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4 results on '"J. S., Anjana"'

1. Qualitative Assessment of Resilience: Lessons from Rural Women in South India.

Author

Mohan, Radhika, Menon, Preetha, J. S., Anjana, and J., Aswathy

Subjects
RURAL women, PSYCHOLOGICAL resilience, QUALITATIVE research, COVID-19 pandemic
Abstract

Resilience among women has garnered significant research attention, especially in the context of the COVID-19 pandemic. The 2020 United Nations' theme of "Building rural women's resilience in the wake of COVID-19" aligned with that of the present study and sought to assess the applicability of the positive cognitive triad and psychological capital lenses in understanding the resilience characteristics of rural women in India. The study involved a diverse group of conveniently selected 31 rural women from the Idukki district, Kerala, South India, spanning an age range of 18 to 74 years. The deductive and inductive analyses of interview transcripts revealed convergence to the proposed positive cognitive triad -psychological capital framework and the emergence of new themes. Notably, gender emerged as a distinct theme that did not align with the operational definition of resilience, highlighting its significance in explaining resilience among Indian rural women. The study acknowledges limitations such as limited generalizability, social desirability bias, and a lack of quantitative data. In conclusion, this research contributes valuable insights to the literature on resilience among Indian rural women, emphasizing the importance of gender-centric and culturally sensitive resilience measures. The study recommends the implementation of such measures to enable a comprehensive assessment of resilience in this population, providing valuable resources for government and non-government agencies to design appropriate psychosocial interventions. [ABSTRACT FROM AUTHOR]

Published
2024

3. Impact of Surgery on Extramammary Paget’s Disease Vulva: a Case Series

Author

Amrita B Rao, J. Siva Ranjith, S. Suchetha, T R Preethi, J S Anjana, and P. Rema

Subjects
musculoskeletal diseases, medicine.medical_specialty, urogenital system, business.industry, Standard treatment, Hyperkeratosis, Disease, medicine.disease, Extramammary Paget's disease, Vulva, Surgery, medicine.anatomical_structure, Oncology, Surgical oncology, otorhinolaryngologic diseases, medicine, Original Article, Surgical excision, business
Abstract

Extramammary Paget's disease is a rare neoplasm that may affect the vulva. It usually presents as a pruritic red eczematous lesion with islands of hyperkeratosis that is often mistaken for other benign conditions. There are no specific guidelines for the management of this disease. Surgical excision is the standard treatment but recurrences are common in spite of extensive surgery with negative margins. We report here a series of 7 cases of Paget's disease vulva treated by primary surgery. The series highlights some of the challenges in the diagnosis and management of Paget's disease vulva.

Published
2021

4. Language Identification From Speech Features Using SVM and LDA

Author

S. S. Poorna and J. S. Anjana

Subjects
Language identification, Computer science, Speech recognition, Feature vector, Feature extraction, 020207 software engineering, 02 engineering and technology, Speech processing, Support vector machine, 030507 speech-language pathology & audiology, 03 medical and health sciences, ComputingMethodologies_PATTERNRECOGNITION, Formant, 0202 electrical engineering, electronic engineering, information engineering, Feature (machine learning), Mel-frequency cepstrum, 0305 other medical science
Abstract

Speech based language identification system has a wide range of applications in the field of telephone services, multilingual translation services, government intelligence and monitoring etc. Identifying the exact speech feature for classification is an important problem in the language identification research area. In this work, we are comparing the performance measures of a language identification system using two different supervised learning algorithms. Mel frequency cepstral coefficients and formant feature vectors are extracted for classification purpose. The system which is developed using the database of seven different Indian languages is capable of identifying languages with LDA giving a maximum classification accuracy of 93.88% when compared to SVM with a classification accuracy of 84%.

Published
2018

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