30 research outputs found
Homology Modeling and Docking Studies on Lukocidin Lukd in Staphylococcus Aureus.
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
FEMINISM IN BHARATI MUKHERJEE'S NOVEL JASMINE: A STRUGGLE FOR EMANCIPATION OF SELF
No full textFeminism is a movement that supports women across a wide range of concerns, including their sense of self, independence, and responsibility throughout fields particularly politics, economics, and family life. Feminism's rapid expansion around the world helped bring India's feminists into the limelight. Women nowadays are no longer passive observers; they are actively pursuing justice, freedom, and equality. Third-world feminist author Bharathi Mukherjee is preoccupied with the concerns and issues facing women in South Asia, especially India. This article analyze female protagonist, Jasmine, her struggle for independence, innate femininity, and defiance of patriarchy and the many ways in which she undergoes metamorphosis and ultimately resurrection as an undocumented immigrant in America
A Dataset for Troll Classification of Tamil Memes
No full textSocial media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people. This exchange is not free from offensive, trolling or malicious contents targeting users or communities. One way of trolling is by making memes, which in most cases combines an image with a concept or catchphrase. The challenge of dealing with memes is that they are region-specific and their meaning is often obscured in humour or sarcasm. To facilitate the computational modelling of trolling in the memes for Indian languages, we created a meme dataset for Tamil (TamilMemes). We annotated and released the dataset containing suspected trolls and not-troll memes. In this paper, we use the a image classification to address the difficulties involved in the classification of troll memes with the existing methods. We found that the identification of a troll meme with such an image classifier is not feasible which has been corroborated with precision, recall and F1-score.
The internet has facilitated its user-base with a platform to communicate and express their views without any censorship. On the other hand, this freedom of expression or free speech can be abused by its user or a troll to demean an individual or a group. Demeaning people based on their gender, sexual orientation, religious believes or any other characteristics –trolling– could cause great distress in the online community. Hence, the content posted by a troll needs to be identified and dealt with before causing any more damage. Amongst all the forms of troll content, memes are most prevalent due to their popularity and ability to propagate across cultures. A troll uses a meme to demean, attack or offend its targetted audience. In this shared task, we provide a resource (TamilMemes) that could be used to train a system capable of identifying a troll meme in the Tamil language. In our TamilMemes dataset, each meme has been categorized into either a “troll” or a “not_troll” class. Along with the meme images, we also provided the Latin transcripted text from memes. We received 10 system submissions from the participants which were evaluated using the weighted average F1-score. The system with the weighted average F1-score of 0.55 secured the first rank.
@inproceedings{suryawanshi-etal-2020-tamil-meme,
title = "A Dataset for Troll Classification of {Tamil} Memes",
author = "Suryawanshi, Shardul and
Chakravarthi, Bharathi Raja and
Verma, Pranav and
Arcan, Mihael and
McCrae, John P and
Buitelaar, Paul",
booktitle = "Proceedings of the 5th Workshop on Indian Language Data Resource and Evaluation (WILDRE-5)",
month = May,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)"
}
@inproceedings{suryawanshi-chakravarthi-2021-findings,
title = "Findings of the Shared Task on Troll Meme Classification in {T}amil",
author = "Suryawanshi, Shardul and
Chakravarthi, Bharathi Raja",
booktitle = "Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages",
month = apr,
year = "2021",
address = "Kyiv",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.dravidianlangtech-1.16",
pages = "126--132",
abstract = "The internet has facilitated its user-base with a platform to communicate and express their views without any censorship. On the other hand, this freedom of expression or free speech can be abused by its user or a troll to demean an individual or a group. Demeaning people based on their gender, sexual orientation, religious believes or any other characteristics {--}trolling{--} could cause great distress in the online community. Hence, the content posted by a troll needs to be identified and dealt with before causing any more damage. Amongst all the forms of troll content, memes are most prevalent due to their popularity and ability to propagate across cultures. A troll uses a meme to demean, attack or offend its targetted audience. In this shared task, we provide a resource (TamilMemes) that could be used to train a system capable of identifying a troll meme in the Tamil language. In our TamilMemes dataset, each meme has been categorized into either a {``}troll{''} or a {``}not{\_}troll{''} class. Along with the meme images, we also provided the Latin transcripted text from memes. We received 10 system submissions from the participants which were evaluated using the weighted average F1-score. The system with the weighted average F1-score of 0.55 secured the first rank.",
Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source
No full textCorrelation between 3D surface roughness and characteristic features extracted from laser speckle pattern was done using an inexpensive laser pointer and a digital single lens reflex (DSLR) camera in previous research work. There had been no comparison work done between the experimental setup which uses a laser pointer, which has a diode laser as the laser source, and the experimental setup, which uses a He-Ne laser as the laser source. As such, in the current work, a comparison study between two experimental setups was carried out. One experimental setup was using a He-Ne laser, spatial filter, and charged coupled device (CCD) camera, while another experimental setup was using a laser pointer and DSLR camera. The laser beam was illuminated at angles of 30°, 45°, and 60° from the horizontal. When a laser beam falls on the surface, the beam gets scattered, and the scattered beam undergoes interference and produces speckle patterns which are captured using a camera. Using a Matlab program, the gray level co-occurrence matrix (GLCM) characteristic features, such as contrast (GLCM), correlation (GLCM), energy (GLCM), entropy (GLCM), homogeneity (GLCM), and maximum probability, and non-GLCM characteristic features, such as mean, standard deviation (STD), uniformity, entropy, normalized R, and white-to-black ratio (W/B), were extracted and correlated with 3D surface roughness parameters. The coefficient of determination (R(2)) was determined for each case. Compared to the setup using a laser pointer, the setup using a He-Ne laser gave better results. In the setup using the He-Ne laser, there were correlations with a coefficient of determination R(2) ≥ 0.7 at illumination angles of 30°, 45°, and 60°, whereas in the setup using a laser pointer, there were correlations with R(2) ≥ 0.7 at illumination angles of 30° and 45°. Mean characteristic features had more correlations with R(2) ≥ 0.7 in the case of the angle of illumination of 45° (7 out of 36 correlations) and 60° (11 out of 82 correlations), while R-normalized characteristic features had more correlations with R(2) ≥ 0.7 in the case of the angle of illumination of 30° (9 out of 38 correlations) for the setup using the He-Ne laser. Correlation (GLCM) had more correlations with R(2) ≥ 0.7 in the case of the setup using a laser pointer (2 out of 2 correlations for illumination angle of 30°, and 4 out of 19 correlations for an illumination angle of 45°). Roughness parameters S(a) and S(q) had more correlations with R(2) ≥ 0.7 for an illumination angle of 30° (1 out of 2 correlations each), and S(p) and S(z) had more correlations with R(2) ≥ 0.7 for an illumination angle of 45° (4 out of 19 correlations each) in the case of the setup using a laser pointer. The novelty of this work is (1) being a correlation study between 3D surface roughness and speckle pattern using a He-Ne laser and spatial filter, and (2) being a comparison study between two experimental setups on the correlation between 3D surface roughness and speckle pattern
Removal of clouds from satellite images using time compositing techniques
No full textClouds in satellite images are a deterrent to qualitative and quantitative study. Time compositing methods compare a series of co-registered images and retrieve only those pixels that have comparatively lesser cloud cover for the resultant image. Two different approaches of time compositing were tested. The first method recoded the clouds to value 0 on all the constituent images and ran a \u27max\u27 function. The second method directly ran a \u27min\u27 function without recoding on all the images for the resultant image. The \u27max\u27 function gave a highly mottled image while the \u27min\u27 function gave a superior quality image with smoother texture. Persistent clouds on all constituent images were retained in both methods, but they were readily identifiable and easily extractable in the \u27max\u27 function image as they were recoded to 0, while that in the \u27min\u27 function appeared with varying DN values. Hence a hybrid technique was created which recodes the clouds to value 255 and runs a \u27min\u27 function. This method preserved the quality of the \u27min\u27 function and the advantage of retrieving clouds as in the \u27max\u27 function image. The models were created using Erdas Imagine Modeler 9.1 and MODIS 250 m resolution images of coastal Karnataka in the months of May, June 2008 were used. A detailed investigation on the different methods is described and scope for automating different techniques is discussed.10 pages, 8 figure
Correction: The Effect of Rural-to-Urban Migration on Obesity and Diabetes in India: A Cross-Sectional Study
No full text[This corrects the article on p. e1000268 in vol. 7.].
The Academic Editor's name and institution were erroneously omitted from the metadata of the PDF and HTML versions of this article. The Academic Editor providing expert input on this paper was Peter Byass, Umeå Centre for Global Health Research, Department of Public Health and Clinical Medicine, Umeå University, Sweden. For more information about the role of the Academic Editor in PLoS Medicine's editorial process, see our Author Guidelines: http://www.plosmedicine.org/static/guidelines.action#overview
Author Correction: Inherited causes of clonal haematopoiesis in 97,691 whole genomes (Nature, (2020), 586, 7831, (763-768), 10.1038/s41586-020-2819-2)
No full text© 2021, The Author(s), under exclusive licence to Springer Nature Limited. In this Article, Abhishek Niroula should have been listed as an author, with the affiliations: Broad Institute of MIT and Harvard, Cambridge, MA, USA; and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. They performed additional bioinformatic analyses (see ‘Author contributions’). The original Article has been corrected online
Investigation of a rapid screening method to study the effects of the snowdrop lectin (Galanthus nivalis Agglutinin) on plant pathogens
No full textTwo Tobravirus expression vectors were evaluated for the use as a rapid screening method for anti-nutritional proteins against plant pathogens. Accumulation of green fluorescent protein (GFP) and snowdrop lectin gene (Galanthus nivalis agglutinin, LECGNA2, M55556) in Nicotiana benthamiana by Tobacco rattle virus expression vectors was characterized. Virally expressed proteins were detected in leaves (3-14 days post-inoculatiion) and roots (6-24 dpi) by UV (GFP), western blotting and tissue printing. 25 -50 ng of GNA was detected in root extracts. Cross protection was induced by TRV-GFP. Foreign genes inserted in place of TRV RNA2 non-structural genes (2b and 2c) were stably maintained over serial passages. But recombination at remaining 'cross-over' sites may occur. 2D iso-electricfocusing detected a 50-kDa GNA molecule in root and leaf extract. GNA did not confer resistance to root-knot nematodes, although gall by root-knot nematodes (mixed Meloidogyne spp. and M.javanica Crete line 17) were significantly reduced by 22% in roots infected by TRV-GNA (3.83 sqrt galls and 4.5 sqrt galls respectively) compared to virus-free roots treatment (4.94 sqrt galls, sed 0.398; p<.025 and 5.273 sqrt galls, sed 0.2403; <.003 respectively). Effects of GNA on Aulacorthum solani was delayed to the second nymph generation (N2). Mean N2 weights feeding on TRV-GNA (0.246 mg ±0.0159; p <05) and TRV-fsGNA (0.212 mg ±0.018; p<.001) infected plants were significantly smaller by 15.2% and 26.6% respectively, compared to virus-free treatments (0.290 mg ±0.014). Similar trends were detected for total nymph weights. Low toxicity was related to high quality phloem and ingestion of smaller volumes for normal development (i.e. concentration effect). Decrease in gall by the mixed Meloidogyne population and an unexpected toxicity to A solani indicated that truncated GNA was a protein with merolectin properties. The viability of this system as a rapid 'm planta' expression system is discussed
