22
20
16481
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Title
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Articles
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Faculty Publications -Articles
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Factors influencing purchase decision and brand switching in the passenger car segment in Bengaluru
Subject
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Brand Switching; Passenger Cars; Purchase Intention. Purchase Decision
Description
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This study identifies and analyses the Product Attributes of Passenger Cars and the demographic factors that influence consumer Purchase Decision and Brand Switching in the Indian context, specific to the city of Bengaluru. It discusses the existing knowledge pertaining to Passenger Cars and a conceptual framework is developed based on the review of literature. The research identifies what drives the Purchase Decision and Brand Switching for the Indian consumers and analyses how it differs based on demographic variables such as age, gender and income. Based on the model thus created, the research seeks to segment the Indian Passenger Car consumers according to the significant demographic variables thus identified. A questionnaire was administered to 200 respondents of different age, income and gender groups within the city of Bangalore. The data was then analyzed using Factor Analysis, One-way ANOVA and frequency analysis in SPSS.It was found that Quality, Aftersales Service, Safety and Price are the major value factors effecting purchase decision of Indian Passenger Car consumer. Age and income also has a significant influence of Purchase Decision and Brand Switching. It was also found that purchase intention varies between different age and income groups. The research was conducted within the city of Bangalore alone which may not be generalized to the entire country. 2020 SERSC.
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Adishesha Sairam K.B.; Barkathunissa A.
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International Journal of Advanced Science and Technology, Vol-29, No. 5, pp. 2540-2554.
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Science and Engineering Research Support Society
Date
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2020-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084055001&partnerID=40&md5=6b5020aea923d13f5ebb686f64326ab0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084055001&partnerID=40&md5=6b5020aea923d13f5ebb686f64326ab0</a>
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ISSN: 20054238
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Online
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English
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Article
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Adishesha Sairam K.B., School of Business and Management, Christ (Deemed to be University), Bengaluru, India; Barkathunissa A., School of Business and Management, Christ (Deemed to be University), Bengaluru, India
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Title
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Faculty Publications
Conference Paper
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Adithiya, Dhanush; Jayabalan, Bhuvana; Beaulah Soundarabai, P.; Augustin, Peter
Title
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Evaluating Generalization and Robustness of U-Net Based Image Steganography
Date
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01-01-2025
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Proceedings - 2025 International Conference on Transformative Computing Technologies, ICTCT 2025;pp.178-183
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<a href="https://doi.org/10.1109/ICTCT69201.2025.00045" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICTCT69201.2025.00045</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037437357?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037437357?origin=resultslist</a>
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Adithiya D., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Jayabalan B., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Beaulah Soundarabai P., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India; Augustin P., Christ (Deemed to be) University, Department of Computer Science, Bangalore, India
Description
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This paper investigates the effectiveness and generalization ability of U-Net based image steganography models across multiple datasets, with comparisons to the classical Least Significant Bit (LSB) substitution method. Models were trained on STL-10, CIFAR-10, and Stanford Cars datasets and evaluated both in-distribution and on out-of-distribution internet images. Results show that the STL-10 model consistently achieved the best trade-off between imperceptibility and recovery quality, while the CIFAR-10 model failed to generalize due to its low resolution and limited diversity. Baseline experiments confirmed that LSB achieves extremely high PSNR and SSIM at low payloads, but suffers sharp increases in Bit Error Rate (BER) under higher payloads or even mild distortions such as JPEG compression and Gaussian noise. By contrast, the U-Net model provided more stable recovery and greater robustness, highlighting the advantages of learned feature embeddings over handcrafted substitution. These findings underscore the importance of dataset diversity and robustness testing in developing practical steganographic systems for real-world deployment. 2025 IEEE.
Subject
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Deep Learning; Generalization; Image Steganography; Robustness; U-Net
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Institute of Electrical and Electronics Engineers Inc.
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ISBN: 979-833159195-3;
Language
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English
Type
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Conference paper
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Restricted Access; Hardcopy may be available in the library
-
https://archives.christuniversity.in/files/original/e03ca3789f76de1daa58e0343bbd1ec0.pdf
e1e5a9cc76af0e84c2d809e422d9e3dd
Dublin Core
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Title
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Thesis
PhD
PhD Thesis
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Title
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Occupational exposure to cooking oil fumes biochemical cytogenetic and molecular signatures /
Subject
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Life Science_Zoology
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Aditi Chaudhary - 2071802
Publisher
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CHRIST (Deemed to be University)
Date
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2024-07-06
Language
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English
Type
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PhD
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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Title
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The Development of Structured Tele Based Medicine Concept Using Programmable System
Subject
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and telemedicine; Binomial law; distributed adaptation; videoconferencing
Description
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In the medical field, clinics and hospitals frequently use dispersed applications like telediagnosis. These apps must nevertheless provide information security in order to properly transit security measures like firewalls and proxies. The User Datagram Protocol (UDP) is often recommended for videoconferencing applications because of its low latency; nevertheless, security problems occur when UDP tries to pass through firewalls and proxies without a specified set of fixed ports. In order to overcome these obstacles, this study presents a revolutionary platform that uses Transmission Control Protocol (TCP) rather of UDP: VAGABOND, which stands for 'Video Adaptation framework, across security gateways, based on transcription,' Adaptation Proxies (APs) that are designed to accommodate user preferences, device variations, and dynamic changes in network capacity comprise VAGABOND. This platform's versatility at the user and network levels guarantees seamless operation in a range of scenarios. VAGABOND uses a binomial probability distribution to start making adaptation decisions. This distribution is formed from the retention of video packets inside a certain time period. VAGABOND gets beyond firewall and proxy constraints by using ordinary TCP ports (like 80 or 443) to provide videoconferencing data via TCP. But even though TCP is a dependable transport protocol, it can occasionally have latency and socket timeout problems. VAGABOND has clever adaptation techniques to deal with these problems and ensure smooth data transfer. 2024 IEEE.
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Adnan M.M.; Pant R.; Nirsanametla Y.; Fatima T.; Kumar M.; Kumar N.S.
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2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024, pp. 1285-1289.
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Institute of Electrical and Electronics Engineers Inc.
Date
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2024-01-01
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<a href="https://doi.org/10.1109/ICACITE60783.2024.10616820" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE60783.2024.10616820</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201810041&doi=10.1109%2FICACITE60783.2024.10616820&partnerID=40&md5=f441b0d62938c5220f28cb3af887856f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201810041&doi=10.1109%2fICACITE60783.2024.10616820&partnerID=40&md5=f441b0d62938c5220f28cb3af887856f</a>
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ISBN: 979-835036016-5
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Adnan M.M., The Islamic University, Najaf, Iraq; Pant R., Uttaranchal University, Uttaranchal Institute of Management, Uttarakhand, India; Nirsanametla Y., Chitkara University, Centre of Research Impact and Outreach, Punjab, Rajpura, 140401, India; Fatima T., Cmr Technical Campus, Department of Cse, Telangana, Hyderabad, India; Kumar M., Christ University, School of Business and Management, Bangalore, India; Kumar N.S., Srm Institute of Science & Technology, Department of Computer Science & Engineering, Chennai, Vadapalani, 26, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Title
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Front-End Security Analysis forCloud-Based Data Backup Application Using Cybersecurity Tools
Subject
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Cloud computing; Cyber security; Data backup application; Front-end security analysis
Description
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In this challenging, demanding, daunting, and competitive business world, the rise, and growth of cybercrimes are very high. With the proliferation of Cloud Computing techniques, usually in industrial arenas, business information and important clients data are stored and managed using cloud platforms. Application programs are developed to handle such valuable information assets of the organizations. Cloud backups are provided for these client data where security is the most concerning aspect. There are many vulnerabilities in the current scenario where intruders can cause havoc. Destruction of the product can happen by exploiting vulnerabilities that can put the company and the product in jeopardy. It may create a bad impression about the organization among the customers, competitors, and the public world. This paper shows the work done by a cyber security team whose main objective is to run vulnerability analysis and mitigate threats on an application that backs up the clients data to the cloud. Cyber Security is an important aspect in all types of businesses because it protects all categories of data such as fragile data, private information, intellectual property data, and other data including governmental and industrial information systems from theft and damage which concludes in huge financial loss and loss of client data. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Affan Ahamed S.M.K.N.U.; Mathew Wilson V.; Elappila M.; Malayath Jose S.
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Lecture Notes in Networks and Systems, Vol-660 LNNS, pp. 187-196.
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Springer Science and Business Media Deutschland GmbH
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-99-1203-2_16" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-1203-2_16</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164966132&doi=10.1007%2F978-981-99-1203-2_16&partnerID=40&md5=0c4440fd87177c619bbea935a58ab532" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164966132&doi=10.1007%2f978-981-99-1203-2_16&partnerID=40&md5=0c4440fd87177c619bbea935a58ab532</a>
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ISSN: 23673370; ISBN: 978-981991202-5
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Affan Ahamed S.M.K.N.U., CHRIST (Deemed to be University), Bengaluru, India; Mathew Wilson V., CHRIST (Deemed to be University), Bengaluru, India; Elappila M., CHRIST (Deemed to be University), Bengaluru, India; Malayath Jose S., University of Liverpool, Liverpool, L69 3BX, United Kingdom
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Title
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Articles
Article
Faculty Publications -Articles
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Title
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Damaged Relay Station: EEG Neurofeedback Training in Isolated Bilateral Paramedian Thalamic Infarct
Subject
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EEG neurofeedback training; neuropsychological rehabilitation; stroke; thalamic infarcts
Description
An account of the resource
Stroke is a major public health concern and leads to significant disability. Bilateral thalamic infarcts are rare and can result in severe and chronic cognitive and behavioral disturbances - apathy, personality change, executive dysfunctions, and anterograde amnesia. There is a paucity of literature on neuropsychological rehabilitation in patients with bilateral thalamic infarcts. Mr. M., a 51 years old, married male, a mechanical engineer, working as a supervisor was referred for neuropsychological assessment and rehabilitation with the diagnosis of bilateral paramedian thalamic infarct after seven months of stroke. A pre-post comprehensive neuropsychological assessment of his cognition, mood, and behavior was carried out. The patient received 40 sessions of EEG-Neurofeedback Training. The results showed significant improvement in sleep, motivation, and executive functions, however, there was no significant improvement in memory. The case represents the challenges in the memory rehabilitation of patients with bilateral thalamic lesions. 2024 Neurology India, Neurological Society of India.
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Afsar M.; Rajeswaran J.
Source
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Neurology India, Vol-72, No. 6, pp. 1277-1279.
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Wolters Kluwer Medknow Publications
Date
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2024-01-01
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<a href="https://doi.org/10.4103/neuroindia.NI_605_20" target="_blank" rel="noreferrer noopener">https://doi.org/10.4103/neuroindia.NI_605_20</a>
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ISSN: 283886; PubMed ID: 39691007; CODEN: NURYA
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Online
Language
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English
Type
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Article
Coverage
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Afsar M., Department of Psychology, School of Humanities and Social Sciences, Christ (Deemed to be University), Delhi NCR, India; Rajeswaran J., Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences, Karnataka, Bangalore, India
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Book Chapter
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Faculty Publications- Book Chapter
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Title
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Leveraging FinTech for the Advancement of Circular Economy
Subject
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challenges related to FinTech; circular economy; FinTech; FinTech in circular economy; Sustainable development
Description
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During the past six decades, there has been a lot of emphasis on increasing production and fulfilling the demands of the fast-growing population. As a result, there has been unprecedented utilization and depletion of natural resources and harm to the environment. It was rightly realized by government and policymakers that there is an indispensable need to align economic development with the environment. In other words, the world needs to pursue environmentally friendly economic development. In order to achieve sustainable development, the thought leaders devised a new approach called circular economy. The circular economy focuses on reusing and recycling materials to reduce the consumption of natural resources and minimize waste creation. In recent years, financial technology commonly known as FinTech has become a significant part of commercial activities across many industries. FinTech has benefited organizations and users in terms of cost and time saving with a high degree of reliability. This article outlines the ways in which FinTech supports the cause of a circular economy. It also explores the impediments in this path. 2024 Scrivener Publishing LLC.
Creator
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Agarwa R.; Fatima M.; Malhotra A.
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Fintech for Esg and the Circular Economy, pp. 49-62.
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wiley
Date
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2024-01-01
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<a href="https://doi.org/10.1002/9781394234035.ch4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/9781394234035.ch4</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214636296&doi=10.1002%2F9781394234035.ch4&partnerID=40&md5=7287674fcc50295ecdaf1739cf9bb4d4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214636296&doi=10.1002%2f9781394234035.ch4&partnerID=40&md5=7287674fcc50295ecdaf1739cf9bb4d4</a>
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ISBN: 978-139423403-5; 978-139423396-0
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Online
Language
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English
Type
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Book chapter
Coverage
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Agarwa R., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, India; Fatima M., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, India; Malhotra A., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, India
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Book Chapter
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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
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Understanding green economy
Description
An account of the resource
Resource efficiency, environmentally friendly consumption and production, and the green economy's contribution to sustainable development resource efficiency refer to the ways in which resources are used to deliver value to society and aims to reduce the amount of resources needed, as well as emissions and waste generated, per unit of product or service. Sustainable consumption and production aim to improve production processes and consumption practices to reduce resource consumption, waste generation, and emissions across the full life cycle of processes and products. A macroeconomic strategy for achieving sustainable economic growth is offered by the green economy, with a primary emphasis on investments, jobs, and skills. 2024, IGI Global. All rights reserved.
Creator
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Agarwal A.
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Green Economy and Renewable Energy Transitions for Sustainable Development, pp. 1-22.
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IGI Global
Date
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2024-01-01
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<a href="https://doi.org/10.4018/979-8-3693-1297-1.ch001" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-1297-1.ch001</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193961014&doi=10.4018%2F979-8-3693-1297-1.ch001&partnerID=40&md5=b4c9af367ea31c8e41db63960d866003" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193961014&doi=10.4018%2f979-8-3693-1297-1.ch001&partnerID=40&md5=b4c9af367ea31c8e41db63960d866003</a>
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ISBN: 979-836931298-8; 979-836931297-1
Format
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Online
Language
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English
Type
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Book chapter
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Agarwal A., Christ University, India
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Book Chapter
Book Chapter
Faculty Publications- Book Chapter
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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
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Role of social media influencers in fashion and clothing
Description
An account of the resource
This study provides an overview of the influence of social media influencers in the fashion and clothing industry. With the increasing presence of social media in people 's lives, individuals are easily influenced by what they see online, leading to the adoption of trends promoted by influencers. Influencers, who have established their personal brand and gained a substantial following, play a key role in shaping consumer preferences and driving sales. Social media platforms allow fashion brands to connect with their audience, democratizing fashion shows and enabling direct interaction. The rise of fast fashion and the influence of fashion influencers have contributed to the growth of the clothing industry. Businesses are now utilizing AI-powered analytics and dedicated platforms to enhance their influencer marketing strategies. In summary, social media influencers have a significant impact on consumer behavior, driv- ing sales and shaping trends in the fashion and clothing industry. 2023, IGI Global. All rights reserved.
Creator
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Agarwal A.; Jaiwant S.V.
Source
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Social Media and Online Consumer Decision Making in the Fashion Industry, pp. 203-229.
Publisher
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IGI Global
Date
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2023-01-01
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<a href="https://doi.org/10.4018/978-1-6684-8753-2.ch012" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-6684-8753-2.ch012</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169521784&doi=10.4018%2F978-1-6684-8753-2.ch012&partnerID=40&md5=8341bc5ea4981344eb69462faac040b4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169521784&doi=10.4018%2f978-1-6684-8753-2.ch012&partnerID=40&md5=8341bc5ea4981344eb69462faac040b4</a>
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ISBN: 978-166848755-6; 978-166848753-2
Format
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Online
Language
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English
Type
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Book chapter
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Agarwal A., CHRIST University (Deemed), India; Jaiwant S.V., CHRIST University (Deemed), India
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Dublin Core
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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
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Food wastage and consumerism in circular economy: a review and research directions
Subject
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Bibliometric analysis; Circular economy; Consumerism; Food waste; Network analysis; Systematic review
Description
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Purpose: Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerisms impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability. Design/methodology/approach: A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023. Findings: The findings reveal four prominent factors behavioural, environmental, socioeconomic and technological in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways. Research limitations/implications: Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour. Originality/value: Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends. 2024, Emerald Publishing Limited.
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Agarwal A.; Srivastava S.; Gupta A.; Singh G.
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British Food Journal, Vol-126, No. 6, pp. 2561-2587.
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Emerald Publishing
Date
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2024-01-01
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<a href="https://doi.org/10.1108/BFJ-04-2023-0272" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/BFJ-04-2023-0272</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191252618&doi=10.1108%2FBFJ-04-2023-0272&partnerID=40&md5=e9cd3b9838b17263128b0488e391e55a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191252618&doi=10.1108%2fBFJ-04-2023-0272&partnerID=40&md5=e9cd3b9838b17263128b0488e391e55a</a>
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ISSN: 0007070X
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Online
Language
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English
Type
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Review
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Agarwal A., School of Management, BML Munjal University, Gurgaon, India; Srivastava S., Operations and Decision Sciences, Christ University, Bangalore, India; Gupta A., Marketing Area, Indian Institute of Foreign Trade (IIFT), New Delhi, India; Singh G., The University of the South Pacific, Suva, Fiji
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Articles
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Dublin Core
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Title
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Siamese-Based Architecture for Cross-Lingual Plagiarism Detection in English-Hindi Language Pairs
Subject
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Bi-LSTM; CNN; cross-lingual plagiarism detection; deep learning; Siamese architecture
Description
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The cross-lingual plagiarism detection (CLPD) is a challenging problem in natural language processing. Cross-lingual plagiarism is when a text is translated from any other language and used as it is without proper acknowledgment. Most of the existing methods provide good results for monolingual plagiarism detection, whereas the performances of existing methods for the CLPD are very limited. The reason for this is that it is difficult to represent the text from two different languages in a common semantic space. In this article, a novel Siamese architecture-based model is proposed to detect the cross-lingual plagiarism in English-Hindi language pairs. The proposed model combines the convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM) network to learn the semantic similarity among the cross-lingual sentences for the English-Hindi language pairs. In the proposed model, the CNN model learns the local context of words, whereas the Bi-LSTM model learns the global context of sentences in forward and backward directions. The performances of the proposed models are evaluated on the benchmark data set, that is, Microsoft paraphrase corpus, which is converted in the English-Hindi language pairs. The proposed model outperforms other models giving 67%, 72%, and 67% weighted average precision, recall, and F1-measure scores. The experimental results show the effectiveness of the proposed models over the baseline models because the proposed model is very efficient in representing the cross-lingual text very efficiently. Copyright 2023, Mary Ann Liebert, Inc., publishers 2023.
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Agarwal B.; Gupta M.K.; Sharma H.; Poonia R.C.
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Big Data, Vol-11, No. 1, pp. 48-58.
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Mary Ann Liebert Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1089/big.2020.0243" target="_blank" rel="noreferrer noopener">https://doi.org/10.1089/big.2020.0243</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148113862&doi=10.1089%2Fbig.2020.0243&partnerID=40&md5=1c6e40380eddb57ebf9c9fc74910f569" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148113862&doi=10.1089%2fbig.2020.0243&partnerID=40&md5=1c6e40380eddb57ebf9c9fc74910f569</a>
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ISSN: 21676461; PubMed ID: 36260373
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Online
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English
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Article
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Agarwal B., Department of Computer Science and Engineering, Indian Institute of Information Technology Kota (IIIT Kota), Rajasthan, Jaipur, India; Gupta M.K., Department of Computer Science and Engineering, Swami Keshvanand Institute of Technology, Management and Gramothan, Rajasthan, Jaipur, India; Sharma H., Department of Computer Science and Engineering, Rajasthan Technical University, Rajasthan, Kota, India; Poonia R.C., Department of Computer Science, Christ (Deemed to Be University), Karnataka, Bangalore, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Title
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A Framework for Dress Code Monitoring System using Transfer Learning from Pre-Trained YOLOv4 Model
Subject
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CNN; Object Detection; Transfer Learning; YOLOv4
Description
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Maintaining a proper dress code in organizations or any environment is very important. It not only imbibes a sense of discipline but also reflects the personality and qualities of people as individuals. To follow this practice, some organizations like educational institutions and a few corporations have made it mandatory for the personnel to maintain proper attire as per their regulations. Manual checks are performed to adhere to the organizations' regulations which becomes tedious and erroneous most of the times. Having an automated system not only saves time but also there is very little scope of mistakes and errors. Taking this into context, the main aim and idea behind the project is to propose a model for detecting the dress code in such workplaces and educational institutions where the attire needs to be regularly monitored. The model detects Business Formals (Blazer, Shirt & Pants) worn by the personnel, for which CNN has been considered, along with YOLOv4, for performing the detection, due to its nature of giving the highest accuracy in comparison to the other object-detection models. Providing the Mean Average Precision of around 81%, it becomes evident that the model performs quite well in performing the detections. 2023 IEEE.
Creator
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Agarwal D.; Gupta P.; Eapen N.G.
Source
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International Conference on Emerging Trends in Engineering and Technology, ICETET, Vol-2023-April
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IEEE Computer Society
Date
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2023-01-01
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<a href="https://doi.org/10.1109/ICETET-SIP58143.2023.10151460" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICETET-SIP58143.2023.10151460</a>
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ISSN: 21570477; ISBN: 979-835034842-2
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Online
Language
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English
Type
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Conference paper
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Agarwal D., CHRIST (Deemed to Be University), Department of Data Science, Lavasa, India; Gupta P., CHRIST (Deemed to Be University), Department of Data Science, Lavasa, India; Eapen N.G., CHRIST (Deemed to Be University), Department of Data Science, Lavasa, India
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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
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Conference Papers
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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
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The effect of airline service quality on customer satisfaction and loyalty in India
Subject
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Aviation industry; Behavioral intention; Customer satisfaction; Marketing strategies; Quality of service
Description
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Indian Aviation Industry has been one of the world's fastest-growing aviation industries with private airlines representing more than 75 percent of the domestic aviation industry. With an 18 percent compound annual growth rate (CAGR) and 454 airports and airstrips in place in the country, 16 of which are designated as international airports, it has been stated that by 2011 the aviation sector will be witnessing a revival. In 2009, with traffic movement rising and revenues rising by nearly US$ 21.4 million, India's Airports Authority appears expected to earn better margins in 2009-10, as indicated by the Civil Aviation Ministry's latest estimates. The most crucial step in identifying and providing high-quality service is to understand exactly what customers expect. Quality of service is one of the best models for measuring customer expectations and perceptions. A company's performance results in customer satisfaction with a product or service. Passenger satisfaction is important to customer sovereignty. Customers can be loyal without being highly satisfied and being highly satisfied and yet not being loyal. Companies are required to gain a better understanding of the online environment relationship between satisfaction and behavioural intention, and to assign online marketing strategies between satisfaction initiatives and behavioural intention programme. In addition, the findings of this research will assist airline managers to better serve their customers, track and improve quality of service and achieve the highest level of satisfaction for their passengers. 2020 Elsevier Ltd. All rights reserved.
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Agarwal I.; Gowda K.R.
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Materials Today: Proceedings, Vol-37, No. Part 2, pp. 1341-1348.
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Elsevier Ltd
Date
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2020-01-01
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<a href="https://doi.org/10.1016/j.matpr.2020.06.557" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.matpr.2020.06.557</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102471390&doi=10.1016%2Fj.matpr.2020.06.557&partnerID=40&md5=df0506f2be860e21d4c70ab25314d9b4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102471390&doi=10.1016%2fj.matpr.2020.06.557&partnerID=40&md5=df0506f2be860e21d4c70ab25314d9b4</a>
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ISSN: 22147853
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Agarwal I., Institute of Management, CHRIST Deemed-to-be University, Bengaluru, Karnataka, 560029, India; Gowda K.R., School of Business and Management, CHRIST Deemed-to-be University, Bengaluru, Karnataka, 560029, India
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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
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Conference Papers
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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
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Performance Analysis of YOLOv7 and YOLOv8 Models for Drone Detection
Subject
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CNN (convoluted neural network); Computer Vision; Drone Detection; UAS (Unmanned Aerial System); unmanned aerial vehicles (UAVs); Yolo (You Only Look Once); Yolov7; Yolov8
Description
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Drone detection techniques are used to detect unmanned aerial systems (UAS) also commonly known as drones. A rapid increase in these drones has limited the airspace safety and so the research for drone detection has emerged. This study compares between the two widely used deep-learning models, previously used YOLOv7 and the latest YOLOv8. The overall finding of this study suggests that the YOLOv8 deep-learning model appears to be more promising and may make valuable contributions on their own. We got the result that for 10 epochs YOLOv8 gave 50.16% accuracy while YOLOv7 gave 48.16% accuracy making YOLOv8 more promising for the task. As a practical application for future work, we intend to deploy YOLOv8 on edge devices to achieve real-time drone detection in critical security applications. 2023 IEEE.
Creator
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Agarwal K.; Ashik Sanyo M.S.; Bakshi S.; Vinay M.; Jayapriya J.; Deepa S.
Source
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2023 International Conference on Network, Multimedia and Information Technology, NMITCON 2023
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/NMITCON58196.2023.10276343" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/NMITCON58196.2023.10276343</a>
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ISBN: 979-835030082-6
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Online
Language
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English
Type
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Conference paper
Coverage
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Agarwal K., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Ashik Sanyo M.S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Bakshi S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Vinay M., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Jayapriya J., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Deepa S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India
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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
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Title
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Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy
Subject
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classifier; Decision Tree; Gaussian Naive Bayes; Logistic Regression; Machine Learning; Natural Language Processing; Random Forest; Sentiment Analysis; Support Vector Machines; Twitter; XGBoost
Description
An account of the resource
With the exponential growth of social networking sites, people are using these platforms to express their sentiments on everyday issues. Collection and analysis of people's reactions to purchases of products, public services, etc. are important from a marketing and innovation perspective. Sentiment analysis also called opinion mining or emotion extraction is the classification of emotions in text. This technique has been widely used over the years to determine sentiment within given text data. Twitter is a social media platform primarily used by people to express their feelings about specific events. In this paper, collected tweets about National Education Policy which has been a hot topic for a while; and analyzed them using various machine learning algorithms such as Random Forest classifier, Logistic Regression, SVM, Decision Tree, XGBoost, Naive Bayes. This study shows that the Decision tree algorithm is performing best, compare to all the other algorithms. 2023 IEEE.
Creator
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Agarwal K.; Deepa S.; Sivabalan R.V.; Balakrishnan C.
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Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023, pp. 862-870.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
Identifier
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<a href="https://doi.org/10.1109/IITCEE57236.2023.10091034" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IITCEE57236.2023.10091034</a>
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ISBN: 978-166546263-1
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Online
Language
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English
Type
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Conference paper
Coverage
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Agarwal K., Christ University, Department Computer Science, Bangalore, India; Deepa S., Christ University, Department Computer Science, Bangalore, India; Sivabalan R.V., Christ University, Department Computer Science, Bangalore, India; Balakrishnan C., Christ University, Department Computer Science, Bangalore, India
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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
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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
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Genetic Algorithm-Based Optimization ofUNet forBreast Cancer Classification: A Lightweight andEfficient Approach forIoT Devices
Subject
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Compression & Acceleration; Deep Learning; Genetic Algorithm; Semantic Segmentation; UNet
Description
An account of the resource
IoT devices are widely used in medical domain for detection of high blood sugar and life threatening disease such as cancer. Breast cancer is one of the most challenging type of cancer which not only affects women but in some cases men also. Deep learning is one of the widely used technology which provides efficient classification of cancerous lumps but it is not useful for IoT devices as the devices lack resources such as storage and computation. For the suitability in IoT devices, in this work, we are compressing UNet, the popular semantic segmentation technique, for the pixel-wise classification of breast cancer. For compressing the deep learning model, we use genetic algorithm which removes the unwanted layers and hidden units in the existing UNet model. We have evaluated the proposed model and compared with the existing model(s) and found that the proposed compression technique suppresses the storage requirement to 77.1%. Additionally, it also improves the inference time by 3.82without compromising the accuracy. We conclude that the primary reason of inference time improvement is the requirement of less number of weight and bias by the proposed model. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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Agarwal M.; Dwivedi A.K.; Gupta S.K.; Najafzadeh M.; Jindal M.
Source
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Communications in Computer and Information Science, Vol-2054 CCIS, pp. 386-396.
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Springer Science and Business Media Deutschland GmbH
Date
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2024-01-01
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<a href="https://doi.org/10.1007/978-3-031-56703-2_31" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-56703-2_31</a>
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ISSN: 18650929; ISBN: 978-303156702-5
Format
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Online
Language
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English
Type
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Conference paper
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The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Agarwal M., Bennett University, Greater Noida, India; Dwivedi A.K., Bennett University, Greater Noida, India; Gupta S.K., Bennett University, Greater Noida, India; Najafzadeh M., Department of Water Engineering, Graduate University of Advanced Technology, Kerman, Iran; Jindal M., CHRIST (Deemed to be University), Bangalore, India
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Title
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Book Chapter
Book Chapter
Faculty Publications- Book Chapter
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Women empowerment in India: Are we on the right track?
Description
An account of the resource
Information and communication technologies (ICTs) have attracted the continued attention of national governments, international bodies, private organizations, civil societies, and NGOs. ICT has the potential to act as an influential method for promoting gender equality and social-economic and political empowerment of women. The chapter describes a number of ICT-backed initiatives in different countries targeted towards various concerns of women such as health, education, violence, governance, income, etc. It demonstrates the ability of ICT for empowering women especially those belonging to the marginalized group. This chapter examines the key challenges including technical, social, and economic to the usage of ICT for women's development as well as suggests initiatives for initiatives for national governments, policy makers, and organizations focusing on the issue of women empowerment. 2023, IGI Global.
Creator
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Agarwal M.; Nagariya R.; Patel B.S.; Sharma P.; Baral M.M.; Mukherjee S.
Source
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ICT as a Driver of Women's Social and Economic Empowerment, pp. 244-263.
Publisher
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IGI Global
Date
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2023-01-01
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<a href="https://doi.org/10.4018/978-1-6684-6118-1.ch015" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-6684-6118-1.ch015</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162867623&doi=10.4018%2F978-1-6684-6118-1.ch015&partnerID=40&md5=b7c7c024368e603686418129860ebe9c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162867623&doi=10.4018%2f978-1-6684-6118-1.ch015&partnerID=40&md5=b7c7c024368e603686418129860ebe9c</a>
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ISBN: 978-166846119-8; 1668461188; 978-166846118-1
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Online
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English
Type
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Book chapter
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Agarwal M., Jaipuria Institute of Management, Indore, India; Nagariya R., CHRIST University (Deemed), Bangalore, India; Patel B.S., Thiagarajar School of Management, India; Sharma P., Birla Institute of Technology Mesra, Jaipur, India; Baral M.M., GITAM School of Business, GITAM University, Visakhapatnam, India; Mukherjee S., GITAM School of Business, GITAM University, Visakhapatnam, India
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Dublin Core
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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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
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An Efficient andOptimized Convolution Neural Network forBrain Tumour Detection
Subject
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Acceleration; Brain Tumour; CNN; Compression
Description
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Brain tumour is a life threatening disease and can affect children and adults. This study focuses on classifying MRI scan images of brain into one of 4 classes namely: glioma tumour, meningioma tumour, pituitary tumour and normal brain. Person affected with brain tumours will need treatments such as surgery, radiation therapy or chemotherapy. Pretrained Convolution Neural Networks such as VGG19, MobileNet, and AlexNet which have been widely used for image classification using transfer learning. However due to huge storage space requirements these are not effectively deployed on edge devices for creation of robotic devices. Hence a compressed version of these models have been created using Genetic Algorithm algorithm which occupies nearly 3040% of space and also a reduced inference time which is less by around 50% of original model. The accuracy provided by VGG19, AlexNet, MobileNet and Proposed CNN before compression was 92.18%, 89.45%, 93.75% and 96.85% respectively. Similarly the accuracy after compression for VGG19, AlexNet, MobileNet and Proposed CNN was 91.34%, 88.92%, 94.40% and 95.29%. 2023, Springer Nature Switzerland AG.
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Agarwal M.; Sharma L.K.; Gupta S.K.; Garg D.; Jindal M.
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Communications in Computer and Information Science, Vol-1781 CCIS, pp. 459-474.
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Springer Science and Business Media Deutschland GmbH
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-3-031-35641-4_38" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-35641-4_38</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169045456&doi=10.1007%2F978-3-031-35641-4_38&partnerID=40&md5=0b4ea2dae63e22522d25f9a277f455e0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169045456&doi=10.1007%2f978-3-031-35641-4_38&partnerID=40&md5=0b4ea2dae63e22522d25f9a277f455e0</a>
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ISSN: 18650929; ISBN: 978-303135640-7
Format
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Online
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English
Type
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Conference paper
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Agarwal M., Bennett University, Greater Noida, 201310, India; Sharma L.K., Bennett University, Greater Noida, 201310, India; Gupta S.K., Bennett University, Greater Noida, 201310, India; Garg D., Bennett University, Greater Noida, 201310, India; Jindal M., Christ Deemed to be University Delhi NCR, Mariam Nagar, Ghaziabad, 201003, India
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Dublin Core
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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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/.
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Whale Optimization Based Approach toCompress andFasten CNN forCrop Disease andSpecies Identification
Subject
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CNN; Cnn compression; Crop disease; Deep neural network
Description
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In recent years deep learning and machine learning have been widely researched for image based recognition. This research proposes a simplified CNN with 3 layers for classification from 39 classes of crops and their diseases. It also evaluates the performance of pre-trained models such as VGG16 and ResNet50 using transfer learning. Similarly traditional Machine Learning algorithms have been trained and tested on the same dataset. The best accuracy using proposed CNN was 87.67% whereas VGG16 gave best accuracy of 91.51% among Convolution Neural Network models. Similarly Random Forest machine learning method gave best accuracy of 93.02% among Machine Learning models. Since the pre-trained models are having huge size hence in order to deploy these solutions on tiny edge devices compression is done using Whale Optimization. The maximum compesssion was obtained with VGG16 of 88.19% without loss in any performance. It also helped betterment of inference time of 44.13% for proposed CNN, 56.76% for VGG16 and 63.23% for ResNet50. 2023, Springer Nature Switzerland AG.
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Agarwal M.; Singh S.P.; Kaliyar R.; Gupta S.K.; Garg D.; Jindal M.
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Communications in Computer and Information Science, Vol-1781 CCIS, pp. 309-320.
Publisher
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Springer Science and Business Media Deutschland GmbH
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-3-031-35641-4_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-35641-4_25</a>
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Restricted Access
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ISSN: 18650929; ISBN: 978-303135640-7
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Agarwal M., Bennett University, Gr. Noida, 201310, India; Singh S.P., Bennett University, Gr. Noida, 201310, India; Kaliyar R., Bennett University, Gr. Noida, 201310, India; Gupta S.K., Bennett University, Gr. Noida, 201310, India; Garg D., Bennett University, Gr. Noida, 201310, India; Jindal M., Christ Deemed to be University Delhi NCR, Mariam Nagar, Ghaziabad, 201003, India
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Articles
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Faculty Publications -Articles
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Indian Social Stock Exchange as a Funding Avenue for Social Enterprises
Subject
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for-profit enterprises; non-profit enterprises; social enterprises; social stock exchange
Description
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Purpose: The growth of Indian social enterprises faces a significant obstacle, which is a lack of access to finance. The social stock exchange was recently launched to cater to this problem. This study explored the financial challenges the selected social enterprises faced in India and analyzed the performance of small and medium enterprises platforms. Methodology: Three variables were subjected to descriptive analysis: migration to the principal board, funds generated, and listings by small and medium-sized enterprises. Furthermore, market volatility was evaluated using the generalized autoregressive conditional heteroskedasticity (GARCH) model. To explore financial constraints, primary research entailed conducting in-depth interviews utilizing the case study technique with both for-profit and non-profit social companies. Findings: The findings from the study concluded that IPO financing significantly supported Indian SMEs. Additionally, social enterprises face significant financing challenges related to affordability, availability, and regulation. Social stock exchange presents a promising solution to these constraints. Practical Implications: The study has recommended defining social enterprises legally will help in strengthening the operating framework of a social stock exchange. The study emphasized the important role of finance in the viability of social enterprises by highlighting financial challenges. The findings provided useful information for various stakeholders to bridge the funding gap, thereby promoting the potential advantages of the social stock exchange platforms. Originality: The study addressed the research gap with an examination of small and medium enterprise platforms and the influence of the social stock exchange on social enterprise financing in India. Primary data from both for-profit and non-profit social entrepreneurs added a disaggregated dimension. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved.
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Agarwal N.; Patavardhan R.
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Prabandhan: Indian Journal of Management, Vol-17, No. 7, pp. 42-56.
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Associated Management Consultants Pvt. Ltd.
Date
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2024-01-01
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<a href="https://doi.org/10.17010/pijom/2024/v17i7/173636" target="_blank" rel="noreferrer noopener">https://doi.org/10.17010/pijom/2024/v17i7/173636</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201412089&doi=10.17010%2Fpijom%2F2024%2Fv17i7%2F173636&partnerID=40&md5=b2c14aeab618763d778952c021f5eeae" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201412089&doi=10.17010%2fpijom%2f2024%2fv17i7%2f173636&partnerID=40&md5=b2c14aeab618763d778952c021f5eeae</a>
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ISSN: 9752854
Format
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Online
Language
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English
Type
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Article
Coverage
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Agarwal N., Department of Economics, Christ University, Bannerghatta Road Campus, Bannerghatta Main Road, Pai Layout, Hulimavu, Karnataka, Bengaluru, 560 076, India; Patavardhan R., Department of Economics, Christ University, Bannerghatta Road Campus, Bannerghatta Main Road, Pai Layout, Hulimavu, Karnataka, Bengaluru, 560 076, India