35 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 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 novel approach for the synthesis of functionalized hydroxylamino derivative of dihydroquinazolinones Subject The topic of the resource 4-Chloro-N-hydroxybenzimidoylchloride; dihydroquinazolinones; isatoic anhydride Description An account of the resource A new metal-free and modular approach for the synthesis of various functionalized dihydroquinazolinones has been developed from isatoic anhydride, amines, 4-chloro-N-hydroxybenzimidoylchloride to yield up to 71%. The reaction has been screened in various bases, solvents at different temperatures. The substrate scope of the reaction has been studied with various amines and the possible reaction mechanism for this reaction has also been proposed. 2020, 2020 Taylor & Francis Group, LLC. Creator An entity primarily responsible for making the resource Jaganmohan C.; Vinay Kumar K.P.; Venkateshwarlu R.; Mohanty S.; Kumar J.; Venkateswara Rao B.; Raghunadh A.; Tadiparthi K. Source A related resource from which the described resource is derived Synthetic Communications, Vol-50, No. 14, pp. 2163-2170. Publisher An entity responsible for making the resource available Bellwether Publishing, Ltd. 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/10.1080/00397911.2020.1768406" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/00397911.2020.1768406</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085966335&doi=10.1080%2F00397911.2020.1768406&partnerID=40&md5=2b77f75d7204a81f0e9e36d6dfaa3ef6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085966335&doi=10.1080%2f00397911.2020.1768406&partnerID=40&md5=2b77f75d7204a81f0e9e36d6dfaa3ef6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 397911; CODEN: SYNCA 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 Jaganmohan C., Dr. Reddys Laboratories Limited, Hyderabad, India, Department of Organic Chemistry and FDW, Andhra University, Visakhapatnam, India; Vinay Kumar K.P., Dr. Reddys Laboratories Limited, Hyderabad, India; Venkateshwarlu R., Dr. Reddys Laboratories Limited, Hyderabad, India; Mohanty S., Dr. Reddys Laboratories Limited, Hyderabad, India; Kumar J., Dr. Reddys Laboratories Limited, Hyderabad, India; Venkateswara Rao B., Department of Organic Chemistry and FDW, Andhra University, Visakhapatnam, India; Raghunadh A., Dr. Reddys Laboratories Limited, Hyderabad, India; Tadiparthi K., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Novel Approach for Web Mining Taxonomy for High-Performance Computing Subject The topic of the resource Document object model; Self-organising map; Web mining; WebLog Expert Description An account of the resource Web mining is a central part of data analysis. The fetching and discovering knowledge from the different web data in data mining mechanism is more important nowadays. Web usage mining customs data mining practice for the investigation of custom decoration from different data storages. In this article paper, introducing a new approach for web mining taxonomy for high-performance computing. The primary motivation of this research is on the data collection in different real-time web servers for implementation and analysis. This article is focussed the WebLog Expert lite 9.3 tools for our study. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Samanta D.; Dutta S.; Galety M.G.; Pramanik S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-291, pp. 425-432. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-16-4284-5_37" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-16-4284-5_37</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116830871&doi=10.1007%2F978-981-16-4284-5_37&partnerID=40&md5=26457c8059dfcf142df2def1704bc75f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116830871&doi=10.1007%2f978-981-16-4284-5_37&partnerID=40&md5=26457c8059dfcf142df2def1704bc75f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981164283-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Samanta D., Department of Computer Science, Christ University, Bangalore, India; Dutta S., Institute of Engineering and Management, Kolkata, India; Galety M.G., College of Engineering and Technology, Catholic University in Erbil, Erbil, Kurdistan Region, Iraq; Pramanik S., Haldia Institute of Technology, Haldia, 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 novel approach in prediction of crop production using recurrent cuckoo search optimization neural networks Subject The topic of the resource Crop production; Data mining; Discrete DBN?VGG Net classifier; Recurrent cuckoo search optimization algorithm Description An account of the resource Data mining is an information exploration methodology with fascinating and understand-able patterns and informative models for vast volumes of data. Agricultural productivity growth is the key to poverty alleviation. However, due to a lack of proper technical guidance in the agriculture field, crop yield differs over different years. Mining techniques were implemented in different applications, such as soil classification, rainfall prediction, and weather forecast, separately. It is proposed that an Artificial Intelligence system can combine the mined extracts of various factors such as soil, rainfall, and crop production to predict the market value to be developed. Smart analysis and a comprehensive prediction model in agriculture helps the farmer to yield the right crops at the right time. The main benefits of the proposed system are as follows: Yielding the right crop at the right time, balancing crop production, economy growth, and planning to reduce crop scarcity. Initially, the database is collected, and the input dataset is preprocessed. Feature selection is carried out followed by feature extraction techniques. The best features were then optimized using the recurrent cuckoo search optimization algorithm, then the optimized output can be given as an input for the process of classification. The classification process is conducted using the Discrete DBN? VGGNet classifier. The performance estimation is made to prove the effectiveness of the proposed scheme. 2021 by the authors. Licensee MDPI, Basel, Switzerland. Creator An entity primarily responsible for making the resource Rajagopal A.; Jha S.; Khari M.; Ahmad S.; Alouffi B.; Alharbi A. Source A related resource from which the described resource is derived Applied Sciences (Switzerland), Vol-11, No. 21 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 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3390/app11219816" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/app11219816</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117689718&doi=10.3390%2Fapp11219816&partnerID=40&md5=47e62179a726d4af8bde18057f196412" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117689718&doi=10.3390%2fapp11219816&partnerID=40&md5=47e62179a726d4af8bde18057f196412</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 20763417 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 Rajagopal A., Department of Computer Science and Business Systems, Sethu Institute of Technology, Virudhunagar, Kariapatti, 626115, India; Jha S., School of Sciences, Christ (Deemed to be University), NCR?New Delhi Campus, Ghaziabad, 201003, India; Khari M., School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India; Ahmad S., Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia; Alouffi B., Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia; Alharbi A., Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, 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 A Novel Approach to Automatic Ear Detection Using Banana Wavelets and Circular Hough Transform Subject The topic of the resource adaptive histogram equalization; banana wavelets; biometric; ear detection; hough transform; skin segmentation Description An account of the resource Ear is an attractive biometric trait that maintain their structure with increasing age. Because of the complex geometry of ear, its detection is very difficult. This paper proposes a modified algorithm for automatic detection of 2D ear images using Banana wavelets and Hough transform. Banana wavelets derived from bank of stretched and curved Gabor wavelets are used to identify curvilinear ear structure. Addition of a preprocessing stage, prior to application of banana wavelets is found to improve the detection results further. The proposed algorithm is brought in to comparison with three existing algorithms and evaluated on standard databases. In addition to manual detection accuracy, this paper also calculates the efficiency of the proposed method using automatic classification techniques. The features like LBP and Gabor extracted from segmented ear image is used by different classifiers to determine whether the segmented portion of the image is class Ear or Non ear. 2019 IEEE. Creator An entity primarily responsible for making the resource Resmi K.R.; Raju G. Source A related resource from which the described resource is derived 2019 International Conference on Data Science and Communication, IconDSC 2019 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 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IconDSC.2019.8816919" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IconDSC.2019.8816919</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072759298&doi=10.1109%2FIconDSC.2019.8816919&partnerID=40&md5=3ff7270e489904690196de77df006743" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072759298&doi=10.1109%2fIconDSC.2019.8816919&partnerID=40&md5=3ff7270e489904690196de77df006743</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-153869319-3 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 Resmi K.R., School of Computer Science, Mahatma Gandhi University, Kottayam, India; Raju G., Department 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 Novel Approach to Enhance Influencer Marketing in E-commerce: A Cross-A-Siamese Perspective Subject The topic of the resource e-commerce; influencer marketing; social media influencers (SMI) Description An account of the resource One of the most notable aspects of the Internet is the fact that the cost of (global) communication has been drastically decreased. Individuals may potentially reach massive audiences with their messages over the Internet due to its widespread use. With the rise of blog services, social networking platforms, etc., people's technological talents are no longer a limiting factor. Data preprocessing, feature selection, and model training should all be done in this sequence of significance. Applying fundamental data preparation techniques guaranteed the data's accuracy and relevancy. Feature selection includes the computation of an influencer's overall rank based on six important criteria, which are used for influencer identification and ranking. Feature retrieval is the first step in training Unified Cross-A-Siamese models. The proposed method outperforms two cutting-edge methods: Attention module and siamese. Accuracy increased by 95.70 percent once the approach was used. 2024 IEEE. Creator An entity primarily responsible for making the resource Akram N.; Dahiya S.; Jafersadhiq A.; Akila D.; Girdharwal N.; Chauhan A. Source A related resource from which the described resource is derived International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 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/IACIS61494.2024.10721951" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IACIS61494.2024.10721951</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208779312&doi=10.1109%2FIACIS61494.2024.10721951&partnerID=40&md5=4fd793e05e24b7b2381862999cb8554d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208779312&doi=10.1109%2fIACIS61494.2024.10721951&partnerID=40&md5=4fd793e05e24b7b2381862999cb8554d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036066-0 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 Akram N., Magadh Professional Institute, Patna, India; Dahiya S., Universal Ai University, Department of Management, Maharashtra, Karjat, India; Jafersadhiq A., Kalasalingam Academy Research and Education, Kalasalingam Business School, Department of Business Administration, India; Akila D., Saveetha College of Liberal Arts and Sciences, Simats, Department of Computer Applications, Chennai, India; Girdharwal N., Prestige Institute of Management & Research (PIMR), Department of Management, Indore, India; Chauhan A., Christ (Deemed to be University), Department of Life Sciences, 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 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 Suhaas, K.P.; Senthil, S.; Deepa, B.G. Title A name given to the resource A novel approach to optimize power utilization and scheduling in dynamic networks through generative adversarial network-based prediction of network parameters Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Quantum Computing;Volume;5;pp.103-122 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1515/9783111354934-006" target="_blank" rel="noreferrer noopener">https://doi.org/10.1515/9783111354934-006</a> <a href="https://www.scopus.com/pages/publications/105038239338?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038239338?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 Suhaas K.P., Department of Information Science and Engineering, The National Institute of Engineering, Mysuru, India; Senthil S., Department of Computer Applications, Dayanand Sagar University, Bengaluru, India; Deepa B.G., Department of Computer Science, Christ University, Bengaluru, India Description An account of the resource The infrastructure-less network communication has been in an ever-increasing demand to cater to the needs of effective communication while the network dynamism exists. The quality of service (QoS)quality of service (QoS) demands increasing the efficiency of network by reducing the time taken for a data packet to reach the destination, increasing the probability of successful data transmissiondata transmission, minimizing packet loss,packet loss and optimizing power utilizationpower utilization. In this study, a generative adversarial network-based learning modelgenerative adversarial network-based learning model has been developed that considers the previous network statistics, as realized data, to predict future network patterns by the generatorgenerator to make such predictions, called as unrealized data, as near to the realized data. Further, the proposed model uses penalty-award criteria by the discriminatordiscriminator, to fine-tune the predicted network parameters. Now, having the set of realized and unrealized data, the model uses Markov decision processMarkov decision process to perform power scheduling and effective utilization of buffer space. The buffer utilization in the intermediate nodes necessitates the model to stochastically schedule the data transmission, depending on the percentage of utilization of buffer. Simulation results denote the effective utilization of buffer that makes continued transmission of data, whenever possible, without having data packet lossdata packet loss. Also, power scheduling, by the use of goodput function and increased transmission probability improves the power utilization that ultimately increases the lifetime of the network. 2026 Walter de Gruyter GmbH, Berlin/Boston, Genthiner Stra 13, 10785 Berlin. Subject The topic of the resource Ad hoc networks; buffer overflow; channel fading coefficient; generative adversarial networks; Goodput; Markov decision process; network parameters; power scheduling; quality of service; reinforcement learning; resource optimization; transition probability Publisher An entity responsible for making the resource available Walter de Gruyter GmbH Relation A related resource ISSN: 29400112; 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 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 Novel Approach to Optimizing Third-Party Logistics Growth through IT, Big Data, and Machine Learning for Superior Supply Chain Management Subject The topic of the resource Big Data Analytics; IT Integration; Logistics Innovation; Logistics Optimization; Predictive Analytics; Real-Time Monitoring; Supply Chain Efficiency Description An account of the resource The purpose of this research is to explore proper development prospects of 3PL business, particularly focusing on the utilization of Information Technology and big data technologies for improving the solidity of supply chains. The change of the industry that started from the provision of services and then became an integrated solution implies the rising role of IT as one of the means for supply chain improvement. Based on the market study and investigation of customers' behaviors, as well as the contexts of the 3PL industry of the India, this research outlines how the IT and big data analytics can contribute to the operations improvement and innovation of the 3PL. Besides, this paper aims at finding out whether the Big Data analytics can enhance the competitiveness of third party logistics providers in a volatile market. 2024 IEEE. Creator An entity primarily responsible for making the resource Shyamsunder C.; Roshani P.; Soni H.; Dankan Gowda V.; Aghav S.; Abdullah I. Source A related resource from which the described resource is derived 2024 2nd World Conference on Communication and Computing, WCONF 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/WCONF61366.2024.10692305" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/WCONF61366.2024.10692305</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207390480&doi=10.1109%2FWCONF61366.2024.10692305&partnerID=40&md5=3ce94eb15786de54a2e1f13ad3ce3cd4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207390480&doi=10.1109%2fWCONF61366.2024.10692305&partnerID=40&md5=3ce94eb15786de54a2e1f13ad3ce3cd4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039532-7 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 Shyamsunder C., Symbiosis Institute of Business Management, Hyderabad Symbiosis International University, Pune, India; Roshani P., Department of Commerce, Christ University, Karnataka, Bangalore, India; Soni H., Symbiosis Institute of Business Management, Hyderabad Symbiosis International University, Pune, India; Dankan Gowda V., Department of Electronics and Communication Engineering, BMS Institute of Technology and Management, Karnataka, Bangalore, India; Aghav S., Symbiosis Law School, Hyderabad, Symbiosis International (Deemed University), Pune, India; Abdullah I., Department of Computer Science, Al-Turath University College, Baghdad, Iraq Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Martin, Joseph John; George, Jossy P; Alapatt, Bosco Paul Title A name given to the resource A Novel Approach to Packet Dropping and Malicious Attack Detection using Ensemble Techniques 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 Proceedings of 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2025;pp.1458-1463 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICICV64824.2025.11085510" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICV64824.2025.11085510</a> <a href="https://www.scopus.com/pages/publications/105013070858?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013070858?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 Martin J.J., CHRIST (Deemed to Be University), India; George J.P., Christ University, India; Alapatt B.P., Christ University, India Description An account of the resource Packet-dropping attacks interrupt data transfer while damaging security protocols, which create a threat to wireless Sensor Networks and Mobile Ad Hoc networks. This paper examines packet-dropping detection methods as well as security attack identification since these threats represent significant risks to networks such as Wireless sensor networks and Mobile Ad Hoc Networks. The research paper utilized a dataset from Kaggle for network traffic analysis, which classified packets through their behaviors as either abnormal or normal. The detection employed a stacking classifier with logistic regression as the meta-classifier and Support Vector Machine, Gradient Boosting, and K-Nearest Neighbour as its main constituents. The analysis model showed high detection rates for packet-dropping incidents, reaching 93.5%, and for malicious attacks, reaching 98.2%, based on the experimental test results. The obtained data shows that stacking models show stable reliability levels above traditional approaches. Ensemble learning proves effective for discovering cyber threats through results that reduce the number of incorrect detections. The stacking classifier functions as a dependable framework for developing security measures required to protect computer networks from modern-day threats. 2025 IEEE. Subject The topic of the resource Cross Validation; Gradient Boosting; KNN; Packet Dropping Detection; Stack Classifier; SVM Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833151175-3; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Novel Approach to Predicting the Risk of Illegal Activity and Evaluating Law Enforcement Using WideDeep SGRU Model Subject The topic of the resource Gated Recurrent Unit(GRU); Illegal Activity; Law Enforcement Officers (LEO) Description An account of the resource The main reaction to the illicit extraction of natural resources in protected areas around the world is law enforcement patrols headed by rangers. On the other hand, research on patrols' efficacy in reducing criminal behavior is lacking. Similarly, tactics to enhance the effectiveness of patrol organization and monitoring have received very little attention. Sequencing is crucial for model training, feature selection, and preprocessing. Preprocessing steps include cleaning, discretizing, duplicating, and normalizing data. Feature selection makes use of genetic algorithms, which are basically search algorithms with an evolutionary bent that factor in natural selection and genetics. Training stacked GRU models necessitates meticulous feature management. Even the most cutting-edge algorithms, GRU and BiGRU, are no match for the suggested technique. An astounding 97.24% accuracy grade was disclosed by the results, showcasing exceptional growth. 2024 IEEE. Creator An entity primarily responsible for making the resource Mishra P.; Anusha P.; Kumar A.; Pal S.; Patra J.P.; Chauhan A. Source A related resource from which the described resource is derived 1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 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/ICECCC61767.2024.10593977" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICECCC61767.2024.10593977</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200657446&doi=10.1109%2FICECCC61767.2024.10593977&partnerID=40&md5=fdbfb038bb3effe675cfd1430d23b203" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200657446&doi=10.1109%2fICECCC61767.2024.10593977&partnerID=40&md5=fdbfb038bb3effe675cfd1430d23b203</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037180-2 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 Mishra P., Computer Science and Application Reva University, Karnataka, Bangalore, India; Anusha P., R.M.K. Engineering College, Department of ECE, Tamilnadu, Kavaraipettai, India; Kumar A., SCA Manav Rachna International Institute of Research and Studies, Haryana, Faridabad, India; Pal S., Computer Science and Engineering Indian Institute of Technology Jammu, Jammu & Kashmir (UT), Jagti, India; Patra J.P., EE And EEE Krupajal Engineering College-KEC, Odisha, Puri, India; Chauhan A., CHRIST (Deemed to be University), Department of Life sciences School of Sciences, 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 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 novel approach to study generalized coupled cubic SchringerKorteweg-de Vries equations Subject The topic of the resource CNLS equation; KdV equation; Long and short waves; Modified Sardar sub-equation method; Solitons Description An account of the resource The Kortewegde Vries (KdV) equation represents the propagation of long waves in dispersive media, whereas the cubic nonlinear Schringer (CNLS) equation depicts the dynamics of narrow-bandwidth wave packets consisting of short dispersive waves. A model that couples these two equations seems intriguing for simulating the interaction of long and short waves, which is important in many domains of applied sciences and engineering, and such a system has been investigated in recent decades. This work uses a modified Sardar sub-equation procedure to secure the soliton-type solutions of the generalized cubic nonlinear SchringerKorteweg-de Vries system of equations. For various selections of arbitrary parameters in these solutions, the dynamic properties of some acquired solutions are represented graphically and analyzed. In particular, the dynamics of the bright solitons, dark solitons, mixed bright-dark solitons, W-shaped solitons, M-shaped solitons, periodic waves, and other soliton-type solutions. Our results demonstrated that the proposed technique is highly efficient and effective for the aforementioned problems, as well as other nonlinear problems that may arise in the fields of mathematical physics and engineering. 2022 Creator An entity primarily responsible for making the resource Akinyemi L.; Veeresha P.; Darvishi M.T.; Rezazadeh H.; ?enol M.; Akpan U. Source A related resource from which the described resource is derived Journal of Ocean Engineering and Science, Vol-9, No. 1, pp. 13-24. Publisher An entity responsible for making the resource available Shanghai Jiaotong University Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.joes.2022.06.004" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.joes.2022.06.004</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132504407&doi=10.1016%2Fj.joes.2022.06.004&partnerID=40&md5=116dcc11e9251a01150e13c5b09652bf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132504407&doi=10.1016%2fj.joes.2022.06.004&partnerID=40&md5=116dcc11e9251a01150e13c5b09652bf</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 24680133 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 Akinyemi L., Department of Mathematics, Lafayette College, Easton, PA, United States; Veeresha P., Department of Mathematics, Christ Deemed to be University, Bengaluru, 560029, India; Darvishi M.T., Department of Mathematics, Razi University, Kermanshah, 67149, Iran; Rezazadeh H., Faculty of Engineering Technology, Amol University of Special Modern Technologies, Amol, Iran; ?enol M., Department of Mathematics, Nev?ehir Hac? Bekta? Veli University, Nev?ehir, Turkey; Akpan U., Drexel University, Department of Mathematics, Philadelphia, PA, United States Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Shivaprasad, D.L.; Guru, D.S.; Kavitha, R. Title A name given to the resource A Novel Approach towards Key-point based Real-time Children Emotion Prediction 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 Procedia Computer Science;Volume;258;pp.588-598 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.procs.2025.04.293" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2025.04.293</a> <a href="https://www.scopus.com/pages/publications/105007134493?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007134493?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 Shivaprasad D.L., Department of Studies in Computer Science, University of Mysore, Manasagangotri, Mysuru, India; Guru D.S., Department of Studies in Computer Science, University of Mysore, Manasagangotri, Mysuru, India; Kavitha R., Department of Data Science, CHRIST (Deemed to Be University), Bangalore, India Description An account of the resource Emotion prediction is crucial in mental healthcare. It is vital in children as it aids in managing behavioral issues and early identification of emotional distress that can lead to helpful mental health support. The research uniquely centres on children's emotional expressions, addressing a gap in existing emotion detection studies, which often focus on adults. By specifically tailoring the model to recognize subtle expressions unique to children, the study contributes valuable insights into child psychology and emotion recognition. To address this gap, this work attempts to establish a comprehensive children's emotion dataset that can facilitate the study of emotions across various pose orientation. The approach introduces advanced key-point detection techniques that capture a higher density of facial landmarks, allowing for more nuanced analysis of emotional expressions. This fine-grained detection enables the identification of subtle changes that are critical in interpreting children's emotions. An effective face detector with deep architecture is designed to handle all pose orientations from key image frames. Optimal features are then chosen by re-ranking the features using a hybrid feature selection mechanism. The emotion category is revealed by careful analysis of sequences of emotion identification from these features and is not based on a single frame. This framework holds promise for educational institutions and healthcare facilities, offering insights into children's behavior through emotion analysis. Through experimental analysis and comparisons with three existing SOTA emotion prediction models, it is observed that the proposed system consistently outperforms existing models by exhibiting an accuracy of 77.7 on average. Overall, this study recommended that the proposed model is suitable for children's emotion prediction. 2025 The Author(s). Subject The topic of the resource Children Emotion Recognition; Feature Re-ranking; Key-frame Extraction; Key-point Feature Extraction; Static Key-points Publisher An entity responsible for making the resource available Elsevier B.V. Relation A related resource ISSN: 18770509; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource All Open Access; Gold Open Access Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A novel approach using steganography and cryptography in business intelligence Description An account of the resource In the information technology community, communication is a vital issue. And image transfer creates a major role in the communication of data through various insecure channels. Security concerns may forestall the direct sharing of information and how these different gatherings cooperatively direct data mining without penetrating information security presents a challenge. Cryptography includes changing over a message text into an unintelligible figure and steganography inserts message into a spread media and shroud its reality. Both these plans are successfully actualized in images. To facilitate a safer transfer of image, many cryptosystems have been proposed for the image encryption scheme. This chapter proposes an innovative image encryption method that is quicker than the current researches. The secret key is encrypted using an asymmetric cryptographic algorithm and it is embedded in the ciphered image using the LSB technique. Statistical analysis of the proposed approach shows that the researcher's approach is faster and has optimal accuracy. 2021, IGI Global. Creator An entity primarily responsible for making the resource Pramanik S.; Ghosh R.; Ghonge M.M.; Narayan V.; Sinha M.; Pandey D.; Samanta D. Source A related resource from which the described resource is derived Integration Challenges for Analytics, Business Intelligence, and Data Mining, pp. 192-217. Publisher An entity responsible for making the resource available IGI Global 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/10.4018/978-1-7998-5781-5.ch010" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-7998-5781-5.ch010</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135085086&doi=10.4018%2F978-1-7998-5781-5.ch010&partnerID=40&md5=5e99f39fc363b909e5e8071b7a7caf01" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135085086&doi=10.4018%2f978-1-7998-5781-5.ch010&partnerID=40&md5=5e99f39fc363b909e5e8071b7a7caf01</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-179985783-9; 1799857816; 978-179985781-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pramanik S., Haldia Institute of Technology, India; Ghosh R., Haldia Institute of Technology, India; Ghonge M.M., Sandip Institute of Technology and Research Centre, India; Narayan V., MMM Collage, Gorakhpur, India; Sinha M., CHRIST University (Deemed), India; Pandey D., Department of Technical Education, India, IET, India; Samanta D., CHRIST University (Deemed), 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 novel approach with matrix based public key crypto systems Subject The topic of the resource Complexity; Discrete Logarithm Problem; Matrix Key; Security Analysis Description An account of the resource Here in this model, a new mechanism is used for Public Key Cryptography. A generator matrix is used to generate a field with a large prime number. The generator matrix, prime number and quaternary vector are used as global variables. The Generator Matrix is powered by a private key to generate Public Key. Since the model is based on Discrete Logarithm Problem, which is Hard problem, the proposed algorithm supports the features like Authenticity of users, Security & Confidentiality of data transmitted. Going by the construction of the algorithm, Encryption is being done on blocks of data for which it consumes less computing resources. Going by complexity of the algorithm, the key length needed is about 72 bit lengths to provide sufficient strengths against crypto analysis. 2017 Taru Publications. Creator An entity primarily responsible for making the resource Krishna A.V.N.; Narayana A.H.; Madhura Vani K. Source A related resource from which the described resource is derived Journal of Discrete Mathematical Sciences and Cryptography, Vol-20, No. 2, pp. 407-412. 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 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/09720529.2015.1085738" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/09720529.2015.1085738</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020504274&doi=10.1080%2F09720529.2015.1085738&partnerID=40&md5=7890fcfa36d5b19274f2a9cc09edad1b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020504274&doi=10.1080%2f09720529.2015.1085738&partnerID=40&md5=7890fcfa36d5b19274f2a9cc09edad1b</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 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 Krishna A.V.N., Computer Science & Engineering Department, Faculty of Engineering, Christ University, Bangalore, 560029, Karnataka, India; Narayana A.H., Electrical Engineering, Indian Institute of Technology, Indore, 453552, Madhya Pradesh, India; Madhura Vani K., Computer Science & Engineering, Sreyas Institute of Engineering & Technology, Hyderabad, 500068, Telangana, 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 Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Parashar, Jyoti; Upreti, Kamal; Fatima, Iram; Gangwar, Divya; Saini, Ashok Kumar; Vats, Prashant Title A name given to the resource A Novel Architecture for a Medical Image Recognition System Using Deep Learning-Based Multiple Regression Evaluation 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 Smart Innovation, Systems and Technologies;Volume;398;pp.325-341 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-5200-3_23" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-5200-3_23</a> <a href="https://www.scopus.com/pages/publications/85218464062?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218464062?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 Parashar J., Department of Computer Science & Engineering, Dr. Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India; Fatima I., Department of AI & ML, Dr. Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India; Gangwar D., Department of Management, Babu Banarasi Das Institute of Technology & Management, New Delhi, India; Saini A.K., Department of Computer Science & Engineering, School of Computer Science & Engineering, Manipal University Jaipur, Rajasthan, Jaipur, India; Vats P., Department of Computer Science & Engineering, School of Computer Science & Engineering, Manipal University Jaipur, Rajasthan, Jaipur, India Description An account of the resource Models based on machine learning are optimization models that collect data, assess it, and deliver the reports required by specialists and management to make the best decisions. The application of contemporary machine learning allows the organization to quickly analyze photographs, differentiate voices assist in providing customer service, assess the information that is at hand, and uncover connections to aid in decision-making processes. The results of this investigation use quantitative methodologies to collect data and analyze it using mathematical procedures such as regression modeling as well as analysis of variance. Deep learning techniques applied to digital imaging, particularly in medical treatment, can increase picture quality, aid in modeling, aid in making the best possible diagnosis, and successfully address demands from patients. To analyze the hypothesis, investigators intend to utilize statistical approaches such as descriptive data analysis, regression evaluation, and analysis of variance (ANOVA). The authors employ the purposive sample approach to choose respondents from the healthcare industry. Purpose sampling is a non-probability sampling approach. Researchers collected data from 193 respondents working at hospitals that are privately owned in Southern Asia. As stated by the study, all factors, including efficiently meeting patient needs, have a probability value of under 0.05, indicating that they are statistically noteworthy. Following the study, the coefficient of variance (R squared) is 0.744, or 74.4%. According to the study, there is a high association between better image quality and ML-based digital picture identification systems. The recognition of patterns and the application of artificial intelligence to computerized recognition of pictures also have a close link. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource ANOVA analysis; Deep learning; Digital imaging; Regression analysis Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 21903018; ISBN: 978-981975199-0; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Novel Artificial Intelligence System for the Prediction of Interstitial Lung Diseases Subject The topic of the resource Deep learning; HRCT; ILD; Multi-label classification; Transfer learning Description An account of the resource Interstitial lung disease (ILD) encompasses a spectrum of more than 200 fatal lung disorders affecting the interstitium, contributing to substantial mortality rates. The intricate process of diagnosing ILDs is compounded by their diverse symptomatology and resemblance to other pulmonary conditions. High-resolution computed tomography (HRCT) assumes the role of the primary diagnostic tool for ILD, playing a pivotal role in the medical landscape. In response, this study introduces a computational framework powered by artificial intelligence (AI) to support medical professionals in the identification and classification of ILD from HRCT images. Our dataset comprises 3045 HRCT images sourced from distinct patient cases. The proposed framework presents a novel approach to predicting ILD categories using a two-tier ensemble strategy that integrates outcomes from convolutional neural networks (CNNs), transfer learning, and machine learning (ML) models. This approach outperforms existing methods when evaluated on previously unseen data. Initially, ML models, including Logistic Regression, BayesNet, Stochastic Gradient Descent (SGD), RandomForest, and J48, are deployed to detect ILD based on statistical measures derived from HRCT images. Notably, the J48 model achieves a notable accuracy of 93.08%, with the diagnostic significance of diagonal-wise standard deviation emphasized through feature analysis. Further refinement is achieved through the application of Marker-controlled Watershed Transformation Segmentation and Morphological Masking techniques to HRCT images, elevating accuracy to 95.73% with the J48 model. The computational framework also embraces deep learning techniques, introducing three innovative CNN models that achieve test accuracies of 94.08%, 92.04%, and 93.72%. Additionally, we evaluate five full-training and transfer learning models (InceptionV3, VGG16, MobileNetV2, VGG19, and ResNet50), with the InceptionV3 model achieving peak accuracy at 78.41% for full training and 92.48% for transfer learning. In the concluding phase, a soft-voting ensemble mechanism amplifies training outcomes, yielding ensemble test accuracies of 76.56% for full-training models and 92.81% for transfer learning models. Notably, the ensemble comprising the three newly introduced CNN models attains the pinnacle of test accuracy at 97.42%. This research is poised to drive advancements in ILD diagnosis, presenting a resilient computational framework that enhances accuracy and ultimately betters patient outcomes within the medical domain. 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Raju N.; Augustine D.P.; Chandra J. Source A related resource from which the described resource is derived SN Computer Science, Vol-5, No. 1 Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-023-02524-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-02524-3</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181497206&doi=10.1007%2Fs42979-023-02524-3&partnerID=40&md5=a4f3647e56761e09098ce41e53c92520" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181497206&doi=10.1007%2fs42979-023-02524-3&partnerID=40&md5=a4f3647e56761e09098ce41e53c92520</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2662995X | CS; 2023-2024; Vol-1; 00091-00092 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 Raju N., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Augustine D.P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Chandra J., Department of Computer Science, 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 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 novel assessment of bio-medical waste disposal methods using integrating weighting approach and hesitant fuzzy MOOSRA Subject The topic of the resource Bio-medical waste; Criteria importance through inter criteria correlation; Multi-criteria decision making; Multi-objective optimization on the basis of simple ratio analysis; Subjective and objective weight integrated approach; Waste management Description An account of the resource Bio-medical waste (BMW) management is highly important precaution for human health and environmental concern. There are several disposal treatment followed by medical practitioners in medical waste management. Here, a few disposal treatment is considered to be an alternatives. When assessing, it is necessary to evaluate and assume that all disposal treatment methods are safe and hygienic. In this way, every alternative assessment is evaluated based on the social acceptance, technology and operation, environmental protection, cost, noise and health risk. Finally the best alternative is chosen. When BMW is disposed and we select the best treatment method in BMW management, it can lead to multi-criteria decision making (MCDM) processes related to uncertain critical assessments. When making a decision, the decision makers having some hesitation to give their suggestions. Therefore, here we use hesitant MCDM method. In today's practice we have choose five methods of BMW disposal methods used in the medical world and we have its alternatives. One of these alternative is sorted by six criteria weights for selecting the best method. The main aim of this research paper is propose a new methodology of hesitant fuzzy weight finding technique, it is named as Hesitant Fuzzy Subjective and Objective Weight Integrated Approach (HF-SOWIA) and also propose a new hesitant fuzzy rank finding methodology, it is named as Hesitant Fuzzy Multi-Objective Optimization on the basis of Simple Ratio Analysis (HF-MOOSRA). After evaluation, the result shows that autoclaving is the best alternative for BMW disposal treatment methods. Furthermore, sensitivity analysis is make in order to observe the difference of alternative ranking when the importance of subjective and objective weights changes. 2020 Elsevier Ltd Creator An entity primarily responsible for making the resource Narayanamoorthy S.; Annapoorani V.; Kang D.; Baleanu D.; Jeon J.; Kureethara J.V.; Ramya L. Source A related resource from which the described resource is derived Journal of Cleaner Production, Vol-275 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 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.jclepro.2020.122587" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jclepro.2020.122587</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088360925&doi=10.1016%2Fj.jclepro.2020.122587&partnerID=40&md5=7a8177dff1cb739fd7cbec29b67bd612" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088360925&doi=10.1016%2fj.jclepro.2020.122587&partnerID=40&md5=7a8177dff1cb739fd7cbec29b67bd612</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9596526; CODEN: JCROE 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 Narayanamoorthy S., Department of Mathematics, Bharathiar University, Coimbatore, 641 046, India; Annapoorani V., Department of Mathematics, Bharathiar University, Coimbatore, 641 046, India; Kang D., Department of Industrial and Management Engineering, Inje University 197 Inje-ro, Gimhae-si, 50834, Gyeongsangnam-do, South Korea; Baleanu D., Department of Mathematics, Cankaya University, Balgat, Ankara, Turkey, Turkey and Institute of Space Sciences, Magurele, Bucharest, Romania; Jeon J., Department of Industrial & Systems Engineering, Gyeongsang National University, Jinju- Si, Gyeongsangnam-do, South Korea; Kureethara J.V., CHRIST (Deemed to Be University), Bangalore, India; Ramya L., Department of Mathematics, Bharathiar University, Coimbatore, 641 046, 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 Novel Assessment of Healthcare Waste Disposal Methods: Intuitionistic Hesitant Fuzzy MULTIMOORA Decision Making Approach Subject The topic of the resource decision making; Healthcare waste management; hesitant fuzzy; intuitionistic fuzzy set; MCDM; MULTIMOORA Description An account of the resource Waste produced from medical facilities systems incorporates a blend of dangerous waste which can posture dangers to humans and ecological receptors. Lacking administration of healthcare waste can prompt hazard to medicinal service specialists, patients, public health, communities and the wider environment. Hence, proper management of healthcare waste is imperative to reduce the associated health and environment risk. In this paper, we extend the MULTIMOORA decision making method with intuitionistic hesitant fuzzy set to evaluate the healthcare waste treatment methods. Intuitionistic hesitant fuzzy set is a generalized form of a hesitant fuzzy set. Intuitionistic hesitant fuzzy set considers the uncertainty of data in a single framework and take more information into account. The MULTIMOORA method consists of three parts namely the ratio system, reference point approach and the full multiplicative form. In the optimal ranking methods, the IHF-MULTIMOORA method is uncomplicated it is able to be used practically with high dimension intuitionistic hesitant fuzzy sets. For pathological, pharmaceutical, sharp, solid and chemical wastes, the preferred waste disposal methods are deep burial, incineration, autoclave, deep burial, and chemical disinfection, respectively. 2013 IEEE. Creator An entity primarily responsible for making the resource Geetha S.; Narayanamoorthy S.; Kang D.; Kureethara J.V. Source A related resource from which the described resource is derived IEEE Access, Vol-7, pp. 130283-130299. 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 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACCESS.2019.2940540" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCESS.2019.2940540</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077758699&doi=10.1109%2FACCESS.2019.2940540&partnerID=40&md5=19870b44fd96448c7289d2ed18948eed" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077758699&doi=10.1109%2fACCESS.2019.2940540&partnerID=40&md5=19870b44fd96448c7289d2ed18948eed</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 21693536 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 Geetha S., Department of Mathematics, Bharathiar University, Coimbatore, 641046, India; Narayanamoorthy S., Department of Mathematics, Bharathiar University, Coimbatore, 641046, India; Kang D., Department of Industrial and Management Engineering, Inje University, Gimhae, 50834, South Korea; Kureethara J.V., Department of Mathematics, 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 A Novel Auto Encoder- Network- Based Ensemble Technique for Sentiment Analysis Using Tweets on COVID- 19 Data Description An account of the resource The advances in digitalization have resulted in social media sites like Twitter and Facebook becoming very popular. People are able to express their opinions on any subject matter freely across the social media networking sites. Sentiment analysis, also termed emotion artificial intelligence or opinion mining, can be considered a technique for analyzing the mood of the general public on any subject matter. Twitter sentiment analysis can be carried out by considering tweets on any subject matter. The objective of this research is to implement a novel algorithm to classify the tweets as positive or negative, based on machine learning, deep learning, the nature inspired algorithm and artificial neural networks. The proposed novel algorithm is an ensemble of the decision tree algorithm, gradient boosting, Logistic Regression and a genetic algorithm based on the auto-encoder technique. The dataset under consideration is tweets on COVID-19 in May 2021. 2024 Taylor & Francis Group, LLC. Creator An entity primarily responsible for making the resource Jyothsna R.; Rohini V.; Paulose J. Source A related resource from which the described resource is derived Machine Intelligence: Computer Vision and Natural Language Processing, pp. 257-272. Publisher An entity responsible for making the resource available CRC Press 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/10.1201/9781003424550-14" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003424550-14</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173359844&doi=10.1201%2F9781003424550-14&partnerID=40&md5=55d5e5402de5728b2b231c0b7073ed7a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173359844&doi=10.1201%2f9781003424550-14&partnerID=40&md5=55d5e5402de5728b2b231c0b7073ed7a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100096031-0; 978-103220199-3 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 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 Jyothsna R., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Paulose J., Department of Computer Science, Christ University, Karnataka, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 novel automated method for coconut grading based on audioception Subject The topic of the resource Coconut grading; Dagging; Fast Fourier Transform; Naive bayes; Sequential minimal optimization (SMO); Sound processing Description An account of the resource The quality of the coconuts used for various purposes is of utmost importance. Demand for better quality products is constantly on the rise due to the improvements in the standard of living of people. There is a possibility that a bad coconut goes unnoticed by the traders, as it is hard to decide if a coconut is good or bad by relying only on its external appearance. Traditionally, quality assessment is carried out manually with the help of three senses; sight, hearing and smell. In the proposed work, a sound processing technique is used in an attempt to automate this process which overcomes the drawbacks of manual processing, which can be used in large godowns and warehouses. This proposed method provides the quality assessment of the coconut purely based on audioception. While creating the database, coconuts varying in size, shape, color and water content were taken from several places as a source for the dataset. Features are extracted from the sound pattern produced by the dropped coconut, which forms the basis for classification. Sequential Minimal Optimization (SMO), Dagging and Naive Bayes classifiers were used and the results obtained were found to be encouraging. 2005 ongoing JATIT & LLS. Creator An entity primarily responsible for making the resource Thomas P.; Anita H.B. Source A related resource from which the described resource is derived Journal of Theoretical and Applied Information Technology, Vol-95, No. 10, pp. 2265-2273. Publisher An entity responsible for making the resource available Asian Research Publishing Network 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="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020192617&partnerID=40&md5=ae8d39d517a8b74afc99f48d0170639e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020192617&partnerID=40&md5=ae8d39d517a8b74afc99f48d0170639e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19928645 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 Thomas P., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Anita H.B., Department of Computer Science, Christ University, Bengaluru, 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 novel automated method for the detection of strangers at home using parrot sound Subject The topic of the resource Crest Factor; Dynamic Ratio; Fourier transform; NavieBayes; Sound Analysis. Description An account of the resource The sound produced by parrots is used to gather information about their behavior. The study of sound variation is important to obtain indirect information about the characteristics of birds. This paper is the first of a series in analyzing bird sounds, and establishing the adequate relation of bird's sound. The paper proposes a probabilistic method for audio feature classification in a short interval of time. It proposes an application of digital sound processing to check whether the parrots behave strangely when a stranger comes. The sound is classified into different classes and the emotions of the birds are analyzed. The time frequency of the signal is checked using spectrogram. It helps to analyze the parrot vocalization. The mechanical origin of the sound and the modulation are deduced from spectrogram. The spectrogram is also used to check the amplitude and frequency modulation of sound and the frequency of the sound are detected and analyzed. This research and its findings will help the bird lovers to know the bird behavior and plan according to that. The greater understanding of birds will help the bird lovers to feed and care for birds. BEIESP. Creator An entity primarily responsible for making the resource Antony F.; Anita H.B. Source A related resource from which the described resource is derived International Journal of Recent Technology and Engineering, Vol-7, No. 6, pp. 911-915. Publisher An entity responsible for making the resource available Blue Eyes Intelligence Engineering and Sciences Publication Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067039676&partnerID=40&md5=6c8f4d3378b8b2a9dd5e95d0caed8957" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067039676&partnerID=40&md5=6c8f4d3378b8b2a9dd5e95d0caed8957</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22773878 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 Antony F., CHRIST (Deemed to be University), India; Anita H.B., Department of Computer Science at CHRIST (Deemed to be University), India