505 20 11858 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Building Robust FinTech Applications and Reducing Strain on Strategic Data Centers using the LoTus Model Subject The topic of the resource Agile; Architecture; FinTech; LoTus Model; Scrum; Software Development; Software Engineering Description An account of the resource Agile is a well-known project management approach that has been used for many years. It places a strong emphasis on client satisfaction, adaptability, and teamwork. Agile was first developed as a software development approach, but it has now been modified for application in other sectors including marketing and finance. The Agile Manifesto, which was released in 2001 and explains the principles and ideals of Agile development, is the foundation of the Agile ideology. One or more of the guiding principles is to adapt to change instead of following a plan, prioritize functional software over thorough documentation, and collaborate with customers over negotiating contracts. Agile has gained popularity over time as businesses try to be adaptable and responsive to their customers' constantly changing business demands. The lack of predictability in Agile is one of its key drawbacks. Agile stresses client cooperation and adaptation, therefore the finished product could differ somewhat from what was originally planned. For businesses that depend on meticulous planning and a rigid schedule, this lack of predictability can be problematic. It faced a serious problem during the process of building a finance application called JazzFinance. This has led to build another robust and systematic software development method called as LoTus model. The proposed LoTus is an acronym for two abbreviations. Those are lean optimization TypeFace for Unified Systems (LoTus) and Locate dependencies, optimize for reusability, Test-Driven environment, Unify Design and Scalability. This article goes through the development of LoTus and how it has helped us build a stable finance application within a small amount of stipulated time. 2023 IEEE. Creator An entity primarily responsible for making the resource Lakshmikanth Rajath Mohan T.; Jayapandian N. Source A related resource from which the described resource is derived Proceedings of the 7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023, pp. 1176-1181. 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/ICICCS56967.2023.10142355" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICCS56967.2023.10142355</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163848977&doi=10.1109%2FICICCS56967.2023.10142355&partnerID=40&md5=971488e21a743901a9c81f494e2d316c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163848977&doi=10.1109%2fICICCS56967.2023.10142355&partnerID=40&md5=971488e21a743901a9c81f494e2d316c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039725-3 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 Lakshmikanth Rajath Mohan T., CHRIST (Deemed to Be University), School of Engineering and Technology, India; Jayapandian N., CHRIST (Deemed to Be University), School of Engineering and Technology, 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 ANN Based MPPT Using Boost Converter for Solar Water Pumping Using DC Motor Subject The topic of the resource ANN; BLDC; Boost Converter; MPPT; PID; SPV Description An account of the resource The solar DC pump system is simple to set up and run completely on its own without the need for human intervention. Solar DC pumps require fewer solar panels to operate than AC pumps. Solar PV Arrays, a solar DC regulator, and a DC pump make up the Solar DC Pump system. The nonlinear I-V characteristics of solar cells, PV modules have average efficiency compare to other forms of energy, and output power is affected by solar isolation and ambient temperature. The prominent factor to remember is that there will be a significant power loss owing to a failure to correspond between the source and the load. In order to get the most power to load from the PV panel, MPPT is implemented in the converter circuit using PWM and a microcontroller. In order to give the most power to load from the source, the solar power system should be designed to its full potential. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Jurme T.; Phelgay T.; Gyeltshen P.; Dorji S.; Tobgay T.; Praghash K.; Chidambaram S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-647 LNNS, pp. 841-851. 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/10.1007/978-3-031-27409-1_77" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-27409-1_77</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163327588&doi=10.1007%2F978-3-031-27409-1_77&partnerID=40&md5=2724be996b8e1b3b82d9451129a19876" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163327588&doi=10.1007%2f978-3-031-27409-1_77&partnerID=40&md5=2724be996b8e1b3b82d9451129a19876</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303127408-4 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 Jurme T., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Phelgay T., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Gyeltshen P., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Dorji S., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Tobgay T., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Praghash K., Department of Electronics and Communication Engineering, Christ University, Bengaluru, India; Chidambaram S., Department of Electronics and Communication Engineering, Christ 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 Tracking and Localization of Devices - An IoT Review Subject The topic of the resource Internet of Things; Localization; Tracking; Wireless Sensor Networks Description An account of the resource S everal IoT applications have immediate impacts on daily lives. The notion of "connected life, which includes IoT has been discussed. Apps that rely on localization are also featured. IoT is originally used to determine the precise position of things, animals, and people. The second tracks everyone and everything that's on the move, including pets, kids, and the elderly people. Localization and tracking are integral parts of security and surveillance systems in interconnected homes. This study reviews the state-of-the-art IoT-based localization and tracking approaches and outlines the key technical aspects, and contrast localization initiatives based on Internet of Things (IoT) with those that do not show how they might be used in a variety of contexts. It is now well established that localization and tracking methods based on the Internet of Things (IoT) are more pervasive and accurate than their predecessors. 2023 IEEE. Creator An entity primarily responsible for making the resource Sivadevuni S.S.; Ravichandran S.K. Source A related resource from which the described resource is derived 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, pp. 1321-1325. 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/ICICT57646.2023.10134278" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICT57646.2023.10134278</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163485509&doi=10.1109%2FICICT57646.2023.10134278&partnerID=40&md5=c87cc7a79ab413078cfba05ee16e6c84" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163485509&doi=10.1109%2fICICT57646.2023.10134278&partnerID=40&md5=c87cc7a79ab413078cfba05ee16e6c84</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039849-6 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 Sivadevuni S.S., Department of Computer Science and Engineering, Christ University, Bengaluru, India; Ravichandran S.K., Department of Computer Science and Engineering, Christ 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 An Advanced and Ideal Method for Tumor Detection and Classification from MRI Image Using Gamma Distribution and Support Vector Machine Subject The topic of the resource Diagnosis process; Gamma distribution; Tumor Description An account of the resource As indicated by a measurable report distributed by the registry of central brain tumor at United States (CBTRUS), roughly 59,550 individuals were recently diagnosed to have essential benign and essential harmful brain tumors in 2017. Besides, in excess of 91,000 individuals, in the United States alone, were living with an essential harmful cerebrum tumor and 367,000 were living with an essential kind brain tumor. The task of detecting the position of the tumor in the body of the patient is the starting point for a medical treatment in the diagnosis process. The main aim of this study is to design a computer system, which is able to detect the tumor presence in the digital images of the brain in the patient and to accurately define its borderline. In this proposed model, gamma distribution method is used for training, testing, and for the feature extraction process, while SVM, support vector machine is used for the classification process. Most of the algorithms find it difficult to segment the tumors that were present in the edges. But with the help of gamma distribution along with the use of edge analysis, it is easier to identify those tumor areas that are present in the edges, thus making it easier for the preprocessing process. Gamma distribution also provides us with high accuracy, and it can also point the exact location of the tumor than compared to other algorithms. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Aruna S.K.; Sambandam R.K.; Thaiyalnayaki S.; Vetriveeran D. Source A related resource from which the described resource is derived Smart Innovation, Systems and Technologies, Vol-313, pp. 439-447. 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/10.1007/978-981-19-8669-7_38" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-8669-7_38</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164916687&doi=10.1007%2F978-981-19-8669-7_38&partnerID=40&md5=06153dd2ee2e5669fdff2f617354fb38" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164916687&doi=10.1007%2f978-981-19-8669-7_38&partnerID=40&md5=06153dd2ee2e5669fdff2f617354fb38</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21903018; ISBN: 978-981198668-0 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 Aruna S.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University)Kengeri Campus, Karnataka, Bangalore, India; Sambandam R.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University)Kengeri Campus, Karnataka, Bangalore, India; Thaiyalnayaki S., Department of Computer Science and Engineering, School of Computing, Bharath Institute of Higher Education and Research (Deemed to be University), Tamilnadu, Chennai, India; Vetriveeran D., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University)Kengeri Campus, 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 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 Characteristic Mode Analysis of Fashion Brands Conductive Logos as Potential Radiators Subject The topic of the resource bandwidth capabilities; Characteristic modes analysis; fashion brands; propagation modes Description An account of the resource A few popular fashion brand logos, which can be employed as potential radiating elements, are investigated in this paper based on the theory of characteristic mode (TCM). Such an analysis would further help design multi-band wearable antennas within the frequency range from 1 to 6 GHz. The resonant behavior and bandwidth capability for various modes are presented and discussed. It is observed that all the studied logos demonstrate a first resonant frequency around 1.5 GHz, while both Lacoste and Louis Vuitton logos show wider modal bandwidths capabilities. 2023 IEEE. Creator An entity primarily responsible for making the resource Kumar N.; Koohestani M.; Khanna R. Source A related resource from which the described resource is derived 2023 IEEE Radio and Antenna Days of the Indian Ocean, RADIO 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/RADIO58424.2023.10146095" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/RADIO58424.2023.10146095</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163370914&doi=10.1109%2FRADIO58424.2023.10146095&partnerID=40&md5=b0d5716a69bc44976e1a15bf749f7669" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163370914&doi=10.1109%2fRADIO58424.2023.10146095&partnerID=40&md5=b0d5716a69bc44976e1a15bf749f7669</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034791-3 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 Kumar N., Christ University, Eced, Bengaluru, India; Koohestani M., Ietr, ole Supieure d'ectronique de l'Ouest, Cnrs 6164, Angers, Paris, France; Khanna R., Thapar Institute of Engineering and Technology, Punjab, 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 Financial Big Data Analysis Using Anti-tampering Blockchain-Based Deep Learning Subject The topic of the resource Anti-Tampering Model; Blockchain; Deep Learning; Financial Big Data Description An account of the resource This study recommends using blockchains to track and verify data in financial service chains. The financial industry may increase its core competitiveness and value by using a deep learning-based blockchain network to improve financial transaction security and capital flow stability. Future trading processes will benefit from blockchain knowledge. In this paper, we develop a blockchain model with a deep learning framework to prevent tampering with distributed databases by considering the limitations of current supply-chain finance research methodologies. The proposed model had 90.2% accuracy, 89.6% precision, 91.8% recall, 90.5% F1 Score, and 29% MAPE. Choosing distributed data properties and minimizing the process can improve accuracy. Using code merging and monitoring encryption, critical blockchain data can be obtained. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Praghash K.; Yuvaraj N.; Peter G.; Stonier A.A.; Priya R.D. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-647 LNNS, pp. 1031-1040. 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/10.1007/978-3-031-27409-1_95" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-27409-1_95</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163328423&doi=10.1007%2F978-3-031-27409-1_95&partnerID=40&md5=b13127a4758a0b68493932107a635851" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163328423&doi=10.1007%2f978-3-031-27409-1_95&partnerID=40&md5=b13127a4758a0b68493932107a635851</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303127408-4 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 Praghash K., Department of Electronics and Communication Engineering, Christ University, Bengaluru, India; Yuvaraj N., Department of Research and Publications, ICT Academy, IIT Madras Research Park, ManagerChennai, India; Peter G., CRISD, School of Engineering and Technology, University of Technology Sarawak, Sibu, Malaysia; Stonier A.A., School of Electrical Engineering, Vellore Institute of Technology, Tamil Nadu, Vellore, India; Priya R.D., Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, Tamil Nadu, Coimbatore, 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 Tumor Infiltration of Microrobot using Magnetic torque and AI Technique Subject The topic of the resource ANFIS; CNN; Disease Prediction; Machine learning Description An account of the resource Because of their surroundings and lifestyle alternatives, human beings, these days be afflicted by a huge style of illnesses. thus, early contamination prediction will become crucial. on the other hand, primarily based just on signs, docs warfare to make correct forecasts. The most challenging issue is accurately forecasting illnesses, which is why machine learning is essential to accomplish this task. To identify concealed patterns within vast amounts of medical data, disease information is processed using data mining techniques. We evolved a extensive contamination prediction primarily based on the affected person's signs. We rent the device getting to know techniques Convolutional Neural network (CNN) and ANFIS to exactly count on sickness (adaptive community-based totally fuzzy inference machine). For an correct forecast, this trendy illness prediction considers the character's way of life picks and fitness history. ANFIS outperforms CNN's set of rules in phrases of popular infection prediction, with an accuracy price of 96.7%. additionally, CNN consumes extra memory and processing energy than ANFIS because it trains and assessments on facts from the UCI repository. The Anaconda notebook is a suitable tool for implementing Python programming as it contains a range of libraries and header files that enhance the accuracy and precision of the process. 2023 IEEE. Creator An entity primarily responsible for making the resource Shalini R.; Mishra L.; Athulya S.; Chimankar A.G.; Kandavalli S.R.; Keshav Kumar K.; Selvan R.S. Source A related resource from which the described resource is derived ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings 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/ViTECoN58111.2023.10157336" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ViTECoN58111.2023.10157336</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165534220&doi=10.1109%2FViTECoN58111.2023.10157336&partnerID=40&md5=ecb0e66b1c15e33dea8bbf8b83f3e250" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165534220&doi=10.1109%2fViTECoN58111.2023.10157336&partnerID=40&md5=ecb0e66b1c15e33dea8bbf8b83f3e250</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034798-2 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 Shalini R., School of Computing Sciences, Vels Institute of Science Technology and Advanced Studies, Department of BCA & IT, Chennai, India; Mishra L., Khwaja Moinuddin Chishti Language University, Department of Electronics and Communication Engineering, Uttar Pradesh, India; Athulya S., Christ Deemed to Be University, Faculty of Engineering, Department of Computer Science and Engineering, Bangalore, India; Chimankar A.G., Chatrapati Shivaji BCA and BCS College, Department of B.Sc. Computer Science, Maharashtra, India; Kandavalli S.R., Sri Padmavati Mahila Visva Vidyalayam, Department of Electronics and Communication Engineering, Tirupati, India; Keshav Kumar K., G. Narayanamma Institute of Technology and Science, Department of Humanities and Mathematics, Hyderabad, India; Selvan R.S., Annamacharya Institute of Technology & Sciences, Department of Electronics and Communication Engineering, Tirupati, 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 Deep Convolutional Kernel Neural Network based Approach for Stock Market Prediction using Social Media Data Subject The topic of the resource Convolutional Neural Network (CNN); Extreme Learning Machine (ELM); Kernel Extreme Learning Machine (KELM) Description An account of the resource Several economists and social scientists have held a longstanding fascination with the practice of stock market prediction. As the stock market is essentially uncontrollable chaos, many experts believe that trying to predict it is futile. Due to the complexity of the numerous factors, accurate stock price predictions are notoriously difficult to achieve. While the market behaves more like a scale than a voting machine over the long run, its behavior may be predicted with some certainty. Information from Twitter is used into the algorithm. In this proposed method, a convolutional extreme learning machine model with kernel support was introduced (CKELM). To improve feature extraction and data classification, the CKELM model builds on the KELM's hidden layer by adding convolutional and subsampling layers. The convolutional layer and the subsampling layer do not employ the gradient technique to fine-tune their parameters because some designs worked well with random weights. When compared to popular models like CNN and KELM, The proposed model fares quite well, with an accuracy of around 98.3 percent. 2023 IEEE. Creator An entity primarily responsible for making the resource Agarwal V.; Ravi Kumar P.; Shankar S.; Praveena S.; Dubey V.; Chauhan A. Source A related resource from which the described resource is derived Proceedings of the 7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023, pp. 78-82. 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/ICICCS56967.2023.10142522" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICCS56967.2023.10142522</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163888913&doi=10.1109%2FICICCS56967.2023.10142522&partnerID=40&md5=a248d4f3e9490f1a707d39da60ff171f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163888913&doi=10.1109%2fICICCS56967.2023.10142522&partnerID=40&md5=a248d4f3e9490f1a707d39da60ff171f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039725-3 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 Agarwal V., ATLAS SkillTech University, ISME, Maharashtra, Mumbai, India; Ravi Kumar P., Kristu Jayanti College (Autonomous), K.Narayanapura, Department of Media Studies, Karnataka, Bangalore, India; Shankar S., Computational Intelligence Srmist Kattankulathur, Tamil Nadu, Chengalpattu, India; Praveena S., Mahatma Gandhi Institute of Technology (MGIT), Department of Electronics and Communication Engineering, Telangana, Hyderabad, India; Dubey V., Computer Science and Engineering, Bharat Institute of Engineering and Technology, Telangana, Hyderabad, India; Chauhan A., CHRIST (Deemed to Be University), Department of Life 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 Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Enhancing red wine quality prediction through Machine Learning approaches with Hyperparameters optimization technique Subject The topic of the resource Grid search; Hyperparameter tuning; Machine learning classifiers; Red wine; Regressors Description An account of the resource In light of the intricacy of the winemaking process and the wide variety of elements that could affect the taste and quality of the finished product, predicting red wine quality is difficult. ML methods have been widely used in forecasting red wine quality from its chemical characteristics in recent years. This Paper evaluated the comparison of classification and regression methods to predict the quality of red wine and performed the initial data analysis and exploratory data analysis on the data. This study implemented different Classifiers and Regressors that were trained and tested. Contrasted and Comparative analysis of the accuracies of eight models with hyperparameter tuning optimization, including Logistic Regression, Gradient Boosting, Extra Tree, Ada Boost, Random Forest, Support Vector Classifier, and Decision Tree, Knn and measured the classification report with F1, Accuracy, and Recall Scores. For Imbalance data, SMOTE Classifier was used. This study performed the Cross-validation technique, such as Grid search and with the best hyperparameters tuning. The study's findings demonstrated that the Gradient Boosting technique accurately predicted red wine quality. This research shows the promising results of Gradient Boosting for predicting red wine quality and adds important context to the usage of machine learning classifiers for this challenge. 2023 IEEE. Creator An entity primarily responsible for making the resource Amzad Basha M.S.; Desai K.; Christina S.; Sucharitha M.M.; Maheshwari A. Source A related resource from which the described resource is derived 2023 2nd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 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/ICEEICT56924.2023.10157719" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEEICT56924.2023.10157719</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165756417&doi=10.1109%2FICEEICT56924.2023.10157719&partnerID=40&md5=10ebee4274e6253fb6d090659a62ed73" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165756417&doi=10.1109%2fICEEICT56924.2023.10157719&partnerID=40&md5=10ebee4274e6253fb6d090659a62ed73</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039763-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Amzad Basha M.S., GITAM School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India; Desai K., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Christina S., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Sucharitha M.M., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Maheshwari A., School of Commerce, Finance, Christ (Deemed to Be University), Department of Commerce, Ghaziabad, 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 Innovative Method for Alzheimer Disease Prediction using GP-ELM-RNN Subject The topic of the resource Alzheimer Disease (AD); GP (Garson-Purned); Grey Level Co-occurrence Matrix (GLCM) Description An account of the resource Brain illnesses are notoriously challenging because of their fragility, surgical complexity, and high treatment costs. Contrarily, it is not obligatory to carry out the operation, as the outcomes of the procedure may fall short of expectations. Adult-onset Alzheimer's disease, which causes memory loss and losing information to varied degrees, is one of the most common brain diseases. This will vary from person to person based on their current health situation. This highlights the need of using CT brain scans to classify the extent of memory loss and determine the patient's risk for Alzheimer's disease. The four main goals of Alzheimer's disease detection are preprocessing the data, extracting features, selecting features, and training the model with GP-ELM-RNN. The Replicator Neural Network has been utilized earlier for AD detection, however this study offers an improved version of the network, modified with ELM learning and the Garson algorithm. From this study, it is deduced that the proposed method is not only efficient, but also quite precise. In this research, GP-ELM-RNN network is built to four groups of images representing different stages of Alzheimer's disease: very mildly demented, mildly demented, averagely demented, and non-demented. The class of very mildly demented patients was found to have the highest accuracy (99.1%) and specificity (0.984%). As compared to the ELM and RNN models, this technique achieves superior accuracy (around 99.23%). 2023 IEEE. Creator An entity primarily responsible for making the resource Abd Algani Y.M.; Vidhya S.; Ghai B.; Acharjee P.B.; Kathiravan M.N.; Dwivedi V.K. Source A related resource from which the described resource is derived Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, pp. 723-728. 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/ICAAIC56838.2023.10140571" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAAIC56838.2023.10140571</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163684137&doi=10.1109%2FICAAIC56838.2023.10140571&partnerID=40&md5=d53996823d1b1b0781a2f67268192103" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163684137&doi=10.1109%2fICAAIC56838.2023.10140571&partnerID=40&md5=d53996823d1b1b0781a2f67268192103</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166545630-2 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 Abd Algani Y.M., The Arab Academic College for Education in Israel-Haifa, Department of Mathematics, Israel; Vidhya S., Rmk College of Engineering and Technology, S&H(Mathematics), Tamilnadu, Chennai, India; Ghai B., Ccsit Teerthankar Mahaveer University, Uttar Pradesh, Moradabad, India; Acharjee P.B., Christ University, Faculty Member, Maharashtra, Pune, India; Kathiravan M.N., Dr. N.G.P Arts and Science College, Department of Biotechnology, Tamil Nadu, Coimbatore, India; Dwivedi V.K., Vishwavidyalaya Engineering College, Department of Mathematics, Chhattisgarh, Surguja, 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 Characteristic Mode Analysis of Metallic Automobile Logo Geometry Subject The topic of the resource 5G; Automobile logos; multi-band; Theory of characteristic mode (TCM) Description An account of the resource This paper presents a characteristic mode analysis of a few popular automobile logo geometries. It is performed to get an insight into the physical behavior of those geometries which can be employed as a radiating element, such as an antenna. Such an analysis helps design multi-band and multi-mode antennas suitable for 5G sub-6 GHz bands. The resonant behavior, bandwidth capability, and modal current distribution analysis are presented for various modes of different automobile logo geometries, demonstrating that Audi, Suzuki, and Volkswagen logos show multi-band performance. Moreover, due to having symmetric modes, the BMW logo was found to be suitable for designing a circularly polarized antenna. 2023 IEEE. Creator An entity primarily responsible for making the resource Kumar N.; Seetharamdoo D.; Koohestani M. Source A related resource from which the described resource is derived 2023 IEEE Radio and Antenna Days of the Indian Ocean, RADIO 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/RADIO58424.2023.10146080" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/RADIO58424.2023.10146080</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163297269&doi=10.1109%2FRADIO58424.2023.10146080&partnerID=40&md5=d0a5b89524599273cf8c97a54a5eb899" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163297269&doi=10.1109%2fRADIO58424.2023.10146080&partnerID=40&md5=d0a5b89524599273cf8c97a54a5eb899</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034791-3 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 Kumar N., Christ University, Eced, Bengaluru, India; Seetharamdoo D., Univ Gustave Eiffel, COSYS-LEOST, Villeneuve d'Ascq, F-59650, France; Koohestani M., Eseo School of Engineering, Eeed, Angers, France Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource On Automatic Target Recognition (ATR) using Inverse Synthetic Aperture Radar Images Subject The topic of the resource Automatic Target Recognition; Deep learning; Feature extraction; Image Classification; ISAR Image Detection; Ship Classification Description An account of the resource Inverse Synthetic Aperture Radar (ISAR) is used to image sea surface targets during day/night and all-weather capabilities for applications such as coastal surveillance, ship self-defense, suppression of drug trafficking etc. Hence automating classification of ships by means of machine learning methods has become more significant. Typical classification approaches consist of pre-processing, feature extraction and processing by classifiers. Image processing techniques are applied for pre-processing ISAR images. Transformation invariant features are then extracted to which classifiers such as SVM, Neural Networks (NNs) are applied. The performance of these algorithms depend on the manually chosen features and is trained to perform well for different target profiles. The target image (profile of target) varies depending on the target type, aspect angle and motion introduced due to different sea states. In addition, Deep learning methods are also being explored for classification of ships. The challenge is to classify ships for different sea conditions and image acquisition parameters with limited database and processing resource. 2023 IEEE. Creator An entity primarily responsible for making the resource Sudarson Rama Perumal T.; Gaurav G.S.; Helen Josephine V.L.; Joshua Samuel Raj R. Source A related resource from which the described resource is derived 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, pp. 953-956. 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/ICICT57646.2023.10134428" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICT57646.2023.10134428</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163540791&doi=10.1109%2FICICT57646.2023.10134428&partnerID=40&md5=1d810dbce0359215bca2aca7ef444f55" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163540791&doi=10.1109%2fICICT57646.2023.10134428&partnerID=40&md5=1d810dbce0359215bca2aca7ef444f55</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039849-6 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 Sudarson Rama Perumal T., Dept. of CSE, Rohini College of Engineering and Technology, TamilNadu, India; Gaurav G.S., Dept. of. ISE, CMR Institute of Technology, Bengaluru, India; Helen Josephine V.L., Business Analytics, School of Business and Management, Christ University, Bangalore, India; Joshua Samuel Raj R., Faculty of EDICT, Bahrain Polytechnic, Isa Town, Bahrain 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 Earlier Stage Identification of Bone Cancer with Regularized ELM Subject The topic of the resource Canny Edge Detection; Improved Harris Corner Detection; Regularized Extreme Learning Machine (RELM) Description An account of the resource A major focus of current research in the field of image processing is the application of such methods to the field of medical imaging. While dealing with biological issues like fractures, canoers, ulcers, etc., image processing facilitated pinpointing the precise cause and tailoring a remedy. In the field of tumor identification, medical imaging has set a new standard by overcoming a number of challenges. Medical imaging is the practice of generating images of the human body for diagnostic or exploratory purposes. Because of its high image quality, MRI is the method of choice for detecting tumors. This research study proposes the integration of RLM to detect tumors and presents an automatic bone cancer detection system to assist oncologists in making early diagnosis of bone malignancies, which in turn allows patients to receive treatment as soon as possible. This research work also proposes to detect bone tumors by using a combination of the RELM based M3 filtering, Canny Edge segmentation, and the Enhanced Harris corner approach. When compared to other models like CNN, ELM, and RNN, the suggested technique achieves an accuracy of around 97.55%. 2023 IEEE. Creator An entity primarily responsible for making the resource Murugesan S.; Sharma N.; Jayalakshmi N.; Pant K.; Chauhan A.; Acharjee P.B. Source A related resource from which the described resource is derived Proceedings of the 7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023, pp. 1849-1854. 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/ICICCS56967.2023.10142670" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICCS56967.2023.10142670</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163833300&doi=10.1109%2FICICCS56967.2023.10142670&partnerID=40&md5=a3f783e2dac007237fe41c784bf6838c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163833300&doi=10.1109%2fICICCS56967.2023.10142670&partnerID=40&md5=a3f783e2dac007237fe41c784bf6838c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835039725-3 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 Murugesan S., R.M.D Engineering College, Kavaraipettai, Tamilnadu, Tiruvallur, India; Sharma N., Lovely Professional University, Department of Physical Education, Punjab, India; Jayalakshmi N., PSNA College of Engineering and Technology, Tamilnadu, Dindigul, India; Pant K., Graphic Era Deemed to Be University, Department of Biotechnology, Uttrakhand, Dehradun, India; Chauhan A., CHRIST (Deemed to Be University), Department of Life Sciences, Karnataka, Bengaluru, India; Acharjee P.B., CHRIST University, Computer Science, Maharashtra, Pune, 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 Model Using Interacted-ARIMA andANN Models forEfficient Forecasting Subject The topic of the resource INTARIMA; Interacted lagged variables; Interaction; Time series Description An account of the resource When two models applied to the same dataset produce two different sets of forecasts, it is a good practice to combine the forecasts rather than using the better one and discarding the other. Alternatively, the models can also be combined to have a hybrid model to obtain better forecasts than the individual forecasts. In this paper, an efficient hybrid model with interacted ARIMA (INTARIMA) and ANN models is proposed for forecasting. Whenever interactions among the lagged variables exist, the INTARIMA model performs better than the traditional ARIMA model. This is validated through simulation studies. The proposed hybrid model combines forecasts obtained through the INTARIMA model from the dataset, and those through the ANN model from the residuals of INTARIMA, and produces better forecasts than the individual models. The quality of the forecasts is evaluated using three error metrics viz., Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Empirical results from the application of the proposed model on the real dataset - lynx - suggest that the proposed hybrid model gives superior forecasts than either of the individual models when applied separately. The methodology is replicable to any dataset having interactions among the lagged variables.. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Baskaran T.; John N.; Dhandra B.V. Source A related resource from which the described resource is derived Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol-14078 LNAI, pp. 747-756. 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/10.1007/978-3-031-36402-0_69" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-36402-0_69</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164954546&doi=10.1007%2F978-3-031-36402-0_69&partnerID=40&md5=b298399f8f7e51b3f4a2b4cfd11b4d6f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164954546&doi=10.1007%2f978-3-031-36402-0_69&partnerID=40&md5=b298399f8f7e51b3f4a2b4cfd11b4d6f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 3029743; ISBN: 978-303136401-3 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 Baskaran T., CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; John N., CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Dhandra B.V., CHRIST (Deemed to be University), Hosur Road, 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 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 Evolution, Trends, and Future Developments of Business Intelligence Subject The topic of the resource Artificial intelligence; Business intelligence; Machine learning; Strategic revolution Description An account of the resource A decision-making process backed by the integration and evaluation of an organization's data resources is referred to as business intelligence. Since information has been recognized as a business's most valuable asset, it is a crucial resource for its growth and plays an increasingly important role in a variety of organization kinds. This research article examines the history of business intelligence technologies, their relevance in current times, and all the future developments that seem possible. Organizations are transforming into various approaches based on the information and networking in the twenty-first century in response to a chaotic and ambiguous environment marked by hazy organizational boundaries and rapid change. Knowledge-based assets become apparent to be the core of long-term strategic edge and the cornerstone of success in the twenty-first century in such situations. The primary characteristics of business intelligence are determined by data analysis, processing, and visualization. Relational tables are used by business intelligence technologies to store and display a lot of organized and unstructured data. They utilize specialized tools and mathematics to produce intricate visual reports. This research has been aggravated to focus on the upcoming strategic revolution in the market with numerous cutting-edge business intelligence technologies. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Vinay V.; Mathew A.; Siby A. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-645 LNNS, pp. 9-18. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-0769-4_2" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-0769-4_2</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164926030&doi=10.1007%2F978-981-99-0769-4_2&partnerID=40&md5=486f8a7f2b0b033dcb9c1788a506a163" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164926030&doi=10.1007%2f978-981-99-0769-4_2&partnerID=40&md5=486f8a7f2b0b033dcb9c1788a506a163</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981990768-7 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 Vinay V., CHRIST (Deemed to be University), Bangalore, India; Mathew A., CHRIST (Deemed to be University), Bangalore, India; Siby A., 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 Blockchain Scalability: Solutions, Challenges and Future Possibilities Subject The topic of the resource Blockchain; First layer solutions; Scalability; Second layer solutions; Sharding Description An account of the resource In recent years, blockchain has received a lot of interest and has also been widely adopted. Yet, blockchain scalability is proving to be a difficult problem. To create a new node in platforms like Bitcoin takes few days of time. This scalability problem has few proposed solutions. The present alternatives to blockchain scalability are divided into two groups in this paper: first layer and second layer techniques. Second layer solutions suggest procedures that are deployed outside of the blockchain, while first layer methods propose adjustments to the blockchain (i.e., altering the blockchain design, such as block size). We concentrate on sharding as a viable first-layer solution to the scalability problem. The thought behind sharding is to split the blockchain network into numerous groups, each processing a different set of transactions. Furthermore, we compare few of the already available sharding-based blockchain solutions and present a performance-based comparative analysis in form of the benefits and drawbacks of the existing solutions. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Roy M.; Singh M.; Radhakrishnan B. Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering, Vol-1026 LNEE, pp. 133-149. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-1410-4_12" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-1410-4_12</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164905257&doi=10.1007%2F978-981-99-1410-4_12&partnerID=40&md5=078872339c94989bdd2f324536b40df2" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164905257&doi=10.1007%2f978-981-99-1410-4_12&partnerID=40&md5=078872339c94989bdd2f324536b40df2</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18761100; ISBN: 978-981991409-8 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 Roy M., Computer Science Department, Christ (Deemed to Be) University, Bengaluru, India, Department of Computer Applications, CMR Institute of Technology, Bengaluru, India; Singh M., Computer Science Department, Christ (Deemed to Be) University, Bengaluru, India; Radhakrishnan B., JPMorgan Chase & Co., New York, 10017, NY, 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 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 Optimal Sizing and Placement of Distributed Generation in Eastern Grid of Bhutan Using Genetic Algorithm Subject The topic of the resource Active Power Loss; Distributed Generation; Genetic Algorithm; Optimization; Voltage Profile Description An account of the resource Power system has to be stable and reliable for its users. Nevertheless, due to the aging and ignorance, it tends to be unreliable and unstable. Distributed Generation (DG) is a small-scale energy production which are usually connected towards the load. It helps in the reduction of power losses and improvement of profile of voltage in a distribution network. However, if a DG is not optimally placed and sized, it will rather lead to an increase in a power loss and also deteriorates the voltage profile. This report exhibits the importance of DG placement and sizing in a distribution network using Genetic Algorithm (GA). Apart from the optimum DG placement and sizing, different scenarios with numbers of DGs is also being analyzed in this report. On eastern grid of Bhutan, a detailed analysis for its performance is carried out through MATLAB platform to demonstrate and study the effectiveness and reliability of a methodology that is being proposed. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Rai R.; Dahal R.; Wangchuk K.; Dorji S.; Praghash K.; Chidambaram S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-647 LNNS, pp. 831-840. 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/10.1007/978-3-031-27409-1_76" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-27409-1_76</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163400563&doi=10.1007%2F978-3-031-27409-1_76&partnerID=40&md5=f864a235411bc72d489556b2d0dc38df" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163400563&doi=10.1007%2f978-3-031-27409-1_76&partnerID=40&md5=f864a235411bc72d489556b2d0dc38df</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303127408-4 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 Rai R., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Dahal R., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Wangchuk K., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Dorji S., Department of Electrical Engineering, Jigme Namgyel Engineering College, Dewathang, Bhutan; Praghash K., Department of Electronics and Communication Engineering, Christ University, Bengaluru, India; Chidambaram S., Department of Electronics and Communication Engineering, Christ 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 Front-End Security Analysis forCloud-Based Data Backup Application Using Cybersecurity Tools Subject The topic of the resource Cloud computing; Cyber security; Data backup application; Front-end security analysis Description An account of the resource In this challenging, demanding, daunting, and competitive business world, the rise, and growth of cybercrimes are very high. With the proliferation of Cloud Computing techniques, usually in industrial arenas, business information and important clients data are stored and managed using cloud platforms. Application programs are developed to handle such valuable information assets of the organizations. Cloud backups are provided for these client data where security is the most concerning aspect. There are many vulnerabilities in the current scenario where intruders can cause havoc. Destruction of the product can happen by exploiting vulnerabilities that can put the company and the product in jeopardy. It may create a bad impression about the organization among the customers, competitors, and the public world. This paper shows the work done by a cyber security team whose main objective is to run vulnerability analysis and mitigate threats on an application that backs up the clients data to the cloud. Cyber Security is an important aspect in all types of businesses because it protects all categories of data such as fragile data, private information, intellectual property data, and other data including governmental and industrial information systems from theft and damage which concludes in huge financial loss and loss of client data. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Affan Ahamed S.M.K.N.U.; Mathew Wilson V.; Elappila M.; Malayath Jose S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-660 LNNS, pp. 187-196. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-1203-2_16" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-1203-2_16</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164966132&doi=10.1007%2F978-981-99-1203-2_16&partnerID=40&md5=0c4440fd87177c619bbea935a58ab532" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164966132&doi=10.1007%2f978-981-99-1203-2_16&partnerID=40&md5=0c4440fd87177c619bbea935a58ab532</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981991202-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Affan Ahamed S.M.K.N.U., CHRIST (Deemed to be University), Bengaluru, India; Mathew Wilson V., CHRIST (Deemed to be University), Bengaluru, India; Elappila M., CHRIST (Deemed to be University), Bengaluru, India; Malayath Jose S., University of Liverpool, Liverpool, L69 3BX, United Kingdom 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 Hyperspectral Image Classification Using Denoised Stacked Auto Encoder-Based Restricted Boltzmann Machine Classifier Subject The topic of the resource Hyperspectral images; Noise; PyTorch; Restricted Boltzmann Machine; Stacked Auto Encoder Description An account of the resource This paper proposes a novel solution using an improved Stacked Auto Encoder (SAE) to deal with the problem of parametric instability associated with the classification of hyperspectral images from an extensive training set. The improved SAE reduces classification errors and discrepancies present within the individual classes. The data augmentation process resolves such constraints, where several images are produced during training by adding noises with various noise levels over an input HSI image. Further, this helps in increasing the difference between multiple classes of a training set. The improved SAE classifies HSI images using the principle of Denoising via Restricted Boltzmann Machine (RBM). This model ambiguously operates on selected bands through various band selection models. Such pre-processing, i.e., band selection, enables the classifier to eliminate noise from these bands to produce higher accuracy results. The simulation is conducted in PyTorch to validate the proposed deep DSAE-RBM under different noisy environments with various noise levels. The simulation results show that the proposed deep DSAE-RBM achieves a maximal classification rate of 92.62% without noise and 77.47% in the presence of noise. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Yuvaraj N.; Praghash K.; Arshath Raja R.; Chidambaram S.; Shreecharan D. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-647 LNNS, pp. 213-221. 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/10.1007/978-3-031-27409-1_19" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-27409-1_19</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163373120&doi=10.1007%2F978-3-031-27409-1_19&partnerID=40&md5=d42d9a7616a39e7fb0ec6c5ccf499c4e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163373120&doi=10.1007%2f978-3-031-27409-1_19&partnerID=40&md5=d42d9a7616a39e7fb0ec6c5ccf499c4e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303127408-4 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 Yuvaraj N., Research and Publications, ICT Academy, IIT Madras Research Park, Chennai, India; Praghash K., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India; Arshath Raja R., Research and Publications, ICT Academy, IIT Madras Research Park, Chennai, India; Chidambaram S., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India; Shreecharan D., Department of Electronics and Communication Engineering, CHRIST 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 Enhancing IoT Security Through Deep Learning-Based Intrusion Detection Subject The topic of the resource Adaptive Moment Estimation; Edge Computing; Gated Recurrent Units; Intrusion Detection; IoT-23 Description An account of the resource The Internet of Things (IoT) has revolutionized the way we interact with technology by connecting everyday devices to the internet. However, this increased connectivity also poses new security challenges, as IoT devices are often vulnerable to intrusion and malicious attacks. In this paper, we propose a deep learning-based intrusion detection system for enhancing IoT security. The proposed work has been experimented on IoT-23 dataset taken from Zenodo. The proposed work has been tested with 10 machine learning classifiers and two deep learning models without feature selection and with feature selection. From the results it can be inferred that the proposed work performs well with feature selection and in deep learning model named as Gated Recurrent Units (GRU) and the GRU is tested with various optimizers namely Follow-the-Regularized-Leader (Ftrl), Adaptive Delta (Adadelta), Adaptive Gradient Algorithm (Adagrad), Root Mean Squared Propagation (RmsProp), Stochastic Gradient Descent (SGD), Nesterov-Accelerated Adaptive Moment Estimation (Nadam), Adaptive Moment Estimation (Adam). Each evaluation is done with the consideration of highest performance metric with low running time. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Creator An entity primarily responsible for making the resource Jyotsna A.; Mary Anita E.A. Source A related resource from which the described resource is derived Communications in Computer and Information Science, Vol-1823 CCIS, pp. 95-105. 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/10.1007/978-3-031-35299-7_8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-35299-7_8</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164746190&doi=10.1007%2F978-3-031-35299-7_8&partnerID=40&md5=4705a6cd1f3506cfa37fb0f16af5bb5f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164746190&doi=10.1007%2f978-3-031-35299-7_8&partnerID=40&md5=4705a6cd1f3506cfa37fb0f16af5bb5f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18650929; ISBN: 978-303135298-0 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 Jyotsna A., Department of Computer Science and Engineering, Christ (Deemed to Be University), Bangalore, India; Mary Anita E.A., Department of Computer Science and Engineering, Christ (Deemed to Be University), Bangalore, India