40 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 Systematic Review of Challenges, Tools, and Myths of Big Data Ingestion Subject The topic of the resource Data ingestion; Flume; Ingestion challenges; Ingestion myths; Kafka; NiFi Description An account of the resource Each sector of the digital world generates enormous data as human life continues to transform. Areas like data analytics, data science, knowledge discovery in databases (KDD), machine learning, and artificial intelligence depend on highly distributed data which requires appropriate storage in a data lake. Collecting the data from different heterogeneous sources and creating a single lake of data is called data ingestion. Ironically, data ingestion has been treated as a less important stage in data analysis because it is considered a minor first step. There are several misconceptions in the data and analytics domain about data ingestion. The survey employed in this research presents a list of significant challenges faced by information technology (IT) industries during data ingestion. The available frameworks are compared in terms of standard parameters that are set against the existing challenges and myths. The findings from the comparison are compiled in a tabular format for easy reference. The paper places emphasis on the significance of data ingestion and attempts to present it as a major activity on the big data platform. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Irfan M.; George J.P. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 481-494. 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_43" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_43</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135020977&doi=10.1007%2F978-981-19-2211-4_43&partnerID=40&md5=4dd335dd06cbffb4fc534d41c7d7213e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135020977&doi=10.1007%2f978-981-19-2211-4_43&partnerID=40&md5=4dd335dd06cbffb4fc534d41c7d7213e</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 Irfan M., CHRIST (Deemed to be University), Lavasa Campus, Bengaluru, India; George J.P., CHRIST (Deemed to be University), Lavasa Campus, 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 Predicting Stock Market Price Movement Using Machine Learning Technique: Evidence from India Subject The topic of the resource Artificial Neural network; GBM; Investment component; Machine Learning; Stock Price Prediction Description An account of the resource The stock market is uncertain, volatile, and multidimensional. Stock prices have been difficult to predict since they are influenced by a variety of factors. In order to make critical investment and financial decisions, investors and analysts are interested in predicting stock prices. Predicting a stock's price entails developing price pathways that a stock might take in the future. ANN and mathematical Geometric Brownian movement technique were employed in this study to forecast a stock market closing price of Indian companies. The comparative analysis indicates that the Geometric Brownian Method is better than ANN in giving better MAPE and RMSE Values. 2022 IEEE. Creator An entity primarily responsible for making the resource Praveen Kumar T.; Mallieswari R.; Kirupa Priyadarsini M. Source A related resource from which the described resource is derived 2022 International Conference on Interdisciplinary Research in Technology and Management, IRTM 2022 - 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 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IRTM54583.2022.9791640" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IRTM54583.2022.9791640</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133465251&doi=10.1109%2FIRTM54583.2022.9791640&partnerID=40&md5=0c9edd5a6bc77fed487054a9c1135080" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133465251&doi=10.1109%2fIRTM54583.2022.9791640&partnerID=40&md5=0c9edd5a6bc77fed487054a9c1135080</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547886-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Praveen Kumar T., Business And Management Christ, (Deemed To Be University), Bengaluru, India; Mallieswari R., Ramaiah Institute Of Management, Management Department, India; Kirupa Priyadarsini M., Psg Institute Of Management, Management Department, 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 AI-Based Forensic Model for Online Social Networks Subject The topic of the resource AI; Cybercrime; Forensics; Social media Description An account of the resource With the growth of social media usage, social media crimes are also creeping sprightly. Investigation of such crimes involves the thorough examination of data like user, activity, network, and content. Although investigating social media looks quite straight forward process, it is always challenging for the investigators due to the complex process involved in it. Due to the immense growth of social media content, manual processing of data for investigation is not possible. Most of the works from this area provide an automatic model or semi-automated, and much of the contributions lacks the logical reasoning and explainability of the evidence extracted. Searching techniques like entity-based search and explainable AI add value to the quick retrieval within appropriate scope and explain the results to the court of law. This paper provides a model by adding these new techniques to the basic forensic process. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Pawar V.; Jose D.V. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 209-218. 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_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_18</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135010778&doi=10.1007%2F978-981-19-2211-4_18&partnerID=40&md5=bd4ab2ff2ef08b883ca0ffbf52b8b4fa" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135010778&doi=10.1007%2f978-981-19-2211-4_18&partnerID=40&md5=bd4ab2ff2ef08b883ca0ffbf52b8b4fa</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 Pawar V., Department of Computer Applications, CMR Institute of Technology, Bengaluru, India, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Jose D.V., Department of Computer Science, 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 Improving Indoor occupancy estimation using a hybrid CNN-LSTM approach Subject The topic of the resource air quality; CNN; Deep learning; IAQ; LSTM; occupancy estimation Description An account of the resource Indoor Air Quality (IAQ) monitoring has been a significant research domain in energy conservation. Many energy resources are required to maintain the IAQ using airconditioning or other ventilation systems. Currently, the research works highly optimize an on-demand driven energy usage depending on the occupant present inside the building. In the last decade, numerous research works have evolved for such an optimization by installing sensors and predicting occupants using machine learning techniques. This research fails to deploy non-intrusive sensors and appropriate machine learning algorithms to predict the occupancy count. Advancement in neural network techniques termed deep learning has made significant performance in recognition and cognitive tasks. Thus, this paper proposes a hybrid deep learning model that stacks the convolutional neural network (CNN) and long short term memory (LSTM) to improve the prediction rate of the occupancy count. Experimentation has been carried out in real-time multivariate sensor data for the occupancy estimation and evaluated the performance in terms of accuracy, RMSE, MAPE, and coefficients of determinants. 2022 IEEE. Creator An entity primarily responsible for making the resource Ramanujam E.; Sharma A.; Hussian J.J.; Perumal T. Source A related resource from which the described resource is derived 2022 International Conference on Intelligent Controller and Computing for Smart Power, ICICCSP 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/ICICCSP53532.2022.9862328" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICICCSP53532.2022.9862328</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137793534&doi=10.1109%2FICICCSP53532.2022.9862328&partnerID=40&md5=d9cdf155a7d0cf48064875c460483e6b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137793534&doi=10.1109%2fICICCSP53532.2022.9862328&partnerID=40&md5=d9cdf155a7d0cf48064875c460483e6b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547258-6 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 Ramanujam E., School of Engineering and Technology, Christ (Deemed to Be) University, Department of Computer Science and Engineering, Bengaluru, India; Sharma A., School of Engineering and Technology, Christ (Deemed to Be) University, Department of Computer Science and Engineering, Bengaluru, India; Hussian J.J., School of Engineering and Technology, Christ (Deemed to Be) University, Department of Computer Science and Engineering, Bengaluru, India; Perumal T., Universiti Putra, Department of Computer Science, Serdany, Selangor, Malaysia 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 Based recommendation system Using User-Item Interaction Subject The topic of the resource Clustering; Collaborative Filtering; Content-based Filtering; Machine Learning; Movie Recommendation; User ratings Description An account of the resource Electronic commerce, or e-commerce, is the activity of trading services and commodities through the internet. Identifying the item that the consumer may buy from the enormous number of possibilities accessible to solve this difficulty is now one of the key difficulties encountered by most E-commerce businesses. Recommender systems have been implemented. Recommender systems (RS) are systems that collect information from users about their preferences and allow them to make decisions from the available options. Today, various recommender systems are growing with the advent of web-based information. As you can see from various articles, such recommender systems are used in a variety of industries, from simple objects to more sophisticated objects.RS has gained popularity in the previous decade, particularly in the realm of E-Commerce and related sectors. This report aims to identify recent developments as well as their potential for improvement. It is intended to elaborate on a number of points. And also work more on user-item based recommendation. These types of user-item based recommendation will be more effective in fashion area. 2022 IEEE. Creator An entity primarily responsible for making the resource Akshay K.; Nair A.M. 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. 1745-1749. 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/ICACITE53722.2022.9823576" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823576</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135477888&doi=10.1109%2FICACITE53722.2022.9823576&partnerID=40&md5=d1f393443f01abc86211f1c8c79c7ca0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135477888&doi=10.1109%2fICACITE53722.2022.9823576&partnerID=40&md5=d1f393443f01abc86211f1c8c79c7ca0</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 Akshay K., Christ (Deemed to Be University), Lavasa Campus, Department of Data Science, Maharashtra, Pune, India; Nair A.M., Christ (Deemed to Be University), Lavasa Campus, Department 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 MRI Images to Discover Brain Tumor Detection Using CNN and VGG-16 Subject The topic of the resource Brain tumor; CNN; Detection; Image processing; MRI; VGG-16 Description An account of the resource Brain tumor is a malignant illness where irregular cells, excess cells and uncontrollable cells are grown inside the brain. Now-a-days Image processing plays a main role in discovery of breast cancer, lung cancer and brain tumor in initial stage. In Image processing even the smallest part of tumor is sensed and can be cured in early stage for giving the suitable treatment. Bio-medical Image processing is a rising arena it consists of many types of imaging approaches like CT scans, X-Ray and MRI. Medical image processing may be the challenging and complex field which is rising nowadays. CNN is known as convolutional neural network it used for image recognition and that is exactly intended for progression pixel data. The performance of model is measured using two different datasets which is merged as one. In this paper two models are used CNN and VGG-16 and finding the best model using their accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Vasudevan A.; Preethi N. Source A related resource from which the described resource is derived Smart Innovation, Systems and Technologies, Vol-302, pp. 415-422. 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/10.1007/978-981-19-2541-2_32" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2541-2_32</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135874345&doi=10.1007%2F978-981-19-2541-2_32&partnerID=40&md5=50e82db3a701a711308caf68879515d6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135874345&doi=10.1007%2f978-981-19-2541-2_32&partnerID=40&md5=50e82db3a701a711308caf68879515d6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21903018; ISBN: 978-981192540-5 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 Vasudevan A., Christ University, Bangalore, India; Preethi N., 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 Diagnosis of Osteoporosis from X-ray Images using Automated Techniques Subject The topic of the resource Bone mineral density; Osteoporosis; Residual Block; Skip connections.; U-net Description An account of the resource Osteoporosis is Bone Disease most commonly seen in aged people due to various food habits and life style habits. The bone becomes so brittle and weak which may break just from a fall. So, it is required to attend this Issue as there are various challenges faced by medical domain to identify and treat Osteoporosis. In this paper we focus on identifying and detecting osteoporosis using X-ray images using modified U-net Architecture using Residual Block and skip connections and done comparison study with existing models, as per state-of-art our model outcomes issues in existing model and obtain better accuracy. 2022 IEEE. Creator An entity primarily responsible for making the resource Dodamani P.S.; Danti A. Source A related resource from which the described resource is derived 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022, pp. 497-500. 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/COM-IT-CON54601.2022.9850579" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/COM-IT-CON54601.2022.9850579</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137523180&doi=10.1109%2FCOM-IT-CON54601.2022.9850579&partnerID=40&md5=b37f1038e7f91e30eb44e9582864a0dd" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137523180&doi=10.1109%2fCOM-IT-CON54601.2022.9850579&partnerID=40&md5=b37f1038e7f91e30eb44e9582864a0dd</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166549602-5 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 Dodamani P.S., Christ University, Computer Science and Engineering, Bangalore, India; Danti A., Christ 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 COVID-19 Pandemic: Review on Emerging Technology Involvement with Cloud Computing Subject The topic of the resource Artificial ?ntelligence; Blockchain; Cloud computing; COVID; Drones; Internet of things; Robots Description An account of the resource Cloud computing is the latest technology that has a significant influence on everyones life. During the COVID-19 crisis, cloud computing aids cooperation, communication, and vital Internet services. The pandemic situation made the people switch to online mode. The technology helped to bridge the gap between the work space and personal space. A quick evaluation of cloud computing services to health care is conducted through this study in COVID situation. A short overview on how cloud computing technologies are critical for addressing the current predicament has been held. The paper also discusses distant working of cloud computing in health care. Moreover, cloud infrastructure provides a way to connect with different aid personnel. The patient data can be transferred to the cloud for monitoring, surveillance, and diagnosis. Thus, health care is provided instantaneously to all the individuals. Additionally, the study addresses the privacy and security-related issues with appropriate solutions. The paper also briefs on the different kind of services are provided by different CSPs that are cloud service providers to confront this epidemic. This article primarily focuses on cloud computing technology involvement in COVID, and secondary focus is on other technology like blockchain, drones, machine learning and Internet of things in COVID-19. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Anushka Xavier K.; Chetradevee S.L.; Jayapandian N. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-461, pp. 223-233. 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_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2130-8_18</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137002220&doi=10.1007%2F978-981-19-2130-8_18&partnerID=40&md5=84dc07212e15962ece54413da8d7a4f3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137002220&doi=10.1007%2f978-981-19-2130-8_18&partnerID=40&md5=84dc07212e15962ece54413da8d7a4f3</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 Anushka Xavier K., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India; Chetradevee S.L., Department of Computer Science and Engineering, Christ University, Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, Christ University, Kengeri Campus, 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 5G Planning and QoE Management Using Mathematical Benchmarking Techniques for Europe and Middle Eastern Countries Subject The topic of the resource 5G; Data Envelopment Analysis; EMEA; Goal Setting; Quality of Experience Description An account of the resource This paper analyses performance of Europe and Middle Eastern (EMEA) countries over 5G networks across eight key QoE metrics using robust and sophisticated mathematical techniques. The current position of the countries is realized along with feasible benchmarks/targets for metrics that need improvement. The benchmark countries and stretch goals are also presented. 2022 IEEE. Creator An entity primarily responsible for making the resource Gracia S.; Soundarabai P.B.; Raj P. Source A related resource from which the described resource is derived 2022 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 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/CONECCT55679.2022.9865844" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CONECCT55679.2022.9865844</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138306665&doi=10.1109%2FCONECCT55679.2022.9865844&partnerID=40&md5=85fa18027f969e3cd2cffb1f62f8cd79" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138306665&doi=10.1109%2fCONECCT55679.2022.9865844&partnerID=40&md5=85fa18027f969e3cd2cffb1f62f8cd79</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166549781-7 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 Gracia S., Christ University, Department of Computer Science, Bangalore, India; Soundarabai P.B., Christ University, Department of Computer Science, Bangalore, India; Raj P., Reliance Jio Platforms Ltd., Site Reliability Engineering Coe, 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 Impact of Prolonged Screen Time on the Mental Health of Students During COVID-19 Subject The topic of the resource College students; COVID-19; Mental health; Online classes; Screen time Description An account of the resource The COVID-19 pandemic has struck every sector around the world, including the education sector. The pandemic has forced educational institutions around the world to close, putting academic calendars in jeopardy. To keep academic activities going, most educational institutes have switched to online learning platforms. However, the lack of e-learning readiness and the current crisis has taken a toll on students mental health significantly. In this study, we hope to understand better students impressions of online education and the impact of prolonged screen time on students mental health. From the responses of 438 students, our study aims to identify the causes of stress in students due to the online mode of education. From eye stress to limited social interaction, all factors leading to poor mental health are considered. Suggestions for addressing the challenges of online education and approaches to create a more successful online learning environment are also provided. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Shaji A.M.; Vivekanand K.S.; Aurelia S.; Das D. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 469-480. 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_42" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_42</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135077532&doi=10.1007%2F978-981-19-2211-4_42&partnerID=40&md5=d467961e7beeac2db8daf0bd7a99d09b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135077532&doi=10.1007%2f978-981-19-2211-4_42&partnerID=40&md5=d467961e7beeac2db8daf0bd7a99d09b</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 Shaji A.M., CHRIST (Deemed to be University), Bangalore, India; Vivekanand K.S., CHRIST (Deemed to be University), Bangalore, India; Aurelia S., CHRIST (Deemed to be University), Bangalore, India; Das D., 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 Applying Ensemble Techniques for the Prediction of Alcoholic Liver Cirrhosis Subject The topic of the resource Alcoholic liver disease; Ensemble classifier; Liver cirrhosis; Machine learning; Random forest; Stacked ensemble classifier; XGBoost Description An account of the resource More than fifty percent of all liver cognate deaths are caused by alcoholic liver disease (ALD). Excessive drinking over the time leads to alcohol-related steatohepatitis and fatty liver, this in turn can lead to alcoholic liver fibrosis (ALF) and in due course alcohol-related liver cirrhosis (ALC). Detecting ALD at an early stage will reduce the treatment cost to the patient and reduce mortality. In this research, a two-step model is developed for predicting the liver cirrhosis using different ensemble classifiers. Among 41 features recorded during data collection, only 15 features arefound to be effective determinants of the class variable. The proposed stacked ensemble technique for ALD prediction is compared with other ensemble models such as random forest, AdaBoost, and bagging. Through experimentation, it is observed that the proposed model with XGBoost and decision tree as base models and logistic regression as Meta model exhibits prediction accuracy of 93.86%. The prediction accuracy of theproposed stacked ensemble technique is 0.2% better in prediction accuracy and 0.3% reduced error rate in comparison with random forest classifier. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Vinutha M.R.; Chandrika J.; Krishnan B.; Kokatnoor S.A. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 433-445. 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_39" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_39</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135054733&doi=10.1007%2F978-981-19-2211-4_39&partnerID=40&md5=3d449fa1b83f044f9de0eb133ff157f9" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135054733&doi=10.1007%2f978-981-19-2211-4_39&partnerID=40&md5=3d449fa1b83f044f9de0eb133ff157f9</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 Vinutha M.R., Department of ISE, Malnad College of Engineering, Hassan, 573201, India; Chandrika J., Department of ISE, Malnad College of Engineering, Hassan, 573201, India; Krishnan B., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Kokatnoor S.A., Department of Computer Science and Engineering, CHRIST (Deemed to be University), 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 A Multi Objective Artificial Eco-System Based Optimization Technique Integrating Solar Photovoltaic System In Distribution Network Subject The topic of the resource Agriculture Feeder; Artificial Eco-System based Optimization; Distribution system; Multi Objective Optimization Technique; Solar PV system Description An account of the resource Agricultural sector contributes 6.4% of total economic generation across the world. Notably, the utilization of technology to improve the yield and economy is rapidly increasing. To provide continuous supply to the residential customers, the agricultural feeder grid-dependency has to be integrated with Solar Photo Voltaic (SPV) systems. In this paper, an Artificial Eco-System based Optimization (AEO) algorithm is proposed for simultaneously identifying the locations and quantifying the sizes of SPV systems. A practical distribution system feeder 'Racheruvu 11kV agricultural feeder' Andhra Pradesh, India is considered for simulation purpose and the performance is compared with the standard IEEE-33 radial distribution system. 2022 IEEE. Creator An entity primarily responsible for making the resource Kamal Kumar U.; Janamala V. Source A related resource from which the described resource is derived International Conference on Trends in Electrical, Electronics, Computer Engineering, TEECCON 2022, pp. 128-134. 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/TEECCON54414.2022.9854838" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TEECCON54414.2022.9854838</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138118162&doi=10.1109%2FTEECCON54414.2022.9854838&partnerID=40&md5=f42dfd66cfca136a9bb00de4c311be6b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138118162&doi=10.1109%2fTEECCON54414.2022.9854838&partnerID=40&md5=f42dfd66cfca136a9bb00de4c311be6b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548366-7 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 Kamal Kumar U., Christ (Deemed to Be University), Dept. of Electrical and Electronics Engineering, Bangalore, 560 074, India; Janamala V., Christ (Deemed to Be University), Faculty of Engineering, Dept. of Electrical and Electronics Engineering, Bangalore, 560 074, 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 Efficient Face Recognition System using Deep Transfer Learning Subject The topic of the resource Artificial neural networks; machine learning; Transfer learning Description An account of the resource Face recognition is an AI-based innovation used to find and recognize human appearances in videos and images. Organizations can apply face recognition to many different kinds of fields which may include biometrics, regulation of law, security and individual wellbeing; so as to take observation of individuals in any scenario. Face recognition has advanced from simple vision methods to progress in ML; and further to progressively refined neural networks (ANN) and related advances. It currently assumes an indispensable part as the initial phase in numerous basic applications, including the task of tracking a face. Face recognition is utilized to focus cameras or count the number of individuals present in a particular region. The innovation likewise has showcasing applications, for instance, showing recommended promotions when a specific user is detected. 2022 IEEE. Creator An entity primarily responsible for making the resource Ragsania R.; 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. 2199-2203. 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/ICACITE53722.2022.9823797" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823797</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135496522&doi=10.1109%2FICACITE53722.2022.9823797&partnerID=40&md5=d5638336639a173e1adede28f4944ae4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135496522&doi=10.1109%2fICACITE53722.2022.9823797&partnerID=40&md5=d5638336639a173e1adede28f4944ae4</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 Ragsania R., Christ University, Department of Data Science, India; Vijayalakshmi S., 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 One Time Password-Based Two Channel Authentication MechanismUsing Blockchain Subject The topic of the resource Blockchain; Bluetooth; Fog nodes; Hashing; OTP Description An account of the resource Using Fog Nodes, also known as IOT devices are increasing everyday with more and more home automation, industry automation, automobile automation, etc. Security threats for these devices are also increasing. One of the threats is impersonating one fog node, stealing data and taking control of the network which is also known as the Sybil attack. To provide security, most fog devices use one step or two step authentication and sometimes use encryption. With static passwords, there is a chance of compromise by password sharing and leaking. Some weak encryption algorithms used are also compromised. Data about fog nodes in the network is stored in a weak database and is tampered. OTP-based Two Channel Authentication Mechanism (OTPTAM) to authenticate the fog nodes with metadata stored in Blockchain Database and communicate using channels encrypted with Elliptical Ciphers can solve the majority of these problems. Metadata of the nodes like Bluetooth MAC address, network mac address, telephone number are all stored in the blockchain and the OTP is exchanged via these channels to ensure the authenticity of the fog nodes. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Asha H.P.; Jingle I.D.J. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 229-237. 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_20" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_20</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135072150&doi=10.1007%2F978-981-19-2211-4_20&partnerID=40&md5=ac047cd0049cabbfc866f2c8482729e0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135072150&doi=10.1007%2f978-981-19-2211-4_20&partnerID=40&md5=ac047cd0049cabbfc866f2c8482729e0</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 Asha H.P., Department of Computer Science and Engineering, School of Engineering and Technology, Christ (Deemed to be) University, Bangalore, India; Jingle I.D.J., Department of Computer Science and Engineering, School of Engineering and Technology, 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 CoInMPro: Confidential Inference and Model Protection Using Secure Multi-Party Computation Subject The topic of the resource Confidential inference and model protection; Machine learning (ML); Privacy; Privacy-preserving machine learning (PPML); Secure multi-party computation (SMPC) Description An account of the resource In the twenty-first century, machine learning has revolutionized insight generation by using historical data across domains like health care, finance, and pharma. The effectiveness of machine learning solutions depends largely on the collaboration between data owners, model owners, and ML clients, without privacy concerns. The existing privacy-preserving solutions lack efficient and confidential ML inference. This paper addresses this inefficiency by presenting the Confidential Inference and Model Protection, also known as the CoInMPro, to solve the privacy issue faced by model owners and ML clients. The CoInMPro technique is suggested with an aim to boost the privacy of model parameters and client input during ML inference, without affecting the accuracy and by paying a marginal performance cost. Secure multi-party computation (SMPC) techniques were used to calculate inference results confidentially after sharing client input and model parameters privately from different model owners. The technique was implemented in Python language using the open-source SyMPC library to support the SMPC function. The Boston Housing Dataset was used, and the experiments were run on Azure data science VM using Ubuntu OS. The result suggests CoInMPros effectiveness in addressing privacy concerns of model owners and inference clients, with no sizable impact on accuracy and trade-off. A linear impact on performance was noted with an increase of secure nodes in the SMPC cluster. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Tiwari K.; Bisht K.; George J.P. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 1-14. 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_1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_1</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135054262&doi=10.1007%2F978-981-19-2211-4_1&partnerID=40&md5=089e4c8b7eacbd6bd3f0aca9a09b5564" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135054262&doi=10.1007%2f978-981-19-2211-4_1&partnerID=40&md5=089e4c8b7eacbd6bd3f0aca9a09b5564</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 Tiwari K., CHRIST University, Bengaluru, India; Bisht K., CHRIST University, Bengaluru, India; George J.P., 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 Machine Learning based Loan Eligibility Prediction using Random Forest Model Subject The topic of the resource Borrowers; Customer Prediction; Data Collecction; Lloan Eligibility; Machine Learning; Random Forest Description An account of the resource When one or more people, organizations, or other entities lend money to other people, organizations, or entities, it is known as a loan. The recipient (that is the borrower) takes on a debt for which he or she is normally accountable for interest payments until the loan is repaid. The major goal of this proposed model is to ensure that an individual, institution, or organization seeking for a loan is properly verified before granting them the loan they require. Before authorizing a loan for any individual or business several factors must be considered. That including gender, education, and the number of dependents. The goal of proposed model is to automate the method, which will save time and energy while improving the efficiency of the process. This particular process input is having two different kind of data set. First one is train data set and second set is test data set. The first date set that is train data set is generally used to train and assess the machine learning model accuracy. The loan eligibility predictions are generated using the test data set. To forecast loan eligibility and train this random forest, machine learning method called Random Forest. The proposed random forest model is providing higher accuracy level. This model is providing 28 % higher accuracy level compare to regular prediction. 2022 IEEE. Creator An entity primarily responsible for making the resource Reddy C.S.; Siddiq A.S.; Jayapandian N. Source A related resource from which the described resource is derived 7th International Conference on Communication and Electronics Systems, ICCES 2022 - Proceedings, pp. 1073-1079. 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/ICCES54183.2022.9835875" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCES54183.2022.9835875</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136323011&doi=10.1109%2FICCES54183.2022.9835875&partnerID=40&md5=7fcf8f6c66506dc06bba7a8b81831425" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136323011&doi=10.1109%2fICCES54183.2022.9835875&partnerID=40&md5=7fcf8f6c66506dc06bba7a8b81831425</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166549634-6 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 Reddy C.S., Christ, Deemed to Be University, Department of Cse, Bangalore, India; Siddiq A.S., Christ, Deemed to Be University, Department of Cse, Bangalore, India; Jayapandian N., Christ, Deemed to Be University, Department of Cse, 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 Analytical Study on the influence of using Trimmed Gait Energy Images for Human Gait Biometrics using Deep Learning Subject The topic of the resource Biometric; Convolution neural networks; Gait Energy Images; Gait recognition; trimmed images Description An account of the resource Gait based human recognition is founded on the principle that every human being has a distinctive style of walking. With the rise in the use of video surveillance devices, gait is one of the most convenient biometrics to use, in forensics. This paper is an analytical study of the effect of using trimmed Gait Energy Images (GEI) for Human Recognition using different deep learning techniques. Gait energy images are a spatiotemporal, silhouette-based representation of the human gait. GEIs from the CASIA B Multiview dataset was used to build two other sets of data by subtracting the upper body Deep learning and transfer learning techniques including Convolution Neural Networks (CNN) and VGG16 algorithms had been implemented to carry out the recognition. Results showed that the performance of the model using upper body images gives a greater accuracy than the lower body images. It has also been observed that the accuracy of recognition provided by the upper part of the body is almost the same as that achieved by the whole body, which brings forth the idea that the upper part of the body is the most pertinent in Human Identification using Gait as a biometric. 2022 IEEE. Creator An entity primarily responsible for making the resource Poulose N.P.; Kt T. 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. 1266-1269. 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/ICACITE53722.2022.9823497" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823497</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135468879&doi=10.1109%2FICACITE53722.2022.9823497&partnerID=40&md5=63edf660bf93d298e59a9a9abea99922" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135468879&doi=10.1109%2fICACITE53722.2022.9823497&partnerID=40&md5=63edf660bf93d298e59a9a9abea99922</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 Poulose N.P., Christ University, Bangalore, Department of Data Science, Bangalore, India; Kt T., Christ University, Bangalore, Department of Data Science, 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 CNN-RNN based Hybrid Machine Learning Model to Predict the Currency Exchange Rate: USD to INR Subject The topic of the resource CNN; DNN; FLANN; LSTM; RNN Description An account of the resource Foreign currency exchange plays an imperative part in the global business and in monetary market. It is also an opportunity for many traders as an investment option and the advance knowledge of fluctuation helps the investors making right decision on time. However, due to its volatile nature, prediction of foreign currency exchange is a challenging task. This paper implements two models based on machine learning, namely Recurrent Neural Networks (RNN) and a Hybrid model of Convolutional Neural Networks (CNN) with RNN known as CNN-RNN to assess the accuracy in predicting the conversion rate of US Dollar (USD) to Indian Rupees (INR). The data set used to verify and validate the models is the daily currency exchange rate (USD to INR) available in public domain. The experimental results show that the simple RNN model performs slightly better than the hybrid model in this particular case. Though the accuracy of the hybrid model is very high in terms of error calculation still the single RNN model is the better performer. This does not straight away reject the hybrid model rather needs more experimental analysis with changing architecture and data set. 2022 IEEE. Creator An entity primarily responsible for making the resource Singh G.; Sarangi P.K.; Rani L.; Sharma K.; Sinha S.; Sahoo A.K.; Rath B.P. 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. 1668-1672. 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/ICACITE53722.2022.9823844" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823844</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135450011&doi=10.1109%2FICACITE53722.2022.9823844&partnerID=40&md5=0430a53b1d8def6ab8a7c56ca034948f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135450011&doi=10.1109%2fICACITE53722.2022.9823844&partnerID=40&md5=0430a53b1d8def6ab8a7c56ca034948f</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 Singh G., Chitkara University Institute of Engineering and Technology, Chitkara University Punjab, Department of Computer Science and Engineering, India; Sarangi P.K., Chitkara University Institute of Engineering and Technology, Chitkara University Punjab, Department of Computer Science and Engineering, India; Rani L., Chitkara University Institute of Engineering and Technology, Chitkara University Punjab, Department of Computer Science and Engineering, India; Sharma K., Chitkara University Institute of Engineering and Technology, Chitkara University Punjab, Department of Computer Science and Engineering, India; Sinha S., Christ University, Department of Computer Science and Engineering, Bangalore, India; Sahoo A.K., Graphic Era Hill University, Department of Computer Science and Engineering, Dehradun, India; Rath B.P., Cognizant Technology Solutions Ltd., Department of 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 Machine Learning Techniques in Predicting Heart Disease a Survey Subject The topic of the resource and random forest; decision tree; heart disease; logistic regression; support vector machine Description An account of the resource The heart serves an important role in living creatures. Diagnosis and forecast of cardiac illnesses demand greater precision, perfection, and accuracy because such tiny mistakes can lead to weariness and death. Numerous heart-related deaths have occurred, and the incidence rates have been rising over time. Predicting the development of heart disorders is important to work in the medical industry. Every month, many databases related to the patient are kept. The information gathered can be used to predict the occurrence of future diseases. This article gives an outline of cardiovascular diseases and modern treatments. Also, the focus of this research is to outline some current research on applying machine learning techniques to predict heart disease, analyze the many machine learning algorithms employed, and determine which technique(s) are useful and efficient. Artificial neural network (ANN), decision tree (DT), fuzzy logic, K-nearest neighbor (KNN), Naive bayes (NB), and support vector machine (SVM) are data mining and machine learning approaches used to predict cardiac disease. This paper includes an overview of the present method based on features, the algorithms are compared, and the most accurate algorithm is analyzed. 2022 IEEE. Creator An entity primarily responsible for making the resource Roy R.E.; Kulkarni P.; 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. 373-377. 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/AIC55036.2022.9848945" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIC55036.2022.9848945</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137786934&doi=10.1109%2FAIC55036.2022.9848945&partnerID=40&md5=7abcd5062d96953ffe5411d2fbee12c4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137786934&doi=10.1109%2fAIC55036.2022.9848945&partnerID=40&md5=7abcd5062d96953ffe5411d2fbee12c4</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 Roy R.E., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India; Kulkarni P., 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 Improvement to Recommendation system using Hybrid techniques Subject The topic of the resource Collaborative Filtering method; Content-based filtering method; Hybrid Recommendation; Limitation; Movie Recommendation; User ratings Description An account of the resource Currently, recommendation systems are a common tool for providing individualized recommendations and item information to users. For personalization in the recommendation system, there are a variety of strategies that can be used. To improve system performance and offset the shortcomings of individual recommendation strategies, a hybrid recommender system integrates two or even more recommendation techniques. The demand to summarize all of the knowledge on actual methods and algorithms utilized in hybrid recommended systems necessitates the need for a systematic review in the domain. These materials will be employed to aid in the development of an auto-switching hybrid recommender system. In the content-based filtering technique, the algorithm is based on the contents of items and the collaborative filtering technique algorithm combines the relationship between user and item. Both of the approaches of recommendation system are suffers from some limitations, this is a big issue to predict better recommendations to the user. Hybrid systems are introduced to overcome the main limitations of both techniques. These systems are made with a combination of content-based and collaborative filtering techniques and have advantages of both techniques. With the use of hybrid systems, the quality of recommendations is improved. Hybrid recommendation systems use previous data of a user to find his/her interest and then they target the set of an adjacent user which is similar with that user and according to adjacent user recommend things to the user. Hybrid systems offer the items that share the common things that a user rated highly (Content-based filtering) and make suggestions by comparing the interest of a similar user (Collaborative filtering). 2022 IEEE. Creator An entity primarily responsible for making the resource Ramesh R.; 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. 778-782. 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/ICACITE53722.2022.9823879" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823879</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135492454&doi=10.1109%2FICACITE53722.2022.9823879&partnerID=40&md5=c6569f4ff71fcb2f09fb9d7977dfd85d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135492454&doi=10.1109%2fICACITE53722.2022.9823879&partnerID=40&md5=c6569f4ff71fcb2f09fb9d7977dfd85d</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 Ramesh R., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Pune, India; Vijayalakshmi S., Christ (Deemed to Be University), Department of Data Science, Maharashtra, Pune, India