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1 – 3 of 3Rajshree Varma, Yugandhara Verma, Priya Vijayvargiya and Prathamesh P. Churi
The rapid advancement of technology in online communication and fingertip access to the Internet has resulted in the expedited dissemination of fake news to engage a global…
Abstract
Purpose
The rapid advancement of technology in online communication and fingertip access to the Internet has resulted in the expedited dissemination of fake news to engage a global audience at a low cost by news channels, freelance reporters and websites. Amid the coronavirus disease 2019 (COVID-19) pandemic, individuals are inflicted with these false and potentially harmful claims and stories, which may harm the vaccination process. Psychological studies reveal that the human ability to detect deception is only slightly better than chance; therefore, there is a growing need for serious consideration for developing automated strategies to combat fake news that traverses these platforms at an alarming rate. This paper systematically reviews the existing fake news detection technologies by exploring various machine learning and deep learning techniques pre- and post-pandemic, which has never been done before to the best of the authors’ knowledge.
Design/methodology/approach
The detailed literature review on fake news detection is divided into three major parts. The authors searched papers no later than 2017 on fake news detection approaches on deep learning and machine learning. The papers were initially searched through the Google scholar platform, and they have been scrutinized for quality. The authors kept “Scopus” and “Web of Science” as quality indexing parameters. All research gaps and available databases, data pre-processing, feature extraction techniques and evaluation methods for current fake news detection technologies have been explored, illustrating them using tables, charts and trees.
Findings
The paper is dissected into two approaches, namely machine learning and deep learning, to present a better understanding and a clear objective. Next, the authors present a viewpoint on which approach is better and future research trends, issues and challenges for researchers, given the relevance and urgency of a detailed and thorough analysis of existing models. This paper also delves into fake new detection during COVID-19, and it can be inferred that research and modeling are shifting toward the use of ensemble approaches.
Originality/value
The study also identifies several novel automated web-based approaches used by researchers to assess the validity of pandemic news that have proven to be successful, although currently reported accuracy has not yet reached consistent levels in the real world.
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Jayanth R Varma and Rahul Ghosh
“NTL suffered huge losses in its foreign exchange hedging activities as its highly complex leveraged structured products backfired badly in the wake of the Global Financial Crisis…
Abstract
“NTL suffered huge losses in its foreign exchange hedging activities as its highly complex leveraged structured products backfired badly in the wake of the Global Financial Crisis of 2007 and 2008. The CFO and the Treasury head have both been sacked, and Joshi, the new CFO, has embraced aggressive litigation as NTL's survival strategy to cope with the losses that threaten its solvency. In the meantime, NTL also faces tax investigations and whistleblower allegations of fraud, and it finds that the record-keeping of its derivative transactions was hopelessly incomplete and patchy. A complete reconstruction of the entire derivative transaction history is the only way to rebuild trust, and that task falls on Reddy, a seasoned derivatives expert brought in by the Board specifically for this purpose.
In this dire situation, Seth, the founder Chairman of NTL decides that NTL needs to put all this behind it and focus on rebuilding the business. The challenge for Seth, Joshi and Reddy is to go about doing this in an environment that offers very few rays of hope.”
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This paper aims to review the recent advances in processing and utilization of Madhuca longifolia flowers to address its potential as an industrial ingredient.
Abstract
Purpose
This paper aims to review the recent advances in processing and utilization of Madhuca longifolia flowers to address its potential as an industrial ingredient.
Design/methodology/approach
The paper analyzes the harvesting practices of flowers and recent works on the value addition.
Findings
Mahua flowers are rich source of natural sugars (glucose, fructose, sucrose, etc.) and hence are deliberately used for liquor production by tribal besides various food products, namely, Mahua ladoo, barfi, kheer, sweet puri and as grain staple. Mahuain medicine has been curing people since ages such as in rakhtpitta, diarrhoea and skin diseases and as aphrodisiac, galactagogue, carminative, antihelmenthic, antibacterial and antioxidant. Mahua candy, cake, ready to serve beverages, toffee, squash, ladoo, bars, etc. have been developed as value-added products. However, such a wonderful nature’s gift remains underused due to post harvest spoilage.
Practical implications
Improvement in storage facilities and processing of flowers after harvesting and drying will lead to enhanced availability of flowers for industrial purposes for food, feed and fodder. More value-added products can be prepared by the preparation of flower-juice concentrate, as well as efforts are made to produce powder from the flowers.
Originality/value
Post-harvest spoilage of Mahua flowers due to improper collection and handling practices, and filthy storage conditions is the major limitation of Mahua flowers to be used as a potential industrial ingredient. An improvement in collection, handling and pre-processing practices can diversify its use from liquor production to various value-added and functional food products at an industrial scale.
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