41 20 2150 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 Survey on Adaptive Authentication Using Machine Learning Techniques Subject The topic of the resource Behavior-based fingerprinting; Browser fingerprinting; Context-based fingerprinting; Risk-based authentication; Security and privacy Description An account of the resource Adaptive authentication is a reliable technique to dynamically select the best mechanisms among multiple modalities to authenticate a user based on the users risk profile generated using behavior and context-based information. Websites or enterprise applications enabled with adaptive authentication will have a more robust security system as analyzing the large volume of the user, device, and browser data in real time generates a risk score that decides the appropriate level of security. Though a significant amount of research is being carried out on adaptive authentication, no single model is suitable for a global attack. This paper provides a structured (extensive) survey of current adaptive authentication techniques available in the literature to identify the challenges which demand future research. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Pramila R.M.; Misbahuddin M.; Shukla S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 317-335. 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/10.1007/978-981-19-2211-4_28" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_28</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135096913&doi=10.1007%2F978-981-19-2211-4_28&partnerID=40&md5=183355bc1c1500ac57bbed27c64c7cdf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135096913&doi=10.1007%2f978-981-19-2211-4_28&partnerID=40&md5=183355bc1c1500ac57bbed27c64c7cdf</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Pramila R.M., Christ University, Bangalore, India; Misbahuddin M., Centre for Development and Advanced Computing (CDAC), Electronics City, Bangalore, India; Shukla S., Christ University, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Customer Behavior Analysis Using Unsupervised Clustering and Profiling: A Machine Learning Approach Subject The topic of the resource Affiliation rule mining model; Agglomerative Clustering; Customer Behavior Prediction Model Analysis; Customer Segmentation; Hierarchical Clustering Description An account of the resource Now-a-days, client conduct models are reliably established on information mining of client information, and each model is supposed to answer one solicitation at one point on schedule. Anticipating client conduct is a problematic and irksome task. Thus, making client conduct models requires the right strategy and approach. Right when an estimate model has been fabricated, it is challenging to restrict it for the motivations driving the advertiser, to pick the very thing displaying moves to make for every client or for the party of clients. Notwithstanding the multifaceted nature of this arrangement, most client models are completely fundamental. As the need might arise, most client conduct investigation models ignore such endless proper factors that the gauges they make are overall not altogether strong. This paper plans to encourage a connection rule mining model to expect client conduct using a typical electronic retail store for data combination and concentrate critical examples from the client conduct data. In this undertaking, a solo grouping of information on the customer's records from a regular food item company's data set will be played out. Customer segmentation is the act of clustering customers into bunches that reflect likenesses among customers in each group. Customers are separated into sections to advance the meaning of every customer to the business. To change items as indicated by unmistakable requirements and practices of the customers. It additionally assists the business with obliging the worries of various kinds of customers. Customers were clustered using a technique known as agglomerative clustering, which is a type of hierarchical clustering. Agglomerative clustering is a method for clustering data in a hierarchical order. It entails merging cases until you reach the appropriate number of clusters. The number of clusters to be produced is determined using the Elbow Method. 2022 IEEE. Creator An entity primarily responsible for making the resource Gopal A.C.; Jacob L. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 2075-2078. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823646" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823646</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135447402&doi=10.1109%2FICACITE53722.2022.9823646&partnerID=40&md5=1bfb6e2376bac2a811baa70682750e0a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135447402&doi=10.1109%2fICACITE53722.2022.9823646&partnerID=40&md5=1bfb6e2376bac2a811baa70682750e0a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gopal A.C., Christ University, Department of Data Science, India; Jacob L., Christ University, Department of Data Science, 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 Machine Learning Methods leveraging ADFA-LD Dataset for Anomaly Detection in Linux Host Systems Subject The topic of the resource ADFA-LD; Anomaly Detection; Host Intrusion Detection System; Linux; Machine Learning Description An account of the resource Advancement in network technology and revolution in the global internet transformed the overall Information Technology (IT) infrastructure and its usage. In the era of the Internet of Things (IoT) and the Internet of Everything (IoE), most everyday gadgets and electronic devices are IT-enabled and can be connected over the internet. With the advancements in IT technologies, operating systems also evolved to leverage these advancements. Today's operating systems are more user-friendly and feature-rich to support current IT requirements and provide sophisticated functionalities. On the one hand, these features enabled operating systems accomplish all current requirements, but on the other hand, these modern operating systems increased their attack surface considerably. Intrusion detection systems play a significant role in providing security against the broad spectrum of attacks on host systems. Intrusion detection systems based on anomaly detection have become a prominent research area among diverse areas of cyber security. The traditional approaches for anomaly detection are inadequate to discover the operating system level anomalies. The advancement and research in Machine Learning (ML) based anomaly detection open new opportunities to tackle this challenge. The dataset plays a significant role in ML-based system efficacy. The Australian Defence Force Academy Linux Dataset (ADFA-LD) comprises thousands of normal and attack processes system call traces for the Linux platform. It is the benchmark dataset used for dynamic approach-based anomaly detection. This paper provided a comprehensive and structured study of various research works based on the ADFA-LD for host-based anomaly detection and presented a comparative analysis. 2022 IEEE. Creator An entity primarily responsible for making the resource Khandelwal P.; Likhar P.; Yadav R.S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Intelligent Technologies, CONIT 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CONIT55038.2022.9848305" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CONIT55038.2022.9848305</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137264153&doi=10.1109%2FCONIT55038.2022.9848305&partnerID=40&md5=a4795dce4b9f313b3542507b66cc4a82" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137264153&doi=10.1109%2fCONIT55038.2022.9848305&partnerID=40&md5=a4795dce4b9f313b3542507b66cc4a82</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548407-7 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 Khandelwal P., Christ(Deemed to Be University), Department of Computer Science, Bengaluru, India; Likhar P., Centre for Artificial Intelligence and Robotics (CAIR), Defence Research and Development Organisation (DRDO), Bengaluru, India; Yadav R.S., Centre for Artificial Intelligence and Robotics (CAIR), Defence Research and Development Organisation (DRDO), 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 Pulse Shaper Design for UWB-Based Medical Imaging Applications Subject The topic of the resource Clutter; Gaussian pulse; Ringing effect; UWB pulse shaping filter Description An account of the resource In this paper, a pulse shaping filter is designed to shape the higher-order derivatives of the basic UWB Gaussian pulse for efficient pulse transmission through human tissues for medical imaging applications. The shaped pulse for the desired center frequency fits the FCC mask and power spectral density (PSD) specifications with higher spectral efficiency being achieved. It is observed that the ringing effect of Gaussian pulse is reduced by using the proposed bandpass FIR shaping filter. The low ringing effect observed in the shaped pulse ensures better antenna power distribution and improved location accuracy which is critical factor for medical imaging applications. The pulses synthesized are highly orthogonal which aids in multi-access communication, improved bit error rate (BER) performance and short duration UWB pulses leading to higher data rate transmission. The drooping frequency response characteristics of the synthesized pulse have reduced clutter hence tightly focused image obtained for imaging applications. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Devika Menon M.K.; Rodrigues J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-461, pp. 897-907. 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/10.1007/978-981-19-2130-8_70" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2130-8_70</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136968352&doi=10.1007%2F978-981-19-2130-8_70&partnerID=40&md5=b937847220d2d60661083e87546862a8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136968352&doi=10.1007%2f978-981-19-2130-8_70&partnerID=40&md5=b937847220d2d60661083e87546862a8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192129-2 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 Devika Menon M.K., CHRIST (Deemed to Be University), Bengaluru, India; Rodrigues J., 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 Hybrid AI Talent Acquisition Model: An Opinion Mining and Topic based approach Subject The topic of the resource Analytics; Artificial Intelligence; NLP; Sentiment Analysis; Topic modelling Description An account of the resource Artificial Intelligence models have found their usage in the human resource domain. In this paper, job reviewers' opinions on online discussion boards have been captured. The relative importance of factors has been established through an extensive literature review. First, LDA Topic modelling by adopting PCA is performed on unstructured text data has been analyzed. Second, sentiment analysis using the Li-Hu method has been employed to understand job seekers' satisfaction with job portals. The proposed model, 'Hybrid AI Talent Acquisition Model,' follows a novel approach to streamlining the jobseeker opinion related to online outlets. 2022 IEEE. Creator An entity primarily responsible for making the resource Jas D.; Antony A.C.; Saxena A.; Sharma M.; Gupta S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Intelligent Technologies, CONIT 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CONIT55038.2022.9847968" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CONIT55038.2022.9847968</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137260005&doi=10.1109%2FCONIT55038.2022.9847968&partnerID=40&md5=673ee33b94c99713d8a3f968987b4750" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137260005&doi=10.1109%2fCONIT55038.2022.9847968&partnerID=40&md5=673ee33b94c99713d8a3f968987b4750</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548407-7 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 Jas D., Christ University, India; Antony A.C., Christ University, India; Saxena A., Christ University, India; Sharma M., Christ University, India; Gupta S., Christ University, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Comparative Investigation on the use of Machine Learning Techniques for Currency Authentication Subject The topic of the resource Currency Authentication; Data mining; K-means clustering; Random Forest; Support Vector Machine; unsupervised learning. Supervised Learning Description An account of the resource In the present banking sector, identifying the real and the fake note is a very challenging task because if we do it manually, it takes a long time to check which is real and which is fake. This research study article aims to authenticate the money between real and fake by using different machine algorithms facilitating learning, such as K-means Clustering, Random Forest Classification, Support Vector Machines, and logistics Regression. Specifically, we consider the banknote dataset. The data of money is extracted from various banknote images by using the wavelet transform tool, which is primarily used to remove elements from the images. However, we are mainly concerned with the different machine learning algorithms, so we take the two variables, where the first variable indicates image variance and the second indicates image skewness. We use these two variables to train our machine learning algorithms. So, majorly, by applying the different machine learning algorithms, which are supervised and unsupervised, we find the accuracy for the respective machine learning algorithms and then visualize and classify the real and fake notes separately. Finally, the prediction is based on integrity, which means the efficiency value is based on how much the mechanism system can uncover the fake notes. Then, after calculating the accuracy of currency authentication, there is a high possibility that the accuracy of the particular algorithm is the best algorithm, so the application of currency authentication will be very useful for the bank to easily find duplicate notes. 2022 IEEE. Creator An entity primarily responsible for making the resource Sharma A.; Prathap B.R.; Hussain J. Source A related resource from which the described resource is derived 2022 1st International Conference on Artificial Intelligence Trends and Pattern Recognition, ICAITPR 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICAITPR51569.2022.9844207" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAITPR51569.2022.9844207</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136824363&doi=10.1109%2FICAITPR51569.2022.9844207&partnerID=40&md5=ffe960edb89ad4b8cf47f920e915bdc8" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136824363&doi=10.1109%2fICAITPR51569.2022.9844207&partnerID=40&md5=ffe960edb89ad4b8cf47f920e915bdc8</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166542521-6 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 Sharma A., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India; Prathap B.R., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India; Hussain J., CHRIST(Deemed to Be University), Computer Science and Engineering, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Improved and Efficient YOLOv4 Method for Object Detection in Video Streaming Subject The topic of the resource Object detection; Optimized inferencing; YOLOV4 Description An account of the resource As object detection has gained popularity in recent years, there are many object detection algorithms available in today's world. Yet the algorithm with better accuracy and better speed is considered vital for critical applications. Therefore, in this article, the use of the YOLOV4 object detection algorithm is combined with improved and efficient inference methods. The YOLOV4 state-of-the-art algorithm is 12% faster compared to its previous version, YOLOV3, and twice as faster compared to the EfficientDet algorithm in the Tesla V100 GPU. However, the algorithm has lacked performance on an average machine and on single-board machines like Jetson Nano and Jetson TX2. In this research, we examine the performance of inferencing in several frameworks and propose a framework that effectively uses hardware to optimize the network while consuming less than 30% of the hardware of other frameworks. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Hussain J.; Prathap B.R.; Sharma A. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 305-316. 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/10.1007/978-981-19-2211-4_27" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_27</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135038461&doi=10.1007%2F978-981-19-2211-4_27&partnerID=40&md5=3fc154107c8338e1c50d9121ac01be6a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135038461&doi=10.1007%2f978-981-19-2211-4_27&partnerID=40&md5=3fc154107c8338e1c50d9121ac01be6a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Hussain J., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India; Prathap B.R., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India; Sharma A., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Analysis of Fine Needle Aspiration Images by Using Hybrid Feature Selection and Various Machine Learning Classifiers Subject The topic of the resource Breast cancer; Classification; Feature selection; Fine needle aspiration cytology; Machine learning Description An account of the resource Women die of breast cancer most often worldwide. Breast tissue samples can be examined by radiologists, surgeons, and pathologists for evidence of this cancer. Fine needle aspiration cytology (FNAC) can be used to detect this cancer through a visual microscopic examination of breast tissue samples. This sample must be examined by a cytopathologist in order to determine the patient's risk of breast cancer. To determine if a tumor is malignant, the nuclei of the cells must be characterized by their chromatin texture patterns. A machine learning method is used in order to categorize FNA images into two classes, respectively Malignant and Benign. For detecting abnormalities, numerous feature collection methods and machine learning means are applied here. Using features extracted from the FNA image set, UCI machine learning datasets are used to validate the proposed approach. This paper compares three classification methodologies, namely random forests, Naive Bayes, and artificial neural networks, by examining their accuracy, specificity, precision, and sensitivity, respectively. With the ANN and PCA along with the Chi-square selection method, 99.1% of the classifiers are correctly classified. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Preethi N.; Jaisingh W. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 383-392. 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/10.1007/978-981-19-2211-4_34" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_34</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135092850&doi=10.1007%2F978-981-19-2211-4_34&partnerID=40&md5=fa8c488e792491538da922378af375be" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135092850&doi=10.1007%2f978-981-19-2211-4_34&partnerID=40&md5=fa8c488e792491538da922378af375be</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Preethi N., Christ University, Pune, Lavasa, India; Jaisingh W., School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, Bhopal, 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 Social Media Sentiment Analysis of Stock Market on Tweets Subject The topic of the resource analyze; estimate; machine learning; recommendation system; sentiment analysis Description An account of the resource Sentiment categorization is utilized in today's world to analyze social media data about the stock market and estimate its future stock movement. We investigated the possible influence of 'public sentiment' on 'market trends' using sentiment analysis and machine learning concepts. Due to the enormous number of components involved, such as economic situations, political events, and other environmental factors that may affect the stock price, stock price prediction is an exceedingly complicated and challenging process. Because of these considerations, evaluating a single factor's influence on future pricing and trends is challenging. As more individuals spend time online, the popularity and impact of numerous social media platforms has skyrocketed in recent years. Twitter is one such social media tool that has exploded in popularity. Twitter is a terrific place to stay up to speed on current societal trends and perspectives. The 'Twittersphere' is a melting pot that supports diverse viewpoints, emotions, and trends, and it has the potential to be a crucial influencer in influencing and shaping perceptions. 2022 IEEE. Creator An entity primarily responsible for making the resource Yadav K.; Vijayalakshmi S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 1977-1980. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823529" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823529</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135442240&doi=10.1109%2FICACITE53722.2022.9823529&partnerID=40&md5=a3b07ae1f9de5c319a6bde91d9ef3420" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135442240&doi=10.1109%2fICACITE53722.2022.9823529&partnerID=40&md5=a3b07ae1f9de5c319a6bde91d9ef3420</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Yadav K., Christ University, Dept. of Data Science, Maharashtra, Pune, India; Vijayalakshmi S., Christ University, Dept. of Data 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 Analysis of Challenges Experienced by Students with Online Classes During the COVID-19 Pandemic Subject The topic of the resource COVID-19; Digital divide; Education sector; Online education; Quality education; Student experience; Teaching; Work from home Description An account of the resource In the current context of the COVID-19 pandemic, due to restrictions in mobility and the closure of schools, people had to shift to work from home. India has the worlds second-largest pool of internet users, yet half its population lacks internet access or knowledge to use digital services. The shift to online mediums for education has exposed the stark digital divide in the education system. The digitization of education proved to be a significant challenge for students who lacked the devices, internet facility, and infrastructure to support the online mode of education or lacked the training to use these devices. These challenges raise concerns about the effectiveness of the future of education, as teachers and students find it challenging to communicate, connect, and assess meaningful learning. This study was conducted at one of the universities in India using a purposive sampling method to understand the challenges faced by the students during the online study and their satisfaction level. This paper aims to draw insight from the survey into the concerns raised by students from different backgrounds while learning from their homes and the decline in the effectiveness of education. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Elsheba D.; Sarkar N.; Jabez S.S.; Chully A.A.; Shukla S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 189-197. 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/10.1007/978-981-19-2211-4_16" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_16</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135053554&doi=10.1007%2F978-981-19-2211-4_16&partnerID=40&md5=d14ca72982260f6e44673aa0405d4ab6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135053554&doi=10.1007%2f978-981-19-2211-4_16&partnerID=40&md5=d14ca72982260f6e44673aa0405d4ab6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Elsheba D., Christ University, Bangalore, India; Sarkar N., Christ University, Bangalore, India; Jabez S.S., Christ University, Bangalore, India; Chully A.A., Christ University, Bangalore, India; Shukla S., Christ University, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Some Variations of Domination in Order Sum Graphs Subject The topic of the resource Complement of a graph; Domination; Line graphs; Order sum graphs Description An account of the resource An order sum graph of a group G, denoted by ? os(G), is a graph with vertex set consisting of elements of G and two vertices say a, b? ? os(G) are adjacent if o(a) + o(b) > o(G). In this paper, we extend the study of order sum graphs of groups to domination. We determine different types of domination such as connected, global, strong, secure, restrained domination and so on for order sum graphs, their complement and line graphs of order sum graphs. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Amreen J.; Naduvath S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 117-125. 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/10.1007/978-981-19-2211-4_10" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_10</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135056427&doi=10.1007%2F978-981-19-2211-4_10&partnerID=40&md5=75b8367c1e88b20c2b7fb0d07c572717" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135056427&doi=10.1007%2f978-981-19-2211-4_10&partnerID=40&md5=75b8367c1e88b20c2b7fb0d07c572717</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Amreen J., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, India; Naduvath S., Department of Mathematics, 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 Framework for Digital Forensics Using Blockchain to Secure Digital Data Subject The topic of the resource Blockchain; Digital Evidence; Digital forensics Description An account of the resource Digital forensics (DF) requires evidence integrity and provenance across boundaries of jurisdiction, and blockchain technology is ideal for ensuring that. As part of this paper, we discussed a digital forensic framework designed to help prevent duplication of data and secure digital data. In order to accomplish such forensic capabilities, we provide a block-based forensics framework. Using it, examinations are validated, irreversible, traceable, robust, and demonstrate high levels of confidence among examiners and evidence entities. 2022 IEEE. Creator An entity primarily responsible for making the resource Jacob J.; Kumar S. Source A related resource from which the described resource is derived Proceedings - 2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022, pp. 899-904. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIC55036.2022.9848860" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIC55036.2022.9848860</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137775231&doi=10.1109%2FAIC55036.2022.9848860&partnerID=40&md5=7ebb777cc6fdf286e29ff9c413d134cb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137775231&doi=10.1109%2fAIC55036.2022.9848860&partnerID=40&md5=7ebb777cc6fdf286e29ff9c413d134cb</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-150905001-7 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 Jacob J., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India; Kumar S., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Image Recognition, Recusion Cellular Classification Using Different Techniques and Detecticting Microscopic Deformities Subject The topic of the resource Deep Convolutional neural networks; microscopic images; Transfer learning Description An account of the resource Deep convolutional neural networks (CNNs) have turn out to be one of the most advanced approaches trendy distinguishing snapshots in extraordinary fields. White blood cell classification is crucial for diagnosing anaemia, leukaemia, and a variety of other hematologic illnesses. Transfer learning with CNNs is frequently used in biological image categorization. Traditional methods for WBC classification is costly is terms of time and money. In the paper three convolutional neural network architectures are proposed which is based on transfer learning for microscopic image classification and compare the performance of models. The paper compares Transfer learning models like VGG-16, VGG-19, VGG-19 SVM hybrid and AlexNet. VGG-16 gives the best classification performance in comparison. VGG-16 model is which has a train accuracy of 0.9538 and train loss of 0.1322. 2022 IEEE. Creator An entity primarily responsible for making the resource Thomas S.; Vijaylakshmi S. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 1053-1055. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823758" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823758</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135491583&doi=10.1109%2FICACITE53722.2022.9823758&partnerID=40&md5=613cf674676c30ca147d9f5f4f85793f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135491583&doi=10.1109%2fICACITE53722.2022.9823758&partnerID=40&md5=613cf674676c30ca147d9f5f4f85793f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Thomas S., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Lavasa, 412112, India; Vijaylakshmi S., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Lavasa, 412112, 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 Clustering-based Optimal Resource Allocation Strategy in Title Insurance Underwriting Subject The topic of the resource Clustering; Gower distance; Linear optimization; Operations Research; Optimal Resource Allocation; PAM. Description An account of the resource Production of insurance policies in all types of Insurance requires a thorough examination of the entity against which the Insurance is to be issued. In health insurance, it is the past medical data of the individuals. Vehicle insurance needs the examination of the vehicle and the owner's data. Likewise, in Title Insurance, it is the historical data of the property which needs scrutiny before the policy issuance. Underwriters perform the job of examining the property records. The scrutiny of the property records requires a high degree of the domain and legal expertise, and title insurance underwriters are often associated with legal professions. They do the final round of validation of the examination process. There are examination teams that take care of the initial set of regular examination tasks associated with each title insurance order. Some human experts assign the orders to the team associates. Not all the orders are of the same complexity in terms of examination. The allocation of the tasks happens based on the gut feeling of the supervisor, considering their experience with the team members. Our research creates clusters of the orders based on specific parameters associated with the orders. It builds a cost model of the past associates working on orders belonging to different clusters. Based on this cost matrix, we have built an optimal task allocation model that assigns the orders to the associates with the promise of optimal cost using a Linear programming solution used frequently in operations research. 2022 IEEE. Creator An entity primarily responsible for making the resource Guha A.; Obaidat M.S.; Samanta D.; Islam S.K.H. Source A related resource from which the described resource is derived Proceedings of the 2022 International Conference on Computer, Information and Telecommunication Systems, CITS 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CITS55221.2022.9832993" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CITS55221.2022.9832993</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136093753&doi=10.1109%2FCITS55221.2022.9832993&partnerID=40&md5=278a6df6990a82f0a4061be297c56b28" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136093753&doi=10.1109%2fCITS55221.2022.9832993&partnerID=40&md5=278a6df6990a82f0a4061be297c56b28</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548615-6 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 Guha A., CHRIST University, Eagle Labs First American India Private Limited, Department of Computer Science, Karnataka, Bangalore, India; Obaidat M.S., Department of Computer Science, Cybersecurity Center, University of Texas-Permian Basin, United States, University of Jordan, KASIT, Amman, 11942, Jordan, University of Science and Technology, School of Computer and Communication Engineering, Beijing, China, Amity University, Noida, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, Karnataka, India; Islam S.K.H., Indian Institute of Information Technology Kalyani, Department of Computer Science and Engineering, West Bengal, 741235, 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 Comparison of Machine Learning Algorithms for Predicting Chronic Kidney Disease Subject The topic of the resource Chronic Kidney Disease; CKD classification; Machine learning algorithms; Random Forest; XGBoost Description An account of the resource Early detection and characterization of chronic renal disease are crucial to ensure that patients receive the best possible treatment. This study uses data mining techniques to uncover hidden information about patients. The outcomes of using the Random Forest, Multilayer Perceptron (MLP), Support Vector Machine (SVM), Decision Tree, XGBoost, LGBM Classifier, GaussianNB, KNeighbors Classifier, and XGBRF classifier have been compared. In our study, we demonstrate that Random Forest and XGBoost algorithms are more effective in classifying and predicting the severity level of chronic kidney disease 2022 IEEE. Creator An entity primarily responsible for making the resource James N.; Kaushik J. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 1134-1139. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823572" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823572</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135454910&doi=10.1109%2FICACITE53722.2022.9823572&partnerID=40&md5=65ef5e0557bf4c52f52418742048c87b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135454910&doi=10.1109%2fICACITE53722.2022.9823572&partnerID=40&md5=65ef5e0557bf4c52f52418742048c87b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant James N., Christ (Seems to Be University), Department of Data Science, Pune, India; Kaushik J., Christ (Seems to Be University), Department of Data Science, 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 Protection Against SIM Swap Attacks on OTP System Subject The topic of the resource Authentication; Biometrics; Keystroke dynamics; Machine learning models; OTP; Password; Password-less authentication; Security; Supervised learning; Unsupervised learning Description An account of the resource One-time password-based authentication stands out to be the most effective in the cluster of password-less authentication systems. It is possible to use it as an authentication factor for login rather than an account recovery mechanism. Recent studies show that attacks like SIM swap and device theft raise a significant threat for the system. In this paper, a new security system is proposed to prevent attacks like SIM swap on OTP systems, the system contains a risk engine made up of supervised and unsupervised machine learning model blocks trained using genuine user data space, and the final decision of the system is subject to a decision block that works on the principles of voting and logic of an AND gate. The proposed system performed well in detecting fraud users, proving the systems significance in solving the problems faced by an OTP system. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Varghese E.; Pramila R.M. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 219-228. 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/10.1007/978-981-19-2211-4_19" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_19</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135076642&doi=10.1007%2F978-981-19-2211-4_19&partnerID=40&md5=c7d9ec875e6862d94c4065a3f5f64e6a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135076642&doi=10.1007%2f978-981-19-2211-4_19&partnerID=40&md5=c7d9ec875e6862d94c4065a3f5f64e6a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Varghese E., Christ University, Bangalore, India; Pramila R.M., Christ University, Bangalore, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analysis and Forecasting of Crude Oil Price Based on Univariate and Multivariate Time Series Approaches Subject The topic of the resource ARIMA; Cointegration; GARCH; Granger causality; Petroleum products; VAR; VECM Description An account of the resource This paper discusses the notion of multivariate and univariate analysis for the prediction of crude oil price in India. The study also looks at the long-term relationship between the crude oil prices and its petroleum products price such as diesel, gasoline, and natural gas in India. Both univariate and multivariate time series analyses are used to predict the relationship between crude oil price and other petroleum products. The Johansen cointegration test, EngleGranger test, vector error correction (VEC) model, and vector auto regressive (VAR) model are used in this study to assess the long- and short-run dynamics between crude oil prices and other petroleum products. Prediction of crude oil price has also been modeled with respect to the univariate time series models such as autoregressive integrated moving average (ARIMA) model, Holt exponential smoothing, and generalized autoregressive conditional heteroskedasticity (GARCH). The cointegration test indicated that diesel prices and crude oil prices have a long-run link. The Granger causality test revealed a bidirectional relationship between the price of diesel and the price of gasoline, as well as a unidirectional association between the price of diesel and the price of crude oil. Based on in-sample forecasts, accuracy metrics such as root mean square logarithmic error (RMSLE), mean absolute percentage error (MAPE), and mean absolute square error (MASE) were derived, and it was discovered that VECM and ARIMA models can efficiently predict crude oil prices. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Thomas A.; John N. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 137-151. 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/10.1007/978-981-19-2211-4_12" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_12</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135051783&doi=10.1007%2F978-981-19-2211-4_12&partnerID=40&md5=eeb2847c1bee80e98db85c548b40d750" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135051783&doi=10.1007%2f978-981-19-2211-4_12&partnerID=40&md5=eeb2847c1bee80e98db85c548b40d750</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Thomas A., CHRIST (Deemed to be University), Bengaluru, India; John N., 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 Monitoring and Controlling Data Through the Internet of Things (IOT) System: A Framework to Measure the Public Health Subject The topic of the resource Internet of Things; Pressure; Public Health; Rate; Sensor; Sharing Description An account of the resource Associating and sharing information by means of the web between actual things, or 'things,' coordinated with sensors, programming, and different advances are known as the Internet of Things (IoT). In order to improve technology through IoT, there have been a number of important studies and investigations. This study exhibits how the Internet of Things might be utilized to screen wellbeing. In this research work, with the help of IoT based human wellbeing checking framework the information circulatory strain, beat rate, internal heat level, pulse, and other crucial signs are providing to the internet. The use of IoT for the human health monitoring system in later on future, need a very accurate assessment of risk and this is required to provide a long term information to the device. 2022 IEEE. Creator An entity primarily responsible for making the resource Veeraiah V.; Prasad A.B.; Sapna S.; Verma D.; Pranavan S.; Dasuki A.I. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 226-229. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICACITE53722.2022.9823746" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823746</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135460323&doi=10.1109%2FICACITE53722.2022.9823746&partnerID=40&md5=68416007bbb95b384ebf74b24ca7b225" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135460323&doi=10.1109%2fICACITE53722.2022.9823746&partnerID=40&md5=68416007bbb95b384ebf74b24ca7b225</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Veeraiah V., Adichunchanagiri University, Computer Science, Department of R&d, Karnataka, Mandya, India; Prasad A.B., Institute of Law, Nirma University, Gujarat, Ahmedabad, India; Sapna S., School of Law, Christ (Deemed to Be University)., India; Verma D., Graphic Era Deemed to Be University, Department of Biotechnology, Uttrakhand, Dehradun, India; Pranavan S., Dhanalakshmi Srinivasan College of Engineering, Civil Engineering, Salem to Kochin National Highway, Near Nandhi Temple, Navakkarai-PO, Coimbatore, India; Dasuki A.I., Yusuf Maitama Sule University, Department of Business Administration, Kano, Nigeria 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 Measuring Consumer Perception for P2P Platform: NLP Approach Subject The topic of the resource Analysis; Google reviews; LDA; Sentiment analysis; Topic Modelling Description An account of the resource The pandemic has forced lenders and borrowers to switch to alternative borrowing., investment solutions. This research explores the Google reviews of users of four P2P lending platforms in India. To understand user sentiments and emotions about P2P lending platforms. The researchers has analysed user sentiments using Vader and Liu Hu methods and defined the polarity as positive or negative sentiment. Further., Plutchik's wheel of emotions was used to relate with the emotions expressed by the users. A purposeful random sampling method was used to select only 4 out of 21 registered P2P lending platforms based on their date of incorporation. The research also defined a framework for carrying out the sentiment analysis process for this study. The overall results showed that 75.51 % of users had positive sentiments., whereas., only 19.35% of users had negative sentiments about the P2P lending platforms. As most of the reviews posted were from the borrower's., emotion of joy was seen in all 4 platforms., followed by emotions of sadness., surprise., anger., disgust., and fear. 2022 IEEE. Creator An entity primarily responsible for making the resource Gupta S.; Mahajan J.; Saxena A. Source A related resource from which the described resource is derived 2022 2nd International Conference on Intelligent Technologies, CONIT 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CONIT55038.2022.9848083" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CONIT55038.2022.9848083</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137260891&doi=10.1109%2FCONIT55038.2022.9848083&partnerID=40&md5=92de07f8ae97491e8ca53bf0b67e1305" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137260891&doi=10.1109%2fCONIT55038.2022.9848083&partnerID=40&md5=92de07f8ae97491e8ca53bf0b67e1305</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548407-7 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 Gupta S., Christ University, India; Mahajan J., Christ University, India; Saxena A., Christ University, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Circulant Completion of Graphs Subject The topic of the resource ? -completion; Circulant completion; Circulant completion graph; Circulant completion number; Circulant labelling; Circulant span Description An account of the resource A graph G with vertex set as {v0, v1, v2,.., vn-1} corresponding to the elements of Zn, the group of integers under addition modulo n, is said to be a circulant graph if the edge set of G consists of all edges of the form {vi, vj} where (i-j)(modn)?S?{1,2,,n-1}, that is, closed under inverses. The set S is known as the connection set. In this paper, we present some techniques and characterisations which enable us to obtain a circulant completion graph of a given graph and thereby evaluate the circulant completion number. The obtained results provide the basic eligibilities for a graph to have a particular circulant completion graph. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Antony T.B.; Naduvath S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 181-188. 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/10.1007/978-981-19-2211-4_15" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_15</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135040196&doi=10.1007%2F978-981-19-2211-4_15&partnerID=40&md5=6904684f11ae22dfad619a848ecf47c9" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135040196&doi=10.1007%2f978-981-19-2211-4_15&partnerID=40&md5=6904684f11ae22dfad619a848ecf47c9</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Antony T.B., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, India; Naduvath S., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, India