cd4ad5723a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187647518&amp;doi=10.1007%2f978-981-99-9524-0_13&amp;partnerID=40&amp;md5=b36ccd6a30bf9b01413f71cd4ad5723a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981999523-3 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 Patil M.A., Department of Computer Science and Engineering, Christ (Deemed to be University) School of Engineering and Technology, Kengeri, Karnataka, Bengaluru, 560074, India, Department of Computer Science and Engineering, G. Narayanamma Institute of Technology and Science, Shaikpet, Telangana, Hyderabad, 500104, India; Manohar M., Department of Computer Science and Engineering, Christ (Deemed to be University) School of Engineering and Technology, Kengeri, Karnataka, Bengaluru, 560074, India; Laxuman C., Zonal Agricultural Research Station, UAS-R, Karnataka, Kalaburagi, 585101, India; Parane K., NITK Surathkal, Karnataka, Surathkal, India; Dodamani B.M., Zonal Agricultural Research Station, UAS-R, Karnataka, Kalaburagi, 585101, India; Sunkad G., University of Agricultural Sciences, Karnataka, Raichur, 584104, 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 Sensitive crop leaf disease prediction based on computer vision techniques with handcrafted features Subject The topic of the resource ADNN; ARDO; CNN; LSTM; OLSTM-CNN Description An account of the resource Agricultural production is considered the primary source of the economy of many countries. Tomato and Potatoes are the most sensitive and consumable vegetables worldwide. However, during the growth of these crops, they suffer from many leaf diseases, which lead to loss of productivity and economy of the farmers. Many farmers detect and find plant diseases that are more time-consuming, expensive, and require expert decisions following the naked eye method. Therefore, early and accurate diagnosis of Tomato and Potato crops leaf diseases plays a vital role in sustainable agriculture. So, this research paper proposes an efficient leaf disease classification model based on computer vision techniques. The proposed Adaptive Deep Neural Network (ADNN) leaf disease classification method is a hybrid model which combines an optimized long short-term memory (OLSTM) and convolution neural network (CNN). The weight values supplied in the LSTM classifier are optimally selected using the Adaptive Raindrop Optimization algorithm. The handcrafted features are extracted from the segmented image and fused with the hybrid deep neural network to improve the classifier performance. The ADNN method consists of five steps: preprocessing, feature extraction, segmentation, handcrafted feature extraction, and classification. At first, the images are given to the preprocessing stage to remove the noise from leaf images. Then, the image-affected portion is segmented using an enhanced radial basis function neural network. After the segmentation process, the segmented image is given as an input to the adaptive deep neural network (ADNN) that classifies various types of diseases in the Potato and Tomato leaves. The efficiency of the ADNN model based on the OLSTM-CNN approach is determined concerning multiple metrics, namely Accuracy, Precision, Recall, F-measure, Specificity, and Sensitivity. The ADNN model achieved the best Accuracy of 98.02% for Tomatoes and 98% for Potatoes. The ADNN is compared with existing state-of-the-art CNN, LSTM, ResNet50, and MobileNet techniques. The performance analysis proved that the ADNN model improved efficiency in terms of all metrics and methods. 2023, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. Creator An entity primarily responsible for making the resource Patil M.A.; Manur M. Source A related resource from which the described resource is derived International Journal of System Assurance Engineering and Management, Vol-14, No. 6, pp. 2235-2266. 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s13198-023-02066-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s13198-023-02066-0</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168140856&amp;doi=10.1007%2Fs13198-023-02066-0&amp;partnerID=40&amp;md5=5a8adb0285259ccdafa99c33cc047ac4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168140856&amp;doi=10.1007%2fs13198-023-02066-0&amp;partnerID=40&amp;md5=5a8adb0285259ccdafa99c33cc047ac4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9756809 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 Patil M.A., Department of Computer Science and Engineering, Christ(Deemed to be University) School of Engineering and Technology, Kengeri, Karnataka, Bengaluru, 560074, India, Department of Computer Science and Engineering, G. Narayanamma Institute of Technology and Science, Shaikpet, Telangana, Hyderabad, 500104, India; Manur M., Department of Computer Science and Engineering, Christ(Deemed to be University) School of Engineering and Technology, Kengeri, Karnataka, 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 Smart Attendance Management System using IoT Subject The topic of the resource Biometrics authentication; IoT; MySQLDB; PiCam; Raspberry Pi Description An account of the resource Taking student attendance is mandatory in an educational organization, and maintaining those attendance plays a vital role. The conventional way of taking student attendance in any institution is time-consuming and challenging, because in the conventional procedure taking attendance/Roll call is performed manually by calling student names as per their roll numbers and marking 'absent(A)' or 'present(P)' on the attendance/logbook accordingly in every class per day. To improve teaching efficiency/teaching time in classrooms by reducing the time required for Roll call's, we have proposed a biometric student attendance system based on IoT. The proposed system records students' attendance using the facial-based biometric system and stores the attendance details on the server through the internet. In this system, the Raspberry pi camera captures the student face images and compares them with the stored images in the database. If the captured image is comparable with the stored image, then the student's attendance is recorded on the remote server as a present(P) in class; otherwise, attendance is recorded as absent (A). The developed system has been tested for sample classes, and the results proved that the system is simple, cost-effective, and portable for managing students' attendance. 2022 IEEE. Creator An entity primarily responsible for making the resource Patil M.A.; Parane K.; Sivaprasad D.D.; Poojara S.; Lamani M.R. Source A related resource from which the described resource is derived 2022 2nd International Conference on Computer Science, Engineering and Applications, ICCSEA 2022 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/ICCSEA54677.2022.9936433" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCSEA54677.2022.9936433</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142369430&amp;doi=10.1109%2FICCSEA54677.2022.9936433&amp;partnerID=40&amp;md5=05e8bead475330ef500fc8728f1e3ef4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142369430&amp;doi=10.1109%2fICCSEA54677.2022.9936433&amp;partnerID=40&amp;md5=05e8bead475330ef500fc8728f1e3ef4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166545834-4 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 Patil M.A., Vasavi College of Engineering, Department of It, Hyderabad, Telangana, India; Parane K., Nit Surathkal, Dept. of Cse, Karnataka, India; Sivaprasad D.D., Kampala International University, School of Computing and It, Kampala, Uganda; Poojara S., Institute of Cs, University of Tartu, Tartu, Estonia; Lamani M.R., Christ (Deemed to Be University), Kengeri Campus, Dept. of Cse, Bangalore, 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 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 A colorimetric chemosensor for distinct color change with (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol to detect Cu2+ in real water samples Subject The topic of the resource Chemosensor; Colorimetry; DFT studies; Schiff base; Water samples Description An account of the resource The study reports the synthesis of chemosensor (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol (C1), a highly sensitive, colorimetric metal probe that shows distinct selectivity for the detection of Cu2+ ion in various real water samples. Upon complexation with Cu2+ in CH3OH/H2O (60:40 v/v) (aqueous methanol), the C1 demonstrate significant enhancement in the absorption at 250nm and 300nm with a color change from light yellow to brown which was visualized using naked-eye. Therefore, these properties make C1 as an effective candidate for on-site Cu2+ ions detection. The emission spectrum of C1 illustrated TURN-ON recognition of Cu2+ with a limit of detection (LOD) of 46nM. Furthermore, Density Functional Theory (DFT) calculations were performed to better understand the interactions between C1 and Cu2+. The obtained results suggested that the electron clouds present around the NH2 innitrogen and sulfur in SH play a pivotal role in the formation of a stable complex. The computational results were in good agreement with the experimental UVvisible spectrometry results. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to The Japan Society for Analytical Chemistry. Creator An entity primarily responsible for making the resource Patil N.; Dhake R.B.; Phalak R.; Fegade U.; Inamuddin; Naushad M.; Bathula C.; Kanchi S.; Govender K. Source A related resource from which the described resource is derived Analytical Sciences, Vol-39, No. 8, pp. 1413-1423. 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s44211-023-00355-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s44211-023-00355-z</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160933423&amp;doi=10.1007%2Fs44211-023-00355-z&amp;partnerID=40&amp;md5=b1ff4230be21abf2ed537c6e61f3854a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160933423&amp;doi=10.1007%2fs44211-023-00355-z&amp;partnerID=40&amp;md5=b1ff4230be21abf2ed537c6e61f3854a</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 9106340; PubMed ID: 37280486; CODEN: ANSCE 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 Patil N., Department of Chemistry, D. D. N. Bhole College, Bhusawal, MH, Jalgaon, 425201, India, Department of Chemistry, Bhusawal Arts, Science and P. O. Nahata Commerce College, Bhusawal, MH, Jalgaon, 425201, India; Dhake R.B., Department of Chemistry, D. D. N. Bhole College, Bhusawal, MH, Jalgaon, 425201, India; Phalak R., Department of Chemistry, D. D. N. Bhole College, Bhusawal, MH, Jalgaon, 425201, India; Fegade U., Department of Chemistry, Bhusawal Arts, Science and P. O. Nahata Commerce College, Bhusawal, MH, Jalgaon, 425201, India; Inamuddin, Advanced Functional Materials Laboratory, Department of Applied Chemistry, Zakir Husain College of Engineering and Technology, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, 202002, India; Naushad M., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, Saudi Arabia; Bathula C., Division of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea; Kanchi S., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, 560 029, India; Govender K., Department of Chemical Sciences, Doornfontein Campus, University of Johannesburg, P. O. Box 17011, Johannesburg, 2028, South Africa, National Institute for Theoretical and Computational Sciences (NITheCS), Stellenbosch, South Africa 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 Liberalisation and cashew industry: evidence from India (1965 to 2018) Subject The topic of the resource cashew industry; India; liberalisation; regression Description An account of the resource We examine the impact of liberalisation on production, import, export and area under cultivation of cashew industry in India during 1965 to 2018 period using regression method. We divide data into two sub-periods. The liberalisation and pre-liberalisation period is from 1965 to 1991 and the post-liberalisation period covers the period from 1992 to 2018. We find that cashew production is not influenced post trade liberalisation. This study also finds trade liberalisation has a significant and positive impact on export. Further, we reveal an insignificant impact of liberalisation on import. This study show that the area under cultivation is not changed after the trade liberalisation. 2024 Inderscience Publishers. All rights reserved. Creator An entity primarily responsible for making the resource Patil P.; Faniband M. Source A related resource from which the described resource is derived International Journal of Business and Globalisation, Vol-36, No. 4, pp. 373-380. Publisher An entity responsible for making the resource available Inderscience Publishers Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1504/IJBG.2024.138015" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJBG.2024.138015</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191088219&amp;doi=10.1504%2FIJBG.2024.138015&amp;partnerID=40&amp;md5=20d69b715e2a57dae6c69eb2a089fcd8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191088219&amp;doi=10.1504%2fIJBG.2024.138015&amp;partnerID=40&amp;md5=20d69b715e2a57dae6c69eb2a089fcd8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17533627 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 Patil P., Ministry of Commerce and Industry (APEDA), Government of India, India; Faniband M., Department of Commerce, CHRIST (Deemed to be University, 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 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 Dandelion Algorithm for Optimal Location and Sizing of Battery Energy Storage Systemsin Electrical Distribution Networks Subject The topic of the resource Dandelion algorithm; Energy storage system; Loss minimization; Optimization; Radial distribution network Description An account of the resource This paper describes a new way to improve the performance of an EDN by integrating distributed battery energy storage systems (BESs) in the best way possible. This method is based on the Dandelion Algorithm (DA). The search space for BES locations is first predetermined using loss sensitivity factors (LSFs), and then DA is used to determine the optimal locations and sizes. The reduction of real power distribution loss is regarded as the primary objective function, and the impact of BESs is extended to examine the network voltage profile, voltage stability, and GHG emissions. IEEE 33-busEDN is used to calculate the computational efficiency of LSF-DA. Results show that DA is more efficient than Archimedes optimization (AOA), future search algorithm(FSA), pathfinder algorithm(PFA), and butterfly optimization algorithm(BOA) algorithms. Furthermore, the results show that the proposed DA enhances all technological and environmental factors and RDN performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Patil R.; Janamala V. Source A related resource from which the described resource is derived Studies in Computational Intelligence, Vol-1117, pp. 315-323. 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/10.1007/978-3-031-43009-1_26" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-43009-1_26</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183400067&amp;doi=10.1007%2F978-3-031-43009-1_26&amp;partnerID=40&amp;md5=e0a7ab334850a0ad735e0f50fe9c97fa" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183400067&amp;doi=10.1007%2f978-3-031-43009-1_26&amp;partnerID=40&amp;md5=e0a7ab334850a0ad735e0f50fe9c97fa</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1860949X 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 Patil R., SKN Sinhgad College of Engineering, Maharashtra, Pamdharpur, India; Janamala V., CHRIST (Deemed to be University), Karnataka, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Advancements in Deep Learning Techniques for Potato Leaf Disease Identification Using SAM-CNNet Classification Subject The topic of the resource convolutional neural network; data normalization; GoogLeNet; potato leaf diseases; Spatial Attention Mechanism Description An account of the resource Potato leaf diseases like Late Blight and Early Blight significantly challenge potato cultivation, impacting crop yield and quality worldwide. Potatoes are a staple for over a billion people and crucial for food security, especially in developing countries. The economic impact is substantial, with Late Blight alone causing annual damages over $6 billion globally. Effective detection and management are essential to mitigate these effects on agricultural productivity and economic stability. This paper presents a novel approach to potato leaf disease detection using advanced deep learning and optimization techniques. Key components include data normalization to eliminate noise, feature extraction using GoogLeNet, and hyperparameter tuning through the Elk Herd Optimizer (EHO). Additionally, a Spatial Attention Mechanism and Convolutional Neural Network (SAM-CNNet) are employed for robust classification. The method is validated using the Plant Village dataset, yielding an accuracy of 98.58%, with precision of 97.68%, recall of 98.42%, and F1-Score of 98.21%, demonstrating exceptional performance and reliability. This study highlights the proposed approach's efficacy in accurately identifying and classifying potato leaf diseases, offering a promising solution for precision agriculture and crop management. Copyright: 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license. Creator An entity primarily responsible for making the resource Patil S.; Satya A.D.V.; Bajjuri U.R.; Damarapati P.K.; Manur M.; Thirumalraj A.; Vatambeti R. Source A related resource from which the described resource is derived Ingenierie des Systemes d'Information, Vol-29, No. 5, pp. 2021-2030. Publisher An entity responsible for making the resource available International Information and Engineering Technology Association 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/10.18280/isi.290533" target="_blank" rel="noreferrer noopener">https://doi.org/10.18280/isi.290533</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207450988&amp;doi=10.18280%2Fisi.290533&amp;partnerID=40&amp;md5=1a9b37d4fe16dfe4c3d8ee4fe647d79a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207450988&amp;doi=10.18280%2fisi.290533&amp;partnerID=40&amp;md5=1a9b37d4fe16dfe4c3d8ee4fe647d79a</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 16331311 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 Patil S., Department of Information Technology, MLR Institute of Technology, Hyderabad, 500043, India; Satya A.D.V., Department of Chemistry, New Horizon College of Engineering, Bengaluru, 560103, India; Bajjuri U.R., Department of Computer Science and Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, 521230, India; Damarapati P.K., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, 522302, India; Manur M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Thirumalraj A., Department of Computer Science and Engineering, K. Ramakrishna College of Technology, Trichy, 621112, India; Vatambeti R., School of Computer Science and Engineering, VIT-AP University, Vijayawada, 522237, 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 Reviews Review Faculty Publications- Reviews 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 Text Mining-A Comparative Review of Twitter Sentiments Analysis Subject The topic of the resource airline sentiments; decision trees; gaussian naive bayes; gini index; machine learning; multinomial naive bayes; multinomial naive bayes with bagging; Opinion mining; random forest Description An account of the resource Background: Text mining derives information and patterns from textual data. Online social media platforms, which have recently acquired great interest, generate vast text data about human behaviors based on their interactions. This data is generally ambiguous and unstructured. The data includes typing errors and errors in grammar that cause lexical, syntactic, and semantic uncertainties. This results in incorrect pattern detection and analysis. Researchers are employing various text mining techniques that can aid in Topic Modeling, the detection of Trending Topics, the identification of Hate Speeches, and the growth of communities in online social media net-works. Objective: This review paper compares the performance of ten machine learning classification techniques on a Twitter data set for analyzing users' sentiments on posts related to airline usage. Methods: Review and comparative analysis of Gaussian Naive Bayes, Random Forest, Multinomial Naive Bayes, Multinomial Naive Bayes with Bagging, Adaptive Boosting (AdaBoost), Optimized AdaBoost, Support Vector Machine (SVM), Optimized SVM, Logistic Regression, and Long-Short Term Memory (LSTM) for sentiment analysis. Results: The results of the experimental study showed that the Optimized SVM performed better than the other classifiers, with a training accuracy of 99.73% and testing accuracy of 89.74% compared to other models. Conclusion: Optimized SVM uses the RBF kernel function and nonlinear hyperplanes to split the dataset into classes, correctly classifying the dataset into distinct polarity. This, together with Feature Engineering utilizing Forward Trigrams and Weighted TF-IDF, has improved Optimized SVM classifier performance regarding train and test accuracy. Therefore, the train and test accuracy of Optimized SVM are 99.73% and 89.74% respectively. When compared to Random Forest, a mar-ginal of 0.09% and 1.73% performance enhancement is observed in terms of train and test accuracy and 1.29% (train accuracy) and 3.63% (test accuracy) of improved performance when compared with LSTM. Likewise, Optimized SVM, gave more than 10% of enhanced performance in terms of train accuracy when compared with Gaussian Nae Bayes, Multinomial Nae Bayes, Multinomial Nae Bayes with Bagging, Logistic Regression and a similar enhancement is observed with Ada-Boost and Optimized AdaBoost which are ensemble models during the experimental process. Optimized SVM also has outperformed all the classification models in terms of AUC-ROC train and test scores.. 2024 Bentham Science Publishers. Creator An entity primarily responsible for making the resource Patil S.; Subil D.; Nasar N.; Kokatnoor S.A.; Krishnan B.; Kumar S. Source A related resource from which the described resource is derived Recent Advances in Computer Science and Communications, Vol-17, No. 1, pp. 21-37. Publisher An entity responsible for making the resource available Bentham Science Publishers Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.2174/2666255816666230726140726" target="_blank" rel="noreferrer noopener">https://doi.org/10.2174/2666255816666230726140726</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185523490&amp;doi=10.2174%2F2666255816666230726140726&amp;partnerID=40&amp;md5=f786f90143f1c9275a7e687287251656" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185523490&amp;doi=10.2174%2f2666255816666230726140726&amp;partnerID=40&amp;md5=f786f90143f1c9275a7e687287251656</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 26662558 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 Review Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patil S., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, Bangalore, India; Subil D., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, Bangalore, India; Nasar N., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, Bangalore, India; Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, Bangalore, India; Krishnan B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, Bangalore, India; Kumar S., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, 74, 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 Lattice thermal conduction in suspended molybdenum disulfide monolayers with defects Subject The topic of the resource Grain boundary scattering; Lattice thermal conductivity; MoS ₂ monolayer ; N-process; Vacancy scattering Description An account of the resource In this study, we investigated the effect of lattice defects comprising vacancies and boundaries on the lattice thermal conductivity (LTC), ? p , of suspended molybdenum disulfide monolayers (MLs) over a wide temperature range (1 &lt; T &lt; 500 K). Using the phonon Boltzmann formalism, the acoustic phonons were considered to be scattered by the sample and grain boundaries, isotopic impurities, vacancies, and other phonons via Umklapp and normal (N-) processes. ? p was evaluated using a modified Callaway model by considering the in-plane longitudinal acoustic and transverse acoustic phonons, and out-of-plane flexural acoustic phonon modes. We demonstrated the need to include the often neglected non-resistive N-processes when evaluating the LTC. Numerical calculations of the temperature dependence of the LTC for crystalline and polycrystalline MoS 2 MLs showed the dominance of sample-dependent scattering mechanisms at low temperatures (T &lt; 100 K) and of phonon-phonon scattering at higher temperatures, where the N-processes played an important role. The effects of vacancies and boundaries were to alter the behavior and suppress the magnitude of the LTC. The suppression due to vacancies was greater in crystalline MLs with specular surfaces and in polycrystalline MLs with larger grain sizes. The calculations compared well with recent thermal conductivity data obtained for polycrystalline samples. The need for further investigations is suggested. 2018 Elsevier Ltd Creator An entity primarily responsible for making the resource Patil S.B.; Sankeshwar N.S.; Mulimani B.G. Source A related resource from which the described resource is derived Journal of Physics and Chemistry of Solids, Vol-129, pp. 31-40. 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 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.jpcs.2018.12.032" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jpcs.2018.12.032</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059463464&amp;doi=10.1016%2Fj.jpcs.2018.12.032&amp;partnerID=40&amp;md5=2f6169c84150d52ea6831725538a78e1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059463464&amp;doi=10.1016%2fj.jpcs.2018.12.032&amp;partnerID=40&amp;md5=2f6169c84150d52ea6831725538a78e1</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 223697; CODEN: JPCSA 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 Patil S.B., Department of Physics, Karnatak University, Dharwad, 580003, Karnataka, India; Sankeshwar N.S., Department of Physics, Karnatak University, Dharwad, 580003, Karnataka, India, Department of Physics, Christ University, Bangalore, 560029, Karnataka, India; Mulimani B.G., Department of Physics, Karnatak University, Dharwad, 580003, 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 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 Effect of vacancies on thermopower of molybdenum disulfide monolayers Subject The topic of the resource monolayer MoS₂ ; thermopower; vacancies Description An account of the resource A detailed theoretical investigation of the effect of scattering of electrons and phonons by lattice vacancies in molybdenum disulfide (MoS2) monolayers (MLs) on diffusion, S d, and phonon-drag, S g, components of thermoelectric power (TEP), S, is presented over a wide-temperature range (1 &lt; T &lt; 300 K) using the Boltzmann transport formalism. The diffusion component is assumed to be influenced, not only by vacancies via short-range and Coulomb disorder scattering, but also by charged impurities (CIs) and acoustic and optical phonons. In the case of S g, the phonons are considered to be scattered, besides the vacancies, by sample boundaries, substitutional isotopic impurities, as well as other phonons via both N- and U-processes. Numerical calculations of S d and S g, as functions of temperature and vacancy defect density are presented for MoS2 MLs with n s = 1017 m-2 supported on SiO2/Si substrates. The role of carrier scatterings by mono-sulfur and mono-molybdenum vacancies in influencing the overall electron and phonon relaxation rates and in determining S d and S g are investigated. The behavior of S d and S g is found to be noticeably influenced by vacancy scattering. The influence on S d is seen to be more for mono-sulfur vacancies for densities lesser than 1%. The influence, is to enhance S d slightly for MLs with realizable CI concentrations. On the other hand, S g is found to depend sensitively on the vacancy disorder for T &lt; 50 K; a S-vacancy density of 0.1% is found to suppress the characteristic peak of S g by almost 60%. The extent of reduction in the characteristic peak of S g, observable in low temperature measurements of S, can provide information about defect density. The calculations demonstrate that defect engineering of MoS2 ML systems can be used to tune their thermoelectric performance. A need for detailed experimental studies is suggested. 2018 IOP Publishing Ltd. Creator An entity primarily responsible for making the resource Patil S.B.; Sankeshwar N.S.; Mulimani B.G. Source A related resource from which the described resource is derived Journal of Physics D: Applied Physics, Vol-51, No. 30 Publisher An entity responsible for making the resource available Institute of Physics Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1088/1361-6463/aaccc8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1088/1361-6463/aaccc8</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049966430&amp;doi=10.1088%2F1361-6463%2Faaccc8&amp;partnerID=40&amp;md5=ced981d1ec5629fa2a5ca547b0d4f373" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049966430&amp;doi=10.1088%2f1361-6463%2faaccc8&amp;partnerID=40&amp;md5=ced981d1ec5629fa2a5ca547b0d4f373</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 223727; CODEN: JPAPB 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 Patil S.B., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India; Sankeshwar N.S., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India, Department of Physics, Christ University, Bangalore, Karnataka, 560029, India; Mulimani B.G., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, 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 Role of charged impurities in thermoelectric transport in molybdenum disulfide monolayers Subject The topic of the resource charged impurities; electrical conductivity; electronic thermal conductivity; MoS₂; Thermoelectric power Description An account of the resource A theoretical study of the electronic properties, namely, electrical conductivity (EC), electronic thermal conductivity (ETC) and thermoelectric power (TEP) in 2D MoS2 monolayers (MLs), over a wide range of temperatures (10 &lt; T &lt; 300 K), is presented employing Boltzmann transport formalism. Considering the electrons to be scattered by screened charged impurities and the acoustic, optical and remote phonons, the transport equation is solved using Ritz iterative method. Numerical calculations of EC, ETC and TEP presented for supported and free-standing MLs with high electron concentrations, as a function of temperature, bring out the relative importance of the various scattering mechanisms operative. The role of CIs, with regard to both concentration and separation from the substrate-ML interface, in determining the properties of supported MLs is demonstrated for the first time. Validity of Wiedemann-Franz law and Mott formula are examined for supported and free standing MLs. Calculations are in consonance with recent experimental data on mobility and TEP of exfoliated SiO2-supported MoS2 ML samples. In the case of TEP it is found that though the diffusion contribution is dominant the inclusion of the drag component, incorporating contributions from all relevant phonon scattering mechanisms, is needed to obtain good agreement with the data. 2017 IOP Publishing Ltd. Creator An entity primarily responsible for making the resource Patil S.B.; Sankeshwar N.S.; Mulimani B.G. Source A related resource from which the described resource is derived Journal of Physics Condensed Matter, Vol-29, No. 48 Publisher An entity responsible for making the resource available Institute of Physics Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1088/1361-648X/aa91a0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1088/1361-648X/aa91a0</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037681757&amp;doi=10.1088%2F1361-648X%2Faa91a0&amp;partnerID=40&amp;md5=0d053d4dd4232430fde5c42415e2545f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037681757&amp;doi=10.1088%2f1361-648X%2faa91a0&amp;partnerID=40&amp;md5=0d053d4dd4232430fde5c42415e2545f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9538984; PubMed ID: 28984276; CODEN: JCOME 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 Patil S.B., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India; Sankeshwar N.S., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India, Department of Physics, Christ University, Bangalore, Karnataka, 560029, India; Mulimani B.G., B.L.D.E. University, Vijayapura, Karnataka, 586103, 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 Effect of phonon-substrate scattering on lattice thermal conductivity of monolayer MoS2 Description An account of the resource The effect of phonon-substrate scattering on lattice thermal conductivity (LTC) of supported MoS2 MLs is investigated over a wide temperature range (1 Creator An entity primarily responsible for making the resource Patil S.B.; Sankeshwar N.S.; Mulimani B.G. Source A related resource from which the described resource is derived AIP Conference Proceedings, Vol-2265 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/10.1063/5.0018891" target="_blank" rel="noreferrer noopener">https://doi.org/10.1063/5.0018891</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096625243&amp;doi=10.1063%2F5.0018891&amp;partnerID=40&amp;md5=656bc7279366bd458c5545262f1c5cd8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096625243&amp;doi=10.1063%2f5.0018891&amp;partnerID=40&amp;md5=656bc7279366bd458c5545262f1c5cd8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 0094243X; ISBN: 978-073542025-0 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 Patil S.B., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India; Sankeshwar N.S., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, India, Department of Physics and Electronics, Christ (Deemed to be University), Bengaluru, Karnataka, 560029, India; Mulimani B.G., Department of Physics, Karnatak University, Dharwad, Karnataka, 580003, 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 Parkinson's Disease Progression Prediction Using Longitudinal Imaging Data and Grey Wolf Optimizer-Based Feature Selection Subject The topic of the resource Feature selection; Grey Wolf Optimizer; Imaging data; Parkinson Disease; Progression Prediction Description An account of the resource This work uses longitudinal imaging data and a feature selection method based on the Grey Wolf Optimizer (GWO) to create a novel method for forecasting the course of Parkinson's disease.Magnetic resonance imaging (MRI) and positron emission tomography (PET) longitudinal imaging data offer important insights into the structural and functional changes in the brain over time. However, because of its great dimensionality, analysing this complicated data might be difficult. We suggest using the GWO-based feature selection method to identify the most informative imaging features related to illness development in order to solve this problem.The Grey Wolf Optimizer is an algorithm that draws inspiration from nature and imitates the way that grey wolves hunt. By effectively locating an ideal subset of features that maximise classification or regression performance, it has demonstrated promising results in feature selection challenges. GWO will be used in our investigation to choose the most pertinent imaging features from the longitudinal data, lowering dimensionality and improving the model's ability to predict outcomes.Using machine learning strategies, we will build a predictive model that includes the chosen features and longitudinal imaging data. We hope to equip clinicians with a tool to forecast the course of each patient's Parkinson's disease by utilising this model. By assisting in early diagnosis, treatment planning, and disease progression monitoring, this predictive skill can ultimately improve the overall management of Parkinson's disease and the quality of life for those who are affected. Our method has great promise for expanding the fields of neurodegenerative disease prediction and personalised therapy because it integrates longitudinal imaging data and the Grey Wolf Optimizer-based feature selection method in a novel way. 2024, Ismail Saritas. All rights reserved. Creator An entity primarily responsible for making the resource Patil S.C.; Mane D.A.; Singh M.; Garg P.; Desai A.B.; Rawat D. Source A related resource from which the described resource is derived International Journal of Intelligent Systems and Applications in Engineering, Vol-12, No. 3s, pp. 441-451. Publisher An entity responsible for making the resource available Ismail Saritas 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="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179358409&amp;partnerID=40&amp;md5=9af5293c613b1a9cbfb7e3119e5ef295" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179358409&amp;partnerID=40&amp;md5=9af5293c613b1a9cbfb7e3119e5ef295</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21476799 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 Patil S.C., Department of General Medicine, Krishna Vishwa Vidyapeeth, Maharashtra, Karad, India; Mane D.A., Statistician Krishna Vishwa Vidyapeeth, Maharashtra, Karad, India; Singh M., School of Sciences, Christ University, Delhi NCR campus, India; Garg P., St. Andrews Institute of Technology and Management, Gurugram, Haryana, Farrukh Nagar, India; Desai A.B., Department of Computer Science and Engineering, Graphic Era Hill University, Uttarakhand, Dehradun, India; Rawat D., Department of Computer Science &amp; Engineering, Graphic Era Deemed to be University, Uttarakhand, Dehradun, 248002, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An improved AI-driven Data Analytics model for Modern Healthcare Environment Subject The topic of the resource Approach; Improve; Powerful; Progressed; Statistics Description An account of the resource AI-driven statistics analytics is a swiftly advancing and impactful era that is transforming the face of healthcare. By leveraging the energy of AI computing and gadget studying, healthcare organizations can speedy gain insights from their huge datasets, offering a greater comprehensive and personalized approach to hospital therapy and populace health management. This paper explores the advantages of AI-driven statistics analytics in healthcare settings, masking key benefits along with progressed analysis and treatment, better-affected person effects, and financial savings. Moreover, this paper addresses the main challenges associated with AI-pushed analytics and offers potential solutions to enhance accuracy and relevance. In the long run, statistics analytics powered by way of AI gives powerful opportunities to improve healthcare outcomes, and its use is expected to expand within the coming years. 2024 IEEE. Creator An entity primarily responsible for making the resource Patil S.C.; Takkalapally P.; Kasula B.Y.; Logeshwaran J. Source A related resource from which the described resource is derived 2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 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/ICCCNT61001.2024.10724303" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCNT61001.2024.10724303</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212928085&amp;doi=10.1109%2FICCCNT61001.2024.10724303&amp;partnerID=40&amp;md5=e37a23c13d472e313d4d7760f9182123" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212928085&amp;doi=10.1109%2fICCCNT61001.2024.10724303&amp;partnerID=40&amp;md5=e37a23c13d472e313d4d7760f9182123</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037024-9 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 Patil S.C., United States; Takkalapally P., Lewis University, Department of Engineering, Computing and Mathematical Sciences, United States; Kasula B.Y., University Of The Cumberlands, Dept of Information Technology, Williamsburg, KY, United States; Logeshwaran J., CHRIST (Deemed to be University), Department of Computer Science, 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 Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Patil, Anand; Akilesh, V.K.R.; Lakshmi, R.B. Title A name given to the resource Decentralized financial assets: An attraction beyond stock market investments Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived FinTech and Robotics Advancements for Green Finance and Investment;pp.251-284 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-0355-0.ch009" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-0355-0.ch009</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105023560746?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023560746?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patil A., Christ University, India; Akilesh V., Christ University, India; Lakshmi R.B., Christ University, India Description An account of the resource The Chapter revolves around the attraction that the blockchain-backed decentralized financial products have created in the investment market. These new-gen decentralized finances would be Defi, Metaverse coins, Stablecoins, Cryptocurrency, smart contracts, and privacy coins. The influence of social media and high internet penetration levels have made the retail and partial investors very well aware of many alternate financial investment products. Though there is an increase seen in the Stock Market investments as well a drastic increase in the alternate market is seen. In recent times major stock markets have created indexes separately. It is the icing on the cake with the highest attention of the globe. The regulations have put the Defi Assets under unpredictable volatility but the attraction towards cryptocurrency and other digital asset gain still exists. The study aims to identify the relationship between the increase in investment in the stock market and the alternative. 2025 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833730357-4; 979-833730355-0; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Patil, Anand; Raj, M.S. Prathibha; Shankar, R. Gowri; Lakshmi, R.B. Title A name given to the resource Cultivating wellness: Synergy of emerging technologies in spiritual and wellness tourism Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Meaningful Tourism: Strategies and Future Development;pp.145-162 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1108/978-1-83797-837-320251022" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/978-1-83797-837-320251022</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003856467?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003856467?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patil A., Christ University, India; Raj M.S.P., Christ University, India; Shankar R.G., Christ University, India; Lakshmi R.B., Christ University, India Description An account of the resource This academic analysis explores the dynamic landscape of wellness tourism from 1998 to September 2021, emphasizing the surge in scholarly publications post-2010, primarily contributed by the United States. Key findings identify major authors, significant papers, and evolving trends while acknowledging research limitations and offering recommendations. Additionally, the 2022 study highlights 10 pivotal elements enriching holistic health resorts, coupled with strategic marketing and DMO influence. A comprehensive review utilizing the PRISMA methodology reveals two significant research clusters, focusing on tourist motivations and behavior, anticipating post-pandemic research and the need for diverse data sources. Wellness tourism embodies dynamism and diversity, driven by an ever-growing yearning for well-being, relaxation, and self-care. Travelers can choose from a broad spectrum of dimensions and destinations to personalize their wellness journeys according to their unique aspirations and goals, making it an exceptionally adaptable and customized form of travel. The industry's trajectory is set for continued expansion and transformation as more individuals acknowledge the paramount importance of nurturing their holistic well-being. However, a notable research gap is identified: the incorporation of cutting-edge technologies like wearable technology, virtual reality, and artificial intelligence in wellness tourism remains underexplored. This study addresses this void by investigating the utilization of technology to craft personalized and immersive wellness experiences, its impact on traveler preferences and behavior, and its role in destination management and marketing strategies. Recognizing technology's pivotal role in wellness tourism, this study seeks to bridge the gap between traditional wellness practices and contemporary technological advancements, fostering a holistic approach to well-being in the modern era. 2025 Anand Patil, M.S. Prathibha Raj, R. Gowri Shankar and R.B. Lakshmi. All rights reserved. Subject The topic of the resource Academic analysis; Emerging technologies; Holistic; Synergy; Wellness tourism Publisher An entity responsible for making the resource available Emerald Publishing Relation A related resource ISBN: 978-183797837-3; 978-183797838-0; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Patil, Anand; Sanwal, Neha Title A name given to the resource Impact of ESG Factors on the Financial Performance of Corporates in India Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Behavioral Finance and AI Tools for Sustainability;pp.227-249 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-9684-1.ch009" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-9684-1.ch009</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021717693?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021717693?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patil A., Christ University, Bangalore, India; Sanwal N., Christ University, Bangalore, India Description An account of the resource This study investigates the connection between Indian companies' financial results and Environmental, Social, and Governance (ESG) performance, with a focus on socially and environmentally sensitive industries. There is little data on the financial effects of ESG integration in developing nations like India, even though it is becoming more and more crucial for long- term value development. Using a quantitative approach involving ESG ratings and financial indicators (Return on Equity [ROE], Return on Assets [ROA], and Return on Capital Employed [ROCE]) we analyze the performance of firms from 2021 to 2023 in five different sectors. Among the pillars, environmental issues had the most significant effect on material financial success, showing a positive but weak correlation with ESG scores. However, the study also investigates into sectoral distinctions, pointing to differential financial outcomes associated with ESG across industries. 2025 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836939686-5; 979-836939684-1; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Patil, Anand; Shekar, Swathi Title A name given to the resource Impact of green management on firm performance in the purview of AI and data analytics: A comprehensive review Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Green Engineering for Optimizing Firm Performance: AI and Automation for Sustainable Technologies;pp.172-194 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003626527-8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003626527-8</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014235436?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014235436?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patil A., School of Business and Management, CHRIST (Deemed to Be University), Bangalore, Karnataka, India; Shekar S., School of Business and Management, CHRIST (Deemed to Be University), Bangalore, Karnataka, India, Jain (Deemed to Be University), Bangalore, Karnataka, India Description An account of the resource Sustainability has evolved from being a goal to a fundamental practice in the business world. Organizational survival depends on its adaptability, and innovative practices are a dire necessity for businesses to stay afloat. From this perspective, data analytics and artificial intelligence highly influence business decisions. They are elemental, have a substantial impact, and hence need to be absorbed into each aspect of organizational management. Over the years, businesses embracing green management principles have witnessed a significant impact on overall organizational performance. This study aims to provide a broad-spectrum analysis of this discipline using bibliometric analysis conducted on publications in the Scopus database over the last three decades using VOSviewer software. Multiple aspects of the discipline are tested to provide comprehensive results. The subject, citations, contributions of authors, countries, and institutions, as well as the active sources of publication, are some of the disclosures in the current study. These aspects collectively reveal the positive relationship between the adaptation of green management and firm performance through the lens of data analytics and AI. It is necessary to understand the depth of previous and ongoing advancements to propose new postulates and ideologies, which is met in this chapter. 2026 Anand Patil, Swathi Shekar. All rights reserved. Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 978-104038889-1; 978-104104034-7; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library