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Article: A unified approach of detecting misleading images via tracing its instances on web and analyzing its past context for the verification of multimedia content.

Varshney, Deepika / Vishwakarma, Dinesh Kumar

International journal of multimedia information retrieval

2022 Volume 11, Issue 3, Page(s) 445–459

Abstract: The verification of multimedia content over social media is one of the challenging and crucial issues in the current scenario and gaining prominence in an age where user-generated content and online social web-platforms are the leading sources in shaping ...

Abstract	The verification of multimedia content over social media is one of the challenging and crucial issues in the current scenario and gaining prominence in an age where user-generated content and online social web-platforms are the leading sources in shaping and propagating news stories. As these sources allow users to share their opinions without restriction, opportunistic users often post misleading/unreliable content on social media such as Twitter, Facebook, etc. At present, to lure users toward the news story, the text is often attached with some multimedia content (images/videos/audios). Verifying these contents to maintain the credibility and reliability of social media information is of paramount importance. Motivated by this, we proposed a generalized system that supports the automatic classification of images into credible or misleading. In this paper, we investigated machine learning-based as well as deep learning-based approaches utilized to verify misleading multimedia content, where the available image traces are used to identify the credibility of the content. The experiment is performed on the real-world dataset (Media-eval-2015 dataset) collected from Twitter. It also demonstrates the efficiency of our proposed approach and features using both Machine and Deep Learning Model (Bi-directional LSTM). The experiment result reveals that the Microsoft BING image search engine is quite effective in retrieving titles and performs better than our study's Google image search engine. It also shows that gathering clues from attached multimedia content (image) is more effective than detecting only posted content-based features.
Language	English
Publishing date	2022-07-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2649485-1
ISSN	2192-662X ; 2192-6611
ISSN (online)	2192-662X
ISSN	2192-6611
DOI	10.1007/s13735-022-00235-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Framework for detection of probable clues to predict misleading information proliferated during COVID-19 outbreak.

Varshney, Deepika / Vishwakarma, Dinesh Kumar

Neural computing & applications

2022 Volume 35, Issue 8, Page(s) 5999–6013

Abstract: Spreading of misleading information on social web platforms has fuelled huge panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. To identify the credibility of the posted claim, we have ... ...

Abstract	Spreading of misleading information on social web platforms has fuelled huge panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. To identify the credibility of the posted claim, we have analyzed possible evidence from the news articles in the google search results. This paper proposes an intelligent and expert strategy to gather important clues from the top 10 google search results related to the claim. The N-gram, Levenshtein Distance, and Word-Similarity-based features are used to identify the clues from the news article that can automatically warn users against spreading false news if no significant supportive clues are identified concerning that claim. The complete process is done in four steps, wherein the first step we build a query from the posted claim received in the form of text or text additive images which further goes as an input to the search query phase, where the top 10 google results are processed. In the third step, the important clues are extracted from titles of the top 10 news articles. Lastly, useful pieces of evidence are extracted from the content of each news article. All the useful clues with respect to N-gram, Levenshtein Distance, and Word Similarity are finally fed into the machine learning model for classification and to evaluate its performances. It has been observed that our proposed intelligent strategy gives promising experimental results and is quite effective in predicting misleading information. The proposed work provides practical implications for the policymakers and health practitioners that could be useful in protecting the world from misleading information proliferation during this pandemic.
Language	English
Publishing date	2022-11-13
Publishing country	England
Document type	Journal Article
ZDB-ID	1480526-1
ISSN	1433-3058 ; 0941-0643
ISSN (online)	1433-3058
ISSN	0941-0643
DOI	10.1007/s00521-022-07938-3
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Article: An automated multi-web platform voting framework to predict misleading information proliferated during COVID-19 outbreak using ensemble method.

Varshney, Deepika / Vishwakarma, Dinesh Kumar

Data & knowledge engineering

2022 Volume 143, Page(s) 102103

Abstract: The spreading of misleading information on social web platforms has fuelled massive panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. Previous studies mainly relied on a specific web ... ...

Abstract	The spreading of misleading information on social web platforms has fuelled massive panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. Previous studies mainly relied on a specific web platform to collect crucial evidence to detect fake content. The analysis identifies that retrieving clues from two or more different sources/web platforms gives more reliable prediction and confidence concerning a specific claim. This study proposed a novel multi-web platform voting framework that incorporates 4 sets of novel features: content, linguistic, similarity, and sentiments. The features have been gathered from each web-platforms to validate the news. To validate the fact/claim, a unique source platform is designed to collect relevant clues/headlines from two web platforms (YouTube, Google) based on specific queries and extracted features concerning each clue/headline. The proposed idea is to incorporate a unique platform to assist researchers in gathering relevant and vital evidence from diverse web platforms. After evaluation and validation, it has been identified that the built model is quite intelligent, gives promising results, and effectively predicts misleading information. The model correctly detected about 98% of the COVID misinformation on the constraint Covid-19 fake news dataset. Furthermore, it is observed that it is efficient to gather clues from multiple web platforms for more reliable predictions to validate the news. The suggested work depicts numerous practical applications for health policy-makers and practitioners that could be useful in safeguarding and implicating awareness among society from misleading information dissemination during this pandemic.
Language	English
Publishing date	2022-11-11
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1466273-5
ISSN	0169-023X
ISSN	0169-023X
DOI	10.1016/j.datak.2022.102103
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Article ; Online: SPATIAL MODELLING OF URBAN GROWTH AND URBAN INFLUENCE

Md. Julfikar ALI / Deepika VARSHNEY

Journal of Urban and Regional Analysis, Vol 4, Iss 2, Pp 129-

APPROACH OF REGIONAL DEVELOPMENT IN DEVELOPING ECONOMY (INDIA)

2022 Volume 148

Abstract: Urbanization and regional development are closely associated. Allocation of higher and lower order facilities and specialization of business influence urban growth which diffuses its benefits to the surrounding countryside. Subsequently, socio-economic ... ...

Abstract	Urbanization and regional development are closely associated. Allocation of higher and lower order facilities and specialization of business influence urban growth which diffuses its benefits to the surrounding countryside. Subsequently, socio-economic development of the region comes into being. The continuous increase of urban size can not be sustained rather declining growth will certainly set in long run. Optimum level of its growth depends on the capacity of an urban centre to provide required facilities to the people in fair manner. Hierarchical growth of urban centres in association with location of civic amenities induces regional development in hierarchical dimension which is the common problem in developing economy. Subsequently, few of the urban centres are having large number of facilities while others are lacking corresponding to their population size. Formulation of pragmatic planning model is the rescue of wiping out such problems. It is an attempt to analyze the hierarchical growth of urban centres associated with their functional potentiality and diffusion of urban developmental impulses to the surrounding rural part. Further, it proposes a model for developing economy like India to solve the problem of regional variations of development. Besides, it examines the adequacy and inadequacy of facilities in the urban centres and puts forward planning recommendations, so that a balanced regional development would be achieved by not leaving any rural part out of the zone of functional influence of urban centre.
Keywords	urban growth ; regional development ; urban influence ; functional weightage ; Cities. Urban geography ; GF125 ; Urban groups. The city. Urban sociology ; HT101-395
Subject code	910
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	University of Bucharest
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Toll-like receptor 2 (-196 to -174) del

Varshney, Deepika / Singh, Shoor Vir / Mohanty, Keshar Kunja / Kumar, Santosh / Varshney, Nitin / Sinha, Ekata / Barik, Sushanta Kumar

Frontiers in microbiology

2024 Volume 14, Page(s) 1305974

Abstract: Objectives: The objective of this study is to analyze the association between : Methods: The present case-control study included 101 pulmonary TB patients, 104 multidrug-resistant TB patients, 48 extremely drug-resistant TB patients, and 130 healthy ... ...

Abstract	Objectives: The objective of this study is to analyze the association between Methods: The present case-control study included 101 pulmonary TB patients, 104 multidrug-resistant TB patients, 48 extremely drug-resistant TB patients, and 130 healthy and unrelated controls residing in the same locality. The genotyping method for Results: The frequency of heterozygous ( Conclusion: The findings suggested that in the present population, the heterozygous (
Language	English
Publishing date	2024-01-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2023.1305974
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Article ; Online: Effect of hypobaric hypoxia on the fiber type transition of skeletal muscle: a synergistic therapy of exercise preconditioning with a nanocurcumin formulation.

Kushwaha, Asha D / Varshney, Rajeev / Saraswat, Deepika

Journal of physiology and biochemistry

2023 Volume 79, Issue 3, Page(s) 635–652

Abstract: Hypobaric hypoxia (HH) leads to various adverse effects on skeletal muscles, including atrophy and reduced oxidative work capacity. However, the effects of HH on muscle fatigue resistance and myofiber remodeling are largely unexplored. Therefore, the ... ...

Abstract	Hypobaric hypoxia (HH) leads to various adverse effects on skeletal muscles, including atrophy and reduced oxidative work capacity. However, the effects of HH on muscle fatigue resistance and myofiber remodeling are largely unexplored. Therefore, the present study aimed to explore the impact of HH on slow-oxidative fibers and to evaluate the ameliorative potential of exercise preconditioning and nanocurcumin formulation on muscle anti-fatigue ability. C2C12 cells (murine myoblasts) were used to assess the effect of hypoxia (0.5%, 24 h) with and without the nanocurcumin formulation (NCF) on myofiber phenotypic conversion. To further validate this hypothesis, male Sprague Dawley rats were exposed to a simulated HH (7620 m) for 7 days, along with NCF administration and/or exercise training. Both in vitro and in vivo studies revealed a significant reduction in slow-oxidative fibers (p < 0.01, 61% vs. normoxia control) under hypoxia. There was also a marked decrease in exhaustion time (p < 0.01, 65% vs. normoxia) in hypoxia control rats, indicating a reduced work capacity. Exercise preconditioning along with NCF supplementation significantly increased the slow-oxidative fiber proportion and exhaustion time while maintaining mitochondrial homeostasis. These findings suggest that HH leads to an increased transition of slow-oxidative fibers to fast glycolytic fibers and increased muscular fatigue. Administration of NCF in combination with exercise preconditioning restored this myofiber remodeling and improved muscle anti-fatigue ability.
MeSH term(s)	Rats ; Male ; Mice ; Animals ; Rats, Sprague-Dawley ; Muscle, Skeletal/metabolism ; Hypoxia/metabolism ; Oxidation-Reduction ; Muscle Fatigue
Language	English
Publishing date	2023-05-06
Publishing country	Spain
Document type	Journal Article
ZDB-ID	1325104-1
ISSN	1877-8755 ; 0034-9402 ; 1138-7548
ISSN (online)	1877-8755
ISSN	0034-9402 ; 1138-7548
DOI	10.1007/s13105-023-00965-1
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Article ; Online: Mitochondrial Ca

Kushwaha, Asha D / Kalra, Namita / Varshney, Rajeev / Saraswat, Deepika

IUBMB life

2023 Volume 75, Issue 8, Page(s) 673–687

Abstract: Severe hypoxia triggers apoptosis leads to myofibers loss and is attributable to impaired intracellular calcium ( ... ...

Abstract	Severe hypoxia triggers apoptosis leads to myofibers loss and is attributable to impaired intracellular calcium (iCa
MeSH term(s)	Humans ; Calcium/metabolism ; Tumor Suppressor Protein p53/genetics ; Tumor Suppressor Protein p53/metabolism ; Proteostasis ; Mitochondria/metabolism ; Myoblasts ; Apoptosis ; Hypoxia/metabolism ; Mitochondrial Membrane Transport Proteins/metabolism ; Membrane Potential, Mitochondrial
Chemical Substances	Calcium (SY7Q814VUP) ; Tumor Suppressor Protein p53 ; Mitochondrial Membrane Transport Proteins
Language	English
Publishing date	2023-03-31
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1492141-8
ISSN	1521-6551 ; 1521-6543
ISSN (online)	1521-6551
ISSN	1521-6543
DOI	10.1002/iub.2720
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Article ; Online: A unified approach for detection of Clickbait videos on YouTube using cognitive evidences.

Varshney, Deepika / Vishwakarma, Dinesh Kumar

Applied intelligence (Dordrecht, Netherlands)

2021 Volume 51, Issue 7, Page(s) 4214–4235

Abstract: Clickbait is one of the form of false content, purposely designed to attract the user's attention and make them curious to follow the link and read, view, or listen to the attached content. The teaser aim behind this is to exploit the curiosity gap by ... ...

Abstract	Clickbait is one of the form of false content, purposely designed to attract the user's attention and make them curious to follow the link and read, view, or listen to the attached content. The teaser aim behind this is to exploit the curiosity gap by giving information within the short statement. Still, the given statement is not sufficient enough to satisfy the curiosity without clicking through the linked content and lure the user to get into the respective page via playing with human psychology and degrades the user experience. To counter this problem, we develop a Clickbait Video Detector (CVD) scheme. The scheme leverages to learn three sets of latent features based on User Profiling, Video-Content, and Human Consensus, these are further used to retrieve cognitive evidence for the detection of clickbait videos on YouTube. The first step is to extract audio from the videos, which is further transformed to textual data, and later on, it is utilized for the extraction of video content-based features. Secondly, the comments are analyzed, and features are extracted based on human responses/reactions over the posted content. Lastly, user profile based features are extracted. Finally, all these features are fed into the classifier. The proposed method is tested on the publicly available fake video corpus [FVC], [FVC-2018] dataset, and a self-generated misleading video dataset [MVD]. The achieved result is compared with other state-of-the-art methods and demonstrates superior performance.
Language	English
Publishing date	2021-01-02
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1479519-X
ISSN	1573-7497 ; 0924-669X
ISSN (online)	1573-7497
ISSN	0924-669X
DOI	10.1007/s10489-020-02057-9
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Article ; Online: Investigating the Role of Classical Ayurveda-Based Incineration Process on the Synthesis of Zinc Oxide Based Jasada Bhasma Nanoparticles and Zn

Balkrishna, Acharya / Sharma, Deepika / Sharma, Rohit K / Bhattacharya, Kunal / Varshney, Anurag

ACS omega

2023 Volume 8, Issue 3, Page(s) 2942–2952

Abstract: Jasada bhasma (JB) is a zinc oxide-based Indian traditional Ayurveda-based herbo-metallic nanoparticle used for the treatment of zinc (Zn) deficiency and autoimmune and inflammatory disorders. JB is made by following the Ayurveda-based guidelines using ... ...

Abstract	Jasada bhasma (JB) is a zinc oxide-based Indian traditional Ayurveda-based herbo-metallic nanoparticle used for the treatment of zinc (Zn) deficiency and autoimmune and inflammatory disorders. JB is made by following the Ayurveda-based guidelines using zinc oxide (ZnO) as a raw material and going through 17 cycles of the high-temperature incineration and trituration process known as "Ma̅raṇa" in the presence of herbal decoctions prepared from the leaves of
Language	English
Publishing date	2023-01-09
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.2c05391
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Book ; Online: Multimodal Sentiment Analysis

Aggarwal, Aditi / Varshney, Deepika / Patel, Saurabh

Perceived vs Induced Sentiments

2023

Abstract: Social media has created a global network where people can easily access and exchange vast information. This information gives rise to a variety of opinions, reflecting both positive and negative viewpoints. GIFs stand out as a multimedia format offering ...

Abstract	Social media has created a global network where people can easily access and exchange vast information. This information gives rise to a variety of opinions, reflecting both positive and negative viewpoints. GIFs stand out as a multimedia format offering a visually engaging way for users to communicate. In this research, we propose a multimodal framework that integrates visual and textual features to predict the GIF sentiment. It also incorporates attributes including face emotion detection and OCR generated captions to capture the semantic aspects of the GIF. The developed classifier achieves an accuracy of 82.7% on Twitter GIFs, which is an improvement over state-of-the-art models. Moreover, we have based our research on the ReactionGIF dataset, analysing the variance in sentiment perceived by the author and sentiment induced in the reader
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning ; Computer Science - Social and Information Networks
Subject code	306
Publishing date	2023-12-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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