95 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 Exploring the Frontier: Space Mining, Legal Implications, and the Role of Artificial Intelligence Subject The topic of the resource Artificial Intelligence; Environmental Ethics; Legal Frameworks; Space Mining; Technological Advancements Description An account of the resource This analysis delves into the multifaceted dimensions of space mining and artificial intelligence, exploring technological advancements, legal challenges, environmental concerns, and ethical implications. Through topic modeling and sentiment analysis of 160 articles, five core themes are identified: Technological and Exploration Advances, Resource Extraction and Environmental Concerns, Legal and AI Integration, Ethical and Paradigm Shifts, and challenges and Innovations in Space Mining. The discussion highlights the optimistic yet cautious outlook on space mining, emphasizing the need for continued innovation, comprehensive legal frameworks, ethical stewardship, and environmental protection as humanity ventures into this new frontier. 2024 IEEE. Creator An entity primarily responsible for making the resource Yadav R.K.; Somu C.S. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545181" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545181</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204501959&doi=10.1109%2FTQCEBT59414.2024.10545181&partnerID=40&md5=c0c4ae8090ccaabcfe79694c8bcfde66" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204501959&doi=10.1109%2fTQCEBT59414.2024.10545181&partnerID=40&md5=c0c4ae8090ccaabcfe79694c8bcfde66</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Yadav R.K., Christ University, Bengaluru, India; Somu C.S., 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 Digital Water Dynamics: Analyzing VA Tech Wabag's Influence on India's Water Technology Landscape Subject The topic of the resource Digital Water Solutions; India's Water Sector; Sustainable Water Management; VA Tech Wabag Description An account of the resource This research delves into the transformative role of VA Tech Wabag in India's water technology landscape, amid the burgeoning challenges of water scarcity, pollution, and infrastructure inadequacies. Leveraging a comprehensive review of literature and fundamental analysis, the study underscores the global shift towards digitalization and sustainability in water management, situating VA Tech Wabag's initiatives at the forefront of this paradigm shift. Through innovative digital water solutions and large-scale infrastructure projects, the company has markedly enhanced water quality and availability across diverse urban and rural settings, underpinning its financial resilience and growth trajectory despite regulatory and fiscal hurdles. The discussion extrapolates the implications of these technological advancements, highlighting the company's commitment to environmental stewardship, community engagement, and the imperative for continuous innovation within a dynamic industry landscape. Conclusively, the paper affirms VA Tech Wabag's pivotal contributions to water security and resilience, advocating for future research on the scalability of digital water technologies and their long-term impacts on resource management. This study, enriched with specific data points and analyses, aims to offer a well-substantiated overview of VA Tech Wabag's influence on shaping a sustainable and efficient water technology ecosystem in India. 2024 IEEE. Creator An entity primarily responsible for making the resource Joseph D.; Girish S. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545195" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545195</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204495386&doi=10.1109%2FTQCEBT59414.2024.10545195&partnerID=40&md5=148fbd40d666e8c0d7be337c6d298510" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204495386&doi=10.1109%2fTQCEBT59414.2024.10545195&partnerID=40&md5=148fbd40d666e8c0d7be337c6d298510</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Joseph D., Christ University, School of Commerce, Finance & Accountancy, India; Girish S., Christ University, School of Commerce, Finance & Accountancy, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Enhancing Copper Price Prediction: A Machine Learning and Explainable AI Approach Subject The topic of the resource Copper price prediction; Explainable AI (XAI); Machine learning models; Random Forest algorithm; Time series forecasting Description An account of the resource This research introduces a hybrid model for copper price prediction, employs advanced machine learning models (linear regression, random forest, SVM, Adaboost, ARIMA), and utilizes the SHAP method for model interpretability. The study focuses on transportation-related variables over a 10-year period from Bloomberg Terminal, employing STL decomposition for time series forecasting. Key features impacting copper prices are identified, emphasizing the significance of demand, transportation, and supply. The Random Forest model highlights the critical role of demand. Addressing transportation supply constraints is crucial for enhancing model output in the dynamic copper market. 2024 IEEE. Creator An entity primarily responsible for making the resource Singh A.; Mahajan J.; Sharma M.; Saxena A.; Khan M.H.; Kakani R. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545208" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545208</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204469793&doi=10.1109%2FTQCEBT59414.2024.10545208&partnerID=40&md5=9386fa4b1f2ccb603876b8d2aa6b0550" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204469793&doi=10.1109%2fTQCEBT59414.2024.10545208&partnerID=40&md5=9386fa4b1f2ccb603876b8d2aa6b0550</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Singh A., Christ University, Bengaluru, India; Mahajan J., Christ University, Bengaluru, India; Sharma M., Christ University, Bengaluru, India; Saxena A., Christ University, Bengaluru, India; Khan M.H., Christ University, Bengaluru, India; Kakani R., Sg Analytics, 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 Role of Artificial Intelligence in Influencing Impulsive Buying Behaviour Subject The topic of the resource Artificial intelligence (AI); consumer behaviour; data analysis; impulse buying behaviour Description An account of the resource This research paper investigates the influence of Artificial Intelligence (AI) on impulsive buying behaviour in the digital commerce domain. The study explores how AI algorithms, data analysis, and customized marketing approaches influence impulsive buying decisions, reshaping traditional understandings of this phenomenon. The analysis draws from a confluence of psychological principles, technological advancements, and marketing strategies, aiming to shed light on how AI not only forecasts but also incites impulsive buying behaviours. The study identifies research gaps, such as the integration of AI with emotional triggers, the comparative effectiveness of AI vs. human influence, and cross-cultural and demographic variability. The research methodology involves a descriptive study with a questionnaire-based survey, and data analysis tools such as ANOVA and paired t-tests. This research contributes to the broader discussion on digital-age consumer behaviors, underscoring the revolutionary role of AI in transforming retail experiences and beyond. 2024 IEEE. Creator An entity primarily responsible for making the resource Roy B.; D'Souza M.S.; Bhattacharjee S.; Acharjee P.B.; Thorat S.; Bhayani T. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545278" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545278</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204494971&doi=10.1109%2FTQCEBT59414.2024.10545278&partnerID=40&md5=e87d260b4ecdd2875c56b0adc68897dc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204494971&doi=10.1109%2fTQCEBT59414.2024.10545278&partnerID=40&md5=e87d260b4ecdd2875c56b0adc68897dc</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 B., Christ University, India; D'Souza M.S., Christ University, India; Bhattacharjee S., Christ University, India; Acharjee P.B., Christ University, India; Thorat S., Christ University, India; Bhayani T., 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 Beyond the Stats: How Investment Decisions Are Influenced by Non-Accounting Data Subject The topic of the resource accounting information; decision-making factors; financial markets; financial reports; investment analysis; Investment decision-making; market information; non-accounting information; shareholders Description An account of the resource Making investment decisions is a complex process that is influenced by data from non-accounting and accounting sources. In order to better understand the importance of financial reports in comparison to non-accounting data [1], this article examines this complexity. The study is guided by three main objectives: determining the relative importance of financial reports against non-accounting sources; determining the effect of non-accounting information on investment decisions [2]; and investigating the role of demographic factors on this effect. The study finds that, when making investment decisions, shareholders more frequently turn to non-accounting sources through thorough analysis and statistical testing. Notably, credit rating agencies, stock indices, and brokers all have a big say in how decisions are made, highlighting their significance. This work improves our knowledge of how accounting and non-accounting data interact to influence investment decision-making. It emphasizes how crucial it is to take into account a variety of information sources in order to make wise financial decisions [3]. When navigating the ever-changing market landscape of today, investors, financial analysts, and politicians can benefit greatly from these ideas. 2024 IEEE. Creator An entity primarily responsible for making the resource Sharma R.; Prajkta Yawalkar D.; Sanghvi M.; Bikash Acharjee P.; Ashfaq A.; Dixit A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545146" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545146</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204434234&doi=10.1109%2FTQCEBT59414.2024.10545146&partnerID=40&md5=a4159e50c4ac04ee909e650968a1c5c7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204434234&doi=10.1109%2fTQCEBT59414.2024.10545146&partnerID=40&md5=a4159e50c4ac04ee909e650968a1c5c7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Sharma R., Christ University, Bengaluru, India; Prajkta Yawalkar D., Christ University, Bengaluru, India; Sanghvi M., Christ University, Bengaluru, India; Bikash Acharjee P., Christ University, Bengaluru, India; Ashfaq A., Christ University, Bengaluru, India; Dixit A., 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 SmartHealth: Personalized Diet and Exercise Plans Using Similarity Modeling Subject The topic of the resource cosine similarity; healthcare informatics; Pearson correlation; personalized recommendations; personalized wellness Description An account of the resource Due to the growing prevalence of chronic diseases stemming from unhealthy lifestyles, a personalized approach to patient care is crucial. This paper delves into a system that utilizes cosine similarity and Pearson correlation to generate tailored diet and exercise plans, effectively managing chronic diseases. The system focuses on common chronic conditions like diabetes, hypertension, and thyroid disorders. Through sophisticated similarity modeling for diet and exercise, the proposed system provides integrated and personalized lifestyle recommendations, outperforming non-personalized or basic rule-based systems. 2024 IEEE. Creator An entity primarily responsible for making the resource Kulkarni K.S.; Bansal D.; Bhagat V.V.; Ganie A.H. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545041" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545041</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204492602&doi=10.1109%2FTQCEBT59414.2024.10545041&partnerID=40&md5=7e53885505782bdff5fac5bc94009fff" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204492602&doi=10.1109%2fTQCEBT59414.2024.10545041&partnerID=40&md5=7e53885505782bdff5fac5bc94009fff</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Kulkarni K.S., Christ University, Department of Data Science, Bangalore, India; Bansal D., Christ University, Department of Data Science, Bangalore, India; Bhagat V.V., Christ University, Department of Data Science, Bangalore, India; Ganie A.H., Christ University, 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 IoT Based Enhanced Safety Monitoring System for Underground Coal Mines Using LoRa Technology Subject The topic of the resource Internet of Things (IoT); LoRa Technology; LoRaWAN protocol; Low Power Wide Area Network (LPWAN); Underground Coal Mining Description An account of the resource Extracting coal from Underground mine is a hazardous and tough job that needs continuous monitoring of environmental conditions to protect workers health and safety. Though some research works have explored wireless monitoring devices for underground mining, such as ZigBee and Wi-Fi technologies, they come with inherent restraints for instance restricted coverage, susceptibility to interference, reliability issues, security concerns, and high-power consumption. An Enhanced Safety Monitoring System for coal extraction from Underground Mines, employing LoRa communication technology for the effectual transmission of collected data to overcome existing challenges is discussed in this paper. The proposed system consists of two subsystems, one for monitoring the status of miners and another for comprehensive monitoring. LoRaWAN (Long Range Wide Area Network) is a multipoint protocol and this media access control (MAC) enables low-power devices to establish communication with Internet of Things (IoT) applications over extended wireless connections for long-range networks. LoRaWAN operates on lower radio frequencies, thereby providing a longer range of communication. This technology is known for its efficiency in optimizing LPWAN, offering extended range, extended battery life, robustness, and cost-effectiveness, making it highly suitable for industrial mining applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Joy S.; Bale A.S.; Anju M.I.; Baby Chithra R.; Patil K.A.; Neethu P.S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-1029 LNNS, pp. 125-130. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-61929-8_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-61929-8_18</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204603785&doi=10.1007%2F978-3-031-61929-8_18&partnerID=40&md5=d9fc2a9d02a5865a4421a9d99ed2ff3f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204603785&doi=10.1007%2f978-3-031-61929-8_18&partnerID=40&md5=d9fc2a9d02a5865a4421a9d99ed2ff3f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-303161928-1 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 Joy S., Department of ECE, New Horizon College of Engineering, Bengaluru, 560103, India; Bale A.S., Department of ECE, New Horizon College of Engineering, Bengaluru, 560103, India; Anju M.I., Department of ECE, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, 600026, India; Baby Chithra R., Department of ECE, New Horizon College of Engineering, Bengaluru, 560103, India; Patil K.A., Division Electronics & Telecommunication Engineering, M.S. Ramaiah Institute of Technology, Bengaluru, 560103, India; Neethu P.S., Department of ECE, 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 Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model Subject The topic of the resource quantum computer architecture; Quantum computing; quantum machine learning; quantum neural networks Description An account of the resource This study explores the application of Quantum Convolutional Neural Networks (QCNNs) in the realm of image classification, particularly focusing on datasets with a highly reduced number of features. We investigate the potential quantum computing holds in processing and classifying image data efficiently, even with limited feature availability. This research investigates QCNNs' application within a highly constrained feature environment, using chest X-ray images to distinguish between normal and pneumonia cases. Our findings demonstrate QCNNs' utility in classifying images from the dataset with drastically reduced feature dimensions, highlighting QCNNs' robustness and their promising future in machine learning and computer vision. Additionally, this study sheds light on the scalability of QCNNs and their adaptability across various training-test splits, emphasizing their potential to enhance computational efficiency in machine learning tasks. This suggests a possibility of paradigm shift in how we approach data-intensive challenges in the era of quantum computing. We are looking into quantum paradigms like Quantum Support Vector Machine (QSVM) going forward so that we can explore trade offs effectiveness of different classical and quantum computing techniques. 2024 IEEE. Creator An entity primarily responsible for making the resource Khatoniar R.; Vyas V.; Acharya V.; Saxena A.; Saxena A.; Neiwal R.; Korgaonkar K. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545121" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545121</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204471580&doi=10.1109%2FTQCEBT59414.2024.10545121&partnerID=40&md5=b51c697fe98a7090a1cf056fa022674b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204471580&doi=10.1109%2fTQCEBT59414.2024.10545121&partnerID=40&md5=b51c697fe98a7090a1cf056fa022674b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Khatoniar R., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, India; Vyas V., C-DAC Pune, Pune, India; Acharya V., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, India; Saxena A., Christ University, Bengaluru, India; Saxena A., C-DAC Pune, Pune, India; Neiwal R., MeitY (Delhi), Delhi, India; Korgaonkar K., Bits Pilani, Csis Department, K K Birla Goa Campus Goa, 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 Deep Learning Based Age Estimation Model Subject The topic of the resource Accuracy; convolutional neural network (CNN); Data Augmentation; Machine learning algorithm; Mean absolute error; Preprocessing; RELU Description An account of the resource To improve accuracy and resilience in demographic categorization, this research presents a novel use of Convolutional Neural Networks (CNNs) for age prediction. Deep learning is utilized to achieve this goal. Precise estimation of age has become essential in a variety of areas, including human-computer interaction, marketing, and healthcare. The ability of CNNs to handle the intricacies of facial features for accurate demographic forecasts is examined in this study. The research covers every step of the age prediction process, including dataset collection, prepossessing, model architecture, and assessment measures. The CNN is trained to automatically extract hierarchical characteristics from facial photos, which enables the model to recognize complex patterns related to age. The architecture's flexibility to different lighting conditions, facial expressions, and postures. In this research, we deal with deep learning-based perceived age estimation in still-face pictures. Our Convolution Neural Network models (CNNs) have been trained prior on Image Net for picture classification, as they use the VGG architecture. In addition, we analyze the effects of tailoring over Web photos having known age, considering a lack of apparent age-annotated annotated images. In addition, this work adds to the increasing library of studies on the use of deep learning methods for demographic data evaluation by showing the effectiveness of CNNs to predict age. The results show how, in practical situations, CNNs could significantly enhance the precision and dependability of age prediction systems. 2024 IEEE. Creator An entity primarily responsible for making the resource Reddy G.J.; Bendili S.; Vinodha D.; Jenefa J.; Sambandam R.K.; Vetriveeran D. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545269" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545269</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204482593&doi=10.1109%2FTQCEBT59414.2024.10545269&partnerID=40&md5=13551662f0d49d361ac40ccbfeca5911" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204482593&doi=10.1109%2fTQCEBT59414.2024.10545269&partnerID=40&md5=13551662f0d49d361ac40ccbfeca5911</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Reddy G.J., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Bengaluru, India; Bendili S., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Bengaluru, India; Vinodha D., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Bengaluru, India; Jenefa J., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Bengaluru, India; Sambandam R.K., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Bengaluru, India; Vetriveeran D., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, 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 Explainable Artificial Intelligence: Frameworks for Ensuring the Trustworthiness Subject The topic of the resource and Transparency; Autonomy; Control; Data Privacy; Fairness; Reliability; Safety and Security Description An account of the resource The growing computer power and ubiquity of big data are allowing Artificial Intelligence (AI) to gain widespread adoption and applicability in a wide range of sectors. The absence of an explanation for the conclusions made by today's AI algorithms is a significant disadvantage in crucial decision-making systems. For example, existing black-box AI systems are vulnerable to bias and adversarial assaults, which can taint the learning and inference processes. Explainable AI (XAI) is a recent trend in AI algorithms that gives explanations for their AI conclusions. Many contemporary AI systems have been shown to be vulnerable to undetectable assaults, biased against underrepresented groups, and deficient in user privacy protection. These flaws damage the user experience and undermine people's faith in all AI systems. This study proposes a systematic way to tie the social science notions of trust to the technology employed in AI-based services and products. 2024 IEEE. Creator An entity primarily responsible for making the resource Shama U.; Sharma V.; Gupta V. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545063" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545063</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204449341&doi=10.1109%2FTQCEBT59414.2024.10545063&partnerID=40&md5=7514240432d4d683ddf10df45d0ca3f3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204449341&doi=10.1109%2fTQCEBT59414.2024.10545063&partnerID=40&md5=7514240432d4d683ddf10df45d0ca3f3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Shama U., Christ University, Banglore, India; Sharma V., Christ University, Banglore, India; Gupta V., Christ University, Banglore, 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 Ethical and Societal Implications of Artificial Intelligence in Space Mining Subject The topic of the resource Artificial Intelligence (AI); Economic Efficiency; Ethical Considerations; Governance; Space Mining Description An account of the resource The advent of Artificial Intelligence (AI) in space mining marks a pivotal shift in the exploration and utilization of extraterrestrial resources. This paper presents a thematic analysis of the ethical, societal, technological, economic, and environmental implications of integrating AI in space mining operations. Through topic modeling of relevant literature, five key themes were identified: AI integration and ethical considerations, economic efficiency and equity, technological innovations and advancements, international collaboration and governance, and environmental sustainability and planetary protection. These themes highlight the potential of AI to revolutionize space mining, enhancing efficiency and enabling the extraction of valuable resources beyond Earth. However, they also underscore the need for robust ethical frameworks, equitable economic models, international cooperation, and sustainable practices to address the multifaceted challenges posed by this frontier. The paper concludes with recommendations for future research and policy-making, emphasizing the importance of inclusive, collaborative approaches to ensure the responsible and beneficial advancement of space mining. 2024 IEEE. Creator An entity primarily responsible for making the resource Yadav R.K.; Somu C.S. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545295" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545295</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204464813&doi=10.1109%2FTQCEBT59414.2024.10545295&partnerID=40&md5=4b1e7dc016b6631716e2f8969f4b9435" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204464813&doi=10.1109%2fTQCEBT59414.2024.10545295&partnerID=40&md5=4b1e7dc016b6631716e2f8969f4b9435</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Yadav R.K., Christ University, Bengaluru, India; Somu C.S., Christ University, Bengaluru, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Enhancing Natural Gas Price Prediction: A Machine Learning and Explainable AI Approach Subject The topic of the resource Feature Engineering; Machine Learning Algorithms; Model Evaluation; Natural Gas; Predictive Analysis Description An account of the resource This research includes an innovative approach to refine natural gas price predictions by employing advanced machine learning techniques, including Random Forest, Linear Regression, and Support Vector Machine algorithms. Against the backdrop of natural gas's increasing influence in the energy sector, both environmentally and economically, the study adopts a robust methodology using a comprehensive dataset from Kaggle. Through rigorous data preprocessing, feature engineering, and model training, the chosen algorithms are optimized to capture complex patterns within the data, demonstrating the potential to significantly enhance forecast precision. The application of these techniques aims to extract meaningful insights, providing stakeholders in the natural gas market with more accurate and reliable predictions, there by contributing to a deeper understanding of market dynamics and informed decision- making. 2024 IEEE. Creator An entity primarily responsible for making the resource Singh K.; Mahajan J.; Singh V.P.; Paswan A.S.; Saxena A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545057" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545057</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204456145&doi=10.1109%2FTQCEBT59414.2024.10545057&partnerID=40&md5=3946dd63d268db5e91bba072c4a62d6a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204456145&doi=10.1109%2fTQCEBT59414.2024.10545057&partnerID=40&md5=3946dd63d268db5e91bba072c4a62d6a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Singh K., Christ University, India; Mahajan J., Christ University, India; Singh V.P., Ewec, United Arab Emirates; Paswan A.S., 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 Optimizing Food Production with a Sustainable Lens: Exploring Blockchain Technology in Raw Plant Materials and Organic Techniques in Achieving Sustainable Development Goals Subject The topic of the resource Environmental security; Food security; Long-term farming; Organic techniques; Raw plant materials utilization; Renewable resources; Sustainable agriculture; Waste reduction Description An account of the resource Amidst a rising population and mounting environ- mental concerns, India seeks a transformative approach to ensure food security and sustainable agriculture by 2030, as outlined in Sustainable Development Goal 2 (SDG 2). This research explores the immense potential of organic farming methods and raw plant materials to unlock this vision. Plants have a wealth of unrealized potential that extends beyond their conventional functions. The study looks at how different plant parts, like branches, leaves, stems, and even "waste"materials, can be used in a variety of ways to increase self-sufficiency, lessen environmental impact, and access renewable resources. Case studies from across the globe highlight this potential, highlighting the many advantages for the environment and communities. Additionally, the study investigates the innovative use of blockchain technology to promote a more transparent and resilient agricultural environment in India. Imagine blockchain-powered climate-smart practices, safe and transparent transactions, and precision agriculture led by sensor data. Water-efficient irrigation, environmentally friendly pest control, and strong traceability systems are all part of this vision, which aims to strengthen the Indian agricultural sector's resilience. The study suggests a framework of customized policy recommendations centered on non-losable farming methods in recognition of the need for wider implementation. This framework, created especially for the Indian context, supports the promotion of agrotourism, improved education and extension services, accessible financial risk management tools, and the smart redistribution of subsidies. The research highlights the transformative potential of this approach by highlighting the many benefits of these practices, including the environmental (less water use, increased biodiversity, improved soil health, and carbon sequestration), social (better community resilience, food security, farmer income, preservation of cultural heritage, equitable trade), and economic (premium market access, lower input costs, and higher yields) gains. In the end, this research offers a strong plan of action for India to greatly advance SDG 2 and create a more sustainable future for all of its people. A food system that feeds people and the environment can be developed by carefully using organic farming methods and unprocessed plant resources in conjunction with successful legislative initiatives. 2024 IEEE. Creator An entity primarily responsible for making the resource Parameswaran S.; Sanghvi M.; Josephine Williams M.; Tandon A.; Rawat G.; Som A.; Monica L. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545026" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545026</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204435602&doi=10.1109%2FTQCEBT59414.2024.10545026&partnerID=40&md5=874f44a7cb00cb4463711230c5e4683f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204435602&doi=10.1109%2fTQCEBT59414.2024.10545026&partnerID=40&md5=874f44a7cb00cb4463711230c5e4683f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Parameswaran S., Christ University, School of Business and Management, India; Sanghvi M., Christ University, School of Business and Management, India; Josephine Williams M., Sri Krishna Arts & Science College, School of Commerce, India; Tandon A., Christ University, School of Business and Management, India; Rawat G., Christ University, School of Business and Management, India; Som A., Christ University, School of Business and Management, India; Monica L., Christ University, School of Business and Management, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Enhancing Workplace Efficiency with The Implementation of the Internet of Things to Advance Human Resource Management Practices Subject The topic of the resource Change Management; Data Privacy; Employee Engagement; Employee Satisfaction; Human Resource Management (HRM) Practices; Internet of Things (IoT); Organizational Dynamics; Qualitative and Quantitative Analysis; Real-time Monitoring; Security Concerns; Technological Innovation; Technology Integration; Workplace Culture; Workplace Efficiency Description An account of the resource Improving human resource management via the use of the Internet of Things (IoT) is the focus of this research. The primary objective is to enhance productivity in the workplace. The researchers utilized a mix of qualitative (describing) and quantitative (numbers-based) techniques to collect and analyses data. This research shows that key HR KPIs are positively affected by using IoT in HRM. Businesses utilizing IoT for real-time monitoring have better operations and more engaged employees. The study found that state-of-the-art technology, extensive training, and effective change management were needed to overcome people's security concerns and unwillingness to change. The Internet of Things may transform HRM and corporate operations, according to study. According to study, companies should invest in people-focused technologies and services. It emphasizes creating a workplace that embraces new technology while prioritizing security and privacy. In conclusion, the study's results may help organizations navigate HRM and the IoT's changing terrain. It suggests linking HR and technology to improve workplace flexibility and efficiency. 2024 IEEE. Creator An entity primarily responsible for making the resource Preeti; Patil S.; Lenka R.M.; Sandhya D.; Lourens M.; Chakravarthi M.K. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545155" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545155</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204485356&doi=10.1109%2FTQCEBT59414.2024.10545155&partnerID=40&md5=0e5634ad8c579f374b0cab434b1adf38" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204485356&doi=10.1109%2fTQCEBT59414.2024.10545155&partnerID=40&md5=0e5634ad8c579f374b0cab434b1adf38</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Preeti, Hr. Manager Frontier Group, India; Patil S., Indira School of Business Studies, Pune, India; Lenka R.M., Symbiosis International (Deemed) University, Symbiosis Institute of Management Studies, Pune, India; Sandhya D., School of Business and Management, Christ University (Yeshwantpur Campus), India; Lourens M., Durban University of Technology, Faculty of Management Sciences, South Africa; Chakravarthi M.K., VIT-AP University, School of Electronics Engineering, Amaravathi, 522237, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource 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 Critical Estimation of CO2Emission Towards Designing a Framework Using BlockChain Technology Subject The topic of the resource automobile industry; blockchain; Carbon footprint Description An account of the resource The automobile industry is a significant global contributor of carbon footprint this industry has impacted climate change, the research explores the existing methods of carbon footprint tracking and creates a framework by applying blockchain technology by connecting all the countries into one system as blockchain carries the capability to do due to its transparency, security and immutability the proposes of decentralised framework for real time tracking quarterly and implementing the necessary policies to mitigate the raising emission. The methodology encompasses of data analysis of using time series analysis globally and focusing certain parts of the world to show the emissions and creating a design that can help us in tracking the carbon footprint making all over the countries around to participate in suggesting to create a pathway for the future generations a better world as advance technologies come into the world for better ways to save the environment. 2024 IEEE. Creator An entity primarily responsible for making the resource Kaivalya G.S.; Subramanian P.; Acharjee P.B.; Rishab Gupta B. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545126" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545126</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204502414&doi=10.1109%2FTQCEBT59414.2024.10545126&partnerID=40&md5=c15a6f2affbdd76b1064e21395abefaf" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204502414&doi=10.1109%2fTQCEBT59414.2024.10545126&partnerID=40&md5=c15a6f2affbdd76b1064e21395abefaf</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Kaivalya G.S., Dept. of Business and Management, Christ University, India; Subramanian P., Dept. of Business and Management, Christ University, India; Acharjee P.B., Dept. of Computer Science, Christ University, India; Rishab Gupta B., Dept. of Science, 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 Artificial Intelligence (AI) in CRM (Customer Relationship Management): A Sentiment Analysis Approach Subject The topic of the resource AI (Artificial Intelligence); Analytics; Campaigns; CRM (Customer Relationship Management); Customer data; Marketing; Personalization Description An account of the resource The use of customer relationship management (CRM) in marketing is examined in this essay. It looks at how CRM makes it possible to use reviews, integrate AI, conduct marketing in real time, and conduct more regular marketing operations. CRM tactics are illustrated through case studies of businesses like Uber, T-Mobile, Amazon, Apple, and Apple. CRM offers centralized data, better marketing and sales, and better customer support. There is also a discussion of the ethical, private, security, adoption, and scalability challenges of AI in CRM. In general, CRM makes data-driven decisions and customer insights easier to achieve to increase growth, loyalty, and engagement. 2024 IEEE. Creator An entity primarily responsible for making the resource Acharjee P.B.; Salunkhe H.A.; Thorat S.; Dhote R.; Khnbhadiya P.; Manchanda A.; Sharma N. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545168" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545168</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204481946&doi=10.1109%2FTQCEBT59414.2024.10545168&partnerID=40&md5=584828c84fdb158b8959d095808cb736" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204481946&doi=10.1109%2fTQCEBT59414.2024.10545168&partnerID=40&md5=584828c84fdb158b8959d095808cb736</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Acharjee P.B., School of Business and Management, Christ University, Bangalore, India; Salunkhe H.A., School of Business and Management, Christ University, Bangalore, India; Thorat S., School of Business and Management, Christ University, Bangalore, India; Dhote R., School of Business and Management, Christ University, Bangalore, India; Khnbhadiya P., School of Business and Management, Christ University, Bangalore, India; Manchanda A., School of Business and Management, Christ University, Bangalore, India; Sharma N., School of Business and Management, 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 IOT-Enabled Supply Chain Management for Increased Efficiency Subject The topic of the resource Artificial intelligence; Big Data; IoT; Supply chain management; Technology; Traditional supply chain Description An account of the resource Deep learning methods have demonstrated potential Supply chain is a set or group of people as well as companies responsible for producing goods and getting it to their consumers. The producers of the raw materials are the first links in the chain, and the vehicle that delivers the finished goods to the client is the last. Lower costs and higher productivity are the benefits of an efficient supply network, which emphasizes the importance of management of supply chain. The internet of things, or IoT, is a network of mechanical and digital technology that can communicate with one another and send data without the need for human contact. Smart items were included into the conventional supply chain system to increase intelligence, automation potential, and intelligent decision-making. The existing supply chain system is offering previously unforeseen chances to increase efficiency and reduce cost. The aim and motive of our research is to analyze the methods of supply chain management where the main elements of IoT in management of supply chain will be highlighted. 2024 IEEE. Creator An entity primarily responsible for making the resource Nanjundan P.; James B.V.; George J.P.; Tiwari A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545070" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545070</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204479192&doi=10.1109%2FTQCEBT59414.2024.10545070&partnerID=40&md5=a96e756cb9fdf771f738697e811e2102" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204479192&doi=10.1109%2fTQCEBT59414.2024.10545070&partnerID=40&md5=a96e756cb9fdf771f738697e811e2102</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Nanjundan P., Christ (Deemed to Be University), Department of Data Science, India; James B.V., Christ (Deemed to Be University), Department of Commerce, India; George J.P., Christ (Deemed to Be University), Department of Data Science, India; Tiwari A., Christ (Deemed to Be University), Department of Commerce, 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 Factor Analysis for Portfolio Returns: Investigating How Macroeconomic Factors Impact the Performance of the equity Portfolio Subject The topic of the resource Economic Indicators; equity portfolio; regression analysis Description An account of the resource This paper investigates the complex relationship between macroeconomic factors and equity portfolio performance using regression analysis. In today's volatile financial environment, it emphasizes the importance of understanding how variables such as interest rates, inflation, money supply and GDP influence investment outcomes. Exact statistical techniques and historical data from a specific time period are used to uncover hidden factors affecting portfolio returns, with a particular focus on interest rates, inflation, money supply, and GDP. The goal of the research is to provide a comprehensive understanding of how these macroeconomic factors influence the equity investments. 2024 IEEE. Creator An entity primarily responsible for making the resource Nawani A.; Khanra P.; Dhalwani S.; Birari A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545071" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545071</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204482916&doi=10.1109%2FTQCEBT59414.2024.10545071&partnerID=40&md5=20d754bdb679f24830cf963b35397ab4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204482916&doi=10.1109%2fTQCEBT59414.2024.10545071&partnerID=40&md5=20d754bdb679f24830cf963b35397ab4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Nawani A., Christ University, India; Khanra P., Christ University, India; Dhalwani S., Christ University, India; Birari 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 Detection of Lung Cancer with a Deep Learning Hybrid Classifier Subject The topic of the resource Artificial Intelligence (AI); Computer-Aided Diagnosis (CAD); Convolution Neural Networks (CNN); Deep Learning; Feature Selection; Healthcare Technology; Hybrid Classification; Image Classification; Image Preprocessing; Lung Cancer; Medical Diagnosis; Medical Imaging; Medical Research; SVM Hybrid Classifier; VGG-16 Description An account of the resource This article presents a deep learning framework combining a convolutional neural network (CNN) and a support vector machine (SVM) for lung cancer diagnosis. The model uses data divided into six groups: 250 images in the training set and 150 images in the test set. The work includes preliminary data and development using the Keras image data generator, VGG-16 architecture, high-level rules, and SVM classifier training with labels and vectors. The model achieves 90% accuracy with 85% selection impact and 75% cross-validation flexibility using VGG-16 and SVM hybrid classifier. This study finally revealed the classification of the model by multi-class ROC curve analysis and confusion matrix. 2024 IEEE. Creator An entity primarily responsible for making the resource Kamatagi P.; Jacob L.; Balagangadhar K. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545082" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545082</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204466153&doi=10.1109%2FTQCEBT59414.2024.10545082&partnerID=40&md5=00b6d65b07f30f99a6cf60a04e8f16f4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204466153&doi=10.1109%2fTQCEBT59414.2024.10545082&partnerID=40&md5=00b6d65b07f30f99a6cf60a04e8f16f4</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Kamatagi P., Christ (Deemed to Be University), Department of Data Science, Lavasa, India; Jacob L., Christ (Deemed to Be University), Department of Data Science, Lavasa, India; Balagangadhar K., Christ (Deemed to Be University), Department of Data Science, Lavasa, India Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Novel CNN Approach for Condition Monitoring of Hydraulic Systems Subject The topic of the resource CNN; Deep Learning; Industry 4.0; Operations Management; Predictive Maintenance Description An account of the resource In the dynamic landscape of Industry 4.0, the ascendancy of predictive analytics methods is a pivotal paradigm shift. The persistent challenge of machine failures poses a substantial hurdle to the seamless functioning of factories, compelling the need for strategic solutions. Traditional reactive maintenance checks, though effective, fall short in the face of contemporary demands. Forward-thinking leaders recognize the significance of integrating data-driven techniques to not only minimize disruptions but also enhance overall operational productivity while mitigating redundant costs. The innovative model proposed herein harnesses the robust capabilities of Convolutional Neural Networks (CNN) for predictive analytics. Distinctively, it selectively incorporates the most influential variables linked to each of the four target conditions, optimizing the model's predictive precision. The methodology involves a meticulous process of variable extraction based on a predetermined threshold, seamlessly integrated with the CNN framework. This nuanced and refined approach epitomizes a forward-looking strategy, empowering the model to discern intricate failure patterns with a high degree of accuracy. 2024 IEEE. Creator An entity primarily responsible for making the resource Khan R.; Bhagat V.; Ganie A.H. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT59414.2024.10545150" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545150</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204501324&doi=10.1109%2FTQCEBT59414.2024.10545150&partnerID=40&md5=203d93fad9f6cc2f8de0909a5cea615b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204501324&doi=10.1109%2fTQCEBT59414.2024.10545150&partnerID=40&md5=203d93fad9f6cc2f8de0909a5cea615b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Khan R., Dept. of Data Science, Christ (Deemed to Be) University, Bangalore, India; Bhagat V., Dept. of Data Science, Christ (Deemed to Be) University, Bangalore, India; Ganie A.H., Dept. of Data Science, Christ (Deemed to Be) University, Bangalore, India